Search Results

Unmanned Aircraft Systems (UAS) emerge as a viable, operational technology for potential civil and commercial applications in the National Airspace System (NAS). Although this new type of technology presents great potential, it also introduces a need for a thorough inquiry into its safety impact on the NAS. This study presents a systems-level approach to analyze the safety impact of introducing a new technology, such as UAS, into the NAS. Utilizing Safety Management Systems (SMS) principles and the existing regulatory structure, this paper outlines a methodology to determine a mandatory safety baseline for a specific area of interest regarding a new aviation technology, such as UAS Sense and Avoid. The proposed methodology is then employed to determine a baseline set of hazards and causal factors for the UAS Sense and Avoid problem domain and associated regulatory risk controls.

This paper outlines an analytical framework to perform a data-driven, risk-based assessment of Air Traffic Control (ATC) facilities. Safety associated with an ATC facility is modeled as an influence network using a set of risk factors. A novel hybrid approach employing Adaptive-Network based Fuzzy Inference Systems is introduced to propagate the model. Statistical analysis of system-wide data for each risk factor is performed to identify outliers and understand underlying distributions. They are then used to define Fuzzy Membership Functions for model variables. Analytical Hierarch Process (AHP) is used to determine rules required by the model's inference engine. Finally, the methodology is applied to a set of ATC facilities using real data.