Estimating cognitive load using remote eye tracking in a driving simulator

  • Authors:
  • Oskar Palinko;Andrew L. Kun;Alexander Shyrokov;Peter Heeman

  • Affiliations:
  • University of New Hampshire;University of New Hampshire;University of New Hampshire;Oregon Health & Science University

  • Venue:
  • Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
  • Year:
  • 2010

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Abstract

We report on the results of a study in which pairs of subjects were involved in spoken dialogues and one of the subjects also operated 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 physiological and performance measures show high correspondence suggesting that remote eye tracking might provide reliable driver cognitive 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.