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There are some questions but "should cars start moving while a person is still on the crosswalk?" is surely not one of them.
A person laying on the ground in a crosswalk was likely never considered by the team to include in their training data. Those outlier situations are exactly what real world data is needed for. And the only way to properly train for most of these situations is to drive in the real world. The real world isn't perfect situations and nice lines on fresh asphalt so while base training in perfect situations is useful, it will still miss the exact same situation in a real world environment with crappy infrastructure.
Not sure what or how Cruise uses the data collected in real-time, but I can see camera visuals categorizing a person laying in the crosswalk as something like damage to painted lines, and small debris that can be ignored. Other sensors like radar and lidar might have categorized returns as something like echoes or false results that could be ignored, again because a person laying in the crosswalk is extremely unlikely. False data returns happen all the time with things like radar and lidar, millions of data points are ignored as outliers or info that can be safely ignored, and sometimes that categorization is incorrect.
I actually work at one of these AV companies. We definitely have training data on adults and children laying down. I'd be very very very surprised if Cruise doesn't due to all the people laying down on the sidewalks in SF. In addition, the clarity of the lidar/camera data on objects on the road is very clear. You can see the dips and potholes in the road as well as specifically see the raises of the painted lines. There's no way they weren't tracking the person.
I could see predictions on the pedestrian saying the coast is clear. Once the initial crash happens, there likely isn't enough room to stop in time even with a max break.