Dynamic Passenger Assignment for Major Railway Disruptions Considering Information Interventions

Zhu, YC Youcai; Goverde, Rob M.P.

doi:10.1007/s11067-019-09467-4

Cited by 26 publications

(8 citation statements)

References 22 publications

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“…Ghaemi et al [16] investigated the impact of railway disruption prediction and used a multinomial logit choice model to determine the passenger route choices together with the macroscopic MILP rescheduling model of Ghaemi et al [10] in an iterative framework. Zhu and Goverde [17] proposed a schedule-based passenger assignment model to distribute passengers. Zhu and Goverde [18] used this model to determine passengers' paths and the passenger-dependent weights in the objective function, with the aim of minimizing the cancelled trains, number of skipping stops and passenger delays.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Bešinović

Wang

Zhu

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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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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Section: Literature Reviewmentioning

confidence: 99%

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

Bešinović

Wang

Zhu

et al. 2022

IEEE Trans. Intell. Transport. Syst.

Self Cite

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“…In this condition, the waiting time is 4.5 min, and the valid train frequency is 9 min. Considering the effective frequency, the new model (F2) can be rewritten as 4 Complexity…”

Section: Optimal Strategy With Capacity Constraintsmentioning

confidence: 99%

“…At the same time, when the disturbance or disruption happened, the operation scheme and the timetable could be adjusted according to the assignment results, such as retiming and providing short loop trains. In this way, the disorder could be solved with a more passenger-friendly solution [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Passenger Behavior Simulation in Congested Urban Rail Transit System: A Capacity‐Limited Optimal Strategy Model for Passenger Assignment

Lu¹,

Cao²

2022

Complexity

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Optimal strategy, one of the main transit assignment models, can better demonstrate the flexibility for passengers using routes in a transit network. According to the basic optimal strategy model, passengers can board trains based on their frequency without any capacity limitation. In the metropolitan cities such as Beijing, Shanghai, and Hong Kong, morning commuters face huge transit problems. Especially for the metro system, there is heavy rush in metro stations. Owing to the limited train capacity, some passengers cannot board the first coming train and need to wait for the next one. To better demonstrate the behavior of passengers pertaining to the limited train capacity, we consider capacity constraints for the basic optimal strategy model to represent the real situation. We have proposed a simulation-based algorithm to solve the model and apply it to the Beijing Subway to demonstrate the feasibility of the model. The application of the proposed approach has been demonstrated using the computational results for transit networks originating from practice.

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“…They maximized the service level provided to passengers by reducing the delays of the operated trains and the number of canceled trains. Reference [30] presented a new passenger assignment model based on scheduling during major interruptions, which considered the passengers starting travelling before, during and after the interruptions. The model considered time-dependent passenger demand, service variations and vehicle capacity constraints to track individual travels, which was helpful to evaluate a interrupted timetable based on passenger orientation.…”

Section: A Timetable Scheduling and Reschedulingmentioning

confidence: 99%

Scheduling Extra Train Paths Into Cyclic Timetable Based on the Genetic Algorithm

Tan

Wang

2020

IEEE Access

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In order to support the process of scheduling a hybrid cyclic timetable, this paper is devoted to inserting additional non-cyclic train paths into existing cyclic timetable. The adding train paths problem is an integration of timetable scheduling and rescheduling problem. The train dispatcher can not only modify the given timetable to manage the interruptions in existing operations, but also establish schedules for additional trains. A multi-objective model minimizing both the travel time of additional trains and the variation of existing trains is proposed in this paper. In addition, we consider both general constraints and some additional practical constraints, such as the overtaking priority constraint, reasonable adjustment of initial schedules and the scheduled connections. This problem is very difficult and must be solved in practice. A heuristic algorithm is introduced to find high-quality solutions for large-scale cases within reasonable computing time. Based on high-speed railway line in China, the case studies illustrate the methodology and compare the performance of trains. Numerical experiments indicate that the proposed solution approach to the adding train paths problem is promising. INDEX TERMS High-speed railway, cyclic timetable, adding additional train paths, genetic algorithm, mixed integer programming.

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Dynamic Passenger Assignment for Major Railway Disruptions Considering Information Interventions

Cited by 26 publications

References 22 publications

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

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

Passenger Behavior Simulation in Congested Urban Rail Transit System: A Capacity‐Limited Optimal Strategy Model for Passenger Assignment

Scheduling Extra Train Paths Into Cyclic Timetable Based on the Genetic Algorithm

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