학술논문

Human-Autonomy Teaming Assistant to Support Small Uncrewed Aircraft Systems for Wildland Firefighting Operations
Document Type
Conference
Source
2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS) Human-Machine Systems (ICHMS), 2024 IEEE 4th International Conference on. :1-8 May, 2024
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Automation
Surveillance
Human-machine systems
Contingency management
Safety management
Autonomous aerial vehicles
Control systems
Human-Autonomy Teaming (HAT)
Automated Assistant
In-time Aviation Safety Management System (IASMS)
Wildland Firefighting
Multi-vehicle Control
Ground Control Station (GCS)
Mission Risk
Workload
Situation Awareness
Trust
Language
Abstract
An exploratory human-in-the-loop simulation was conducted to investigate and characterize a Human-Autonomy Teaming (HAT) Assistant to support a remote operator of multiple small Uncrewed Aircraft Systems (sUAS) using a ground control station (GCS) in the context of a wildland fire surveillance mission. Operator performance using the GCS with the HAT Assistant (Assisted Mode) was compared to operator performance using the GCS without the HAT Assistant (Unassisted Mode) during two types of contingency-event scenarios (Low and High Complexity). In the Assisted Mode, the HAT Assistant provided updates to the level of risk to the mission along with recommendations for risk mitigation, which were not provided in the Unassisted Mode. No significant differences in objective performance and subjective ratings of workload, situation awareness, and trust in automation between the Assisted and Unassisted Modes were detected, however there were indications that participants preferred the Assisted GCS over the Unassisted GCS and directions for further development were explored. Additional work is necessary to further refine the HAT Assistant and better characterize its effects on remote operator performance while managing multiple sUAS assets. Future work is recommended to optimize the implementation of an assistant to support operator performance during different missions and across vehicle classes.

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