Coordinated Optimization of Passenger Flow Control and Train Skip-Stop Strategy in Metro Systems Incorporating Reservation

Peak-hour congestion in metro systems poses significant challenges to operational reliability and passenger experience. This study investigates a coordinated operational strategy that integrates passenger flow control, reservation-based entry, and skip-stop train operations to alleviate congestion in high-density metro corridors. A mathematical optimization model is formulated to jointly capture passenger demand, station crowding, and train capacity constraints, and is solved using an adaptive large neighborhood search algorithm. Numerical experiments based on a real-world metro line demonstrate that the proposed framework can effectively reduce passenger waiting time and improve the balance of passenger distribution across stations under peak-hour conditions. The results indicate that coordinating multiple operational measures yields better performance than applying individual strategies in isolation, highlighting the practical value of the proposed approach for congested metro systems.

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Publication Details

Journal
Vehicles
Published
2026-03-16
DOI
https://doi.org/10.3390/vehicles8030062
Primary Topic
Railway Systems and Energy Efficiency
Type
article
Field-Weighted Citation Impact
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article

Coordinated Optimization of Passenger Flow Control and Train Skip-Stop Strategy in Metro Systems Incorporating Reservation

Jiaxin Li, Xujie Feng, Xiaoya Gao
Vehicles
Railway Systems and Energy Efficiency
article

Coordinated Optimization of Passenger Flow Control and Train Skip-Stop Strategy in Metro Systems Incorporating Reservation

Jiaxin Li, Xujie Feng, Xiaoya Gao
article en

Abstract

Peak-hour congestion in metro systems poses significant challenges to operational reliability and passenger experience. This study investigates a coordinated operational strategy that integrates passenger flow control, reservation-based entry, and skip-stop train operations to alleviate congestion in high-density metro corridors. A mathematical optimization model is formulated to jointly capture passenger demand, station crowding, and train capacity constraints, and is solved using an adaptive large neighborhood search algorithm. Numerical experiments based on a real-world metro line demonstrate that the proposed framework can effectively reduce passenger waiting time and improve the balance of passenger distribution across stations under peak-hour conditions. The results indicate that coordinating multiple operational measures yields better performance than applying individual strategies in isolation, highlighting the practical value of the proposed approach for congested metro systems.

VehiclesVol. 8(3)
Beijing Jiaotong University (CN), China Academy of Transportation Sciences (CN)
Sustainable cities and communities
Openalex Percentile: Top 22%
Railway Systems and Energy Efficiency
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