[Animats]

In my opinion the underlying assumption autopilots are built with are wrong. It is assumed that the road is free to drive on. Only when the vehicle computer detects a known object on the road that it knows should not be there it is applying brakes or trying to steer around. I would feel safer if the algorithm would assume the negative case as default and only give the „green light“ once it determined that the road is free to drive on.

I agree, but it will up the false alarm rate in a system without good depth perception for all objects. This is tough with cameras only. Reflective puddles are a problem; they're hard to range with vision only. Anything that doesn't range well, which is most very uniform surfaces, becomes a reason to slow down. As you get closer, the sensor data gets better and you can usually decide it's safe to proceed.

Off-road autonomous vehicles have to work that way, but on-road ones can be more optimistic.

Waymo takes a hard line on this, and their vehicles drive rather conservatively as a result. They do have false-alarm problems and slowdowns around trouble spots.

[oaw-bct-ar-bamf]

Would you rather optimize for a faster overall fleet, or a fleet with stress free driving, no incidents, no need to intervene or be to be worried.

If the system gets faster over time, even better. But I cannot imagine huge adoption unless the system gets actually reliable. I am pretty much in favor of the Waymo approach.

[oaw-bct-ar-bamf]

Having high false positive results with only single or dual sensors only shows how ‚bad‘ we still are with controlled secure automated driving.