In a previous paper, a statistical analysis of runway incursion (RI) events was conducted to ascertain their relevance to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to perhaps several of the AvSP top ten TC. That data also identified several primary causes and contributing factors for RI events that served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events. The system-level BBN model will allow NASA to generically model the causes of RI events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of RI events in particular, and to improve runway safety in general. The development, structure and assessment of that BBN for RI events by a Subject Matter Expert panel are documented in this paper.
Development of a Bayesian Belief Network Runway Incursion Model
2014
11 pages
Report
No indication
English
Statistical Analysis , Runway incursions , Air traffic , Air traffic control , Aircraft safety , Belief networks , Nasa programs , Air traffic controllers(Personnel) , Statistical analysis , Crossings , Decision making , Data bases , Information analysis , Takeoff , Predictions , Collision avoidance
DEVELOPMENT OF A BAYESIAN BELIEF NETWORK RUNWAY INCURSION MODEL (AIAA 2014-2158)
British Library Conference Proceedings | 2014
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