I'm trying to figure out if I can keep my current car until autonomous vehicles become broadly available. Anyone here have an informed opinion on when that will happen?
I don't think that a conversion will be easy. In addition to all of the necessary sensors and automated controls, you'd need to find someone willing to either do the conversion for you or sell you the parts needed to do it yourself, including a license for the software. Given the liability issues and low payoff involved, I doubt that any of the players involved will be licensing their software for diy/conversion use.
Isn't the long term plan of google to licence the technology to car makers? Also the sensors and manipulators seem like standard components so they 'll probably not cost a lot when they are produced at scale.
I believe that is their plan. However, I don't see them going after the aftermarket—too many variables, and given the liability issues involved (for instance, what would happen if a sensor was installed incorrectly?), I think they'll avoid the aftermarket channel entirely.
At the opening yes. Midgame, is requiring autonomous cars only in certain situations - perhaps highway/freeway lanes. Endgame is, of course, autonomous only - aftermarket is inevitable there. But the tech will be old and reliable by then.
I don't see us ever getting to a point where human drivers are prohibited—at least not in the time span where we'd need to worry about converting existing vehicles. In the USA at least, driving is so closely associated with the idea of "freedom" that such a move would be politically untenable, no matter the potential for lives saved. Also, I think that once the majority of vehicles are autonomous, the remaining human drivers become less of a danger—I'd argue that most accidents involve two parties making mistakes (even the "not-at-fault" driver wasn't driving as defensively as they could have been).
It will be interesting to see how insurance rates change for autonomous vehicles—a vehicle with no potential for manual control should in theory be much cheaper to insure.
The cars are developed in California. The weather is great here almost all the time. The cars are still under development and inclement weather is an obvious thing the team must be thinking about. I fully expect, in time, that autonomous vehicles to drive more safely in bad weather than people. (They'll be more cautious, for one.)
Absolutely. If you've ever driven though heavy snow, you know that you can barely see any of the road (no white or yellow lines) and lights are the only part of other cars that you can see. Signs and other traffic signals get completely covered with snow. People can barely drive in those conditions, I highly doubt that a self driving car could with current technology. Although I have high hopes for the future.
Why would machines be worse than humans in bad weather if they are better than humans in good weather? Its not like our eyes are better than the machines cameras.
If its because human drivers can better "build a mental model" of whats happening with limited visibility/data - that seems like the same problem that autonomous cars are designed to solve.
Whats stopping autonomous cars from making progress in the bad weather arena? Is it just we haven't done enough miles in that weather and we need to train the ML some more?
You're putting a lot of faith in the ability to solve a very difficult problem. Computer vision has made huge strides in recent years, but it's still far behind the capabilities of the human visual cortex. It's not just a matter of building a simple model and training it until it achieves arbitrarily high accuracy. ML encompasses a powerful set of tools, but it's not a magic black box that eats data and spits out AI.
We don't yet know how the human brain processes images at a detailed level, and it's too complex of a system to optimize by brute-force. The best ML image processing systems still rely on a lot of pre-encoded assumptions, and require huge amounts of training data/computational resources, and don't perform as well as humans even on simple tasks.
For now, autonomous vehicles "cheat" a lot by using sensor technologies like lidar and radar -- techniques that produce spatial data that can be interpreted more easily than raw imagery. That adds a lot to the hardware costs, but it's currently the only way we can make them perform acceptably well in real-world scenarios. And conditions that interfere with those technologies more severely, like fog or snow, are still crippling.
Actually there's no reason to suppose that computer vision hasn't already exceeded the human capacity. After all, it has lidar and radar. Cheating or not, it has a very good result.
Agreed -- don't knock it if it works! However, those kinds of sensors don't really fall into what's normally considered "computer vision".
Mind you, I'm extremely optimistic about the potential successes of autonomous cars in the near- to mid-future (the next 5 to 25 years, say). But I don't want people to get the wrong impression about where the state of the art is today. And in particular, I want to push back against the idea that machine learning is a solved problem, and that autonomous cars can teach themselves to drive as well as a human if we only give them enough miles of practice.
Vision algorithms are pretty shaky to begin with. We've made leaps and bounds of improvements but they're still pretty far behind what people are able to do. In inclement conditions I think humans still out perform machines pretty handily. Eventually it'll be an even field or there will be sensors added to cars that can just see through the snow/rain but that's not where we are.
Basically, the sensors they tend to equipped with aren't even close to being sufficient in poor whether. Humans are EXTREMELY good at pattern recognition and can manage to make it work, but computers just aren't at that level yet. It'll take a combination of improved sensors and computer vision (ie, pattern recognition) to make it happen.
Because Google has mapped out the roads to a very specific level; this allows them to use sensors in the cars that don't have to have the fidelity of human eyes etc. As Google's maps become out of date, they need to be recreated or checked. Their system won't scale...
