Can't tell if the camera has poor contrast resolution or if it was indeed that dark. With the dynamic range available on digital sensors, it seems to me that even without some form of FLIR it still should be more possiblle to capture this for sensors than eyes at any rate. Do self driving vehicles use any of this, especially at night?
> That’s only because there’s no light on her until the end.
Yes, quiet true.
> The car hardware should have seen her. If it doesn’t work in the dark it shouldn’t be on the road imho.
I tend to agree. I think unfortunately this video indicates that the car did not perform worse than a human. It's still valuable to have cars that perform better than humans, even if they aren't perfect.
Isn't that the exact same video in poorer quality?
I think the question now is how well a LIDAR is supposed to work in the dark. I keep hearing people saying that the hardware should've "seen" her, but speaking purely in terms of physics, how exactly is that supposed to work? Doesn't night vision still require a minimum threshold of light in order to work? How much light?
If that's true, this would certainly suggest a big failure from the LIDAR system in this incident. I wonder how that claim is tested. Would city lights interfere with testing (similar to how you can't see stars in the middle of cities)?
Even in that over-exposed video, at 35mph, I think you would have to be extremely lucky to not hit her. From her coming into view to collision is ~700ms. Subtract average human reaction time (250ms), and that leaves a little less than half a second to swerve.
A human would have made this mistake, but I don't know enough about LIDAR to understand if a computer should have made this mistake. Is night vision poor on these machines?
Then slow down. If you can't stop or swerve when something becomes visible to you then you're driving too fast regardless of the posted speed limit. Period.
> I tend to agree. I think unfortunately this video indicates that the car did not perform worse than a human. It's still valuable to have cars that perform better than humans, even if they aren't perfect.
I disagree. I think this video shows that the car performs much worse than I would expect a human to.
I have my own dashcam videos at night that look very similar to this, and I definitely think I would not have hit a large object such as a pedestrian walking a bicycle on a straight road such as this in a 35mph zone.
> That’s only because there’s no light on her until the end.
It seems like the car is out driving its headlights. Assuming a road line is about 10 feet (as is typical), only about 20~30 feet of distance is illuminated... but at 30mph you need ~45ft for an average car to break, and at 40mph you need ~80ft. (According to [1] -- ignoring reaction time.) Is there something wrong with the headlights? Is the video just that bad? (And if so, is it even used for decision making by the car?)
How is this video "better?" This is clearly somebody holding a camera recording a screen and seems to have much more artifacting and brightness changes.
When I cross-reference the lane lines at 0:03 with google maps[1], I get an estimate of the car being about 60ft-70ft away from the victim when I was first able to spot her shoe in the video. Some googling[2] says human reaction at 40mph would've taken 59ft, with an additional 80ft of actual stopping time.
This seems in line with the police report that "it would have been difficult to avoid this collision in any kind of mode (autonomous or human-driven)"
Maybe a SDV with superhuman reaction time should've been able to stop some 10ft after hitting her, and maybe if it had night vision-like sensors, it should've been able to see her from farther away, but my impression is that it would've been impossible for a regular human driver to avoid this accident.
Given that the SDV didn't attempt to reduce speed before she was visible under regular light, I'm forced to assume the sensors do require light in order to detect obstacles and that there wasn't enough light to activate the sensor before the headlights illuminated her.
The speed limit is only 35 not 40 on that road unless we're looking at different roads? If the driver is paying attention they could turn the wheel a bit and split the left lane (there doesn't appear to be anyone else on the road) and avoid the person who was half way through the lane at time of impact. Might not clear the person but clipping the back of the bike would certainly be better than a direct impact. You wouldn't even have to jerk the wheel and swerve at such a slow speed and on a dry road with modern tcs even over-correcting is handled by tcs to limit what your input does. Of course all this is just playing arm chair quarterback so who knows if someone including myself would have been able to react in time. More of a thought experiment to how an alternative could have occurred.
I'm curious how the visibility differs between what we see on this camera and what a human actually sees in person.
According to google maps, the speed limit is 45 northbound (which is the way the car was going), 35 southbound. The report was that the car was going at 38, but I could not find stopping ranges estimates for that exact number. So give or take a little.
Looking at the video, it seemed like the driver reacted (facially) about a second after she shifted her gaze from some device to the road. It took me several runs of replaying the video to narrow down the time between when I first saw her shoe and collision to about 2 seconds. Also, recall this was at 10pm. In my opinion, swerving or braking with a 1-2 second notice is extremely hard, especially if it's late and you're tired. To be perfectly honest, if it was me, I don't think I would've been able to react at all before the collision.
1. Human eyes have a better dynamic range than cameras do. The camera is thus displaying a worse contrast than a human eye can see.
2. Motion is preattentive in the visual system. (When you think about it, panicking about subtle motion in the corner of your eye tends to be evolutionarily advantageous).
So the time we have to identify the pedestrian using the video is a minimum bound of the time, not necessarily an accurate reflection of the time. It is not clear how much extra time (if any) a reasonable driver would have in this incident.
On a collision course, there's zero relative motion of the object you're about to collide with. It's one of the quirks of the human vision system that makes it particularly ill-suited to operating motor vehicles.
With all the logged sensor data this should be the best documented fatal collision in history and will be able to be replayed again and again with different software to see if it was avoidable with the current hardware configuration.
Obviously a sad situation, but it's reassuring that the knowledge from one crash can lead to all other autonomous vehicles learning to avoid it in the future.
I'm surprised the vehicle didn't detect an object moving into its field of view. What are the expectations from the driver under the terms of Arizona's self-driving car laws? Are they expected to remain engaged as a driver, or are they permitted to allow the car to perform all of the driving? It's impossible to say whether an attentive drive would have changed the outcome of this scenario -- largely because a highly compressed video doesn't really convey what the driver actually was capable of seeing, but it's very clear from the video that the driver was more focused on a phone (or some other device) and was not an active participant in driving the vehicle.
I'm definitely interested in the legal expectations too. If it turns out LIDAR completely dropped the ball here, it might not be the case (given AZ's lax rules) that Uber would be penalized for LIDAR that was substandard.
Presumably, there'd be regulations for software too, classifiers and AI decision making. Has any jurisdiction set standards in this?
Wow, I had thought it impossible for the Uber AV to be in the right lane, and for the victim to be crossing left-to-right, for the police to claim that the victim couldn't be seen until it was too late. But I didn't expect the road to be so dark, given what we saw in the accident photos (which might have been over-exposed?) and Google Maps, which showed a lot of street/sidewalk lighting.
In the moment that we can fully see her, she does look unambiguously like a person walking a bike across the road (reports say there were plastic bags on the bike, but they weren't obvious/obstructive in the camera view). Is the AV's LIDAR expected to detect this kind of thing, even if it's too dark for human eyes?
The video of the Uber driver doesn't look great for the driver. I mean she doesn't look particularly engaged -- but I suspect that's what most of us would look like at the wheel. But she definitely seems to be looking downwards, right at the moment of impact.
Unless some other incriminating info is discovered, I hope that the driver isn't the sole focus of punishment (doesn't help that she's a convicted armed robber, albeit years ago). Being able to brake in time for the victim seems difficult even in most ideal and alert conditions. And I have to think human operators are going to suffer complacency when 95-99% of the time they never have to actually drive -- making that switch seems to be a situation ripe with problems.
I don't mean that Uber execs/testers/engineers (again, assuming there isn't other incriminating evidence) should be scapegoats. I hope the result involves regulations that add more transparency to reporting (especially in Arizona), and public debate about the expectations of AV and AI.
The dynamic range of small sensor digital cameras is so poor that it is impossible to judge whether or not she would have been visible to the naked eye based on the video.
That's a great point. I did think, looking at the video, that the street was unnaturally dark. The camera seems to be exposed for night lights and the headlights too.
Most cameras have very poor contrast in low light situations that are interspaced with lights like a typical street with streetlamps, your eye does significantly better.
LiDAR is not affected by the amount of visible (sun) light. I'm very curious to see the data returned from the LiDAR, because this should've been a very clear human frame, albeit with a bike behind it.
LIDAR still has a signal to noise ratio that limits it though, especially with materials that reflect little with the wavelength used (usually NIR, somewhere around 980nm, the military uses 1500 because it's more eye-safe).
But even then, this impacts the maximal detection range only. Even if the obstacle suddenly popped up at 20m it should have been enough to drastically reduce the collision speed.
Digital image quality is generally far inferior to naked eye visibility, but even in the image, the pedestrian can be seen for at least a full second.
The driver clearly was unfortunately not paying attention. She clearly reacts within a few hundred milliseconds of looking up, which is to say immediate reaction time in terms of mental processing. That means that we cannot use her reaction time to gauge how early she could have seen the pedestrian to compensate for poorer optics of digital cameras.
As I understand LIDAR, it should work even at night (as it generates its own light and measures response time). This is a pedestrian, walking across a road, with nothing possible to occlude her. There is no reason it should not have identified an obstacle in the road (she's been in the road for several seconds, after all, having crossed at least 3 lanes of traffic by that point). Even if the visual camera had problems identifying the object, LIDAR should have flagged it.
> I hope that the driver isn't the sole focus of punishment
As sad as this accident was, I don't see how the driver or Uber is legally at fault. Pedestrians crossing outside of a crosswalk are supposed to yield to traffic. The victim in this video is stunningly oblivious to the fact that she's on a roadway.
Obviously we want self-driving tech to be good enough to avoid such an accident, particularly since a human probably could have; I'm not arguing otherwise. But legally, the victim was clearly at least partially at fault here.
I think one thing this incident is going to do is to point up the limitations of having a human at the wheel, supposedly ready to take over. In a true sudden emergency, after tens of thousands of miles of uneventful riding around, that just isn't going to happen reliably.
> Pedestrians crossing outside of a crosswalk are supposed to yield to traffic.
Pedestrians always have the right-of-way. They might get a ticket for jaywalking in some cities, but it's never permissible to hit someone with your car, regardless of whether they're in a crosswalk. Vehicular manslaughter is no minor infraction, and Uber can expect a civil suit from the victim's family even if there are no criminal charges.
They will probably lose in arizona (In My Lawyerly Opinion) but Uber will settle it out anyway.
It's not only comparative negligence, you don't have to always yield. In fact, Arizona has a weird set of rules that would make this exact set of events a law school exam style question:
Arizona: Vehicles must yield the right-of-way to pedestrians within a crosswalk that are in the same half of the roadway as the vehicle or when a pedestrian is approaching closely enough from the opposite side of the roadway to constitute a danger. Pedestrians may not suddenly leave the curb and enter a crosswalk into the path of a moving vehicle that is so close the vehicle is unable to yield. Pedestrians must yield the right-of-way to vehicles when crossing outside of a marked crosswalk or an unmarked crosswalk at an intersection. Where traffic control devices are in operation, pedestrians may only cross between two adjacent intersections in a marked crosswalk.
One saving grace for any plaintiff is that in AZ you can recover 1% damages even if you are 99% at fault.
The wildcard here is that interior video. The safety driver was clearly not paying attention. Although the exterior video seems to exonerate her, everybody knows that even with no bright clothing and in between streetlights, a pedestrian rolling a bicycle wouldn't be that invisible.
On the other hand, that pedestrian was astonishingly oblivious, crossing a two-lane roadway with a 45mph speed limit and not even looking for oncoming traffic. If she did that every night for a couple of years, I think her odds of having at least a close call would approach 100%.
Just FYI: In the US, this not legally true, and definitely not legally true in a lot of comparative negligence states.
While its true you can't just hit people with your car, any civil suit that is filed would be usually lost in most of these states (where lost == you may not recover money). It does vary, some states (like AZ) allow you to recover 1% even if you are 99% at fault.
In fact, what you say about right of way is not even true in very pedestrian friendly states like California. In California (and most states), what the person you replied to wrote is correct.
21950.
(a) The driver of a vehicle shall yield the right-of-way to a pedestrian crossing the roadway within any marked crosswalk or within any unmarked crosswalk at an intersection, except as otherwise provided in this chapter.
(b) This section does not relieve a pedestrian from the duty of using due care for his or her safety. No pedestrian may suddenly leave a curb or other place of safety and walk or run into the path of a vehicle that is so close as to constitute an immediate hazard. No pedestrian may unnecessarily stop or delay traffic while in a marked or unmarked crosswalk.
(c) The driver of a vehicle approaching a pedestrian within any marked or unmarked crosswalk shall exercise all due care and shall reduce the speed of the vehicle or take any other action relating to the operation of the vehicle as necessary to safeguard the safety of the pedestrian.
(d) Subdivision (b) does not relieve a driver of a vehicle from the duty of exercising due care for the safety of any pedestrian within any marked crosswalk or within any unmarked crosswalk at an intersection.
Pedestrians do always have the right of way, but they bear a bit of responsibility as well to make sure the driver is aware of them, and not just walk out into the road. I have been on both sides of the wheel here, and it can never be assumed that a car knows a person is there.
This is a shit show now. A new technology is being tested, and the tester is a convicted armed robber, and was not even looking at the road during the test drive. I think every single person in Uber that has anything to do with this testing program is guilty of homicide, including the driver. This could've been at least non-fatal.
The description given before the video was released painted a picture in my mind that the woman was on the median and "suddenly" entered the roadway in front of the vehicle. I pictured someone darting across the road directly in front of the car, with no way to stop in time.
This video shows a completely different scenario. The woman started on the median, but the vehicle was in the #2 lane. She wasn't visible to the naked eye but she also wasn't darting into traffic and had to cross the #1 lane before even being in the path of the vehicle. A human driver certainly would have difficulty stopping in time, but why did the sensor package not pick her up? This doesn't appear to be the close call we were told it was. To me, this seems like exactly the scenario that autonomous driving vehicles are intended to prevent.
Sure, if we were actually sitting in the front seat we would have a different perspective. Want to convince me it was unavoidable? Release the IR footage too.
Have to agree with you. This is the automatic exposure control of the camera. my 1440p dash cam does the same thing. In its video it looks like everything outside of the cone of the headlights is pitch dark, but it is actually not. I have seen deer standing by the side of the road and later checked the dash cam, which did not pick them up at all.
Keep in mind the video isnt nessisarily representitive of what you would see with the naked eye. Most cameras have very poor contrast in low light situations that are interspaced with lights like a typical street with streetlamps, your eye does significantly better.
I disagree, if you look at any of the Waymo videos you can see they have great recognition of every car, pedestrian, and obstacle within 100 meters of the car, and most of that data (point cloud lidar/radar at the very least) would work in pitch black without even headlights. Thus it's extremely reasonable to expect that autonomous vehicles will easily prevent scenarios like this.
Inclement conditions, defensive driving, etc. are much harder to work with but this should have been cake.
If you turn your headlights off on a dark country road, your sight capabilities actually go up, not down. The problem is: most roads are lit or you st least have to compete with other headlights, and it would make you harder to see.
Go to [0] and [1] and count how many times they use the word "safe." We're not hoping autonomous vehicles are safer, we're being sold on them as the safer alternative. So yes, this type of close call situation is exactly where these vehicles are supposed to be superior.
That's a very misleading comparison, even as an informal, rough comparison for the sake of argument.
Such a comparison would have to take into account the amount of human-driven cars and automated cars - not just taking a picture of a single day, but the variance over time (e.g. if today there are a thousand automated cars in operation, and yesterday there were 50, that can distort the average stats); automated cars aren't driving in certain areas/times/weather conditions whereas human-driven cars are, etc.
Automated cars may be safer, but, open snark – I hope it's not calculating its sensor data in this way — close snark.
Maybe a better word than "intended" would be "expected". As in, most normal, rational, reasonable people basically familiar with the technology involved expect this to be preventable.
Being buried in lawsuits isn't a great way to make money, generally speaking. The people hoping to make lots of money at this should have a pretty high level of motivation to make it safe.
I would expect most autonomous systems to extrapolate the movements of anything in the vicinity and check whether it's going to cross paths with the vehicle. I would speculate that LIDAR (or whatever systems they use for object detection) simply failed to detect her.
Bikes are mainly curved, small pieces of metal, and absorptive pieces of rubber. Their reflectors are designed for viewing them from the front or rear, not the sides. I wonder whether lidar can even differentiate a sideways bike from noise.
In principle, I agree. But, I wonder if holding a bike in front of you is almost like holding a mirror that obscures the lidar ability to detect a solid mass.
edit: but she is in front of the bike, so this shouldn't matter. Does the darkness of her clothing impact any of the sensors?
Even if those in-wheel reflectors are removed, the wheel rims are reflective and the seat post is reflective (at minimum). And additionally there are several things that are way less reflective than a bicycle that you don't want to hit in the middle of the road. Like a deer, or a pothole, or a pedestrian.
A bicycle shouldn't need to be covered in reflectors to be safe from getting run over by a car. However anybody who cycles at night (as I do frequently) should wear reflective clothing because the road is full of reckless drivers.
What is striking to me is I haven't seen anyone talking about evasive maneuvers. The car must have been able to see the person, and the road looks empty, why not swerve?
At the absolute bare minimum, hit the brakes and reduce the impact. An attentive human driver would have at least started to hit the brakes. The software should have had plenty of time (I'm estimating a full second) to do something productive.
I have the very strong suspicion that the driver has turned autonomous drive mode off, perhaps to be able to watch tv or something. She seems extremely distracted by the dashboard and there is no way that sensors could not alert her of that presence. Also, apparently the car was driving at 38mph in an area where the speed limit was 35mph. Would the autonomous mode allow that?
> Also, apparently the car was driving at 38mph in an area where the speed limit was 35mph. Would the autonomous mode allow that?
This seems key. Whether in autonomous mode or not, whether someone got hit or not, this clearly should not have been happening, and as such indicates some malfunction or lapse in protocol.
OTOH, if the issue was "human thought computer was driving, computer was actually off", this might be a completely new class of errors in driving (although it does happen in aviation, where both pilots think the other one is PF: https://aviation.stackexchange.com/questions/5091/how-are-co... )
I bet the police chief who gave the quotation saw that video once and was startled at how suddenly the person appeared in that video and didn't check and see things like there was another lane or anything about the surroundings.
I was under exactly the same impression. From the description a few days ago, I had imagined someone on the right hand side of the road stepping out from between two parked cars.
From the video this morning I was wondering how it was possible the vehicle lidar and radar didn't pick this up. This is exactly the sort of thing I would hope these additional sensors could pick up easily.
Also from the released video, it was clear to me the "human driver" of the car was not paying attention. Looks like they are looking at their phone at lap level 90% of the time, unless there was something like a "camera/lidar" view in the dash they were looking at.
Having a human in these self driving cars is useless. There is so little for the human to do that it is hard to keep them from checking out. And once they do, they might as well not be there. Seems like "Safety Theater" to me, make the public and the Uber riders feel like there is still a human in the loop, when there really isn't.
Yes, particularly the 'theatre' part. Its expensive and useless.
More useful would be to have a central location with humans monitoring dozens of cars, like a sort of air-traffic control situation. Better chance of keeping their attention with enough going on. They'd be there in case of difficulties, know when a car 'went off the rails' or notify authorities in case of an accident.
And with Central monitoring you could easily have people switch out frequently, and run drills like they do with lifeguards. The lifeguards at our neighborhood pool change positions every 15 or 30 minutes or go on break, with new ones cycling in. The water park does something where the supervisors will periodically introduce a special ball to the water which the lifeguards have to "save".
I worry that monitoring dozens of cars would be too much information for the "Road Traffic Control" to be able to respond in the 1.5 seconds that were available in this video, especially if they have such "low dynamic range" as what we see in this video. But maybe Lidar data would have showed the RTC operator something the car didn't see?
I'm really looking forward to the findings about what radar, lidar, and sonar sensors were saying during this time.
I think this brings up an interesting philosophy for autonomous driving technology - is it feasible if it's "only as good as human driving"?
I mean I've seen comments that a human might not have seen the pedestrian. Is that a "defense" of driving AI? That's it's about as good as human driving?
Seems to me the public won't accept driverless cars unless there is significant evidence that it's much better than human drivers - after all human drivers make a lot of mistakes and cause a lot of fatalities. I don't think any other claims of the advantages of AI driving could offset any negative publicity of injury or death.
I think experience is the best teacher. In a perfect world, Uber will look at the data, determine why this happened. The AI will learn and it won't happen again. That is compared to countless new human drivers entering the road every year. That's not a defense, or an excuse, but an explanation or reality.
I know we don't live in a perfect world, but regardless, we can't change what happened here, so it's best to learn something from it.
Since I've seen this be a very controversial statement here in the past, I'd just like to point out to everyone that American drivers on four lane roads are not expecting pedestrians to be in the middle of the road and not at a crosswalk. That is not a normal thing to happen in America, and no one expects it to happen. It is a very rare situation.
--edit: okay guys... no where did anyone argue that you shouldn't be watching for pedestrians crossing. Stop yelling "gotcha!" like you caught me in a trap. What I'm arguing against is the common refrain on these articles that there is no such thing as jaywalking and the pedestrian has the right to the road over the car. Maybe it's true in Europe judging by comments on previous articles, but it's not common in the US. It's illegal.
Congratulations on expertly knocking down your own strawman, though.
I have driven in the US for over 20 years and have the opposite experience. I am constantly looking for people, animals (deer are quite dangerous to hit, and they move _way_ faster) and lost count long long ago how many times I have been in very similar or worse situations.
It's not even remotely rare. Drive on campus or downtown in AZ for a more than a few minutes.
Yes, obviously you should watch for objects unexpectedly crossing the road. No one argued you shouldn't. The point is, some people have and will still argue that the pedestrian has more right to the road than the driver and pedestrians should be allowed to cross anywhere they please. But that's not how it works in the US, crossing roads like this is illegal unless it's done at a crosswalk, and normally people are not stupid enough to do it with oncoming traffic.
"obviously you should watch for objects unexpectedly crossing the road. No one argued you shouldn't."
Strawman. I argued the opposite. You made the grossly incorrect assertion "That is not a normal thing to happen in America, and no one expects it to happen. It is a very rare situation."
If preprogrammed cars cant handle random objects in unexpected places then they are uber DOA.
There is a limerick to this effect with the same message -- you may have (or think you have) the right-of-way, but as a pedestrian you should never insist on it.
But the legality is to some extent beside the point. Autonomous vehicles aren't going to be tuned to pedestrian yielding rules state-to-state, simply because hitting a pedestrian is never an acceptable outcome if avoidable no matter who is in the right/wrong.
I think you can generally say that there are few countries where one would expect people to cross a four lane road without watching out for cars. I'm not sure why you would think that to be a controversial statement, especially considering that the person being hit in the video is also not just walking on the street but crossing it.
Obviously the concrete level of awareness that drivers usually have is probably related to a lot of other circumstances (light conditions/amount of traffic etc.)
I don't think it to be a controversial statement, I know it to be controversial. Just look at the other reply posted at exactly the same time as yours with someone saying they totally expect pedestrians crossing illegally wearing black at night.
The last thread about this contained a very long argument from some Europeans who disagree with the core concept of "jaywalking". Some people really do hold the belief that roads are for pedestrians first and cars last, contrary to US law.
That is strange. Maybe they were not talking about 4 lane roads? Because on smaller streets I would also expect pedestrians, especially if there is not boardwalk. But in my opinion this is indifferent to the situation at hand anyway because this video is about somebody crossing the street without respecting the cars right of way, which can't be deemed common behaviour by anybody.
First of all, I don't think we are. Also, I live in a modestly sized European city of about 650k citizens (excl. metro), and even we do have some sections of road with 4 lanes in each direction, and in intersections, even more. I'm quite sure bigger cities have more of those, even in Europe.
There's no specific 'no pedestrian' signage, and there are no nearby marked crossings. If that road were in [for example] the UK, Australia, NZ, or much of Europe, the car wouldn't have had right of way.
I'm currently in Europe (Germany) and if I cross a 4 lane road thinking I have the right of way, I'm dead. Can you point to any road provision that supports your thesis? Because my quick research does not confirm your standpoint. It also seems to defy logical sense to let cars on a 4 lane road stop for pedestrians because there would be an enormous amount of accidents when cars overtake each other
Wow! You are saying no one in the US expects, or at least consider that could be an obstacle on the street in front of you? It doesn't mean necessarily a pedestrian. An animal? Cargo lost by a truck in front of you?
It is the responsibility of the driver to be alert and try to minimize the impact. Just because a cyclist shouldn't cross a four-lane road in the middle of the night, doesn't mean you shouldn't look for obstacles.
As an American, this general kind of situation is a reasonably common situation with people and animals (people more in urban environments, large animals more in rural ones, and both in many suburban ones) and something I was taught to be aware of in public school driver's education classes.
The particular combination of speed and distance may not be common, but the general situation isn't rare.
People crossing streets mid block is such a common in pheonix that last week Arizona announced a plan spend $250k on educating the community on this very problem. Pheonix is one of the most dangerous cities for pedestrians and bikers. Pheonix is built for cars not people, a ton of roads are fast 4 Lanes in residential areas.
>the pedestrian has the right to the road over the car. Maybe it's true in Europe judging by comments on previous articles, but it's not common in the US. It's illegal.
You are conflating two different concepts. In every state in the U.S., it is illegal to hit a pedestrian whether or not they are where they are supposed to be. If you see a pedestrian jaywalking then you are required to avoid the pedestrian to the greatest extent possible. Anything less is at least manslaughter.
Perhaps, but the pedestrian also did not react at all to the car. Even though she knew she was crossing a street and should look for cars, see the headlights, hear the engine, etc.
The pedestrian was a homeless person. I don't mean to be insensitive but there's a chance she wasn't in a condition to recognise the danger of what she was doing.
Regardless, it is the driver's responsibility to perceive and avoid hazards like this and I think that would've been pretty easy given it's a big wide empty road with overhead lighting. This looks like the kind of bad low light footage my cheap dashcam produces in similar conditions.
For better or worse, it's not the pedestrian on trial here. It's the self-driving vehicle which completely failed to register a significant obstacle directly in front of it for nearly two seconds. There is no scenario where this is an acceptable response from a control system in charge of a 1500kg projectile in a shared public space.
Even if you're not a cyclist, it's a good idea to wear something with reflective stripes when you're out on dark roads. This is actually the law in several European countries.
How did LIDAR and IR not catch that? That seems like a pretty serious problem.
It's clear from the video that a human driver actually would've had more trouble since the pedestrian showed up in the field of view right before the collision, yet that's in the visible spectrum.
When I argue for automated driving (as a casual observer), I tell people about exactly this sort of stuff (a computer can look in 20 places at the same time, a human can't. a computer can see in the dark, a human can't).
Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
Like parent said, it's low-light in the visible spectrum, but I'd totally expect these vehicles to scatter tons of light in non-visible spectrums, making these conditions well-lit in those spectrums. Like a bat using echolocation.
I think the point GP was making is that an attentive human driver may have been able to see the pedestrian much earlier than when she becomes visible on the video.
this, the human visual system adapts to darkness. Consider that the victim who obviously is crossing the street as part of their lifestyle has likely done this many times before, and of all the vehicles that could have hit the victim, the one that did happened to be one of uber's self-driving vehicles with a clearly inattentive driver behind the wheel. A driver paying attention to the road would have at least hit the brakes well before impact.
Intermittent street lights reduce the adaptation though and add glare - the human visual range for scotopic ('dark adapted') and mesopic (twilight conditions) vision is about 4 orders of magnitude of luminance (cd/m²) that the retina can perceive simulataneously from 0 to saturation, without adaptation (dilating pupil). Dark to light adaptation is very rapid and happens in fractions of a second, light to dark adaptation happens over minutes.
The eye will adapt to a mean level of light in the larger FOV (not fovea only) - that is why instrument clusters on cars need to be low-level lit, to not disturb this adaptation. Exterior light sources like headlights and street lights further influence adaptation and veiling glare can lead to light sources overshadowing smaller luminance signals and pushing them out of the range that the eye is adapted for.
I don't think modern digital sensors actually under perform human vision, or it's at least not obvious. They have made huge improvements in the last decade.
Also, When a digital camera records an image, a gamma curve is applied to it before display, which makes up for a bias against the darker portions which the digital equipment does not inherently have.
Considering the streetlights, I cannot imagine any excuse. This video will sadly give them the benefit of public doubt but anyone familiar with lighting digital video will be unconvinced that the video feed was the culprit.
I take a photo with my iPhone in night conditions and the image I see on the screen comes out way darker than I saw with my eyes. That has to be corrected for, no?
No. The term we need to introduce here is "Dynamic Range". It is pointless to say "Sony A7s can vastly outperform the eye" where it could have been set for a low light exposure. Human eye has an amazing dynamic range - I don't know the exact number today, but last time I checked was like 3 years ago and the cameras at the time (D800) were not even close to human dynamic range.
That's because you're comparing a single exposure from a digital camera. You can have dynamic range far in excess of the human eye with HDR techniques, by combining difference exposures and/or by exposing different pixels on the same image differently.
Don't forget compression artifacts. A dark object against a dark background in a highly compressed video is going to get compressed into just looking like the background.
I downloaded the video directly and it looks like it's 133 kbps for the video data at about 360p, which is just abysmally low. So it's not surprising that it's difficult to pick out detail in such a contrasty scene given the degree of compression and the resolution.
Yeah releasing the sensory data beyond human visible spectrum would be way more informative about if a better designed AV would have dealt with this better.
I'm glad it was not me driving down that road that night, I don't think I could have prevented it.
I think you sell your driving skills very short here. Assuming you have normal eyesight, you would have likely a 10-fold higher dynamic range than the visible camera footage shown. The gap between streetlights would have been easily discernible with your eyes, unlike in the camera footage.
See I wonder about that. In compromises conditions (many) drivers will drive slower and be more cautious. Perhaps computers need to be given a sense of fallibility? Computer can sense low light conditions and drive even more cautiously as a result.
It's clear from the video that a human driver actually would've had more trouble since the pedestrian showed up in the field of view right before the collision, yet that's in the visible spectrum.
