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

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