App. Res. of Comp. Accepted Paper
Vol. 44, 2027 No. 1

Multi-agent reinforcement learning method for motorized–non-motorized vehicle interaction at unsignalized intersections

Zhou Dan1,2
Zhang Xinying1
Long Yunwei1
Liang Zhiqin1
1. College of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin Guangxi 541004, China
2. Guangxi Key Laboratory of Smart Transportation, Guilin University of Electronic Technology, Guilin 541004, China
DOI: 10.19734/j.issn.1001-3695.2026.06.0151

Abstract

To address dynamically varying social preferences and unstable early-stage reinforcement learning in motorized–non-motorized vehicle interactions at unsignalized intersections, this study developed a multi-agent reinforcement learning model integrating behavior cloning (BC) initialization and dynamic social value orientation (SVO) . The model represented a straight-moving motor vehicle and a left-turning non-motorized vehicle as agents, initialized policy networks through BC, and dynamically adjusted individual and social reward weights according to predicted post-encroachment time (PET) . The study extracted 556 interaction scenarios from the inD dataset and used 421 for training and 135 for testing. Results show that the method achieves an average displacement error of 0.88 m, a final displacement error of 1.85 m, and a PET of 1.99 s. Compared with two baselines, it reduces average displacement error and increases PET, balancing trajectory accuracy and interaction safety. The repository provides model training code at https://gitee.com/zhangresearch/svo-bc-maddpg.

Foundation Support

国家自然科学基金资助项目(52462048)
广西自然科学基金资助项目(2024GXNSFAA010278)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.06.0151
Publish at: Application Research of Computers Accepted Paper, Vol. 44, 2027 No. 1

Publish History

[2026-09-08] Accepted Paper

Cite This Article

周旦, 张鑫迎, 龙云溦, 等. 面向无信号交叉口机非交互的多智能体强化学习方法 [J]. 计算机应用研究, 2027, 44 (1). (2026-09-14). https://doi.org/10.19734/j.issn.1001-3695.2026.06.0151. (Zhou Dan, Zhang Xinying, Long Yunwei, et al. Multi-agent reinforcement learning method for motorized–non-motorized vehicle interaction at unsignalized intersections [J]. Application Research of Computers, 2027, 44 (1). (2026-09-14). https://doi.org/10.19734/j.issn.1001-3695.2026.06.0151. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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