Metro passenger flow control with station-to-station cooperation based on stop-skipping and boarding limiting

Jiang, Man; Li, Haiying; Xu, Xinyue; Xu, Shipeng; Miao, Jianrui

doi:10.1007/s11771-017-3424-x

Cited by 48 publications

(14 citation statements)

References 21 publications

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“…e goal of the stop-skipping strategy was to minimize the impact of accidental disturbances. In addition to the studies on realtime management, Jiang et al [31] investigated the stopskipping strategy under given total inbound demand. To modify the inbound passenger distribution among stations, the authors built a passenger original station choice model based on utility theory.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Urban Metro Management Approach for Crowd Density Control

Zhou

Zheng

Cen

et al. 2021

Journal of Advanced Transportation

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Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range.

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Section: Introductionmentioning

confidence: 99%

A Data-Driven Urban Metro Management Approach for Crowd Density Control

Zhou

Zheng

Cen

et al. 2021

Journal of Advanced Transportation

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“…For example, Wang et al [14] studied the joint PFC problem between stations on a rail line to minimize the average passenger delay. By considering the dynamic propagation features of passenger flow, Jiang et al [15] developed a dynamic PFC model on a metro line for maximizing the comprehensive profit of both boarding passengers and limited passengers. Shi et al [17] proposed a method for collaboratively optimizing the origin-destination PFC strategies of multiple stations.…”

Section: Introductionmentioning

confidence: 99%

Integrated Optimization of Bus Route Adjustment With Passenger Flow Control for Urban Rail Transit

Zhou

et al. 2021

IEEE Access

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The contradiction between transport capacity and passenger demand in urban rail transit is usually prominent during peak hours in some megacities of China, and some passenger flow control measures have been adopted to alleviate passenger congestion. To better save passengers' travel time when taking passenger flow control measures, this paper proposes an integrated optimization method of bus route adjustment with networklevel passenger flow control for urban rail transit, in which the controlled passengers can freely choose to shift to bus or to retain in urban rail transit for pursuing a lower travel cost. With the objectives of minimizing average additional travel time for all affected passengers and maximizing the operating revenue of urban rail transit, an integer non-linear programming model is formulated to determine the inbound passenger volumes and bus adjustment schemes. To solve this proposed model effectively, a multi-objective particle swarm optimization based on dual-population co-evolution is designed. Finally, three sets of numerical experiments, including an integrated optimization experiment and two independent optimization experiments of passenger flow control, are implemented to demonstrate the feasibility and benefits of the proposed method.

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“…Further, Jiang et al [28] proposed a coordinated optimization scheme, which combined both the coordinated passenger inflow control and train rescheduling strategies, to minimize the penalty value of passengers being stranded along the whole line. In addition, the station hall control method, which requires passengers to wait in the station hall, was studied in literatures [30][31][32][33][34]. For example, Jiang et al [32] constructed a mathematical model to maximize the profits of passengers by simultaneously controlling nonstop stations and limiting boarding.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the station hall control method, which requires passengers to wait in the station hall, was studied in literatures [30][31][32][33][34]. For example, Jiang et al [32] constructed a mathematical model to maximize the profits of passengers by simultaneously controlling nonstop stations and limiting boarding. Shi et al [34] proposed a mathematical model aiming at minimizing the total waiting time for passengers and passenger accumulation risks in an oversaturated network.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Multilevel Collaborative Passenger Flow Control in Peak Hours for a Subway Line

Xue

Jia

Guo

2020

Advances in Mathematical Physics

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Due to contradiction of large-scale passenger demand and limited transportation capacity, the passengers who cannot be transported away in time accumulate and congest in stations. To ensure travel safety, improve travel efficiency, and ameliorate waiting environments for passengers, this paper proposes an adaptive multilevel collaborative passenger flow control strategy integrating the control of station entrance and station hall. An integer linear programming model is constructed, which aims at minimizing the total passenger waiting time and taking the safe capacity of each key area of all stations as the necessary constraints. The model is applied in two scenarios with different scales of passenger demand in the morning peak of the Batong line. The results show that the proposed model can adaptively activate the appropriate control level, limit the amount of accumulated passengers in each key area of the station within its safe capacity, and shorten the total passenger waiting time.

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Metro passenger flow control with station-to-station cooperation based on stop-skipping and boarding limiting

Cited by 48 publications

References 21 publications

A Data-Driven Urban Metro Management Approach for Crowd Density Control

A Data-Driven Urban Metro Management Approach for Crowd Density Control

Integrated Optimization of Bus Route Adjustment With Passenger Flow Control for Urban Rail Transit

Adaptive Multilevel Collaborative Passenger Flow Control in Peak Hours for a Subway Line

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