Toyota's Gill Pratt on Self-Driving Cars and the Reality of Full Autonomy
spectrum.ieee.org
spectrum.ieee.org
I think progress is great and self-driving cars are awesome, but I don't believe they're just around the corner.
I can also think of a few ways to prevent number 2 (basically, a combination of GPS + knowing where all intersections occur + road data from thousands of other connected cars = knowledge of where every stop sign is. Certainly not foolproof, but I think ultimately it is a problem that has possible solutions)
The rest of your examples are fantastic though, #3 being quite terrifying actually. They are all very intriguing thought-experiments and I look forward to seeing your future additions!
They're who's at fault, but you're the one who's dead.
I'd rather my car avoids holes in the road even if they haven't been marked [yet].
This is what my dad taught me too and why I've since always been cautious both as a driver, bicyclist and pedestrian even when I'm in the right to drive/go. Being right isn't as fun when someone's on their way to the hospital/morgue.
Provided that your tires are normal (and not the thin-sidewall don't-my-ride-look-cool tires with big rims), and in relatively normal balance - and you are going a normal speed - it most likely will drop slightly then bounce off the lip, jarring car forcefully, but likely not doing much damage.
If the tire doesn't blow (it may), then you might get a cracked rim (if alloy) or bent rim (if steel and depending on the force and deformation), and you would probably want to have the tire inspected (because the plys may be compromised in the area from the sharp impact, which could cause premature interior delamination of the tire in the future).
Yes - ideally you want you or your car to avoid an open manhole or large pothole, but in general, its unlikely to be the cause of a serious accident.
I don't know how Tesla's video only solution would cope, but they're not Level 5 yet.
This is not actually a particularly interesting edge case.
The water-case is more interesting, but I would counter by posing the question of how a human would know whether a water-filled pot hole is safe to navigate? A clear water pothole would not impinge the LIDAR, a murky water one might and could fool LIDAR I suppose (I can not find any solid info on this interface).
Of course car RADAR and a visual camera are likely to also be fitted - both of which could identify a water-filled pothole which LIDAR might struggle with (RADAR can penetrate water and find the unknown backscatter, a camera can simply see the murky-water pothole and choose to navigate around it or stop - in both cases a human can't make a better informed decision).
The problem is not so much availability of information (a sensor packed car has a lot more information than a human behind a windshield), but making sense of that information, particularly in those 0.0001% uncommon, strange cases.
Humans can connect evidence (a manhole cover sitting next to a water filled hole) because they generally know how things work (aka common sense knowledge, long standing problem in AI). Humans can infer what happened and predict what could happen. These things are not really available to AI which is these days more like see-react, not see-anticipate-react. I have a specific post on this on my blog:http://blog.piekniewski.info/2016/11/03/reactive-vs-predicti... The blog has many other posts on limits of todays approach and on some ideas to fix it in the future.
I agree that some of these cases may be challenging to some humans (particularly inattentive), but we want the self driving car to be (much) safer than inattentive driver, so we need to set the bar high.
In reality there will always be a different situation. These situations sit in the statistical long tail (are too infrequent to reliably train, and too frequent to ignore) and vary enormously from case to case. These are just examples.
An argument from the vaguery of "humans have context" with regards to driving is a poor one - humans that are driving do not do a good job of analysing context because of reaction times, and do not share a common context they react to similarly.
You haven't made a compelling case, because you've yet to present a compelling example (i.e. one definitely unsolvable by reasonably usable technology on an autonomous platform). The manhole scenario is based on assumption about the operation of LIDAR which simply aren't true and you've had to modify it in a number of ways to try and make it tricky (i.e. when has there ever been a manhole completely full of water?)
Sometimes, the utility wouldn't be at fault. It has happened in the past the people would steal manhole covers to sell them for scrap (you know, to get money for their next 'fix').
This is less of an issue now, as most scrap companies won't take manhole covers anymore, unless the seller can prove they represent the locality shown on the cover, and that they have such authorization...
...but there are less scrupulous scrap companies.
Anyway, just a food for though, autonomy really requires a lot of "intelligence" and our technology is not quite there to deal with all these bizarre corner cases. I'm glad you like it.
I actually love trying to make computers deal with the real world - it quickly reveals just how goddamn complicated the real world is, and how many things we think as hard and fast are utterly arbitrary.
There are a lot of rules and laws and they change from country to country, or in the US' case, even from state to state. Self-driving cars must know these things and react accordingly. So I think the scenarios presented here are just a few (admittedly, more far-fetched than others) more contexts amidst the probably hundreds of others that already have to work correctly for switching safely between city and motorway driving, driving in a living street, observing right of way correctly in all circumstances (roundabouts, weird stuff like four-way stops, signs changing ROW for one intersection, or a stretch of road, lowered kerbs, people exiting a living street even though it's to the right, cars on an on-ramp and perhaps letting them in based on how far the on-ramp still continues, ...).
Stop signs are interesting in any case, since they have a characteristic shape. If we go full autonomous, then snow-covered signs must be correctly observed as well, at which point any octagon shape may be a stop sign (perhaps, again, depending on context). Same with signs that don't reflect well anymore at night.
