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Validation of Mid Air Collision Detection Model using Aviation Safety Data

항공안전 데이터를 이용한 항공기 공중충돌위험식별 모형 검증 및 고도화

  • 백현진 (항공안전기술원 데이터분석연구센터) ;
  • 박배선 (인하대학교 산업과학기술연구소) ;
  • 김혜욱 (한국항공대학교 항공정책연구소)
  • Received : 2021.11.17
  • Accepted : 2021.12.14
  • Published : 2021.12.31

Abstract

In case of South Korea, the airspace which airlines can operate is extremely limited due to the military operational area located within the Incheon flight information region. As a result, safety problems such as mid-air collision between aircraft or Traffic alert and Collision Avoidance System Resolution Advisory (TCAS RA) may occur with higher probability than in wider airspace. In order to prevent such safety problems, an mid-air collision risk detection model based on Detect-And-Avoid (DAA) well clear metrics is investigated. The model calculates the risk of mid-air collision between aircraft using aircraft trajectory data. In this paper, the practical use of DAA well clear metrics based model has been validated. Aviation safety data such as aviation safety mandatory report and Automatic Dependent Surveillance Broadcast is used to measure the performance of the model. The attributes of individual aircraft track data is analyzed to correct the threshold of each parameter of the model.

Keywords

Acknowledgement

본 연구는 국토교통과학기술진흥원의 "빅데이터 기반 항공안전관리 기술개발 및 플랫폼 구축"(20BDAS-B158275-01)의 일환으로 수행되었으며, 지원에 감사드립니다.

References

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