With the urban population growth and rising transportation demand, the importance of vehicle operation organization in urban rail transit systems has become crucial. The existing contradiction between passenger service levels and vehicle capacity allocation needs addressing, especially in the context of long-term operations, to enhance efficiency. This article systematically studies vehicle operation optimization based on existing research findings. A space-time node network connection diagram is constructed to target daily vehicle operation issues, leading to the development of a daily operation plan compilation model aimed at minimizing operational costs without maintenance constraints. An improved greedy algorithm is introduced to solve this model, involving three main steps: generating daily operation plans, connecting these plans, and fixing the number of vehicles in the depot. Case analyses reveal that the number of operating vehicles decreased from 25 to 13, significantly optimizing operational costs and balance. This demonstrates the effectiveness of the improved algorithm in urban rail transit and offers new approaches for vehicle scheduling in transportation systems.
Research on urban rail transit vehicle operation model based on passenger flow variation
International Conference on Smart Transportation and City Engineering (STCE 2024) ; 2024 ; Chongqing, China
Proc. SPIE ; 13575
28.04.2025
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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