Presentation
Developing an Augmented Reality Air Traffic Training Model for Uncrewed Aircraft Operators
SessionPoster Session 1
DescriptionEvery month the FAA receives over 100 reports of drones near airports (FAA, 2025). The recent airborne collision between an aerial firefighting aircraft and a drone during the Los Angeles fires highlights the importance of UAS pilots’ situational awareness of air traffic and interpretation of ADS-B traffic data in their decision-making process (Ding & Rodriguez, 2025). ADS-B technology enables UAS pilots to identify nearby aircraft, but UAS manufacturer operator manuals often provide little detail on the ADS-B operations, warnings, indications, or appropriate flight response. The performance of this integrated ADS-B technology and the associated display of airborne traffic varies widely across manufacturers. Additionally, UAS pilots lack a training environment where they can safely experience airborne crewed aircraft and then practice appropriate avoidance maneuvers. Developers of detect and avoid technologies and automated avoidance maneuvers also lack a similar environment that is low cost and accessible for safely testing these technologies. The objective of this research is to explore the use of an economic augmented reality (AR) training model that may provide a safe real-world UAS air traffic environment that supports UAS training and research.
Event Type
Poster
TimeTuesday, October 14th5:30pm - 6:30pm CDT
LocationRiverside East