I've built a number of mobile robots over the years, and watched many others build them as well as part of a robotics club. One truism is that most robotics problems are pretty easy given ideal sensors and sensors for every variable :-). When I started building robots I quickly understood that 'sensor fusion' is more about trying to tease reality out of a very noisy cloud of data than it is AI or fancy software. I spent a month trying to get a robot to go precisely straight so that my dead reckoning algorithm would work.
The blog post linked in https://news.ycombinator.com/item?id=15435063 sure makes it sound like they are making serious progress on the hard problems.
The CA DMV autonomous vehicle reports of accidents and disconnects are the closest thing available to objective data right now. Waymo is way ahead on disconnects. Cruise is getting rear-ended a lot lately. Google used to get that a lot, but they seem to have gotten past that.
(The main compatibility problem with autonomous vehicles so far is being rear-ended. The typical situation is that the autonomous vehicle advances into an intersection, detects some good reason to stop like cross-traffic previously occluded, stops, and gets rear-ended. The accel/decel profile for entering occluded situations may have to be made more compatible with human behavior to get the human drivers behind to behave properly. This isn't a big problem; damage in those collisions is very low.)
GM Super Cruise shipped, but despite the name, Cruise Automation made essentially no contribution.
We're not going to be shipping anything.