While heavy snow / rain is a hard scenario to get self-driving cars into, I would argue that they have the possibility to be better than humans. We are dependent on our poor quality vision. Cars could use laser, low light vision, thermal imaging, etc. to look right through heavy snow or fog!
In some parts of the country, it's pretty normal. The roads are caked with snow for weeks at a time and you can get into white out conditions if the wind picks up. As long as you slow down accordingly, it's usually not an issue.
Then put your auto in manual mode and drive it by hand. No reason not to roll them out in the next five years. If it detects rain or snow it simply refuses to self-drive.
~5 years. Freightliner's auto-drive truck is already in production, and light vehicle manufacturers, Google, Apple, Bosch are all pushing the limits pretty fast (and Tesla of course!).
I'll bet you $1k that fully autonomous cars will not be:
(1) legal to ride on at least 90% of public roads AND
(2) available for sale to the general public AND
(3) for under $250,000 in 2015 dollars AND
(4) in the state of California AND
(5) on or before June 5 2020.
Deal? (If I were richer, I'd bet more, in order to up my chances of being happy either way. I want to lose, but don't think I will.)
I think we're going to quibble on 2 and 3. It doesn't matter what the capital cost of the vehicle is if you no longer need to own the vehicle and can order it on demand from Google, Uber, etc.
If you want to hammer out details, my email is in my profile. We'd use LongBets [1] to keep track, and under the condition that the loser has to donate the amount chosen to a charity of the winner's choice.
I don't see how autos could realistically cost $250k each anyway. They are not using significantly more raw resources. Electric cars are an accurate comparison, because they also have top of the line tech in a specific domain - batteries. And volume batteries are a much bigger manufacturing problem than radar systems, which have been assembled (but not at auto-fleet scale) for decades, albeit not with current tech, but much more closer to current assembly than what Teslas LI batteries are.
I imagine something like this Google car could go to market for around $80k today, and thats factoring in huge amounts of per-unit overhead for building factories to assemble them en masse in the first place.
An auto upgrade kit to a traditional car probably won't cost more than 20k if they permit the retrofitting of old vehicles when the ball starts rolling.
If you're fine riding with other people, then a self driving car is just a Lyft Line with one extra seat available and without driver wages to pay. I think they're going to drive down the costs of a ride to a level where buying a car doesn't make sense for many people even before self driving cars happen.
IMHO, fully autonomous cars for the general public are at least 10+ years away.
What I'm excited about is how we will soon see more and more autonomous 'features' i.e. lane changing, smarter adaptive cruise control and parking lot mode.
Will Google’s self-driving cars get into accidents? Have they gotten into accidents before?
> Safety is our top priority. In the 6 years of our project, we’ve been involved in a small number of accidents in more than 1.8 million miles of autonomous and manual driving combined. Our vehicles have not caused any accidents while in self-driving mode. For more information, view our monthly reports.
So no accidents in self-driving mode; a "small number" during "manual driving"...and credit to Google, even though there is only one monthly report, it contains a listing of past accidents:
I skimmed over the dozen listed incidents. Several of them were during "autonomous" mode but are incidents in which another car is described as hitting the vehicle. Arguably, none of the "manual" mode accidents were egregiously the fault of Google.
However, I think the definition of "caused" will be debate here and for years to come. In one Feb. 2015 incident, the autonomous Google car is struck in the side rear by a car that rolled through a crossbound stop sign. The Google car is described as "Applying the brakes in response to its detection of the other vehicle's speed and trajectory"...since the collision ended up happening anyway, and it hit the rear of the Google car...doesn't that imply that if the Google car hadn't cautiously applied the brakes while going through the intersection, it would have cleared the intersection without getting hit? Also worth noting: the Google human driver tried to take control during the autobrake sequence...so it's possible that his/her reaction and manual braking was what led to the rear collision.
Even if they do cause rare accidents they ll be successful. I think in the end humans will adjust to drive more rationally when they learn how to spot autonomous cars.
Tbh, i think it will result in more frustration by drivers at large. Eg, think of on the freeway, note the people who drive the actual speed limit. They're driving perfectly, yet people constantly pass them.
It's worse on county roads (like in my local area, 50mph) without passing lanes. If you drive the speed limit you can almost guarantee to be passed by many cars, sometimes even dangerously, because it annoys people to go below the speed limit they perceive as correct.
I like to go around the speed limit (admittedly, simply to avoid tickets), usually ~3mph over, but it will annoy me to no end if i have to drive 5mph slower because of someone in front of me. On these popular county roads i speak of, i usually go faster than i want (5-10mph over), because i don't like being dangerously and needlessly passed.
Now, i'm not saying the self-driving cars are wrong in any way. I'm also aware that the roads i speak of will be among the last to get self driving cars. Nevertheless, i think humans will have to learn to drive far less aggressively. Though, when self-driving outnumber the normal drivers, it may not matter.
I wouldn't go so far as that. I liken it more to air travel. You'll be permitted to drive a car, but you'll require far more instruction, the environment will be much more closely monitored, and it'll be much easier to remove someone's privileges for safety infractions.
