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NTL Classification:NTL-AVIATION-AVIATIONNTL-AVIATION-Air Traffic ControlNTL-AVIATION-Aviation Human FactorsNTL-AVIATION-Aviation Safety/AirworthinessNTL-SAFETY AND SECURITY-Aviation Safety/AirworthinessNTL-SAFETY AND SECURITY-Human FactorsNTL-SAFETY AND SECURITY-SAFETY AND SECURITYNTL-REFERENCES AND DIRECTORIES-Statistics
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Abstract:In this paper we present the results of
applying data mining techniques to identify patterns and
anomalies in air traffic control operational errors (OEs).
Reducing the OE rate is of high importance and remains a
challenge in the aviation safety community. Existing
studies, which use traditional methods and focus on
individual aspects of OEs, are limited to operations at a
single facility, or events in a short period of time. A holistic
study of historical data available on OEs has not been
conducted. We have applied an attribute focusing
technique to study 15 years of operational errors at all
FAA Air Route Traffic Control Centers (ARTCCs) 1 in the
National Airspace System (NAS) in the U.S. We have
found ‘interesting’ patterns of common characteristics,
anomalies, and changes in trends of operational errors.
We interpreted the results with the help of domain experts
and plan to do a similar analysis for OEs at other types of
air traffic control facilities (towers and TRACONs) as well.
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