Data mining of air traffic control operational errors

Details

• Creators:
  Nazeri, Zohreh
• Subject/TRT Terms:
  Air Traffic Control Data Mining Human Error
• Resource Type:
  Proceedings
• Corporate Publisher:
  Brown University. Center for the Study of Race and Ethnicity in America
• NTL Classification:
  NTL-AVIATION-AVIATION ; NTL-AVIATION-Air Traffic Control ; NTL-AVIATION-Aviation Human Factors ; NTL-AVIATION-Aviation Safety/Airworthiness ; NTL-SAFETY AND SECURITY-Aviation Safety/Airworthiness ; NTL-SAFETY AND SECURITY-Human Factors ; NTL-SAFETY AND SECURITY-SAFETY AND SECURITY ; NTL-REFERENCES AND DIRECTORIES-Statistics
• 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.
  
  
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:680a8de378c62db82c3f84eb819309b0c0a09b2fb6fc2f6f1de5b7436b45cc6d
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/5884/dot_5884_DS1.pdf
• File Type:
  [PDF - 175.41 KB ]