I think by far the biggest danger with self-driving cars won't be how "accurate" they are at driving - I'm sure they'll be much better at that - but hacking. We'll enter an age you could view someone's location in real-time (GPS) and then be able to kill them with potentially relatively low ties back to yourself.
Granted, Google's security is about as good as it gets for most stuff, but what about companies like Audi, BMW [1], Daimler, Ford...Toyota [2]? Many people will still buy cars from them well into the future.
I see no issues for a robot taxi insurance, since it could be done with the same scheme, as the current testing vehicles are insured (a large deposit to the state).
Once robot taxis are everywhere, I would expect that there will be robot car rentals and robot car long-term rentals. They are also not different from the taxis; people just rent them for longer.
As for real ownership, the question is unclear. Probably, it will be so rare, that a deposit will work too.
This brings up the point I'm most looking forward to if we can get this stuff widespread: massive carpooling.
Forget Uber. Get a Google-AV subscription, find the nearest "unoccupied" AV (or call for one to come pick you up, preferably scheduled in advance to it's just waiting for you when you get out), hop in, state destination, get off. Car continues on its merry way to its next duty. Repeat when you want to go back home. Much less massive waste of space involved in all those parking lots. Much less opportunity cost waste. Less total cars in existence for the same amount of travelers.
It's like a public transit pass, but the bus stops are exactly where you want them, and the bus passes exactly when you need it, and you don't have to deal with that insane, smelly old guy who dances in the middle of the bus and then shakes peoples' shoulders so they give him pocket change.
No argument...I have no doubt that an automated driver will perform better than the average driver, statistically...and even more so if automated driving becomes the norm (reducing the irregular situations encountered on the road). However, I think it'll be a very, very long time until humans aren't fixated on the the instances in which a robot/algorithm messed up, while subconsciously ignoring/accepting the many human-caused accidents. In fact, one of the strengths of automated processes will be something that leads to increased scrutiny...the fact that it's easier to audit/reproduce automated behavior...any time something goes awry, we have the ability to pick it apart in minute detail, including all prior documentation.
This is not the same for human-caused incidents...though we do fixate on pieces of incidental data that might exist: is there a record showing that the driver sent a text right before they crashed? Are there credit car receipts for a bar? Or, in a more extreme case, the medical history of the Germanwings pilot who is believed to have downed his plane.
Insurance companies will love insuring these cars because they will be involved in far fewer accidents, and will have a complete log of exactly what happened so it will be easy to assign blame.
Not just that, but human drivers have a lot of "hidden variables" affecting their accident risk -- level of experience, state of mind, aggressiveness, familiarity with local roads, and so on. Insurance companies have to try to account for all of that when calculating premiums, based on a limited number of data points.
With autonomous vehicles, two cars of the same model running the same software should be more or less interchangeable. So even leaving aside the number of accidents that occur, the level of uncertainty should be a lot lower.
Insurance companies will hate insuring these cars because the first human fatality is absolutely going to court, and it'll be a complete circus. The media will go apeshit.
I know the insurance question keeps coming up, but I'm not sure I understand it. The way I see it, these cars won't be released into the wild until and if they can perform on par or better than human drivers...which will require that they be able to follow the rules of the road as well as or better than human drivers. That being the case, I don't see why the insurance would be any more of a factor for the autonomous cars than for current drivers. If they fail to follow the rules of the road and cause an accident (or negligently contribute to one), they'll be on the hook and insurance will have to cover it. If not, there's no insurance liability to consider. Am I missing something that the liability would somehow be greater in an autonomous vehicle in the case of the same accident that would otherwise be caused by a human?
I think the real question is WHO should be liable. If the car is in an accident that is for some reason deemed that car's fault. Is the passenger / owner at fault, or is the manufacturer? Will you buy a vehicle and Google be liable for the damages?
> That said, when they sell one of these things to a person, how the heck are they going to handle the insurance?
There will be a large fluctuation prices as data becomes available but its like insuring any other system ultimately. They calculate the odds, add in their needs, and come up with a figure.
I doubt it'd be significantly different than today since all of these can be switched to manual mode.
I am curious why google dabbles in all these strange projects removed from their core business, which seems to be organizing the worlds information and making some money off that. are these merely hobbies of eccentric, rich founders?
On the other hand I am glad somebody is pouring money into fundamental research. The government has limited funds. Many big companies that formally had big R&D cutback during downsizings.
Google is a machine learning company. Knowing about how people use their phone (Android), Computer (ChromeOS), etc a self driving car gives them more and more data to refine and expand their algorithms.
At the same token it is because they have these vast troves of data and some of the best machine learning scientists in the word, they are suited to do this type of research.
Another thing to think about is that if we are not distracted by the commute we will spend more time using Google services.
(note: this is supposed to be pseudo-tongue-in-cheek-back-of-the-envelope math)
Let's say they invest...I dunno $300m in developing this technology (completely made-up number)
- The average commute time in the U.S. is ~30 minutes...or 1 hour per day. I don't know what it is globally, but for fun we'll assume it's the same for everybody on the planet.