That's not at all clear to me. I don't know too much about cameras, but it looks to me like the camera is making the scene appear much darker than it actually is.
In the video, you can see many street lights projecting down onto the ground, and the person was walking the the gap between two streetlights. The gap between street lights (and hence the person) was in the field of view of the camera the entire time; they just weren't "visible" in the camera because of the low lighting. I'm confident my eyes are good enough that I would have been able to see this person at night in these lighting conditions. (Whether I could have reacted in time is another question.) It seems to me like the camera just doesn't have the dynamic range needed for driving in these low light conditions, which is a major problem.
Which makes me wonder if the Uber autocar is just relying on camera vision to drive itself... If it is, and it's been lying to authorities (I don't know what they said to the authorities about their cars' capabilities), that could be big.
The point is not germane. What is germane is that a car that supposedly uses LIDAR and infrared, and presumably was approved by the regulators on the basis of such, should have had no problem seeing the pedestrian as LIDAR and infrared are unaffected by night and at least shown some indication of braking but did not. This suggests that the car does not in fact utilize any of those fancy (non-vis) detection methods. Alternatively, these fancy detection methods were fooled by the bicycle and thus misclassified as an error or something.
My point is that it's likely the camera view we're seeing has nothing to do with the self driving portion of the vehicle (a good hint to this is the interior view--useless to autonomous driving, but a common feature of dash cams).
The car has a LIDAR sensor mounted on the roof. It is supposed to continuously scan 360° of the environment. Since LIDAR is an active sensor (it emits light), the car should have seen the person and bicycle even in the dark. That it did not do so suggests the car does not evaluate LIDAR input, or it dismissed the object as erroneous data.
It has 64 lasers, spread out over about 27 degrees - about 0.4 degrees per laser, from almost horizontal to an angle of 24 degrees or so down. Now take a look at where it is mounted on the car, and envision these laser beams spreading out and being spun in a circular conical area around the car.
Now - if you think about it - as the distance from the sensor increases, the beams are spread further apart. I'd be willing to bet that at about 200 feet or so away from the car, very few of the beams would hit a person and reflect back. Also - take a look at the reflectance data in the spec. Not bad...but imagine you are wearing a fuzzy black jacket on your top half. How much reflectance now?
What do you think the point cloud returned to the car is going to look like? Will it look like a human? Hard to say - but you feed that into a classifier algorithm, there's a possibility that it's not going to identify the blob as a "human" to slow down. Especially when you add some bags, a strange gait, plus the bicycle behind the person. All of this uncertainty adds up.
I am also willing to bet that only the LIDAR was used for collision detection (beyond the radar on the unit). Any cameras - even IR based - would likely only be used for lane keeping and following purposes, plus traffic sign identification. Maybe even "rear view of vehicle" detection. Ideally it would be used for "person/animal" identification and classification to - but again, given the camera sensor, and who knows what the IR sensor saw or didn't see, along with the weird lighting conditions - well, who knows how it would have classified that mix?
Lots of variables here - lots of "ifs" too. All we can do is speculate, because we don't have the raw data. Uber would do well to release the entire raw dataset from all the sensors to the community and others to look over and learn from.
Finally - I am not an expert on any of this; my only "qualifications" on this subject is having taken and passed a couple of Udacity MOOCs - specifically the "Self-Driving Car Engineer Nanodegree" program (2016-2017), and their "CS373" course (2012). Both courses were very enlightening and educational, but could only really be considered an introduction to this kind of tech.
I have to agree. Just like a normal camera has issues in low-light, it is clear that this camera is diminishing exactly how light the road ahead was. While I can't say confidently that I would have been able to stop to prevent hitting them, watching the video in full screen does lead me to believe that I would have seen them and been able to apply the brakes at least enough to reduce the impact. Also, watching the video of the interior it is clear the driver was looking at his phone or doing something else just prior to the impact. This alone leaves me skeptical to just how much could have been done to prevent this accident.
The footage from a normal camera should not matter, a self driving car is equipped with stuff that works regardless of light conditions like LIDAR oor IR cameras. This looks to me like a software failure.
The footage from the normal camera does matter in that it's the main way that we (humans) can process the scene. The parent comments are just pointing out that the camera footage is likely darker than the actual scene in person.
Even so, I count a full second from when a human paying attention would have seen something just using this video as eyes, until impact. The stopping distance at 35mph is 136ft, which is 2.65 seconds at 35mph, so the accident would still happen but the impact speed could be lower.
Yeah, but at that speed, it's more than possible to swerve around an obstacle rather than screeching to a halt before touching it. Even turning slightly to the left/right would have made a dramatic difference in the outcome to this person's life. Not to mention the person in the car that might have also been severely injured if this was a heavier obstacle.
This was purely bad software, and no failure scenario being programmed in. I really don't think it's that difficult to program split-second reaction to obstacles that appear into the driving path. We need to get to a point where these vehicles can do stuff like this, even in a 2-dimensional way:
They seem to use 2.5 seconds as the standard for drivers to perceive and react to an obstacle, which based upon studies covers 90% of all drivers. 1.5 seconds to perceive, 1 second to react. Then you have maneuver time on top of that 2.5 seconds.
Given this, 1 second seems very low. A large percentage of drivers would probably plow into them at full speed.
Waymo cars are capable of sensing vehicles and pedestrians at least half a block away in every directions. I was reserving any judgement on wether this collision could have been prevented, but seeing the video tells me that 1) a human driver might have hit the victim regardless, and 2) I'm very surprised that the LIDAR sensor didn't cause the car to stop to a halt much, much earlier. This is exactly the kind of situation that I would expect self-driving cars to be better than human drivers.
This 100%. When I drive, I watch the road. I don't watch my mobile phone, I don't watch the kids behind, I don't watch my wife. I don't watch the sky. I don't watch the GPS.
I just watch the road in front of me.
My idea is that the car has been behaving well for a long time and consequently the driver lowered is vigilance. Big mistake.
I agree that dashcam/external cam footage is going to be limited and possibly misleading, and I would think/hope such footage isn't the primary factor in evaluating accident cases. But I do think there's value to it. I shouldn't have said that it is the "main" way for us to process a scene, but the most accessible/relatable way.
What you posted looks pretty cool, I don't know enough about it to understand what I should be prioritizing focus on, but we can chalk that up to ignorance. The benefit that driver-view footage has is that it is a viewpoint all of us are familiar with. If you ask me to watch dashcam footage to assess some kind of traffic thing, there's a general expectation of where I keep my eyes and what I notice.
This normal-human-view mode is probably going to be necessary in AV cases in which we determine whether the car's AI did the right thing. Presumably, as AV becomes mainstream and extremely safe, these accidents will involve edge cases and outliers which are poorly interpreted by sensors/non-human-vision. Seeing the scene as a human driver does might be a necessary starting place?
But the Uber case in AZ, IMO, proves your point. The Tempe police quickly made a judgement call based on what seems to be inadequate video. Everyone who can now view the video will also be inclined to think how impossible it would be to avoid hitting the victim, even if the actual scene in-person has much more light. And of course, we don't want to judge AV solely on whether it performs as well as normal humans.
exactly this. what's the response time of software? it ought to be close to zero and significantly faster than human's. let's say it's a generous 0.5s - no brakes where applied at all, and even with the crappy darkened video we got (place isn't that dark https://www.youtube.com/watch?v=1XOVxSCG8u0 ) the pedestrian was in view for 2 to 3 seconds.
car didn't see it at all even in those last moments.
Well it was a pedestrian but they were walking their bike across the road. It's not like the software should make a distinction between a cyclist in the way and a bicycle with no rider in the way.
Indeed, it's hard to find pedals without them. Even ones that cost $10 a pair have reflectors. Unfortunately, pedal reflectors are ineffective when the bicycle's path of travel is perpendicular to the light source. The video doesn't reveal evidence of other reflectors, such as the common spoke-mounted ones whose purpose it is to highlight a bicycle traveling crosswise. For a moment, the bicycle is clearly illuminated by the headlights; I don't see any spots of light on the wheels or elsewhere.
For a side view, the reflectors on the tires (visible at the end of the video) are way better indicators of “watch out! Bicycle” than those reflectors.
See this video for a comparison of visibility (not in English, but that's immaterial - set speed to 2x ;)): starting with a "bike ninja" and going all the way to "Christmas tree" https://youtu.be/oAFQ2pAnMFA?t=1m0s
It's from 2011, there's been a lot of improvement in consumer-grade cameras since. Even so, it fits my perception IRL: even a small reflector is orders of magnitude better than no reflector, and adding multiple (esp. covering 360 viewing angles) makes you stand out at night; same goes for pedestrians.
Uber may not be at fault, legally speaking. That's up to the legal authorities to decide.
However, as a society and civilization, and even more so, as engineers and scientists, we are going to expect that the autonomous car matches or exceeds human-level performance in critical situations like this.
Therefore the time spent on investigating, understanding, and discussing the root causes of the accident is worth understanding. Accidents like these generally do not happen due to a single factor. It is necessary to understand all the necessary factors if we want to make autonomous driving systems more reliable.
At the very least we need to understand whether the pedestrian appeared in the other sensors that a human could have identified by looking at the sensor data, and if yes, whether the autonomous system matched or exceeded human-level performance by detecting the pedestrian, and if the pedestrian was indeed detected, why the autonomous driving system failed to respond to the situation.
Surely not? Cars are routinely driven by people who are not owners, and liability for traffic offences (including that the vehicle must be insured) is with the driver.
In my experience typically only minor infractions like parking violations are assigned to the registered owner of the vehicle, but in other case – accidents, running red lights etc. – the driver is liable regardless of who owns the car.
No. The general rule is that negligence is required to be held responsible. If I let my next door neighbor borrow my car to go to the grocery store, and he hits someone, I'm not responsible. Unless, the person can prove "negligent entrustment", i.e. it was irresponsible just to let this person borrow my car, e.g. they're a habitual drunk, or blind, or 11.
However, most auto liability insurance covers whoever you permit to drive the vehicle, so the owners policy does typically cover the fender bender on the way to the grocery store.
Correct, the owner's insurance policy is the primary coverage when the owner lends their car to a 3rd party. Obviously in the case of a moving violation the driver is at fault and receives the penalty, but damage is still covered by the owner's policy. In the case where the other driver is at fault, that car's owner's insurance is liable.
A fully attentive human driver might have hit this person regardless. Would they have hit them while taking no evasive action whatsoever? No swerving, no brakes?
I don't think so: the dash cam video is misleading. I had multiple ninjas jump at me before, and although I did notice and avoid them, they were not visible on the dashcam until the very last moment. Surely Uber would not release data to intentionally mislead the public?
This dashcam footage was released by the local police. It's likely they don't have the ability to access the autonomous car's working telemetry. Given Uber's legal history I doubt they'll release anything until they're compelled to by law. Personally I find it borderline irresponsible of Tempe PD to release this video and statements based on this video so early in the investigation.
Or flick your high beams, quick beeps, adjust speed... I do all these things if I see anything on a collision course with my vehicle.
It is surprising to learn that these vehicles are operating at night. To collect training data, since nighttime driving is inevitable, perhaps there are ways to simulate night to the computer vision systems during daytime so the human supervisor can still see clearly.
Lol, the "human supervisor", looking at his knees, probably on reddit or tweeting.
Would you trust this system that didn't even manage to slow down at all with a pedestrian slowly pushing a bike directly in front of it, artificially adjusted to be even worse, driving during the day??
This is pretty much the experience I have with my dash cam, a Yi. In its recorded video, its automatic exposure control make it look like everything outside of the headline cone is pitch black, but it is actually not. I have seen deer and possums by the side of the road, and debris etc, that did not show up when I later checked the video for the same period. There is enough spillover light from modern headlights that a human whose eyes are dilated and adjusted to dark conditions will see a pedestrian standing on the median, stepping off it, crossing the inner lane towards the car's current lane. More than enough time to begin to brake and possibly swerve. I have dodged animals in a situation similar to this.
I compare it to the backup camera in my car. While close up at night it is good, if something or someone is a short distance away I can barely make them out. However, looking in my mirrors I can see them or at least make out that someone or something is there.
A camera can have pretty good dynamic range at night, but it needs a big sensor, a huge lens to operate with a fast shutter speed. In the video, you can already see the motion blur, indicating shutter speed is slower than what it needs to be to identify nearby objects in low light.
Autonomous cars are never going to be viable. Just looking at the cost of high-end SLR sensors and lenses that you'd need to match human eye dynamic range, and you're already looking at an expensive setup, before we even get to things like 360-degree vision and IR/LIDAR/Hyperspectral imaging. And that's in addition to all the compute problems.
Sorry Silicon Valley tech-bros, but it's a fantasy you're chasing that's never going to happen. The quicker we can end this scam industry, the better.
I think you’re comparing object detection to high quality photography though. There are plenty of options that can detect objects at night. Even cheap infrared technology, I would think, would be sufficient for picking up moving objects at night.
High-quality exists because the human eye is that sensitive and discerning. And there aren't plenty of options that can detect objects at night. IR isn't any cheaper, and then you have to figure out what IR bands you want to detect.
Wetware is astonishing stuff. All the propaganda to anthropomorphize machines is showing here... cheap IR sensors are not the issue. AI is not intelligent and inanimate objects have no self.
They should pivit to augmenting drivers, not attempting to drive for them. I would happily utilize a properly designed HUD (meaning I have source access) connected to a fast MerCad or bolometer array.
Sorry for lack of input or varied discussion but I just had to stop and say how goddamn friggin cool it would be to have bolometers hooked up to a smart HUD that didn't interfere with your vision of the road. Something really translucent that smartly blended it's color scheme as to not interfere with the coloration of signs and details beyond your view on the road / around the road.
But you are right, though. I think augmenting drivers sounds like a great idea in the sense you talk about. The kind of augmenting drivers I don't want are those stupid headbands you'd wear that beep like crazy if your head starts tilting in a way that resembles falling asleep. If you are in danger of falling asleep at the wheel and need a device like that I think it's pretty obvious one should take a nap on the side of the road or in a free parking lot, haha. Hopefully if we do wind up headed in that direction the people inventing will have a similar way of thinking and inventing.
I've read (see [1]) that humans have a low-light ability that approximates ISO 60,000, a pretty large value and larger than simple video cameras provide. However, very high end pro/enthusiast SLR's go considerably higher, see this real-time astrophotography with the Sony a7s at ISO 409,600 (youtube video [2]). The same Sony will work great in full sunlight too.
The Canon ME20F-SH is a video camera reaches ISO 4,000,000. This camera has a dynamic range of 12 stops and is available at B&H for $20,000. [4]
Of course, this isn't exactly the challenge that cameras face when assessing a scene. The dynamic range happens within a single scene all at the same time. Wide dynamic range (WDR) is the term I've seen used in describing video cameras that can handle both bright and dim areas within the same scene.
No that's not how ISO works. The Canon ME20F-SH shoots high definition video at professional video shutter speeds and has an available ISO range of 800 to 4,560,000. At $20,000 I'm not suggesting that this exact camera would be appropriate for use in autonomous vehicles, but I am pointing out that video systems can now exceed the capabilities of human eyes.
There are a number of video samples shot on the Canon ME20F-SH on YouTube. In these one can see that under low light situations the camera is shooting at ordinary video speed (the camera supports shutter speeds from 24 to 60 fps). I'm not trying to push the Canon ME20F-SH; I don't have any association with Canon. The manual for this camera is available on-line if you'd like to read up on it: [1].
The actual exposure of a video frame or image depends upon the f-stop of the camera's lens (aperture), the shutter speed, and the ISO of the image sensor. See [2].
Basically, each doubling or halving the shutter speeds corresponds to one "full-stop" in photography. Each full stop of exposure doubles or halves the amount of light reaching the sensor. Changing the aperture of the camera's lens by full stops also doubles or halves the amount of light reaching the sensor. Full stops for camera lenses are designated as f1, f1.4, f2, f2.8, f4, f5.6, etc.
The light sensitivity of the film or sensor is also customarily measured in full stops. Very slow fine grained color film is ISO 50 and is usually used in full sunlight. ISO 100 is a bit more flexible and ISO 400 used to be considered a "fast" film for situations where more graininess would be acceptable in exchange for low light situations. Each doubling of ISO number corresponds to a full stop. So a photo take with ISO 400 at f2 with 1/1000 second shutter would have the same "brightness" as a picture taken at ISO 100 at f2.8 with 1/125 second shutter (less 2 stops ISO, less 1 stop aperture, and plus three stops shutter speed). Naturally, other factors come into play, the behavior of film or digital sensors at extremely slow or extremely fast shutter speeds isn't linear, there are color differences, and noise issues too. See [3] if you are interested in more about how photography works.
> I have seen deer and possums by the side of the road
Both of those have eyes that act as reflectors and you can see their eyes well before you can actually see the whole animal.
This[0] suggests that the total time required for a human to avoid an incident like this is 3.6s (at 35 mph, casual googling suggests the car was doing 40). Even if we add 1 second of extra time to deal with it I'm not sure that makes the cut.
I know what you're talking about with the eyes, I spend a lot of time driving rural WA highways at night, but no. I have seen deer that had their heads facing the other way and were standing in the shoulder/ditch area. In conditions where i can definitely make out the shape of the deer and its location but the dash cam sensor misses it entirely.
Your last paragraph is a valid calculation if this were a case of a person stepping directly off a curb into the lane of traffic. However, it appears that they were probably standing on the median looking to cross, then stepped off into the left-most lane of traffic, an empty lane, proceeded across that lane towards the lane in which the car was traveling. In this sort of situation human intuition will recognize that a person standing on the median of a high-speed highway is likely to do something unusual. Particularly when you observe the visual profile of, as media has reported, a homeless person who is using the bicycle with numerous plastic bags hanging off it to collect recycling.
Driver didn't see this person because the driver was occupied with smartphone, only occasionally glancing up.
Also, has anyone here talked about the effect on the eyes of watching a (typically) bright white screen vs letting them adjust to the light of the night yet? This point deserves to be brought up.
Perhaps the video was intentionally darkened to simulate this effect. :P
I'd like to have an interior view of what driver was actually looking at. It couldn't have been a FLIR monitor, for sure.. it seems more likely to be a phone held in the right hand? Bit hard to tell with the quality of the footage, but driver looked rather tired to boot.
If so (a hand held phone), in Australia that driver would be going to jail for culpable driving causing loss of life.
It could have been anything readable. I got the feeling it was either a Kindle or something like that or maybe even a hardcopy of something printed or written on paper. This was just a hunch but I think it's being validated in my mind by the fact that there was no light seeming to shine on the driver's face but that's probably due to the night vision camera not picking up that type of light? I don't really know. My mind is filling in a lot of gaps here, I realize.
EDIT: Upon re-watching the video a third time and really paying attention to this I don't think there is any real way for us to know without confirmation from the driver them self or an official report on the incident. My mind was definitely deciding things that just aren't discover-able from the video itself.
"Uber also developed an app, mounted on an iPad in the car’s middle console, for drivers to alert engineers to problems. Drivers could use the app anytime without shifting the car out of autonomous mode. Often, drivers would annotate data at a traffic light or a stop, but many did so while the car was moving"
The whole project seemed designed for an outcome like this. Eg allowing app to be used whilst on the move, after reducing from 2 to 1 operators. Culpability ought to lie with Uber.
That's their only purpose. Nobody in their right mind could expect human observers to stay as alert as an actual driver when cruising for days with an AI that is good enough to not require interventions all the time. Passengers add nothing to safety, and an almost reliable AI will make anyone a passenger after a short while.
I think he is, at least, I've never heard of any law that removes responsibility from a driver if driving a self-driving car. I think this will also apply to empty cars, if they get into an accident, the owner is liable.
>Also, has anyone here talked about the effect on the eyes of watching a (typically) bright white screen vs letting them adjust to the light of the night yet? This point deserves to be brought up.
Using bright interior lighting at night is something that we've known not to do for more than a century. If the driver couldn't be expected to see the pedestrian because the interior lighting or UX was too bright that is not something that does not reflect favorably upon Uber.
Other people in the thread have pointed out the woman stepped out in a darker area between where the street lights are placed. Reflecting eyes are not the only way to detect an object. A person watching the road would have seen her dark silhouette contrasting to the next patch of light.
Also remember she was not a stationary object. She was in the act of crossing the road. Human eyes/brains are good at detecting motion in low light even if we can't 100% make out what the object is.
I have lived in Tempe and know that part of town well. There are apartments, gas stations, hotels, strip malls, fast food restaurants and a strip club. It's not a pitch black country road.
Yep that exposure control / sensor quality of the dash cam in the video was rubbish. My own Blackvues produce far, far better results than that. Just look at how nothing is illuminated by street lights, this clearly has the effect of making the poor rider appear "out of nowhere". Also agree it appeared driver was on smart phone most of the time, thus not in control of the vehicle, and had thus no business being on the road as these are systems UNDER TEST.
If that's the best Uber can produce then they ought to hang their heads in shame. Unless it was doctored with... as I find it hard to believe they'd put such rubbish quality cameras in their trials.
Do you trust Uber to provide all the data, or would they selectively produce data favorable to them?
Do you trust Uber to provide unedited raw video, or would they process it to increase contrast, make it appear that nothing was visible in the dark areas of the frame, reduce the resolution, drop frames, etc.?
The internal camera (let's be honest and call it the scapegoat camera, because that's the only practical use for human "safety drivers" when they are not permanently engaged) must take almost all its light from IR, because we don't see anything of the smartphone screen glare that the eye movement so clearly hints at.
I don't think the driver is looking at her smartphone. I think she's checking the car's monitor (as in a computer screen). Although to be fair, that should be showing the car's view of its surroundings so I don't know what's going on there.
Edit: Nevermind. Someone posted a picture of the car's interior, below and there's no computer screen.
Ok so this is getting old now, but I just came across the following - which show what I'd expect the roads to look like, and geesh were Uber ever full of crap to release their video which pretty much had the effect of exonerating them.
The driver has been described as male in news reports:
> "The driver said it was like a flash, the person walked out in front of them," Moir said, referring to the backup driver who was behind the wheel but not operating the vehicle. "His first alert to the collision was the sound of the collision."
Human eyes have the same issue: if you are next to a bright light source, the areas without or less light will look much more dark. I assume cameras work the same way?
Cameras work the same way, but much much more poorly. A human eye can see multiple orders of magnitude higher range of light to dark areas at the same time. The accepted estimate is that the human eye can detect a 1 million: 1 range from light to dark in terms of photon intensity.
But this has got to be just the black-box camera, right? Surely the actual camera they use as a driving sensor is much better than this? Not to mention the LIDAR and all the other sensors that should have caught this.
> clear the driver was looking at his phone or doing something ...
Seriously, what else can you expect. These companies who do put these things on the road with the justification that "There is a human behind the wheel" should be taken out back and shot in the head...Just pull the plug. No more self driving cars for them. Those are just the kind of tech companies we don't want around...
See, it is not a mistake that they are making. They know well enough that this human behind this wheel is a useless as a dummy. But they do it any way. What does it say about them?
1. A driver who is not looking at the road cannot "potentially intervene", and is as good as no driver at all..
2. These companies seem to be doing nothing to make sure that the drivers will pay attention always and is always in a position to intervene. They even seemed to allow smart phone usage while they are in the car.
So, according to them, the human behind the wheel is just a decoy to prevent backlash from officials and the public, so that they can always say, "look, there is a human behind the wheel if something goes wrong"...
Also, even if they implement some measures, they can only make sure that the driver has eyes on the road. Not that they are actually paying attention. A driver who is actively driving the car will notice a lot more stuff than a passenger who is just looking at the road. There is no way to make a human pay that kind of attention with out actually driving the car. So at best, your "driver behind the wheel" is as good as a passive passenger.
And as told before, the companies are not even trying to make sure of that.
I agree completely. As far as I can tell, the driver did not even have hands on the steering wheel. How hard would it have been to put sensors on the steering wheel to require both hands? They didn't even do that. Although even if they did, I agree with your statement that "[t]here is no way to make a human pay that kind of attention with out actually driving the car."
Frequent, randomly scheduled disengagements should keep the driver quite on edge, preventing them from becoming a passenger. But each and every one of them would create additional risk, so the net improvement might be negative. There is just no way to get this right, except for being reluctant of pushing to scale. With all the hype, wishful thinking and investor pressure, this clearly isn't happening.
I've been thinking about this for the last couple of days, and it's definitely a hard problem -- even with steering wheel sensors and eye tracking, it doesn't stop people zoning out and not being ready to react.
I did wonder if you could require the driver to make control inputs that aren't actually used to control the car but are monitored for being reasonably close to how the computer is controlling the car, and then the automation disengages (with a warning) if the driver is not paying sufficient attention. I then realised that may be _worse_ - in the event of a problem, the driver would have to switch to real inputs that override, which may delay action and not be something they do automatically. It would mean they are paying attention more to see if the automation is making errors where they have more time to react though (e.g. sensor failure that is causing erratic behaviour but not led to an emergency situation).
I wonder if a hybrid approach might be viable -- fake steering is used to ensure that the driver is alert and an active participant, but the driver hitting the brakes immediately takes effect and disengages the automation.
Not difficult at all, and you can make them keep reasonable attention. Look at the new Cadillac driver assist: sensors in the wheel for hand placement -and- eye tracking. If the driver isn’t watching the road/holding the wheel, they get escalating alarms until the autopilot disengages.
And that’s consumer drive assist tech, not “we are experimenting with full autopilot” tech, where I’d think such safety measures would be even more appropriate.
This is a solvable and solved technical challenge. Uber just didn’t devote any resources to it because they don’t appear to give a shit beyond acquiring a legal fig leaf to shift liability from themselves to an individual.
I could be wrong, but I believe part of the reason for having a human behind the wheel is that it allows the testing to take place under existing driving laws. At some point prior to an unmanned vehicle being allowed on the road, lawmakers need to have some kind of framework in place to deal with any incidents that arise. With a human behind the wheel, a fully autonomous car is legally no different to cruise control - it's just a driver assist, and the human behind the wheel is still ultimately responsible for whatever the vehicle does.
In that context, the landscape changes significantly - instead of a self driving car that mowed down a pedestrian, we have a driver who was too busy looking at her phone to pay attention to what her vehicle was doing. From the various articles, it seems that she's not an engineer, and is there in effectively the same capacity as any other Uber driver. If that's the case, she's putting far too much trust into an experimental system. I agree that Uber could do more in the way of technological means to ensure the driver is paying attention, but at some point, an adult with a job needs to be responsible for doing that job.
>lawmakers need to have some kind of framework in place to deal with any incidents that arise. With a human behind the wheel..
The framework should have been in place before these vehicles were ever put on the roads. For example, there should have been some formally specified tests for a self driving vehicle before it can be put be on the road, even with a back up driver..
> a fully autonomous car is legally no different to cruise control - it's just a driver assist, and the human behind the wheel is still ultimately responsible for whatever the vehicle does.
Any thing that does not require drivers to keep their hands on the wheel is not a driver assist. It IS the driver. So there should be tests that make sure of the competence of the tech that is in the drivers seat.
>they can only make sure that the driver has eyes on the road. Not that they are actually paying attention. //
I'm certain that if you can design and build a self-driving car that you can design a simplistic human attention monitoring system that will cause the car to pull over if attention level is too low.
Gaze monitoring that checks for looking downwards or away from the carriageway for extended or too often repeated periods wouldd probably be enough.
I imagine the attention of the "vehicle operator" is vital to the proper training of the vehicles -- if they don't see near misses, or failures to slow for potential hazards, or failures to react to other road users then how can the softwares faults be corrected? Do they get a human to review all footage after the drive?
The difference between Waymo and Uber here should be the difference between being allowed to continue, or getting barred from further self-driving research.
I feel sorry for the 'safety driver' here as it seems likely much of the liability will fall on her. As a transgendered ex-felon she can't have had a lot of fantastic job opportunities. I wonder how much Uber was paying her to sit in the hot seat.
I am pretty sure Uber uses an iPad app for its autonomous vehicles. The driver is looking at that iPad application periodically along with the physical windshield view.
If you search "Uber autonomous vehicle" you can see some videos of the display. From what I gather, basically gathers the signals into a human readable model. In general I wouldn't have recommended this driving style but it might have been too dark to see much anyway.
I don’t understand this, I’ve seen a few people comment in the same vein.
People can safely drive in total darkness with the aid of their amazing human eyes and high-beams.
If for some other reason visibility is low you slow down - not rely on glancing at a backlit display ruining your own night vision and taking your eyes off the road for seconds at a time.
I can confidently assert that Asian or atleast Indian drivers will almost assuredly not hit the pedestrian in this scenario; We have trained our eyes and senses to watch out for these as it happens all the time.
EDIT: what i meant, in light of the downvotes is that humans can train themselves to see, and just that folks driving in Asia have heightened sense of alertness, due to their environment. Hope it came out alright.
> Also, watching the video of the interior it is clear the driver was looking at his phone or doing something else just prior to the impact. This alone leaves me skeptical to just how much could have been done to prevent this accident.
Wait, aren't you mean to have your hands on the wheels at all times? I don't see what to be skeptical about when if he just followed the law this could have been avoided.
It seems to me the driver might be in for some legal trouble.
Low beams at high speed do not give enough advance warning to reliably prevent a collision; as your lights are turned downward, you see a pedestrian only when they're quite close.
In general, traffic safety requires that road planners ensure that one of three conditions always applies:
a) the roads are lighted from above;
b) cars are able to use high beams;
c) there are no pedestrians crossing the highway.
This can be done in general, mostly by investments in infrastructure to ensure lighting or isolated highways wherever the density doesn't allow to drive with high beams.
> Also, watching the video of the interior it is clear the driver was looking at his phone or doing something else.
