I agree that ultimately they need a significant amount of local training data. But I believe they would be better off having a human drive a car around to map things out, run their 'AI' on the results, and then manually review/correct lower confidence results. Or, better yet, make a database and have cities provide feeds of changes/permits/closures.
"Sorry, I know you crashed, your car's on fire, and you're bleeding out. But I need to get this road closure form submitted before I can help, or a self driving car might ignore the stationary accident and make things worse. Ugh, 5G's not working today... hold on..."
The cars must be able to handle random, unexpected events happening without maps, and without external guidance. A wheel falls off a truck in front of you for metal fatigue reasons and is bounding down the road - that's a thing that happens, and a thing that in no way will be reported before it becomes relevant.
If a self driving car can't handle this sort of thing (or an accident and coming on a flagger) autonomously, it has no business being allowed on the road.
And if it can - then there's no need to have a centralized database of weird things, because it can deal with the range of events autonomously.
Start talking about 99.998% or so, OK, now it's worth sitting down with the math. But 98% accuracy at avoiding construction/existing crashes/etc is horrible.
> And if it can - then there's no need to have a centralized database of weird things, because it can deal with the range of events autonomously.
'Conditions on top of the road' (vehicles, debris, etc.) and 'conditions of the road itself' are not the same thing and I'm not sure why you think that they are.
Define -
1. Several.
2. Not working.
Disc: Googler but I don't know if that's necessary since I don't work at Waymo.
Self-driving will arrive eventually, but don't hold your breath.