Performance modeling of agent-aided operator-interface interaction for the control of multiple UAVs

The control of multiple uninhabited air vehicles (UAVs) is operator intensive and can involve high levels of workload. Feedback from operators indicates that improvements in operator interfaces would reap significant gains in system performance and effectiveness. Incorporating automation agents in UAV control stations has been proposed as a solution to reduce workload and improve overall human-machine performance. This research investigated the efficacy of agent-aided operator interfaces in a scenario that involved multiple UAVs with the interfaces modeled as part of the UAV tactical workstations of a maritime patrol aircraft. A performance model was developed to compare the difference between mission activities with and without agent aids that was reflected in task conflict frequency, number of ongoing tasks, and task completion time. The simulation results revealed that agent-aided interfaces permitted operators to continue working under high time pressure, resulting in critical tasks being achieved in reduced time.