Adaptive Levels of Automation for UAV Supervisory Control

Several unmanned air vehicle (UAV) programs are investigating ways of automating UAV control system functions to increase the number of aircraft controlled by a single operator. However, research indicates that implementing high-levels of automation and putting the human operator in a passive monitoring role can leave the operator out of the loop and unable to intervene effectively when required to take control of system tasks. Also, significant workload increases can occur as the human assumes system control tasks. To counter these problems, a human-centered approach to automation has been proposed, in which the human and the machine work together as a system. The goal is to keep the human in the loop by having the human perform meaningful tasks and to keep the workload manageable at all times. Two complimentary approaches have been developed that address the OOTL performance problem: Level of Automation and Adaptive Automation. Tools are needed to investigate the feasibility of implementing adaptive levels of autonomy in a UAV control station context. The goal of this SBIR program is to devise an architecture suitable for a multi-UAV control station simulation test-bed that will allow testing and evaluating different methods for adaptive levels of autonomy.