Supporting Dynamic Re-Planning In Multiple Uav Control: A Comparison of 3 Levels of Automation

Unmanned Aerial Vehicle (UAV) control currently requires multiple operators to supervise the mission of a single vehicle. The goal is to improve this ratio and have a single operator supervise up to 10 UAVs. Achieving this goal requires the introduction of automated systems that support multitasking and decision-making. However, there is uncertainty about the appropriate level of automation (LOA). The present study compared re-planning performance at three LOAs (manual, intermediate, full automation) of 30 participants who each supervised 9 UAVs. Full automation resulted in the best re-planning performance and matched intermediate automation in terms of target detection. The manual condition showed significantly poorer performance on these tasks, especially in high workload, but suffered the smallest loss of UAVs. Subjectively, most participants preferred intermediate automation, which they trusted more than full automation. The findings from this research help inform UAV system design and add to the knowledge base in human-automation collaboration