DRIVER DATA AS A PREDICTOR OF CRASH INVOLVEMENT: A COMPARATIVE ANALYSIS OF HEAVY TRUCK OPERATORS VERSUS OTHER DRIVERS

Data from the National Accident Sampling System (NASS) are used to construct linear regression models with prior recorded accidents as the dependent variable. Independent variables investigated include driver age, miles of driving experience, prior moving violation convictions of several types, and driver training history. The distribution of the NASS data were found to be generally consistent with previously reported research. The results of univariate and multivariate analyses demonstrate that heavy truck drivers form a discrete subset of all accident-involved drivers, whose accident history is more reliably predicted by a more parsimonious model as compared to drivers of other vehicle types.

  • Supplemental Notes:
    • Proceedings of the 28th Annual Conference, Denver, Colorado, October 8-10, 1984.
  • Corporate Authors:

    American Association for Automotive Medicine

    P.O. Box 222
    Morton Grove, IL  United States  60053
  • Authors:
    • Mitter, E L
    • Vilardo, F J
  • Conference:
  • Publication Date: 1984

Media Info

  • Features: References; Tables;
  • Pagination: p. 111-121
  • Monograph Title: PROCEEDINGS OF THE TWENTY-EIGHTH ANNUAL CONFERENCE, DENVER, COLORADO, USA, OCTOBER 8-10, 1984. AMERICAN ASSOCIATION FOR AUTOMOTIVE MEDICINE

Subject/Index Terms

Filing Info

  • Accession Number: 00395800
  • Record Type: Publication
  • Source Agency: National Highway Traffic Safety Administration
  • Files: HSL, TRIS, USDOT
  • Created Date: Jun 30 1985 12:00AM