Experimental evaluation of tasking and teaming design patterns for human delegation of unmanned vehicles

Abstract

AbstractThis work discusses different approaches for the cooperation between humans as a supervisor and multiple unmanned vehicles (UVs). We evaluated the most promising approach experimentally with expert pilots of the German Air Force. The co-agency of humans and highly automated unmanned systems (i.e., human autonomy teaming, HAT) is described by the use of a design and description language for HAT design patterns. This design language is used to differentiate control modes for tasking, teaming, and swarming of UVs. The different control modes are then combined in a planner agent (PA) design pattern that further enables the UV guidance on scalable delegation levels from a single individual up to a team. The desired system behavior and interaction concept of the PA for these scalable delegation levels is then transferred to the domain of manned-unmanned teaming in fighter aircraft missions. To demonstrate the applicability of the system, we implemented the concept into our fast-jet simulator of the Institute of Flight Systems (IFS) and conducted an experimental campaign with expert pilots. The results of the experiment showed (1) task delegation with the PA design pattern is faster and reduces the error potential; (2) scalable delegation levels enable a pilot and situation-specific task delegation; (3) the delegation of teams is faster and reduces the error potential; however, in some situations, deeper access through the scalable delegation levels is needed; (4) the concept is intuitive and the transparency and trust in UVs and swarms were very high; and (5) the pilots could imagine operating such systems in the future. Overall speaking the presented PA design pattern is suited for the guidance of UVs and the scalable delegation levels are beneficial.