Computational Modeling of Age-Differences In a Visually Demanding Driving Task: Vehicle Detection
Abstract
While older adults experience fewer automobile accidents than the rest of the population their crash rate per mile driven parallels that of new drivers. Many accidents can be linked to visual detection problems, e.g., not seeing a car approaching at an intersection. The visual task of detecting an approaching vehicle was modeled with a neuro-physiologically motivated computational simulation of early vision, the National Automotive Center - Visual Perception Model (NAC-VPM). The scientific literature documenting age-related changes in early vision was reviewed in relationship to the components of the N AC-VPM, and the model was fit to lab data from older observers. The model fit the older observers' data adequately, particularly when the data was partitioned into subsets based on viewing conditions. Model fits were compared to calibrations based on younger observers' data. The calibrations based on older observers were substantially different from calibrations based on younger observers, indicating that the model can capture age-related differences in visual perception. When calibrated to the older adults' data, the model successfully predicted conditions under which vehicle detection was particularly difficult for older adults.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 07, 1997
- Accession Number
- ADA600550
Entities
People
- Darryl Byrk
- Euijung Sohn
- Gary Witus
- Grant Gerhart
- R. D. Ellis
- Richard Goetz
- Thomas Meitzler
Organizations
- United States Army Tank Automotive Research, Development and Engineering Center