Related Experiment Video
Updated: Feb 28, 2026
Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
Published on: September 18, 2012
Visual Sensory and Visual-Cognitive Function and Rate of Crash and Near-Crash Involvement Among Older Drivers Using
Carrie Huisingh1, Emily B Levitan2, Marguerite R Irvin2
1Department of Ophthalmology, University of Alabama at Birmingham, Birmingham, Alabama, United States.
Purpose:
An innovative methodology using naturalistic driving data was used to examine the association between visual sensory and visual-cognitive function and rates of future crash or near-crash involvement among older drivers.
Methods:
The Strategic Highway Research Program (SHRP2) Naturalistic Driving Study was used for this prospective analysis. The sample consisted of N = 659 drivers aged ≥70 years and study participation lasted 1 or 2 years for most participants. Distance and near visual acuity, contrast sensitivity, peripheral vision, visual processing speed, and visuospatial skills were assessed at baseline. Crash and near-crash involvement were based on video recordings and vehicle sensors. Poisson regression models were used to generate crude and adjusted rate ratios (RRs) and 95% confidence intervals, while accounting for person-miles of travel.
Results:
After adjustment, severe impairment of the useful field of view (RR = 1.33) was associated with an increased rate of near-crash involvement. Crash, severe crash, and at-fault crash involvement were associated with impaired contrast sensitivity in the worse eye (RRs = 1.38, 1.54, and 1.44, respectively) and far peripheral field loss in both eyes (RRs = 1.74, 2.32, and 1.73, respectively).
Conclusions:
Naturalistic driving data suggest that contrast sensitivity in the worse eye and far peripheral field loss in both eyes elevate the rates of crash involvement, and impaired visual processing speed elevates rates of near-crash involvement among older drivers. Naturalistic driving data may ultimately be critical for understanding the relationship between vision and driving safety.
