Exponential. It gives range and shape data, which a pure-optical system needs to infer from a 2D image. This kind of image processing is still an open problem in ML.

The usual metric for self-driving car success is "disengagements per mile", ie how frequently a driver needs to intervene to avoid a crash. From my anecdotal readings of Tesla Autopilot reviews, it's on the order of 0.1 per mile. For Waymo and Cruise, it's on the order of 0.01 per THOUSAND miles. That's a very different definition of "driver" than the one that Tesla Autopilot requires.

I don't know the total number of miles on all Teslas on Autopilot, but it has had much more than one accident.

EDIT: and that Waymo crash was not a self-driving error; it was T-boned by a human-driven car running a red light.