Predicting Motor Vehicle Collisions in a Driving Simulator in Young Adults Using the Useful Field of View Assessment

Traffic Inj Prev. 2015;16(8):818-23. doi: 10.1080/15389588.2015.1027339. Epub 2015 Mar 20.

Abstract

Objective: Being involved in motor vehicle collisions is the leading cause of death in 1- to 34-year-olds, and risk is particularly high in young adults. The Useful Field of View (UFOV) task, a cognitive measure of processing speed, divided attention, and selective attention, has been shown to be predictive of motor vehicle collisions in older adults, but its use as a predictor of driving performance in a young adult population has not been investigated. The present study examined whether UFOV was a predictive measure of motor vehicle collisions in a driving simulator in a young adult population.

Method: The 3-subtest version of UFOV (lower scores measured in milliseconds indicate better performance) was administered to 60 college students. Participants also completed an 11-mile simulated drive to provide driving performance metrics.

Results: Findings suggested that subtests 1 and 2 suffered from a ceiling effect. UFOV subtest 3 significantly predicted collisions in the simulated drive. Each 30 ms slower on the subtest was associated with nearly a 10% increase in the risk of a simulated collision. Post hoc analyses revealed a small partially mediating effect of subtest 3 on the relationship between driving experience and collisions.

Conclusion: The selective attention component of UFOV subtest 3 may be a predictive measure of crash involvement in a young adult population. Improvements in selective attention may be the underlying mechanism in how driving experience improves driving performance.

Keywords: driving experience; driving simulator; selective attention; top-down processing; useful field of view.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Adolescent
  • Adult
  • Attention
  • Automobile Driving / psychology*
  • Computer Simulation
  • Female
  • Humans
  • Male
  • Risk Assessment / methods
  • Task Performance and Analysis
  • Visual Fields*
  • Young Adult