Detecting drivers' cognitive load from saccadic intrusion

In this paper, we have explored use of Saccadic Intrusion to detect drivers' cognitive load and instantaneous perception of developing road hazards. Saccadic Intrusion is a type of eye gaze movement which was earlier found to be related to change in cognitive load. We have developed an algorithm to detect saccadic intrusion from a commercially available low-cost eye gaze tracker and conducted four user studies involving a driving simulator and cognitive and hazard perception tests. Our results show that average velocities of saccadic intrusion increases with increase in cognitive load and recording saccadic intrusion and eye blinks for 6 s duration can predict drivers' instantaneous perception of developing road hazards. (C) 2018 Elsevier Ltd. All rights reserved.