Geometry inferred from range sensors can certainly provide an additional useful source of information, but it's far from clear that the right approach to contro

Geometry inferred from range sensors can certainly provide an additional useful source of information, but it's far from clear that the right approach to controlling a self-driving vehicle is mostly to solve a geometry problem. For example, even if a range sensor can provide a perfect estimate of the location and geometry of pedestrian, how do you predict whether the pedestrian will dart out into the road or stop because they see a car coming. Human drivers have learned from years of (mostly) visual experience observing human behaviors to make reliable predictions about such things. Perhaps machines can too. Since evolution didn't provide us with our personal lidars, human drivers are an existence proof that it is possible to learn reliable driving performance from vision alone. Which isn't to say that machine learning based on vision alone is already close to human-level or competency or that human-level competency is sufficient for a automated driving system or that sophisticated sensors don't make the problem a bit easier. But I don't know how you can be so confident that vision alone (or primarily) won't be route that eventually succeeds.