In this work, various quantitative methods for the identification of high risk intersections in urban areas are studied. The paper describes the development of a method for the identification of such intersections. The identification method is based on separating data on each intersection into couples of traffic directions which are grouped according to the type of collision (rear-end or right-angle accidents) that is associated with each couple of directions. For each of the two groups. a statistical model is defined which estimates the number of accidents, as a Poisson process. The accident expectation is a function of the traffic volumes, the number of lanes in the relevant directions, and the existence of traffic lights. A list of high risk intersections based on the deviation from the expected number of accidents, was built for each model. This list was then compared to a naive list based only on the number of accidents. A similar comparison was made with an aggregate model for the total number of accidents at each intersection. It was found that, for the lists based on traffic directions, the naive lists were very similar to the lists derived from the other models. On the basis of these findings, a simple method was defined for the identification of high risk intersections in urban areas. The research was carried out on a sample of 76 intersections located in Tel-Aviv. (a) for the covering abstract of the seminar see IRRD 273510.
Samenvatting