> Dumb question: how do these systems distinguish a traffic light?
Well, how do you distinguish / identify a traffic light?
For me it's a combination of knowing the area, knowing what a traffic light looks like, and observing the behaviour of traffic around (mostly in front) of me (if the intersection isn't visible).
For an autonomous vehicle, they'd use the same methods plus they'd have the non-trivial added benefit of colleague robots feeding them updated information.
> Suppose the sun is shining straight at you and you need to squint ...
I'm sure the human eye + sunglasses + visor comes a poor second compared to CCD + mechanical + IR + (etc) can do.
> What about when it's raining, misting or drizzling, snowing heavily, etc. and the traffic lights are these fragmented outlines that you, the human, can heuristically distinguish but a machine might not?
Interesting use of the word heuristic there. If you can determine the heuristics you are using, then an autonomous vehicle can use the same.
> One last thought: suppose it's right turn on red and first car in line is a self-driving vehicle. Can it really look left and safely determine there's enough time to beat the cross traffic? If it's highly conservative and just waits until green, there could be ten irate motorists behind it and guaranteed to honk and curse.
This, and variations, frequently come up in discussions on AV. There's an implicit expectation that no one building these things has considered this problem (this is clearly false). There's two explicit expectations that once a tipping point of AV's are out there, a) there'll be a regulatory push to massively accelerate the adoption close to 100%, and b) inter-vehicle communication means this problem won't arise. In the short term these problems may occur, but to address your question, yes, I'd suggest a computer would be better able to predict if there's enough time to safely turn than most humans.
> I worry that if these machines can't demonstrate 110% of a human's ability ...
Which human would you pick?
Anyway, I wouldn't worry - none of these problems are intractable.
OK the inter-vehicle communication and crowd sourcing and AI sound like they will manage it. I'm assuming though that we'll eventually want AV-aware sensors attached to every light and every stop sign and every intersection. UHF RFID or some such that is cheap to deploy.
I think there'd be massive cost in retro-fitting lights and intersections - probably easier to agree on a mechanism for new infrastructure, and rely upon current approaches for extant infrastructure.
My concern is more about the regulatory side -- before any of this stuff gets widely deployed, various authorities are going to have to come up with some standards, and for the most part nation states are spectacularly poor at doing this sensibly in isolation, and horrendously woeful at doing it in cooperation. I suspect we'll end up with cars & infrastructure that are not 100% interoperable across borders.
Well, how do you distinguish / identify a traffic light?
For me it's a combination of knowing the area, knowing what a traffic light looks like, and observing the behaviour of traffic around (mostly in front) of me (if the intersection isn't visible).
For an autonomous vehicle, they'd use the same methods plus they'd have the non-trivial added benefit of colleague robots feeding them updated information.
> Suppose the sun is shining straight at you and you need to squint ...
I'm sure the human eye + sunglasses + visor comes a poor second compared to CCD + mechanical + IR + (etc) can do.
> What about when it's raining, misting or drizzling, snowing heavily, etc. and the traffic lights are these fragmented outlines that you, the human, can heuristically distinguish but a machine might not?
Interesting use of the word heuristic there. If you can determine the heuristics you are using, then an autonomous vehicle can use the same.
> One last thought: suppose it's right turn on red and first car in line is a self-driving vehicle. Can it really look left and safely determine there's enough time to beat the cross traffic? If it's highly conservative and just waits until green, there could be ten irate motorists behind it and guaranteed to honk and curse.
This, and variations, frequently come up in discussions on AV. There's an implicit expectation that no one building these things has considered this problem (this is clearly false). There's two explicit expectations that once a tipping point of AV's are out there, a) there'll be a regulatory push to massively accelerate the adoption close to 100%, and b) inter-vehicle communication means this problem won't arise. In the short term these problems may occur, but to address your question, yes, I'd suggest a computer would be better able to predict if there's enough time to safely turn than most humans.
> I worry that if these machines can't demonstrate 110% of a human's ability ...
Which human would you pick?
Anyway, I wouldn't worry - none of these problems are intractable.