Eventually these autonomous vehicles should share driving condition data in real-time-ish. If one car finds a stretch of the road slippery, it should basically mark it on the map as a bad location, and then other cars and be careful.

I think weather conditions can also predict road conditions pretty well. And the combine that with historical data on where things were slippery, I bet you can create a pretty good model of what conditions to expect across a driving environment.

Although in Canada, sometimes all roads in a city are just horrid - dozens of cars in ditches or hitting each other because no one can stop. And maybe in those cases, autonomous vehicles should refuse to drive until it is improved.

Where I live, the sharing is done at a meta level. I live in the Sierra Nevada mountains of California and we often get experienced snow drivers who get stuck immediately because they aren't used to driving on 25% grades that experience frequent freeze / thaw cycles (and therefore generate ice). The issues here are predictable and don't even require real-time sharing.

When someone new moves into town, someone will typically explain to them to watch for where the sun hits the ground in winter. Where that happens on a steep slope, avoid driving there when there is snow. Before they know to do this, a human will attempt to climb that hill, not make progress because of the ice, back down, and try another route. This is a rural area without much traffic, so conditions might change significantly between "real-time" updates.

So, we have human drivers "zooming out" in a couple of ways... in time/context (observing conditions that lead to certain routes becoming high risk) and in problem resolution (try another route). This is quite different from what is currently being tried algorithmically.

True, historical data is basically what humans use too. I just wonder if there's a way to prevent the accidents that would generate that data