- Google made $66billion in 2014 (or about $9.43 per person on the planet, assuming 7billion people)
- Assume most people are awake 16 hours during a day.
- However, if people are stuck driving for 1 hour out of those 16, that's only 15 hours they can build revenue for google.
- This means google is generating about $.63 per available waking hour per person.
- 1 more available hour is $.63*7billion = a possible "new" market of $4.4billion/year assuming every person
This would pay back the R&D costs handsomely + tons of profit in the first year if google can get everybody to switch all at once.
Even if it takes a decade or two to switch humanity to self-driving cars, it would still pay for itself quickly.
Innovation is one way to protect your business from failure. Relying on a single business model, for decades, naively assumes that society will always want, or need, your product or service.
I tip my hat to Google, for attempting to stay ahead of the curve.
Their core mission is to organize the world's data. They've organized geospatial and road infrastructure records on their way to building out Google maps. They have traffic patterns based on Android GPS tracking, as well as via such venues as Waze and Uber. And they have a huge trove of visual data and algorithms derived from core search and working with images. While they may not be a traditional robotics company, their approach to this seems fundamentally guided by their expertise in data infrastructure, analysis, and AI algorithms...all of which were essential to their core mission. Also, it helps that they were very profitable in their core product, allowing them to expand in such a fashion.
I always assume it's about gathering data. I am probably completely wrong, but frankly i feel like every large decision i've seen from Google comes down to 2 core concepts:
1. Enable more people to use your service
2. Create devices that can gather more data
The thing is, a ton of device types can fit into one of these schemes. Phones for example, both let people use your service, as well as gather a ton of data. As we increase the technology in phones, they may even be mapping the environment.
Likewise, these self-driving cars are able to exploit much of Google's current offerings, as well as contribute mapping of a near limitless amount of roads/etc.
If Google can pull far ahead in the technology they can become the self-driving service. Even if they don't create the cars but instead lease the technology to normal makers, Google now has constantly updating maps, traffic patterns, routes, building changes, etcetc.
Sure, Google made a car, but i don't think they car in the slightest about the car itself. They need to push to improve the technology and legislation as fast as they are able - everything else, people and car manufactures, will catchup eventually.
Some people joked about the fact that selfdriving cars could be continuous Google Maps scanner in disguise. But back to business, every company will face crisis at one point, better explore alternatives while you can.
Google might also consider what else they can suggest to the in car captive audience that they know all about. Imagine this scenario:
Google Now - In car edition:"Since we have plenty of time before your appointment, press 'accept' to stop at the showroom for those soft-furnishings you searched yesterday, and receive a credit towards this ride".
> I am curious why google dabbles in all these strange projects removed from their core business, which seems to be organizing the worlds information and making some money off that.
> Google hasn't posted an annual increase in the average cost-per-click since the third quarter of 2011. It hasn't posted a quarterly boost since the second quarter of that year. Both streaks remain intact.
Their per-click margins aren't going up and there is a limit to what they can do in that situation to grow net revenue.
So they are looking for new growth markets since the margins on their core business aren't really going to change substantially with new investment.
Throwing small amounts of money at things like driverless cars is something they can control and will likely give them the first mover advantage in a new market. They take over and become the "Microsoft of Driverless Cars" and they've got a huuuuuuuuuuuge new profit center.
If not, they blew through a bit of cash. They have plenty of cash.
Google doesn't give out much info about how their system works. It seems to be very much like the technology from the DARPA Urban Challenge in 2007. Most of the improvements since seem to relate to predicting the movements of other street users. That's not surprising, considering Google's focus on "big data".
Sensor technology hasn't improved much. It's still mostly cameras, Velodyne rotating LIDAR units and off the shelf centimeter Doppler RADAR units. Flash LIDAR and millimeter RADAR aren't volume products yet. They will be once auto companies get serious about this.
> Aging or visually impaired loved ones wouldn't have to give up their independence.
I know this is simply phase one, but I'm hoping google puts some emphasis on individuals in wheelchairs in future prototypes because this technology can be life changing for some with extremely limited mobility - my mother being one of them. Independence is key here and the the majority of us can't conceive what it's like to to be dependent on others for everything. A user with a wheelchair or power chair needs to able to get in and out of the self driving car with zero assistance.
This is really impressive. However, has any one else thought about the ethical dilemmas these algorithms will have to decide upon?
Say for instance that two pedestrians, a young child and an old person, suddenly find themselves in front of a self-driving car. There is not time for the car to brake in time so the algorithm has to make a choice: Which pedestrian gets hit?
I think we'll see more questions like these in the coming years as AI progresses and we become more dependent on it.
This assumes a flaw in the cars algorithm to be travelling too quickly at an upcoming intersection - or a pedestrian breaking the law by jay-walking or crossing during a "no cross" time.
