It's not an ML problem. Waymo uses Lidar, because that's what google started with over a decade ago and they never moved past it. Lidar is pretty bad for self-driving for many reasons, they hit a brick wall with it years ago and haven't moved past since.

So it's either scrap the company, or try to make something of it. So they picked a city with the second lowest rainfall anywhere in the US, and pre-programmed in some areas of the Phoenix metropolitan area into the car. Streets, lane counts, how to make turns at each intersection, how the lanes match up, markings...etc. Once pre-programmed, they lock the cars in the area and drive the pre-programmed routes, using Lidar to try not to bump into stuff.

The gimmick here is in the strange definition of level 4 autonomy. Unlike the other levels, level 4 allows for geofencing. This makes it pretty misleading since it means if you train your car to drive around an empty parking lot without a driver, and nowhere else, that's technically level 4 autonomy and you can market it as that. Cars have been able to self drive around a parking lot since the 90's if not earlier, and self navigate entire deserts since like 2001, so it's not really an impressive feat.

They're hoping it will be good enough to start robo taxi services in areas they can get the pre-programming working well enough to not keep failing. But there really isn't a point, they have to perpetually re-program the cars by re-scanning the entire geofenced area. It stops being economical the moment any other competitor makes actual self driving cars that aren't based on gimmicks.