They explain it in the software talk. In short, I think his thesis is: Lidar is expensive, and gives surprisingly limited data (just points of depth) and is li

They explain it in the software talk. In short, I think his thesis is: Lidar is expensive, and gives surprisingly limited data (just points of depth) and is like a crutch that will only get so far. It will not get you to full autonomy so why not spend the time and money on vision which will (as proven by humans). They also do use radar and ultrasonics (not visual spectrum). At some point your machine must be good enough via machine learning to give a very good impression of understanding intention in other road users, pedestrians etc. One example they gave was a distracted pedestrian with a phone. Lidar tells you nothing save an obstacle is on the pavement, it won’t tell you they might step out without looking, but machine learning on a massive dataset can.