So at some point, I suppose the infrastructure (broadly understood - including laws) may be modified to reduce the dependence on cultural context and other things machines are weak at. So for instance, it won't be every sorta-octagonal shape that works as stop sign, it will be required by law to be clearly visible and also have some machine-friendly accommodations, and SDVs will be free to ignore signs without those accommodations.
(Doesn't solve the prank problem, but humans are equally vulnerable to a targeted prank anyway.)
In New England, snow can completely cover the road surface for days or even weeks at a time, and ever-changing piles of snow cover the curbs and parts of the lanes. Humans just choose a path without regard to where the lanes are in the summer. On some roads this turns a four lane road into a two lane road with a lane-width snow pile between the lanes. In a few spots it turns a two lane road into a one lane, with drivers from different directions taking turns.
Now I really wish I had taken more photos that year specifically to illustrate this sort of thing.
I'm not sure where did that come from. One fatality per 200 million miles not good? Seriously, there are millions of people travelling every day. And true, there are accidents, but I think this "Humans aren't really good at driving" mantra is not really serious (but frequently repeated recently by PR of some companies).
Attentive humans are extremely good at driving, distracted humans are much worse, but perhaps the technology should focus first on the much easier task of making sure the driver attends. That would probably safe many lives, before we can have a real autonomous car.
In Nordic countries, you don't see the lane markings for several months, they are under snow and ice. And sometimes, when it melts in April or May, you notice you have been driving on the roadside for a few months :-)
Oh, and you don't see anything at all if you are behind a truck or a bus.
In some parts of some Nordic countries. In my part of my Nordic country we haven't had proper snow for probably about 6 or 7 years and even then it was only for a few weeks.
But more generally. If the snow clearing machines where also driver less then they might be able to run more or them more often and keep the roads clearer.
I would hesitate using the word "equally". People are actually quite robust. Particularly the second human in row will certainly not be tricked by the same prank that tricked the first one.
Not sure why this would be a problem? The car can identify a dangerous road surface and navigate around it.
>Many stop signs.
Is it really so bad if the car does stop at every one? It's inconvenient, but not dangerous. Unless there's someone behind in which case the car should know whether there's a safe stopping distance behind and act accordingly.
>Fire in a tunnel.
This doesn't seem like it would be that difficult to detect. And also, I would expect self-driving cars to have an emergency stop button.
>Tornado.
I would imagine this could be detected as a visual anomaly, but more generally... yeah natural disasters suck.
>Potential car-jacking.
I really don't think this should be the car's responsibility. If there's a serious risk of people with guns ambushing you on a road, then it's not safe and you shouldn't be driving there. How the self-driving car reacts to that is the least of my concerns.
Well, I think the idea behind this prompt was more about how it would handle humans where there shouldn't be any. I would imagine that with the premise that the car would stop for unexpected pedestrians, a car jacking/mugging of this type should be as simple as simply find a remote road, wait for a car with a preferred target, and then intercept - the car would acquiesce and make a person vulnerable to an attack (as simple as smashed windows with a window breaker and then an attack on the occupant.
The picture has an extreme outlier, but criminals adjust to technology pretty fast, especially when it makes their lives easier. It may not be armed gunmen looking to get you, but if you can be assured you'll get a target to stop, I'm not sure why criminals wouldn't exploit it.
edit: change "attach" to "attack" as I meant it originally
The scenario I'm familiar with involved a bicyclist crashing, or laying down, his bike on a slow stretch of road in an industrial area. His companions would approach the car when it stopped. The deterrent for this is a harsh criminal penalty, not AI.
It never became a commonplace crime, in spite of being relatively simple.
Or, you know, you could just drive yourself. Or pay a driver. Or stop fantasizing about embarrassingly absurd stuff that has nothing to do with the efficacy of automotive autonomy.
In defense of the article, which is pretty reasonable, it doesn't mention the ridiculous hijacking example you were harping on. That is quite a unique situation, technically and ethically.
The other examples you gave: bad roads, downed power lines, weather, and fire are all much more reasonable examples, with much more straightforward solutions available. It's essentially obstacle avoidance and exception handling. The article's example of situations involving not having any safe place to stop is even more interesting.
edit: I was referring to TFA, not to the artist who illustrated some stuff on his blog and shared it here. Which was also a fine effort...
It is clearly one of the implied reasons a bunch of armed men would be standing around on the road in that picture. What makes it "ridiculous," exactly?
If you're on a road with armed men with hostile intent, the fact that your autonomous car is unable to offer a solution is absolutely the least of your worries. The unique properties of the armed men on the side of the road problem are not representative of the more general problems vehicle autonomy involves. Take your pick.
But if they actually intend to harm you, you've got bigger problems, and you should probably hire a professional defensive driver instead of expecting consumer AI to support your edge case.
Assume the following for a moment: It is known that, when presented with pedestrians in an unexpected area, an automated car will plot away around them or will yield until they are no longer in the way.
