• DocumentCode
    663269
  • Title

    An optimization approach for real-time headway control of railway traffic

  • Author

    Jing Xun ; Bin Ning ; Ke-Ping Li ; Tao Tang

  • Author_Institution
    State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
  • fYear
    2013
  • fDate
    Aug. 30 2013-Sept. 1 2013
  • Firstpage
    25
  • Lastpage
    31
  • Abstract
    Headway irregularity not only increases average passenger wait time but also causes additional energy consumption and more delay time at bottlenecks. A real-time headway control model is proposed to maintain headway regularity at bottlenecks in railway network by adjusting the travel time on each segment for each train. The adjustment of travel time is based on a consensus algorithm. In the proposed consensus algorithm, the control law is obtained by solving Ricatti equation. The minimum running time on segment is also considered. The computation time of the proposed method is analyzed and the analysis result shows that it can satisfy the requirement on real-time. The proposed model is tested and the consensus trend of headways can be observed through simulation. The simulation results also demonstrate that energy consumption canbe reduced by 0.1% at most and the delay time is reduced by 6.5% at least after using the proposed method.
  • Keywords
    Riccati equations; delays; energy consumption; optimisation; railways; Ricatti equation; average passenger wait time; bottlenecks; consensus algorithm; delay time; energy consumption; headway irregularity; optimization approach; railway network; railway traffic; real-time headway control model; Decision support systems; CBTC; Consensus Algorithm; Cooperative Control; Headway Regularity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Rail Transportation (ICIRT), 2013 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-5278-9
  • Type

    conf

  • DOI
    10.1109/ICIRT.2013.6696262
  • Filename
    6696262