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

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.

21st International Symposium on Aviation Psychology

“…Operators that control UAS are responsible for providing lower-level control inputs directly to UAS flight, navigation, and payload sub-systems to achieve the flight and mission objectives. In contrast, when operators perform supervision of UAS, the responsibility for lowerlevel control is delegated to the UAS automation (Porat et al, 2016). The operator becomes responsible for providing higher level control actions to the UAS decision making automation entity.…”

“…The operator becomes responsible for providing higher level control actions to the UAS decision making automation entity. In examples of supervisory control in several multi-UAS implementations, the operator will input mission planning parameters into the autonomy so that it can develop courses of actions and present them to the operator for review (Porat et al, 2016).…”

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

“…Shorter message time durations lead to wave glider pilots spending less time worrying about closing communication links while executing other tasks. Autonomous behaviors exhibiting high performance in executing shorter message durations enable increased usability of the system due to a reduction in mental workload for the pilot 54,55 . Pilots can override the autonomous navigation feature for any glider to assist with forming a communications chain between the two nodes (flags) for expediting message traffic.…”

Remote supervision of autonomous agricultural machines: Concepts and feasibility

“…However, the human is still included in the control loop to perform high-level cognitive tasks like mission and system monitoring to ensure safety and overall efficiency of the operation (Ruff et al 2002;Cummings 2015). Currently, one flight operator can supervise multiple drones due to their autonomous capability (Porat et al 2016) 2013) developed a GPRS-based system used to monitor real-time crop yield remotely. Also, the machinemachine interaction (machine synchronize) feature in tractors and combines is another example of remote subsystem supervision.…”