Supposed that with the condition, you were having your car drive you from downtown to your small suburb that requires going down any generally empty road. (i.e., no one is around because it's late) In the distance, 4 people form a loose barrier that the car can't safely pass through so it triggers the logic to yield to pedestrians. The people are muggers, and they quickly break the windows and proceed to mug.
Yes, it's a very specific scenario, but if such a case of logic exists, how long until such a scenario becomes common place? This isn't asking AI to evaluate and protect people from targeted attacks or inventing paranoid delusions of importance, it's about figuring out how to respond to a fairly simple abuse of an often called for bit of logic in the AI.
And again, you're talking about a car that's surrounded by cameras by design. It would be easy to include a button that immediately starts streaming all camera info to cloud storage (or indeed, just do so by default if mugging were such a huge problem).
I mean this is just reality in a lot of places; I don't see how you can just handwave it away. Cars are designed to operate in all kinds of extremes that probably don't apply to your personal situation.
Yes, and self-driving cars will not be suitable for those extremes. I don't see how that's a major problem?
I don't think the latter is necessary for self-driving cars to be successful.
Even in an idyll you could imagine some novel circumstance created by, say, downed power lines.
That it if the passenger pays enough attention, which they won't. Also note: each one of these cases can be programmed indeed. But that is like fighting Wingrad schema by typing in all possible sentences. In reality none of this will happen, but something else will, which we don't even anticipate.
I think the point is that there are millions of different things that can go wrong, and many have a 1 in 1000000 occurrence. Human intelligence is able to improvise, but what will cars do?
Halt, and send a warning signal to any vehicles nearby. Which is better than what we can ordinarily accomplish today in those one in a million occurances.
The challenge for the autonomous car would be "how to know that it doesn't really know". I wonder if some existing philosophy or theories are applicable for such a purpose in the real world. Does anyone have pointers?
Tesla's data so far suggests that their current autopilot implementation is reducing crashes by 40% - http://www.theverge.com/2017/1/19/14326258/teslas-crash-rate... - and while these cases are all problematic, they're all fairly rare, and the cases in which they come up and the car reacts wrongly and that's a major problem are going to be even rarer. On top of that, self-driving car performance is only going to improve.
It doesn't really matter (in terms of the value of self-driving cars - there's a mostly independent marketing question) if there's a couple of cases where self-driving cars make the wrong choice and kill you, if there are many thousands of cases where they save your life. It's effectively changed a great many risky situations into some new and different but less likely ones.
If driving a self-driving car significantly increases my odds of survival while driving, in addition to giving me huge amounts of bonus free time, then I'm definitely interested, regardless of risky but rare cases like this.
This is unlikely to cause a problem with a car's direction or motion of travel; at worst case, it may cause a blowout, but tires and rims are surprisingly tough (purposefully). I've hit potholes as large as manholes, and other than being very surprising, no damage was done.
Then again, I drive a pickup truck - I wouldn't expect something much smaller to handle as well.
Still, the rate of speed and balance of the car would all play into the scenario. While it would be better for a car to avoid an open manhole (or pothole for that matter), it generally isn't a crazy scenario if the car hits one, either.
If you want to see and hear about crazy stories of mishaps people have, yet the car continues to be mostly drivable, check out the sub-reddit "Just Rolled Into The Shop":
https://www.reddit.com/r/Justrolledintotheshop/
You'll learn both just how stupid people are with their cars and driving, as well as just how robust vehicles actually are.
> Tornado is crossing the road.
Do people really drive when there are tornados nearby? Shouldn't they be hiding in a cellar, or something?
I've driven by two (small) tornados while travelling long distances over the last 15 or so years.
A lot of stuff we take for granted such a supporting oneself by a nearby wall when loosing balance, is completely out of reach of todays "AI".
I wonder how many other possible unintended consequences there will be
Adverts only continue to exist because they ultimately find the sweetspot between inconvenience and payoff. A road mobile billboard is inconveniencing everyone and the payoff is nil. In contrast to a YouTube advert where the payoff is the youtube video, a mobile billboard has no payoff.
Cars led to more deaths than people had on horseback. I'm starting to feel autonomous vehicles will be the same sort of innovation. More elderly/younger people could use them, and ultimately more deaths will result as people's carelessness increases.
Tesla is still cashing in while resisting safety features like requiring hands on the wheel. Meanwhile, accidents like the death in Hong Kong go mostly unnoticed in the US.
I'm surprised the NHTSA doesn't have a rule saying auto-pilot should be 100% autonomous, in control, and capable of driving in the current conditions, or it should pull over, turn itself off, and put the car in manual control mode. Counting on drivers to understand when auto-pilot can and can't handle driving conditions seems like a completely stupid idea and a recipe for disaster.
Yup. The Tesla accident in Hong Kong (or Heibei province?) [1] seems like another likely case. We only know about that because the driver had a dashcam that saved the video, and the parents found a lawyer to sue. Tesla claims they don't have data on whether or not autopilot was active at the time of the crash. Yet the dashcam survived..
Tesla and others need some regulation with teeth. They should be required to have black-box style data recorders. They should also be required to report accidents involving autopilot.
