To add insult to injury, the manner in-use today of modeling humans as essentially just another kind of dynamic object breaks down extremely quickly once humans are normalized to the presence of autonomous robots. The humans change their own behavior model to achieve their own objective function. They're not dynamic objects, they're learning objects, and now your AV models (which will include human interaction and reaction behaviors on purpose if you're it right and on accident if you're not) breakdown along an entirely new longitudinal axis.

I think the AV market fundamentally broke when GM acquired Cruise for $1B seemingly out if nowhere.

1) Because the reality is that the DARPA Urban Challenge result was not assuredly generalizable, and it may be the case that there's still basic science to be done before the domain is just better, cheaper sensors & high-performance compute away from being productionizable.

2) It's not at all clear that deep learning is really iterating toward a solution to this problem either, but the improvements to methods and hardware have produced the ability to make very compelling demos, that even the purveyors of themselves might believe in, and show iterative improvements on the previous result, thus fueling more investment into something that isn't even known to be possible.

3) But, none of that would matter if GM hadn't decided to make a power move in throwing $1B at an acquisition and in one fell swoop turned an early stage unproven scientific research market into a super, super frothy capital market where it looked like anybody at any moment could be a unicorn without any clear reason or any fundamentals.

Investors went insane and the expectations and promises followed them.