Abstract

Terminal capacity and performance have become a major concern for rail transit agencies in China due to the ever increasing passenger demand. This paper develops a mixed integer programming (MIP) optimization model to estimate the turnback capacity and performance of a rail transit terminal with two-tail tracks. The capacity evaluation and delay propagation are described and assessed as anN-track integrated model with minimal time span and train delay. Operations and design parameters such as tail track allocation strategies, maximum layover time, headway pattern, buffer time distribution scheme, and primary delay are also considered in this model. The effectiveness of the model is tested by a case study with computation results drawn from one terminal station in Shanghai, China. The case study results show that unfixed platform time and flexible tail track allocation strategies can improve the capacity of turnback operation, and the strategy of allowing swapping of the tail tracks has a significantly positive impact on delay absorption.

Highlights

  • A rail transit terminal is a key point for train movements, where trains reverse direction to provide continuing service in the opposite direction

  • A simple model was presented in Transit Cooperative Research Program (TCRP) Report 13 [3], and the capacity of a 2-track stub-end terminal based on infrastructure layout and train movement characteristics was estimated

  • In TCRP Report 165, Kittelson et al [4] presented a formula to extend the approach to estimating terminal layover time and found that the layout and configuration design of a terminal played a key role in providing delay recovery and service performance

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Summary

Introduction

A rail transit terminal is a key point for train movements, where trains reverse direction (turn back) to provide continuing service in the opposite direction. The main objectives of this paper are to construct a new MIP optimization model for the turnback capacity and disruption management problems of a rail transit terminal and to develop a robust numerical tool that can help transit agencies to better assess the capacity and performance of their terminals to serve the Mathematical Problems in Engineering ever increasing demands, while considering the major factors that affect the capacity of a transit terminal. The application of this model may be applied to the planning, design, and safety assessment of a rail transit terminal

Background
Problem Description
Optimization Model
B Train 1
Strategy 1
Strategy 2
Strategy 3
Strategy 4
Application on Shanghai Rail Transit Line 1
Conclusions
Full Text
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