USING TRAFFIC CONVICTION CORRELATES TO IDENTIFY HIGH ACCIDENT-RISK DRIVERS

The California Department of Motor Vehicles, in its attempt to protect the public from drivers who represent unacceptably high accident risks, has developed a strategy for identifying high-risk drivers. One such system is the department's negligent operator point system. This study explores the viability of predicting accidents from equations constructed to predict convictions for the general driving population. The results suggest that identification of future accident-involved drivers can be improved by either of two approaches. The first is to construct equations based on a combination of prior accidents and citations. The second alternative involves multivariate approach in which the prediction equation consists of a two-variable vector of subsequent citations and accidents.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Corporate Authors:

  Elsevier

  The Boulevard, Langford Lane
  Kidlington, Oxford  United Kingdom  OX5 1GB
• Authors:
  • Gebers, M A
  • Peck, R C
• Publication Date: 2003-11

Language

• English

Media Info

• Features: References; Tables;
• Pagination: p. 903-912
• Serial:
  • Accident Analysis & Prevention
  • Volume: 35
  • Issue Number: 6
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Crash rates; Crash risk forecasting; High risk drivers; Multivariate analysis; Point demerit systems; Regression analysis
• Geographic Terms: California
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 00963976
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Oct 2 2003 12:00AM