(Meta: I do not know an appropriate place for this on Stack Exchange. There does not appear to be any groups related to autonomous driving technology and computer 3D vision / perception systems.)
For self driving vehicles using 3D depth perception LIDAR on a highway with hundreds of other vehicles also using various other LIDAR sweep beam or spot-field (kinect style) emission scanners, how is it able to distinguish its own signal returns, from the scanning being done by the other systems?
For an extremely large multilane highway, or complex multi-way intersections such emissions can be seen in all directions, covering all surfaces, and there is no way to avoid detecting the beam emissions from other scanners.
This seems to be the main technical hurdle for implementing LIDAR for autonomous driving vehicles. It does not matter if it works perfectly if it’s the only vehicle on the road using LIDAR.
The real question is how it deals with being inundated with spurious signals from similar systems in a future scenario where LIDAR is present on every vehicle, potentially with multiple scanners per vehicle and scanning in all directions around each vehicle.
Is it capable of functioning normally, can it somehow distinguish its own scanning and reject others, or in the worst case can it fail completely and just report garbage data that is useless, and it doesn’t know that it’s reporting garbage data?
This at least seems to be a strong case for having passive 3D computer vision that’s just based on natural light and stereo camera depth integration, as is done in the human brain.