Automation Reliability and Other Contextual Factors in Multi-UAV Operator Selection

Abstract

Multi-unmanned air vehicle (UAV) operation requires a unique set of skills and high demand for new operators requires selection from populations without previous flight training. To support developing criteria for multi-UAV operator selection, the present study investigated the role of multiple individual difference factors in performance under different multi-UAV specific contexts. Specifically, we compared performance under fatigue using a high- and low-reliability automated aid. Accuracy on surveillance tasks, as well as reliance on automation were assessed. Video gaming expertise was associated with reduced stress and less reliance with a low-reliability automated aid. Distress was the most robust predictor of performance accuracy, but high distress was harmful only when reliability was low. Personality correlates of performance varied with both automation reliability and gender. Our findings suggest that multi-UAV operator selection should take into account the reliability of the automated systems.