Cooperative passenger flow control in an oversaturated metro network with operational risk thresholds

Shi, Jungang; Yang, Lixing; Jing, Yang; Feng, Zhou; Gao, Ziyou

doi:10.1016/j.trc.2019.08.008

Cited by 78 publications

(30 citation statements)

References 39 publications

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“…All passengers can be served, even when the subway system reaches its maximum capacity. Therefore, this study does not address passenger control measures ( Shi et al, 2019;Liu et al, 2020b ) and capacity expansion measures ( Chen et al, 2019 ) to deal with over-saturated passenger demand. Furthermore, train capacity is not considered.…”

Section: N (E )mentioning

confidence: 99%

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

D’Ariano

Yang

et al. 2021

Transportation Research Part B: Methodological

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Subway lines connecting different urban functional zones in large cities have directiondependent and time-variant passenger demand, namely, asymmetry in passenger demand. Most existing studies adopt a symmetric strategy to design operations in both directions and sequentially optimize the different problems associated with operations, thereby failing to meet the asymmetry in passenger demand. This study formulates an asymmetric operation strategy as an integrated mixed-integer non-linear model to optimize the entire operational process of rolling stock from the perspective of service quality and operating costs. Based on the proposed model, an exact algorithm is proposed with speed-up techniques to quickly generate an optimal solution. To this end, the original model is decomposed into several sub-problems that can be exactly solved by using a forward dynamic programming algorithm. Based on actual data from the Beijing subway's Yizhuang line, numerical experiments are conducted to investigate the effectiveness of the asymmetric operation strategy, to identify managerial insights on the integrated optimization, and to evaluate the performance of the proposed methodology.

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Section: N (E )mentioning

confidence: 99%

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

D’Ariano

Yang

et al. 2021

Transportation Research Part B: Methodological

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“…Xu et al [29] proposed a bilevel programming to regulate volumes of inbound and transfer passengers, in which the upper level was to optimize the control strategies, while the lower level was to redistribute passengers in metro networks. Shi et al [30] proposed an integer linear programming model for the network passenger flow control problem to jointly minimize the total passenger waiting time and passenger accumulation risks at all stations.…”

Section: Literature Reviewmentioning

confidence: 99%

Equity-Oriented Train Timetabling with Collaborative Passenger Flow Control: A Spatial Rebalance of Service on an Oversaturated Urban Rail Transit Line

Gong

Mao

Wang

et al. 2020

Journal of Advanced Transportation

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On an oversaturated urban rail transit line, passengers at downstream stations have to wait for more trains until they get aboard, resulting in service imbalance problem. To improve the service quality, this paper proposes an integrated optimization approach combining the train timetabling and collaborative passenger flow control, with the aim of minimizing indicators associated with the passenger service imbalance and train loading capacity utilization. Considering train regulation constraints and passenger loading dynamics, a mixed-integer linear programming model is formulated. Based on the linear weighting technique, an iterative heuristic algorithm combining the tabu search and Gurobi solver is designed to solve the proposed model. Finally, a simple case with different-scale instances is used to verify that the proposed algorithm can obtain near-optimal solution efficiently. Moreover, a real-world case of Beijing Subway Batong Line is implemented to compare performances of the proposed approach with those under the original timetable and noncollaborative passenger flow control.

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“…1 , the transfer passenger demand at this station is always greater than the outside arrival passenger demand, which is particularly obvious during peak periods. Although some studies [5] , [6] , [7] , [8] , [9] have paid a great deal of attention to this problem, most still neglect to control transfer passengers simultaneously with outside arrival passengers. To relieve crowding and enhance efficiency as much as possible on an overall line, there is an urgent need to study passenger flow control strategies combined with train scheduling under the influence of transfer passengers—a need that is not addressed in the existing literature.…”

Section: Introductionmentioning

confidence: 99%

“…Their problem was formulated as a mixed-integer programming model to simultaneously adjust the number of inbound and transfer passengers, which could be solved by the genetic algorithm. Shi et al [9] developed an integer linear programming model to generate an optimal passenger flow control strategy for an urban rail transit system. Based on analyses of the alighting and boarding processes, Wang et al [14] formulated an integer programming model to achieve the optimal state for the entire urban rail transit line, with a focus on minimizing the average passenger delay.…”

Section: Introductionmentioning

confidence: 99%

A Distributionally Robust Optimization Method for Passenger Flow Control Strategy and Train Scheduling on an Urban Rail Transit Line

Yang

et al. 2022

Engineering

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Regular coronavirus disease 2019 (COVID-19) epidemic prevention and control have raised new requirements that necessitate operation-strategy innovation in urban rail transit. To alleviate increasingly serious congestion and further reduce the risk of cross-infection, a novel two-stage distributionally robust optimization (DRO) model is explicitly constructed, in which the probability distribution of stochastic scenarios is only partially known in advance. In the proposed model, the mean-conditional value-at-risk (mean-CVaR) criterion is employed to obtain a tradeoff between the expected number of waiting passengers and the risk of congestion on an urban rail transit line. The relationship between the proposed distributionally robust model and the traditional two-stage stochastic programming (SP) model is also depicted. Furthermore, to overcome the obstacle of model solvability resulting from imprecise probability distributions, a discrepancy-based ambiguity set is used to transform the robust counterpart into its computationally tractable form. A hybrid algorithm that combines a local search algorithm with a mixed-integer linear programming (MILP) solver is developed to improve the computational efficiency of large-scale instances. Finally, a series of numerical examples with real-world operation data are executed to validate the proposed approaches.

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Cooperative passenger flow control in an oversaturated metro network with operational risk thresholds

Cited by 78 publications

References 39 publications

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

Equity-Oriented Train Timetabling with Collaborative Passenger Flow Control: A Spatial Rebalance of Service on an Oversaturated Urban Rail Transit Line

A Distributionally Robust Optimization Method for Passenger Flow Control Strategy and Train Scheduling on an Urban Rail Transit Line

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