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 un-congested 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, roadgeometry 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 orderedlogit 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, 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 impactof 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.
Abstract