ITSC 2024 Paper Abstract

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Paper ThBT13.15

Lin, Xiao (Beijing Jiaotong University), Wu, Xueliang (Beijing Mass Transit Railway Operation Corporation Limited), Shang, Du (Beijing Jiaotong University), Su, Shuai (Beijing Jiaotong university)

Optimization of Rescheduling under Temporary Speed Restrictions in Urban Rail Transit: A MILP Model Approach

Scheduled for presentation during the Poster Session "Railway systems and applications" (ThBT13), Thursday, September 26, 2024, 14:30−16:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Keywords Simulation and Modeling, Theory and Models for Optimization and Control, Traffic Theory for ITS

Abstract

In urban rail operations, temporary speed limits may be imposed on certain sections due to factors such as track cracks, subway track maintenance, line construction, track renovation, or other external operations near track. These issues could prevent trains from running according to the scheduled timetable, leading to trains delay, cancellations, and longer waiting times for passengers. To reduce the impact of these disruptions, this paper introduces a model-based optimization method for scheduling temporary speed limits on urban rail lines. The model aims to minimize the deviation of trains from their planned timetable and the number of train cancellations, while establishing operational constraint models. Ultimately, the model undergoes linearization to facilitate a solution, which is achieved through numerical integration alongside the application of the Big-M method. This paper considers decision variables and constraints related to train speed limit operations and formulates the problem as a Mixed Integer Linear Programming (MILP) model, which can be solved by the CPLEX optimizer. An example is provided to illustrate the effectiveness of the proposed train scheduling model.The computational results indicate that the establishment of the optimization model reduces the impact of temporary speed restrictions.

 

 

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