Collision Type Categorization Based on Crash Causality and Severity Analysis

The purpose of this paper is to present an empirical inquiry into the categorization of collision types based on contribution factors and severity distribution. This study used Connecticut crash data from selected two-lane roads originated from police reports from 1996 to 2001. K-means cluster analysis methodology was conducted to categorize 10 collision types into 4 groups according to the similar pattern of their contribution factors. The severity distribution of the collision types was then considered to further divide up or combine the categories. The result of this analysis offers an analytical way at categorizing collisions to relate crash risk to causalities and further driver misbehaviors, and provides a crash categorization that can lead to more accurate and specific severity prediction.

• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Zhang, Chen
  • Ivan, John N
  • Jonsson, Thomas
• Conference:
  • Transportation Research Board 86th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2007-1-21 to 2007-1-25
• Date: 2007

Language

• English

Media Info

• Media Type: CD-ROM
• Features: Figures; References; Tables;
• Pagination: 21p
• Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

• TRT Terms: Cluster analysis; Crash analysis; Crash causes; Crashes; Mathematical models; Mathematical prediction; Traffic safety
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I80: Accident Studies;

Filing Info

• Accession Number: 01044787
• Record Type: Publication
• Report/Paper Numbers: 07-2454
• Files: BTRIS, TRIS, TRB
• Created Date: Feb 8 2007 7:08PM