A serious self driving vehicle must be able to see around with different sensors. But then it must have a lot of computing power on board to merge different streams of data coming from different sensor. That adds up to the computing power required to make a proper prediction of the trajectories of dozen of other objects moving around the vehicle. I don't know about the latest model, but I knew that the google cars few years ago had the boot occupied by big computers with several CUDA cards.
That's not something you can put in a commercial car sold to the public, what you get is a car that relies only on one camera to look around and has a sensor in the bumper that cuts the engine if activated, but it does not create an additional stream of data. Maybe that there is a second camera looking down at the line on the road, but the data stream is not merged to the other, it is used to adjust the driving commands. I don't even know if the little onboard computer they have is able to computes the trajectories of all the objects around the car. Few sensors and little processing power, that is not enough, it is not a self driving car.
When Tesla sells a car with driving assistance they tell to the customer that their car is not a self driving car, but they fail to explain why, where is the difference. How big is the gap. That's one of the reasons why we had so many accidents.
Similar post earlier.
It starts from the same news, but taking the idea from the book in the link it asks something different.