Game Theory-Based Control Strategy For Trajectory Following of Four-Wheel Independently Actuated Autonomous Vehicles

Trajectory Following Control (TFC) and lateral stability control are always significant for Autonomous Ground Vehicles (AGVs). However, sometimes it is quite a challenge to achieve excellent tracking performance with less stability loss. In this paper, a novel two-agent non-cooperative game framework is built to explore the coordination approach of the integrated TFC and Direct Yaw Control (DYC) issue. Then the game theory-based control strategies are proposed and two information patterns are investigated. In the open-loop case, the Nash equilibrium of each control cycle is determined by solving discrete-time Riccati equations. When it comes to the closed-loop pattern, the game complexity increases because each player can revise his own game strategy according to the other players' strategy evolution, and thus the dynamic programming method based on the Bellman's principle is applied to derive the control strategies. Besides, a Linear Parameter-Varying (LPV) method is adopted to facilitate the process of discretizing the state-space model in every control cycle. Finally, simulation tests based on Carsim-Simulink joint platform and experimental tests are carried out to verify the effectiveness of the proposed approach.

Automated summary

The paper introduces a novel two-agent non-cooperative game framework to address the coordination of trajectory following control and lateral stability control for Autonomous Ground Vehicles. Control strategies based on game theory are proposed and tested through simulations and experiments. Additionally, a Linear Parameter-Varying method is used to facilitate the process of discretizing the state-space model.