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Automated real-time railway traffic control: an experimental analysis of reliability, resilience and robustness

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  • Francesco Corman
  • Egidio Quaglietta
  • Rob M. P. Goverde

Abstract

Railway transportation provides sustainable, fast and safe transport. Its attractiveness is linked to a broad concept of service reliability: the capability to adhere to a timetable in the presence of delays perturbing traffic. To counter these phenomena, real-time rescheduling can be used, changing train orders and times, according to rules of thumb, or mathematical optimization models, minimizing delays or maximizing punctuality. In the literature, different indices of robustness, reliability and resilience are defined for railway traffic. We review and evaluate these indices applied to railway traffic control, comparing optimal rescheduling approaches such as Open Loop and Closed Loop control, to a typical First-Come-First-Served dispatching rule, and following the timetable (no-action). This experimental analysis clarifies the benefits of automated traffic control for infrastructure managers, railway operators and passengers. The timetable order, normally used in assessing a-priori reliability, systematically overestimates unreliability of operations that can be reduced by real-time control.

Suggested Citation

  • Francesco Corman & Egidio Quaglietta & Rob M. P. Goverde, 2018. "Automated real-time railway traffic control: an experimental analysis of reliability, resilience and robustness," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(4), pages 421-447, May.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:4:p:421-447
    DOI: 10.1080/03081060.2018.1453916
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    Cited by:

    1. Zhang, Huimin & Li, Shukai & Wang, Yihui & Yang, Lixing & Gao, Ziyou, 2021. "Collaborative real-time optimization strategy for train rescheduling and track emergency maintenance of high-speed railway: A Lagrangian relaxation-based decomposition algorithm," Omega, Elsevier, vol. 102(C).
    2. Luan, Xiaojie & De Schutter, Bart & Meng, Lingyun & Corman, Francesco, 2020. "Decomposition and distributed optimization of real-time traffic management for large-scale railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 72-97.

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