You drive up to the highway, and then relax until you need to get off - sounds like a great start to me. You can equip that highway with a boat load of sensors and transmitters to understand these fancy brainy machines. After a few years, build more such highways with the lessons learnt from the experiments.

The problem is that, while this would be a really nice car feature (and probably great for safety), it does nothing for the people who don't want to own a car and just want a car and computer driver at their beck and call. Unfortunately for these folks, the autonomous highway driving is relatively near-term while door-to-door autonomy is probably decades away.

If the lines aren’t painted on the side of the road, they can’t drive.

If they meet a road sign they don’t know, they can’t drive. We have several “special” signs In Denmark, but a lot of the times it’s because the sign was too faded/dirty/covered in snow.

Of leaves, branches and some such are on the road, they can’t drive.

If traffic misbehaves, they can’t drive.

If road quality drops, or there is big pools of water on the side of the road, they can’t drive.

Basically they can’t drive.

I can’t tell you what tech we are testing, but we are trying two different manufacturers and they are both “cutting edge” and we’re testing a fleet of 16 cars over 3 years.

Another municipaly managed to get an autonomous bus going in its city center though, so it’s definitely still coming, it’s just really really far away.

About 10 years ago, I read a paper from an Institute of Transportation in Australia about the use of low power microwave transmitters along the lanes of the highway which can "guide" the intelligent cars along the highways and also the idea of a car mesh that can communicate learning( as in I found a pot hole here that wasn't in our map, be careful!) That sounds a very practical approach of course with the government investment on roads. After all, it is the government's charter to build public infrastructure! The car companies need to work with public policy and not try to make something within their bounds.

Imagine a system that munches visual clues + RADAR/LIDAR data + Microwave or RF transmitters embedded in the road + GPS/SATNAV + data from other cars via local mesh network. Now, that I'd think about trusting a little bit. Also, I'd definitely be watching 007 movies while my car drives me :-)

   it does nothing for the people who don't want to own a car and just want a car and computer driver at their beck and call. 

If you could make a Tesla owner's commute from SF to Sand Hill Road a much better experience (via autonomous-only toll road), I'd say that's one hell of a start.

But it might be another of those the perfect is the enemy of the good type situations.

I had a motorcyclist riding on the shoulder of the highway going in the opposite direction as traffic only this Saturday.

I bet i could use a bored child and a drone to stop level 5 cars.

Fully Autonomous vehicles are a fools errand. Volvo has it right.

Go ahead and do it.

FWIW, there are lots of constrained environments with fully autonomous vehicles. Volvo themselves have autonomous trucks operating in mines:

http://www.volvogroup.com/en-en/news/2016/sep/news-2297091.h...

”The cars would be able to run in fully "unsupervised" autonomous mode on certain, pre-approved and pre-mapped freeways in their respective communities”. Volvo said that drivers would be able to fully disengage from the driving process, instead spending time reading a book or watching a video.

Because car companies are not in the business of building highways is my guess.

You mean the private-project innovators here, right?

I can't for the life of me understand why people would think that the sponsors/"corruptors" would act better without a government, even when parts of that government is corrupted by the private entities.

(Also, you'll unfortunately discover that a subset of customers are total assholes. These days I believe that working in a customer service, or other field that has you interact with a wide variety of people on a daily basis, is the best way to ultimately lose faith in humanity.)

Also, customers were the worst. Either from wanting free stuff because they came in so often to wanting preferential treatment because they were older, the vast majority of customers seem to want everything handed to them on a silver platter.

There’s a reason why most government offices are full of 1970s olive tile and orange cubicles.

  Why don't we start with an experimental inter-city highway where cars could run with full automation?

Use an ICO to build an autonomous vehicle-only highway stacked with sensors etc. SF to Oakland for instance. Token value increases as more people use the road. Token has inherent value because it’s the only way to access the road.

The problem with an inter-city highway is that you would have to require every car driving on it to be able to recognize and interact with those sensors. That would be decidedly unfair to those who cannot afford to upgrade their car to go on that road.

So that does bring up an interesting question though, when and where are we going to have roads where only autonomous vehicles are allowed?

the pros for all is that it is limited access, we already have many areas with HOV and Toll lanes that can be adapted, very simple driving conditions, easy to visually mark and electronically mark as well. Heck you could initially finance it by making them all toll lanes until widespread adoption / etc

That's what they said about I90 in MA and that was how many decades ago. The government doesn't get rid of revenue sources.

The sampling rate of the sensors should be diminished, maybe halved or even more, in order to make it harder for the car to park.

The car should observe, also with a low sampling rate, how the driver drives the car, make it's own prognostics on how it would drive, and compare them with what the driver chose to do, in order to learn. In that case the driver should be able to indicate the car that a certain action he/she performed, should be forgotten by the car, flagged as an illegal or dangerous maneuver.

When a car can do that well, park and project, then the sample rate should get upped in order to feed the car with more reliable data. If it handles that data without hiccups, and increased reliability, then a next stage can begin.

Who could've thunk it?! The people who think we're going to have real Level 5 autonomous driving in 2 years (not the "we're bullshitting you with Level 5, but it's really more like Level 3.5" kind) are insane.

There's no way we're going to simulate every single condition a car could encounter anywhere on Earth and get the cars to do the "right thing" 100% of the time by 2019-2020.

