[xg15]

Yeah, my understanding was also that the (remaining) hard part of self-driving cars is guessing the intentions of other traffic participants. There are a lot of assumptions human drivers can make about pedestrians, e.g. whether a pedestrian has seen the car or not, whether they will wait for it, have no intention of crossing at all - or will just run across the street.

A model might potentially be able to understand those situations, but it would need a lot of highly task specific training data and it would never be clear if the training really covered all possible situations.

The other problem I see is that a lot of situations in traffic are really two-way communication, even if it is nonverbal and sometimes so implicit we don't realize it. But usually pedestrians will also try to infer what the driver is thinking whether he saw them, etc. In those situations, a self-driving car is simply a fundamentally different kind of traffic participant and pedestrians will interact with it differently than they would with a normal car. That problem is independent of machine learning and seems much harder to solve to me.