IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt3ms7789j.html
   My bibliography  Save this paper

Integrating Management of Truck and Rail Systems in Los Angeles

Author

Listed:
  • Dessouky, Maged
  • Fu, Lunce
  • Hu, Shichun

Abstract

This project establishes models to optimize the balance of freight demand across rail and truck modes. In real life situations, trains often travel at different speeds (i.e. passenger trains and freight trains share the same rail network). This incurs train delay whereby reducing the efficiency of the rail network. To provide a solution for this problem, we develop heuristic algorithms to improve conventional dispatching rules to reduce the average train delay. Then we build a control model and provide the solution procedure to adapt a dynamic headway concept inspired by new signaling technology like Positive Train Control (PTC). Rail network data of the Southern California region is collected to perform a detailed simulation analysis. The simulation results show significant improvement of network efficiency brought by our model and algorithms: as high as 21% reduction in average train delay with our best dispatching policy while with the dynamic headway control model, the average train delay is reduced by 40%. The railway network is therefore shown to have the potential to increase throughput capacity by 20%. View the NCST Project Webpage

Suggested Citation

  • Dessouky, Maged & Fu, Lunce & Hu, Shichun, 2018. "Integrating Management of Truck and Rail Systems in Los Angeles," Institute of Transportation Studies, Working Paper Series qt3ms7789j, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt3ms7789j
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/3ms7789j.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mu, Shi & Dessouky, Maged, 2013. "Efficient dispatching rules on double tracks with heterogeneous train traffic," Transportation Research Part B: Methodological, Elsevier, vol. 51(C), pages 45-64.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenliang Zhou & Xiaorong You & Wenzhuang Fan, 2020. "A Mixed Integer Linear Programming Method for Simultaneous Multi-Periodic Train Timetabling and Routing on a High-Speed Rail Network," Sustainability, MDPI, vol. 12(3), pages 1-34, February.
    2. Ursani, Ziauddin & Mei, T.X. & Whiteing, Anthony, 2013. "A fault tolerance approach for railway scheduling and train control," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 161-173.
    3. Li, Feng & Gao, Ziyou & Wang, David Z.W. & Liu, Ronghui & Tang, Tao & Wu, Jianjun & Yang, Lixing, 2017. "A subjective capacity evaluation model for single-track railway system with δ-balanced traffic and λ-tolerance level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 43-66.
    4. Sairong Peng & Xin Yang & Hongwei Wang & Hairong Dong & Bin Ning & Haichuan Tang & Zhipeng Ying & Ruijun Tang, 2019. "Dispatching High-Speed Rail Trains via Utilizing the Reverse Direction Track: Adaptive Rescheduling Strategies and Application," Sustainability, MDPI, vol. 11(8), pages 1-20, April.
    5. Yin, Jiateng & Yang, Lixing & Tang, Tao & Gao, Ziyou & Ran, Bin, 2017. "Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 182-213.
    6. Xu, Xiaoming & Li, Keping & Yang, Lixing, 2015. "Scheduling heterogeneous train traffic on double tracks with efficient dispatching rules," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 364-384.
    7. Yin, Jiateng & Tang, Tao & Yang, Lixing & Gao, Ziyou & Ran, Bin, 2016. "Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 178-210.
    8. Zhan, Shuguang & Kroon, Leo G. & Zhao, Jun & Peng, Qiyuan, 2016. "A rolling horizon approach to the high speed train rescheduling problem in case of a partial segment blockage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 32-61.

    More about this item

    Keywords

    Engineering; Delays; Freight trains; Freight transportation; Headways; Passenger trains; Positive train control; Railroad tracks; Switches (Railroads);
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsdav:qt3ms7789j. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.