Currently, car companies are not required to report accident rates involving autonomous-driving modes in most states. I think only California and a couple others require it.
[1] https://electrek.co/2016/09/14/another-fatal-tesla-autopilot...
> Because of the damage caused by the collision, the car was physically incapable of transmitting log data to our servers and we therefore have no way of knowing whether or not Autopilot was engaged at the time of the crash.
Well that is even more troubling. Looking past the suspicious lack of logs from the car in the incident, it should be a rock hard lose-your-business-license requirement for any kind of autonomy in cars, that the log data is preserved in accidents. I can imagine very few scenarios where a black box type of device could not be salvaged from a wrecked car.
EDIT: From the wording, it seems like it may actually have been the 'transmitting' of the data that was impossible. That would make things even worse, if Tesla could not even be bothered to requisition the car data (through legal means if necessary) in a case where a bug in their software may have killed someone.
Given that self driving cars are a potential job creator you might find those regulations removed.
This is the first time I’ve seen someone refer to automated cars as a job creator. It’s almost always presented as the thing that will kill the trucking and taxi jobs by the millions.
And then a massive job destroyer. Of truly scary proportions.
http://www.slate.com/blogs/moneybox/2017/01/23/kansas_city_s...
Edit: expanded on why a for profit company being pro-Republican would be against its own self interest.
I disagree. Level 4 does not require driver attention. That is still a long way off.
From Wikipedia [1]:
Level 4: The automated system can control the vehicle in all but a few environments such as severe weather. The driver must enable the automated system only when it is safe to do so. When enabled, driver attention is not required.
Level 5: Other than setting the destination and starting the system, no human intervention is required. The automatic system can drive to any location where it is legal to drive and make its own decision.
(NB: When he says "The article was talking about level 5", it's clear from context that stale2002 means that the article was talking about level 5 in terms of technological difficulty and timelines.)
Sincerely asking. Doesn’t that mean it requires driver attention?
For instance, a Level 4 car probably can't deal with unexpected road construction, and might simply bring the car to a halt, smoothly but quickly. It would be dangerous if the driver was asleep and the car stopped dead on the highway for the 30 seconds it takes someone to wakeup and get oriented, but it could be pretty safe if the driver just needs to look up from their movie and grab the wheel.
That's just speculation, though.
No, Pratt is saying that manufacturers are hyping level 4 as being around the corner, but it is not. Pratt does not think the claims for level 4 are sufficiently backed up:
"...That’s Level 4. And I wouldn’t even stop there: I would ask, “Is that at all times of the day, is it in all weather, is it in all traffic?”
> Level 4 doesn't require driver attention, it just requires the driver to be (instantly?) available if the system has a problem
How exactly would that work? You don't have to be attentive but you must be available to take over?
At any rate, this is not the definition provided by the Society of Automotive Engineers [1], which is the definition NHTSA has adopted for levels of autonomous vehicles.
SAE says for level 4:
"the driving mode-specific performance by an automated driving system of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene"
In other words, the system could request human intervention, but it will still do something even if the human does not respond.
Wikipedia appears to have either summarized this in different words or has a different version.
> this change-over is the situation that Pratt worries about in his fourth answer.
I wholeheartedly agree with Pratt that "In some ways, the worst case is a car that will need driver intervention once every 200,000 miles..."
But that doesn't actually contradict stale2002 or diminish the enormous potential economic importance by more than (say) a factor of 2. Level 4 systems that are available to use 60% of the time are still revolutionary, and compatible with both stale2002's and Pratt's comments.
> How exactly would that work?
See my comment to function_seven for my speculation. Although I used the Wikipedia definition, I believe everything I said is compatible with the definition from SAE you have quoted. In particular "the system could request human intervention, but it will still do something even if the human does not respond" does not conflict with "it just requires the driver to be available if the system has a problem" because the "something" the system may do is bring the car to a rapid (or even emergency) stop. This can become dangerous if the human can't resume control within a few seconds, but is an easily acceptable risk to occur once every 100k miles as a price of Level 4 autonomy.
stale2002 said the article is talking about level 5, and that level 4 is around the corner.
Yet the article is talking about level 5, 4, and below. It is saying some car companies are overhyping their capability to reach levels 4 and 5.
Pratt feels even level 4 is not right around the corner.
> Level 4 systems that are available to use 60% of the time are still revolutionary
To reach a certain level, you must operate under the definition of that level 100% of the time. You can't be level 4 60% of the time. That's level 3.
I agree it would be revolutionary to be at level 3. Right now no car is there. They're all at level 2, which require human monitoring of the driving situation.
No. I'm looking at the SAE definitions, where it says
> A particular vehicle may have multiple driving automation features such that it could operate at different levels depending upon the feature(s) that are engaged.
clearly indicating that the levels describe modes of operation, not immutable car classifications.
Regardless, this has just become a semantical dispute. stale2002's comment makes the most sense under the interpretation "cars that that can drive at Level 4 60% of the time are just around the corner", and that comment is a valuable counterpoint to the reasonable interpretation of Pratt's interview.
