Knowledge Commons of Institute of Automation,CAS
A Policy-Based Reinforcement Learning Approach for High-Speed Railway Timetable Rescheduling | |
Yin Wang1,2,3; Yisheng Lv1,2; Jianying Zhou4; Zhiming Yuan3; Qi Zhang3; Min Zhou5 | |
2021 | |
会议名称 | 2021 IEEE International Intelligent Transportation Systems Conference |
会议日期 | 19-22 Sept. 2021 |
会议地点 | Indianapolis, IN, USA |
摘要 | In the daily management of high-speed railway systems, the train timetable rescheduling problem with unpredictable disturbances is a challenging task. The large number of stations and trains leads to a long-time consumption to solve the rescheduling problem, making it difficult to meet the realtime requirements in real-world railway networks. This paper proposes a policy-based reinforcement learning approach to address the high-speed railway timetable rescheduling problem, in which the agent minimizes the total delay by adjusting the departure sequence of all trains along the railway line. A two-stage Markov Decision Process model is established to model the environment where states, actions, and reward functions are designed. The proposed method contains an offline learning process and an online application process, which can give the optimal rescheduling schedule based on the current state immediately. Numerical experiments are performed over two different delay scenarios on the Beijing-Shanghai high-speed railway line. The simulation results show that our approach can find a high-quality rescheduling strategy within one second, which is superior to the First-Come-First-Served (FCFS) and First-Scheduled-First-Served (FSFS) methods. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 人工智能+交通 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/47493 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
通讯作者 | Yisheng Lv; Jianying Zhou |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.China Academy of Railway Sciences Corporation Limited 4.Shanghai Lixin University of Accounting and Finance 5.Beijing Jiaotong University |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yin Wang,Yisheng Lv,Jianying Zhou,et al. A Policy-Based Reinforcement Learning Approach for High-Speed Railway Timetable Rescheduling[C],2021. |
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