Our roads demand predictable and familiar human behavior from every participant to ensure safety for every car and driver on the road.
Recent breakthroughs in imitation learning have now made this possible. It starts with observation: collecting all of the macro and micro behaviors that make up human driving. We can then build a model that imitates those behaviors in software, creating a driver that behaves like a real person. Once we successfully imitate baseline human behavior, we can then take the next step to improve upon human driving. We first eliminate all the passive human errors, like non-observation (e.g. texting, falling asleep), and then identify and eliminate the active human errors that cause accidents or close calls.