Optimal Bus-Bridging Service under a Metro Station Disruption

Yin, Haodong; Wu, Jianjun; Sun, Huijun; Qu, Yunchao; Yang, Xin; Bo, Wang

doi:10.1155/2018/2758652

Cited by 25 publications

(13 citation statements)

References 21 publications

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“…( 2017 ) Metro system congestion and overcrowding mitigation through bus bridging Case study for Shanghai (China) Yin et al. ( 2018 ) Three-layer discrete choice behavior model to analyze the dynamic passenger flow demand under station disruption Case for Beijing (China) Zhang and Lo ( 2020 ) Contract design between a mass transit provider and a bus company providing the bridging service …”

Section: Appendixmentioning

confidence: 99%

Robustness and disturbances in public transport

Voß

Xie

2022

Public Transp

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Network-based systems are at the core of our everyday life. Whether it is electronic networking, electricity grids or transportation, users expect the networks to function properly and provide a feeling of safety and security. However, there may be disturbances. In this paper, we consider disturbances in the context of public transportation. The focus in this respect is on public transport planning and operations. To classify and cope with disturbances, one can find many ideas, including robustness, resilience, vulnerability, disruption mitigation or delay management. We survey related streams of literature and put them into perspective. As a major insight we show that different strands of literature exist that may benefit from becoming better connected and intertwined. Together with recent advances in information technology and solution methods, more integrated problem settings incorporating robustness and disturbances can play a major role in future planning and operations.

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Section: Appendixmentioning

confidence: 99%

Robustness and disturbances in public transport

Voß

Xie

2022

Public Transp

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“…Zhang et al studied the best initial time of bridging bus [37]. Yin established a three-layer discrete selection model for dynamic passenger flow demand after disruption and set up a bridging bus plan to minimize the total passenger evacuation time and bus operation cost [38]. Wang studied the influencing factors of passengers' travel choices under URT network disruption [39], while Wei explored the impact of disruption on passenger travel behaviour based on multiagent [40].…”

Section: Literature Reviewmentioning

confidence: 99%

An Optimization Approach considering Passengers’ Space-Time Requirements for Bus Bridging Service under URT Disruption

Shao

Song

2022

Journal of Advanced Transportation

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Rapid urbanization and growth of population in megacities generate severe pressures on urban rail transit (URT) system. The quantity and frequency of disruptive events have increased significantly, which might have obvious adverse impacts. A large number of passengers are stranded at disrupted URT station when a disruptive event occurs. One essential solution for passenger evacuation is the bus bridging service. This paper is aimed at addressing the passenger evacuation problem caused by a disruptive event in the URT network, by proposing a bus bridging service model considering the passengers’ space-time requirements. The model is proposed to minimize the waiting time of passengers and considers factors including bus service capacity limitations, bus stop parking capacity, and the maximum bridging time limit of a single bus. Buses are assumed to provide bridging service on either the local bus route or the direct bus route. The optimal routes and scheduling plans of bridging bus are designed. The model is applied to an example of a disruptive event in Shanghai URT line 9. The results of this example show that the proposed model is capable of reducing the waiting time of passengers and the number of buses used by 3.2% and 24.7%, compared with the traditional bus bridging service. Further analysis of the example shows that it is not a cost-effective solution to reserve a large number of buses for URT disruption. Decision-makers should comprehensively trade off between passengers’ space-time demands and monetary costs of bus bridging service.

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“…Although dynamic passenger demand was taken into account with a rolling horizon approach, the essence is taking static passenger flows at the end of each rolling period as the input of the proposed model. Some other researchers studied travel behavior of passengers and travel demand after disruptions, which could provide references for this study [18][19][20]. For example, Wang et al [18] studied the demand modelling of affected passengers and formulated it as a bulk queuing problem with the theory of stochastic process.…”

Section: Journal Of Advanced Transportationmentioning

confidence: 99%

“…The results showed the bridging demand continued for hours. Yin et al [19] proposed a three-layer discrete choice behavior model to predict dynamic passenger flows. It was found that as time passed, an increasing number of passengers would alter their planned routes or quit metro journeys during the disruption.…”

Section: Journal Of Advanced Transportationmentioning

confidence: 99%

Optimization of Bus Bridging Service under Unexpected Metro Disruptions with Dynamic Passenger Flows

Wang

Yuan

Yin

2019

Journal of Advanced Transportation

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A metro disruption is a situation where metro service is suspended for some time due to unexpected events such as equipment failure and extreme weather. Metro disruptions reduce the level of service of metro systems and leave numerous passengers stranded at disrupted stations. As a means of disruption management, bus bridging has been widely used to evacuate stranded passengers. This paper focuses on the bus bridging problem under operational disruptions on a single metro line. Unlike previous studies, we consider dynamic passenger flows during the disruption. A multi-objective optimization model is established with objectives to minimize total waiting time, the number of stranded passengers and dispatched vehicles with constraints such as fleet size and vehicle capacity. The NSGA-II algorithm is used for the solution. Finally, we apply the proposed model to Shanghai Metro to access the effectiveness of our approaches in comparison with the current bridging strategy. Sensitivity analysis of the bus fleet size involved in the bus bridging problem was conducted.

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Optimal Bus-Bridging Service under a Metro Station Disruption

Cited by 25 publications

References 21 publications

Robustness and disturbances in public transport

Robustness and disturbances in public transport

An Optimization Approach considering Passengers’ Space-Time Requirements for Bus Bridging Service under URT Disruption

Optimization of Bus Bridging Service under Unexpected Metro Disruptions with Dynamic Passenger Flows

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