Effects of Imperfect Automation and Task Load on Human Supervision of Multiple Uninhabited Vehicles
Many current and emerging systems require human operators to supervise multiple uninhabited vehicles (UVs) with the support of automation. Automation is not 100% reliable; ergo it is important to understand the effects of automation imperfection on performance. This study investigated the effects of automation reliability on system performance with multiple UVs under different levels of task load. Twelve participants completed 12 ?missions? supervising 3 (low load) or 6 (high load) UVs. Participants used one UV to conduct Reconnaissance, Surveillance and Target Acquisition. They were assisted with an automatic target recognition (ATR) system whose reliability was low, medium, or high. Overall system performance was higher than user or ATR performance alone. The gain in system performance with the ATR was particularly effective with medium and high automation reliability. Thus, human-robot teams can benefit from imperfect automation even under high workload conditions.