posted on 2016-01-22, 13:34authored byParaskevi Michalaki, Mohammed Quddus, D.E. Pitfield, Andrew Huetson
Problem The severity of motorway accidents that occurred on the hard shoulder (HS) is higher than for the main carriageway (MC). This paper compares and contrasts the most important factors affecting the severity of HS and MC accidents on motorways in England. Method Using police reported accident data, the accidents that occurred on motorways in England are grouped into two categories (i.e., HS and MC) according to the location. A generalized ordered logistic regression model is then applied to identify the factors affecting the severity of HS and MC accidents on motorways. The factors examined include accident and vehicle characteristics, traffic and environment conditions, as well as other behavioral factors. Results Results suggest that the factors positively affecting the severity include: number of vehicles involved in the accident, peak-hour traffic time, and low visibility. Differences between HS and MC accidents are identified, with the most important being the involvement of heavy goods vehicles (HGVs) and driver fatigue, which are found to be more crucial in increasing the severity of HS accidents. Practical applications Measures to increase awareness of HGV drivers regarding the risk of fatigue when driving on motorways, and especially the nearside lane, should be taken by the stakeholders.
Funding
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).
History
School
Architecture, Building and Civil Engineering
Published in
Journal of Safety Research
Volume
55
Pages
89 - 97
Citation
MICHALAKI, P. ... et al., 2015. Exploring the factors affecting motorway accident severity in England using the generalised ordered logistic regression model. Journal of Safety Research, 55, pp.89-97.
This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/
Publication date
2015
Notes
This is an open access article published by Elsevier under the CC BY
license (http://creativecommons.org/licenses/by/4.0/).