Probably checking the computer installed for diagnostics of the autopilot system. If it's in self driving mode and you are the engineer in charge, you'd want to constantly check what the system is seeing vs the actual conditions on the road.
If you're the driver of a car you're supposed to ensure safety by looking out, not verifying sensory information. If Uber designed their cars to show a rendering of the computer's perception to the driver, or other sensory output, they would violate that principle.
To me it looks like the guy is just falling asleep at a boring job. In all likelihood that was not an engineer more than any other taxi driver is an engineer.
The software is the "driver" of this car. Not the human behind the wheel. Take a look at job descriptions [0] for this. They always include a bit about "operating in vehicle computers". The fact, we don't know what the person is doing.
also note that pushing the brakes was not the only option : steering the wheel to avoid collision was another, maybe more efficient. Still, I feel the same as you do : I cannot guarantee I would have avoided this.
> The gap between street lights (and hence the person) was in the field of view of the camera the entire time
But the gap between street lights is going to be very hard to see into.
> I'm confident my eyes are good enough that I would have been able to see this person at night in these lighting conditions.
I think you're overconfident. Human low light vision is very good if there is low light everywhere. But it is not good at seeing into low light regions when brightly lit regions are nearby.
That said, I agree that a visible light video camera is likely to be even worse that human vision under the given circumstances. But as others have commented elsewhere in this thread, the car is not just supposed to be using a visible light video camera. It has LIDAR and IR sensors, which should have clearly shown the pedestrian well before visible light did.
> But the gap between street lights is going to be very hard to see into.
This wholly contradicts my experience driving at night on a street with street lights. I can't recall a time in my entire life I have had significant difficulty seeing into the gap between street lights. Keep in mind that the gap is not arbitrarily chosen.
Edited to note that I have experienced difficulties in low-vis conditions such as snow storms, sand storms, VERY strong rain storms, etc. None of which apply to this situation.
Keep in mind a lot of folks in this thread might be suddenly realizing they have reduced ocular ability at night, a likely common condition that pretty much nobody is aware of when it’s minor (because it’s not obvious something is amiss; maybe it’s just that dark). I agree with you that streetlights and headlights are almost universally sufficient in my experience. If they’re not, it’s worth getting your eyes checked out for light sensitivity at night. You never know.
I’m not sure a typical eye exam checks for it, either, because none of the tests I can think of seem like they’d be useful.
(As usual, an even keeled comment based on family experience is -2 and rapidly being silenced with zero feedback inside 5 minutes, which makes me wonder why I contribute to this community at all, probably time to stop)
I suspect it's too late to chnage now but have a "throwaway" account is an indicator you might not be committed to the community. one has to dig a little deeper to find out a multi year history with 4000 karma. so first impressions of your comments might be getting biased (it might just the "red car effect" but i am seeing a lot more throwaway accounts these days)
I would also not judge the community based on reactions to this very contentious thread - i am wary of jumping in on this one, but thought it worth noting your comment was not wildly out of place.
Judging a comment, or commenter, based on karma is asinine. Respond to comment, not commenter; ideas not people. You are not well representing HN, and this is my 'unpopular opinion' account talking. There are plenty of better ways to engage, and I do appreciate your enthusiasm for HN. Perhaps this is an apt introduction to the heated discussion that is HN.
This may be how you believe you see the world but most people take reputation into consideration and on sites which expose that information account age and karma are very popular cues for that.
Karma does not mean shit. It just means you are complaisant. I think the proper way to use things like HN/reddit is to always use a throwaway account and always speak your mind without the fear of negative karma...So I also agree 100% with the parent. Reply the comment, not the commenters, their karma or their entire history.
Well, in my view I was responding both to the comment ("i am leaving") and the commentor (making the years of participation and 4000 points relevant). If someone has been a contributor for many years then we should consider why they chose to leave. it might be them, it might be us.
I actually believe i am representing HN as a place where different opinions can be voiced, hopefully in a manner to generate light not heat. Heated discussions are rarely the useful or interesting ones to read.
Thank you for appreciating my enthusiasm.
PS
Are you using two accounts - one ("my 'unpopular opinion' account) for saying things you fear people might not like? That seems odd. May I ask why?
I did one at my last eye exam and it was pressing a button when you see dim flashes in all different locations. If you had low sensitivity, you wouldn't see those flashes and presumably you'd get a low score.
That test mostly isn't testing sensitivity, it's testing field of view which is an indicator of some potential eye health issues. It might end up testing sensitivity incidentally but that's not the purpose.
> Keep in mind that the gap is not arbitrarily chosen.
It's not supposed to be, no. But the gaps are not always optimal. The spacing of the street lights in the video (to the extent I can tell) seems to be quite wide, wider than I would think is optimal.
The edges of the "lightpool" that the lamps normally cast is probly being clipped by the cameras crappy dynamic contrast, it is almost certainly a much larger lightpool in real life.
If Tempe is like Tuscon, they are using different kinds of street lighting from the rest of the country to minimize light pollution for star gazing reasons.
> But the gap between street lights is going to be very hard to see into.
Looking, right now, at a parking lot between two lights from a well-lit room. I can make out most of the outline of the black car in the middle of the "darkness" without any trouble. This isn't even the low light vision kicking in (which I agree isn't going to kick in if you're driving). Human vision should be able to make out the pedestrian earlier than the video footage.
How long does it take you to make out the black car and determine that it's a car? What if the car were coming straight at you out of darkness and you were standing in the light of a street lamp?
Also, are you looking straight at the car? Or are you looking elsewhere so that the car is in your peripheral vision, the way it would be if it were on the side of a road you were driving on?
Not when you transition from high to low light conditions. The problem is night vision has more noise which makes movement detection far more difficult. This is made worse because the pupil can't fully dilate making the gaps seem much darker.
This street in particular is weird at night because the street downstream rises up, and the light from those lamps is cast at a higher point. The place she was hit is extremely dangerous because there are no lights on her, and no lights behind her.
FWIW the spot where the crash happened is in fact badly lit. I know this anecdotally from having been at the location for events -- it's right next to a concert venue -- but it can also be seen on other dashcam videos.
In this video [1] driving northbound, same as the vehicle in the crash, the car first goes under AZ-202, emerges under a streetlight, goes through a darker spot, then another streetlight (as you see the rocky outcrop), and then a very dark spot: and suddenly, you see a right-turn lane that wasn't there before. The latter dark spot is where the crash happened.
Another video by the same author, driving southbound [2], provides another useful reference. And these videos are three years old, yet the illumination of the roadway has not improved. Cameras exaggerate the contrast a bit, but not unreasonably so. The streetlights in question essentially aim directly downwards, illuminating the roadway immediately underneath, but much less of the surrounding air than other designs. This is responsible for the dark gaps, albeit it does significantly reduce light pollution.
Found more. The car in this video is going southbound, camera facing backwards [3]. This view faces the same way as the Uber did, but of course this video is moving away from the scene, and offset by a few dozen meters to the west. The drastic change in roadway illumination can still be seen.
In a fourth video [4], the car is going northbound, like the Uber, in the proper lanes, but the camera is pointing obliquely front-right. The illumination seems better, but you can still see the intensity of the shadows, including environmental shadows and the car's own shadow, as it moves between the lights.
Tucson does it due to the nearby observatory. The greater Phoenix area has a huge glow that washes out all the stars. You can see the glow as far away as Casa Grande when you come out of the little rocky pass on I-10 north of there.
> The greater Phoenix area has a huge glow that washes out all the stars.
I live in the Phoenix area, on the west side closer to Glendale (specifically, the border between Phoenix and Glendale is literally in my back yard).
There are times in the summer where the glow from the city is so bright, that rather than a dark sky (never black), you have a grey dimly lit sky instead.
Literally, "the sky was the color of television tuned to a dead channel" - maybe not as bright as the static Gibson was referring to, but still bright enough to see by - even without a full moon.
Everyone is moaning and slicing and dicing what the self-driving vehicle did wrong but, since you're familiar with the area: are pedestrians typically expected to be crossing this road?
Seems like the accident has a lot of factors that might not only be the self-driving car's fault, nor even a human driver that was fully in control. Regardless of how well people may want self-driving cars to do, one thing that can actually exist in the present is to make sure that we are creating safe ways for pedestrians to cross a road.
I've also driven around here a lot. No, pedestrians are not common. Maybe once a week in my experience? They do love to cross outside of crosswalks at night, though, and I've found that I have to adjust my own eyes' object recognition to look for moving shadows and not just moving lights, because they're very hard to see even in well-lit areas.
I've driven many thousands of hours at night and have dealt with a fair number of crazy pedestrians including a rather ... uncoordinated ... guy in Casa Grande who decided to go in circles on his bike in the middle of the road at around 3 AM for no discernible reason. Fortunately that place was much better lit and I was able to see him and stop until he got out of my side of the road.
So it's not that common, but yes, every so often you will see some person in black jaywalking across a wide road at night and they're quite hard to see. I don't think a lot of people appreciate that the streets here are wide & fast and that there just isn't that much pedestrian traffic even in daytime.
That was my suspicion. I've lived in very suburban areas before as well as rural ones where you might even be going 55 on a two-lane road with no street lighting whatsoever.
Here in LA, it's dense and traffic can't get up to very high speeds and we have relatively frequent places to cross safely if people choose to do so. I've definitely seen those who choose not to walk an extra 100 feet to wait at a crosswalk nearly hit in dusk or night traffic.
No amount of automation is going to bring the accident rate down to 0 so through a combination of factors, such as traffic and community design, we can work in tandem with automated driving to get closer. There's still the X factor of our human ability to do really dumb stuff.
This site lies on the approach route for Sky Harbor airport. I'd imagine the street lights are intentionally designed to reduce light pollution at the expense of "on the ground" effects.
It's not so simple. Technically, you are not wrong but a video feed should have been sufficient here. It should also be considered that digital video has improved drastically over the last decade.
Even LIDAR aside, computer vision and a raw video feed should have been enough to have prevented this collision.
When a digital camera records an image, a gamma curve is applied to it before display, which makes up for our bias against the darker portions which the digital equipment does not have. We are very capable of guessing the results of bright conditions but not dark conditions via compressed video.
Moreso, these cars should not be using consumer CCDs with compression. They should be utilizing the full possible scope of video.
> When a digital camera records an image, a gamma curve is applied to it before display, which makes up for our bias against the darker portions which the digital equipment does not have.
Gamma correction makes up for a bias against darker portions in the display, not in our eyes. It's a holdover from the CRT days where the change in brightness between pixel values of, say, 10 and 11, was far less than the change between 250 and 251. Human eyes have excellent low-light discernment which is why 'black' doesn't really look black and you can make out blocky shapes during dark scenes on some DVDs.
Compressed video lacks information in the blacks and that is why we see blocks. The blocks are not there before compression, so it’s not simply a matter of detecting them. While we are good at seeing objects in blacks, your explanation alone doesn’t account for why compression algorithms reason to remove so much of that data. Maybe we are saying the same thing. It’s hard to tell.
Your assertion about the origins, however, are at odds with what I have been taught, my understanding, and all the supporting info I am finding in a quick search. My understanding is that luminance values from a sensor have something of an empirical scale but I’m sure this no complete explanation. I am speaking from my working knowledge. I can’t find anything supporting that it is simply a fix for discrepancies between display types. Can you link to something or explain what I am missing?
> The dynamic range of the human eye is vastly better than a visible spectrum camera.
Certainly better than any camera mounted on a dashboard.
It's honestly a bit surreal how the pedestrian appears out of the splotch of pure darkness in the frame. That's low dynamic range and resolution (or high compression) at work, not how light behaves in reality.
I figured that light in front of the car was mostly just messing with the camera but that driver sure didn’t see that pedestrian either. I’m willing to give a human driver the benefit of the doubt here and say that even with eyes on the road and hands on the wheel the outcome would likely have been the same. The pedestrian was not highly visible - no reflectors, dark clothes, it’s really hard to see people like this.
The eye can gain a lot more stops through adaptation (irising, low-light rod-only vision), but those mechanisms dont come into play when viewing a single scene -- and cameras can also make adjustments, e.g. shutter speed and aperture - to gain as much, if not more, range.
A camera captures the entire scene in a frame with a fixed dynamic range. Human vision builds the scene with spatially variant mapping, the scene is made from many frames with different exposures stacked together in real time.
I'm concerned about poor scotopic adaptation due to the rather bright light source inside the car - maybe it's the display he's looking at. I see a prominent amount of light on the ceiling all the way to the back of the car and right on his face. It's really straight forward to collect the actual scene luminances from this particular car interior and exterior in this location, but my estimation is the interior luminance is a bigger problem for adaptation than the street lights because the display he's presumably looking at has a much wider field of view, and he's looking directly at it for a prolonged period of time. It's possible he's not even scotopically adapted because of this.
And also why is he even looking at the screen? He's obviously distracted by something. Is this required for testing? Ostensibly he's supposed to drive the car first. Is this display standard equipment? Or is it unique to it being an Uber? Or is it an entertainment device?
Retest with an OEM lit interior whose driver is paying attention. We already know the autonomous setup failed. But barriers are in place than also increase the potential for the human backup driver to fail.
I agree, but I don’t think the eye can adapt beyond its inherent dynamic range over a matter of milliseconds - the iris is not opening or closing over that timescale, so you’re relying on the inherent dynamic range of the retina (which is pretty good).
What the eye IS doing is some kind of HDR processing, which is much better than the gamma and levels applied to that video. I bet a professional colorist could grade that footage to make it a much better reflection of what the driver could see in the shadows - even with a crappy camera, you can usually pull out quite a bit of shadow detail.
Since in the video, we aren't seeing the original scene, but rather, the camera's interpretation of that scene, I think it would be hard to judge except to base it on what your average streetlight brightness is.
Like a camera, your eye also has only so much dynamic range. So if those street lights are bright enough, or your interior lights are too bright, you might have nearly zero visibility in those shadows.
But it is certain that a self driving car "should" be able to see. Even two cheap digital cameras one tuned to see the darker range and the other brighter should easily see in these type situations.
"Even two cheap digital cameras one tuned to see the darker range and the other brighter"
Sounds a lot like rods and cones in our eyes, huh?
There's another difference with eyeballs that would almost certainly have helped here - the low light sensitive peripheral vision that the rods provide is also attuned to movement, we're more sensitive to movement in peripheral vision as well as being better able to see in low light.
You wouldn't need two different cameras, just one camera shooting HDR video (alternating between over/underexposing the frame so that no information is clipped) to get a clear image at all exposure levels.
Eyeballs are pretty good at night vision once adjusted, but good high sensitivity cameras can be much better. And let's not get started on LIDAR/RADAR... it seems clear to me that this was not a sensory deficiency, it was poorly designed/tested software.
No, much more like the iris in our eye. Turn on a bright light inside a car and see how hard it is to see outside on a dark night. Modern HDR cameras have a much higher dynamic range than the human eye. Hence the surreal HDR photos you see.
I also suspect that human eyeballs would have a different view of the light/dark portions of what's depicted there, and especially eyeballs would have probably had a much higher chance of detecting movement in peripheral vision than that video gives any hint of.
We typically cant see much detail in the scene out of our small region of focus, but you can bet if a tiger appears from behind a tree our visual system will scream to the brain _look over there right now!_
Our eyes and our entire visual processing system is very much not "just like a webcam, but made out of meat".
Is it possible that driving under intermittent street lights messes with the aperture or image recognition? It would be like flashing a strobe light at the camera.
right, so the camera's night vision mode that detects objects in the dark would have been completely blinded by the street lights while passing under the streetlamp. Take night vision goggles and look at a light. It blinds the whole field of vision.
The only thing that I think was the cars fault was that the car is programmed to drive when the driver is driving around distracted. There is no point to a human driver sitting behind the wheel of an autonomous vehicle if they aren't paying attention.
People need to understand that self driving mode isn't a freedom from the responsibility of driving safely. Rather its a tool to help ensure that driving statistically becomes safer as more self driving vehicles find their ways onto the road.
Hopefully someday all cars will be self driving and dangerous hazards/traffic reduced to the point that they are virtually none existent rather than being towards the top of the list of "preventable death" and "things humans don't want to waste most of their time during the day doing".
I’ve driven that location on that road many many times at night and no it is not that dark, it is lit up well like most city streets. The video make the contrast appear greater.
I have a dashcam, and I've seen night videos from it.
In fact, the picture from my dashcam seems much better than this low quality mess, but still night videos from it come out much less visible than reality.
I've tried to rewatch some parts of videos later, and I find I was able to see much more detail on the sidewalk and on the periphery than was captured by the dashcam. Everything gets blown out in the night videos by the headlights.
I believe that a human would be able to see in those conditions. It's a lit street with a car with functioning headlamps. It wasn't foggy or rainy.
I've personally driven down country roads without any lighting except my headlights and saw deer poking their head out of the woods a ways away for which I slowed down in case they darted across the street. Someone slowly walking their bike would be trivial.
The video makes it seem impossible but afterwards in the interviews the driver said it wasn't too bad after his eyes adjusted. He did have some issues with his own lamp blinding him which lead to errors. (He actually won this stage.)
As far as I'm concerned Uber's software/hardware is completely at fault and not ready for public testing. I'm uncertain how much better everyone else's tech is but Uber's typical carefree approach has ruined it for everyone.
There are consumer level dashcam that can shift up to 12800 ISO which can create a fairly distringuishable picture with ambient moonlight.[1]
Canon builds sensors with ISO's in the millions which should be able to see distinguishable shapes without ANY light. [2]
> It's a lit street with a car with functioning headlamps.
The headlamps may have been functioning, but they appeared to be aimed way too low. You can see that the car is able to traverse the distance lit up by the headlamp in about a second at 38 mph. If the headlamps were aimed properly, it should light up the road about 5 seconds ahead of the car.
> If the headlamps were aimed properly, it should light up the road about 5 seconds ahead of the car.
A system with this rule baked in would be driving slower.
People adjust the way they drive based on what their environment is doing, how well their equipment is working and their own alertness. Except in the extremes we should not accept misconfigured equipment as an excuse. And if a system detects that there is no acceptably safe speed for it to go then it should not move at all.
> A system with this rule baked in would be driving slower.
Arguably, the system should detect a misconfiguration like this when the car is turned on and not allow the car to be driven until the problem is fixed.
The whole reason many people on here have been advocating for self driving cars is that they can see obstructions more or less perfectly in the dark with LIDAR. I am much more interested in what that sensor said.
I'm reluctant to infer exactly what a human eye would have seen in that situation. I have absolutely driven down streets in suburbia where the gap between street lights was large enough to make them quite dark, and that video was an example of exactly what I was afraid of happening whenever I drove down those streets (though admittedly my fear was hitting a white tailed deer).
I think it might also be fair to argue that the car's high beams were not on (but again, that shouldn't matter because of LIDAR, right?).
I'm not confident even an above average human driver would be able to avoid that accident, even if good eyesight gave you an extra half second to respond. Dark clothing and no reflectors means that person was definitely invisible to both the camera and the driver for some time after they would have been visible in daylight.
I've had a couple of situations where someone appeared close to my line of travel with low visibility clothing (at night) that scared the living shit out of me, and they weren't trying to cross the street.
To be clear, I am not blaming the victim here, but do wear high visibility clothing when you're a pedestrian near high speed roads at night.
Sad side note that most people appear unaware of the benefits even the simplest and cheapest of reflectors do provide.
The seemingly random design decision of many runner manufacturers to embed tiny reflector strips in their shoes have no doubt saved countless lives. And their owners would probably be none the wiser.
Yup. There's a place for education here. I know I wasn't really aware of the benefits until adult age, when I started to find myself more often in a car, at night, in rural areas. I still remember the first experience, in which I've noticed a cyclist on another lane ~0.5 seconds before we passed him. Dark clothes, dark bike, zero reflective elements.
In Norway, when growing up, I was frequently exposed to campaigns saying "Bruk refleks!" (Use reflector(s)!), and given free ones at every opportunity.
Of course it makes sense there where daylight may be hard to find half the year, however even in Australia, once it is dark the darkness is the same.
And I haven't seen a single government initiative to increase visibility awareness - most people are completely in the dark. (Sorry)
Riding shared bike trails in Melbourne at night on the commute home, this is something I think about often in the "winter" months. Peds may hate the strong glare from my LEDs, but it is the only thing the has half the chance of making out ninjas against the frequent sports ground stadium floodlights the path goes by.
And those who are aware often lack the understanding that with glare-minimizing headlights, reflective surfaces at or below knee-level are many times more useful than anything higher. A reflective hat would be pointless.
> The whole reason many people on here have been advocating for self driving cars is that they can see obstructions more or less perfectly in the dark with LIDAR. I am much more interested in what that sensor said.
That is not the whole reason, it is one of many reasons.
> To be clear, I am not blaming the victim here, but do wear high visibility clothing when you're a pedestrian near high speed roads at night.
A person with common sense and a developed understanding of the situation would drive more slowly in situations like this. The law says that you don't drive faster than you can see.
A similar thing (no fatalities, just a shopping cart pushed by homeless people) happened to me. Ever since then, I have learned to be much more aware of situations like this (tunnel of light surrounded by darkness).
This just shows that Uber's tech is bad and that they let it on the road shows that their culture is still at least partly rotten.
I don't think Dara is the do gooder that some people are making him out to be. His primary motivation seems to be to usher Uber to an IPO. IMHO, if he actually had ethics, he would be front and center on this. Your company just killed someone. Where are you?
> The law says that you don't drive faster than you can see.
Amusingly, the law also says that manufacturers have to produce headlights that cast light out far enough to leave you adequate stopping distance at 60mph. Almost no headlights on the market currently do that.
Not a counterpoint, just a tangent that I find sadly amusing.
The ninja is the reference standard for real-world pedestrians. It's up there with the surprise moose. Systems that can only detect bright peds are going to be horrific meat grinders and lead to autocar hell instead of autocar heaven.
Preventing the accident might not have been possible, but even being able to decrease speed by a tiny amount would have greatly improved the pedestrian's chance of survival. Slowing from the 38mph that the car was traveling down to 30mph would decrease the chance of fatality from about 45% to below 10%.
I do know a bit about cameras, and you're spot on.
You will frequently see dash cam footage and night photography blow out the relative highlights and blacken the relative shadows.
This is because (cheap) hardware does not have the same dynamic range as human eyes, especially at night. So "properly exposed" it has to make a call to capture light values in the middle somewhere. Those light values too far out the top it interpreted as white, those out the bottom it interpreted as black, created an artificial high contrast version of what a human eye would see.
This is pretty intuitive, generally when we're driving down the road with our lights on, we aren't literally moving between pools of black, often in many urban areas I'll even forget to turn my lights on because I can see well enough.
You MAY be able to get a VERY BAD interpretation post processing of what a human would see by increasing the brightness of those pixels near the black threshold.
True but there are trails that cross over the road, it is an odd area. If you zoom out on google maps you will see some of the trails. Note the sidewalk/pathway. It is no pedestrian but has paths for them so it sends mixed signals.
I saw that. The median is landscaped with a bizarre X-shaped paved area. It can't be intended for recreational use or walking; it's a divider between two fast roads. At all four entrances to the X, there is the no pedestrians sign.
Also even if the camera was perfectly accurate about human field of view, no human driver in his right mind would drive so fast with such a poor visibility. Any judge would qualify this as reckless driving.
So either way the software failed:
-If AI misjudged Lidar information and didn’t compute the slow moving pedestrian it’s a fail
-If it didn’t have enough computer vision space it should have slowed down
Possibly in the second scenario the human test driver is at fault too because he should have noticed bad condition and hit the autopilot kill switch.
In France it’s 100% (in civil cases), unless the driver can prove it’s a suicide. It just goes by kinetic energy: you store it, you are responsible for it. Other people don’t have to dodge your car. And since death penalty is not part of the arsenal, killing a pedestrian is not an appropriate sentence if they commit a infraction that’s punished with a 50€ fine.
If any of you have a dash cam it's very obvious how the light levels of images captured at night look like this video and is VERY different from what you see as a driver - objects are much brighter than this with your own eyes.
Also - the car is driving way too fast.
I did some driving tonight and paid close attention to when I naturally slowed down - and albeit I'm probably on the higher curve of good drivers in that I don't tailgate, drive the speed limit and generally slow much slower than the speed limit when conditions are poor (fog/rain/snow, night, slick/wet roads, near curves/hills where I can't see the road). I noticed that many of the times I naturally slowed down on the roads here I slowed considerably under the speed limit by 10 to 20 MPH in some areas. It seems this Uber SDV is generally going as fast as it is possibly allowed to regardless of what it can see.
I don't really know how it works in the US or in this state, but in my country, you simply can't drive when it's as dark as the video appears. Either you're not in a city and you can turn your mainbeam headlights on (the blinding ones), or you're in a city and the road is much more lit and the speed limit is 50kph.
With those, the driver would've seen her from a mile away.
Yep. I live half a mile away and just drove the same path tonight around 10pm, it's nothing like the video. There are spots that are darker than others, but they don't look nearly as dark. Nowhere on the street looks pitch black, there's ambient light everywhere.
For anyone who's interested, try taking your phone with the camera app open into a dark room and comparing what you see to what's on the screen. Which shows more detail?
Out of interest-- can you take a pic while the lighting outside is similar (assuming weather hasn't changed dramatically?) and maybe adjust exposure to what your eyes see? Or take a camera phone pic for comparison?
The driver wasn't fixed on the road but he glanced two times prior the collision and had no hesitation. It seems that it was at least dark enough for him not to notice a person + a bike on a large road.
I'm also very (sadly) surprised that she crossed that kind of road at night without hurrying or reacting to the sound of cars approaching.
I too think visibility is better than it appears in the video, but I'm not so sure it's good enough to help all that much. However, even with visibility as bad as in the video, I'm confident in my ability to handle the situation. I would probably not be able to break in that short amount of time and from that speed, but neither would I drive at that speed. When there are less than ideal conditions (in this case visibility), it is our responsibility as drivers to adapt and lower the speed, possibly dramatically. This goes for autonomous cars too. If the road in front of me and the areas next to it are not clearly visible, I'd drive at such a speed that a collision would in all likelihood only result in scrapes.
I think you are wrong since this people die of this exact scenario almost everyday. The camera might be making it darker but that doesn't mean that every driver (Everyone's eyes and reaction times are different) would have been able to see her and get out of the way.
This is exactly it. I see people mentioning seeing the victim at the last second but these vehicles are supposed to be better. They scan in non visible spectrums with LIDAR. Lack of safety vest, lack of headlights, none of it is supposed to matter... or at least it shouldn't completely compromise the vehicle's systems. Camera's may not work as well but an obstacle directly in the path should still be detected. Especially an obstacle that would reflect LIDAR and give off a very obvious infrared signature.
This video also shows another point I made recently in a conversation. People need stimulus to keep them alert and focused. I don't think it's at all reasonable to expect someone to sit idly with almost no interaction or responsibility and expect them to stay alert. The human brain doesn't function that way.
I watched the video a bunch of times and I'm not 100% sure how the vehicle could have reacted at the upper maximum of time where she would have been visible to LIDAR, and maybe for Radar, to make a significant difference. At least given the two options where it could have slowed maybe 10km/hr at most (from the 40mph aka 64km/hr speed limit) but that's still an if and I'm not sure it would have ensure the survivability of the jaywalker OR safety of the people in the vehicle at that speed.
The other option is swerving which might have been a possible solution here as well, but that would also have been highly dangerous for the people in the car as well at those speeds, within that timeframe, possibly causing >1 fatality or serious injury.
Regardless I'm very much speculating here regarding reaction times based on watching a low quality video, I'm really looking forward to expert analysis here rather than speculation on the capabilities of LIDAR/Radar + computation speed at 60km/hr... even considering a human driver would have 100% hit this person.
If the vehicle can't detect objects in the non visible spectrum (even just IR) at least as far away as a human can in the visible spectrum then that is a showstopper right there for the technology. Additionally if it can't then it shouldn't be traveling at a speed where it can't react in time.
My question is given it could detect the jaywalking object (regardless of visible light) within the very very short timeframe at those speeds, on what looks like a highway, I'm curious if it's rational to expect even the future ideal machines (say 5yrs from now) to have been able to react in that situation.
It's not as obvious as people here are pretending it is.
Yet even then we now have a previously unknown model to test our machines on to prevent it from happening again. Given a human would 99%+ of the time not have seen this woman in time, then I believe we'll at a very minimum be better off as a society as a result of this... as wrong as that sounds, because it's now a high-priority dataset, not just a sad story in the local news (if even) we'll forget about tomorrow as it would be with a human driver.
> Given a human would 99%+ of the time not have seen this woman in time
I'm far from convinced that a human would not have seen this woman in time.
See all the comments in this thread about how the dashcam footage is much worse than reality, and even one person who drives that road regularly saying it's not that bad visibility-wise.
I think if I had seen that lady slowly walking her bike onto the road in my adjacent lane, I would have slowed down for sure. And from seeing my own nighttime dashcam videos, I think I would have seen her. She's the only object nearby, on a fairly straight road with no adverse weather conditions. I would have seen someone pushing a bike onto the next lane.
Maybe I would have hit her still, but I would have slowed down for sure.
So the speed limit on Mill Avenue, where the crash took place is 35 mph. The uber was traveling at 40 mph. The reason Mill’s speed limit is 35 instead of 45 (like most Arizona’s major roads) is because it’s got much heavier pedestrian traffic than typical.
If an autonomous vehicle cannot detect pedestrians crossing a slower-than-typical road with enough time to at least not kill them, it shouldn’t be on the road. If that means uber can’t drive autonously at night, too bad for them.
To be fair, the law currently is very permissive to drivers, and a human may not have been deemed at fault. Despite going 40 in a 35 zone, when (due to reduced visibility) they actually should have been going 25. You are supposed to go only as fast as you can stop, given current visibility. Regardless of the speed limit.
> I watched the video a bunch of times and I don't see how the vehicle could have slowed down within the 700ms max where she would have been visible to a LIDAR, to make much of a difference.
