It does not seem like you have much experience with either LiDAR or stereo vision. These systems have well known performance characteristics and advantages. Li

It does not seem like you have much experience with either LiDAR or stereo vision. These systems have well known performance characteristics and advantages. LiDAR has its limitations (in terms of point density and scan rate, and cost), but its range estimate accuracy just blows stereo vision away for automotive settings. The error on range estimates from stereo “disparity” goes up as range squared for fundamental-physics reasons. Accurate calculation of disparity relies on well calibrated optics (clean, physically rigid) and it’s easy to disrupt that. Stereo is also target-sensitive. Stereo ranging is enhanced by certain target features, like large, smooth surfaces with texture (say, stucco walls, or car grilles). It is made more difficult by smaller target surfaces with weird curvature. I’m sure that stereo that did well on auto-sized surfaces would do much worse for pedestrian or motorcycle (size and shape) surfaces.