Current TACC/auto-steer doesn’t use deep learning except on the newest Model 3/Y vehicles with “TeslaVision”. All cars with radar use the radar and radar only to determine if they should stop for the following car.
How does TeslaVision work with stationary objects at night? Like say a big ass truck with its lights off? Do you just pray the vision system recognizes “something” is there? I know they want to pursue a pure-vision system with no radar input, but it seems like there will be some crazy low light / low visibility edge cases you’d have to deal with.
How does a human detect a big ass truck with its lights off at night? This is solvable with computer vision. Tesla's dataset is almost nothing but edge cases, and they keep adding more all the time. My money says they'll get there.
The thing is we don’t. Many people die from rear ending broke down trucks. I’m fine with that, I’m not so sure if regulators will be fine with a TSLA killing someone and going “welp, a human wouldn’t have seen it either, let’s just add this to our edge case dataset”.
