A Matheuristic for the Integrated Disruption Management of Traffic, Passengers and Stations in Urban Railway Lines

Journal Article (2021)
Author(s)

Nikola Bešinović (TU Delft - Transport and Planning)

Yihui Wang (Beijing Jiaotong University)

Songwei Zhu (Beijing Jiaotong University)

E. Quaglietta (TU Delft - Transport and Planning)

Tao Tang (Beijing Jiaotong University)

R.M.P. Goverde (TU Delft - Transport and Planning)

Transport and Planning
Copyright
© 2021 Nikola Bešinović, Yihui Wang, Songwei Zhu, E. Quaglietta, Tao Tang, R.M.P. Goverde
DOI related publication
https://doi.org/10.1109/TITS.2021.3093570
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Nikola Bešinović, Yihui Wang, Songwei Zhu, E. Quaglietta, Tao Tang, R.M.P. Goverde
Transport and Planning
Issue number
8
Volume number
23
Pages (from-to)
10380-10394
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Abstract

In big cities, the metro lines usually face great pressure caused by huge passengers demand, especially during peak hours. When disruptions occur, passengers accumulate quickly at stations. It is of great importance for dispatchers to take passenger flow control into consideration for the traffic management to ensure passengers' safety and to maintain their satisfaction. This paper proposes an integrated disruption management model, which incorporates train rescheduling and passenger flow control. In this model, the train services can be short-turned, cancelled and rerouted, while the number of passengers entering a station is managed by controlling the station gates with consideration of the capacities of platforms and trains. Moreover, the number of passengers arriving at a station is calculated according to the origin-destination matrices. The objectives are to recover the train operation to the original timetable as soon as possible and to minimize the waiting time of passengers outside the stations. With the interaction between train services, passengers and station gates, an iterative metaheuristic approach is proposed to solve the integrated disruption management problem. Based on the data of a Beijing metro line, numerical experiments are conducted to test the proposed algorithm. The results demonstrate the importance of integrated disruption management and the effectiveness of our solution method.

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