What the eyes reveal: Investigating the detection of automation failures.

In order to detect automation failures in a timely manner, operators are required to monitor automated systems efficiently. The present study analysed eye movements to predict whether or not participants could detect an automation failure. Eye movements were recorded whilst 101 participants were monitoring an automated system where automation failures occurred at irregular intervals.

Eye-tracking measurements and their link to a normative model of monitoring behaviour.

Unlabelled: Increasing automation necessitates operators monitoring appropriately (OMA) and raises the question of how to identify them in future selections. A normative model was developed providing criteria for the identification of OMA. According to this model, the monitoring process comprises distinct monitoring phases (orientation, anticipation, detection and recheck) in which attention should be focused on relevant areas.