Crashes and crash-surrogate events: Exploratory modeling with naturalistic driving data

Kun-Feng Wu*, Paul P. Jovanis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

59 Scopus citations

Abstract

There is a need to extend and refine the use of crash surrogates to enhance safety analyses. This is particularly true given opportunities for data collection presented by naturalistic driving studies. This paper connects the original research on traffic conflicts to the contemporary literature concerning crash surrogates using the crash-to-surrogate ratio, π. A conceptual structure is developed in which the ratio can be estimated using either a Logit or Probit formulation which captures context and event variables as predictors in the model specification. This allows the expansion of the crash-to-surrogate concept beyond traffic conflicts to many contexts and crash types. The structure is tested using naturalistic driving data from a study conducted in the United States (Dingus et al.; 2005). While the sample size is limited (13 crashes and 38 near crashes), there is reasonable correspondence between predicted and observed crash frequencies using a Logit model formulation. The paper concludes with a summary of empirical results and suggestions for future research.

Original languageEnglish
Pages (from-to)507-516
Number of pages10
JournalAccident Analysis and Prevention
Volume45
DOIs
StatePublished - 1 Mar 2012

Keywords

  • Crash surrogate
  • Naturalistic driving study data analysis
  • Traffic safety

Fingerprint Dive into the research topics of 'Crashes and crash-surrogate events: Exploratory modeling with naturalistic driving data'. Together they form a unique fingerprint.

Cite this