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Front Psychol. 2016 May 24;7:568. doi: 10.3389/fpsyg.2016.00568. eCollection 2016.

Supervising and Controlling Unmanned Systems: A Multi-Phase Study with Subject Matter Experts.

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Department of Primary Care & Public Health Sciences, King's College LondonLondon, UK; Department of Industrial Engineering and Management, Ben Gurion University of the NegevBeer Sheva, Israel.
Department of Industrial Engineering and Management, Ben Gurion University of the Negev Beer Sheva, Israel.
HFE Independent Consultant Tel-Aviv, Israel.
Synergy Integration Ltd. Tel-Aviv, Israel.


Proliferation in the use of Unmanned Aerial Systems (UASs) in civil and military operations has presented a multitude of human factors challenges; from how to bridge the gap between demand and availability of trained operators, to how to organize and present data in meaningful ways. Utilizing the Design Research Methodology (DRM), a series of closely related studies with subject matter experts (SMEs) demonstrate how the focus of research gradually shifted from "how many systems can a single operator control" to "how to distribute missions among operators and systems in an efficient way". The first set of studies aimed to explore the modal number, i.e., how many systems can a single operator supervise and control. It was found that an experienced operator can supervise up to 15 UASs efficiently using moderate levels of automation, and control (mission and payload management) up to three systems. Once this limit was reached, a single operator's performance was compared to a team controlling the same number of systems. In general, teams led to better performances. Hence, shifting design efforts toward developing tools that support teamwork environments of multiple operators with multiple UASs (MOMU). In MOMU settings, when the tasks are similar or when areas of interest overlap, one operator seems to have an advantage over a team who needs to collaborate and coordinate. However, in all other cases, a team was advantageous over a single operator. Other findings and implications, as well as future directions for research are discussed.


DSS; UAV; automation; control ratio; decision support systems; human factors; macrocognition; unmanned aerial systems

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