Training an autonomous car to drift is a surprisingly good method for testing a car’s ability to drive evasively. Under typical conditions, a driver points the car where they want to go and uses the accelerator and brake pedals to control the speed. When drifting, whether intentionally or not, this goes out the window.

“Suddenly the car is pointed in a very different direction than where it’s going. Your steering wheel controls the speed, the throttle affects the rotation, and the brakes can impact how quickly you change directions,” Goh said. “You have to understand how to use these familiar inputs in a very different way to control the car, and most drivers just aren’t very good at handling the car when it becomes this unstable.”

Commercial vehicles are outfitted with Electronic Stability Control systems that try to prevent cars from entering these unstable states, but this is where drifters thrive. They harness this instability to maneuver the car in more agile and precise ways that allow them to scorch through a narrow obstacle course without so much as grazing the barriers.

By studying the habits of professional drivers and testing those same control maneuvers in MARTY, the Stanford team has enabled the car to use a greater range of its physical limits to maintain stability through a broader range of conditions, and the mathematics involved could allow autonomous systems to maneuver with the agility of a drift racer in emergencies.

“Through drifting, we’re able to get to extreme examples of driving physics that we wouldn’t otherwise,” Goh said. “If we can conquer how to safely control the car in the most stable and the most unstable scenarios, it becomes easier to connect all the dots in between.”