The sensitivity of different methodologies for characterizing drivers' gaze concentration under increased cognitive demand

An observer's visual scanning behavior tends to narrow during periods of increased cognitive demand. Thus, measures of gaze concentration have become a popular method of gauging cognitive demand, but the consensus on the best method for computing gaze concentration is still evolving. This analysis considers measures of gaze concentration while driving an on-road vehicle, with and without two types of secondary cognitive demand (auditory and visuospatial working memory). We compare the advantages and disadvantages of several different methods for measuring gaze concentration, as well as a direct statistical comparison of their relative sensitivities. We find that several methods produce similar effect sizes, and that these are consistent across task types. Horizontal gaze dispersion, as measured from the standard deviation of horizontal gaze position, attained the largest effect size, indicating that it is the most sensitive to changes in gaze concentration under cognitive demand, while also being one of the simpler metrics to calculate. Our results show that complex eye tracking data sets from applied, ecologically valid situations such as on-road driving can be analyzed effectively with maximal sensitivity and minimal analytical burden to produce a robust measure of a driver's general allocation of attention. (C) 2014 Elsevier Ltd. All rights reserved.