Developing a Cluster-Based Algorithm for Collision Hotspot Identification

Traffic safety is one of the most important goals for roadway design and traffic system operations. Collision hotspot identification serves as a major fundamental component for traffic safety performance measurements. With identified collision hotspots, limited resources can be better allocated to improve roadway safety. There has been a significant amount of studies on collision hotspots identification over the past decades. However, most studies only considered crash counts as the sole roadway safety performance indicator. In this study, a new cluster-based method is proposed to quantify roadway safety conditions. This method is able to incorporate more heterogeneous safety-related factors for clustering, such as crash fatality, injuries, and average collision duration. Compared with the prevailing Empirical Bayes methods, the authors cluster-based method demonstrates its improved accuracy and efficiency, and can be easily implemented in practice.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 2381-2395
  • Monograph Title: CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems

Subject/Index Terms

Filing Info

  • Accession Number: 01531194
  • Record Type: Publication
  • ISBN: 9780784413623
  • Files: TRIS, ASCE
  • Created Date: Jul 2 2014 3:03PM