Title: A game theory-based decision model for lane changing in a mixed traffic environment

Authors: Xuelong Zheng; Xuemei Chen; Yunhao Tang; Rui Qu; Yaohan Jia

Addresses: School of Mechanical Engineering, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China ' School of Mechanical Engineering, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China ' School of Mechanical Engineering, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China ' School of Mechanical Engineering, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China ' School of Mechanical Engineering, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China

Abstract: Cooperative lane changing is a complex challenge in mixed traffic scenarios involving human-driven and autonomous vehicles (HVs and AVs, respectively). With the aim of enhancing cooperation between AVs and HVs, in this study, first, three interactive behaviours were analysed: free lane change, cooperative lane change, and competitive lane change. The willingness to change lanes was assessed based on the degree of cooperation and competition among the vehicles involved in the interaction process. Second, game theory was used to establish a game model for achieving cooperative lane changing in mixed traffic. The as-designed model aimed to maximise the aggregate expected utility by incorporating the coefficients of competition and cooperation. These coefficients were adjusted and the associated costs of these strategies were evaluated; then, the Lemke-Howson algorithm was employed to determine the Nash equilibrium of the game model.

Keywords: autonomous vehicle; mixed traffic; interaction behaviour; decision-making; game theory; Nash equilibrium.

DOI: 10.1504/IJVD.2024.146781

International Journal of Vehicle Design, 2024 Vol.96 No.3/4, pp.193 - 214

Received: 20 Jan 2024
Accepted: 11 Sep 2024
Published online: 17 Jun 2025 *

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