The current study evaluatedthe utility of electroencephalography (EEG) cognitive state to track workload and engagement changes in air traffic control students of differing experience during a Terminal Radar Approach Control (TRACON) scenario. EEG recordings were collected from 47 air traffic control students (27 with high and 20 with low experience) during a five phase TRACON scenario. The scenario fluctuated in the number of aircraft released per phase and the presence or absence of uncontrolled departures/arrivals. EEG workload probabilities werehigher during the phase with uncontrolled departures/arrivals and maximum number of aircraft compared to phases with no uncontrolled arrivals/departures and fewer aircraft. Metrics of engagement did not vary throughout the scenario. Trends toward experience level differences in EEG metrics were observed, with less experienced students displaying slightly higher workload and engagement probabilities compared to their more experienced counterparts. Both experience groups madethe most errorsafter the highest workload period.
Bernhardt, K. A.,
Ferraro, F. R.,
& Petros, T.
(2017). Tracking Workload and Engagement in Air Traffic Control Students Using Electroencephalography Cognitive State Metrics. 19th International Symposium on Aviation Psychology, 518-523.