Computational modeling of age-differences in a visually demanding driving task: vehicle detection

Abstract

The visual task of detecting an approaching vehicle was modeled with a neurophysiologically motivated computational vision model, 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 NAC-VPM, and the model was fit to laboratory 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.