Let's give it the most realistic scenario of a blind-turn intersection with an obstruction such as a bush make it impossible to see the sidewalk on the right-hand side. The two pedestrians in question are a grandparent and their grandchild crossing without looking both ways for their safety.
Is there oncoming traffic? Is there an empty sidewalk to drive on? Can the car make an attempt to brake as safely and quickly as possible and sound the horn to alert the pedestrians to get out of the way? Is it safe enough to perform a handbrake turn? Is it safe enough to perform a bootleg turn?
Before asking which pedestrian the car chooses to hit, I would exhaust all other available options to prevent such a scenario from happening in the first place.
So your answer to my hypothetical question of what an algorithm should do in a situation where whatever the outcome a life will be lost, is to say that this scenario will never happen without a flaw in the cars algorithm? That seems very narrow minded to me. Let me put it this way: When all your other available options are exhausted what should the choice be?
There has to be too little room to perform an evasive maneuver. The road has to be too crowded or too small to perform an evasive maneuver. The pedestrians would have to be deaf or suffer from "deer fright". The car would have to be travelling too quickly to brake and would have had to fail to notice the pedestrians about to cross.
The scenario is one that requires so many worst-case-scenario events to be happening simultaneously as to say the scenario is likely avoidable altogether in one of numerous ways. So yes, I'm calling your hypothetical scenario a little contrived.
To answer the hypothetical with the answer you're expecting; people have already made this choice in the past for disaster scenarios:
"Women and children first."
The algorithm would choose to hit the elderly person over the child in your scenario. The ethical choice becomes more complex if the pedestrians in question are both children or both women. I don't think humans have made an ethical decision on such a choice.
So yes, I'm calling your hypothetical scenario a little contrived.
Yes, that is the often the point of hypothetical scenarios.
I was not expecting any particular answer, I simply find the problem interesting. It begs the question: Does this mean there is a line of code somewhere that ultimately has to make that decision?
I don't see how that begs the question at all. If an algorithm exists to make such a decision it is a given that the code would exist to allow it to make that decision.
Without the code a more simple scenario plays out. The car continues along its current trajectory and kills whichever pedestrian was in front of the vehicle, which could be both of them.
I personally would rather not have sexist cars that would hit a same-aged man over a same-aged woman.
Women and children first is not a policy of who is most valuable. It is a policy of who is most vulnerable. In disasters it is presumed that the women and children cannot fend for themselves (and while there is a biological aspect to women being on average weaker than men the presumption of women and children first is still painfully sexist) and that the men coming up behind are more likely to survive than any alternative, where men go first and "the vulnerable" take up the rear.
Even besides that, how do you know if a child is more valuable than an elderly person?
Its not as simple a problem as yesteryears well intentioned sexism and ageism. But the real answer is much simpler:
The car would, in the situation where it could not avoid hitting a person, hit whomever it computes to be most likely to survive.
Expand the question to factor that the person struck will die with 100% certainty and you arrive to the same situation of which choice to make.
The choice of children vs elderly rarely comes down to value - but rather life. The elderly person has lived their life while the child, potentially, has many more years ahead of them. Humans don't tend to give a value to life other than life itself - and extending life or saving multiple lives over a single life tends to be the popular choice. It would be impossible to judge a persons' "value" or measure it without having information on them prior to the event.
I think the real answer to this sort of question is: Who cares?
There are tens of thousands of people dying every year in very real car crashes, plus probably an order of magnitude more suffering life-changing injuries, and self-driving cars have a huge potential to cut way down on that. Meanwhile, situations like that virtually never happen - maybe like once a year in the entire US. If they can eliminate even 10% of the actual accidents, then they could run down both pedestrians in that imaginary scenario, and still be way ahead.
It may be fun to think about ethical dilemmas like that, but they are fantastically rare compared to the huge numbers of perfectly ordinary crashes that happen every day. Let's fix those, and worry about the rare one-offs after we've reduced the accident rate by 95%.
Yes, I agree with you. These edge cases will probably never actually happen. But again, this is only hypothetical. Are there lines of code that actually define the behaviour of the car in these cases? I think it's an interesting question (-:
Little surprised to see no comments on the car's aesthetic design. My first thought was "ew". At least with Tesla they tried to go with a design that was very appealing to the eye. This car looks like an ugly, mass-produced POC. My better senses tell me it is a prototype unit that was built for function over form. Just saying, if you want to get the public behind your idea, better put together something that is a little more sexy.
Then again, Smart Cars are equally ugly and they have gained some huge traction, at least with car2go, so what do I know.
I'm willing to bet the aesthetic design is a very deliberate choice. Google knows that there's a lot of skepticism toward the idea of autonomous cars, largely based on their unfamiliarity. By limiting the initial version to 25mph and making it shaped like a Cozy Coupe, they're making it seem as non-threatening as they possibly can.
I can't wait until I don't have to drive, but it's hard to see how much of a difference google is making. We're in downtown MV and these cars are continuously driving around, and one is parked every night a couple of houses down from my girlfriend's house.
