A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 15.3, Top 1 (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
J. Wu and Y. C. Lou, “Efficient centralized traffic grid signal control based on meta-reinforcement learning,” IEEE/CAA J. Autom. Sinica, 2023. doi: 10.1109/JAS.2023.123270
Citation: J. Wu and Y. C. Lou, “Efficient centralized traffic grid signal control based on meta-reinforcement learning,” IEEE/CAA J. Autom. Sinica, 2023. doi: 10.1109/JAS.2023.123270

Efficient Centralized Traffic Grid Signal Control Based on Meta-Reinforcement Learning

doi: 10.1109/JAS.2023.123270
More Information
  • loading
  • [1]
    X. Zang, H. Yao, G. Zheng, N. Xu, K. Xu, and Z. Li, “Metalight: Value-based meta-reinforcement learning for traffic signal control,” in Proc. AAAI Conf. Artificial Intelligence, 2020.
    [2]
    H. Zhang, C. Liu, W. Zhang, G. Zheng, and Y. Yu, GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning. New York, USA: Association for Computing Machinery, 2020, p. 1783–1792. [Online]. Available: https://doi.org/10.1145/3340531.3411859
    [3]
    C. Finn, P. Abbeel, and S. Levine, “Model-agnostic meta-learning for fast adaptation of deep networks,” in Proc. Int. Conf. Machine Learning, 2017, pp. 1126–1135.
    [4]
    J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov, “Proximal policy optimization algorithms,” arXiv preprint arXiv: 1707.06347, 2017.
    [5]
    J. Schulman, P. Moritz, S. Levine, M. Jordan, and P. Abbeel, “Highdimensional continuous control using generalized advantage estimation,” 2018.
    [6]
    G. Zheng, Y. Xiong, X. Zang, J. Feng, H. Wei, H. Zhang, Y. Li, K. Xu, and Z. Li, “Learning phase competition for traffic signal control,” in Proc. 28th ACM Int. Conf. Information and Knowledge Management, 2019, pp. 1963–1972.
    [7]
    H. Wei, N. Xu, H. Zhang, G. Zheng, X. Zang, C. Chen, W. Zhang, Y. Zhu, K. Xu, and Z. Li, “Colight: Learning network-level cooperation for traffic signal control,” in Proc. 28th ACM Int. Conf. Information Knowledge Management, 2019.
    [8]
    H. Wei, G. Zheng, V. Gayah, and Z. Li, “A survey on traffic signal control methods,” arXiv preprint arXiv: 1904.08117, 2019.
    [9]
    P. Varaiya, “The max-pressure controller for arbitrary networks of signalized intersections,” in Advances in Dynamic Network Modeling in Complex Transportation Systems, Springer, 2013, pp. 27–66.
    [10]
    H. Wei, G. Zheng, H. Yao, and Z. Li, “Intellilight: A reinforcement learning approach for intelligent traffic light control,” in Proc. 24th ACM SIGKDD Int. Conf. Knowledge Discovery & Data Mining. 2018, pp. 2496–2505.
    [11]
    I. Arel, C. Liu, T. Urbanik, and A. G. Kohls, “Reinforcement learningbased multi-agent system for network traffic signal control,” IET Intelligent Transport Syst., vol. 4, no. 2, pp. 128–135, 2010. doi: 10.1049/iet-its.2009.0070
    [12]
    H. Wei, C. Chen, G. Zheng, K. Wu, V. Gayah, K. Xu, and Z. Li, “Presslight: Learning max pressure control to coordinate traffic signals in arterial network,” in Proc. 25th ACM SIGKDD Int. Conf. Knowledge Discovery & Data Mining, 2019, pp. 1290–1298.
    [13]
    L. Ma, B. Xue, and J. Wu, “Centralized traffic signal control for multiple intersections based on sequence-to-sequence model and attention mechanism,” in Proc. IEEE Int. Intelligent Transportation Systems Conf., 2021, pp. 2519–2524.

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(3)  / Tables(1)

    Article Metrics

    Article views (168) PDF downloads(23) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return