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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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A Study on Traffic Big Data Mapping Using the Grid Index Method

그리드 인덱스 기법을 이용한 교통 빅데이터 맵핑 방안 연구

  • Chong, Kyu Soo (Dept. of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology) ;
  • Sung, Hong Ki (Dept. of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology)
  • 정규수 (한국건설기술연구원 미래융합연구본부) ;
  • 성홍기 (한국건설기술연구원 미래융합연구본부)
  • Received : 2020.11.13
  • Accepted : 2020.12.11
  • Published : 2020.12.31
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Abstract

With the recent development of autonomous vehicles, various sensors installed in vehicles have become common, and big data generated from those sensors is increasingly being used in the transportation field. In this study, we proposed a grid index method to efficiently process real-time vehicle sensing big data and public data such as road weather. The applicability and effect of the proposed grid space division method and grid ID generation method were analyzed. We created virtual data based on DTG data and mapped to the road link based on coordinates. As a result of analyzing the data processing speed in grid index method, the data processing performance improved by more than 2,400 times compared to the existing link unit processing method. In addition, in order to analyze the efficiency of the proposed technology, the virtually generated data was mapped and visualized.

최근 자율주행의 발달로 차량에 장착된 다양한 센서가 일반화 되고 그 센서에서 발생되는 빅 데이터는 교통 분야에서 활용도가 높아지고 있다. 본 연구에서는 이러한 교통 빅 데이터의 활용을 위해 실시간으로 발생되는 차량 센싱 빅 데이터와 도로 기상 등 공공데이터를 지도상에 효율적으로 맵핑하기 위한 그리드 인덱스 기법을 제안하였으며, 제안한 그리드 공간 분할 방식과 그리드 ID 부여 방식에 대하여 적용 가능성 및 효과를 분석하였다. 차량 센서에서 실시간 분석된 강수 데이터를 전국 화물차의 디지털 운행기록장치(DTG, Digital Tachograph) 데이터를 기반으로 가상 생성하여 좌표기반으로 맵핑하였으며, 제안 방식과 링크 단위 처리방식의 처리 속도를 비교하였다. 제안 방식은 링크 단위의 처리 방식 대비 약 2,400배 이상의 데이터 처리 성능 개선을 나타냈다. 추가로 그리드 맵핑의 적용 가능성 및 링크 단위 맵핑과의 차별성을 확인하고자 가상 생성한 데이터를 시각화하고 비교하였다.

Keywords

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