Understanding crash potential associated with teen driving: Survey analysis using multivariate graphical method

J Safety Res. 2019 Sep:70:213-222. doi: 10.1016/j.jsr.2019.07.009. Epub 2019 Jul 23.

Abstract

Introduction: Teen crash involvement is usually higher than other age groups, and they are typically overrepresented in car crashes. To infer teen drivers' understanding of crash potentials (factors that are associated with crash occurrence), two sources of data are generally used: retrospective data and prospective data. Retrospective data sources contain historical crash data, which have limitations in determining teen drivers' knowledge of crash potentials. Prospective data sources, like surveys, have more potential to minimize the research gap. Prior studies have shown that teen drivers are more likely to be involved in crashes during their early driving years. Thus, there is a benefit in examining how teen drivers' understanding of crash potentials change during their transition through licensing stages (i.e., no licensure to unrestricted licensure).

Method: This study used a large set of teen driver survey data (a dataset from approximately 88,000 respondents) of Texas teens to answer the research question. Researchers provided rankings of the crash potentials by gender and licensure stages using a multivariate graphical method named taxicab correspondence analysis (TCA).

Results: The findings show that driving behavior and understanding of crash potentials differ among teens based upon various licensing stages. Practical applications: Findings from this study can help government authorities to refine policies of teen driver licensing and implement potential countermeasures for safety improvement.

Keywords: Crash potentials; Licensing; Multivariate graphical method; Taxicab correspondence analysis; Teen driver survey.

MeSH terms

  • Accidents, Traffic / prevention & control*
  • Accidents, Traffic / statistics & numerical data
  • Adolescent
  • Adolescent Behavior*
  • Adult
  • Automobile Driving* / statistics & numerical data
  • Comprehension
  • Female
  • Health Knowledge, Attitudes, Practice*
  • Humans
  • Licensure*
  • Male
  • Policy
  • Prospective Studies
  • Retrospective Studies
  • Surveys and Questionnaires
  • Texas