There's also a steering wheel. (Why is everybody here missing this?!) I could totally see it having moved out of the way.
In order for steering to be a collision avoidance strategy, the system would have to risk the life of the driver. It may be fairly easy to recognise an obstruction on the road, but determining that it's human is much harder. If a plastic bag blowing across the road could kill the driver, or other drivers nearby, that would be a very unpopular solution.
They hit the person with the right side of their car, so even a small move left could have avoided this accident. Given that it was a divided highway with an empty lane to their left, moving half a lane over would have been a reasonable response.
Of course, the Uber vehicle did not take any action at all. It doesn't seem to have ever realized that there was a solid object in front of it. Without that, collision avoidance is impossible.
40mph is actually right at the inflection point where survivability changes dramatically. At 40mph it's about a 50/50 chance of a car crash with a pedestrian causing a fatality. At 35mph the chances of a fatality go down to 1 in 3, at 30mph it goes down to 1 in 5. At a little under 20mph it's 1 in 10.
Okay, I've heard that 40mph plenty of times here when AI cars come up, so is it possible the car could have slowed down 10mph? I only suggested 10km/hr as an ideal maximum (aka 35mph) given better technology, not as a baseline for today...
I've also read that the last speed sign was 45mph before this accident. I used 40mph as it was between the 35mph sign that was coming up before the hit and the 45mph one before it.
Braking time is about 4 seconds from 40 mph (average braking acceleration is a bit under half a gee for ordinary cars), which means every second of braking is a roughly 10 mph reduction in speed.
I think your response time calculations are wildly wrong.
The LIDAR sensor[1] being used here can pick up targets up to 120m away. I'm not sure about the RADAR or vision systems also in place, but even LIDAR alone should have been able to easily pick out the pedestrian with plenty of time to come to a full stop.
This is clearly poorly designed autonomous driving software, not a sensory deficiency.
I watched it again and you might be right, there was likely time for something to happen, given the available reaction speed going 40mph on a highway. I'm curious what that something translates to and what affect it could have had on this situation (ie, swerving, slowing by x mph, etc).
Because you didn't do the math yourself, 40 miles per hour is just shy of 18 meters per second. So 120 meters is almost 6.7 seconds at that constant speed (more if you're slowing down). Start of video to collision is less than 5 seconds.
That should give quite a bit of time to slow down then or at least move slightly out of the way, even given the person may not have been detected exactly within the 5s+ of the video + factoring in computation speed + mechanical response times. Although again this is speculation as I'm not intimately familiar with how the objection detection works and what a bike w/ plastic bags may have looked liked crossing the road, plus what available options were at that speed and given the environment. Thanks.
The braking distance at 80 mph for a modern car is 320 feet (just under 100m) the car should have been able to come to a complete stop if the software had been using the LIDAR correctly.
This isn’t a highway. Mill Avenue is one of Tempe’s most pedestrian-trafficked major roads. And it has a slow 35mph speed limit, and is well lit (much better lit than the dash cam shows), because so many pedestrians cross it.
Usually it is the law that you are only allowed to drive as fast as the conditions allow (e.g. CA's "Basic Speed Law".) That includes being able to see obstacles in your path early enough to be able to do something about them.
If you can't see far enough to be able to avoid something in the road, you're simply going too fast. That should apply to machines, but it already applies to humans.
What are you saying exactly, that a human driver would be at fault here given the video evidence?
I believe it's entirely possible for a robot to solve this problem with proper Radar and maybe LiDAR going forward. But I would be extremely skeptical about anyone claiming a human would have been at fault...
If the statement is that "a human would not have been able to stop in time either", then yes, by the letter of the law, a human would have been at fault.
If you can't see where you're going, you need to slow down. Does that seem so unreasonable?
> So, should an accident occur between a jaywalker and a car---if shown that the driver could have/should have seen the person and could have/should have been able to avoid, then without question the driver can be held responsible.
> To a large degree, it comes down to the driver's ability to avoid the accident. If a jaywalker steps right out into the car's path and is instantly hit, the driver will usually not be held responsible. It will be determined that the pedestrian caused the accident.
> However, if the jaywalker strolls into the street a few hundred yards ahead of the car and the driver does not slow down or swerve, the driver could be held responsible. Even though jaywalking is illegal, drivers are expected to take reasonable action to avoid crashes when they can, even if they feel they have the right of way.
> Negligence also comes into play if the driver should have seen the pedestrian but did not. For instance, a driver who is texting and driving may look away from the road and not see someone step into the street, hitting them with the car. The driver could argue that the road was clear and that the person shouldn't have been there. While that may be true, he or she could still face charges.
I never said "every possible illegal or unexpected obstruction". What I said was "if you drive so fast you can't avoid something blocking your lane by the time you see it, you're going too fast." Your quote, in fact, confirms what I said:
However, if the jaywalker strolls into the street a few hundred yards ahead of the car and the driver does not slow down or swerve, the driver could be held responsible.
This was clearly not a case of "someone stepping out right in front of the car", since they were more than halfway across the rightmost lane, walking a bicycle.
Edit: This rule is merely a variation on the universally accepted one that says that if you rear-end someone in another vehicle, you're almost universally at fault (unless it can be proven that they acted in such a way that the collision was unavoidable.) The logic being that if you could not avoid a collision, you were going too fast for the distance you had to the vehicles in front of you.
Are you suggesting that drivers should be less liable for running into stationary objects than they are for running into other vehicles? That seems absurd to me.
> Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
Seems more likely that it's a software problem. Especially given the rest of Uber's behavior, I wouldn't be surprised if they're aggressively shipping incomplete/buggy software in the name of catching up to more careful competitors like Waymo.
Indeed! To LIDAR, she was basically standing in the lane, with a bulky bicycle. To visible light, including the driver, who was apparently half asleep or watching the dashboard, she was in shadow until just before the collision.
So yes, LIDAR should have caught this. Easily. So something was clearly misconfigured. And even if the driver had been carefully watching the road, he probably wouldn't have seen her in time.
But I wonder, is there a LIDAR view on the dashboard?
Right, so assuming LIDAR caught her: I'd imagine the algorithm presumed that she wouldn't cross the center line till she did cross the line, I don't know what to think the algorithm would do there after?
Presumably the algorithm had a pretty good idea of where the lanes were, and if the LIDAR detected a non moving object in an adjacent lane and decided it was fine to ignore it because it presumed it was not going to start moving, that's a pretty broken algorithm.
I don't have the link handy, but I was reading a webpage yesterday (related but not about this crash) which showed Google's self driving car's "view" of a road scene - it's clearly painted different color boxes and identified pedestrians, bicycles, other cars - along with "fences" where it had determined it'd need to slow or stop based on all those objects.
Either Uber's gear is _way_ less sophisticated (to the point of being too dangerous to use in public), it was faulty (but being used anyway, either because its self test is also faulty, or because the driuver/company ignored fault warnings) - or _perhaps_ Google's marketing material is faked and _everybodies_ self driving tech is inadequate?
It’s that last possibility that’s horrifying above all others. The backlash either way is going to be terrible, but if these cars are just not up to the task at all, and have driven millions of miles on public roads... people will lose their minds. Self-driving tech will be banned for a very long time, public trust will go with it, and I can’t imagine when it would return.
This is going to sound bad, but I hope this is just Uber’s usual criminal incompetence and dishonesty, and not a broader problem with the technology. Of the possible outcomes, that would be the least awful. If it’s just Uber moving fast and killing someone, they’re done (no loss there), but the underlying technology has a future in our lifetimes. If not...
Waymo actively test edge cases like this both in their test environments in the desert and via simulation, they have teams dedicated to coming up with weird edge situations like this (pushed bicycle) where the system does not respond appropriately so that it can be improved. All of these situations are kept and built up into a suite of regression tests. https://www.theatlantic.com/technology/archive/2017/08/insid...
I get your concern, but I would probably reserve the word inadequate. If this is the only situation you have to worry about a self driving care hitting and killing you in, and it's the only know data point at this time, some may consider that much more than adequate.
I really don't bundle Tesla in with Waymo, Lyft, Toyota, Uber that are trying to build ground-up self driving cars. Are Tesla actively testing self-driving cars on public roads yet? Are their included sensors even up to the task? I didn't think they even have LiDAR?
True, but this seems to be a simple case of reacting to a person who steps in front of the car. Automatic braking technology exists on even cars that aren't considered "self-driving".
If this is the only data point then uber self driving cars are about 50 times more dangerous than average human drivers (see numbers quoted repeatedly elsewhere; uber has driven about 2 megamiles; human average is 100 megamiles between fatalities)
If that's your idea of adequate, you'd be safer just vowing to get drunk every time you drive from now on, since a modest BAC increases accident rates, but not by a factor of FIFTY!
A website that "does something weird" when you use a single quote in your password... That _could_ be "the only situation you have to worry about". It is _way_ more often a sign of at least the whole category of SQLi bugs, and likely indicative that the devs are not aware of _any_ of the other categories of errors from the OWASP top 10 lists, and you should soon expect to find XSS, CSRF, insecure deserialisation, and pretty much every other common web security error.
If you had to bet on it - would you bet this incident is more likely to be indicative of a "person pushing a bicycle in the dark" bug, or that there's a whole category of "person with an object is not reliably recognised as a person" or "two recognised objects (bicycle and person) not in an expected place or moving in an expected fashion for either of them - gets ignored" bug?
And how much do you want to bet it's all being categorised by machine learning, so the people who built it cant even tell which kind of bug it is, or how it got it wrong, so they'll just add a few hundred bits of video of "people pushing bikes" data to the training set and a dozen or so of them to the testing set and say "we've fixed it!"
> Either Uber's gear is _way_ less sophisticated (to the point of being too dangerous to use in public)
I think this is a very good possibility considering that autonomous vehicles is the goal of the company and they're racing to get to that point before they run out of investment money. They have a lot of incentive to take short cuts or outright lie about their progress.
Looks like a velodyne 64 based laser. It is virtually impossible for those to not be able to see the the bicycle well in advanced. Uber had a serious issue here. Something like:
1. System was off
2. Point clouds were not being registered correctly (at all!)
3. It was actually in manual mode -- safety driver didn't realize or didnt react fast enough.
4. Planning module failed
4. Worst outcome in my opinion: Point cloud registered correctly, obstacle map generated correctly, system was on, planner spit out a path but the path took them through the bicycle.
The LIDAR data look pretty noisy, especially for distant objects. Could not they filter out the pedestrian thinking it is a bush or something like this?
Anything that is tracking an object moving on the road should be looking at the velocity of the scanned object as well as keeping track of some sort of difference from normal. I would think the car should know it's on a two lane one way road, realized an object was moving in one lane with some sort of velocity towards the path of the vehicle, and that perhaps something was not normal.
From the reports of cars running red lights and then this I would imagine they have an extremely high level of "risk" (what it takes for the car to take actions in order to avoid something/stop) that is acceptable.
What would be far worse than a hardware or sensor failure would be to learn that Uber is instead teaching its cabs to fly through the streets with abandon. Instead of having cars that drive like a nice, thoughtful citizen we'll have a bunch of vehicles zooming through the streets like a pissed of cabby in Russia.
Not "center line", because this is a divided highway. So she had to cross two lanes from the median, in order to step in front of the Uber. "Human-sized object in the roadway" should have been enough to trigger braking, even if the trajectory wasn't clear.
> who was apparently half asleep or watching the dashboard
It is possible that a screen provided a clearer (somehow enhanced) view of the road, so I'm reserving judgment for now.
Of course using that screen could be a grave error if the screen relied on sensors that missed the victim. But if it appeared to be better than looking out of the windshield then that points to a process problem and not necessarily a safety driver inattention one.
He startles just before the collision, so anything he was watching on the dashboard arguably showed no more than the video that was released. But maybe the video camera had poor sensitivity at low light, and the driver could have seen her sooner, looking out of the windshield.
I'm not so sure that's just before the collision. The driver claimed that he didn't notice the pedestrian until he heard/felt the collision and it's not like the car hit a large object. I'm not convinced that he startled before the car hit the pedestrian.
"And even if the driver had been carefully watching the road, he probably wouldn't have seen her in time."
I don't know about that.
1. Count the lane markers. (It looks like a astute driver could have stopped? Plus, most drivers might have picked up the reflection a bike gives off when head lights are flashed on it? Just a flash of light bounced off metal, or reflectors is enough to get my attention. There are times at night where I just notice a slight reflection in the peripheral of my vision, and I know to precede with caution, or slam on the brakes. It's usually an animal darting across the street. I don't think I've ever had to slam on the brakes for a bike.)
2. The woman looked at the car while it plowed onto her. She had a look of astonishment? Like why is this car running into me?
How would this have helped at 40MPH? The user would have milliseconds to react and hit the brakes. The point is that the car is self-driving. If a user has to watch a video display and intervene for every edge case it's more dangerous than just driving yourself.
From the released video, if LIDAR was including the entire roadway (all three lanes) there would apparently have been at least four seconds warning.
In production, having a LIDAR display would be pointless. But for testing, it might be useful. But maybe better would be to tell drivers to keep their eyes on the road.
Probably the LIDAR did catch it. Probably the algorithm (neural network) that takes in LIDAR data and outputs whether there is a object in front failed or gave a really low probability which was less than the threshold specified. This happens all the time with deep neural networks.
In any case technology is to blame and self driving should be banned until these issues are resolved.
Maybe we just don’t have the tech yet to make it work. At the very least, Uber surely doesn’t. There’s no way the car didn’t see her, but it didn’t react, which means it failed to recognize what it was seeing.
> It's clear from the video that a human driver actually would've had more trouble since the pedestrian showed up in the field of view right before the collision, yet that's in the visible spectrum.
This was taken by a video camera - which has a much lower range of detectable brightness then the human eye. The pitch-black spots in the video are almost certainly not pitch-black if you were to look at them.
This is drummed into students during the motorcycle training syllabus here (Sydney Australia) - "Do not ride beyond your field of view. It you can't see beyond a curve, crest, fog, rainstorm, queue of traffic or whatever - make sure you're going slow enough that you can stop before you get to the end of where you can see".
I always explain it to friends starting out "you need to assume that just around every corner there's a stationary shipping container that's fallen off a truck. If you cant stop in time by the time you see it - it's your fault for going too fast."
Many people don't seem aware that the reduced speeds at curves aren't because your car can't take the curve at that speed (most can) but because you can't tell if there's an obstruction from a sufficient distance.
A car should not ever be driven faster than conditions allow. If the driver cannot see (from rain, snow, darkness, etc.), then they need to slow down. To do otherwise is putting people on the roads at sever risk of injury or death.
a) there are people on the roads inside those metal boxes on wheels, y'know.
b) "shouldn't be there" is not a bianco cheque for "run them over", at least in the civilized world
" ... since the pedestrian showed up in the field of view right before the collision"
Either the woman had just said the words "Beam me down Scotty" and materialised there like the video feed footage implied - or she'd been in view for quite some time - at least enough time for a person pushing a bicycle to cross en entire lane. If Uber's tech is only capable of detecting her as she "showed up in the field of view right before the collision" - their tech is not fit for purpose and should he held 100% at fault here. (Not that doing that will help her family or friends, but it might help stop Uber and their competitiors from doing it again...)
In pitch darkness, IR cameras can only see more than a visual light camera if you somehow had IR headlights that were more powerful than the visual headlights (they probably don't; that would blind other AVs just like high beams blind other drivers). It doesn't grant you the ability to see in the dark with infinite range. Lidar can sense shapes with more range, but at the cost of dramatically worse resolution and latency. It's conceivable the radar/lidar sensor caught the person in the left lane with a bike and decided that was a reasonable place for a person with a bike to be, then lost track of the person while she walked into the right lane (where the visual/IR system could not see her yet).
It's also entirely possible there was an egregious bug. This video doesn't really tell us much.
We see a nIR video of the driver. Those weird eyes everyone seems to have are the tell-tale sign of nIR as it interacts with the retina. So, we know that nIR sensors are being used in the interior, at least.
That said, Arizona in the summer is going to play havoc with lIR and thermography in erms of false positives and negatives. The sensor suite probably should be using lIR at night for this reason and the switching it off in the day. But given Uber's history, the lack of lIR reeks of cost-cutting.
I'm not an expert in IR or computer vision by any means, so take this with a grain of salt.
Air has such a low thermal mass that it doesn't measurably affect most IR sensors. Hot pavement could be a potential issue, but that shouldn't have a major effect on forward-facing sensors.
Besides, it's only March. Even Arizona isn't that hot yet.
A garden-variety uncooled LWIR camera from FLIR can see a difference of 0.05 degree. As long as the pedestrian isn’t wearing a thermal blanket from head to toe he/she can be seen.
> In pitch darkness, IR cameras can only see more than a visual light camera if you somehow had IR headlights
Did you ever use a thermal IR camera ? What you're saying only apply to cheap chi-com cheapo"IR" CCD (the ones you find in home security), not the FLIR/military-grade stuff.
The video here is misleading. A human driver has a much wider field of view and better low-light vision than this video renders the situation. That's not to say that this would have been prevented by an attentive driver. But it's also clear that the safety driver was not paying attention, so it's even harder to know.
> It's clear from the video that a human driver actually would've had more trouble since the pedestrian showed up in the field of view right before the collision, yet that's in the visible spectrum.
I'm not sure, pls look that pic https://imgur.com/a/VfBck, you can clearly see there exists at least 10-15 meters b/w them right at the time when she pops up. Now I don't know the speed of the car, but I'd wager, a human driver (if s/he was alert) would have attempted a breaking at that moment.
At 38 MPH, the car would cover that distance in 0.7 seconds. That is on the low end of human reaction times for braking, so an average person might not have time.
It strikes me as extremely disingenuous if this is all Uber gave to the police. They should be making as much raw data as possible available. At the very least it'd let other companies test their AIs against the scenario and see if they would catch sight of and be able to avoid the pedestrian, if not then this is one more data point to train them on so it doesn't happen again.
I hope so, but I'm not certain what sorts of legal precedents could be leveraged here. Uber, for instance, might try and avoid sharing non-visual recording data on the basis that it's proprietary information. IANAL but I'm very curious if companies can be compelled to share proprietary formats and tools for examining those formats or translating them into non-proprietary formats (which... is that even a thing legally speaking?) in a case like this.
For instance, if law enforcement had testimony and other warrant allowing things that indicated that a user had stored some vital secret plan in a password field what could the government compel a company to do, assume the disk it relies on is also encrypted for extra fun time
1. Hand over the physical disk
2. Hand over the disk image
3. Hand over the decrypted disk image
4. Hand over the unobfuscated (enc or hashed) string of interest from the decrypted disk image
5. Compel the company to decrypt the string if it was encrypted with a common algorithm (i.e. AES)
6. Compel the company to decrypt the string if it was encrypted in a proprietary manner (i.e. in-house custom encryption)
7. Compel the company to devote resources (how much?) to brute force a one-way common hashed string (i.e. bcrypt)
8. Compel the company to discover a hash salt assuming the company doesn't store it locally but may be able to procure it from the user to do the above.
9. 7 & 8 if the one-way hashing algorithm is proprietary (and weak) and the company raises objections that the process of breaking this string will reveal key components of how the algorithm works (i.e. the hash is just md5(string) XOR "IMMA SECRET_STRING")
10. 7 & 8 if the proprietary algorithm is not weak but the company raises objections over trade secrets for other reasons.
The legalities are beyond me, but the core principal seems pretty simple: if Uber isn't willing to cooperate fully with the NTSB to make autonomous cars safe drivers, then Uber doesn't get to make autonomous cars. Full stop.
It's pretty clear to me (from the second half of the video) the driver was looking down at her phone and glancing up at the road periodically. IMO if she had been focusing on the road, she would have at least started braking before hitting the pedestrian. Or perhaps actually stopped before that happened.
My more generous interpretation is that they were looking at the computer screen where the car shows its interpretation of the situation, people tend to lift their phone towards their face.
This is only a fig-leaf of a driver (for catching legal flak by sitting in the front left seat), not actually operating the vehicle at all. This part was inevitable, given the unbounded technooptimism.
> Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
It's a bit too early to make that conclusion. For all we know, the equipment was malfunctioning. Which I guess technically leads to your point, but we'll have to wait for the investigation to actually know what failed vs. what met expectations (I worry that expectations and tolerances, as set by the car companies, will be revealed to not be as comfortable as we might assume).
It was also a bit too early for the police to release a statement less than 24 hours after the incident saying that it appears that Uber/the car/observer was not at fault.
Jaywalkers ar at fault in Arizona in the case of an accident so it doesn't seem too early.
On the subject: this lady I used to know hit someone who ran out in front of her and started freaking out (thinking they were in some serious trouble) until the police told her "you're fine, they were jaywalking".
> Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
Because the software is still critically flawed, of course...this only represents a present-day failing, not some sort of permanent obstacle for the future.
In addition to that, even if we were limited to the "last moment", there was about half a second or a second time to react. Correct me if I'm wrong, but that should be enough for the car to at least try something.
Isn't the car supposed to brake to minimise the collision, if the swerving is too dangerous (and it wasn't in this case, as the road wasn't too busy)?
How did LIDAR and IR (?) not catch that? That seems like a pretty serious problem.
Something is badly wrong there. That should have been detected by LIDAR, radar, and vision. Yes, they need a wide dynamic range camera for night driving, but such things exist.[1][2] They're available as low-end dashcams; it's not expensive military night vision technology.
Radar should pick up a bicycle at that range. The old Eaton VORAD from about 2000 couldn't, but there's been progress since then.
LIDAR has its limitations; some materials, including the charcoal black fabric used on some desk chairs, are almost nonreflective to LIDAR. But blue jeans, red bike, bare head? Expect solid returns from all of those.
The video shows no indication of braking in advance of the collision. That's very bad. There simply is no excuse for this situation not being handled. The NTSB is looking into this, and they should. I hope the NTSB is able to pry detailed technical data out of Uber and explain exactly what happened. In the first Tesla fatal crash, they didn't get deeply into the software and hardware, because it was clear that the system was behaving as designed, unable to detect a solid tractor trailer crossing in front of the Tesla. The result of that investigation was that Tesla had to get serious about detecting driver inattention, like all the other carmakers with lane keeping and autobrake do.
This time it's a level 4 vehicle, which is supposed to be able to detect any road hazard.
The NTSB has the job of figuring out what went wrong, in detail, the way they do for air crashes.
LIDAR also has limitations on angular resolution just as a function of how the sensor works. It's entirely possible that the size of the person/bike on LIDAR was just too small until it was too late to stop.
Why it didn't even appear to try to stop? You got me, refresh rate on the LIDAR? LIDAR flat out being mounted to high and relying on optical sensors instead for collision avoidance of small targets (like a human head)?
I'm guessing, I'd love to see an NTSB report on this.
Why even bother having a LIDAR system on your self driving car if it doesn't have sufficient resolution to detect a person standing right in front of it?
This doesn't seem like an edge case at all. Pedestrian crossing the road at a normal walking pace, and no obstructions in the way which would block the car's vision. The fact that it's dark out should be irrelevant to every sensor on that car other than the cameras.
Something obviously went terribly wrong here; either with the sensors themselves or the software. Probably both.
For detecting larger obstacles like buildings or other vehicles would be my guess.
Realistically faster sensors should be used to detect obstacles. LIDARs I could find with some cursory googling can run up to 15hz. Computer vision systems can run much faster (I have a little JeVois camera that'll do eyeball tracking at 120hz onboard, I assume something that costs more can do better).
But more importantly, you're vastly trivializing the problem - Standing right in front of it, sure the LIDAR will see the person no problem. Standing 110 feet away (which would be min stopping distance at that speed)? Realizing that, for a LIDAR with a 400' range at 15hz moving at 40mph you get ~7 samples of a point before you're at it... For at least the first 3 frames that person is going to look like sensor noise. At 110 feet that person (which I'm calling a 2' wide target) is 1 degree of your sensor measurement.
It's not that it's useless or broken, more just this a seriously bad case where optical tracking couldn't work and where LIDAR is particularly ineffective at seeing the person because of how it works. More effective might be dedicated time of flight sensors in the front bumpers, unsure how long a range those can get, but they are also relatively "slow" sensors.
It’s not mutually exclusive either. You can have lower frequency, lower angular res 360 spinning LIDAR for low granularity general perception, and also have much higher frequency, brighter, and lower FOV (~90-120deg) solid state lidar mounted at the very least on the front corners of the car. We should be absolutely littering these vehicles with sensors, there’s no reason to be conservative at this stage.
> LIDAR also has limitations on angular resolution just as a function of how the sensor works. It's entirely possible that the size of the person/bike on LIDAR was just too small until it was too late to stop.
I highly doubt this is the issue. I am not sure what Ubers setup is, but even a standard velodyne should have been able to pick that up based on angular resolution.
> Realizing that, for a LIDAR with a 400' range at 15hz moving at 40mph you get ~7 samples of a point before you're at it... For at least the first 3 frames that person is going to look like sensor noise. At 110 feet that person (which I'm calling a 2' wide target) is 1 degree of your sensor measurement.
This is based on the velodyne LIDAR specs I could find last night with some quick googling:
- 400' range
- .04 degree angular resolution
- 15hz max update rate
If you have more accurate real world experience with these sensors and can share more accurate performance characteristics I can update.
These calculations were done assuming a vehicle moving at 40 mph. The stopping distance at that speed is about 110ft. I computed the pixel size by assuming 1 measurement = 1 pixel giving me 9000 pixels per 360 degrees.
Thats the one LIDAR Uber seems to have matching pictures.
5Hz - 20Hz full round sampling rate, lets assume 15 Hz.
The resolution in the horizontal plane is dependent on rotational speed, so at 15 Hz it should be 0,26 degrees.
(0,35/20*15 = 0.26)
For the woman height the angular resolution is 0.4 degrees no matter the rotation speed.
Id est, she would have been atleast one pixel wide from 400 feet and about 2 pixels high and growing in size if we assume 2' wide.
(Not counting bike).
I really see no exuse for Uber messing this up that bad. The LIDAR can't have missed a potential "obstacle" when it got closer, even if the car wouldn't classify it as a human.
I was using Rev E because it's the data sheet I had handy. Mostly I was trying to point out that LIDAR is not some magic thing that always sees everything and there's limitations.
There's with your .26 angular resolution @ 15hz. (I just have a spreadsheet that spits all these out for me.)
These are NOT big targets, they could easily have been mistaken for noise and filtered out. All of the LIDAR data I've ever seen has been fairly noisy and did require filtering to get usable information from it. And given the number of frames they get maybe their filtering was just too aggressive.
Yes, I agree with you that we can't assume that the car could have noticed the woman from 120 meters from LIDAR data alone. Maybe with some kind of sensor fusion with IR-cameras.
But, as it got closer and what the computer though was noise was on about the same place a sane obstacle finder should have given a posetive match. Maybe at 30 - 40 m worst case?
At 142 feet the woman probably had (assuming she was 5.5'):
asind(5.5/142) = 2.21* => 2.21/0.4 = 5.5
So between 5 and 6 "scanlines" going from left to right over her.
Assuming she was 2' wide that's 0.8 degrees which would be 2 to 3 pixels in breadth according to your spread sheet.
That's between 10 and 18 pixels (voxels?) that stand out clearly from the flat road around it, exluding the bike.
If you wan't to get an idea of how LIDAR data looks Velodyne has free samples and a viewer for less resolution models.
It pretty hard to identify obstacles far off, but you will still see there is something there. It's especially easy to identify obstacles that are vertical.
As she got closer, she would eventually show up clearly on the LIDAR data. But since the car never slowed down or went left, it didn't notice her at all even at point blanc (or did see her but failed to do anything about it).
A buddy of mine has a lower end LIDAR on a robot, working with them on SLAM on it, trying to get a similar hardware set up locally over the summer. (I have weird hobbies)
Yeah, I'm willing to accept SOMETHING bad happened here, as I said I really just wanna dissuade people from the notion that LIDARs will see all obstacles all of the time. Not going to say the car acted perfectly and it was sensor failure, but definitely willing to say that the LIDAR probably COULD see her but not as well as people would assume.
Really, I think this was a case of the car over driving their effective sensor range, same as what happens when you're on a dark road and a deer runs into the middle of the road, you simply can't react fast enough by the time you realize the danger is there. Computers are fast but they aren't perfect.
What I'd be particularly interested in was if the computer saw her and if it did the calculation - I can't stop safely in this distance, and decided to just hit the obstacle because it was "safer". At that point we start getting into ethics and this problem gets a lot murkier.
The person in that last picture is something like 5 feet from the car which is far to close to be useful at 40MPH. At those speeds what's important is what it sees at 150 and 200 feet and how fast it can refresh.
When your resolution is low enough to not see this they stop calling it LIDAR and start calling it a rangefinder. If this was actually a fundamental limitation of the sensor then that's the crappiest LIDAR unit I've ever heard of. When I first heard about the accident my initial reaction was "this is why vision only systems are inadequate". The fact that it didn't even detect the object at all before it collided with it with lidar, radar, and vision is inexcusable. This could set fully autonomous cars back enough that forget the cost of one life, this delay could kill tens of thousands because of a preventable accident.
Probably the only explanation was that LIDAR was off, either on purpose (for testing?) or because it broke and there was no safety mechanism to prevent the car from operating if/when LIDAR is off.
I am glad to hear the NTSB is investigating this and not just the local police (who would lack the technical resources to make a useful judgement). Have there been any statements at all from them so far?
The NTSB tends to not make even initial statements until upwards of a several weeks in, and final statements as much as 6 months to a year later. They're nothing if not thorough.
I don't understand why everyone in this thread is so focused on the sensors alone. The sensors might detect anything they like, but they're not going to stop the car on their own. The car has logic that tells it how to react to what its sensors perceive- that's the AI part. If the car's AI can't identify a woman pushing a bike as a woman pushing a bike, or it doesn't know that it has to stop before hitting her- well, then it won't.
