@inproceedings{1cd6dd0b55014c879b8a6f2f8997907c,
title = "Towards enhancement of unmanned aerial vehicle (UAV) operators' situation awareness: How often should their command and control map be updated",
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.",
keywords = "Command and control, Machine learning, Situation awareness, Unmanned aerial vehicle, Workload",
author = "Yuval Zak and Yisrael Parmet and Tal Oron-Gilad",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020 ; Conference date: 23-03-2020 Through 26-03-2020",
year = "2020",
month = mar,
day = "23",
doi = "10.1145/3371382.3378237",
language = "English",
series = "ACM/IEEE International Conference on Human-Robot Interaction",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "538--540",
booktitle = "HRI 2020 - Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction",
address = "United States",
}