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The problem is that Tesla uses an ML classifier to identify objects it sees. Once it has identified them, it can estimate how big it is, and thus how far away i
by diggernet 2y ago
The problem is that Tesla uses an ML classifier to identify objects it sees. Once it has identified them, it can estimate how big it is, and thus how far away it is. But if the classifier doesn't identify the object, it might as well not exist.
Contrast this with Subaru, who uses binocular view through two widely spaced cameras to build a depth map of the view in front of it. It doesn't know or care what is there, only that something is there it shouldn't hit. And so the emergency breaking will trigger for things like trains and stationary emergency vehicles that Tesla seems oblivious to.
Sometimes simpler really is better.
- eurleif 2y agoThis is false. Tesla has an occupancy network.
- diggernet 2y agoPlease pardon my failure to remember the correct term. But fundamentally, it constructs a 3d model based on what it thinks each pixel represents. And sometimes gets it wrong, leading to it having a pattern of driving into stationary objects.
- eurleif 2y agoIt's not a matter of terminology. Tesla's occupancy network "doesn't know or care what is there, only that something is there it shouldn't hit". As the name suggests, it's solely concerned with what space is occupied and what space is unoccupied, not with identifying objects. As such, the distinction you tried to draw between Subaru and Tesla is false, no matter what terms you use.