Crash involvement of drivers with multiple crashes

Susantha Chandraratna, Nikiforos Stamatiadis, Arnold Stromberg

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

A goal for any licensing agency is the ability to identify high-risk drivers. Kentucky data show that a significant number of drivers are repeatedly involved in crashes. The objective of this study is the development of a crash prediction model that can be used to estimate the likelihood of a driver being at fault for a near future crash occurrence. Multiple logistic regression techniques were employed using the available data for the Kentucky licensed drivers. This study considers as crash predictors the driver's total number of previous crashes, citations accumulated, the time gap between the latest two crashes, crash type, and demographic factors. The driver's total number of previous crashes was further disaggregated into the drivers' total number of previous at-fault and not-at-fault crashes. The model can be used to correctly classify at-fault drivers up to 74.56% with an overall efficiency of 63.34%. The total number of previous at-fault crash involvements, and having previous driver license suspensions and traffic school referrals are strongly associated with a driver being responsible for a subsequent crash. In addition, a driver's likelihood to be at fault in a crash is higher for very young or very old, males, drivers with both speeding and non-speeding citations, and drivers that had a recent crash involvement. Thus, the model presented here enables agencies to more actively monitor the likelihood of a driver to be at fault in a crash.

Original languageEnglish
Pages (from-to)532-541
Number of pages10
JournalAccident Analysis and Prevention
Volume38
Issue number3
DOIs
StatePublished - May 2006

Bibliographical note

Funding Information:
The authors wish to thank the Southeastern Transportation Center and the Federal Highway Administration for financial support (we take full responsibility for the conclusions drawn here).

Keywords

  • At-fault drivers
  • Crashes
  • Driver licensing
  • Repeat offenses

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Safety, Risk, Reliability and Quality
  • Law
  • Human Factors and Ergonomics

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