My personal hunch is that fully autonomous self-driving tech is not theoretically possible under currently known computational models, because it implies many well-known NP-Hard problems. Self-driving companies are betting on the ability to find a heuristic/approximation that works "sufficiently well". But I strongly feel that the chasm that needs to be crossed to be "sufficiently good" is not one of magnitude (i.e. we just need more testing!), but of theoretical boundaries, due to the existence of at-least two sub-problems which are not computationally solvable: 1. prediction of what pedestrians/cyclists will do next, and 2. accounting for sensor input distortion under bad weather conditions.
Humans can solve these problems due to life experience, not just driving experience. In other words, I think we're gonna need fully-conscious AI to solve self-driving.
The only way self-driving tech will reach production is if the input space is restricted, which is a significant-but-not-groundbreaking iteration on what we've been doing for decades with airplane autopilots and self-driving monorails. Sure, we can have self-driving cars on specifically designed freeways, but nothing more.