There's so much confusion here, about the capabilities of these systems. People think that a combination of better sensory perception + faster reaction times suffices to drive in the chaos of the real world. That's not so. Sensors and fast thinking won't get you nothing if you can't think right. You have to be able to know what the things are that your sensors detect, and how to react to them.
It's perfectly possible that the Uber' car's LIDAR detected the lady crossing the road- but the AI just didn't know what to do about her and simply did nothing.
Arizona and Tempe especially have lots of darker roads. The LIDAR/computer vision tuning at night doesn't seem right. Maybe it was adjusting for the changing street light brightness but yes this is one situation and the vehicle had just come from the Mill bridge that has festive lights that are strung along the bridge [1].
This is a situation though where the LIDAR should have clearly been better than it was. Maybe it was in a strange state after having seen all the lights and then complete darkness, looks like they were headed north on Mill Ave over the bridge [2] just past the 202 where it is indeed very dark at night and probably the spot right here [3] which matches up with the building in the background, the other way is South and is busy/urban by ASU. They had just crossed a lit up bridge, then dark underpass, then into this area [3]. The area that it happened in [3] does have bike lanes, sidewalks and a crossing sidewalk close by [4] but is by a turn out so not a legal crossing however there are lots of trails through there.
This video is worse than expected by far and may be forever harmful to the Uber brand in terms of software.
In AZ I usually see the self-driving cars out in the day, maybe there is lots of night tuning/work to do yet.
I've been staring at those myself for a couple of hours. My best guess is the crosswalk was moved, but the paths were left. There's a lake nearby and tons of parking under the overpasses, with trails and picnic areas.
Also, the woman was right under a working street lamp. And as was stated in an earlier article the car continued on at 38 mph after the accident. The bike ended up 50 yards down the street.
EDIT: "That spot is east of the second, western-side Mill Avenue bridge that is restricted to southbound traffic, and east of the Marquee Theatre and a parking lot for the Tempe Town Lake. It can be a popular area for pedestrians, especially concertgoers, joggers, and lake visitors. Mid-street crossing is common there, and a walkway in the median between the two one-way roads across the two bridges probably encourages the practice."
"Pedestrians can cross a street without using a crosswalk in many instances without risking a jaywalking ticket, but Arizona law requires pedestrians not using a crosswalk to yield to traffic in the road."
Lots of parks around and trails that do go across the road, it is an odd area.
If you zoom out on google maps you will see some of the trails. Note the sidewalk/pathway, it is no pedestrian but has paths for them so it sends mixed signals.
There's a saying "a sign is not a wall." You can make dangerous things illegal all you want (such as "not overdriving your headlights," hint hint), but it won't stop people doing that. "But that person was not supposed to be there" is a rather weak excuse for manslaughter.
It seems like this perspective may come from the idea that processing camera input is a formality. But the best estimates of the practical computing power of the brain are based on its visual processing capacity, because we know that's a hard problem. CAPTCHAs all depend on humans' ability to process images semantically faster than a computer (spambot). While it probably isn't unsolvable, I don't think it's surprising that this is consistently a challenge.
You can get 320x240 60hz for $2000 as a consumer[1]. On the one hand I wonder what kind of resolution the military grade version is, but I also wonder if the bandwidth/dollar is actually better. I imagine Raytheon basically just makes up a number when they're setting the price of a helicopter gun cam.
No. ITAR controlled, in the context of IR imaging, means that you can't export any thermal imaging systems above 9fps. You can use whatever you want inside the US, and 60fps systems are available for consumers today.
The lady can be seen fairly clearly (even in this poor quality video) at 0.03 and impact occurs at 0.04. That's 1s, which means a distance of approx 17m. If the guy was watching (sort of the point of him being there really) he could have slowed the car significantly and probably even stopped it. These are test vehicles being treated like prod vehicles. They should probably not be on streets with pedestrians quite so soon.
You're massively underestimating human response time to visual cues and also the distance needed to stop a vehicle traveling at 35-40mph. It takes a full quarter of a second to respond to a visual stimulus on average, and more than that to also move your foot and depress a brake pedal. By that time the car was less than 50 feet from the pedestrian. At 40mph braking distance is about 80 feet in good conditions. There is absolutely no way a human driver could have avoided this accident assuming the same visual distance and dynamic range as the camera. Best case, the car may have slowed down a bit before impact.
Human would have had significantly longer than this video. It's not that dark there at night. (Not as dark as the camera would lead you to believe). Swerving distance to avoid death is well within possibility. Aside from that, the possibility of death was further exacerbated by the vehicle not reacting to impact.
You absolutely don’t need to brake in this situation, there are 5 lanes, you release the gas to give the pedestrian more time to finish crossing and if it’s a bit short you go to the next lane over, aiming behind the pedestrian. That’s what everybody was doing in France, now that I am in Arizona the drivers are just murderous towards pedestrians, they don’t release the gas or move to aim behind them, like it’s perfectly ok to kill someone. (Don’t get me started on right on red and exiting from a drive in, I think I will get killed on a sidewalk here)
Swerving is almost always the wrong thing to do from a safety perspective. This situation is identical to a deer in the road at night, a situation in which most traffic safety experts advise hitting the horn and brakes, but not swerving (note that human drivers hit over a million deer in the US every year, despite supposedly being alert and able to see better than cameras at night). You don't have time for a mirror check to see if there's a car next to you, the shoulder might not be safe, and swerving at speed is an excellent way to lose control of your vehicle entirely. There's also a bike perpendicular to the lane, so you would have to swerve way more than just enough to get around a person.
For a deer, swerving is the wrong thing to do, because a deer's life does not matter, so it's worth it to hit the deer.
With a person, though, you are seeking to protect everyone, so the tradeoff swaps in favor of swerving, because the person in the car next to you is far more likely to survive a collision.
No. 1 second isn't enough. From the time you see something till you start moving your muscle is at least 250ms, and that's a very good reaction time, it's much slower for most people. When it comes to breaking, your foot is not on the break, so you have to move it there, and push it. Then the car will start slowing down.
Download one of those reaction time apps for your smartphone, see how well you do when you actually expect something to happen.
I agree thats a textbook case for the non-visual-specrum sensors. Its possible that lidar DID catch it, but the avoidance logic decided to continue forward. For example if it decided a collision was immpossible to avoid, swerving might make things worse. Also its possible the logic thought the timing was such that the bike would pass after the car crossed where the bike was going, so slowing down would actually cause a collision.
How is it in America? Over here (North Europe), one may not use high beams when there is street lighting (even though in this case the lighting seemed not very good).
Im conviced 99-100% that the Automatic Emergency Brakeing (AEB) on my Tesla would have braked for that. The promise of these systems, as you also point out, is that they can see things, humans cant. The "real" cameras on this car (not this dashcam footage), and the LIDAR, should be fine with it beeing near pitch black.
Regarding how the LIDAR did not catch that, there are 4 possibilities I can think of:
1. A software bug failed to recognize the obstacles, or misclassified them, or it fell below some probability threshold.
2. LIDAR didn’t work at the time, and the car did not shutdown.
3. The victim‘s clothing absorbs the LIDAR‘s wavelength pretty much completely, such that it appeared as a „black hole“ and was ignored by the algorithm since this occurs commonly. Unlikely though since the bike itself would surely have registered?
4. It’s hard to see on the video, but is the car going up a slope? In that case, if the LIDAR didn‘t look up far enough, it could have failed to see the victim for optical reasons.
Another option (related to your #1) could be disagreement between the visual field cameras and the LIDAR. Which could result in a lower confidence of an object being a pedestrian.
>> Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
A human is not an "obstruction", dammit. I mean, literally- it's not like hitting a wall. The driver's life will never be in danger and the care may not even be significantly damaged. There's a very special reason why we want self-driving cars to avoid humans, that has nothing to do with the reason we want to avoid obstacles. And because this special reason is very, very special indeed, we need much better guarantees that self-driving vehicle AI is extremely good at avoiding collisions with humans, than we do for anything else.
I'd like to see an Uber SDV drive on Waymo's test tracks (where they have the employees pop all the shit at it). And just see what it does. I'm guessing it will be ridiculous and nightmarish.
The lady was walking the bike at the edge of a light cone.
The inner cam was actually filming in IR.
Uber cars have IR cameras, LIDAR and an also multiple radar sensors.
My guess is that the algorithms have never met a person crossing the street with a bicycle during night time so they just ignored it or considered it to be a glitch.
You can have to approaches regarding labeling driving situations. Either you label with positive tags the situations where the car needs to react. Or you label with positive tags the normal situations when the car does nothing.
Depending on the two approaches you can have a car that kills pedestrians that appear in weird circumstances. I also bet a pedestrian that ducks in the middle of a lane would 100% be killed by a car. Or two people having sex while standing in the middle of a lane.
The other situation you have cars avoiding invisible obstacles that may appear due to some aberrations from sensors (which are far from perfect).
Which is exactly the reason this is nowhere near production: "kinda works, sort of, in trivial cases" is not quite the SDV promise I keep hearing: "my car will also go reasonably straight when I let go of the wheel on a wide, straight stretch of the road, and won't even run over anyone if there is nobody on the road. Therefore, autonomous driving!"
The pedestrian is a lot more obvious to the eye than I suspected, and it's actually quite shocking. They are correct to stop all road tests until they have investigated why they are missing this.
> It's clear from the video that a human driver actually would've had more trouble since the pedestrian showed up in the field of view right before the collision, yet that's in the visible spectrum.
Actually a human driver would be expected to have less visual trouble in this case. People's eyes are far more adaptable to low light conditions than a camera's video. If you've ever tried to take a picture on a visible night using your phone, you've seen this effect.
> When I argue for automated driving (as a casual observer), I tell people about exactly this sort of stuff (a computer can look in 20 places at the same time, a human can't. a computer can see in the dark, a human can't).
Except that the computer did not do that in this case. This car also uses LIDAR and should have noticed the pedestrian long before the accident occurred.
> Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
Either the sensor equipment or the software was defective, otherwise the pedestrian would have been detected.
Speculating: IR interference might have jammed this vehicle's LIDAR for an instant as it sampled the vicinity of the hazard. Any power in the passband of the detector might have been sufficient to saturate it and make it less sensitive to the returning LIDAR signal. This could come from another LIDAR unit in the vicinity. Other possible jammers might include IR laser pointers, TV remotes, or IR camera illuminators.
I don't work on self driving cars or even vision, but I have heard when you are on a highway you start with filtering out small stationary reflections, since they are almost certainly not cars. (Which is maybe why the tesla didn't see the big red firetruck - it was not visible). It's not a big leap to imagine that Uber's LIDAR ignored the bike because it was not recognized as a person, was moving perpendicularly at a low speed, so got pre-filtered as a puddle. We can only guess and Uber will report whatever they want.
Imo this is a clear attempt to shift public opinion. Also for everybody it should be clear, that a car should only drive as fast to be able to break once something comes into sight.
For the whole industry it is very unfortunate, that some just don't understand the responsibility that comes with new technology and it's limitations.
This seems like a simple case. I would have expected the driver assist in my 2017 Subaru to have reacted to something in the road. I'm surprised that the much more sophisticated self driving system did not.
I love our 2017 Outback w/ EyeSight. Luckily, we haven't had to test the auto braking system at high speeds but the lane assist and assisted cruise control are wonderful.
Not a suburu but my passat engaged emergency breaking once. It's was kinda spooky to go for the break and realize its already depressed. Definitely prevented an accident. I was paying attention too, but someone jumped into my lane and slammed their breaks on for who knows why, there wasn't anything in the road...
In some areas that maneuver is a strategy to collect an insurance payout. If the car had many passengers (who would all get soft tissue injuries) this might have been a "swoop and squat."
> someone jumped into my lane and slammed their breaks on for who knows why
Insurance fraud, possibly. Depending on jurisdiction if you rear-end someone you could automatically be 100% at fault (assuming the fraud is not discovered/proven)
Absolutely love my Outback + Eyesight. That said, the lane assist and automatic cruise control are not very sophisticated.
The automatic cruise control is great for freeway and some street driving, but don't expect it to brake very smoothly / like a human. I consider it outsourcing part of my concentration.
Lane assist is nice, but it won't auto-center -- if you were take your hands off the wheel on a straightaway it would "ping-pong" back and forth. I mostly like it on long drives, reduces the amount of effort on bends.
2017 Legacy with "Eye Sight." I have had one or two situations where the car emergency braked on my behalf. It happens when the car in front of me turns off the road and is nearly clear. I don't brake because I know that the car will clear the roadway before I get there but the system doesn't see it that way and brakes. I anticipate that now and avoid anything close enough to cause braking so I don't wind up the front end of a rear end collision.
The other thing this system does is to provide adaptive cruise control. If I'm behind a vehicle that results in slowing down and then switch lanes (to where there is another vehicle in front of me) the car seems to think it can resume speed and slip between the two vehicles. I've come to expect that too and disengage the speed control before switching lanes.
It also provides a warning when approaching the lane markings (unless I have indicated a lane change.) Occasionally it triggers on seams in the pavement. It also provides steering input if the land deviation increases. I've only experienced when I tested it in purpose. I'm not sure it would reliably keep the vehicle in the lane.
Overall the system seems to be pretty good and though not perfect, is a net asset.
That sounds awful. Driving is hard enough when you have to second-guess what other drivers and pedestrians are going to do. Why add to that by having to second-guess what your own car is going to do?
I've got to side with the people who want no auto-driving until we have always-better-than-human auto-driving. When cars only have back seats, and no driver controls beyond a way to state your destination, auto-driving will be acceptable.
I wonder if this was affected by the fact that the pedestrian was in another lane up until the very last second. Perhaps the car detected the pedestrian but failed to consider it an obstacle since it wasn't in its direct path. It could be unexpectedly difficult to account for pedestrian crossing speed if it caused automated cars to stop when a car in the next lane happened to "wobble" towards the automated car's lane.
This is the exact thing I've been thinking all the time: Something's not totally right here: Let's at least slow down to better assess the situation. Everything works better in slo-mo. My human brain would then have much better time to evaluate the scene. This would definitely also hold for the sensors and processing systems for an autonomous vehicle.
And even if it doesn't, and the system still concludes it's noise/an obstacle that isn't going to move etc., a low-speed collision is preferable to a high-speed one. Unless you can be completely confident you aren't going to hit something, slowing down is not a bad default action.
Even if you imagine it thought it was another vehicle stopped in the other lane of traffic, the SDV should have slowed. There's no way you should assume a stopped vehicle isn't hiding another danger and blowing through while speeding is what stupid humans do and what SDVs shouldn't.
I dunno, if it decided to ignore the pedestrian because she was in the other lane that's extremely troubling. The pedestrian was moving laterally across the road. If the car has detected that, it should infer that she might become an obstacle very shortly.
Driving is all about predicting the future. Think of every time you've been able to tell that someone is going to change lanes even though their blinker is off, or slowed down when a ball bounces into the street because you know there's going to be a kid following it. If the car isn't capable of that, it's not ready for public streets.
When combined with her walking a bicycle, I suspect this is an edge case they never tested. It may have tripped up their pedestrian detection or path prediction (or both) if they got inconsistent hits on the bike.
There in lies what might be core to the issue though. "An edge case we hadn't tested" Perhaps how we DO AI right now just isn't quite ready for situations this complex yet? Maybe AI based on "oh I've experienced something like this before" is not quite enough? Are we able to do better in getting a system that can infer what's about to happen and make decisions without experiencing it directly... or even indirectly? I know some AI systems are able to do this now with limited cases... but it does make me still wonder if 0.05% of the time the complexity of this task is still just a little outside the capabilities of our learning systems. And maybe we only see the results when something bad happens in that tiny window of time when the AI is unsure.
I am obviously no AI expert, just what I know from loosely following the field. But things like this cross my mind from time to time.
What's most troubling is it doesn't even matter if the uber car thought the slow object in the other lane was a pedestrian, a car, a tree, whatever. Even if it thought the object was say, the most "normal" thing it could be, another car, this would still be a special situation requiring action. Without knowing the objects classification the estimated speed is enough to decide. Why would a car be stopped in the middle of a lane on a fast road? It should be treated as an obstacle that could grow to the side. After all it could be a police, tow, construction, or disabled vehicle, and a cop or tow worker might be about to walk to the side.
Actually many states now require by law that you get as far as possible from a lane with a disabled vehicle, as many human accidents have happened.
I am convinced uber has been basically pretending to do the mountains of careful and sophisticated crap waymo actually has gone to great lengths to do, and is just racing to put anything out so they can keep stringing investors along as far as they can before the jig is up. Well the jig is up now.
I think target fixation also contributes to accidents involving emergency vehicles on the shoulder.
Back to Uber, the number I hear is that they are striving to go better than 13 miles/intervention to prevent an incident. For Waymo this is over 5000 miles. I'm convinced too.
If the car cannot predict "there's something in the next lane, could be in mine the next moment, better slow down just a bit", it has absolutely NO BUSINESS AT ALL driving around on public roads. At each and every occasion that I drove in a city, I have needed to take at least one such minor evasive maneuver due to someone suddenly getting into my lane, be it a car, a bike or a pedestrian. This is not even driving 101; if the car is unable to handle that, it is quite literally unfit for the road.
I can't count the number of commercials I've seen for Fords and Nissans and Subarus and every kind of modern car that has this exact feature, and this is exactly how the advertising plays out. Someone sprints in front of the car, the car stops automatically, everyone is safe, pedestrian continues with their life. I've never used it in real life, but I assume it works how the ads show it.
If Uber can't match a $25,000 off-the-shelf floor model mass-market midsized sedan for collision avoidance, it's hardly a self-driving car.
The system in my car does this but only under a certain speed, much lower than what the vehicle in this video appears to be doing. It's intended for stop-and-go city driving or to avoid hitting a kid that sprints out of a driveway in a slow residential area, not to slam on the brakes to avoid hitting a deer or person at 40mph.
You would think that a reasonable project plan would attack the human safety/emergency situations first, and then move on to anything else. I guess having a car that avoids accidents but doesn't drive across the country on its own does not make for interesting headlines. This is the consequence of headlines-driven AI... "lets solve something hokey and grabs attention so management will be pleased instead of doing the more meaningful/long term r&d."
On the one hand, the cyclist became visible in the footage at a very late stage. If that is how the drivers eye saw it they would have very little time to react, however they may have been able to do a sharp swerve.
On the other, the operator was clearly distracted regardless of if they would have been able to avoid this.
If they didn't want drivers looking at those displays, why would they put them there? Either looking at those displays is part of the job, or the display should automatically turn off. I'm guessing it's the former.
"however they may have been able to do a sharp swerve."
As someone that enjoys racing cars and other types of high performance driving I feel like I can pretty confidently say this isn't even remotely a realistic statement.
You're grossly overestimating human response times. Even if we're ignoring response time and imagining the driver instantly turning the steering wheel, large SUVs like the XC90 simply can't generate the lateral acceleration required to move the vehicle clear of the pedestrian in the time and space shown in that video.
But as many people have pointed out, what the camera captured is not what the human eye would have seen. The eye has much better dynamic range; an alert driver would have had more time than what we can see on the video.
If there is something that isn't going to help the public perception of autonomous cars at all, it's releasing a compressed to shit capture of another video showing a single camera angle from dozens.
I would say it's a deliberate attempt to manipulate if I didn't also strongly believe ignorance on part of the police department has lead them to believe that autonomous cars could even exit a parking lot without data from many more than this one camera, not to mention the vastly more useful LIDAR on top.
(That's before you consider the video angles shown here are just for dashcam purposes. The real cameras for the autonomous driving are in the sensor array on top of the roof)
Yeah. Does the Uber car really capture video at 480p and 15fps? Also only releasing the video conveniently ignores the fact that these cars have IR and LIDAR. The pedestrian is hard to see in this video essentially because it is dark and they are wearing dark clothing. Neither of these are at all obstacles to LIDAR and IR, and the video at least shows us that the road is clear of obstructions.
>Does the Uber car really capture video at 480p and 15fps?
Probably not, but it isn't like the inputs to the self-driving models really need to be better than that. Lower resolution helps your processing time a lot and there's little point in having an FPS higher than your processing time.
I'm sure at least the collision avoidance part of the system would need to poll at a much higher rate than 15fps. That's up to 67ms latency you're adding. With enough miles that delay could kill people.
Average human reaction speed is around 215ms. Not an apples-to-apples comparison because humans can react much faster to continuous situations (humans have a timing accuracy of around 9.5ms) while a machine-learning model is limited to only reacting once per frame, but still.
If you wan't to compare against human "sample rate", it'd be equivalent to at least ~200 FPS (in order to get the same accuracy with a camera). Sure, the signal takes a moment to plumb its way through, but that's irrelevant to spotting objects.
If they're actually feeding data at 15 FPS into their ML model, then what the fuck were they expecting? Correlating movements at those framerates would be nigh-impossible.
Relying on ML for this is already comically irresponsible, but that'd just be ridiculous.
I think they're pulling it from noticeable monitor FPS rates. I'm not an expert on machine vision, so I couldn't tell you the FPS needed to correlate movements between frames.
My ass, mostly. I'm extrapolating based on monitor framerates and how accurately we can see the velocity of fast-moving objects, and that I can spot a timing difference of ~5ms reliably.
Human eyes are almost comparable in terms of a framerate based on the neuron spiking rates, which are somewhere over 250-500Hz max. Obviously that's not directly comparable though, but it gives an idea of how well we can deal with moving objects.
Average human reaction speed when driving, from the time the dangerous situation happens to the time of first reaction, is usually considered to be in the 700-2000 ms range. The lower bound is with optimal lighting and after something has alerted the driver in advance (e.g. a police car dashing past you a moment before), and the first reaction is not "the brakes are slammed" but "the foot is lifted from the accelerator". Hitting the brakes can take another 100-200 ms.
Given there are no obstructions in the road, LIDAR (or even the decent cameras from the sensor array on top) would obviously show her on a clear collision path many seconds before impact.
So I guess this is the ultimate litmus test if the culture at Uber has changed. They let this video stand and I don't personally think they should be allowed to drive another metre autonomously on public roads.
This is Uber we're talking about. They ran a red light while self-driving, shrugged it off and kept going. They had a team whose job was to avoid regulation by blacklisting the credit cards of police. I would be shocked if Uber does anything other than the bare minimum of apologising.
I think releasing much higher quality and higher dynamic range and multi-spectrum video is going to be a LOT more damming of driverless car tech. Just look at all the commentators here saying they would have not been able to stop in time based on this terrible camera footage (ignoring the vastly better capabilities of their own human eyes).
I'm holding out hope that a good chunk of the public will understand this footage is not at all indicative of the vision capabilities of even the human eye, lest the actual sensor tech on that Uber car. Certainly a good number of people on Twitter do.
If Waymo understood how to stick a knife in they would have replicated this scenario yesterday and released a video. Hell, you could take a Mercedes S class with night view assistant and it would spot this, no problem.
Personally, I'm amazed that we get to see any video at all from this accident... Given that we live in an age where video is king, and given Uber's reputation for going to extreme lengths to get their way, I think we should be thankful to the Tempe Police for getting this important document to the public so quickly.
> If there is something that isn't going to help the public perception of autonomous cars
If there is something now that's going to help with the public perception of this cars that people claim to be autonomous, it's people like you just quitting trying to defend this and care about the deceased ATM. The software and hardware was sub-par, and the driver of a fucking TEST DRIVE was not looking at the road, let aside having hands ready on the steering wheel. The driver's feet were probably wandering around relaxing besides the pedals. TBH I don't give a flying fuck to the public image of autonomous (!) vehicles ATM.
The first question that comes to my mind watching this, is, why didn't the _pedestrian_ see the _car_? It looks as though she didn't even look up until the car was only a few feet away from here. I'm not just trying to "blame the victim". The car "should" have responded sooner. But see-and-avoid works both ways. If you're choosing to cross a road in the dark, you, too, have a responsibility to understand the drivers' limited visiblity and act accordingly. My point is that this is a teachable moment for not only SDV developers, but also for pedestrians.
I sometimes have trouble figuring out what lane an oncoming car is on, with glasses, in daytime. It wouldn't surprise me if she was absent-mindedly taking a familiar route to her homeless camp and mistakenly thought the car was on the left lane.
If the article were about a cyclist who, while riding without a helmet, was run over and killed by a car whose driver didn’t do a safe lane change, and I commented:
“Not trying to blame the victim... but this is a teachable moment not only for drivers, but for cyclists...”
... it would be a true statement, which is why I didn’t say the GP was making a false one, but a normal native speaker would at least recognize it as a strange thing to say.
Cyclists should wear helmets, and the cyclist certainly is partly to blame. But no one was suggesting that the cyclist is guilt-free, so the actual effect of the statement is to try and draw a false equivalence.
It’s like saying “sure, global warming is real, but let’s not forget the effects of gradual and natural cyclical climate change.” No educated person in the discussion “forgot” the second, but by phrasing it this way you’re implying we should be paying equal attention to a large effect and a much smaller one.
No, as others have discussed, driving above the speed limit when it is “the middle of the light with no lights on” means the driver is at fault as well.
Legally correct, but technically wrong. When it comes to judging whether self-driving cars are safe enough to be allowed on the roads with the rest of us, incidents like this are the kiss of death. With a human driver at the wheel this woman would be alive, even though she was jaywalking. This is going to set back public acceptance of self-driving technology a ways.
That's a strong assumption to make, that a human could have done better. It was dark, night, nowhere near a normal crosswalk, and not where I as a driver would normally expect a person to be. I think it would have been hard for even the most alert driver to not hit this person in this circumstance.
The point wasn't quite "what would human do?" but "computer just drives straight over people, BAN KILLER ROBOTS NOW!!!" Public perception and its backlash is not always commensurate with the technical side.
You really think drivers have carte blanche to run down people in the road as long as they have right of way? That drivers have no responsibility to avoid killing people as long as those people aren't on crosswalks? That's what you seem to be saying here.
The fact that the pedestrian died is precisely the point. As a frequent pedestrian, and as a person who likes people, and because people are often pedestrians, I would like to prevent pedestrian deaths. That happens by holding SDV developers to rigorous standards, but also by highlighting that crossing the street safely requires paying close attention and being careful, more so than many people do. I've seen several places where pedestrians have the right of way a lot, and many will just step directly into the street, legally mind you, when cars are traveling quickly nearby. No matter how you slice it, that yields an unacceptably high probability of death, and you can blame whoever you want but you will still be dead. There's a difference between victim blaming, and pointing out that you can avoid becoming a victim by taking sensible precautions. This is the latter. It doesn't absolve SDV developers of any carelessness they may have had in their work to point that out too.
If a pedestrian has the right of way, why should the impetus be on them to be mindful? Why shouldn't the impetus be on drivers to slow down? Why should pedestrians live in constant fear of being killed when the law should protect them?
The law asserts justice, it does not protect against negligence in the moment it is happening. In the case of crossing the road, with a many thousand pound hunk of metal vs a human being, the human will overwhelmingly bear the brunt of the immediate harm.
It seems pretty obvious to me that being a mindful pedestrian is simply a matter of self preservation
Right of way means cars are obligated to stop when you cross the street. It doesn't solve the practical issue of drivers needing at least some time to react, even if they are paying complete attention and driving at a reasonable, safe speed.
Difficulty of looking both ways and pausing for a second before you cross the street: 1 unit. Difficulty of getting getting every single driver in any area where pedestrians have the right of way to drive slow enough that they can make a safe stop assuming any pedestrian can legally dart into the street without warning: 1,000,000,000 units.
And yet I've seen plenty of people turn 90 degrees across a street at their usual walking pace with no pause and with their eyes on their phone and headphones in their ears.
If you want to spin that particular chamber of probability because legally you're technically protected, honestly I feel worse for the driver who has to live with that memory now and wonder what they possibly could have done to prevent it short of just never driving a car at all.
I think the only circumstance where a pedestrian can cross a road without watching for cars is when protected by a traffic light, and even then that's not wise. A pedestrian crossing a road outside of any crosswalk at night and not watching for cars is playing russian roulette. Doesn't mean the driver (or self-driving system) shouldn't have spotted it as well to prevent the accident. But it is clearly a key driver enabling that accident.
> I think the only circumstance where a pedestrian can cross a road without watching for cars is when protected by a traffic light, and even then that's not wise.
You are definitely correct about even then you should check. And once you check and see it is clear...keepchecking as you cross.
An acquaintance of mine from college was killed crossing Colorado Blvd in Pasadena, California late on a Friday afternoon, in a crosswalk at a fully controlled intersection, with the cross traffic having a red light.
Colorado Blvd is a major street, and late on a Friday afternoon would have a fairly high density of cars.
The car that hit him was going something like 80 mph. At the time he started crossing, that car would have been 3 blocks away. Even if it had been the only car on the road, at that distance there would be no way to judge the speed, and any car that far away traveling anywhere near legal speeds would be far enough away to not be a danger to any normal pedestrian crossing.
With the other cars that were on the road on a late Friday, it probably would not even be possible to see the car that hit him when he entered the crosswalk. There would have been several cars stopped at the intersection obstructing his view, plus cars at the intersections further up the road, or in transit between the intersections.
His only chance would have been to keep checking oncoming cars as he crossed, even after all the cars actually at or near his intersection at stopped.
Almost no one does that. Mostly once we see everyone nearby stop we just concentrate on cars that are turning and so might enter the crosswalk even though the light is red (assuming we are in a right turn on red jurisdiction).
Lesson #1: Treat each step as you cross the street as if it is your first step into the street. Do your full "is it safe to cross" scan constantly.
Lesson #2: Cars very far away at the time you start to cross can make it to you before you finish, even if traffic seems heavy enough that there is no way they could go fast enough to reach you. Your scan needs to look out farther than you think it needs to.