Look at the column where human attention is required ("Monitoring of Driving Environment"). Every car in existence requires human monitoring in every driving mode.
The moment attention is not required, the car company becomes liable. Volvo will release a level 4 car this year where they assume liability, however, that is only for a hundred people in Sweden.
"Around the corner" means widely available, and that's just not the case.
Right now Tesla does not reliably save the data from its accidents. How could a car company assume liability when they can't even save the data?
Based on my best understanding of the article and the good description on these levels in the CES keynote linked in the article...
This is Level 2, when the driver must be available instantly. Level 3 is when there driver must be available but there's plenty of time (the article mentioned 15 seconds) to swap.
Level 4 should not need any human intervention when engaged. It can only be engaged when it's safe to do (e.g. in a city in good weather conditions) but once it's enabled, it fulfills the task given to it without ever needing to fall back to human hands. You should be able to sit on the back seat drinking beer. Level 4 should be able to safely stop the car and wait for assistance if things go bad without driver intervention.
Level 2 is where the cars out there are now. Level 5 is a long way away.
Level 5 is "all cars in the entire world don't have steering wheels anymore". Yeah, level 5 is hard, but who cares, level 4 is good enough.
Also, as pointed out in another comment, Level 4 does require driver changeover, it's just that the car is supposed to safely handle the event of driver not responding to that request (e.g. by stopping in the middle of the road).
Well, even trains on tracks have humans ready to pull the break if something is wrong up ahead.
Would you ride a train that had an accident caused by something for which its driverless system was not prepared, but that a human conductor could have avoided?
I think it's possible level 5 will happen. There will still be accidents on roads where only driverless vehicles exist. Some people will choose to ride in such vehicles, and some won't.
I don't think that's true at all. A self-driving car can save money on not having to have a steering wheel, pedals, hand-brake etc. Possibly even won't require airbags or seat belts if safety is improved massively
non-self driving cars could become expensive luxury cars
Maybe in the future. Especially 'hardware and software to run the self-driving system' will cost a few dollars (small computer, zero amortized cost of software)
That's weird to change the definition that way. The levels describe an individual car, not all cars.
The article is mainly about: Level 5 as difficult, inconsistent application of Levels, the fact that rare difficult situations carry most of the valuable information for a learning system, preventing mismatched expectations, untenability of systems which require human attention and vigilance. The final point made was, instead of focusing on self-driving cars, focus on cars which complement human ability. For example, humans are good at theory of mind and inference in rich world models while machines are better at total situational awareness.
I'll add another. Self-Driving cars need models which at the very least, are able to capture uncertainty over predictions. This makes them more robust to glitching catastrophically in parts of the state space that are novel to them.
[1] > Yes, so NHTSA had 1 to 4, and SAE was very smart, they said we’ll take Level 4 and we’ll split it into two things, 4 and 5, and the difference is that Level 5 is everywhere at any time, and 4 is only some places at some times. But otherwise they’re basically the same. The SAE levels are fine, but people keep making mistakes. And so Level 2 systems are often called Level 3, which is wrong. A key thing of Level 3 is that the person does not need to supervise the autonomy. So no guarding of the machine by the human being.
I work in the industry. This is not true. We haven't even completely solved Level 3 yet.
This is a little misleading. Level 4 is full autonomy within certain domains. So actually Level 4 is already here today -- on test campuses. The meaningful question is when is Level 4 coming to cities. Maybe not decades but definitely not "really right around the corner".
Toyota recent technology direction isn't looking good. Instead of selling battery electric cars, they're selling hydrogen fuel cell cars in California.[1] Nobody is buying. Their electric cars are mini-cars. Something went wrong over there.
Pratt has some legitimate criticisms. But many of the really hard but rare problems can be solved by stopping, or going really slow. When you're going really slow, your sensor data from LIDAR is very good and you should have a full ground profile. If you have to inch your way through a field of rocks, that can be done. Remember, the DARPA Grand Challenge cars of 10 years ago could drive off road.
As for "why did it do that" issues, that's mostly a problem for those self-driving systems where machine learning is connected directly between camera and steering wheel. Those are easy to build and give the illusion of working, but are not going to work in hard cases. You want a world model and object recognition, like Google. You can tell how well your object recognition is working by checking its results at long range against its results at short range.
Heck if you go real slow on a highway and traffic isn't... you get rear ended at highway speed.
Or are you just gonna strap an extra lane onto the Brooklyn bridge cause self driving cars have to have it?
Also as the article pointed out human vision can see further than lidar esp in rain so what is a "comfortable speed for an entity with lidar vision is likely to get rear ended by an entity with human vision.
We could improve safety by at least 1% in lots of other ways: lowering speed limits, requiring rear view cameras, raising the licensing age and requiring more frequent tests, cracking down on drunk driving, etc. Building a fully autonomous vehicle seems unnecessarily elaborate to get a 1% safety.
Not if the vehicle also gives you functionality that doesn't currently exist. Freeing humans from having to do the driving has a huge potential value over and above the value of the safety improvement. The other safety improvements you mention don't; in fact they have less net value than the safety improvement, since they also have costs--not the cost of installing the technology, but the cost of getting where you're going more slowly, having to take driving tests more frequently, having to drive your children around till they reach an older age, etc.
