Survey on Driverless Train Operation for Urban Rail Transit Systems

被引:31
|
作者
Wang Y. [1 ]
Zhang M. [1 ]
Ma J. [2 ]
Zhou X. [3 ]
机构
[1] State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing
[2] Transportation Solutions and Technology Applications Division, Leidos, Inc, Reston, 20190, VA
[3] School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, 85287, AZ
基金
中国国家自然科学基金;
关键词
Capacity; Driverless train operation; Energy efficiency; Safety; Urban rail transit;
D O I
10.1007/s40864-016-0047-8
中图分类号
学科分类号
摘要
The length of metro lines with driverless train operation (DTO) systems is increasing globally and is predicted to triple in the next 10 years. This paper gives the history and future trend of the DTO systems. The opportunities provided by the DTO systems, such as lower operation costs, increased capacity, and energy efficiency, are explained and the relevant research are reviewed. Furthermore, the challenges faced by the DTO systems are analyzed, such as safety issues, train control technology, and emergency situations. © 2016, The Author(s).
引用
收藏
页码:106 / 113
页数:7
相关论文
共 50 条
  • [1] A Survey on Energy-Efficient Train Operation for Urban Rail Transit
    Yang, Xin
    Li, Xiang
    Ning, Bin
    Tang, Tao
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (01) : 2 - 13
  • [2] A Train Holding Model for Urban Rail Transit Systems
    Puong, Andre
    Wilson, Nigel H. M.
    [J]. COMPUTER-AIDED SYSTEMS IN PUBLIC TRANSPORT, 2008, 600 : 319 - 337
  • [3] Optimization method for the networking train operation plan of urban rail transit
    Wang, Yongliang
    Zhang, Xingchen
    Xu, Bin
    Xie, Xiaoling
    [J]. Zhongguo Tiedao Kexue/China Railway Science, 2012, 33 (05): : 120 - 126
  • [4] Energy-Efficient Optimization for Train Tracking Operation in Urban Rail Transit
    Gu, Qing
    Ma, Fei
    Meng, Yu
    [J]. 2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2014, : 834 - 839
  • [5] Train Operation Adjustment of the Urban Rail Transit based on Dwell Time Model
    Dong, Hairong
    Liu, Jiazheng
    Chen, Yao
    Sun, Xubin
    [J]. 2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2014, : 2422 - 2427
  • [6] Train Operation Traction Energy Calculation and Saving in Urban Rail Transit System
    Hu, Peng
    Chen, Rongwu
    Li, Haoyu
    Liang, Yi
    [J]. PROCEEDINGS OF THE 2012 SECOND INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC 2012), 2012, : 505 - 507
  • [7] Optimization of Stop-skip Train Operation Scheme for Urban Rail Transit
    Cao Z.
    Yuan Z.
    Li D.
    Zhang S.
    [J]. Yuan, Zhenzhou (zzyuan@bjtu.edu.cn), 2017, Science Press (39): : 15 - 22
  • [8] Urban rail transit Automatic Train Operation system online algorithm research
    Feng, Tangsong
    Cao, Fang
    [J]. 2017 INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS, ELECTRONICS AND CONTROL (ICCSEC), 2017, : 899 - 904
  • [9] Machine Learning in Urban Rail Transit Systems: A Survey
    Zhu, Li
    Chen, Cheng
    Wang, Hongwei
    Yu, F. Richard
    Tang, Tao
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 25 (03) : 2182 - 2207
  • [10] Optimization of Train Operation Plan of Through Operation Between Urban Rail Transit and Suburban Railway
    Tian, Zhiqiang
    Kong, Zibo
    Han, Huiyuan
    Wu, Wanpeng
    Zeng, Juan
    [J]. IAENG International Journal of Applied Mathematics, 2024, 54 (12) : 2612 - 2619