> A bag* or child running into a street is not an usual event, also a car is not going to 'evade' into another car
Opting to drive around a (stationary, visible from a distance) bag in an unpredictable manner is literally how Waymo's first "at fault" accident occurred...
The point is that a human has a concept of a "ball" linked to the concept of "children play football" and an understanding that if one sees the former, one should be prepared for the latter to bursts onto the road from behind the partially-obscured roadside. Appropriate action probably involves easing off the accelerator and lightly tapping the brake so the car behind gets a hint that you might have to stop suddenly on if a child emerges from behind a bush. An autonomous car which fails to anticipate even though it's lightning fast at slamming the brakes on is going to get rear ended a lot more.
The neural network of a self driving car might be able to classify small coloured spheres in the vicinity of the roadway as balls, and the AI will certainly have been taught the concept of a human-shaped obstacle moving across the roadway being a "need to stop" situation, but is unlikely to "learn" the association between the two through a few tens of million miles of regular driving, because only a very small proportion of "need to stop" events involve balls (and only a very small number of sightings of spheres moving in the vicinity of the roadway result in "need to stop" events). Of course, you can hard code a machine to respond to ball-shaped objects moving near roads by slowing down and you can construct a huge number of artificial test scenarios involving balls to teach the AI the association between balls and small children, but either of these options involves engineers envisaging the low frequency hazard and teaching it enough permutations of the sensory input for that hazard for it to be able to anticipate it (and there's a balance to be struck, because nobody wants a paranoid AI which drives through the city braking every time it sees something its neural network identifies as a pedestrian or the front of a parked car protruding from a driveway) Suffice to say, we take for granted our ability to know how to react to things like children chasing balls, staggering 4am drunks, tiny puddles the car in front just drove through versus a raging torrents of water through the usually safely navigable ford, sandbags versus shopping bags, vehicles laden down with loads which look like things which are not vehicles, and people frantically gesturing to stop.