> Freeing humans from having to do the driving has a huge
> potential value
Except that it does not. What would have a value is getting rid of the need to be in traffic at all, no matter self or not self driving car you use.That has value too, but it's a lot less likely than self-driving cars for the foreseeable future. Plus, even if we grant that not having to be in traffic has value, that doesn't mean that not having to do the driving doesn't also have value. They both do.
You contradicted here but provided nothing to back it up? Why don't you think freeing people from driving has value?
http://www.abc.net.au/news/2016-10-26/speed-enforcement-detr...
Most of our safety improvements have come from better car designs like crumple zones, ABS, air bags.
The more you go against natural human behaviours and start treating humans like machines with very low tolerances, the more it makes sense to just have machines do the job
Like cruise control you set it up, for instance to a maximum speed of 50km/h. Then your car won't go over the speed, unless you decide to override it.
I find the design decision they made to let you override the limit very clever : if you press more aggressively on the accelerator pedal, you reach a second max level, which disables the speed limiter. So you feel like originally you already were on full throttle but you have an option to go even more full throttle.
Driving in the city, you don't have to look at your speedometer and can focus on the road more
Isn't the autonomous software systems used in these cars a lot less like a machine and more like a piss poor excuse of a human being? I mean, it is not a machine like the printing press, or a factory assembly line made of robots.
I mean, these systems are "fuzzy" enough to stop them being considered as a machine in the usual sense of the word. So letting the "machine do the job" might not be as good an idea as using a washing machine.
Australia does not take traffic crashes seriously at all.
But to be fair given the level of congestion and quality of the roads I doubt the point of speed cameras at all within the CBD. It's purely revenue raising.
And strongly disagree that Australia doesn't take crashes seriously. We are one of the most regulated societies in the world.
After losing a friend to a DUI driver, I see DUI as being on the order of a manslaughter. I don't want the 12.5 years in jail that a first offense manslaughter charge carries, but the first offense of a 1 year license suspension seems far too light, and the repeat offense terms are egregiously light.
Would you be for making the punishment for texting and driving worse than a DUI? It should be if it's relative to the harm it causes.
I'm only partially being sarcastic. I'm genuinely curious how these punishments for being impaired scale up. I would rather have someone drive by me after 4 drinks who is not tired rather than a mother running on 2 hours asleep with a screaming baby (sleep deprivation is also as bad as drunk driving). Yet the former would lose his/her license at a checkpoint for a year and face a $10k fine, which you say is too little. But the latter would be waved on through.
It all seems very arbitrary and detached from the risk imposed and rather attached to the societal naughtiness of the activity.
So doing something that has a chance of killing someone is equally as bad as killing someone?
I agree driving under the influence is bad, but I disagree that it is just as bad as manslaughter.
Which is why GP didn't say "as being equally as bad".
So switching over when they're 1% safer doesn't mean that's the end state. The margin will keep increasing for many years after that.
Please lord, this. I hate backing up.
Kind of like coding in javascript.
Now if roads are outfitted with instrumentation for autonomous vehicles, _and_ human drivers are prohibited on such roads, _then_ we _might_ see full autonomy. But not before.
If it were up to me, I'd focus on this instrumentation instead: RF guide wires/tags for car localization on the pavement, machine readable signage (even in fog, snow, and heavy rain -- conditions with which cameras and LIDARs cannot deal in principle), inter-car coordination mesh networks and security thereof, autonomous vehicle readable road work signage, police gear to direct traffic of autonomous vehicles, and so on and so forth. There. Hundred billion dollars worth of startups in one paragraph.
As things stand, you can only be fully autonomous at 25mph in California where it never rains, as long as there's no fog, no road work, and no one has messed up the markings on the pavement.
The current generation of self-driving cars is fairly impressive already, but what I'd like to see is a city full of them. I have a feeling that self-driving only works as long as the majority of drivers are human drivers. It's trivially easy to come up with traffic situations that could lead to a deadlock by blidndly following the rules.
Humans will use hand signals, eye contact or someone will violate the rules a little or make way when they don't strictly have to in order to ensure that traffic flows.
I think that car-to-car and/or car-to-road communications will be required before large scale deployment is possible. And I have not heard from a cross-manufacturer effort of creating a protocol for such communication.
Although I do understand why the automotive industry is hell bent on getting their level 2 autonomy out there. Money from the customers is needed to keep the R&D effort going.
I personally did not understand why anyone would want a Level 2 car where you have to be constantly on the lookout until I visited Silicon Valley and drove a stint on US Hwy 101 in rush hour. And I guess this is the initial target market for the self-driving car industry: wealthy individuals who have a stressful morning commute in stop'n'go traffic. Money from these early adopters will go to funding the R&D for the next generation in the hopes that Level 4/5 will some day become reality.
But in my conservative estimate, that's still years away from being adopted en masse. There may be a significant minority of them on the road in 3-5 years but I can't imagine it working very well if they were in the majority.
