Full Professor Kuwait University Kuwait, Al Asimah, Kuwait
This work tried to better understand the factors behind severe and fatal injuries in pedestrian and vehicle accidents while giving a special attention to built environment parameters. Statistical models were applied on the traffic accident data reported by the traffic police in the emirate of Abu Dhabi over a period of 5 and a half years, between 2008 and 2013. A review of the literature on traffic accidents and injury levels showed that Random Parameter Logit models are well suited for pedestrian-vehicle accidents, while Generalized Ordered Logit models prove a good fit for vehicle-vehicle accidents. The models were completed using statistical analysis software STATA from Statacorp. The results of the modelling showed that overall pedestrians above 51 were at a higher risk of sustaining severe or fatal injuries, and that driver and pedestrian distraction was number one reason for pedestrian-vehicle accidents with around 64% of the total. Additionally, bad lighting condition was found to be directly correlated with higher injury levels among pedestrians. Meanwhile, it was observed that on motor ways accidents due to distracted driving were more probable than those in one-way streets, and pavements covered with sand had a negative impact on driver distraction. To better understand the driver behaviour among people in Kuwait, an online survey was conducted, and a total of 625 participants most of whom were females (399) completed it. The completed responses were inputted into SPSS, the statistical software from IBM, in order to look for correlations between the responses. The results showed that being a male and being a younger driver is strongly correlated with taking risks, violating traffic rules as well as driving aggressively. Therefore, to improve road safety in Kuwait, it is important to implement concepts similar to those found in the Abu Dhabi Urban Street Design Manual, followed by strict traffic law enforcement. In addition, conducting awareness campaigns at Universities and secondary school is needed to tackle the younger generation who will soon obtain their driving licenses.
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