The problem is, they drive the same routes over and over. I always see them in the same places, and nowhere else. They have hyper-mapped a small number of routes (mm resolution). And all that highway driving: MV to SF and back on 280, over and over and over again.
81 comments
[ 3.0 ms ] story [ 159 ms ] threadIt will be interesting to see how insurance rates change for autonomous vehicles—a vehicle with no potential for manual control should in theory be much cheaper to insure.
If its because human drivers can better "build a mental model" of whats happening with limited visibility/data - that seems like the same problem that autonomous cars are designed to solve.
Whats stopping autonomous cars from making progress in the bad weather arena? Is it just we haven't done enough miles in that weather and we need to train the ML some more?
We don't yet know how the human brain processes images at a detailed level, and it's too complex of a system to optimize by brute-force. The best ML image processing systems still rely on a lot of pre-encoded assumptions, and require huge amounts of training data/computational resources, and don't perform as well as humans even on simple tasks.
For now, autonomous vehicles "cheat" a lot by using sensor technologies like lidar and radar -- techniques that produce spatial data that can be interpreted more easily than raw imagery. That adds a lot to the hardware costs, but it's currently the only way we can make them perform acceptably well in real-world scenarios. And conditions that interfere with those technologies more severely, like fog or snow, are still crippling.
Mind you, I'm extremely optimistic about the potential successes of autonomous cars in the near- to mid-future (the next 5 to 25 years, say). But I don't want people to get the wrong impression about where the state of the art is today. And in particular, I want to push back against the idea that machine learning is a solved problem, and that autonomous cars can teach themselves to drive as well as a human if we only give them enough miles of practice.
[Because they are.](http://jalopnik.com/this-is-how-bad-self-driving-cars-suck-i...)
Basically, the sensors they tend to equipped with aren't even close to being sufficient in poor whether. Humans are EXTREMELY good at pattern recognition and can manage to make it work, but computers just aren't at that level yet. It'll take a combination of improved sensors and computer vision (ie, pattern recognition) to make it happen.
Arguably, no car should be driving in those conditions unless it is a life or death situation. Because you have a very good chance of dying doing so.
5 years tops. I'd bet on it.
I think we won't need to own cars and will simply press a button like Uber and the car drives us wherever.
I'll bet you $1k that fully autonomous cars will not be: (1) legal to ride on at least 90% of public roads AND (2) available for sale to the general public AND (3) for under $250,000 in 2015 dollars AND (4) in the state of California AND (5) on or before June 5 2020.
Deal? (If I were richer, I'd bet more, in order to up my chances of being happy either way. I want to lose, but don't think I will.)
If you want to hammer out details, my email is in my profile. We'd use LongBets [1] to keep track, and under the condition that the loser has to donate the amount chosen to a charity of the winner's choice.
[1] http://longbets.org/
I imagine something like this Google car could go to market for around $80k today, and thats factoring in huge amounts of per-unit overhead for building factories to assemble them en masse in the first place.
An auto upgrade kit to a traditional car probably won't cost more than 20k if they permit the retrofitting of old vehicles when the ball starts rolling.
What I'm excited about is how we will soon see more and more autonomous 'features' i.e. lane changing, smarter adaptive cruise control and parking lot mode.
Will Google’s self-driving cars get into accidents? Have they gotten into accidents before?
> Safety is our top priority. In the 6 years of our project, we’ve been involved in a small number of accidents in more than 1.8 million miles of autonomous and manual driving combined. Our vehicles have not caused any accidents while in self-driving mode. For more information, view our monthly reports.
So no accidents in self-driving mode; a "small number" during "manual driving"...and credit to Google, even though there is only one monthly report, it contains a listing of past accidents:
http://static.googleusercontent.com/media/www.google.com/en/...
I skimmed over the dozen listed incidents. Several of them were during "autonomous" mode but are incidents in which another car is described as hitting the vehicle. Arguably, none of the "manual" mode accidents were egregiously the fault of Google.
However, I think the definition of "caused" will be debate here and for years to come. In one Feb. 2015 incident, the autonomous Google car is struck in the side rear by a car that rolled through a crossbound stop sign. The Google car is described as "Applying the brakes in response to its detection of the other vehicle's speed and trajectory"...since the collision ended up happening anyway, and it hit the rear of the Google car...doesn't that imply that if the Google car hadn't cautiously applied the brakes while going through the intersection, it would have cleared the intersection without getting hit? Also worth noting: the Google human driver tried to take control during the autobrake sequence...so it's possible that his/her reaction and manual braking was what led to the rear collision.
It's worse on county roads (like in my local area, 50mph) without passing lanes. If you drive the speed limit you can almost guarantee to be passed by many cars, sometimes even dangerously, because it annoys people to go below the speed limit they perceive as correct.
