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The Development of a GIS-based tool to Identify Dangerous Road Segments on the Road Network

Thursday, 19 September, 2013 - 16:00
Campus: Brussels Humanities, Sciences & Engineering campus
Faculty: Social Sciences and Solvay Business School
Koen Van Raemdonck
phd defence

The public defence of the Ph.D. in Applied Economics for Koen Van Raemdonck will take place on Thursday September 19th 2013 at 4pm in the Promotion room, building D, 2nd floor, room D2.01, VUB-Campus Etterbeek, Pleinlaan 2, 1050 Brussel.

The Ph.D. thesis is called "The Development of a GIS-based tool to Identify Dangerous Road Segments on the Road Network."
Promoter: Prof. dr. Cathy Macharis

Please confirm your attendance by Friday September 13nd 2013 to .


Road traffic accidents and traffic safety in general are a huge societal problem. Traffic accidents are estimated to be the third leading cause of premature death worldwide by 2020. Next to the human suffering, traffic accidents also result in huge social and economic costs. This clearly shows the necessity to consistently improve the road safety situation and why traffic safety is a major concern in the view of sustainable development. In order to reduce the number of accidents and road fatalities, appropriate and well-supported road safety measures need to be taken and the road infrastructure has to be improved, permitting to reduce the severity of the consequences of the inevitable human errors. However, because of constraints in time and money, road manufacturers cannot modify all roads in order to improve safety. One effective and widely used approach in order to improve road infrastructure is black spot management, since this makes it possible to allocate the available resources to the most dangerous locations. Therefore, this PhD dissertation focuses on this black spot management and offers a solution for the need for a methodology with sound theoretical foundations in order to identify high risk locations, by developing a GIS-based tool, called the Road Accident Analyzer (RAA), which is based on the state-of-the-art approaches for black spot management. High risk locations are not only identified because of the accidents which happened in the past, the RAA also makes use of an accident prediction model based on the road characteristics, enabling that segments which can be considered dangerous because of its location specific features will also be selected. Consequently the RAA can be considered a useful aid for reaching the common goal which improving road traffic safety definitely is.