Autonomous Racing with AutoRally Vehicles and Differential Games
This addresses the need for safe autonomous vehicles that can react dynamically to other drivers, though it appears incremental as it builds on existing MPPI methods.
The paper tackled the problem of real-time multi-vehicle interactions in autonomous racing by extending Model Predictive Path Integral Control with differential game theory, resulting in the Best-Response MPPI method that competed against a skilled human driver in experiments.
Safe autonomous vehicles must be able to predict and react to the drivers around them. Previous control methods rely heavily on pre-computation and are unable to react to dynamic events as they unfold in real-time. In this paper, we extend Model Predictive Path Integral Control (MPPI) using differential game theory and introduce Best-Response MPPI (BR-MPPI) for real-time multi-vehicle interactions. Experimental results are presented using two AutoRally platforms in a racing format with BR-MPPI competing against a skilled human driver at the Georgia Tech Autonomous Racing Facility.