Title: Traffic intersection crossing method for intelligent vehicles based on game theory

Authors: Yikai Wang; Zhuming Nie; Yuquan Wu; Xiaozhao Fang; Xi He; Hongbo Gao

Addresses: Department of Automation, University of Science and Technology of China, Hefei, Anhui, 230026, China ' Department of Educational Technology, Anhui Normal University, Wuhu, Anhui, 241000, China ' Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China ' School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, 510006, China ' Department of Automation, University of Science and Technology of China, Hefei, Anhui, 230026, China ' Department of Automation, University of Science and Technology of China, Hefei, Anhui, 230026, China

Abstract: Game theory is a tool for decision-making in the face of uncertain factors. In this paper, by analysing the defects of the existing traffic light timing strategy, combined with the existing traffic conditions, a dynamic traffic crossing strategy based on game theory is proposed. This paper attempts to use game theory to determine the traffic relationship between intersections, adjust the timing of traffic lights in real time, and compare it with the existing timing methods through software simulation. The experimental results show that the dynamic traffic strategy proposed in this paper can improve the traffic efficiency, effectively reduce the maximum queue length, and has a strong adaptability to emergencies.

Keywords: game theory; traffic strategy; intelligent vehicles; vehicle-road collaboration; real-time adjustment.

DOI: 10.1504/IJSSC.2023.133236

International Journal of Space-Based and Situated Computing, 2023 Vol.9 No.3, pp.138 - 146

Received: 30 Jun 2021
Received in revised form: 04 Nov 2021
Accepted: 28 May 2022
Published online: 03 Sep 2023 *

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