Abstract (short version):

Both traffic congestion and road accidents impose a burden on society, and it is therefore important for transport policy makers to reduce their impact. An ideal scenario would be that traffic congestion and accidents are reduced simultaneously, however, this may not be possible since it has been speculated that increased traffic congestion may be beneficial in terms of road safety. If this is confirmed then it poses a potential dilemma for transport policy makers. It is therefore important to fully understand the relationship between traffic congestion and road accidents.

 

The relationship between traffic congestion and road accidents appears to be an under researched area. This thesis aims to explore the relationship between traffic congestion and road accidents by using an econometric and GIS approach. The analysis is based on the data from the M25 motorway and its surrounding major roads for the period 2003 – 2007. A series of econometric models have been employed to investigate the effect of traffic congestion on both accident frequency (such as Bayesian spatial models) and accident severity (such as mixed logit models). The model estimation results suggest that traffic congestion is positively associated with the frequency of fatal and serious injury accidents and negatively (i.e. inversely) associated with the severity of accidents that have occurred. Other contributing factors have also been controlled for and produced results consistent with previous studies. It is concluded that traffic congestion overall has a negative impact on road safety. This may be partially due to higher speed variance among vehicles within and between lanes and worse driving behaviour in the presence of congestion.

The results indicate that mobility and safety can be improved simultaneously, and therefore there is significant additional benefit of reducing traffic congestion in terms of road safety. Several policy implications have been identified in order to optimise the traffic flow and improve driving behaviour, which would be beneficial to both congestion and accident reduction.

This thesis also proposes a new map-matching technique so as to assign accidents to the correct road segments, and shows how a two-stage modelling process which combines both accident frequency and severity models can be used in site ranking with the objective of identifying hazardous accident hotspots for further safety examination and treatment.

Key words: Traffic congestion, road accidents, GIS, M25 motorway, site ranking, accident hotspots, spatial econometrics, full Bayesian hierarchical models, ordered and nominal response models, two-stage mixed multivariate models