L3 on freeway has waaaay less edge cases than city streets. I honestly don’t think it’s a hard problem to solve. You don’t even need “generalized AI”. It’s basically just lane centering and adaptive cruise and LiDAR does the heavy lifting to make sure you never hit anything.
I think this is an oversimplification.
Is LiDAR going to detect the 5 large full black trash bags strewn across three slow lanes of 163-S at Fashion Valley at 1500 feet range, just before the I-8 West exit I needed to take yesterday, allowing the car to change to the fast lane, which was (incidentally) preceded by about 10 seconds by a CHP officer traveling 110mph in the fast lane to get on I-8 West?
Or is Level 3 going to detect this condition somehow at 80mph and just tell me to take over in 2 seconds and expect that I comprehend the situation and the situation of the traffic behind and beside me?
Note, other traffic was not stopping; they were dodging the bags or moving to the fast lane. No one stopped stupidly in the middle of the freeway. But plenty of slowing and evasive action. I just changed 4 lanes, slowed a bit, and cruised by at 50-60 in the fast lane well away from the drama. Then made 5 quick lane changes and hit my exit.
Weird things happen. This isn’t even that weird! If things are slow it might be ok. But driving is complicated. Humans make good safe decisions every day.
It’s important that a high speed L3 system be able to detect obstacles at at least 1500 feet when line of sight is there - needs to duplicate or even exceed human vision (if it is going to require a safe takeover). I don’t know what LiDAR can do. It looks like it might have that sort of range, but I’d like to see it do it, with various cars in the way, etc.
Anyway, not saying LiDAR doesn’t help, but there are crazy corner cases for L3. The above is not even that unusual.
Whether it is LiDAR or something else, the required range and contextual understanding required is extraordinary for safe high-speed L3. And I actually think low speed L3 is harder than it looks.