A computer won't be speeding on a residential street. It will identify a child standing on a curb for tracking but otherwise not react to it until it determined that the kid's trajectory would likely intersect the car's. In that case it would break as hard as it needs to bring a car to a quick and safe stop.
But yes, deer beside faster roads etc. should probably trigger precautionary measures to ensure reaction times will be sufficient.
It's despicable that anyone thinks it's acceptable, but it's different to say "you aren't allowed to beat that child to death when you're trying to get home after an exhausting day of work" than to say "Google isn't allowed to beat that child to death in order to sell a few extra taxis".
Cars driven by humans redesigned our cities. Cars driven by computers will probably redesign them again.
(That's not to mention the usual disregard for traffic rules - and thus basic safety - an average human driver has, which other commenters have touched on.)
> Reaction times vary greatly with situation and from person to person between about 0.7 to 3 seconds (sec or s) or more. Some accident reconstruction specialists use 1.5 seconds. A controlled study in 2000 (IEA2000_ABS51.pdf) found average driver reaction brake time to be 2.3 seconds
Unless you expect rocket-propelled children being launched from the sidewalk, that's pretty much it.
(Of course the actual implementation within the entire system will be more complicated, but my point is - a computer can precisely compute what a human tends to intuit.)
A human can tell if there is something going on at the side of the road that might make the human jump into the road. Machines are nowhere near being able to understand the context of many situations that allow humans to predict these things.
How are you expecting to be able to regulate implementation specific details like this across the industry? How would you enforce entirely requirements like this? If it's left to invisible hand of the market I would assume that the demand would be higher for cars with more aggressive driving styles, that will get you from A to B faster.
The situation is super dangerous with human drivers anyway. Children are too small to be noticed and they don't hesitate to jump in front of cars.
If you don’t anticipate the possible movement, you will be too slow. I have very little faith that we are anywhere near systems that can handle this kind of situational awareness, because it requires classification systems and object models of the world that modern AI has yet to reproduce.
The average level of human intelligence is a lot higher than most casual observers realize.
https://waymo.com/safetyreport/
I would guess that they already identify and track pedestrians better than the average human driver (mostly because I expect they do it at greater distance). Whether they model kids standing by the curb better is hard to say.
If I see a child standing near the side of the road, I use more than the velocity and trajectory of the child to estimate future behavior: I look at the direction the child is facing, the overall situation (e.g. is the child playing a game?), what the child is paying attention to, and so on. A child waiting at a bus stop is a dramatically different scenario than a child looking across the street at a puppy. A short adult standing on the side of the road is dramatically different than a child.
This is a hard problem involving multiple levels of recognition and inference. I have little faith that it is solved. My suspicion is that the “engineering solution” is used (i.e. slow down when a human-probable object is near the road). That might work, but will lead to a car thar drives like a paranoid senior citizen with bad eyesight.
I have a suspicion that we’re going to look back in a decade and realize that most of these problems are fundamentally intractable, and that the best any system can do is react via human-encoded heuristics. If so, the path to full autonomy will be an asymptotic one; it will not happen quickly, but through decades of gradual refinement, with lots of fatalities along the way.
I think that the always-sensible speed choices of the automated system will result in a much larger reduction in pedestrian fatalities than any increase from the lack of subtle inference you are concerned with.
Intractable problems can be solved sometimes, just not reliably or in bounded time. If we get to the point where self-driving cars depend on human-encoded rules for reaction, we’ll simply be trading one set of messy heuristic behaviors (people) for another (robots with bad sensors and limited domain awareness).
Will the automated systems be “better” with enough time and investment? Perhaps. But dreams of a fatality-free automobile future will remain science fiction.
i'm pretty sure that during millions of miles of say Waymo's video captured, there has been a lot of people (incl. children) stepping off the sidewalk to cross the road - you don't need that to happen right in front of your car - so their system analyzing the images does recognize the pedestrians and thus their potential for movement.
The solution for self driving cars is easy. Don't ever put yourself in a position where physics prevents you from breaking in time.
They can do this by driving conservatively and not doing dumb things like driving around a corner quickly.
Nobody wants a self driving car that's always driving like a student driver.
Especially if I get the huge benefit of not having to drive.
Driving risky really doesnt speed up your commute very much.
>Especially if I get the huge benefit of not having to drive.
>Driving risky really doesnt speed up your commute very much.
A car behaving will be like a student driver (or delivery truck) at every intersection at which it needs to pull into traffic could easily double or triple your commute time depending on your commute.
Pulling out into traffic should be something that a driver-less car can be much better at. If it isn't at least as good as the average perspective customer people won't buy it.
I would say this is particularly critical metric for taxi fleets since they do a lot of driving on city side streets. People will take taxi with the human if it's faster.
You can already look at Uber pool, which is a direct tradeoff between cost and speed.
The '03 Crown Vic has long since paid off it's capital costs and the cab company gets to blame the driver if things go far enough south for lawyers to get involved.
Until some mythical future where self driving cars are so good and common that the "progressive" states start providing financial disincentives for people to operate their own vehicles (which would be a pretty major about face the vast majority of all transportation and infrastructure related regulation to date) I don't see where the driver-less taxi has a cost advantage in the foreseeable future. Your insurance premium is in large part based on the presence of everyone else around you.
It doesn't matter if the cars cost 100K, the driver wages still are larger than the capital costs.
It seems a human augmented with computers should be the first step before any kind of full autonomy.
It already does. Google colloquially calls it the "idiot detector". It includes things like small children, teenagers on skateboards, bicyclists, etc.
It was responsible for a bit of hilarity that when a hipster was rocking on his fixie at a stop sign, the car would start and stop entering the intersection.
Cars are probably better than humans at detection now.
Self-driving cars see the dog and the child somewhat close to the road and classify them as a hazard IMMEDIATELY and start adjusting for them. And, if they lose track of them, the car goes into "Unseen Idiot" mode. You don't need the dog running out to focus their attention like a human does.
Self-driving cars don't have the attention span problems that humans have. Self-driving cars can watch more than 7 +/- 2 objects (much more) without diverting their attention.
Which means that self-driving cars can watch all 6 of those little kids walking, as well as the 4 on bicycles, and the two playing with the dog over there.
This is why self-driving cars will win ... and quickly.
This stuff is harder than it looks at first glance. Hence the article.
Yes it does. A dog can be run over in order to avoid colliding with a human; the reverse is not true.
> Waymo’s planner can also think several steps ahead. For example, if our software perceives that an adjacent lane ahead is closed due to construction, and predicts that a cyclist in that lane will move over, our planner can make the decision to slow down or make room for the cyclist well ahead of time.
https://storage.googleapis.com/sdc-prod/v1/safety-report/way...
Drive slowly and conservatively, and never ever be in a situation where physics would prevent the car from slowing down in time.
Computers have the attention, but require near infinite training.
Pre-process a few of the child's available functions, and some of yours, to find any collisions in the data. Decrease speed on a gradient equivalent to the probability of collision. (Step 1 - access child's datastore, or be a similar-enough neuroprocessor that the same data is replicated to you locally.)
The number of objects in motion in a roadway space can make this processing prohibitive, which is why we failover to humans. Also, adult humans have more experience (data) at being a child, and so are much more capable of analyzing and predicting with this data, than a self-driving car - at least today.
Of course, I've learned these things from growing up human, but only one computer needs to conquer a driving challenge, maybe driving on a snow hidden road (watch out for barely noticeable ditches on the sides of the road), and then all self-driving cars can do it. It will be interesting to see how long it will take to achieve level 5.