Estimating cognitive load using remote eye tracking in a driving simulator 论文

摘要

We report on the results of a study in which pairs of subjects were involved in spoken dialogues and one of the subjects also operat-ed a simulated vehicle. We estimated the driver’s cognitive load based on pupil size measurements from a remote eye tracker. We compared the cognitive load estimates based on the physiological pupillometric data and driving performance data. The physiologi-cal and performance measures show high correspondence suggest-ing that remote eye tracking might provide reliable driver cogni-tive load estimation, especially in simulators. We also introduced a new pupillometric cognitive load measure that shows promise in tracking cognitive load changes on time scales of several seconds.