Absolutely, been saying this for years (yes, me too :). We will eventually achieve a lot more autonomy and robotization of driving, but it will require massive infrastructural changes, much like the transition from horses to cars.
Why is that a political problem?
Slightly better than average doesn't sound that great to me.
If there's a severe blizzard and my car can't see the road in front of it and we're in a 4G dead zone and it can't get an accurate enough GPS fix to figure out where it's going, I'd be perfectly happy if it safely pulled over to the side of the road and stopped. Heck, I'd prefer to have it safely pull over rather than trying to continue based on some premise of "this vehicle be able to navigate under all possible conditions".
Level 3 is when you have ample time before the switchover, and Level 2 is when the driver must be there in a matter of seconds.
Heck, there could be live read-out of "probability of accident", "probability of death" etc... once we get to level 4 to 5. Computer asks you whether or not to proceed.
What's the threshold at which the computer should be programmed not to proceed? This moral rabbit hole gets big picture fast.
https://www.sae.org/misc/pdfs/automated_driving.pdf
the driving mode-specific performance by an automated driving system of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene
The only way to do all aspects of the dynamic driving task when conditions are untenable is to stop.
For example here in Australia we have an animal called a Kangaroo which when a car approaches will move completely randomly. This includes at the last second jumping straight in front of a car. Most drivers from these areas know to slow down and attempt to drive in the middle of the road if at all possible.
Surely weird situations like this which require local knowledge exist all across the world. But I've yet to see any acknowledgement that this is useful.
I think that the reason why this isn't acknowledged (by people who should know) is likely to be a political one. Examining the solution that I typically seen given for this problem should explain why.
First, the assumption is that driving algorithms are updated to account for any edge case (for instance, an unpredictable animal jumped out this time) after it occurs, so that case is then guaranteed to not re-occur.
This presents a problem: anyone who's ever worked with software before knows that that's an impossibility until a sufficient number of incidents happen in nearly identical ways, or until a fix is manually applied (which itself could take a very long time).
But we fall back on the second part of our argument, statistics. The fact that you're going to crash into something you wouldn't before is outweighed by more than one other person not crashing in a place where the computer can predict and avoid a crash more effectively than a human.
This too, presents a problem, if you also consider the implication that the availability of manual-driving cars will likely be degraded in some way after the introduction of self-driving ones (from having increased cost/regulation/insurance premiums or simply being banned entirely).
If we discount these "weird" situations and fail to make allowances for them, people will get hurt where they wouldn't otherwise (even if the local or global sum of deaths is reduced). The benefits skew in favor of cities where traffic behavior is/will be much more consistent.
So it's best if local knowledge can't be useful- why complicate the matter or feed skeptics talking points if you don't need to?
Why would you need to see any public acknowledgement of something so basic/obvious from very advanced teams working privately on issues like this?
For city driving, these systems need to account for kids straying onto roads, read temporary/roadwork signage, all sorts of random things.
There is a lot of hype regarding deep learning, but I have struggled to find a concise definition apart from the fact that it is now relatively easy to work with monstrously big networks. Backprop and related algorithms have been around for decades. From what I remember of neural nets, one huge drawback was that they would be close to un-debuggable. The learning contained in the net would be inscrutable to a human, to all intents and purposes. Failure data could be recorded and replayed, but any actual reason for failure would frequently not be found. So, tweak the network, resize some layers and try again... I can think of several reasons why that's fundamentally unsuitable to the problem of driving.
I was in Egypt recently, and the sheer amount of lane crossing, merging, pedestrians ducking through multiple lanes of traffic, roadside obstacles, donkey-drawn vehicles etc would be 100% impervious to even a level 3 solution today. I believe the same would be true in India and many other parts of Africa.
So, I really hope that we are not falling blindly into another 5th Generation sinkhole here. History should have taught us better.
By that I mean, all automated cars (especially level 5) would need some kind of network connection (both cellular and mesh) - which means "your" car (if you own one - which from the looks of how things are shaping is going to be highly unlikely), could easily be stopped for variety of reasons with or without your permissions.
It could be hacked by 3 letter agencies, or by hackers who can than case mass disruption.
While I'm not against self driving cars, I'm very cautious against the "self-driving are the best - they'll reduce death on the road and if you don't support it you are a death loving luddite who can't get on with the times" school of thought.
We saw what happened with we gave up control on our phones, and that's slowly happening to our computers (sure, most of readers here can run/use linux, but linux on desktops still has a much lower market share compared to Windows 10).
I just feel like it's not the right future that I imagined as a kid watching star trek and it's disappointing.
EDIT: another unrelated point I'd like to add is the fact that if we want to have autonomous cars on the road - we'd need co-operation between various companies (which would be easy - we have browser vendors do that, why not car companies?), but more importantly, we need a huge overhaul of our infrastructure for autonomous cars and we need to outlaw humans driving cars on such roads).
One way to circumvent this is establish special lanes for self-driving cars where things are much more controlled, well defined and cars in that lane can communicate with each other to avoid crashes. Long segments of highways might be great candidates. This can heat up the virtuous cycle where people buy self-driving cars to be in that lane which pressures authorities to make more lanes available for them and eventually most lanes are for self-driving cars.