The girl who ran a red light three feet in front of me while looking at her phone would agree with you -- that is, if she even realized she had done it. (I was in the crosswalk and I stopped when it became apparent that she wouldn't)
I see a lot of people who cross the street without looking. I definitely don’t get it. I constantly check everywhere even when I clearly have the right of way. But that’s how people are.
These people need to watch more videos of people getting run right the hell over before it finally sinks in. I’ve watched enough that I never walk close alongside any road, and keep a good distance from an intersection while waiting for the cars to stop, because sometimes they don’t!
And I wouldn't be surprised if many of these people are really concerned about the threat of terrorism or of flying while ignoring an imminent lethal risk that is many orders of magnitude higher.
> If you're choosing to cross a road in the dark, you, too, have a responsibility to understand the drivers' limited visiblity and act accordingly.
You have a self-responsibility, which most people act on (self-preservation). But as a driver you have a responsibility to pedestrians who can be killed by the machine that you are driving. That is the greater responsibility and why active care for pedestrians should be one of the highest regards of a driver (or autonomous driving system).
If you're choosing to cross a road in the dark, you, too, have a responsibility to understand the drivers' limited visiblity and act accordingly.
No kidding. This might be a somewhat controversial opinion, but I think the elephant in the room here is this general "pedestrian has right of way" notion. It's much easier for pedestrians to watch out for and evade cars than the other way around, and yet we seem to insist the opposite? That seems rather backwards and contrary to the laws of physics.
THere are several lanes free with plenty of room for the car to pass without issue. I think the pedestrian assumed this was just an inconsiderate driver not slowing down and driving around me... as there is no way on earth that a human would ever have hit her! the video is totally unrepresentative, and if it was representative then the car should have been doing half the speed.
I sure couldn't have reacted quickly enough to have prevented this collision. I'd expect the car to have better reflexes then I do, but given the little time from when the pedestrian first showed up on camera and the time when the collision occurred, I doubt that there was anything that the car could have done, regardless of the sophistication of its software.
Uber clearly has a very terrible problem that their sensors did not pick this up and stop in time, but yeah... if what I saw as a human driver matched what the video camera saw and I hit the brakes the microsecond I saw them, my car still would have hit the person. Brakes aren't magic, and human vision has its limitations.
An autonomous vehicle obviously shouldn't exceed a speed where it's stopping distance exceeds it's vision capabilities, since next time it might as well be a tree trunk. That's sometimes difficult for humans to gauge, but then we want autonomous cars so they can make these calculations (and they are much better equipped to).
I suppose we'll need to wait for some standardization in the sensor department, but it would be great if autonomous car makers could share the sensor data for collisions so that everyone can learn from the mistakes. Test data is great, but there's nothing like real world problems.
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[ 3.4 ms ] story [ 358 ms ] threadThe driver definitely seemed distracted by a device of some kind.
The car hardware should have seen her. If it doesn’t work in the dark it shouldn’t be on the road imho.
Yes, quiet true.
> The car hardware should have seen her. If it doesn’t work in the dark it shouldn’t be on the road imho.
I tend to agree. I think unfortunately this video indicates that the car did not perform worse than a human. It's still valuable to have cars that perform better than humans, even if they aren't perfect.
https://twitter.com/brianawhitney/status/976591851384745984?...
The woman with the bike wasn’t moving fast at all. I dunno...
I think the question now is how well a LIDAR is supposed to work in the dark. I keep hearing people saying that the hardware should've "seen" her, but speaking purely in terms of physics, how exactly is that supposed to work? Doesn't night vision still require a minimum threshold of light in order to work? How much light?
It should work in complete darkness.
If that's true, this would certainly suggest a big failure from the LIDAR system in this incident. I wonder how that claim is tested. Would city lights interfere with testing (similar to how you can't see stars in the middle of cities)?
So it may have ignored the LIDAR because of whatever was coming from the other inputs.
It will be interesting to find out what actually happened. It is clearly a major malfunction or deficiency in the sensors, no doubt.
For a self-driving car to not even apply the brakes at all in this situation is inexcusable.
A human would have made this mistake, but I don't know enough about LIDAR to understand if a computer should have made this mistake. Is night vision poor on these machines?
I disagree. I think this video shows that the car performs much worse than I would expect a human to.
I have my own dashcam videos at night that look very similar to this, and I definitely think I would not have hit a large object such as a pedestrian walking a bicycle on a straight road such as this in a 35mph zone.
It seems like the car is out driving its headlights. Assuming a road line is about 10 feet (as is typical), only about 20~30 feet of distance is illuminated... but at 30mph you need ~45ft for an average car to break, and at 40mph you need ~80ft. (According to [1] -- ignoring reaction time.) Is there something wrong with the headlights? Is the video just that bad? (And if so, is it even used for decision making by the car?)
[1] http://www.government-fleet.com/content/driver-care-know-you...
If the car can't see things in time to stop, it's probably moving too fast for the conditions.
https://twitter.com/brianawhitney/status/976591851384745984?...
The car should have seen that.
This seems in line with the police report that "it would have been difficult to avoid this collision in any kind of mode (autonomous or human-driven)"
Maybe a SDV with superhuman reaction time should've been able to stop some 10ft after hitting her, and maybe if it had night vision-like sensors, it should've been able to see her from farther away, but my impression is that it would've been impossible for a regular human driver to avoid this accident.
Given that the SDV didn't attempt to reduce speed before she was visible under regular light, I'm forced to assume the sensors do require light in order to detect obstacles and that there wasn't enough light to activate the sensor before the headlights illuminated her.
[1](https://www.google.com/maps/@33.4369852,-111.9436199,113m/da...)
[2]https://www.google.com/search?q=stopping+distance+40mph&rlz=...
I'm curious how the visibility differs between what we see on this camera and what a human actually sees in person.
Looking at the video, it seemed like the driver reacted (facially) about a second after she shifted her gaze from some device to the road. It took me several runs of replaying the video to narrow down the time between when I first saw her shoe and collision to about 2 seconds. Also, recall this was at 10pm. In my opinion, swerving or braking with a 1-2 second notice is extremely hard, especially if it's late and you're tired. To be perfectly honest, if it was me, I don't think I would've been able to react at all before the collision.
1. Human eyes have a better dynamic range than cameras do. The camera is thus displaying a worse contrast than a human eye can see.
2. Motion is preattentive in the visual system. (When you think about it, panicking about subtle motion in the corner of your eye tends to be evolutionarily advantageous).
So the time we have to identify the pedestrian using the video is a minimum bound of the time, not necessarily an accurate reflection of the time. It is not clear how much extra time (if any) a reasonable driver would have in this incident.
Obviously a sad situation, but it's reassuring that the knowledge from one crash can lead to all other autonomous vehicles learning to avoid it in the future.
Presumably, there'd be regulations for software too, classifiers and AI decision making. Has any jurisdiction set standards in this?
In the moment that we can fully see her, she does look unambiguously like a person walking a bike across the road (reports say there were plastic bags on the bike, but they weren't obvious/obstructive in the camera view). Is the AV's LIDAR expected to detect this kind of thing, even if it's too dark for human eyes?
The video of the Uber driver doesn't look great for the driver. I mean she doesn't look particularly engaged -- but I suspect that's what most of us would look like at the wheel. But she definitely seems to be looking downwards, right at the moment of impact.
Unless some other incriminating info is discovered, I hope that the driver isn't the sole focus of punishment (doesn't help that she's a convicted armed robber, albeit years ago). Being able to brake in time for the victim seems difficult even in most ideal and alert conditions. And I have to think human operators are going to suffer complacency when 95-99% of the time they never have to actually drive -- making that switch seems to be a situation ripe with problems.
I don't mean that Uber execs/testers/engineers (again, assuming there isn't other incriminating evidence) should be scapegoats. I hope the result involves regulations that add more transparency to reporting (especially in Arizona), and public debate about the expectations of AV and AI.
But even then, this impacts the maximal detection range only. Even if the obstacle suddenly popped up at 20m it should have been enough to drastically reduce the collision speed.
The driver clearly was unfortunately not paying attention. She clearly reacts within a few hundred milliseconds of looking up, which is to say immediate reaction time in terms of mental processing. That means that we cannot use her reaction time to gauge how early she could have seen the pedestrian to compensate for poorer optics of digital cameras.
As I understand LIDAR, it should work even at night (as it generates its own light and measures response time). This is a pedestrian, walking across a road, with nothing possible to occlude her. There is no reason it should not have identified an obstacle in the road (she's been in the road for several seconds, after all, having crossed at least 3 lanes of traffic by that point). Even if the visual camera had problems identifying the object, LIDAR should have flagged it.
As sad as this accident was, I don't see how the driver or Uber is legally at fault. Pedestrians crossing outside of a crosswalk are supposed to yield to traffic. The victim in this video is stunningly oblivious to the fact that she's on a roadway.
Obviously we want self-driving tech to be good enough to avoid such an accident, particularly since a human probably could have; I'm not arguing otherwise. But legally, the victim was clearly at least partially at fault here.
I think one thing this incident is going to do is to point up the limitations of having a human at the wheel, supposedly ready to take over. In a true sudden emergency, after tens of thousands of miles of uneventful riding around, that just isn't going to happen reliably.
Pedestrians always have the right-of-way. They might get a ticket for jaywalking in some cities, but it's never permissible to hit someone with your car, regardless of whether they're in a crosswalk. Vehicular manslaughter is no minor infraction, and Uber can expect a civil suit from the victim's family even if there are no criminal charges.
Arizona: Vehicles must yield the right-of-way to pedestrians within a crosswalk that are in the same half of the roadway as the vehicle or when a pedestrian is approaching closely enough from the opposite side of the roadway to constitute a danger. Pedestrians may not suddenly leave the curb and enter a crosswalk into the path of a moving vehicle that is so close the vehicle is unable to yield. Pedestrians must yield the right-of-way to vehicles when crossing outside of a marked crosswalk or an unmarked crosswalk at an intersection. Where traffic control devices are in operation, pedestrians may only cross between two adjacent intersections in a marked crosswalk.
One saving grace for any plaintiff is that in AZ you can recover 1% damages even if you are 99% at fault.
On the other hand, that pedestrian was astonishingly oblivious, crossing a two-lane roadway with a 45mph speed limit and not even looking for oncoming traffic. If she did that every night for a couple of years, I think her odds of having at least a close call would approach 100%.
It will be interesting to see what happens.
Just FYI: In the US, this not legally true, and definitely not legally true in a lot of comparative negligence states.
While its true you can't just hit people with your car, any civil suit that is filed would be usually lost in most of these states (where lost == you may not recover money). It does vary, some states (like AZ) allow you to recover 1% even if you are 99% at fault.
In fact, what you say about right of way is not even true in very pedestrian friendly states like California. In California (and most states), what the person you replied to wrote is correct.
https://leginfo.legislature.ca.gov/faces/codes_displaySectio...
21950. (a) The driver of a vehicle shall yield the right-of-way to a pedestrian crossing the roadway within any marked crosswalk or within any unmarked crosswalk at an intersection, except as otherwise provided in this chapter.
(b) This section does not relieve a pedestrian from the duty of using due care for his or her safety. No pedestrian may suddenly leave a curb or other place of safety and walk or run into the path of a vehicle that is so close as to constitute an immediate hazard. No pedestrian may unnecessarily stop or delay traffic while in a marked or unmarked crosswalk.
(c) The driver of a vehicle approaching a pedestrian within any marked or unmarked crosswalk shall exercise all due care and shall reduce the speed of the vehicle or take any other action relating to the operation of the vehicle as necessary to safeguard the safety of the pedestrian.
(d) Subdivision (b) does not relieve a driver of a vehicle from the duty of exercising due care for the safety of any pedestrian within any marked crosswalk or within any unmarked crosswalk at an intersection.
: P
Thanks for your informative correction, even though it might not be a bad misconception to have. New idea for a band name: Beneficial Misconception
This video shows a completely different scenario. The woman started on the median, but the vehicle was in the #2 lane. She wasn't visible to the naked eye but she also wasn't darting into traffic and had to cross the #1 lane before even being in the path of the vehicle. A human driver certainly would have difficulty stopping in time, but why did the sensor package not pick her up? This doesn't appear to be the close call we were told it was. To me, this seems like exactly the scenario that autonomous driving vehicles are intended to prevent.
I would expect if IR/LIDAR are working properly the car would see the pedestrian as if broad, bright daylight, so why no reaction at all?
Lots of people are hoping they will prevent such scenarios, the motivation for fielding them is more related to making lots of money.
Inclement conditions, defensive driving, etc. are much harder to work with but this should have been cake.
[0] https://waymo.com/
[1] https://www.uber.com/info/atg/
Of course they are selling them as safe. I still think the funding to work on them is chasing big piles of money.
Automated-car fatalities total: 1
Seems safer, so far.
Also, nothing's going to make walking out in front of a ton of steel going 30+mph 100% safe.
Such a comparison would have to take into account the amount of human-driven cars and automated cars - not just taking a picture of a single day, but the variance over time (e.g. if today there are a thousand automated cars in operation, and yesterday there were 50, that can distort the average stats); automated cars aren't driving in certain areas/times/weather conditions whereas human-driven cars are, etc.
Automated cars may be safer, but, open snark – I hope it's not calculating its sensor data in this way — close snark.
edit: but she is in front of the bike, so this shouldn't matter. Does the darkness of her clothing impact any of the sensors?
A bicycle shouldn't need to be covered in reflectors to be safe from getting run over by a car. However anybody who cycles at night (as I do frequently) should wear reflective clothing because the road is full of reckless drivers.
I guess my bike has the retroreflective sidewalls... or else I was sold a bike illegally.
Humans not paying attention can never be solved, but hopefully we can get to the bottom of this failure and then fix it systemically.
Unfortunately given how shady Uber are, we will never be able to trust their technical analysis in the event one is ever released.
This seems key. Whether in autonomous mode or not, whether someone got hit or not, this clearly should not have been happening, and as such indicates some malfunction or lapse in protocol.
https://www.google.cz/maps/@33.4350531,-111.941492,3a,75y,33...
OTOH, if the issue was "human thought computer was driving, computer was actually off", this might be a completely new class of errors in driving (although it does happen in aviation, where both pilots think the other one is PF: https://aviation.stackexchange.com/questions/5091/how-are-co... )
http://www.thedrive.com/tech/17083/the-battle-for-best-semi-...
From the video this morning I was wondering how it was possible the vehicle lidar and radar didn't pick this up. This is exactly the sort of thing I would hope these additional sensors could pick up easily.
Also from the released video, it was clear to me the "human driver" of the car was not paying attention. Looks like they are looking at their phone at lap level 90% of the time, unless there was something like a "camera/lidar" view in the dash they were looking at.
Having a human in these self driving cars is useless. There is so little for the human to do that it is hard to keep them from checking out. And once they do, they might as well not be there. Seems like "Safety Theater" to me, make the public and the Uber riders feel like there is still a human in the loop, when there really isn't.
More useful would be to have a central location with humans monitoring dozens of cars, like a sort of air-traffic control situation. Better chance of keeping their attention with enough going on. They'd be there in case of difficulties, know when a car 'went off the rails' or notify authorities in case of an accident.
I worry that monitoring dozens of cars would be too much information for the "Road Traffic Control" to be able to respond in the 1.5 seconds that were available in this video, especially if they have such "low dynamic range" as what we see in this video. But maybe Lidar data would have showed the RTC operator something the car didn't see?
I'm really looking forward to the findings about what radar, lidar, and sonar sensors were saying during this time.
I mean I've seen comments that a human might not have seen the pedestrian. Is that a "defense" of driving AI? That's it's about as good as human driving?
Seems to me the public won't accept driverless cars unless there is significant evidence that it's much better than human drivers - after all human drivers make a lot of mistakes and cause a lot of fatalities. I don't think any other claims of the advantages of AI driving could offset any negative publicity of injury or death.
Just a thought in the context of this tragedy.
I know we don't live in a perfect world, but regardless, we can't change what happened here, so it's best to learn something from it.
https://xkcd.com/1838/
Distracted and impaired humans do, and when a mistake is made we can put them in jail. Who can we put in jail for software errors?
And to not jaywalk a bike across a street in the dark!
--edit: okay guys... no where did anyone argue that you shouldn't be watching for pedestrians crossing. Stop yelling "gotcha!" like you caught me in a trap. What I'm arguing against is the common refrain on these articles that there is no such thing as jaywalking and the pedestrian has the right to the road over the car. Maybe it's true in Europe judging by comments on previous articles, but it's not common in the US. It's illegal.
Congratulations on expertly knocking down your own strawman, though.
It's not even remotely rare. Drive on campus or downtown in AZ for a more than a few minutes.
Strawman. I argued the opposite. You made the grossly incorrect assertion "That is not a normal thing to happen in America, and no one expects it to happen. It is a very rare situation."
If preprogrammed cars cant handle random objects in unexpected places then they are uber DOA.
http://www.ncsl.org/research/transportation/pedestrian-cross...
But the legality is to some extent beside the point. Autonomous vehicles aren't going to be tuned to pedestrian yielding rules state-to-state, simply because hitting a pedestrian is never an acceptable outcome if avoidable no matter who is in the right/wrong.
Obviously the concrete level of awareness that drivers usually have is probably related to a lot of other circumstances (light conditions/amount of traffic etc.)
The last thread about this contained a very long argument from some Europeans who disagree with the core concept of "jaywalking". Some people really do hold the belief that roads are for pedestrians first and cars last, contrary to US law.
Judging by the replies in this thread, it would seem some American roads are more pedestrian than they are pavement.
It is the responsibility of the driver to be alert and try to minimize the impact. Just because a cyclist shouldn't cross a four-lane road in the middle of the night, doesn't mean you shouldn't look for obstacles.
The particular combination of speed and distance may not be common, but the general situation isn't rare.
You are conflating two different concepts. In every state in the U.S., it is illegal to hit a pedestrian whether or not they are where they are supposed to be. If you see a pedestrian jaywalking then you are required to avoid the pedestrian to the greatest extent possible. Anything less is at least manslaughter.
Still, the bike and rider were in view front-and-center for plenty of time for an alert driver to brake (if not avoid).
Regardless, it is the driver's responsibility to perceive and avoid hazards like this and I think that would've been pretty easy given it's a big wide empty road with overhead lighting. This looks like the kind of bad low light footage my cheap dashcam produces in similar conditions.
It's clear from the video that a human driver actually would've had more trouble since the pedestrian showed up in the field of view right before the collision, yet that's in the visible spectrum.
When I argue for automated driving (as a casual observer), I tell people about exactly this sort of stuff (a computer can look in 20 places at the same time, a human can't. a computer can see in the dark, a human can't).
Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
The eye will adapt to a mean level of light in the larger FOV (not fovea only) - that is why instrument clusters on cars need to be low-level lit, to not disturb this adaptation. Exterior light sources like headlights and street lights further influence adaptation and veiling glare can lead to light sources overshadowing smaller luminance signals and pushing them out of the range that the eye is adapted for.
Also, When a digital camera records an image, a gamma curve is applied to it before display, which makes up for a bias against the darker portions which the digital equipment does not inherently have.
Considering the streetlights, I cannot imagine any excuse. This video will sadly give them the benefit of public doubt but anyone familiar with lighting digital video will be unconvinced that the video feed was the culprit.
I'm glad it was not me driving down that road that night, I don't think I could have prevented it.
That's not at all clear to me. I don't know too much about cameras, but it looks to me like the camera is making the scene appear much darker than it actually is.
In the video, you can see many street lights projecting down onto the ground, and the person was walking the the gap between two streetlights. The gap between street lights (and hence the person) was in the field of view of the camera the entire time; they just weren't "visible" in the camera because of the low lighting. I'm confident my eyes are good enough that I would have been able to see this person at night in these lighting conditions. (Whether I could have reacted in time is another question.) It seems to me like the camera just doesn't have the dynamic range needed for driving in these low light conditions, which is a major problem.
http://velodynelidar.com/hdl-64e.html (note that this LIDAR is expensive - costs way more than the car it is mounted to)
Here's the manual for it - note the specs in the back:
http://www.velodynelidar.com/lidar/products/manual/HDL-64E%2...
It has 64 lasers, spread out over about 27 degrees - about 0.4 degrees per laser, from almost horizontal to an angle of 24 degrees or so down. Now take a look at where it is mounted on the car, and envision these laser beams spreading out and being spun in a circular conical area around the car.
Now - if you think about it - as the distance from the sensor increases, the beams are spread further apart. I'd be willing to bet that at about 200 feet or so away from the car, very few of the beams would hit a person and reflect back. Also - take a look at the reflectance data in the spec. Not bad...but imagine you are wearing a fuzzy black jacket on your top half. How much reflectance now?
What do you think the point cloud returned to the car is going to look like? Will it look like a human? Hard to say - but you feed that into a classifier algorithm, there's a possibility that it's not going to identify the blob as a "human" to slow down. Especially when you add some bags, a strange gait, plus the bicycle behind the person. All of this uncertainty adds up.
I am also willing to bet that only the LIDAR was used for collision detection (beyond the radar on the unit). Any cameras - even IR based - would likely only be used for lane keeping and following purposes, plus traffic sign identification. Maybe even "rear view of vehicle" detection. Ideally it would be used for "person/animal" identification and classification to - but again, given the camera sensor, and who knows what the IR sensor saw or didn't see, along with the weird lighting conditions - well, who knows how it would have classified that mix?
Lots of variables here - lots of "ifs" too. All we can do is speculate, because we don't have the raw data. Uber would do well to release the entire raw dataset from all the sensors to the community and others to look over and learn from.
Finally - I am not an expert on any of this; my only "qualifications" on this subject is having taken and passed a couple of Udacity MOOCs - specifically the "Self-Driving Car Engineer Nanodegree" program (2016-2017), and their "CS373" course (2012). Both courses were very enlightening and educational, but could only really be considered an introduction to this kind of tech.
This was purely bad software, and no failure scenario being programmed in. I really don't think it's that difficult to program split-second reaction to obstacles that appear into the driving path. We need to get to a point where these vehicles can do stuff like this, even in a 2-dimensional way:
https://youtu.be/uLasBsoZBi0?t=1m40s
https://nacto.org/docs/usdg/relationship_between_speed_risk_...
Getting hit at 10mph still is going to suck but it’s a lot more likely to be broken bones and road-rash.
They seem to use 2.5 seconds as the standard for drivers to perceive and react to an obstacle, which based upon studies covers 90% of all drivers. 1.5 seconds to perceive, 1 second to react. Then you have maneuver time on top of that 2.5 seconds.
Given this, 1 second seems very low. A large percentage of drivers would probably plow into them at full speed.
If all but the slowest 10% can react in 2.5 seconds than I would think many would do a fair bit better.
Edit: Apparently the average person is closer to 1.1 seconds. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.372...
Waymo cars are capable of sensing vehicles and pedestrians at least half a block away in every directions. I was reserving any judgement on wether this collision could have been prevented, but seeing the video tells me that 1) a human driver might have hit the victim regardless, and 2) I'm very surprised that the LIDAR sensor didn't cause the car to stop to a halt much, much earlier. This is exactly the kind of situation that I would expect self-driving cars to be better than human drivers.
Maybe the outcome will be that thermal infrared will be mandated on all sensor packs?
I just watch the road in front of me.
My idea is that the car has been behaving well for a long time and consequently the driver lowered is vigilance. Big mistake.
Unlike many others, sadly - even when they don't have any self-driving tech at all
What you posted looks pretty cool, I don't know enough about it to understand what I should be prioritizing focus on, but we can chalk that up to ignorance. The benefit that driver-view footage has is that it is a viewpoint all of us are familiar with. If you ask me to watch dashcam footage to assess some kind of traffic thing, there's a general expectation of where I keep my eyes and what I notice.
This normal-human-view mode is probably going to be necessary in AV cases in which we determine whether the car's AI did the right thing. Presumably, as AV becomes mainstream and extremely safe, these accidents will involve edge cases and outliers which are poorly interpreted by sensors/non-human-vision. Seeing the scene as a human driver does might be a necessary starting place?
But the Uber case in AZ, IMO, proves your point. The Tempe police quickly made a judgement call based on what seems to be inadequate video. Everyone who can now view the video will also be inclined to think how impossible it would be to avoid hitting the victim, even if the actual scene in-person has much more light. And of course, we don't want to judge AV solely on whether it performs as well as normal humans.
Even if the camera was brighter uber isn't at fault anyway....
I would be very interested to learn whether or not the car's autonomous system identified a bicycle at any point prior to the collision.
car didn't see it at all even in those last moments.
But this was a pedestrian, not a cyclist.
Personally, while riding at night, I look like a Christmas tree. $10 on EBay goes far these days in the reflective tape and bike light department:
What is surprising is that the bike didn't seem to have Tire reflectors like these:
https://www.wired.com/2011/11/fiks-reflective-rim-strips-for...
They are mandatory in lots of countries, to the point that it's impossible to buy tires without them. All brands come with them.
However, as a society and civilization, and even more so, as engineers and scientists, we are going to expect that the autonomous car matches or exceeds human-level performance in critical situations like this.
Therefore the time spent on investigating, understanding, and discussing the root causes of the accident is worth understanding. Accidents like these generally do not happen due to a single factor. It is necessary to understand all the necessary factors if we want to make autonomous driving systems more reliable.
At the very least we need to understand whether the pedestrian appeared in the other sensors that a human could have identified by looking at the sensor data, and if yes, whether the autonomous system matched or exceeded human-level performance by detecting the pedestrian, and if the pedestrian was indeed detected, why the autonomous driving system failed to respond to the situation.
However, most auto liability insurance covers whoever you permit to drive the vehicle, so the owners policy does typically cover the fender bender on the way to the grocery store.
You don't think performing as well as normal humans should be sufficient to allow them on the road?
Or are you saying they should be allowed even if their performance is worse than human? (...as long as some other criterion is met?)
Or swerve out of the way.
It is surprising to learn that these vehicles are operating at night. To collect training data, since nighttime driving is inevitable, perhaps there are ways to simulate night to the computer vision systems during daytime so the human supervisor can still see clearly.
Would you trust this system that didn't even manage to slow down at all with a pedestrian slowly pushing a bike directly in front of it, artificially adjusted to be even worse, driving during the day??
I wouldn't.
Autonomous cars are never going to be viable. Just looking at the cost of high-end SLR sensors and lenses that you'd need to match human eye dynamic range, and you're already looking at an expensive setup, before we even get to things like 360-degree vision and IR/LIDAR/Hyperspectral imaging. And that's in addition to all the compute problems.
Sorry Silicon Valley tech-bros, but it's a fantasy you're chasing that's never going to happen. The quicker we can end this scam industry, the better.
People really need to be told "no".
Probably better to chase after flying cars..
They should pivit to augmenting drivers, not attempting to drive for them. I would happily utilize a properly designed HUD (meaning I have source access) connected to a fast MerCad or bolometer array.
It really is. The eye can detect a single photon. Fingertips can detect 13nm bumps, smaller than a transistor on Coffee-lake CPUs.
We're better off acknowledging machine limits to work on other problems instead.
But you are right, though. I think augmenting drivers sounds like a great idea in the sense you talk about. The kind of augmenting drivers I don't want are those stupid headbands you'd wear that beep like crazy if your head starts tilting in a way that resembles falling asleep. If you are in danger of falling asleep at the wheel and need a device like that I think it's pretty obvious one should take a nap on the side of the road or in a free parking lot, haha. Hopefully if we do wind up headed in that direction the people inventing will have a similar way of thinking and inventing.
No. A camera's dynamic range is pretty much fixed. If you can capture low-light objects it means high-light objects are completely blown out.
2. I'm not sure you can fix the exposure on "fairly cheap" dashcams.
3. "high-light" in night settings are likely much lower than standard daylight, let alone bright daylight.
Though I guess you could have an auto-exposure dashcam standard and add a low-light one which is only active in low light conditions.
http://i.imgur.com/dhcr6YO.png
So the comment above you is correct. A larger sensor can shoot at a lower ISO in the same lighting conditions, because its noise levels are lower.
The Canon ME20F-SH is a video camera reaches ISO 4,000,000. This camera has a dynamic range of 12 stops and is available at B&H for $20,000. [4]
Of course, this isn't exactly the challenge that cameras face when assessing a scene. The dynamic range happens within a single scene all at the same time. Wide dynamic range (WDR) is the term I've seen used in describing video cameras that can handle both bright and dim areas within the same scene.
[1] http://lightartacademy.com/blog/tutorials/camera-vs-the-huma...
[2] https://www.youtube.com/watch?v=ZRzXgSMbBu0
[3] https://www.cambridgeincolour.com/tutorials/dynamic-range.ht...
[4] https://www.bhphotovideo.com/c/product/1187825-REG/canon_100...
There are a number of video samples shot on the Canon ME20F-SH on YouTube. In these one can see that under low light situations the camera is shooting at ordinary video speed (the camera supports shutter speeds from 24 to 60 fps). I'm not trying to push the Canon ME20F-SH; I don't have any association with Canon. The manual for this camera is available on-line if you'd like to read up on it: [1].
The actual exposure of a video frame or image depends upon the f-stop of the camera's lens (aperture), the shutter speed, and the ISO of the image sensor. See [2].
Basically, each doubling or halving the shutter speeds corresponds to one "full-stop" in photography. Each full stop of exposure doubles or halves the amount of light reaching the sensor. Changing the aperture of the camera's lens by full stops also doubles or halves the amount of light reaching the sensor. Full stops for camera lenses are designated as f1, f1.4, f2, f2.8, f4, f5.6, etc. The light sensitivity of the film or sensor is also customarily measured in full stops. Very slow fine grained color film is ISO 50 and is usually used in full sunlight. ISO 100 is a bit more flexible and ISO 400 used to be considered a "fast" film for situations where more graininess would be acceptable in exchange for low light situations. Each doubling of ISO number corresponds to a full stop. So a photo take with ISO 400 at f2 with 1/1000 second shutter would have the same "brightness" as a picture taken at ISO 100 at f2.8 with 1/125 second shutter (less 2 stops ISO, less 1 stop aperture, and plus three stops shutter speed). Naturally, other factors come into play, the behavior of film or digital sensors at extremely slow or extremely fast shutter speeds isn't linear, there are color differences, and noise issues too. See [3] if you are interested in more about how photography works.
