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A Study on Traffic Data Collection and Analysis for Uninterrupted Flow using Drones

드론을 활용한 연속류 교통정보 수집·분석에 관한 연구

  • Seo, Sung-Hyuk (Dept. of Smart City Engineering (Drone and Transportation Eng. Division), Youngsan Univ.) ;
  • Lee, Si-Bok (Dept. of Smart City Engineering (Drone and Transportation Eng. Division), Youngsan Univ.)
  • 서성혁 (영산대학교 스마트시티공학부 드론교통공학전공) ;
  • 이시복 (영산대학교 스마트시티공학부 드론교통공학전공)
  • Received : 2018.11.01
  • Accepted : 2018.11.29
  • Published : 2018.12.31

Abstract

This study focuses on collecting traffic data using drones to compensate for limitation of the data collected by the existing traffic data collection devices. Feasibility analysis was performed to verify the traffic data extracted from drone videos and optimal methodology for extracting data was established through analysis of various data reduction scenarios. It was found from this study that drones are very economical traffic data collection devices and have strength of determining the level-of-service(LOS) for uninterrupted flow condition in a very simple and intuitive way.

본 연구는 기존 교통정보 수집체계의 한계를 보완하기 위한 수단으로써 드론을 사용하였을 경우 교통량, 속도, 밀도 등의 정보를 단시간에 경제적으로 수집 가능하다는 점에 착안하였으며, 이를 위해 드론을 실제 교통현장 촬영영상 분석을 통해 추출된 핵심 교통정보의 타당성 검증과 더불어 다양한 정보수집시나리오 분석을 통해 최적의 교통정보 추출 방법론을 제시하고자 하였다. 본 연구 수행결과, 드론은 단시간에 경제적인 교통정보수집이 가능한 유용한 정보수집 보완수단임은 물론, 매우 간단하고 직관적인 방법으로 연속류 구간의 서비스수준 판정을 가능하게 해 주는 강점이 있는 것으로 확인되었다.

Keywords

References

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  1. UAV를 활용한 실시간 교통량 분석을 위한 딥러닝 기법의 적용 vol.38, pp.4, 2018, https://doi.org/10.7848/ksgpc.2020.38.4.353
  2. Road Traffic Monitoring from UAV Images Using Deep Learning Networks vol.13, pp.20, 2021, https://doi.org/10.3390/rs13204027