Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 1
183-187

Interval-block-based Q-learning algorithm for safe and comfortable braking of intelligent vehicles

Yu Xinlei
Zhou Xianwen
Zhang Yilian
Gu Wei
Key Laboratory of Transport Industry of Marine Technology & Control Engineering, Shanghai Maritime University, Shanghai 201306, China
DOI: 10.19734/j.issn.1001-3695.2023.05.0220

Abstract

To address the safety and comfort issues in intelligent vehicle braking scenarios, this paper proposed a Q-learning algorithm based on interval partitioning. Firstly, the algorithm divided the acceleration of the preceding vehicle into equal-length intervals with a certain interval in the Q-table, and used the interval median to partition the acceleration of the following vehicle. Secondly, the algorithm used a reward function that was negatively correlated with acceleration under safe conditions to encourage the agent to minimize braking acceleration while ensuring safety. Finally, the algorithm followed the ε-greedy strategy during the training of the agent to reduce randomness, and followed the greedy strategy after training to maximize the utilization of the agent. This paper simulated the proposed algorithm and the traditional Q-learning algorithm on three common road scenarios. The experimental results show that the intelligent vehicle used the proposed algorithm has a 100% safety rate in braking scenarios, with an average braking acceleration of less than 2 m/s2, and can handle continuous braking acceleration, which indicates that the proposed algorithm can achieve lower braking deceleration to improve passengers' comfort while ensuring safe braking of the intelligent vehicles. In addition, the algorithm is effective in complex scenarios including continuous braking deceleration and offline environments.

Foundation Support

国家自然科学基金面上项目(62176150)
上海市地方院校能力建设项目(20040501400)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.05.0220
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 1
Section: Algorithm Research & Explore
Pages: 183-187
Serial Number: 1001-3695(2024)01-027-0183-05

Publish History

[2023-07-25] Accepted Paper
[2024-01-05] Printed Article

Cite This Article

余欣磊, 周贤文, 张依恋, 等. 基于区间分块Q学习的智能车辆安全舒适刹车算法 [J]. 计算机应用研究, 2024, 41 (1): 183-187. (Yu Xinlei, Zhou Xianwen, Zhang Yilian, et al. Interval-block-based Q-learning algorithm for safe and comfortable braking of intelligent vehicles [J]. Application Research of Computers, 2024, 41 (1): 183-187. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)