Facilitating the Work of Unmanned Aerial Vehicle Operators Using Artificial Intelligence: An Intelligent Filter for Command-and-Control Maps to Reduce Cognitive Workload.

Journal: Human factors

PMID: 35392697

Abstract

OBJECTIVE: Evaluating the ability of a Gibsonian-inspired artificial intelligence (AI) algorithm to reduce the cognitive workloads of military Unmanned Aerial Vehicle (UAV) operators.

Authors

Yuval Zak

Ben-Gurion University of the Negev, Beersheva, Israel.
Yisrael Parmet

Dept. of Industrial Engineering & Management, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Tal Oron-Gilad

Ben-Gurion University of the Negev, Beersheva, Israel.

Keywords

Aircraft Artificial Intelligence Awareness Humans Unmanned Aerial Devices Workload

External Resources

View on PubMed Access via DOI PubMed (35392697)

Facilitating the Work of Unmanned Aerial Vehicle Operators Using Artificial Intelligence: An Intelligent Filter for Command-and-Control Maps to Reduce Cognitive Workload.

Abstract

Authors

Keywords

External Resources

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