Our new 2023 Model Y has hit the brakes 3 times with TACC on. Once was incredibly hard (caught by the seatbelt), the other 2 times were merely 'hard' (things sliding off the seats). These were truly random events on different points in 2 lane road with nothing interesting happening (no curves or ups and down, no rain, ~60 mph).
I've been thinking how that could happen, and how Tesla is the only car mfg. where this is happening with high frequency (according to my experience with Subaru EyeSight (dual cameras) and Kia EV (radar with single camera)). My hypothesis at this point is that must be due to the ML; in particular the training set: What if the training set includes events that, either correctly or incorrectly, include breaking? These events might then cause breaking in the real world when camera inputs match 'close enough' to the training events. If this were true, Tesla would need to manually validate their ML training data for correct | incorrect breaking events and remove those from the TACC training data set.
Any thoughts on this hypothesis? I am not familiar with how Tesla applies ML to say one way or another - and the details of the ML pipeline and algorithmic implementation details will be certainly be important. It's just that I read / hear that Tesla uses AI that makes me wonder.
I've been thinking how that could happen, and how Tesla is the only car mfg. where this is happening with high frequency (according to my experience with Subaru EyeSight (dual cameras) and Kia EV (radar with single camera)). My hypothesis at this point is that must be due to the ML; in particular the training set: What if the training set includes events that, either correctly or incorrectly, include breaking? These events might then cause breaking in the real world when camera inputs match 'close enough' to the training events. If this were true, Tesla would need to manually validate their ML training data for correct | incorrect breaking events and remove those from the TACC training data set.
Any thoughts on this hypothesis? I am not familiar with how Tesla applies ML to say one way or another - and the details of the ML pipeline and algorithmic implementation details will be certainly be important. It's just that I read / hear that Tesla uses AI that makes me wonder.