I like to go around the speed limit (admittedly, simply to avoid tickets), usually ~3mph over, but it will annoy me to no end if i have to drive 5mph slower because of someone in front of me. On these popular county roads i speak of, i usually go faster than i want (5-10mph over), because i don't like being dangerously and needlessly passed.
Now, i'm not saying the self-driving cars are wrong in any way. I'm also aware that the roads i speak of will be among the last to get self driving cars. Nevertheless, i think humans will have to learn to drive far less aggressively. Though, when self-driving outnumber the normal drivers, it may not matter.
Granted, Google's security is about as good as it gets for most stuff, but what about companies like Audi, BMW [1], Daimler, Ford...Toyota [2]? Many people will still buy cars from them well into the future.
[1] - https://news.ycombinator.com/item?id=8984129
[2] - https://news.ycombinator.com/item?id=9643204
That said, when they sell one of these things to a person, how the heck are they going to handle the insurance?
Once robot taxis are everywhere, I would expect that there will be robot car rentals and robot car long-term rentals. They are also not different from the taxis; people just rent them for longer.
As for real ownership, the question is unclear. Probably, it will be so rare, that a deposit will work too.
Forget Uber. Get a Google-AV subscription, find the nearest "unoccupied" AV (or call for one to come pick you up, preferably scheduled in advance to it's just waiting for you when you get out), hop in, state destination, get off. Car continues on its merry way to its next duty. Repeat when you want to go back home. Much less massive waste of space involved in all those parking lots. Much less opportunity cost waste. Less total cars in existence for the same amount of travelers.
It's like a public transit pass, but the bus stops are exactly where you want them, and the bus passes exactly when you need it, and you don't have to deal with that insane, smelly old guy who dances in the middle of the bus and then shakes peoples' shoulders so they give him pocket change.
This is not the same for human-caused incidents...though we do fixate on pieces of incidental data that might exist: is there a record showing that the driver sent a text right before they crashed? Are there credit car receipts for a bar? Or, in a more extreme case, the medical history of the Germanwings pilot who is believed to have downed his plane.
With autonomous vehicles, two cars of the same model running the same software should be more or less interchangeable. So even leaving aside the number of accidents that occur, the level of uncertainty should be a lot lower.
Insurance companies will hate insuring these cars because the first human fatality is absolutely going to court, and it'll be a complete circus. The media will go apeshit.
There will be a large fluctuation prices as data becomes available but its like insuring any other system ultimately. They calculate the odds, add in their needs, and come up with a figure.
I doubt it'd be significantly different than today since all of these can be switched to manual mode.
http://www.openstreetmap.org/#map=18/37.38487/-122.08136
Without more information about the collision, I think it's hard to say what would have happened if the system had not applied the brakes.
On the other hand I am glad somebody is pouring money into fundamental research. The government has limited funds. Many big companies that formally had big R&D cutback during downsizings.
At the same token it is because they have these vast troves of data and some of the best machine learning scientists in the word, they are suited to do this type of research.
Another thing to think about is that if we are not distracted by the commute we will spend more time using Google services.
Let's say they invest...I dunno $300m in developing this technology (completely made-up number)
- The average commute time in the U.S. is ~30 minutes...or 1 hour per day. I don't know what it is globally, but for fun we'll assume it's the same for everybody on the planet.
- Google made $66billion in 2014 (or about $9.43 per person on the planet, assuming 7billion people)
- Assume most people are awake 16 hours during a day.
- However, if people are stuck driving for 1 hour out of those 16, that's only 15 hours they can build revenue for google.
- This means google is generating about $.63 per available waking hour per person.
- 1 more available hour is $.63*7billion = a possible "new" market of $4.4billion/year assuming every person
This would pay back the R&D costs handsomely + tons of profit in the first year if google can get everybody to switch all at once.
Even if it takes a decade or two to switch humanity to self-driving cars, it would still pay for itself quickly.
I tip my hat to Google, for attempting to stay ahead of the curve.
1. Enable more people to use your service 2. Create devices that can gather more data
The thing is, a ton of device types can fit into one of these schemes. Phones for example, both let people use your service, as well as gather a ton of data. As we increase the technology in phones, they may even be mapping the environment.
Likewise, these self-driving cars are able to exploit much of Google's current offerings, as well as contribute mapping of a near limitless amount of roads/etc.
If Google can pull far ahead in the technology they can become the self-driving service. Even if they don't create the cars but instead lease the technology to normal makers, Google now has constantly updating maps, traffic patterns, routes, building changes, etcetc.
Sure, Google made a car, but i don't think they car in the slightest about the car itself. They need to push to improve the technology and legislation as fast as they are able - everything else, people and car manufactures, will catchup eventually.
Google Now - In car edition: "Since we have plenty of time before your appointment, press 'accept' to stop at the showroom for those soft-furnishings you searched yesterday, and receive a credit towards this ride".
http://adage.com/article/digital/google-profit-misses-estima...
> Google hasn't posted an annual increase in the average cost-per-click since the third quarter of 2011. It hasn't posted a quarterly boost since the second quarter of that year. Both streaks remain intact.
