I’m not sure this has much to do with vision as opposed to fancy self-calibration software. At least a few years ago, Tesla cars would be in self-calibration mode for a while after delivery while they calibrated their cameras. I think the idea is that it’s cheaper to figure out in software where everything is than to calibrate the camera mounts and lenses at the factory.

I see no reason that LiDAR couldn’t participate in a similar algorithm.

A bigger issue would be knowing the shape of the car to avoid clipping an obstacle.

It probably could, but I imagine a LIDAR system would need a similar (large) amount of training data to enable effective self-calibration across a wide variety of situations.

At some point, with enough sensor suites, we might be able to generalize better and have effective lower(?)-shot training for self-calibration of sensor suites.