Reference
G. Cavone, T. van den Boom, L. Blenkers, M. Dotoli, C. Seatzu, and B. De
Schutter, "An MPC-based rescheduling algorithm for disruptions and disturbances
in large-scale railway networks,"
IEEE Transactions on
Automation Science and Engineering, vol. 19, no. 1, p. 99-112, Jan.
2022.
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 a 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.
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BibTeX
@article{Cavvan:21-002,
author = {Cavone, Graziana and van den Boom, Ton and Blenkers, Lex and
Dotoli, Mariagrazia and Seatzu, Carla and De Schutter, Bart},
title = {An {MPC}-Based Rescheduling Algorithm for Disruptions and
Disturbances in Large-Scale Railway Networks},
journal = {IEEE Transactions on Automation Science and Engineering},
volume = {19},
number = {1},
pages = {99-112},
month = jan,
year = {2022}
}