> Google is teaching their car how to navigate city streets, deal with human drivers and pedestrians, navigate intersections, handle construction zones, deal with emergency vehicles and cops directing traffic, etc. All with a much better sensor package than in a Tesla Model S.

The interesting thing is that no matter how much one anticipates situations a priori and builds them into the AI/model, there will likely exist situations not anticipated by the engineers.

For example, it is not clear to me how exactly a situation like https://en.wikipedia.org/wiki/Driving_direction#Sweden will be handled. Will this be "patchable" (never mind the logistics and security issues of providing updates to a nation's fleet), or will it require a full retraining of the AI? Or more generally, how robust/modular will the designed AI be to these kinds of situations?

The reason I like this example is because it is a classic instance where humans have inertia and thus have difficulty in consistently applying the "switch driving side" rule - I have seen international travellers requiring at least a few minutes at the wheel to reorient themselves.

In principle one would hope that a modular software solution can handle things more consistently.