Interaction-Aware Motion Planning as a Game

Abstract

AbstractMotion planning for automated vehicles (AVs) in mixed traffic, where AVs share the road with human-driven vehicles, is a challenging task. To reduce the complexity, state-of-the-art planning approaches often assume that the future motion of surrounding vehicles can be predicted independently of the AV’s plan. This separation can lead to suboptimal, overly conservative behavior especially in highly interactive traffic situations. In this work, we introduce a motion planning algorithm to generate interaction-aware behavior for highly interactive scenarios. The presented algorithm is based upon a reformulation of a bi-level optimization problem, which frames interactions between a human driver and a AV as a Stackelberg game. In contrast to existing works, the algorithm can account for general nonlinear state and input constraints. Further, we introduce mechanisms to integrate cooperation and courtesy into motion planning to prevent overly aggressive driving behavior.