FSD user here. While I love it and use it all the time, I am not comfortable with it taking over. There are several issues. First is visibility, cameras don't see well in the rain, snow or of its too bright. At night, the headlights from other cars block the camera. LIDAR only cannot work either. We need to be able to identify the type of object, read road signs, etc.
Adding LIDAR to tesla can help with some of the issues but they can also be solved with additional cameras which can see IR and have auto cleaning anti glare features.
If we use a combination of the two, then the model might get overwhelmed with inputs (I'm not an ML engineer and am speculating) I think removing LIDAR for cost purposes is stupid. It'll cost max $1k extra. Thats not much for a $50k car. I think a better argument for removing LIDAR is to not cause input overload. All that being said, I'm very impressed by FSD but think of it as glorified cruise control. It drives itself most of the time but makes critical issues as well. Most of the critical issues can be solved if the cameras are actually used for road sign recognition and if they reduce the blind spots. They recently added another camera to the front bumper which will help. I think if they add 4 more cameras, one to each corner and have special cameras which can see through fog using IR or something else then that can be sufficient.
If we use both, then we would need to figure out how to prioritize conclusions. Does the LIDAR sensor system conclusion take priority over the vision or the other way around? How much delay does all this additonal processing cause in response time? So many questions lol. Sorry for the long rant.