Because they're all trying visual- or line-of-sight methods only, I call this the "robo-human" fallacy in ML: trying to automate the processes that humans undergo so that you eventually have a drop-in replacement for a human. But that is a myopic and unimaginative approach because you could be re-assessing the system itself and eliminating inefficiencies that lead to poor performance.

In the autonomous vehicles space, there is massive potential for self-organizing swarm algorithms to control pelotons of cars, rather than individual cars with no intrinsic sense of the general flow of traffic. You wouldn't need a top-down "commander" style architecture, it could be designed so that cars only talk to their immediate neighbors and emergent patterns keep traffic flowing smooth and fast.

I have always been skeptical of the attempts to reduce the amount of information about the road that a car receives. (Moving from stereoscopic to monocular vision to save the cost of one camera seems just stupid.) But people who dream of "smart cities" really seem to see little more than The Jetsons in their mind, and it limits the scope of research to our detriment.