Conduct Safety Risk Management Analysis on small Unmanned Aircraft Detect and Avoid Systems
New and refined safety analysis methods are needed to assess potential hazards for Unmanned Aircraft (UA) Detect and Avoid (DAA) systems. This research will develop analysis tools and methods of risk assessment for small remotely piloted DAA systems that enable safety optimization of DAA design and operations. Through an analysis of DAA systems and operations, the research team will identify disconnects between existing risk assessment methodologies, such as those highlighted in FAA Order 8040.6, and their application to DAA. Additionally, this research will identify hazards and new risk assessment strategies and explore their application to DAA systems and DAA-enabled UAS operations. Ultimately this research will derive toolsets and methods for assessing risk for DAA systems and operations while identifying significant contributions to risk and strategies for mitigation. This information will aid the development of DAA industry standards by exploring current industry complexities associated with the integration of DAA and highlight areas of interest for future research into DAA-enabled UAS operations. This information will also aid the FAA in performing safety risk assessments on DAA industry standards and applicant requests for operational approval.
Applied Aviation Research Center
Kansas State University