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/2134/8279

Title: Road traffic congestion and crash severity: econometric analysis using ordered response models
Authors: Quddus, Mohammed A.
Wang, Chao
Ison, Stephen G.
Keywords: Traffic congestion
Traffic flow
Crash severity
Ordered response models
M25 motorway
Issue Date: 2010
Publisher: © American Society of Civil Engineers
Citation: QUDDUS, M.A., WANG, C. and ISON, S.G., 2010. Road traffic congestion and crash severity: econometric analysis using ordered response models. Journal of Transportation Engineering, 136 (5), pp. 424-435.
Abstract: There is an ongoing debate among transport planners and safety policy makers as to whether there is any association between the level of traffic congestion and road safety. One can expect that the increased level of traffic congestion aids road safety and this is because average traffic speed is relatively low in a congested condition relative to an uncongested condition, which may result in less severe crashes. The relationship between congestion and safety may not be so straightforward, however, as there are a number of other factors such as traffic flow, driver characteristics, road geometry, and vehicle design affecting crash severity. Previous studies have employed count data models either Poisson or negative binomials and their extensions while developing a relationship between the frequency of traffic crashes and traffic flow or density as a proxy for traffic congestion . The use of aggregated crash counts at a road segment level or at an area level with the proxy for congestion may obscure the actual relationship. The objective of this study is to explore the relationship between the severity of road crashes and the level of traffic congestion using disaggregated crash records and a measure of traffic congestion while controlling for other contributory factors. Ordered response models such as ordered logit models, heterogeneous choice models, and generalized ordered logit (partially constrained) models suitable for both ordinal dependent variables and disaggregate crash data are used. Data on crashes, traffic characteristics e.g., congestion, flow, and speed , and road geometry e.g., curvature and gradient were collected from the M25 London orbital motorway between 2003 and 2006. Our results suggest that the level of traffic congestion does not affect the severity of road crashes on the M25 motorway. The impact of traffic flow on the severity of crashes, however, shows an interesting result. All other factors included in the models also provide results consistent with existing studies.
Version: Accepted for publication
DOI: 10.1061/(ASCE)TE.1943-5436.0000044
URI: https://dspace.lboro.ac.uk/2134/8279
Publisher Link: http://dx.doi.org/10.1061/(ASCE)TE.1943-5436.0000044
ISSN: 0733-947X
Appears in Collections:Published Articles (Architecture, Building and Civil Engineering)

Files associated with this item:

File Description SizeFormat
Quddus_et_al_ASCE_2009 Revised Version 27 08 2009.pdf149.96 kBAdobe PDFView/Open
Quddus_et_al_ASCE_2009 Revised Version 27 10 2009 final version.docAccepted version188 kBMicrosoft WordView/Open


SFX Query

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