[1] https://www.usa.canon.com/internet/portal/us/home/products/d...
[2] https://photographylife.com/what-is-iso-in-photography
[3] https://www.amazon.com/Negative-Ansel-Adams-Photography/dp/0...
Both of those have eyes that act as reflectors and you can see their eyes well before you can actually see the whole animal.
This[0] suggests that the total time required for a human to avoid an incident like this is 3.6s (at 35 mph, casual googling suggests the car was doing 40). Even if we add 1 second of extra time to deal with it I'm not sure that makes the cut.
0) http://www.visualexpert.com/Resources/pedestrian.html
Your last paragraph is a valid calculation if this were a case of a person stepping directly off a curb into the lane of traffic. However, it appears that they were probably standing on the median looking to cross, then stepped off into the left-most lane of traffic, an empty lane, proceeded across that lane towards the lane in which the car was traveling. In this sort of situation human intuition will recognize that a person standing on the median of a high-speed highway is likely to do something unusual. Particularly when you observe the visual profile of, as media has reported, a homeless person who is using the bicycle with numerous plastic bags hanging off it to collect recycling.
Also, has anyone here talked about the effect on the eyes of watching a (typically) bright white screen vs letting them adjust to the light of the night yet? This point deserves to be brought up.
Perhaps the video was intentionally darkened to simulate this effect. :P
If so (a hand held phone), in Australia that driver would be going to jail for culpable driving causing loss of life.
https://cdn.geekwire.com/wp-content/uploads/2018/02/Front-_-...
A different picture from that article shows that under the GPS is the gear stick, an emergency button, and a cellphone charger.
EDIT: Upon re-watching the video a third time and really paying attention to this I don't think there is any real way for us to know without confirmation from the driver them self or an official report on the incident. My mind was definitely deciding things that just aren't discover-able from the video itself.
"Uber also developed an app, mounted on an iPad in the car’s middle console, for drivers to alert engineers to problems. Drivers could use the app anytime without shifting the car out of autonomous mode. Often, drivers would annotate data at a traffic light or a stop, but many did so while the car was moving"
https://mobile.nytimes.com/2018/03/23/technology/uber-self-d...
The whole project seemed designed for an outcome like this. Eg allowing app to be used whilst on the move, after reducing from 2 to 1 operators. Culpability ought to lie with Uber.
Using bright interior lighting at night is something that we've known not to do for more than a century. If the driver couldn't be expected to see the pedestrian because the interior lighting or UX was too bright that is not something that does not reflect favorably upon Uber.
Also remember she was not a stationary object. She was in the act of crossing the road. Human eyes/brains are good at detecting motion in low light even if we can't 100% make out what the object is.
I have lived in Tempe and know that part of town well. There are apartments, gas stations, hotels, strip malls, fast food restaurants and a strip club. It's not a pitch black country road.
If that's the best Uber can produce then they ought to hang their heads in shame. Unless it was doctored with... as I find it hard to believe they'd put such rubbish quality cameras in their trials.
Do you trust Uber to provide unedited raw video, or would they process it to increase contrast, make it appear that nothing was visible in the dark areas of the frame, reduce the resolution, drop frames, etc.?
Edit: Nevermind. Someone posted a picture of the car's interior, below and there's no computer screen.
https://arstechnica.com/cars/2018/03/police-chief-said-uber-...
Please check the videos out.
Is that the same cam used by the AI to detect obstacles?
I would expect a safe self driving car to include IR cameras that can be more cautious about moving warm blooded creatures.
Surely some more detailed telemetry data would reveal whether the main issue is with the sensors or with the algorithm.
Now that I think about it, self driving cars may be paralyzed by other self driving cars running IR boosted headlights.
https://en.m.wikipedia.org/wiki/High_dynamic_range_imaging
https://youtube.com/watch?v=gtTdiqDqHc8
> "The driver said it was like a flash, the person walked out in front of them," Moir said, referring to the backup driver who was behind the wheel but not operating the vehicle. "His first alert to the collision was the sound of the collision."
> "The driver, Rafael Vasquez, 44, …"
https://www.bloomberg.com/news/articles/2018-03-20/video-sho...
Seriously, what else can you expect. These companies who do put these things on the road with the justification that "There is a human behind the wheel" should be taken out back and shot in the head...Just pull the plug. No more self driving cars for them. Those are just the kind of tech companies we don't want around...
See, it is not a mistake that they are making. They know well enough that this human behind this wheel is a useless as a dummy. But they do it any way. What does it say about them?
Looking forward to seeing this play out in court.
2. These companies seem to be doing nothing to make sure that the drivers will pay attention always and is always in a position to intervene. They even seemed to allow smart phone usage while they are in the car.
So, according to them, the human behind the wheel is just a decoy to prevent backlash from officials and the public, so that they can always say, "look, there is a human behind the wheel if something goes wrong"...
Also, even if they implement some measures, they can only make sure that the driver has eyes on the road. Not that they are actually paying attention. A driver who is actively driving the car will notice a lot more stuff than a passenger who is just looking at the road. There is no way to make a human pay that kind of attention with out actually driving the car. So at best, your "driver behind the wheel" is as good as a passive passenger.
And as told before, the companies are not even trying to make sure of that.
I did wonder if you could require the driver to make control inputs that aren't actually used to control the car but are monitored for being reasonably close to how the computer is controlling the car, and then the automation disengages (with a warning) if the driver is not paying sufficient attention. I then realised that may be _worse_ - in the event of a problem, the driver would have to switch to real inputs that override, which may delay action and not be something they do automatically. It would mean they are paying attention more to see if the automation is making errors where they have more time to react though (e.g. sensor failure that is causing erratic behaviour but not led to an emergency situation).
I wonder if a hybrid approach might be viable -- fake steering is used to ensure that the driver is alert and an active participant, but the driver hitting the brakes immediately takes effect and disengages the automation.
And that’s consumer drive assist tech, not “we are experimenting with full autopilot” tech, where I’d think such safety measures would be even more appropriate.
This is a solvable and solved technical challenge. Uber just didn’t devote any resources to it because they don’t appear to give a shit beyond acquiring a legal fig leaf to shift liability from themselves to an individual.
In that context, the landscape changes significantly - instead of a self driving car that mowed down a pedestrian, we have a driver who was too busy looking at her phone to pay attention to what her vehicle was doing. From the various articles, it seems that she's not an engineer, and is there in effectively the same capacity as any other Uber driver. If that's the case, she's putting far too much trust into an experimental system. I agree that Uber could do more in the way of technological means to ensure the driver is paying attention, but at some point, an adult with a job needs to be responsible for doing that job.
The framework should have been in place before these vehicles were ever put on the roads. For example, there should have been some formally specified tests for a self driving vehicle before it can be put be on the road, even with a back up driver..
> a fully autonomous car is legally no different to cruise control - it's just a driver assist, and the human behind the wheel is still ultimately responsible for whatever the vehicle does.
Any thing that does not require drivers to keep their hands on the wheel is not a driver assist. It IS the driver. So there should be tests that make sure of the competence of the tech that is in the drivers seat.
I don't know how people let this happen!
I'm certain that if you can design and build a self-driving car that you can design a simplistic human attention monitoring system that will cause the car to pull over if attention level is too low.
Gaze monitoring that checks for looking downwards or away from the carriageway for extended or too often repeated periods wouldd probably be enough.
I imagine the attention of the "vehicle operator" is vital to the proper training of the vehicles -- if they don't see near misses, or failures to slow for potential hazards, or failures to react to other road users then how can the softwares faults be corrected? Do they get a human to review all footage after the drive?
I see waymo drivers all the time actively paying attention to the road.
People can safely drive in total darkness with the aid of their amazing human eyes and high-beams.
If for some other reason visibility is low you slow down - not rely on glancing at a backlit display ruining your own night vision and taking your eyes off the road for seconds at a time.
EDIT: what i meant, in light of the downvotes is that humans can train themselves to see, and just that folks driving in Asia have heightened sense of alertness, due to their environment. Hope it came out alright.
Wait, aren't you mean to have your hands on the wheels at all times? I don't see what to be skeptical about when if he just followed the law this could have been avoided.
It seems to me the driver might be in for some legal trouble.
Someone else thought the same thing and went to get their own footage of the road.
https://www.youtube.com/watch?v=1XOVxSCG8u0
In general, traffic safety requires that road planners ensure that one of three conditions always applies:
a) the roads are lighted from above; b) cars are able to use high beams; c) there are no pedestrians crossing the highway.
This can be done in general, mostly by investments in infrastructure to ensure lighting or isolated highways wherever the density doesn't allow to drive with high beams.
Probably checking the computer installed for diagnostics of the autopilot system. If it's in self driving mode and you are the engineer in charge, you'd want to constantly check what the system is seeing vs the actual conditions on the road.
To me it looks like the guy is just falling asleep at a boring job. In all likelihood that was not an engineer more than any other taxi driver is an engineer.
The software is the "driver" of this car. Not the human behind the wheel. Take a look at job descriptions [0] for this. They always include a bit about "operating in vehicle computers". The fact, we don't know what the person is doing.
0 - https://www.indeed.com/viewjob?jk=597616bf7d02d899&tk=1c96sl...
I don't know about current regulations. Are companies now allowed to operate autonomous cars without a driver that pays attention?
But the gap between street lights is going to be very hard to see into.
> I'm confident my eyes are good enough that I would have been able to see this person at night in these lighting conditions.
I think you're overconfident. Human low light vision is very good if there is low light everywhere. But it is not good at seeing into low light regions when brightly lit regions are nearby.
That said, I agree that a visible light video camera is likely to be even worse that human vision under the given circumstances. But as others have commented elsewhere in this thread, the car is not just supposed to be using a visible light video camera. It has LIDAR and IR sensors, which should have clearly shown the pedestrian well before visible light did.
This wholly contradicts my experience driving at night on a street with street lights. I can't recall a time in my entire life I have had significant difficulty seeing into the gap between street lights. Keep in mind that the gap is not arbitrarily chosen.
Edited to note that I have experienced difficulties in low-vis conditions such as snow storms, sand storms, VERY strong rain storms, etc. None of which apply to this situation.
I’m not sure a typical eye exam checks for it, either, because none of the tests I can think of seem like they’d be useful.
(As usual, an even keeled comment based on family experience is -2 and rapidly being silenced with zero feedback inside 5 minutes, which makes me wonder why I contribute to this community at all, probably time to stop)
I would also not judge the community based on reactions to this very contentious thread - i am wary of jumping in on this one, but thought it worth noting your comment was not wildly out of place.
stay, we have cookies :-)
I actually believe i am representing HN as a place where different opinions can be voiced, hopefully in a manner to generate light not heat. Heated discussions are rarely the useful or interesting ones to read.
Thank you for appreciating my enthusiasm.
PS Are you using two accounts - one ("my 'unpopular opinion' account) for saying things you fear people might not like? That seems odd. May I ask why?
I did one at my last eye exam and it was pressing a button when you see dim flashes in all different locations. If you had low sensitivity, you wouldn't see those flashes and presumably you'd get a low score.
It's not supposed to be, no. But the gaps are not always optimal. The spacing of the street lights in the video (to the extent I can tell) seems to be quite wide, wider than I would think is optimal.
Not according to the post by niftich upthread.
Looking, right now, at a parking lot between two lights from a well-lit room. I can make out most of the outline of the black car in the middle of the "darkness" without any trouble. This isn't even the low light vision kicking in (which I agree isn't going to kick in if you're driving). Human vision should be able to make out the pedestrian earlier than the video footage.
Also, are you looking straight at the car? Or are you looking elsewhere so that the car is in your peripheral vision, the way it would be if it were on the side of a road you were driving on?
In this video [1] driving northbound, same as the vehicle in the crash, the car first goes under AZ-202, emerges under a streetlight, goes through a darker spot, then another streetlight (as you see the rocky outcrop), and then a very dark spot: and suddenly, you see a right-turn lane that wasn't there before. The latter dark spot is where the crash happened.
Another video by the same author, driving southbound [2], provides another useful reference. And these videos are three years old, yet the illumination of the roadway has not improved. Cameras exaggerate the contrast a bit, but not unreasonably so. The streetlights in question essentially aim directly downwards, illuminating the roadway immediately underneath, but much less of the surrounding air than other designs. This is responsible for the dark gaps, albeit it does significantly reduce light pollution.
[1] https://youtu.be/zEaTdYJExq8?t=8m50s [2] https://youtu.be/yfR7krN7z00?t=23m26s
EDIT:
Found more. The car in this video is going southbound, camera facing backwards [3]. This view faces the same way as the Uber did, but of course this video is moving away from the scene, and offset by a few dozen meters to the west. The drastic change in roadway illumination can still be seen.
In a fourth video [4], the car is going northbound, like the Uber, in the proper lanes, but the camera is pointing obliquely front-right. The illumination seems better, but you can still see the intensity of the shadows, including environmental shadows and the car's own shadow, as it moves between the lights.
[3] https://youtu.be/0Dum8Fj71JU?t=13s [4] https://youtu.be/6qHcuW_LCIU?t=16m45s
Tucson does it due to the nearby observatory. The greater Phoenix area has a huge glow that washes out all the stars. You can see the glow as far away as Casa Grande when you come out of the little rocky pass on I-10 north of there.
Edit: removed a duplicated word.
I live in the Phoenix area, on the west side closer to Glendale (specifically, the border between Phoenix and Glendale is literally in my back yard).
There are times in the summer where the glow from the city is so bright, that rather than a dark sky (never black), you have a grey dimly lit sky instead.
Literally, "the sky was the color of television tuned to a dead channel" - maybe not as bright as the static Gibson was referring to, but still bright enough to see by - even without a full moon.
Everyone is moaning and slicing and dicing what the self-driving vehicle did wrong but, since you're familiar with the area: are pedestrians typically expected to be crossing this road?
Seems like the accident has a lot of factors that might not only be the self-driving car's fault, nor even a human driver that was fully in control. Regardless of how well people may want self-driving cars to do, one thing that can actually exist in the present is to make sure that we are creating safe ways for pedestrians to cross a road.
I've driven many thousands of hours at night and have dealt with a fair number of crazy pedestrians including a rather ... uncoordinated ... guy in Casa Grande who decided to go in circles on his bike in the middle of the road at around 3 AM for no discernible reason. Fortunately that place was much better lit and I was able to see him and stop until he got out of my side of the road.
So it's not that common, but yes, every so often you will see some person in black jaywalking across a wide road at night and they're quite hard to see. I don't think a lot of people appreciate that the streets here are wide & fast and that there just isn't that much pedestrian traffic even in daytime.
Here in LA, it's dense and traffic can't get up to very high speeds and we have relatively frequent places to cross safely if people choose to do so. I've definitely seen those who choose not to walk an extra 100 feet to wait at a crosswalk nearly hit in dusk or night traffic.
No amount of automation is going to bring the accident rate down to 0 so through a combination of factors, such as traffic and community design, we can work in tandem with automated driving to get closer. There's still the X factor of our human ability to do really dumb stuff.
I've crossed these myself, but I always look both ways.
Even LIDAR aside, computer vision and a raw video feed should have been enough to have prevented this collision.
When a digital camera records an image, a gamma curve is applied to it before display, which makes up for our bias against the darker portions which the digital equipment does not have. We are very capable of guessing the results of bright conditions but not dark conditions via compressed video.
Moreso, these cars should not be using consumer CCDs with compression. They should be utilizing the full possible scope of video.
See: https://en.wikipedia.org/wiki/Gamma_correction
Gamma correction makes up for a bias against darker portions in the display, not in our eyes. It's a holdover from the CRT days where the change in brightness between pixel values of, say, 10 and 11, was far less than the change between 250 and 251. Human eyes have excellent low-light discernment which is why 'black' doesn't really look black and you can make out blocky shapes during dark scenes on some DVDs.
Your assertion about the origins, however, are at odds with what I have been taught, my understanding, and all the supporting info I am finding in a quick search. My understanding is that luminance values from a sensor have something of an empirical scale but I’m sure this no complete explanation. I am speaking from my working knowledge. I can’t find anything supporting that it is simply a fix for discrepancies between display types. Can you link to something or explain what I am missing?
Certainly better than any camera mounted on a dashboard.
It's honestly a bit surreal how the pedestrian appears out of the splotch of pure darkness in the frame. That's low dynamic range and resolution (or high compression) at work, not how light behaves in reality.
https://i.imgur.com/AlO4h7p.gifv
I figured that light in front of the car was mostly just messing with the camera but that driver sure didn’t see that pedestrian either. I’m willing to give a human driver the benefit of the doubt here and say that even with eyes on the road and hands on the wheel the outcome would likely have been the same. The pedestrian was not highly visible - no reflectors, dark clothes, it’s really hard to see people like this.
unless their phone was showing video of the road in front of them, I don't know why they would have seen her.
The eye can gain a lot more stops through adaptation (irising, low-light rod-only vision), but those mechanisms dont come into play when viewing a single scene -- and cameras can also make adjustments, e.g. shutter speed and aperture - to gain as much, if not more, range.
I'm concerned about poor scotopic adaptation due to the rather bright light source inside the car - maybe it's the display he's looking at. I see a prominent amount of light on the ceiling all the way to the back of the car and right on his face. It's really straight forward to collect the actual scene luminances from this particular car interior and exterior in this location, but my estimation is the interior luminance is a bigger problem for adaptation than the street lights because the display he's presumably looking at has a much wider field of view, and he's looking directly at it for a prolonged period of time. It's possible he's not even scotopically adapted because of this.
And also why is he even looking at the screen? He's obviously distracted by something. Is this required for testing? Ostensibly he's supposed to drive the car first. Is this display standard equipment? Or is it unique to it being an Uber? Or is it an entertainment device?
Retest with an OEM lit interior whose driver is paying attention. We already know the autonomous setup failed. But barriers are in place than also increase the potential for the human backup driver to fail.
What the eye IS doing is some kind of HDR processing, which is much better than the gamma and levels applied to that video. I bet a professional colorist could grade that footage to make it a much better reflection of what the driver could see in the shadows - even with a crappy camera, you can usually pull out quite a bit of shadow detail.
Like a camera, your eye also has only so much dynamic range. So if those street lights are bright enough, or your interior lights are too bright, you might have nearly zero visibility in those shadows.
But it is certain that a self driving car "should" be able to see. Even two cheap digital cameras one tuned to see the darker range and the other brighter should easily see in these type situations.
Sounds a lot like rods and cones in our eyes, huh?
There's another difference with eyeballs that would almost certainly have helped here - the low light sensitive peripheral vision that the rods provide is also attuned to movement, we're more sensitive to movement in peripheral vision as well as being better able to see in low light.
Eyeballs are pretty good at night vision once adjusted, but good high sensitivity cameras can be much better. And let's not get started on LIDAR/RADAR... it seems clear to me that this was not a sensory deficiency, it was poorly designed/tested software.
We typically cant see much detail in the scene out of our small region of focus, but you can bet if a tiger appears from behind a tree our visual system will scream to the brain _look over there right now!_
Our eyes and our entire visual processing system is very much not "just like a webcam, but made out of meat".
The only thing that I think was the cars fault was that the car is programmed to drive when the driver is driving around distracted. There is no point to a human driver sitting behind the wheel of an autonomous vehicle if they aren't paying attention.
People need to understand that self driving mode isn't a freedom from the responsibility of driving safely. Rather its a tool to help ensure that driving statistically becomes safer as more self driving vehicles find their ways onto the road.
Hopefully someday all cars will be self driving and dangerous hazards/traffic reduced to the point that they are virtually none existent rather than being towards the top of the list of "preventable death" and "things humans don't want to waste most of their time during the day doing".
I have a dashcam, and I've seen night videos from it.
In fact, the picture from my dashcam seems much better than this low quality mess, but still night videos from it come out much less visible than reality.
I've tried to rewatch some parts of videos later, and I find I was able to see much more detail on the sidewalk and on the periphery than was captured by the dashcam. Everything gets blown out in the night videos by the headlights.
I've personally driven down country roads without any lighting except my headlights and saw deer poking their head out of the woods a ways away for which I slowed down in case they darted across the street. Someone slowly walking their bike would be trivial.
Reminds me of this video of a Rally driver racing with malfunctioning lamps https://youtu.be/HwyRS_6Uqn0?t=2m36s
The video makes it seem impossible but afterwards in the interviews the driver said it wasn't too bad after his eyes adjusted. He did have some issues with his own lamp blinding him which lead to errors. (He actually won this stage.)
As far as I'm concerned Uber's software/hardware is completely at fault and not ready for public testing. I'm uncertain how much better everyone else's tech is but Uber's typical carefree approach has ruined it for everyone.
There are consumer level dashcam that can shift up to 12800 ISO which can create a fairly distringuishable picture with ambient moonlight.[1]
Canon builds sensors with ISO's in the millions which should be able to see distinguishable shapes without ANY light. [2]
[1] https://youtu.be/hHU-hWG5DDk?t=5m48s [2] https://petapixel.com/2015/09/13/this-is-iso-4560000-with-ca...
The headlamps may have been functioning, but they appeared to be aimed way too low. You can see that the car is able to traverse the distance lit up by the headlamp in about a second at 38 mph. If the headlamps were aimed properly, it should light up the road about 5 seconds ahead of the car.
A system with this rule baked in would be driving slower.
People adjust the way they drive based on what their environment is doing, how well their equipment is working and their own alertness. Except in the extremes we should not accept misconfigured equipment as an excuse. And if a system detects that there is no acceptably safe speed for it to go then it should not move at all.
Arguably, the system should detect a misconfiguration like this when the car is turned on and not allow the car to be driven until the problem is fixed.
They didn't. Either because they are negligent or because the footage is misleading and the system saw the whole thing but did nothing.
I'm reluctant to infer exactly what a human eye would have seen in that situation. I have absolutely driven down streets in suburbia where the gap between street lights was large enough to make them quite dark, and that video was an example of exactly what I was afraid of happening whenever I drove down those streets (though admittedly my fear was hitting a white tailed deer).
I think it might also be fair to argue that the car's high beams were not on (but again, that shouldn't matter because of LIDAR, right?).
I'm not confident even an above average human driver would be able to avoid that accident, even if good eyesight gave you an extra half second to respond. Dark clothing and no reflectors means that person was definitely invisible to both the camera and the driver for some time after they would have been visible in daylight.
I've had a couple of situations where someone appeared close to my line of travel with low visibility clothing (at night) that scared the living shit out of me, and they weren't trying to cross the street.
To be clear, I am not blaming the victim here, but do wear high visibility clothing when you're a pedestrian near high speed roads at night.
The seemingly random design decision of many runner manufacturers to embed tiny reflector strips in their shoes have no doubt saved countless lives. And their owners would probably be none the wiser.
Of course it makes sense there where daylight may be hard to find half the year, however even in Australia, once it is dark the darkness is the same.
And I haven't seen a single government initiative to increase visibility awareness - most people are completely in the dark. (Sorry)
Riding shared bike trails in Melbourne at night on the commute home, this is something I think about often in the "winter" months. Peds may hate the strong glare from my LEDs, but it is the only thing the has half the chance of making out ninjas against the frequent sports ground stadium floodlights the path goes by.
That is not the whole reason, it is one of many reasons.
> To be clear, I am not blaming the victim here, but do wear high visibility clothing when you're a pedestrian near high speed roads at night.
Yes, stupid homeless person.
A similar thing (no fatalities, just a shopping cart pushed by homeless people) happened to me. Ever since then, I have learned to be much more aware of situations like this (tunnel of light surrounded by darkness).
This just shows that Uber's tech is bad and that they let it on the road shows that their culture is still at least partly rotten.
I don't think Dara is the do gooder that some people are making him out to be. His primary motivation seems to be to usher Uber to an IPO. IMHO, if he actually had ethics, he would be front and center on this. Your company just killed someone. Where are you?
Amusingly, the law also says that manufacturers have to produce headlights that cast light out far enough to leave you adequate stopping distance at 60mph. Almost no headlights on the market currently do that.
Not a counterpoint, just a tangent that I find sadly amusing.
You will frequently see dash cam footage and night photography blow out the relative highlights and blacken the relative shadows.
This is because (cheap) hardware does not have the same dynamic range as human eyes, especially at night. So "properly exposed" it has to make a call to capture light values in the middle somewhere. Those light values too far out the top it interpreted as white, those out the bottom it interpreted as black, created an artificial high contrast version of what a human eye would see.
This is pretty intuitive, generally when we're driving down the road with our lights on, we aren't literally moving between pools of black, often in many urban areas I'll even forget to turn my lights on because I can see well enough.
You MAY be able to get a VERY BAD interpretation post processing of what a human would see by increasing the brightness of those pixels near the black threshold.
[1] https://goo.gl/maps/gpugzAZKxcS2
The sign directs people to use a crossing, which is some 100 meters away at the lights around the bend.
So either way the software failed:
-If AI misjudged Lidar information and didn’t compute the slow moving pedestrian it’s a fail
-If it didn’t have enough computer vision space it should have slowed down
Possibly in the second scenario the human test driver is at fault too because he should have noticed bad condition and hit the autopilot kill switch.
Also - the car is driving way too fast.
I did some driving tonight and paid close attention to when I naturally slowed down - and albeit I'm probably on the higher curve of good drivers in that I don't tailgate, drive the speed limit and generally slow much slower than the speed limit when conditions are poor (fog/rain/snow, night, slick/wet roads, near curves/hills where I can't see the road). I noticed that many of the times I naturally slowed down on the roads here I slowed considerably under the speed limit by 10 to 20 MPH in some areas. It seems this Uber SDV is generally going as fast as it is possibly allowed to regardless of what it can see.
With those, the driver would've seen her from a mile away.
For anyone who's interested, try taking your phone with the camera app open into a dark room and comparing what you see to what's on the screen. Which shows more detail?
https://i.imgur.com/eSre3hL.png
[1] https://www.youtube.com/watch?v=1XOVxSCG8u0
I'm also very (sadly) surprised that she crossed that kind of road at night without hurrying or reacting to the sound of cars approaching.
This video also shows another point I made recently in a conversation. People need stimulus to keep them alert and focused. I don't think it's at all reasonable to expect someone to sit idly with almost no interaction or responsibility and expect them to stay alert. The human brain doesn't function that way.
The other option is swerving which might have been a possible solution here as well, but that would also have been highly dangerous for the people in the car as well at those speeds, within that timeframe, possibly causing >1 fatality or serious injury.
Regardless I'm very much speculating here regarding reaction times based on watching a low quality video, I'm really looking forward to expert analysis here rather than speculation on the capabilities of LIDAR/Radar + computation speed at 60km/hr... even considering a human driver would have 100% hit this person.
> Good thing about radar is that, unlike lidar (which is visible wavelength), it can see through rain, snow, fog and dust - Elon Musk
The major car companies have even developed the technology to also allow LiDAR to see through snow/rain without the previous refraction problems: https://qz.com/637509/driverless-cars-have-a-new-way-to-navi...
My question is given it could detect the jaywalking object (regardless of visible light) within the very very short timeframe at those speeds, on what looks like a highway, I'm curious if it's rational to expect even the future ideal machines (say 5yrs from now) to have been able to react in that situation.
It's not as obvious as people here are pretending it is.
Yet even then we now have a previously unknown model to test our machines on to prevent it from happening again. Given a human would 99%+ of the time not have seen this woman in time, then I believe we'll at a very minimum be better off as a society as a result of this... as wrong as that sounds, because it's now a high-priority dataset, not just a sad story in the local news (if even) we'll forget about tomorrow as it would be with a human driver.
I'm far from convinced that a human would not have seen this woman in time.
See all the comments in this thread about how the dashcam footage is much worse than reality, and even one person who drives that road regularly saying it's not that bad visibility-wise.
I think if I had seen that lady slowly walking her bike onto the road in my adjacent lane, I would have slowed down for sure. And from seeing my own nighttime dashcam videos, I think I would have seen her. She's the only object nearby, on a fairly straight road with no adverse weather conditions. I would have seen someone pushing a bike onto the next lane.
Maybe I would have hit her still, but I would have slowed down for sure.
If an autonomous vehicle cannot detect pedestrians crossing a slower-than-typical road with enough time to at least not kill them, it shouldn’t be on the road. If that means uber can’t drive autonously at night, too bad for them.
To be fair, the law currently is very permissive to drivers, and a human may not have been deemed at fault. Despite going 40 in a 35 zone, when (due to reduced visibility) they actually should have been going 25. You are supposed to go only as fast as you can stop, given current visibility. Regardless of the speed limit.
There's also a steering wheel. (Why is everybody here missing this?!) I could totally see it having moved out of the way.
https://www.youtube.com/watch?v=--xITOqlBCM
also check out the one at 1:06 - pilot detects slightly before than the autopilot but the dashcam is still pitch black
Of course, the Uber vehicle did not take any action at all. It doesn't seem to have ever realized that there was a solid object in front of it. Without that, collision avoidance is impossible.
I've also read that the last speed sign was 45mph before this accident. I used 40mph as it was between the 35mph sign that was coming up before the hit and the 45mph one before it.
The LIDAR sensor[1] being used here can pick up targets up to 120m away. I'm not sure about the RADAR or vision systems also in place, but even LIDAR alone should have been able to easily pick out the pedestrian with plenty of time to come to a full stop.
This is clearly poorly designed autonomous driving software, not a sensory deficiency.
If you can't see far enough to be able to avoid something in the road, you're simply going too fast. That should apply to machines, but it already applies to humans.
