Integration of probability and clustering based approaches in the field of black spot identification

Abstract

The objective of the paper is to define a complex methodology to analyze black spot locations of road infrastructure network combining the benefit of both; Empirical Bayes method and K-mean clustering approach. In the first step, K-mean algorithm is used to define homogeneous accident clusters. The homogeneity is described in three terms: traffic conditions, geometric design of the road and accident characteristics. Then, Empirical Bayes method is applied to define black spots based on the determined clusters. Due to the combination of the introduced methods, a powerful technique is provided that is able to identify high-risk locations and cluster dependent segment length as the output of the model.