Abstract
Operators of military Unmanned Aerial Vehicles (UAVs) work in dynamic environments, where they must use shared command and control (C2) maps to orient, plan and perform their work. The map is overloaded with information that is irrelevant to their immediate operational mission. This clutter may harm their situation awareness (SA) and increase workload. An intelligent and dynamic filter algorithm has been developed to reduce the clutter by filtering information items on the map based on the environmental context. Implementing it raises questions regarding the update rate of the map filter. Two update rates were tested and their effect on UAV operators' workload and SA was examined empirically. Operators benefited from higher update rates in terms of SA and workload. This is an important step towards the development of the algorithm, which conceptualizes how intelligent algorithms can be used to improve human operators' interaction with autonomous systems.
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