I believe it's entirely possible for a robot to solve this problem with proper Radar and maybe LiDAR going forward. But I would be extremely skeptical about anyone claiming a human would have been at fault...
If you can't see where you're going, you need to slow down. Does that seem so unreasonable?
http://www.zacharlawblog.com/2015/11/whos-at-fault-in-an-acc...
> So, should an accident occur between a jaywalker and a car---if shown that the driver could have/should have seen the person and could have/should have been able to avoid, then without question the driver can be held responsible.
https://www.nicoletlaw.com/blog/2015/07/what-happens-if-a-ja...
> To a large degree, it comes down to the driver's ability to avoid the accident. If a jaywalker steps right out into the car's path and is instantly hit, the driver will usually not be held responsible. It will be determined that the pedestrian caused the accident.
> However, if the jaywalker strolls into the street a few hundred yards ahead of the car and the driver does not slow down or swerve, the driver could be held responsible. Even though jaywalking is illegal, drivers are expected to take reasonable action to avoid crashes when they can, even if they feel they have the right of way.
> Negligence also comes into play if the driver should have seen the pedestrian but did not. For instance, a driver who is texting and driving may look away from the road and not see someone step into the street, hitting them with the car. The driver could argue that the road was clear and that the person shouldn't have been there. While that may be true, he or she could still face charges.
However, if the jaywalker strolls into the street a few hundred yards ahead of the car and the driver does not slow down or swerve, the driver could be held responsible.
This was clearly not a case of "someone stepping out right in front of the car", since they were more than halfway across the rightmost lane, walking a bicycle.
Edit: This rule is merely a variation on the universally accepted one that says that if you rear-end someone in another vehicle, you're almost universally at fault (unless it can be proven that they acted in such a way that the collision was unavoidable.) The logic being that if you could not avoid a collision, you were going too fast for the distance you had to the vehicles in front of you.
Are you suggesting that drivers should be less liable for running into stationary objects than they are for running into other vehicles? That seems absurd to me.
Seems more likely that it's a software problem. Especially given the rest of Uber's behavior, I wouldn't be surprised if they're aggressively shipping incomplete/buggy software in the name of catching up to more careful competitors like Waymo.
So yes, LIDAR should have caught this. Easily. So something was clearly misconfigured. And even if the driver had been carefully watching the road, he probably wouldn't have seen her in time.
But I wonder, is there a LIDAR view on the dashboard?
I don't have the link handy, but I was reading a webpage yesterday (related but not about this crash) which showed Google's self driving car's "view" of a road scene - it's clearly painted different color boxes and identified pedestrians, bicycles, other cars - along with "fences" where it had determined it'd need to slow or stop based on all those objects.
Either Uber's gear is _way_ less sophisticated (to the point of being too dangerous to use in public), it was faulty (but being used anyway, either because its self test is also faulty, or because the driuver/company ignored fault warnings) - or _perhaps_ Google's marketing material is faked and _everybodies_ self driving tech is inadequate?
This is going to sound bad, but I hope this is just Uber’s usual criminal incompetence and dishonesty, and not a broader problem with the technology. Of the possible outcomes, that would be the least awful. If it’s just Uber moving fast and killing someone, they’re done (no loss there), but the underlying technology has a future in our lifetimes. If not...
I, for one, certainly won't be betting against you there...
https://www.wired.com/story/tesla-autopilot-why-crash-radar/
https://www.theguardian.com/technology/2016/jun/30/tesla-aut...
If that's your idea of adequate, you'd be safer just vowing to get drunk every time you drive from now on, since a modest BAC increases accident rates, but not by a factor of FIFTY!
A website that "does something weird" when you use a single quote in your password... That _could_ be "the only situation you have to worry about". It is _way_ more often a sign of at least the whole category of SQLi bugs, and likely indicative that the devs are not aware of _any_ of the other categories of errors from the OWASP top 10 lists, and you should soon expect to find XSS, CSRF, insecure deserialisation, and pretty much every other common web security error.
If you had to bet on it - would you bet this incident is more likely to be indicative of a "person pushing a bicycle in the dark" bug, or that there's a whole category of "person with an object is not reliably recognised as a person" or "two recognised objects (bicycle and person) not in an expected place or moving in an expected fashion for either of them - gets ignored" bug?
And how much do you want to bet it's all being categorised by machine learning, so the people who built it cant even tell which kind of bug it is, or how it got it wrong, so they'll just add a few hundred bits of video of "people pushing bikes" data to the training set and a dozen or so of them to the testing set and say "we've fixed it!"
I think this is a very good possibility considering that autonomous vehicles is the goal of the company and they're racing to get to that point before they run out of investment money. They have a lot of incentive to take short cuts or outright lie about their progress.
(2016)
1. System was off
2. Point clouds were not being registered correctly (at all!)
3. It was actually in manual mode -- safety driver didn't realize or didnt react fast enough.
4. Planning module failed
4. Worst outcome in my opinion: Point cloud registered correctly, obstacle map generated correctly, system was on, planner spit out a path but the path took them through the bicycle.
From the reports of cars running red lights and then this I would imagine they have an extremely high level of "risk" (what it takes for the car to take actions in order to avoid something/stop) that is acceptable.
What would be far worse than a hardware or sensor failure would be to learn that Uber is instead teaching its cabs to fly through the streets with abandon. Instead of having cars that drive like a nice, thoughtful citizen we'll have a bunch of vehicles zooming through the streets like a pissed of cabby in Russia.
It is possible that a screen provided a clearer (somehow enhanced) view of the road, so I'm reserving judgment for now.
Of course using that screen could be a grave error if the screen relied on sensors that missed the victim. But if it appeared to be better than looking out of the windshield then that points to a process problem and not necessarily a safety driver inattention one.
I don't know about that.
1. Count the lane markers. (It looks like a astute driver could have stopped? Plus, most drivers might have picked up the reflection a bike gives off when head lights are flashed on it? Just a flash of light bounced off metal, or reflectors is enough to get my attention. There are times at night where I just notice a slight reflection in the peripheral of my vision, and I know to precede with caution, or slam on the brakes. It's usually an animal darting across the street. I don't think I've ever had to slam on the brakes for a bike.)
2. The woman looked at the car while it plowed onto her. She had a look of astonishment? Like why is this car running into me?
3. Uber is in deep trouble.
In production, having a LIDAR display would be pointless. But for testing, it might be useful. But maybe better would be to tell drivers to keep their eyes on the road.
_Ubers'_ self driving trials should be banned since they don't seem to exercise enough caution. That shouldn't hold the progress of competitors back.
This is pretty much the worst case scenario.
This was taken by a video camera - which has a much lower range of detectable brightness then the human eye. The pitch-black spots in the video are almost certainly not pitch-black if you were to look at them.
I always explain it to friends starting out "you need to assume that just around every corner there's a stationary shipping container that's fallen off a truck. If you cant stop in time by the time you see it - it's your fault for going too fast."
Either the woman had just said the words "Beam me down Scotty" and materialised there like the video feed footage implied - or she'd been in view for quite some time - at least enough time for a person pushing a bicycle to cross en entire lane. If Uber's tech is only capable of detecting her as she "showed up in the field of view right before the collision" - their tech is not fit for purpose and should he held 100% at fault here. (Not that doing that will help her family or friends, but it might help stop Uber and their competitiors from doing it again...)
It's also entirely possible there was an egregious bug. This video doesn't really tell us much.
That said, Arizona in the summer is going to play havoc with lIR and thermography in erms of false positives and negatives. The sensor suite probably should be using lIR at night for this reason and the switching it off in the day. But given Uber's history, the lack of lIR reeks of cost-cutting.
Air has such a low thermal mass that it doesn't measurably affect most IR sensors. Hot pavement could be a potential issue, but that shouldn't have a major effect on forward-facing sensors.
Besides, it's only March. Even Arizona isn't that hot yet.
Did you ever use a thermal IR camera ? What you're saying only apply to cheap chi-com cheapo"IR" CCD (the ones you find in home security), not the FLIR/military-grade stuff.
I'm not sure, pls look that pic https://imgur.com/a/VfBck, you can clearly see there exists at least 10-15 meters b/w them right at the time when she pops up. Now I don't know the speed of the car, but I'd wager, a human driver (if s/he was alert) would have attempted a breaking at that moment.
For instance, if law enforcement had testimony and other warrant allowing things that indicated that a user had stored some vital secret plan in a password field what could the government compel a company to do, assume the disk it relies on is also encrypted for extra fun time
1. Hand over the physical disk
2. Hand over the disk image
3. Hand over the decrypted disk image
4. Hand over the unobfuscated (enc or hashed) string of interest from the decrypted disk image
5. Compel the company to decrypt the string if it was encrypted with a common algorithm (i.e. AES)
6. Compel the company to decrypt the string if it was encrypted in a proprietary manner (i.e. in-house custom encryption)
7. Compel the company to devote resources (how much?) to brute force a one-way common hashed string (i.e. bcrypt)
8. Compel the company to discover a hash salt assuming the company doesn't store it locally but may be able to procure it from the user to do the above.
9. 7 & 8 if the one-way hashing algorithm is proprietary (and weak) and the company raises objections that the process of breaking this string will reveal key components of how the algorithm works (i.e. the hash is just md5(string) XOR "IMMA SECRET_STRING")
10. 7 & 8 if the proprietary algorithm is not weak but the company raises objections over trade secrets for other reasons.
It's a bit too early to make that conclusion. For all we know, the equipment was malfunctioning. Which I guess technically leads to your point, but we'll have to wait for the investigation to actually know what failed vs. what met expectations (I worry that expectations and tolerances, as set by the car companies, will be revealed to not be as comfortable as we might assume).
On the subject: this lady I used to know hit someone who ran out in front of her and started freaking out (thinking they were in some serious trouble) until the police told her "you're fine, they were jaywalking".
Because the software is still critically flawed, of course...this only represents a present-day failing, not some sort of permanent obstacle for the future.
Isn't the car supposed to brake to minimise the collision, if the swerving is too dangerous (and it wasn't in this case, as the road wasn't too busy)?
Something is badly wrong there. That should have been detected by LIDAR, radar, and vision. Yes, they need a wide dynamic range camera for night driving, but such things exist.[1][2] They're available as low-end dashcams; it's not expensive military night vision technology.
Radar should pick up a bicycle at that range. The old Eaton VORAD from about 2000 couldn't, but there's been progress since then.
LIDAR has its limitations; some materials, including the charcoal black fabric used on some desk chairs, are almost nonreflective to LIDAR. But blue jeans, red bike, bare head? Expect solid returns from all of those.
The video shows no indication of braking in advance of the collision. That's very bad. There simply is no excuse for this situation not being handled. The NTSB is looking into this, and they should. I hope the NTSB is able to pry detailed technical data out of Uber and explain exactly what happened. In the first Tesla fatal crash, they didn't get deeply into the software and hardware, because it was clear that the system was behaving as designed, unable to detect a solid tractor trailer crossing in front of the Tesla. The result of that investigation was that Tesla had to get serious about detecting driver inattention, like all the other carmakers with lane keeping and autobrake do.
This time it's a level 4 vehicle, which is supposed to be able to detect any road hazard. The NTSB has the job of figuring out what went wrong, in detail, the way they do for air crashes.
Again, there is no excuse for this.
[1] https://youtu.be/gWqzJF9tOhw?t=211 [2] https://www.youtube.com/watch?v=as12rjzCQnY
1. Release video to police (with obvious shots of driver/passenger/whatever not paying attention to the road)
2. Investigation reveals accident was caused by driver/passenger/whatever reaction
3. ????
4. Profit (PR win/rescue)
Why it didn't even appear to try to stop? You got me, refresh rate on the LIDAR? LIDAR flat out being mounted to high and relying on optical sensors instead for collision avoidance of small targets (like a human head)?
I'm guessing, I'd love to see an NTSB report on this.
This doesn't seem like an edge case at all. Pedestrian crossing the road at a normal walking pace, and no obstructions in the way which would block the car's vision. The fact that it's dark out should be irrelevant to every sensor on that car other than the cameras.
Something obviously went terribly wrong here; either with the sensors themselves or the software. Probably both.
Realistically faster sensors should be used to detect obstacles. LIDARs I could find with some cursory googling can run up to 15hz. Computer vision systems can run much faster (I have a little JeVois camera that'll do eyeball tracking at 120hz onboard, I assume something that costs more can do better).
But more importantly, you're vastly trivializing the problem - Standing right in front of it, sure the LIDAR will see the person no problem. Standing 110 feet away (which would be min stopping distance at that speed)? Realizing that, for a LIDAR with a 400' range at 15hz moving at 40mph you get ~7 samples of a point before you're at it... For at least the first 3 frames that person is going to look like sensor noise. At 110 feet that person (which I'm calling a 2' wide target) is 1 degree of your sensor measurement.
It's not that it's useless or broken, more just this a seriously bad case where optical tracking couldn't work and where LIDAR is particularly ineffective at seeing the person because of how it works. More effective might be dedicated time of flight sensors in the front bumpers, unsure how long a range those can get, but they are also relatively "slow" sensors.
I highly doubt this is the issue. I am not sure what Ubers setup is, but even a standard velodyne should have been able to pick that up based on angular resolution.
Updating this with math not done at midnight:
This is based on the velodyne LIDAR specs I could find last night with some quick googling: - 400' range - .04 degree angular resolution - 15hz max update rateIf you have more accurate real world experience with these sensors and can share more accurate performance characteristics I can update.
These calculations were done assuming a vehicle moving at 40 mph. The stopping distance at that speed is about 110ft. I computed the pixel size by assuming 1 measurement = 1 pixel giving me 9000 pixels per 360 degrees.
http://velodynelidar.com/docs/datasheet/63-9194_Rev-G_HDL-64...
Thats the one LIDAR Uber seems to have matching pictures.
5Hz - 20Hz full round sampling rate, lets assume 15 Hz.
The resolution in the horizontal plane is dependent on rotational speed, so at 15 Hz it should be 0,26 degrees.
(0,35/20*15 = 0.26)
For the woman height the angular resolution is 0.4 degrees no matter the rotation speed.
Id est, she would have been atleast one pixel wide from 400 feet and about 2 pixels high and growing in size if we assume 2' wide.
(Not counting bike).
I really see no exuse for Uber messing this up that bad. The LIDAR can't have missed a potential "obstacle" when it got closer, even if the car wouldn't classify it as a human.
These are NOT big targets, they could easily have been mistaken for noise and filtered out. All of the LIDAR data I've ever seen has been fairly noisy and did require filtering to get usable information from it. And given the number of frames they get maybe their filtering was just too aggressive.
But, as it got closer and what the computer though was noise was on about the same place a sane obstacle finder should have given a posetive match. Maybe at 30 - 40 m worst case?
At 142 feet the woman probably had (assuming she was 5.5'):
asind(5.5/142) = 2.21* => 2.21/0.4 = 5.5
So between 5 and 6 "scanlines" going from left to right over her.
Assuming she was 2' wide that's 0.8 degrees which would be 2 to 3 pixels in breadth according to your spread sheet.
That's between 10 and 18 pixels (voxels?) that stand out clearly from the flat road around it, exluding the bike.
If you wan't to get an idea of how LIDAR data looks Velodyne has free samples and a viewer for less resolution models.
http://velodynelidar.com/downloads.html
It pretty hard to identify obstacles far off, but you will still see there is something there. It's especially easy to identify obstacles that are vertical.
As she got closer, she would eventually show up clearly on the LIDAR data. But since the car never slowed down or went left, it didn't notice her at all even at point blanc (or did see her but failed to do anything about it).
Yeah, I'm willing to accept SOMETHING bad happened here, as I said I really just wanna dissuade people from the notion that LIDARs will see all obstacles all of the time. Not going to say the car acted perfectly and it was sensor failure, but definitely willing to say that the LIDAR probably COULD see her but not as well as people would assume.
Really, I think this was a case of the car over driving their effective sensor range, same as what happens when you're on a dark road and a deer runs into the middle of the road, you simply can't react fast enough by the time you realize the danger is there. Computers are fast but they aren't perfect.
What I'd be particularly interested in was if the computer saw her and if it did the calculation - I can't stop safely in this distance, and decided to just hit the obstacle because it was "safer". At that point we start getting into ethics and this problem gets a lot murkier.
[1] http://velodynelidar.com/blog/128-lasers-car-go-round-round-...
There's so much confusion here, about the capabilities of these systems. People think that a combination of better sensory perception + faster reaction times suffices to drive in the chaos of the real world. That's not so. Sensors and fast thinking won't get you nothing if you can't think right. You have to be able to know what the things are that your sensors detect, and how to react to them.
It's perfectly possible that the Uber' car's LIDAR detected the lady crossing the road- but the AI just didn't know what to do about her and simply did nothing.
This is a situation though where the LIDAR should have clearly been better than it was. Maybe it was in a strange state after having seen all the lights and then complete darkness, looks like they were headed north on Mill Ave over the bridge [2] just past the 202 where it is indeed very dark at night and probably the spot right here [3] which matches up with the building in the background, the other way is South and is busy/urban by ASU. They had just crossed a lit up bridge, then dark underpass, then into this area [3]. The area that it happened in [3] does have bike lanes, sidewalks and a crossing sidewalk close by [4] but is by a turn out so not a legal crossing however there are lots of trails through there.
This video is worse than expected by far and may be forever harmful to the Uber brand in terms of software.
In AZ I usually see the self-driving cars out in the day, maybe there is lots of night tuning/work to do yet.
[1] https://i.imgur.com/kwxjW36.jpg
[2] https://goo.gl/maps/ey1RA47tKBJ2
[3] https://goo.gl/maps/gpugzAZKxcS2
[4] https://goo.gl/maps/Ni18GfjMP962
Also, the woman was right under a working street lamp. And as was stated in an earlier article the car continued on at 38 mph after the accident. The bike ended up 50 yards down the street.
EDIT: "That spot is east of the second, western-side Mill Avenue bridge that is restricted to southbound traffic, and east of the Marquee Theatre and a parking lot for the Tempe Town Lake. It can be a popular area for pedestrians, especially concertgoers, joggers, and lake visitors. Mid-street crossing is common there, and a walkway in the median between the two one-way roads across the two bridges probably encourages the practice."
"Pedestrians can cross a street without using a crosswalk in many instances without risking a jaywalking ticket, but Arizona law requires pedestrians not using a crosswalk to yield to traffic in the road."
http://www.phoenixnewtimes.com/news/cops-uber-self-driving-c...
If you zoom out on google maps you will see some of the trails. Note the sidewalk/pathway, it is no pedestrian but has paths for them so it sends mixed signals.
If so, then it's really time to do what was done for GPS and declassify it for use by the general public. It's a public safety/public good issue.
[1]: eg https://www.amazon.com/FLIR-Systems-III-320-Thermal-Detector...
With a person, though, you are seeking to protect everyone, so the tradeoff swaps in favor of swerving, because the person in the car next to you is far more likely to survive a collision.
Download one of those reaction time apps for your smartphone, see how well you do when you actually expect something to happen.
If that crash detection can detect shit going on two cars ahead why couldn't LIDAR see that?
having said that. wth was she doing?
or so it would seem... ;)
1. A software bug failed to recognize the obstacles, or misclassified them, or it fell below some probability threshold.
2. LIDAR didn’t work at the time, and the car did not shutdown.
3. The victim‘s clothing absorbs the LIDAR‘s wavelength pretty much completely, such that it appeared as a „black hole“ and was ignored by the algorithm since this occurs commonly. Unlikely though since the bike itself would surely have registered?
4. It’s hard to see on the video, but is the car going up a slope? In that case, if the LIDAR didn‘t look up far enough, it could have failed to see the victim for optical reasons.
A human is not an "obstruction", dammit. I mean, literally- it's not like hitting a wall. The driver's life will never be in danger and the care may not even be significantly damaged. There's a very special reason why we want self-driving cars to avoid humans, that has nothing to do with the reason we want to avoid obstacles. And because this special reason is very, very special indeed, we need much better guarantees that self-driving vehicle AI is extremely good at avoiding collisions with humans, than we do for anything else.
My guess is that the algorithms have never met a person crossing the street with a bicycle during night time so they just ignored it or considered it to be a glitch.
You can have to approaches regarding labeling driving situations. Either you label with positive tags the situations where the car needs to react. Or you label with positive tags the normal situations when the car does nothing.
Depending on the two approaches you can have a car that kills pedestrians that appear in weird circumstances. I also bet a pedestrian that ducks in the middle of a lane would 100% be killed by a car. Or two people having sex while standing in the middle of a lane.
The other situation you have cars avoiding invisible obstacles that may appear due to some aberrations from sensors (which are far from perfect).
I would be very surprised if there is no thermal imaging in autonomous vehicles.
Actually a human driver would be expected to have less visual trouble in this case. People's eyes are far more adaptable to low light conditions than a camera's video. If you've ever tried to take a picture on a visible night using your phone, you've seen this effect.
> When I argue for automated driving (as a casual observer), I tell people about exactly this sort of stuff (a computer can look in 20 places at the same time, a human can't. a computer can see in the dark, a human can't).
Except that the computer did not do that in this case. This car also uses LIDAR and should have noticed the pedestrian long before the accident occurred.
> Yet this crash proves that all the equipment in the world didn't catch a very obvious obstruction.
Either the sensor equipment or the software was defective, otherwise the pedestrian would have been detected.
The LIDAR can catch anything it wants. If the car's AI doesn't know how to deal with it, it won't.
also there are videos showing the real conditions with simple smartphone cams, e.g.: https://www.youtube.com/watch?v=1XOVxSCG8u0
Imo this is a clear attempt to shift public opinion. Also for everybody it should be clear, that a car should only drive as fast to be able to break once something comes into sight. For the whole industry it is very unfortunate, that some just don't understand the responsibility that comes with new technology and it's limitations.
Mirror: https://streamable.com/vllgl
She wasn't wearing anything visible at a pitch black street at night. It seems like there was about 7 meters before her shoes were even visible.
I've got a 2013, and am thinking about trading in.
Insurance fraud, possibly. Depending on jurisdiction if you rear-end someone you could automatically be 100% at fault (assuming the fraud is not discovered/proven)
The automatic cruise control is great for freeway and some street driving, but don't expect it to brake very smoothly / like a human. I consider it outsourcing part of my concentration.
Lane assist is nice, but it won't auto-center -- if you were take your hands off the wheel on a straightaway it would "ping-pong" back and forth. I mostly like it on long drives, reduces the amount of effort on bends.
like travelling down a virtual tube
The other thing this system does is to provide adaptive cruise control. If I'm behind a vehicle that results in slowing down and then switch lanes (to where there is another vehicle in front of me) the car seems to think it can resume speed and slip between the two vehicles. I've come to expect that too and disengage the speed control before switching lanes.
It also provides a warning when approaching the lane markings (unless I have indicated a lane change.) Occasionally it triggers on seams in the pavement. It also provides steering input if the land deviation increases. I've only experienced when I tested it in purpose. I'm not sure it would reliably keep the vehicle in the lane.
Overall the system seems to be pretty good and though not perfect, is a net asset.
I've got to side with the people who want no auto-driving until we have always-better-than-human auto-driving. When cars only have back seats, and no driver controls beyond a way to state your destination, auto-driving will be acceptable.
Driving is all about predicting the future. Think of every time you've been able to tell that someone is going to change lanes even though their blinker is off, or slowed down when a ball bounces into the street because you know there's going to be a kid following it. If the car isn't capable of that, it's not ready for public streets.
I am obviously no AI expert, just what I know from loosely following the field. But things like this cross my mind from time to time.
Actually many states now require by law that you get as far as possible from a lane with a disabled vehicle, as many human accidents have happened.
I am convinced uber has been basically pretending to do the mountains of careful and sophisticated crap waymo actually has gone to great lengths to do, and is just racing to put anything out so they can keep stringing investors along as far as they can before the jig is up. Well the jig is up now.
Back to Uber, the number I hear is that they are striving to go better than 13 miles/intervention to prevent an incident. For Waymo this is over 5000 miles. I'm convinced too.
If Uber can't match a $25,000 off-the-shelf floor model mass-market midsized sedan for collision avoidance, it's hardly a self-driving car.
On the other, the operator was clearly distracted regardless of if they would have been able to avoid this.
As someone that enjoys racing cars and other types of high performance driving I feel like I can pretty confidently say this isn't even remotely a realistic statement.
You're grossly overestimating human response times. Even if we're ignoring response time and imagining the driver instantly turning the steering wheel, large SUVs like the XC90 simply can't generate the lateral acceleration required to move the vehicle clear of the pedestrian in the time and space shown in that video.
I would say it's a deliberate attempt to manipulate if I didn't also strongly believe ignorance on part of the police department has lead them to believe that autonomous cars could even exit a parking lot without data from many more than this one camera, not to mention the vastly more useful LIDAR on top.
(That's before you consider the video angles shown here are just for dashcam purposes. The real cameras for the autonomous driving are in the sensor array on top of the roof)
Probably not, but it isn't like the inputs to the self-driving models really need to be better than that. Lower resolution helps your processing time a lot and there's little point in having an FPS higher than your processing time.
If they're actually feeding data at 15 FPS into their ML model, then what the fuck were they expecting? Correlating movements at those framerates would be nigh-impossible.
Relying on ML for this is already comically irresponsible, but that'd just be ridiculous.
Where does this figure come from?
Human eyes are almost comparable in terms of a framerate based on the neuron spiking rates, which are somewhere over 250-500Hz max. Obviously that's not directly comparable though, but it gives an idea of how well we can deal with moving objects.
So I guess this is the ultimate litmus test if the culture at Uber has changed. They let this video stand and I don't personally think they should be allowed to drive another metre autonomously on public roads.
I would be shocked if we see Uber resume testing any time soon, if at all.
If Waymo understood how to stick a knife in they would have replicated this scenario yesterday and released a video. Hell, you could take a Mercedes S class with night view assistant and it would spot this, no problem.
If there is something now that's going to help with the public perception of this cars that people claim to be autonomous, it's people like you just quitting trying to defend this and care about the deceased ATM. The software and hardware was sub-par, and the driver of a fucking TEST DRIVE was not looking at the road, let aside having hands ready on the steering wheel. The driver's feet were probably wandering around relaxing besides the pedals. TBH I don't give a flying fuck to the public image of autonomous (!) vehicles ATM.
There was a car coming. She shouldn't have been in the road, period.
“Not trying to blame the victim... but this is a teachable moment not only for drivers, but for cyclists...”
... it would be a true statement, which is why I didn’t say the GP was making a false one, but a normal native speaker would at least recognize it as a strange thing to say.
Cyclists should wear helmets, and the cyclist certainly is partly to blame. But no one was suggesting that the cyclist is guilt-free, so the actual effect of the statement is to try and draw a false equivalence.
It’s like saying “sure, global warming is real, but let’s not forget the effects of gradual and natural cyclical climate change.” No educated person in the discussion “forgot” the second, but by phrasing it this way you’re implying we should be paying equal attention to a large effect and a much smaller one.
It seems pretty obvious to me that being a mindful pedestrian is simply a matter of self preservation
Difficulty of looking both ways and pausing for a second before you cross the street: 1 unit. Difficulty of getting getting every single driver in any area where pedestrians have the right of way to drive slow enough that they can make a safe stop assuming any pedestrian can legally dart into the street without warning: 1,000,000,000 units.
And yet I've seen plenty of people turn 90 degrees across a street at their usual walking pace with no pause and with their eyes on their phone and headphones in their ears.
If you want to spin that particular chamber of probability because legally you're technically protected, honestly I feel worse for the driver who has to live with that memory now and wonder what they possibly could have done to prevent it short of just never driving a car at all.
You are definitely correct about even then you should check. And once you check and see it is clear...keep checking as you cross.
An acquaintance of mine from college was killed crossing Colorado Blvd in Pasadena, California late on a Friday afternoon, in a crosswalk at a fully controlled intersection, with the cross traffic having a red light.
Colorado Blvd is a major street, and late on a Friday afternoon would have a fairly high density of cars.
The car that hit him was going something like 80 mph. At the time he started crossing, that car would have been 3 blocks away. Even if it had been the only car on the road, at that distance there would be no way to judge the speed, and any car that far away traveling anywhere near legal speeds would be far enough away to not be a danger to any normal pedestrian crossing.
With the other cars that were on the road on a late Friday, it probably would not even be possible to see the car that hit him when he entered the crosswalk. There would have been several cars stopped at the intersection obstructing his view, plus cars at the intersections further up the road, or in transit between the intersections.
His only chance would have been to keep checking oncoming cars as he crossed, even after all the cars actually at or near his intersection at stopped.
Almost no one does that. Mostly once we see everyone nearby stop we just concentrate on cars that are turning and so might enter the crosswalk even though the light is red (assuming we are in a right turn on red jurisdiction).
Lesson #1: Treat each step as you cross the street as if it is your first step into the street. Do your full "is it safe to cross" scan constantly.
Lesson #2: Cars very far away at the time you start to cross can make it to you before you finish, even if traffic seems heavy enough that there is no way they could go fast enough to reach you. Your scan needs to look out farther than you think it needs to.
The girl who ran a red light three feet in front of me while looking at her phone would agree with you -- that is, if she even realized she had done it. (I was in the crosswalk and I stopped when it became apparent that she wouldn't)
You have a self-responsibility, which most people act on (self-preservation). But as a driver you have a responsibility to pedestrians who can be killed by the machine that you are driving. That is the greater responsibility and why active care for pedestrians should be one of the highest regards of a driver (or autonomous driving system).
No kidding. This might be a somewhat controversial opinion, but I think the elephant in the room here is this general "pedestrian has right of way" notion. It's much easier for pedestrians to watch out for and evade cars than the other way around, and yet we seem to insist the opposite? That seems rather backwards and contrary to the laws of physics.
Still... IR should have seen this.
Not avoiding the collision but perhaps lessening the damage?
It looks like the car doesn't even try to slow down.