I'll be impressed if they even deliver Level 4 (working perfectly only on some types of roads) by 2020. But I think even then car makers will "encounter the unexpected".

It's going to take many years to test these things. And no car makers seem to even mention how they're going to address all the security issues self-driving cars will have.

I like how you added "by 2019-2020", as if doing the right thing 100% of the time was ever possible - let alone the goal. Of course, it isn't - Level 5 is just as good as a human. And extremely rare situation won't be handled well by a human either.

Even if companies figure out way to not get sued, its only matter of time until some very serious tragedy happens such as pregnant woman wearing same dress as color of sky crossing the road getting killed or car running in to school kids. Then there are obvious malicious usage such as modifying car sensors to fool self-driving system and purposely run in to people (cars as weapon scenario). One such thing and it could likely be the trigger for large public outcry, heavy regulations and finally game over for self-driving cars.

I think it might be more desirable to approach self-driving cars in more evolutionary fashion. We can start with self-driving only in less than 25 miles/hr scenarios such as heavy traffic OR sunny days on highways. Then we can start equiping our road networks with dedicated self-driving lanes, supportive beacons on roads and so on. Then gradually move towards make all lanes self-driving.

Why not?

Most people who are still in the media saying it can be done have a financial stake in saying those things. This doesn't make it true.

They'll get 90% there and never really figure out the other 10%.

If it proves to be difficult enough, that level will be when self driving cars are only marginally better than human drivers. That is an unlikely scenario, but it will probably stagnate at a far less perfect level than all but the most pragmatic dreamers envision.

Not before a long time.

A death is really expensive, Americans are trained to sue like crazy, a car accident is a simple case to grasp and attribute to the manufacturer who has a lot of money to pay.

The US has this "anyone can sue anyone at anytime for crazy damages" system. I'd expect any issue to quickly be brought to court and make an example out of them.

Last but not least, after the first death related to a self driving car, the second death will be on the journalists fighting for the coverage.

The first death already happened with a tesla.

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.

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

From http://copradar.com/redlight/factors/

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 the different aspects of autonomy, perception and intent modeling are the unsolved pieces, with the other aspects being relatively well understood. The quality of your sensors (resolution, dynamic range, depth range for Lidar/radar etc) affect the difficulty of the perception task, as does computational power, but even with perfect sensors and high compute the problem is difficult (recognizing the difference between a rock and a crumpled piece of paper requires algorithmic processing of sensor data). The difficulty of perception is best illustrated by pointing to the field of computer vision, which is essentially focused on solving that problem. What seems easy to a human is quite hard for a computer, but really it's only easy at the conscious level, while in fact 70% of the human brain is dedicated to solving the vision problem at any given time.

All the steps after perception rely crucially on it. If perception were perfectly solved, intent modeling is also a difficult problem, but it is relatively easier than perception, as it involves reasoning in a lower dimensional state-action space, albeit with partial information. To make a comparison, intent modeling for diving in urban environments is perhaps harder than beating humans at Go, and may be as hard as beating humans at poker.

If perception and intent modeling are solved, the execution of path planning and control is relatively well understood.

To summarize, the main issues are perception and intent modeling, and these are fundamentally difficult AI problems. So the main thing holding back GM/Volvo/Google is algorithms.

I'm not an expert in the space, but it seems the main issue is the technology is still in (generously) alpha. Basically: the blocker is the technology doesn't work, for any definition of "work" that a layperson would recognize.

Speed control, lane keeping and basic rules are fairly simple. But recognizing a red light when the sun is behind it? Or the bulb is burnt out? Or power is down? Or your windshield is cover with water from a deluge of rain fall? And so on for every single condition, corner, intersection, etc.

It's why 'autopilot' Teslas drive into the side of semi-trucks and rear-end delivery vans pulled over on the shoulder. And we're not even talking about snowy conditions.

In the meantime, business executives and media work hand-in-hand to try and hype everything and promising stuff which cannot be delivered in a short amount of time.

In the race to build a functional autonomous vehicle some companies are getting it done, and others, in spite of big promises, several years of effort, and scaled, well capitalized operations have very little to show for their efforts.

Everybody still has a lot of work to do, but the operations that can, at the very least, demonstrate as proof of concept their cars handling just a few miles of of uninterrupted driving in dynamic environments have cleared the biggest hurdle. Following that big hurdle is the validation process, which is tens of thousands of smaller hurdles stretching out as far as the eye can see, but so long as they've cleared the first, biggest hurdles, you can be reasonably confident they'll get to a minimum viable product eventually so long as they keep at it.

I have confidence in Waymo, GM, and Zoox. With everyone else it's either too soon to tell, or I don't have enough information, or they're sucking:

https://youtu.be/jClxcSBNwcw

So if you're looking for CV/ML people working on the perception part of the stack, look there.

FWIW, I work in this field now and I have fairly low confidence in the non-ML parts of the software stack across the industry. There's a lot more to this problem than well manicured computer-vision demos, and Volvo is a lot less cavalier about loss of human life than almost anyone else, so it's fairly heartening to see them realign around realistic expectations.

Where have the results of their experiments been published such that you feel confident in stating that?

[1]: https://www.theguardian.com/technology/2017/nov/20/uber-volv...

measure once cut twice