Telerobotics, automation, and human supervisory control
Telerobotics, automation, and human supervisory control
Agents that reduce work and information overload
Communications of the ACM
A model for types and levels of human interaction with automation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Human Responsibility for Autonomous Agents
IEEE Intelligent Systems
Cognitively-engineered multisensor image fusion for military applications
Information Fusion
Multiple robot / single human interaction: effects on perceived workload
Behaviour & Information Technology
Journal of Intelligent and Robotic Systems
Managing workload in human-robot interaction: A review of empirical studies
Computers in Human Behavior
Supporting intelligent and trustworthy maritime path planning decisions
International Journal of Human-Computer Studies
On the architecture of a human-centered CAD agent system
Computer-Aided Design
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Remotely operated vehicles (ROVs) are vehicular robotic systems that are teleoperated by a geographically separated user. Advances in computing technology have enabled ROV operators to manage multiple ROVs by means of supervisory control techniques. The challenge of incorporating telepresence in any one vehicle is replaced by the need to keep the human "in the loop" of the activities of all vehicles. An evaluation was conducted to compare the effects of automation level and decision-aid fidelity on the number of simulated remotely operated vehicles that could be successfully controlled by a single operator during a target acquisition task. The specific ROVs instantiated for the study were unmanned air vehicles (UAVs). Levels of automation (LOAs) included manual control management-by-consent, and management-by-exception. Levels of decision-aid fidelity (100% correct and 95% correct) were achieved by intentionally injecting error into the decision-aiding capabilities of the simulation. Additionally, the number of UAVs to be controlled varied (one, two, and four vehicles). Twelve participants acted as UAV operators. A mixed-subject design was utilized (with decision-aid fidelity as the between-subjects factor), and participants were not informed of decision-aid fidelity prior to data collection. Dependent variables included mission efficiency, percentage correct detection of incorrect decision aids. workload and situation awareness ratings, and trust in automation ratings. Results indicate that an automation level incorporating management-by-consent had some clear performance advantages over the more autonomous (management-by-exception) and less autonomous (manual control) levels of automation. However, automation level interacted with the other factors for subjective measures of workload, situation awareness, and trust. Additionally, although a 3D perspective view of the mission scene was always available, it was used only during low-workload periods and did not appear to improve the operator's sense of presence. The implications for ROV interface design are discussed, and future research directions are proposed.