Unmanned Aerial Systems (UASs) - a retrospective look at the operator/UAS ratio and its implications.

Talya Porat, Tal Oron-Gilad, Michal Rotem-Hovev, Jacob Silbiger

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


The importance of operational use of Unmanned Aerial Systems (UASs) both in combat and in civil operations has largely increased, encouraging researchers and practitioners to identify how many UASs can a single operator control, mainly in aim to reduce manpower and training costs. This concern gained even more attention following the US office of the Secretary Defense’s Roadmap for unmanned aircraft systems (UASs: 2005-2030), which emphasized 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”. Trying to answer this question, different configurations of operations, with various numbers of operators and UASs have been looked at. Today, instead of investigating the more traditional question of operator/UAS ratio, which is still being examined with regard to specific applications such as manned-unmanned teams (MUM-T), more complex operational configurations consisting of Multiple Operators and Multiple UASs (MOMU) are being evaluated and even employed in operational configurations.
In this presentation we revisit several studies that were performed, as part of a collaborative project for Ben-Gurion University, Synergy Integration and the Israeli Air Force (IAF), which demonstrate how the focus of research and practice gradually shifted from investigating how many UASs can a single operator control to distribution of work missions and assets among multiple operators. We adopt the Design Research Methodology (DRM), which emphasizes the problem-solving/performance-improving nature of an activity, enabling researchers to rapidly design, develop and test prospective improvements, deploy them and test again to continuously improve the performance of the system. The first study examined the number of Unmanned Aerial Vehicles (UAVs) one operator can monitor (health and status monitoring). The second study examined the number of UAVs one operator can control (Mission and payload management) at a single instance. Studies 3 and 4 compared performance of one operator versus a team of operators controlling the same number of vehicles.
The number of UVs that one operator can control depends on a variety of factors, such as level of automation, use of decision aids, operator’s experience, and complexity of the mission. Our results suggest that one experienced operator can monitor (system health and status) up to 15 UAVs and control up to 3 UAVs efficiently, using moderate levels of automation (i.e., the controlling task required the operator to guard a building, track a vehicle and scan a shore line).
When comparing performance of one operator to a team, we enabled only the single operator to use a toolkit containing decision-making and situation awareness supportive tools, like video feeds thumbnails (seeing feeds of other payloads) and payload coupling (the operator could slave a payload to another payload). Results showed that, when the tasks are similar or when the interest areas are overlapping, one operator may have an advantage over a team who needs to cooperate and coordinate. However, when there is little overlap between missions, a team has an advantage over the single operator. Practical implications and future directions will be discussed.
Original languageEnglish
Title of host publicationAUVSI Israel Chapter & UVID International Conference on Unmanned Vehicles
Publication statusPublished - 2015


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