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Communication Dans Un Congrès Année : 2023

Designing self-organizing railway traffic management

Résumé

Railway traffic management requires a timely and accurate redefinition of routes and schedules in response to detected perturbations of the original timetable. To date, most of the (automated) solutions to this problem require a central authority to take decisions for all the trains in a given control area. An appealing alternative is to consider trains as intelligent agents able to self-organize and determine the best traffic management strategy without any central control. This could lead to more scalable and resilient management strategies, that can also take into account the real-time mobility demand. In this paper, we propose an implementation of a self-organizing railway traffic management system, designed in a way to enable real-world deployment. We describe the different processes brought forth by the trains in a decentralized way, and evaluate the approach in a realistic setting representing traffic in a French control area. The results confirm that self-organizing railway traffic management is a viable option, and foster further research in this direction.
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Dates et versions

hal-04410747 , version 1 (22-01-2024)

Identifiants

  • HAL Id : hal-04410747 , version 1

Citer

Leo D’amato, Federico Naldini, Valentina Tibaldo, Vito Trianni, Paola Pellegrini. Designing self-organizing railway traffic management. RailBelgrade 2023, the 10th International Conference on Railway Operations Modelling and Analysis (ICROMA), International Association of Railway Operations Research and University of Belgrade, Apr 2023, Belgrade, Serbia. ⟨hal-04410747⟩
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