To help autonomous vehicles drive safely at the limits of handling for situations such as obstacle avoidance or encountering a patch of ice, Stanford researchers used data from two test tracks: one from a low-friction environment with ice and snow and the other from Thunderhill Raceway in Willows, CA for high-friction data to develop a neural-network based system. In testing, the AI based system outperformed a more traditional physics-based system.