UAS detect and avoid – alert times and pilot performance in remaining well clear

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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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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 Advances in Intelligent Systems and Computing (Vol. 595, pp. 109–120). Springer Verlag. https://doi.org/10.1007/978-3-319-60384-1_11

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