You don't need autocars to be 1000 times better than humans. You just need them to be equally good as the average driver ALL THE TIME, such that they're never distracted, sleepy, driving unlawfully, etc. The occasional lapse in driver competence is the cause for the vast majority of crashes. I suspect the limitations of driver (or autocar) perception plays a small role in most accidents when compared to lapses.
As residents of a developed country, with a very low death rate per mile driven, we also see traffic risks very differently than the world's norm. The annual death rate per 100k motor vehicles in the US is 13; in India it's 130 in Africa it's 574. In the more unsafe countries, I suspect driver error is the cause of 99% of accidents. Replacing human driver decisions with autocars would reduce worldwide driver fatality risk enormously, reducing perhaps 90% of global traffic fatalities -- about one million people a year.
> At least one manufacturer is afraid that human drivers will bully self driving cars operating with level two autonomy, so they are taking care that in their level 3 real world trials the cars look identical to conventional models, so that other drivers will not cut them off and take advantage of the heightened safety levels that lead to autonomous vehicle driving more cautiously.
If you removed Tesla from the equation, Level 4 autonomy would be half a decade away... it's pretty sad how far behind the industry is from this perennially cash strapped upstart.
Elon's claims notwithstanding, Tesla may actually be half a decade away from L4.
> It's pretty sad how far behind ...
Maybe they are just trying to not over-promise and under-deliver?
This is simply untrue. Volvo will have a release this year.
The notion that Tesla are the only ones innovating because they're the only ones using the public as guinea pigs is hogwash. Mobileye, Tesla's original self driving technology, isn't even part of Tesla. They have other clients.
http://blog.caranddriver.com/meet-the-first-real-family-slat...
The 1% safety people would take the deal at 99% repaid deaths. But I think most people would only be comfortable with a number much lower.
Are their organs usable?
Sounds like a no brainer if they are?
Or does the genie reduce the people killed by the ones no longer saved by organ donations from car accidents?
The genie might have to bring people back to life.
This might make people uncomfortable.
Also try and make it target the purveyors of stupid hypothetical arguments.
This example is not in even remotely close to any situation autonomous vehicles can present.
(The scenario needs work, though - it should be Y people chosen from the road users in question, not just Y random humans.)
It's a testament to Tesla's propaganda that he took the bet. I look forward to claiming my $500 in 10 years time.
If you reformulate the bet as "it will be possible to legally ride in a driverless cab without a license somewhere in the world by the end of 2027" I'll take the bet for $20.
I think you might win your original bet on the technicality of car sales lots being averse to selling these kinds of things and ride sharing services being early movers, and more amenable to insurance. Being able to keep cars in a specific service area will help.
In other words, it takes us two-ish years to learn how to use our vocal cords, and another two to three years to get to 80% of an adult's vocabulary. And yet it takes another 12 years just to increase our vocabularies a handful of percent and to become fairly proficient at piecing together those words into coherent and mature enough communication for full time employment.
And that is just one example. Learn 90% of Haskell in one afternoon...learn the rest over the next two decades of your life. Learn 90% of derivatives trading from one book, but spend the rest of your life learning the rest. They aren't examples so much as they are a fact of life: There is an extremely long tail to learning, and extrapolation of where you will be given how fast you've learned up to some arbitrary point will be impossible.
Self driving cars aren't just learning the rules of the road. They are learning human spatial sensory perception and fast heuristics for ad hoc path planning that have been evolved over several millenia. And yes, they are becoming extremely capable extremely quickly...but you won't be able to extrapolate linearly to get to a point where they can take over.
Not that it affects your point at all, I'm just thinking about words now. And while I'm on the subject, XKCD's "Thing Explainer," a book on how things work using only the 1000 most common words, is great fun.
Are they different people, or did he change the spelling of his name when he moved from legs to wheels? Or is he developing walking cars for Toyota?
Actually his first name is spelled two different ways on this one page, and he looks like the same person, so maybe he changes the spelling of his name frequently: http://images.sciencesource.com/preview/BA4147.html
This seems to be a more responsible and comprehensive engineering perspective than the frenzy and hand waving that accompanies most self driving topics here.
Overestimating AI with little to no data and vastly underestimating not only human driving but the varied traffic conditions they operate in doesn't seem like a realistic or responsible way to solve the problem.
Uber only needs to get to level 4 to change the world.
So they roll out slowly, expanding the possible trips covered as their technology advances.
Since they have such fine control over which routes and which conditions the cars will be expected to perform in, they're actually ideally positioned to work with this technology.
a similar idea would do quite a bit to move the technology forward and increase acceptance. we already have projects that create toll and hov lanes. why can't these also be equipped to assist self driving cars with their tasks?
While I think the Tesla videos were cool, even GM did something similar recently in San Francisco, they are still pretty much scripted events. Tesla is guilty of exploiting the over trusting side of the issue simply by product naming but some of their demos could lead people into assuming far too much ability; will that become a legal liability?