going to be fun watching them deal with snow. though their approach has tended towards detail mapping. someone is going to figure out a break through in marking roads or perhaps they will get sensible and start with limited access highways first.
[0] - https://www.flirmedia.com/MMC/CVS/Tech_Notes/TN_0001_EN.pdf
Self-driving cars are at the intersection of numerous solved domains, yet integrating these remains strangely difficult for the largest companies in the world.
Snow is not just increased visual noise. Just off the top of my head, with no experience in self-driving cars and limited experience in computer vision:
Snow (on the ground and street and curbs) is a vastly lower-contrast visual environment where numerous traditionally distinct features of the landscape are covered by a blanket of white.
Snow is a more dangerous and difficult-to-stop-in environment, with totally different physical dynamics. Recognizing pedestrians (and their intentions), road blocks, debris, etc. is probably already a challenging problem, and with snow it's not only more difficult, it needs to be done from a much farther distance to give adequate stopping time.
Along with snow there are issues with recognizing icy patches and other especially low traction sections on the road and adjusting control inputs accordingly.
I can't tell if you've never driven in snow or never even attempted a basic computer vision or robotics task in your life, or both.
Computer vision is not solved.
Sensor fusion is not solved.
Predicting human behavior is not solved.