Optimizing and Synchronizing Timetable in an Urban Subway Network Considering Passenger Stochastic Demand

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Eslami, Alireza | 2024

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 57066 (09)
University: Sharif University of Technology
Department: Civil Engineering
Advisor(s): Shafahi, Yousef
Abstract:
This research aims to introduce a mathematical model that is capable of producing an optimal and coordinated timetable for the entire urban rail network to minimize passengers’ travel time and the trains’ energy consumption. The proposed model focuses on different speed profiles and a skip-stop strategy while considering the stochastic nature of passengers’ arrival and departure rates. This novel approach enables it to develop a schedule that can endure unprecedented situations. To solve the model, the multi-agent deep deterministic policy gradient algorithm is implemented. This approach was first implemented in a smaller network and was validated with Genetic Algorithm. Eventually, this methodology was implemented on lines 1, 2, and 4 of Tehran’s metro network as a case study. the results indicate that using the skip-stop strategy and optimizing trains’ speed profiles along their paths can reduce the networks’ costs, including passengers’ waiting costs and the trains’ energy consumption costs by 2.3% and 14.8%, respectively
Keywords:
Metro Scheduling ; Stop-Skipping Strategy ; Velocity Profile ; Reinforcement Learning ; Metro Lines Synchronization ; Genetic Algorithm ; Dynamic Demand ; Passenger Demand

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