Abstract
With the rapid growth of Unmanned Aircraft Systems (UAS), NASA was called upon to examine crucial operational and safety concerns regarding the integration of UAS into the National Airspace System (NAS) in collaboration with the Federal Aviation Administration (FAA) and industry. Key research efforts paper focused on understanding and developing requirements for Detect and Avoid (DAA) systems and making sure they are interoperable with Collision Avoidance (CA) technologies. These requirements detail necessary performance of a DAA system designed to help the UAS pilot maintain DAA Well Clear (DWC) from intruder aircraft so that safe separation is retained. NASA Langley’s Human-in-the-Loop (HITL) simulation study known as Collision Avoidance, Self-Separation, and Alerting Times (CASSAT) addressed these DAA requirements in a two-phase study. The first phase examined eleven active air traffic controllers. The second phase, addressed in this paper, examined twelve pilots’ interactions with DAA systems at simulated UAS ground control stations (GCS).
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References
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Acknowledgements
The support of the many people involved in the conduct of this study is gratefully appreciated. Thanks are extended to Aaron Dutle, George Hagen, Cesar Muñoz, Anthony Narkawicz, and Jason Upchurch of the Safety Critical Avionics Systems Branch at the NASA Langley Research Center for contributions to the development of the DAIDALUS Self-Separation algorithms. Thanks are also extended to contributors participating through the NASA Langley Information Technology Enhanced Services (LITES) contract, including: Pierre Beaudoin, Kevin Chan, Joel Ilboudo, Kristen Mark, Robb Myer, Gaurev Sharma, and Jim Sturdy, as well as Steve Hylinski from Adaptive Aerospace Group, Inc., and other support and management personnel. Thanks are also extended to members of the Air Traffic Operations Laboratory (ATOL) for their support, including: Chad Chapman, Ronald Maddox, and Edward Scearce. Thanks are also extended to the tireless efforts of the persons staffing the background traffic pilot stations, the UAS pilot stations, and the ATC adjacent sector/tower consoles.
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Ghatas, R.W., Comstock, J.R., Vincent, M.J., Hoffler, K.D., Tsakpinis, D., DeHaven, A.M. (2018). UAS Detect and Avoid – Alert Times and Pilot Performance in Remaining Well Clear. In: Chen, J. (eds) Advances in Human Factors in Robots and Unmanned Systems. AHFE 2017. Advances in Intelligent Systems and Computing, vol 595. Springer, Cham. https://doi.org/10.1007/978-3-319-60384-1_11
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DOI: https://doi.org/10.1007/978-3-319-60384-1_11
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