Data Analysis to study Sub-threshold Delays incurred by Tyne and Wear Metro Trains
| Autor: | Aleksandrs Rjabovs, Christopher Shilton, Daniel Screen, James Parkinson, Marin Marinov |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Service (systems architecture)
Punctuality Urban rail transit Computer science media_common.quotation_subject Geography Planning and Development Transportation Metro 010501 environmental sciences 01 natural sciences Transport engineering Software 0502 economics and business Headway Electrical and Electronic Engineering Delays 0105 earth and related environmental sciences Civil and Structural Engineering media_common 050210 logistics & transportation business.industry 05 social sciences Performance analysis lcsh:TA1001-1280 lcsh:HE1-9990 Urban Studies Data set Automotive Engineering Metro trains Train lcsh:Transportation engineering lcsh:Transportation and communications Drill down business |
| Zdroj: | Urban Rail Transit, Vol 6, Iss 2, Pp 93-103 (2020) |
| ISSN: | 2199-6679 |
| Popis: | The 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. |
| Databáze: | OpenAIRE |
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