Assessing Workload with Low Cost Eye Tracking During a Supervisory Control Task

Abstract

Automation is fundamentally shifting the tasks that many humans perform. Unmanned aerial vehicles, which originally had stick and rudder control, now rely on waypoint based navigation. The future operators of these systems are increasingly becoming supervisors of automated systems and their primary role is shifting to simply monitoring those systems. This represents a challenge for assessing human performance since there is limited interaction with the systems. Low cost eye tracking, specifically measures of pupil diameter and gaze dispersion, may serve as a means of assessing operator engagement and workload while using these automated systems. The present study investigated the use of a low cost eye tracking system to differentiate low and high workload during an unmanned vehicle supervisory control task. The results indicated that pupil diameter significantly increased during periods of high workload; however, there was no change in the distribution of eye gazes. These results suggest that low cost eye tracking may be an effective means of determining an operator’s workload in an automated environment, however more research is needed on the relationship between gaze distribution, workload and performance within a supervisory control environment.