Overload and automation-dependence in a multi-UAS simulation: Task demand and individual difference factors.

Abstract

Future unmanned aerial systems (UAS) operations will require control of multiple vehicles. Operators are vulnerable to cognitive overload, despite support from system automation. This study tested whether attentional resource theory predicts impacts of cognitive demands on performance measures, including automation-dependence and stress. It also investigated individual differences in response to demands. One-hundred and 1 university student participants performed a multi-UAS simulation mission incorporating 2 surveillance tasks. Cognitive demands and level of automation (LOA) of key tasks were manipulated between-subjects. Results were partially consistent with predictions. Higher task demands impaired performance and elevated distress and workload, as expected. Higher LOA produced greater dependence on automation, but failed to mitigate workload. It was expected that, as the automation was quite reliable, participants would attempt to conserve resources by depending more on automation under high demand. In fact, the opposite tendency was observed. Individuals high in conscientiousness were especially likely to override the automation under high demand, apparently taking charge personally. Neuroticism and distress were also associated with performance, but results did not fit a resource theory interpretation. Thus, understanding impacts of overload in the multi-UAS context requires understanding operator strategy as well as resource insufficiency. Findings have implications for system design, and operator selection and training. (PsycInfo Database Record (c) 2020 APA, all rights reserved).