Principal Investigator Charles Oman
Co-investigator Andrew Liu
his research investigates the effects of prolonged low workload on operator performance in the context of controlling a network of unmanned vehicles (UxVs) with the assistance of an autonomous planner. In addition, this research focuses on assessing the physical, social, and cognitive coping mechanisms that operators rely upon during prolonged low workload missions. Using experimental data gathered in long duration, low task load multiple unmanned vehicle environments, we are developing a model that accounts for boredom and spikes in workload in order to predict operator performance and identify possible opportunities for technological interventions. This research will help in the design of smart decision support tools that can increase vigilance and performance of operators in supervisory control domains with low workload. This research is sponsored by the Office of Naval Research.