EMPIRICAL METHODS IN SUPPORT OF CRASH AVOIDANCE MODEL BUILDING AND BENEFITS ESTIMATION

This paper describes the complex issues associated with proactive prediction of the safety impact of in-vehicle ITS and discusses two techniques for potentially successfully estimating such impacts. Specifically, indirect measurement of safety via promising surrogates, using near crashes and driver errors, as a means to predict crash rate is discussed. This discussion addresses the distinction between near misses and driver errors, and methods fir data collection and analysis. The second method discussed is the collection of empirical, instrumented vehicle data for the specific purpose of providing input into models which estimate safety impacts. This concept, the collection of basic driver behavior and performance data in direct support of providing input to models is discussed by way of example.

  • Availability:
  • Corporate Authors:

    ITS America

    1100 17th Street, NW, 12th Floor
    Washington, DC  United States  20036
  • Authors:
    • Dingus, T A
    • Hetrick, S
    • Mollenhauer, M
  • Publication Date: 1999

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 00779995
  • Record Type: Publication
  • Files: TRIS, ATRI
  • Created Date: Dec 19 1999 12:00AM