Their per-click margins aren't going up and there is a limit to what they can do in that situation to grow net revenue.
So they are looking for new growth markets since the margins on their core business aren't really going to change substantially with new investment.
http://en.wikipedia.org/wiki/Google_driverless_car
Throwing small amounts of money at things like driverless cars is something they can control and will likely give them the first mover advantage in a new market. They take over and become the "Microsoft of Driverless Cars" and they've got a huuuuuuuuuuuge new profit center.
If not, they blew through a bit of cash. They have plenty of cash.
Sensor technology hasn't improved much. It's still mostly cameras, Velodyne rotating LIDAR units and off the shelf centimeter Doppler RADAR units. Flash LIDAR and millimeter RADAR aren't volume products yet. They will be once auto companies get serious about this.
The DARPA Humanoid Challenge is live today. Watch: http://www.theroboticschallenge.org/
I know this is simply phase one, but I'm hoping google puts some emphasis on individuals in wheelchairs in future prototypes because this technology can be life changing for some with extremely limited mobility - my mother being one of them. Independence is key here and the the majority of us can't conceive what it's like to to be dependent on others for everything. A user with a wheelchair or power chair needs to able to get in and out of the self driving car with zero assistance.
Say for instance that two pedestrians, a young child and an old person, suddenly find themselves in front of a self-driving car. There is not time for the car to brake in time so the algorithm has to make a choice: Which pedestrian gets hit?
I think we'll see more questions like these in the coming years as AI progresses and we become more dependent on it.
Let's give it the most realistic scenario of a blind-turn intersection with an obstruction such as a bush make it impossible to see the sidewalk on the right-hand side. The two pedestrians in question are a grandparent and their grandchild crossing without looking both ways for their safety.
Is there oncoming traffic? Is there an empty sidewalk to drive on? Can the car make an attempt to brake as safely and quickly as possible and sound the horn to alert the pedestrians to get out of the way? Is it safe enough to perform a handbrake turn? Is it safe enough to perform a bootleg turn?
Before asking which pedestrian the car chooses to hit, I would exhaust all other available options to prevent such a scenario from happening in the first place.
The scenario is one that requires so many worst-case-scenario events to be happening simultaneously as to say the scenario is likely avoidable altogether in one of numerous ways. So yes, I'm calling your hypothetical scenario a little contrived.
To answer the hypothetical with the answer you're expecting; people have already made this choice in the past for disaster scenarios:
"Women and children first."
The algorithm would choose to hit the elderly person over the child in your scenario. The ethical choice becomes more complex if the pedestrians in question are both children or both women. I don't think humans have made an ethical decision on such a choice.
I was not expecting any particular answer, I simply find the problem interesting. It begs the question: Does this mean there is a line of code somewhere that ultimately has to make that decision?
Without the code a more simple scenario plays out. The car continues along its current trajectory and kills whichever pedestrian was in front of the vehicle, which could be both of them.
Women and children first is not a policy of who is most valuable. It is a policy of who is most vulnerable. In disasters it is presumed that the women and children cannot fend for themselves (and while there is a biological aspect to women being on average weaker than men the presumption of women and children first is still painfully sexist) and that the men coming up behind are more likely to survive than any alternative, where men go first and "the vulnerable" take up the rear.
Even besides that, how do you know if a child is more valuable than an elderly person?
Its not as simple a problem as yesteryears well intentioned sexism and ageism. But the real answer is much simpler:
The car would, in the situation where it could not avoid hitting a person, hit whomever it computes to be most likely to survive.
The choice of children vs elderly rarely comes down to value - but rather life. The elderly person has lived their life while the child, potentially, has many more years ahead of them. Humans don't tend to give a value to life other than life itself - and extending life or saving multiple lives over a single life tends to be the popular choice. It would be impossible to judge a persons' "value" or measure it without having information on them prior to the event.
See: The Trolley Problem
[0] http://healthland.time.com/2011/12/05/would-you-kill-one-per...
[1] http://philpapers.org/archive/BOUWDP
There are tens of thousands of people dying every year in very real car crashes, plus probably an order of magnitude more suffering life-changing injuries, and self-driving cars have a huge potential to cut way down on that. Meanwhile, situations like that virtually never happen - maybe like once a year in the entire US. If they can eliminate even 10% of the actual accidents, then they could run down both pedestrians in that imaginary scenario, and still be way ahead.
It may be fun to think about ethical dilemmas like that, but they are fantastically rare compared to the huge numbers of perfectly ordinary crashes that happen every day. Let's fix those, and worry about the rare one-offs after we've reduced the accident rate by 95%.
Then again, Smart Cars are equally ugly and they have gained some huge traction, at least with car2go, so what do I know.
The problem is, they drive the same routes over and over. I always see them in the same places, and nowhere else. They have hyper-mapped a small number of routes (mm resolution). And all that highway driving: MV to SF and back on 280, over and over and over again.
I am sure they are making progress, but how much?