FailureNet: Detecting and Preventing AV Failures
Intelligent intersection managers can improve safety by detecting dangerous drivers or failure modes in autonomous vehicles, warning oncoming vehicles as they approach an intersection. Enter FailureNet — a recurrent neural network trained end-to-end on trajectories of both nominal and reckless drivers in a scaled miniature city. It accurately identifies control failures, upstream perception errors, and speeding drivers; the network is trained and deployed with autonomous vehicles in the MiniCity. FailureNet yields upwards of 84 percent accuracy when deployed on hardware.