Data Analysis to Study Sub-threshold Delays Incurred by Tyne and Wear Metro Trains

Author:

Screen Daniel,Parkinson James,Shilton Christopher,Rjabovs Aleksandrs,Marinov MarinORCID

Abstract

AbstractThe performance of Tyne and Wear Metro system in the UK is measured on a headway basis, and gaps in service that are 4 min or more in excess of scheduled gaps are investigated and the cause documented. The metro system has a number of infrastructure constraints including single-line sections, junctions and level crossings, all of which have to be taken account of when constructing the timetable, in order to avoid trains being held by the signalling system, causing delays. The objective of this study is to analyse delays less than 4 min, which are not investigated or attributed to a cause, known as sub-threshold delays. The purpose of the analysis is to identify regularly occurring issues which are due to the timetable, in order to recommend changes. Two different data sets were used. The first data set explored specific trains, areas and times of day where delays were highest. The second data set allowed us to drill down on each of those in greater detail by studying station departure times for each train. A number of options to resolve the issues identified during the analysis are proposed. Whilst the results are specific to the Tyne and Wear Metro system, the methodology is suitable for use by other urban rail transit systems. The study identified several areas of future work including resolving data recording issues, carrying out further investigation of trains at peak times in particular scenarios, and automating the analysis through the use of other software.

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Urban Studies,Transportation,Automotive Engineering,Geography, Planning and Development,Civil and Structural Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3