Chen, Mingyang; Jiang, Jingjing; Chen, Boli; (2024) A Game-based Optimal and Safe Lane Change Control of Autonomous Vehicles in Mixed Traffic Scenario. In: 2024 IEEE Conference on Control Technology and Applications (CCTA). (pp. pp. 52-57). IEEE: Newcastle upon Tyne, United Kingdom.

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Abstract

To improve the safety and efficiency of the intelligent transportation system, particularly in mixed traffic environments, where connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) coexist, in this paper a gametheoretic-based trajectory planning framework is proposed. Firstly, a Stackelberg game-based lane change framework is proposed, where both HDV and CAV can change lanes. Second, an optimal control strategy is designed for the CAV subject to the optimal behavior of the HDV, which is derived from the Hamilton–Jacobi–Bellman equation. These strategies are also shown to constitute equilibrium points. Furthermore, the stability of these equilibrium strategies is analyzed. Thirdly, by constructing a zeroing control barrier function, we further show that the above-designed equilibrium strategy renders the collision avoidance set forward invariant under a suitable choice of weight matrices for the CAV cost function. Finally, the simulation results show the effectiveness of our proposed method.

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