Automation-Level Transference Effects in Simulated Multiple Unmanned Aerial Vehicle Control

Abstract

Supervisory control of multiple unmanned aerial vehicles (UAVs) raises many questions concerning the balance of system autonomy with human interaction for effective operator situation awareness and system performance. The reported experiment used a UAV simulation environment to evaluate two applications of autonomy levels across two primary control tasks: allocation (assignment of sensor tasks to vehicles) and router (determining vehicles’ flight plans). In one application, the autonomy level was the same across these two tasks. In the other, the autonomy levels differed, one of the two tasks being more automated than the other. Trials also involved completion of other mission-related secondary tasks as participants supervised three UAVs. The results showed that performance on both the primary tasks and many secondary tasks was better when the level of automation was the same across the two sequential primary tasks. These findings suggest that having the level of automation similar across closely coupled tasks reduces mode awareness problems, which can negate the intended benefits of a fine-grained application of automation. Several research issues are identified to further explore the impact of automation-level transference in supervisory control applications involving the application of automation across numerous tasks.