I don't know if machine learning can ever match the human brain for that. The brain does a lot of fairly advanced inferences that require a deep understanding of the world and the people and things in it.
Still, I'm not sure how much additional inputs would help the ML. If you had to drive by "touch" (LIDAR), you probably shouldn't be allowed to drive. It might be useful when the visual system has failed, to stop the vehicle before it hits something, but if the visual system fails that often then the system wouldn't be usable for any purpose.
Visual input combined with a lot of mental projection and inference and understanding/experience and good split second decision making.
Examples: How does a FSD vehicle use it's camera to identify "black ice" on an overpass? How does it identify that a heavy truck tire has just exploded in it's lane a few cars ahead on the freeway? Or how about a bumper dropped from a car ahead or a large truck losing it's load?
All these and more have happened to me and I lived to tell about it.
I don't know if machine learning can ever match the human brain for that. The brain does a lot of fairly advanced inferences that require a deep understanding of the world and the people and things in it.
Still, I'm not sure how much additional inputs would help the ML. If you had to drive by "touch" (LIDAR), you probably shouldn't be allowed to drive. It might be useful when the visual system has failed, to stop the vehicle before it hits something, but if the visual system fails that often then the system wouldn't be usable for any purpose.