Nash or Stackelberg? -- A comparative study for game-theoretic AV decision-making

Abstract

This paper studies game-theoretic decision-making for autonomous vehicles (AVs). A receding horizon multi-player game is formulated to model the AV decision-making problem. Two classes of games, including Nash game and Stackelber games, are developed respectively. For each of the two games, two solution settings, including pairwise games and multi-player games, are introduced, respectively, to solve the game in multi-agent scenarios. Comparative studies are conducted via statistical simulations to gain understandings of the performance of the two classes of games and of the two solution settings, respectively. The simulations are conducted in intersection-crossing scenarios, and the game performance is quantified by three metrics: safety, travel efficiency, and computational time.