TY - GEN
T1 - Towards the development of a display filter algorithm for command and control (C2) maps for operators of unmanned aerial systems
AU - Zak, Yuval
AU - Oron-Gilad, Tal
AU - Parmet, Yisrael
N1 - Publisher Copyright:
© 2019 Copyright is held by the owner/author(s).
PY - 2019/5/2
Y1 - 2019/5/2
N2 - Operators of military unmanned aerial vehicles (UAVs) work in highly dynamic environments. They have to complete numerous tasks, sometimes simultaneously, while maintaining high situational awareness (SA) and making rapid decisions. Their main focus is on mission management via the UAV's payload, yet, they continuously interact with the command and control (C2) map to obtain SA and make decisions. C2 maps, shared among forces in the environment, are cluttered and overloaded with information. We aim to develop a map display machine-learning based spatial-temporal algorithm that will identify the most relevant information items to the UAV operator and deliver the right visualized information on the C2 map at the right timing. Towards the algorithm development, experiments for collecting user-based importance data were conducted and analysed. For this, a designated UAV C2 Experimental System (UCES) has been developed. Results show high feasibility for the prediction model, allowing to move forward with the following steps of the algorithm development.
AB - Operators of military unmanned aerial vehicles (UAVs) work in highly dynamic environments. They have to complete numerous tasks, sometimes simultaneously, while maintaining high situational awareness (SA) and making rapid decisions. Their main focus is on mission management via the UAV's payload, yet, they continuously interact with the command and control (C2) map to obtain SA and make decisions. C2 maps, shared among forces in the environment, are cluttered and overloaded with information. We aim to develop a map display machine-learning based spatial-temporal algorithm that will identify the most relevant information items to the UAV operator and deliver the right visualized information on the C2 map at the right timing. Towards the algorithm development, experiments for collecting user-based importance data were conducted and analysed. For this, a designated UAV C2 Experimental System (UCES) has been developed. Results show high feasibility for the prediction model, allowing to move forward with the following steps of the algorithm development.
KW - Command and control
KW - Machine learning
KW - Situation awareness
KW - Spatial
KW - Temporal analysis
KW - Unmanned aerial systems
UR - http://www.scopus.com/inward/record.url?scp=85067295438&partnerID=8YFLogxK
U2 - 10.1145/3290607.3312848
DO - 10.1145/3290607.3312848
M3 - Conference contribution
AN - SCOPUS:85067295438
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019
Y2 - 4 May 2019 through 9 May 2019
ER -