Workload, Situation Awareness, and Teaming Issues for UAV/UCAV Operations

Abstract

A new partnership is forming between humans and uninhabited aircraft. To augment the abilities of military forces on the ground and in the air, the US Armed Forces have developed several Unmanned Aerial Vehicles (UAVs) to work in conjunction with human pilots and enhance surveillance and combat capabilities. Even with no onboard pilot, unmanned aerial vehicles (UAVs) and combat-tailored versions (UCAVs) rely on proficient human operators on the ground for proper guidance and munitions deployment. For this reason, system designers must consider several key human factors issues in the development of functional UAV/UCAV systems. This work addresses three of these issues: workload, situation awareness, and teaming concerns. Recommendations to maximize operator efficacy, based on findings from human factors and ergonomics research, are presented as well as implications for training.

Human Factors Considerations in Migration of Unmanned Aircraft System (UAS) Operator Control

“…Given the massive amounts of information currently downlinked from UASs 3 2 and the information processing constraints imposed by the sequential decision-making of human operators, 20 it is key to distribute this information so it can be more efficiently processed for mission accomplishment. 32 This point was highlighted by a study of human systems integration (HSI) issues in military UAS mishaps which found an association between failures in the cognitive domain and operator errors. 5 3 Beyond the issue of information processing, UASs offer the opportunity to employ task specialization beyond the level hereto seen in manned aircraft.…”

“…Such methods have been used successfully in the U.S. space program. 32 Functional specialization could also be utilized in non-emergent, nominal situations to optimize the central role of the human decision-maker within the system. In traditional manned combat aircraft, the pilot has the responsibility to authenticate targets and trigger weapons because they are presumed to be in the best position to assess the situation and make' timely decisions.…”

Supervision of Autonomous Vehicles: Mutual Modeling and Interaction Management

“…time pressure); · The attention of the operator (and the associated workload) is split between the two activities. As we consider that interaction is subordinated to mission achievement and that the operator has finite cognitive resources, interaction complexity should vary depending on the complexity involved by the mission [1]. Indeed, the collaborative effort for a basic activity (i.e.…”

“…In similar ways to Human interaction, it becomes necessary to manage turn-taking, interruptions, task priorities and so forth; · Semantic bridge, as interactions within the UVS become more abstract (higher level) than the current remote operation, some kind of translation service becomes necessary. There is a need to convert operational commands from the operator side to machine-understandable instructions, for instance if 1 For the sake of simplicity we will consider only UVSs with a single GCS and a single operator in the scope of this paper Figure 1. Illustration of the concept of semantic bridge on multi-UV system.…”

“…But as UVSs evolve, the interaction workload will rise as the operator will have to switch between several vehicles, streams of data, decision support systems, and so on. As Mouloua et al have pointed out [1], the complexity of the interaction mechanisms between the operators and the system, and the complexity of the mission should vary in opposite ways. If mission complexity goes up (higher workload), interaction complexity should go down (simpler interaction with the system).…”