Traffic safety analysis by surrogate measures:an extreme value approach

Sammanfattning

Road safety analyses are required for the prevention of road accident fatalities. In Europe, the ambition is "Vision Zero". Data that was used is collected by the research group Transport and Roads which is part of Department of Technology and Society at LTH, Lund University. The dataset of video-recorded traffic situations used in the study was limited to encounters in which one motor vehicle turns left at an intersection and a straight-passing vehicle approaches. Distance between the cars were registered and used as surrogate measure for the risk of collision, specifically, the Minimum Distance (MD) between the involved motor vehicles during an interaction and Post Encroachment Distance (PED). The PED is the distance computed at the moment when the first road-user leaves the lane of the second road-user. The nearness to collision is of interest, thus, the probability that distances are less than 0 need to be computed. Modelling was done with Generalized Extreme Value Distribution (GEV) and Generalized Pareto Distribution (GPD) together with block maxima and Peak Over Threshold (POT), respectively. The model GPD yielded the best results with probability of collision being $.0173%.