Collaborative Optimization of Train Skip-stop and Passenger Flow Control on Subway Line Considering Passenger Evacuation at Transfer Stations

During the morning rush hour, subway lines and transfer stations face enormous pressure on passenger transportation and evacuation in major cities. The paper first explores the strategy of trains skipping transfer stations to reduce congestion at the transfer stations and pressure on passenger evacuation. A collaborative optimization model is then developed to jointly consider train skip-stop strategies at transfer stations and passenger flow control for a subway line operating in two directions, with the objective of minimizing passenger waiting times and transfer delays. The model is transformed into a linear integer programming model by approximating and linearizing relevant nonlinear constraints. The effectiveness of the proposed collaborative optimization model is verified through numerical experiments conducted on Beijing subway line 5. The CPLEX optimization solver, utilizing the branch and bound algorithm, is employed to solve the model, confirming the practical effectiveness of the proposed approach. The experimental results indicated that, compared to the existing passenger flow control with all-stop scheme, the optimized scheme significantly increases the number of passengers by 2954 that is carried by a train within a 14-minute timeframe. Furthermore, it reduces delay times experienced outside stations, transfer delays, and the overall delay time by 58.9%, 16.9%, and 41.6%, respectively. © 2023 Science Press. All rights reserved.