Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/20631

Title: A time-series analysis of motorway collisions in England considering road infrastructure, socio-demographics, traffic and weather characteristics
Authors: Michalaki, Paraskevi
Quddus, Mohammed A.
Pitfield, D.E.
Huetson, Andrew
Keywords: Public health
Vector autoregressive
Issue Date: 2016
Publisher: © The Authors. Published by Elsevier Ltd.
Citation: MICHALAKI, P. ... et al., 2016. A time-series analysis of motorway collisions in England considering road infrastructure, socio-demographics, traffic and weather characteristics. Journal of Transport & Health, in press, available online 11 February 2016, doi:10.1016/j.jth.2015.10.005
Abstract: Traffic injuries on motorways are a public health problem worldwide. Collisions on motorways represent a high injury rate in comparison to the entire national network. Furthermore, collisions that occur on the hard–shoulder are even more severe than those that happen on the main carriageway. The purpose of this paper is to explore motorway safety through the identification of patterns in the sequence of monthly hard–shoulder and main carriageway collisions separately over a long period of time (1993– 2011) by using reported collision data from British motorways. In order to examine the trends of hard– shoulder and motorway collisions over the same period, a Vector Autoregressive (VAR) model is developed; this allows the inclusion of two time-series in the same model and the examination of the effect of one series on the other and vice-versa. Exogenous variables are also added in order to explore the long-term factors that might affect the occurrence of collisions. The factors considered are related to the infrastructure (e.g. length of motorways), socio-demographics (e.g. percentage of young drivers), traffic (e.g. percentage of vehicle-miles travelled by Heavy Goods Vehicles) and weather (e.g. precipitation). The results suggest different patterns in the sequences in terms of the lingering effects of preceding observations for the two time-series. In terms of the significance of exogenous variables, it is suggested that main carriageway collision frequency is affected by weather conditions and the presence of Heavy Goods Vehicles, while hard–shoulder collisions are decreased by the presence of Motorway Service Areas, which allow a safe exit off the motorway to stop and rest in case of fatigue.
Description: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Sponsor: This research was undertaken as part of an Engineering Doctorate project jointly funded by the Centre of Innovative and Collaborative Construction Engineering (CICE) at Loughborough University and Balfour Beatty. The support of the Engineering and Physical Sciences Research Council is gratefully acknowledged (EPSRC Grant EP/F037272/1).
Version: Published
DOI: 10.1016/j.jth.2015.10.005
URI: https://dspace.lboro.ac.uk/2134/20631
Publisher Link: http://dx.doi.org/10.1016/j.jth.2015.10.005
ISSN: 2214-1405
Appears in Collections:Published Articles (Architecture, Building and Civil Engineering)

Files associated with this item:

File Description SizeFormat
1-s2.0-S2214140515006908-main.pdfPublished version862 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.