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.