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One approach would be to record 100-to-1000 trials of how human drivers navigate each particular edge case in vehicles instrumented for autonomous driving.

Sadly, no one seems to have figured out a way to economically motivate human drivers to do this.

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Isn't this part of what Tesla has been doing though? At least they sell cars that simultaneously has:

- human drivers in demanding situations

- sensor and compute package planned for autonomous driving

From there it is mostly a question of

1. getting permissions to collect the data

2. finding some efficient way to store -> sift for interesting situations -> magic happens here -> lots of regression testing -> self driving car -> profit!

I would think?

The problem are not the expected edge cases, but the unexpected ones. No amount of hard coded reactions are going to do for those.

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