An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks

Graziana Cavone, Ton van den Boom, Lex Blenkers, Mariagrazia Dotoli, Carla Seatzu, Bart De Schutter

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling algorithm for real-time control of railway traffic that aims at minimizing the delays induced by the disruption and disturbances, as well as the resulting cancellations of train runs and turn-backs (or short-turns) and shuntings of trains in stations. The real-time control is based on the Model Predictive Control (MPC) scheme where the rescheduling problem is solved by mixed integer linear programming using macroscopic and mesoscopic models. The proposed resolution algorithm combines a distributed optimization method and bi-level heuristics to provide feasible control actions for the whole network in short computation time, without neglecting physical limitations nor operations at disrupted stations. A realistic simulation test is performed on the complete Dutch railway network. The results highlight the effectiveness of the method in properly minimizing the delays and rapidly providing feasible feedback control actions for the whole network.

Original languageEnglish
JournalIEEE Transactions on Automation Science and Engineering
DOIs
Publication statusAccepted/In press - 1 Jan 2021

Keywords

  • Delays
  • Feedback control
  • Heuristic algorithms
  • Mixed Integer Linear (MIL) Programming (MILP)
  • Model Predictive Control (MPC)
  • Optimization
  • Prediction algorithms
  • Rail transportation
  • railway traffic disruption
  • Real-time systems
  • rescheduling algorithms.

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