Visual Entropy Metric Reveals Differences in Drivers' Eye Gaze Complexity across Variations in Age and Subsidiary Task Load

Abstract

The purpose of this study was to evaluate the global complexity of drivers' eye movement behavior as a function of advanced adult age and variations in information processing resource demands. Global complexity was operationalized using an information theory metric commonly known as entropy. Fourteen young (mean age = 27) and 14 older (mean age = 75) participants drove on a 2-lane rural highway while simultaneously performing a subsidiary loading task designed to increase cognitive demands drawing upon either verbal-memory resources or visual-spatial resources (within the context of Wickens' (1980) multiple resource model of attention). Compared to traditional distributional measures of eye movement behavior such as mean saccade amplitude and fixation dwell time, the entropy measure of global complexity was better able to distinguish between young and old drivers as well as between baseline driving and conditions of high visual-spatial task load. These results strongly suggest that global measures of eye movement behavior hold significant potential for increasing our understanding of the interacting effects of normal adult aging and task-induced cognitive demands within the context of real-world driving.