How does existing data improve decision making? A case study of wind-related incidents on rail network

Q. Fu; J. M. Easton

doi:10.1049/cp.2016.0515

How does existing data improve decision making? A case study of wind-related incidents on rail network

Q. Fu
, J. M. Easton

School of Social Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

Weather impacts on rail performance is complex. In this paper, we present an empirical data analysis of train delays, which were particularly attributed to wind, within the Anglia Route of Great Britain's railway network. This investigation involves a variety of data sources that are relevant to those railway incidents, including their detailed records, historic weather and trackside vegetation conditions and so on. Our work briefly explores how those data could be exploited in order to gain a deeper insight into the occurrence of the incidents, given the correlations between various factors, such as wind speed and tree density surrounding the incident sites. The survey findings will serve to underlie further analyses by using more advanced statistical approaches, for which specific recommendations are also made.

Original language	English
Title of host publication	International Conference on Railway Engineering (ICRE 2016)
Publisher	Institution of Engineering and Technology
ISBN (Print)	9781785612923
DOIs	https://doi.org/10.1049/cp.2016.0515
Publication status	Published - 2016
Event	2016 International Conference on Railway Engineering - Brussels, Belgium Duration: 12 May 2016 → 13 May 2016

Conference

Conference	2016 International Conference on Railway Engineering
Abbreviated title	ICRE 2016
Country/Territory	Belgium
City	Brussels
Period	12/05/16 → 13/05/16

Keywords

Big data
Railway
Weather impact
Wind

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1049/cp.2016.0515

Cite this

@inproceedings{ef860f0121274365a48cf3425b6a6481,

title = "How does existing data improve decision making? A case study of wind-related incidents on rail network",

abstract = "Weather impacts on rail performance is complex. In this paper, we present an empirical data analysis of train delays, which were particularly attributed to wind, within the Anglia Route of Great Britain's railway network. This investigation involves a variety of data sources that are relevant to those railway incidents, including their detailed records, historic weather and trackside vegetation conditions and so on. Our work briefly explores how those data could be exploited in order to gain a deeper insight into the occurrence of the incidents, given the correlations between various factors, such as wind speed and tree density surrounding the incident sites. The survey findings will serve to underlie further analyses by using more advanced statistical approaches, for which specific recommendations are also made.",

keywords = "Big data, Railway, Weather impact, Wind",

author = "Q. Fu and Easton, \{J. M.\}",

note = "Publisher Copyright: {\textcopyright} 2016, Institution of Engineering and Technology. All rights reserved.; 2016 International Conference on Railway Engineering, ICRE 2016 ; Conference date: 12-05-2016 Through 13-05-2016",

year = "2016",

doi = "10.1049/cp.2016.0515",

language = "English",

isbn = "9781785612923",

booktitle = "International Conference on Railway Engineering (ICRE 2016)",

publisher = "Institution of Engineering and Technology",

address = "United Kingdom",

}

TY - GEN

T1 - How does existing data improve decision making? A case study of wind-related incidents on rail network

AU - Fu, Q.

AU - Easton, J. M.

PY - 2016

Y1 - 2016

N2 - Weather impacts on rail performance is complex. In this paper, we present an empirical data analysis of train delays, which were particularly attributed to wind, within the Anglia Route of Great Britain's railway network. This investigation involves a variety of data sources that are relevant to those railway incidents, including their detailed records, historic weather and trackside vegetation conditions and so on. Our work briefly explores how those data could be exploited in order to gain a deeper insight into the occurrence of the incidents, given the correlations between various factors, such as wind speed and tree density surrounding the incident sites. The survey findings will serve to underlie further analyses by using more advanced statistical approaches, for which specific recommendations are also made.

AB - Weather impacts on rail performance is complex. In this paper, we present an empirical data analysis of train delays, which were particularly attributed to wind, within the Anglia Route of Great Britain's railway network. This investigation involves a variety of data sources that are relevant to those railway incidents, including their detailed records, historic weather and trackside vegetation conditions and so on. Our work briefly explores how those data could be exploited in order to gain a deeper insight into the occurrence of the incidents, given the correlations between various factors, such as wind speed and tree density surrounding the incident sites. The survey findings will serve to underlie further analyses by using more advanced statistical approaches, for which specific recommendations are also made.

KW - Big data

KW - Railway

KW - Weather impact

KW - Wind

UR - https://www.scopus.com/pages/publications/84998693337

U2 - 10.1049/cp.2016.0515

DO - 10.1049/cp.2016.0515

M3 - Conference contribution

AN - SCOPUS:84998693337

SN - 9781785612923

BT - International Conference on Railway Engineering (ICRE 2016)

PB - Institution of Engineering and Technology

T2 - 2016 International Conference on Railway Engineering

Y2 - 12 May 2016 through 13 May 2016

ER -

How does existing data improve decision making? A case study of wind-related incidents on rail network

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this