The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Methodology of Calibration for Falling Objects Accident-Risk-Zone Approach Detection Algorithm at Port Considering GPS Errors

GPS 오차를 고려한 항만 내 낙하물 사고위험 알고리즘 보정 방법론 개발

  • Son, Seung-Oh (Dept. of Smart city Eng., Hanyang Univ.) ;
  • Kim, Hyeonseo (Dept. of Smart city Eng., Hanyang Univ.) ;
  • Park, Juneyoung (Dept. of Transportation & Logistics Eng, Smart city Eng., Hanyang Univ.)
  • 손승오 (한양대학교 스마트시티공학과) ;
  • 김현서 (한양대학교 스마트시티공학과) ;
  • 박준영 (한양대학교 교통.물류공학과, 스마트시티공학과)
  • Received : 2020.10.12
  • Accepted : 2020.11.11
  • Published : 2020.12.31
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Abstract

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

IoT 디바이스로부터 수집된 위치정보를 활용한 실시간 위치센싱 기술은 항만 등 다양한 산업현장에서 활용되고 있다. 그러나 GPS 센서의 특성상 오차는 항상 존재하며, 이를 활용하는 사고위험 검지 알고리즘은 오차의 고려가 필수적이다. 본 연구는 GPS 오차를 고려한 항만 내 낙하물 사고위험 구역 접근검지 알고리즘의 보정 방법론을 제안한다. IoT 디바이스로부터 수집된 GPS 오차 데이터를 확률변수로 하는 확률밀도함수를 추정하였으며 알고리즘의 검증을 위해 미시적 시뮬레이션을 활용하였다. 검증 결과 알고리즘은 디바이스의 위치오차 1m, 5m에 따라 검지 정확도가 각각 93%, 77%로 나타났다. 본 연구는 향후 디바이스의 성능을 고려한 유효 위험범위 설정 및 안전관리에 중요한 역할을 할 수 있을 것으로 기대된다.

Keywords

Acknowledgement

이 논문은 2020년 해양수산부 재원으로 해양수산과학기술진흥원의 지원을 받아 수행된 연구임(스마트 항만 IoT 융합·운영기술 개발)

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