Train trajectory optimisation of ATO systems for metro lines

Ning Zhao*, Clive Roberts, Stuart Hillmansen, Paul Western, Lei Chen, Zhongbei Tian, Tingyu Xin, Shuai Su

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

This paper describes an Enhanced Brute Force Algorithm application to optimise train trajectory (driving speed curve) for Automatic Train Operation (ATO) systems. A multi-train simulator was developed specifically for the study. It can be used to simulate the movement of railway vehicles and calculate the detailed power system energy consumption with different train trajectories when implemented on an AC or DC powered railway line operating with multiple trains. Results are presented using a practical train trajectory and an optimal train trajectory with a full day timetable and passenger flow on the Beijing Yizhuang Metro Line. Analysis of the results shows that by using an optimal train trajectory, the energy consumption around the power network can be significantly reduced within a constrained journey time. Furthermore, the results also show that the developed simulator is able to facilitate the understanding of the railway traction and power system, and that it provides guidance for adjusting the service timetable and driving strategy to minimise energy usage.

Original languageEnglish
Title of host publication2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1796-1801
Number of pages6
ISBN (Print)9781479960781
DOIs
Publication statusPublished - 14 Nov 2014
Event2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 - Qingdao, China
Duration: 8 Oct 201411 Oct 2014
Conference number: 17th

Conference

Conference2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
Country/TerritoryChina
CityQingdao
Period8/10/1411/10/14

ASJC Scopus subject areas

  • Computer Science Applications
  • Automotive Engineering
  • Mechanical Engineering

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