Integration of Probability and Clustering Based Approaches in the Field of Black Spot Identification

Authors

  • Maen Ghadi
  • Árpád Török
  • Katalin Tánczos
https://doi.org/10.3311/PPci.11753

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.

Keywords:

black spots, empirical Bayesian, k-mean algorithm, cluster analysis, road safety

Citation data from Crossref and Scopus

Published Online

2018-10-19

How to Cite

Ghadi, M., Török, Árpád, Tánczos, K. “Integration of Probability and Clustering Based Approaches in the Field of Black Spot Identification”, Periodica Polytechnica Civil Engineering, 63(1), pp. 46–52, 2019. https://doi.org/10.3311/PPci.11753

Issue

Section

Research Article