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

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

Urban Rail Transit ›› 2020, Vol. 6 ›› Issue (2) : 93 -103.

PDF
Urban Rail Transit ›› 2020, Vol. 6 ›› Issue (2) : 93 -103. DOI: 10.1007/s40864-020-00125-4
Original Research Papers

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

Author information +
History +
PDF

Abstract

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.

Keywords

Urban rail transit / Punctuality / Performance analysis / Metro / Metro trains / Delays / Timetables

Cite this article

Download citation ▾
Daniel Screen, James Parkinson, Christopher Shilton, Aleksandrs Rjabovs, Marin Marinov. Data Analysis to Study Sub-threshold Delays Incurred by Tyne and Wear Metro Trains. Urban Rail Transit, 2020, 6(2): 93-103 DOI:10.1007/s40864-020-00125-4

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Marinov M, Viegas J. A mesoscopic simulation modelling methodology for analyzing and evaluating freight train operations in a rail network. Simul Model Pract Theory, 2011, 19: 516-539

[2]

Rjabovs A, Palacin R, Robinson M (2014) Cab and system design influence on metro drivers’ performance: preliminary study. In: Transport research arena, April 2014, Paris

[3]

Rjabovs A, Palacin R. Attitudes of metro drivers towards design of immediate physical environment and system layout. Urban Rail Transit, 2015, 1(2): 104-111

[4]

Wales J, Marinov M. Analysis of delays and delay mitigation on a metropolitan railway network using event based simulation. Simul Model Pract Theory, 2015, 52: 55-77

[5]

Dampier A, Marinov M. A study of the feasibility and potential implementation of metro-based freight transportation in Newcastle upon Tyne. Urban Rail Transit, 2015, 1(3): 164-182

[6]

Darlton A, Marinov M. Suitability of tilting technology to the Tyne and Wear Metro system. Urban Rail Transit, 2015, 1(1): 47-68

[7]

Rjabovs A, Palacin R. The influence of system design-related factors on the safety performance of metro drivers. Proc Inst Mech Eng Part F J Rail Rapid Transit, 2016, 231: 317-328

[8]

Rjabovs A, Palacin R (2016b) Design and layout of the physical environment in a metro system: appraisal of Tyne and Wear Metro drivers’ perceptions. In: WCTRS, July 2016, Shanghai

[9]

Powell JP, Fraszczyk A, Cheong CN, Yeung HK. Potential benefits and obstacles of implementing driverless train operation on the Tyne and Wear Metro: a simulation exercise. Urban Rail Transit, 2016, 2(3): 114-127

[10]

Powell JP, Batty P, González-Gil A, Palacin R. Determining system-wide energy use in an established metro network. Proc Inst Mech Eng Part F Rail Rapid Transit, 2017, 231(5): 570-577

[11]

Marinov Marin, Şahin İsmail, Ricci Stefano, Vasic-Franklin Gordana. Railway operations, time-tabling and control. Res Transp Econ, 2013, 41(1): 59-75

AI Summary AI Mindmap
PDF

152

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/