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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 1
117-124

Highway on-ramp merging human-like decision based on BC-MAAC algorithm

Yu Di
Zhang Changwen
Xiong Shuangshuang
Liu Pengyou
School of Automation, Beijing Information Science & Technology University, Beijing 100192, China
DOI: 10.19734/j.issn.1001-3695.2024.06.0204

Abstract

To address the lack of human-like intelligence and the difficulty in designing reward functions in multi-agent reinforcement learning algorithms for autonomous driving in complex environments, this paper advanced a human-like decision-making scheme for highway on-ramp merging based on the BC-MAAC algorithm. Combined behavior cloning IDEA with the multi-actor-attention-critic algorithm, it proposed the BC-MAAC algorithm. Derives expert policies from multi-agent expert data collected on the Highway-env platform, and used the KL divergence between the derived expert policies and the current policies of agents to shape the reward function, so as to guide the training process of the agents. At the same time, the algorithm applied an action masking mechanism to filter out unsafe or ineffective actions at each step to improve learning efficiency. Simulation results under two different traffic density scenarios show that the proposed algorithm outperforms the baseline algorithm overall, improving vehicle efficiency and safety. In the easy mode, the proposed algorithm achieves 100% success rate, improves the average speed and the average reward by at least 0.73% and 11.14%, respectively. In the hard mode, the proposed algorithm achieves 93.40% success rate, improves the average speed and the average reward by at least 3.96% and 12.23%, respectively. It is obvious that the BC-MAAC algorithm guides connected autonomous vehicles to complete the highway on-ramp merging task more human-like through cooperation by using the expert reward function.

Foundation Support

国家自然科学基金资助项目(62103057)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.06.0204
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 1
Section: Algorithm Research & Explore
Pages: 117-124
Serial Number: 1001-3695(2025)01-017-0117-08

Publish History

[2025-01-05] Printed Article

Cite This Article

于镝, 张昌文, 熊双双, 等. 基于BC-MAAC算法的高速入口匝道合并类人决策 [J]. 计算机应用研究, 2025, 42 (1): 117-124. (Yu Di, Zhang Changwen, Xiong Shuangshuang, et al. Highway on-ramp merging human-like decision based on BC-MAAC algorithm [J]. Application Research of Computers, 2025, 42 (1): 117-124. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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