Abstract
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.
Highlights
The continuing proliferation in the use of unmanned aerial systems (UASs) in both civil and military operations has presented a multitude of human factors challenges, including assessing the cognitive capabilities of one operator to simultaneously supervise and control multiple platforms, evaluating the advantages and disadvantages of an individual operator vs. a team, and finding meaningful ways to organize and present data
Our studies focused on the allocation among operators in one team while conducting a single scenario, one can start looking at the broader picture—how to break operations into teams, how to assign and allocate the correct number of assets and operators to each one of the teams, and how to coordinate among teams of MOMU operators
We were able to show via Study 1 that a single operator can achieve even a higher ratio of operation between 15 and 17 systems, but only on a limited task or mission component (e.g., health monitoring)
Summary
The continuing proliferation in the use of UASs in both civil and military operations has presented a multitude of human factors challenges, including assessing the cognitive capabilities of one operator to simultaneously supervise and control multiple platforms, evaluating the advantages and disadvantages of an individual operator vs. a team, and finding meaningful ways to organize and present data. Underlying many of these challenges is the issue of how automation capabilities can best be utilized to assist human operators in handling increasing complexity and workload (Fern et al, 2011). The focus on operator-UAS ratio corroborated even more in light of the US Office of the Secretary Defense Roadmap for unmanned aircraft systems (UASs: 2005-2030), which delineates the need to investigate the “appropriate conditions and requirements under which a single pilot would be allowed to control multiple airborne UA [unmanned aircraft] simultaneously.” Since till today the question of how many UASs or UAVs (Unmanned Aerial Vehicles) can one operator control or supervise has become a vital question that many researchers try to answer (e.g., Chen et al, 2013; Goodrich and Cummings, 2014)
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