Robust collaborative passenger flow control on a congested metro line: A joint optimization with train timetabling

Lu, Yahan; Yang, Lixing; Yang, Hai; Zhou, Housheng; Gao, Ziyou

doi:10.1016/j.trb.2022.12.008

Cited by 25 publications

(5 citation statements)

References 29 publications

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“…Constraint (10) assures that the number of passengers boarding the train is less than the number of passengers waiting on the platform. Constraint (11) means that one train is operated to transport the unsatisfied passengers on all the platforms after the last train of the considered time horizon.…”

Section: Constraintsmentioning

confidence: 99%

“…Constraint (20) ensures that the number of passengers boarding bus-bridging services is non-negative. Similar to constraint (11), constraint (21) indicates that a bus will be put into operation at the end of the considered time period.…”

Section: Constraintsmentioning

confidence: 99%

“…Considering the flexible bus routes, Wang et al (2019) [4] established a multi-objective optimization model to minimize the evacuation time and average travel delay of the affected passengers. In addition, collaborative optimization that combines the multiple aforementioned approaches to alleviate congestion to the maximum extent have become a trendy in recent years (Yang et al 2017 [1] , Lu et al 2023 [11] , Shi et al 2018 [10] ). However, it is noteworthy that only a few studies consider the integrated optimization of passenger flow control and busbridging services.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Integrated optimization of passenger flow control and bus-bridging on oversaturated urban rail transit lines

Li,

2023

Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023)

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Section: Constraintsmentioning

confidence: 99%

Section: Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Integrated optimization of passenger flow control and bus-bridging on oversaturated urban rail transit lines

Li,

2023

Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023)

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“…(Wang et al 2020) proposed a multi-station coordinated and dynamic inflow control method in URT, considering the interaction among stations and lines. (Lu et al 2023) introduced a joint optimization of the robust passenger control strategy and train timetable, in which operation efficiency and service fairness are considered.…”

Section: Passenger Flow Controlmentioning

confidence: 99%

A Reinforcement Method for Passenger Flow Control Based on Asynchronous Advantage Actor-Critic Neural Network

Wang

Jin

Luo

et al. 2023

Preprint

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Effective passenger flow management is critical for improving service quality and alleviating congestion in metro networks. However, the dynamic nature of travel demand and the complex structure of metro networks present significant challenges in building and solving control models. Additionally, the high computational costs of existing methods limit their practical applications. To address these challenges, this study proposes a new reinforcement learning (RL) based method for passenger flow control. The method has three components: the network state characterization, the control model, and the reinforcement learning model. Then, the study outlines the “action”, “state”, and “reward” concepts in RL based on the definition of decision variables, constraints, and objective functions in the constructed passenger flow control programming model. An iterative interaction mechanism is introduced to synchronize the control schemes generated by the reinforcement learning unit and the network states. Furthermore, effectively utilizing computational resources, the Asynchronous Advantage Actor-Critic Neural Network (A3C-NN) is trained to optimize the complex programming model. Finally, the proposed approach is validated through a case study using data from Chengdu Urban Rail Transit (URT), demonstrating its effectiveness in achieving various objectives, such as minimizing passenger waiting time, maximizing passenger turnover, and maximizing passenger numbers.

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“…For instance, Shi et al [3] established a mixed-integer linear programming model combining passenger-oriented train scheduling with fine-grained passenger flow control strategies. Lu et al [4] systematically researched the joint optimization of robust passenger flow control strategies and train scheduling on congested subway lines.…”

Section: Introductionmentioning

confidence: 99%

Joint optimization of train scheduling and rolling stock utilization planning: a virtual composition mode

Zheng,

Yuan

2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

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In the context of the increasing unbalanced passenger flow in both time and space, the conventional fixed formation mode is no longer able to cater to the dynamic demands of passengers. Thus, this paper presents a mixed-integer nonlinear programming model that aims to optimize train scheduling, rolling stock utilization planning, and passenger flow control strategy by incorporating virtual formation mode, in which the virtual formation enables trains to modify their composition through coupling/uncoupling operations at stations. The model with nonlinear constraints is subsequently converted into a model with linear constraints, making it amenable to direct solution using Gurobi solver. Finally, a series of numerical experiments are conducted using actual data from the Beijing Changping metro line. The computation results show that the proposed method effectively meets passenger demands while simultaneously ensuring reasonable reductions in operational costs.

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Robust collaborative passenger flow control on a congested metro line: A joint optimization with train timetabling

Cited by 25 publications

References 29 publications

Integrated optimization of passenger flow control and bus-bridging on oversaturated urban rail transit lines

Integrated optimization of passenger flow control and bus-bridging on oversaturated urban rail transit lines

A Reinforcement Method for Passenger Flow Control Based on Asynchronous Advantage Actor-Critic Neural Network

Joint optimization of train scheduling and rolling stock utilization planning: a virtual composition mode

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