[mturmon]

One of the lessons of these first steps toward autonomous driving is: if you have a big array of sensors, and plenty of on board computing, then many driving problems, especially in semi controlled circumstances, like open highways, are within our grasp now.

The sensors and computing are expensive now - especially lidar. But that's an engineering problem, as you suggest.

[jacquesm]

The problems in automated driving are not in controlled and normal circumstances but in all the edge cases and exceptions.

[mturmon]

No objection. But portions of commercial routes can be arranged to get around many of these edge cases.

I was trying to address the question raised by the comment above: is this a problem of principles or of engineering, by saying that for a big (proportion TBD) segment of routes, it's engineering. Put onboard a bunch of sensors and computer power.

[jacquesm]

Yes, but that is a hack of sorts, and if the volumes are low a very expensive one so likely this will not happen until there is a sizable fleet of vehicles that can take advantage of it. You'd expect those things to happen in lock-step.

The apples-to-apples comparison of automated driving to normal driving is that we have an existing road system and we want to use that for automated driving and normal driving and automated driving should meet or exceed normal driving if it is to be successful.

The ultimate adapted commercial route for transport is called a railway, any kind of re-arrangement of the road system in order to adapt it for better use for automated driving is going to be a 'first world only' affair, and probably only a very small subset of that first world.

So for the foreseeable future automated driving systems will have to cope with all of the eventualities, even if for some stretch of their workload they may find things a little easier because of special adaptations (which of course will have to be equally accommodating to human drivers, or at a minimum not hinder them).

[anabis]

>'first world only' affair, and probably only a very small subset of that first world.

As in, heavily trafficked inner city routes like buses. I think it will make a lot of impact fast.

[Retric]

People also do really poorly in edge cases. Don't forget self driving cars are going to quickly have billions of road miles worth of data.

There are plenty of videos of autonomous cars is highly chaotic road conditions, but that's all old hat. Weather is an issue, but weather is also forecastable. Even if you only get rid of truckers in areas stay above freezing that's still a massive change.

[jacquesm]

> People also do really poorly in edge cases.

That's true but if they are simply different edge cases it might already be problematic.

And yes, the data will be there. But even if deep learning + lots of data is 'indistinguishable from magic' that does nothing to dispel the feeling of loss of control and every accident where regular drivers would think 'that would never happen to me' (see the Tesla one with the truck that got rammed) is going to make this a much harder battle.

So the question is: will the initial deployment of self driving vehicles be sufficiently impressive that any such errors will be forgiven?

I'm on the fence on this one, I have no idea where it will go but I'm kind of happy that this is happening now. I got to enjoy the 'drive yourself' period of driving in some of the best cars that were ever made and at the same time I'll probably be able to enjoy increased mobility due to some form of assisted driving much longer than what I would accept for myself as an autonomous driver.

[neltnerb]

Just don't forget that the competition isn't a perfect driver, but a human one. That's a much lower bar.

[tedsanders]

It's not that much lower. In all the Lyft/Uber/Taxi rides I've taken, not once has the driver ever crashed or disengaged. Humans go around 100 million miles per fatality, if I recall correctly. The bar isn't perfection, I agree, but humanity is still a high hurdle (especially when we cost as little as $7/hr).