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UAS Pilot Assessments of Display and Alerting for the Next Generation Airborne Collision Avoidance System XuUnmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.
Document ID
20205008634
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Casey L Smith
(Ames Research Center Mountain View, California, United States)
R Conrad Rorie
(Ames Research Center Mountain View, California, United States)
Kevin J Monk
(Ames Research Center Mountain View, California, United States)
Jillian Keeler
(Ames Research Center Mountain View, California, United States)
Garrett G Sadler
(San Jose State University San Jose, California, United States)
Date Acquired
October 13, 2020
Subject Category
Air Transportation And Safety
Meeting Information
Meeting: Human Factors and Ergonomics Society Conference 2020
Location: Virtual
Country: US
Start Date: October 5, 2020
End Date: October 9, 2020
Sponsors: Human Factors and Ergonomics Society
Funding Number(s)
WBS: 425425.04.02.01.01
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Peer Committee
Keywords
unmanned aircraft systems
detect and avoid
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