Exactly. The way to improve performance on a lot of AI problems is to get past the human tendency to individualistic AI, where every AI implementation has to deal with reality all on its own.

As soon as you get experience-sharing - culture, as humans call it, but updateable in real time as fast as data networks allow - you can build an AI mesh that is aware of local driving conditions and learns all the specific local "map" features it experiences. And then generalises from those.

So instead of point-and-hope rule inference you get local learning of global invariants, modified by specific local exceptions which change in real time.