DOI QR코드

DOI QR Code

A Study on the Density Analysis of Multi-objects Using Drone Imaging

드론 영상을 활용한 다중객체의 밀집도 분석 연구

  • WonSeok Jang (Urban Disaster Prevention Safety Cooperation Course, Univ. of Chonnam National University) ;
  • HyunSu Kim (D.Air) ;
  • JinMan Park (Myoungshin Co.,Ltd.) ;
  • MiSeon Han (MG Engineering) ;
  • SeongChae Baek (Dept. of Architecture Civil Engineering, Univ. of Chonnam National University) ;
  • JeJin Park (Dept. of Architecture Civil Engineering, Univ. of Chonnam National University)
  • Received : 2024.02.14
  • Accepted : 2024.03.06
  • Published : 2024.04.30

Abstract

Recently, the use of CCTV to prevent crowd accidents has been promoted, but research is needed to compensate for the spatial limitations of CCTV. In this study, pedestrian density was measured using drone footage, and based on a review of existing literature, a threshold of 6.7 people/m2 was selected as the cutoff risk level for crowd accidents. In addition, we conducted a preliminary study to determine drone parameters and found that the pedestrian recognition rate was high at a drone altitude of 20 meters and an angle of 60°. Based on a previous study, we selected a target area with a high concentration of pedestrians and measured pedestrian density, which was found to be 0.27~0.30 per m2. The study shows it is possible to measure risk levels by determining pedestrian densities in target areas using drone images. We believe drone surveillance will be utilized for crowd safety management in the near future.

최근 CCTV 영상을 기반으로 인파사고를 예방하는 방안이 추진되고 있다. 그러나 CCTV는 공간적 한계점이 있어 이를 보완하기 위한 연구가 필요한 실정이다. 본 연구에서는 드론 영상을 사용하여 보행자의 밀도를 측정하는 연구를 수행하였다. 기존 연구문헌을 통해 군중의 인파사고 임계값인 1m2당 6.7명을 위험수준으로 선정하였다. 또한 드론의 파라미터를 도출하기 위해 선행연구를 수행한 결과, 고도 20m, 각도 60°에서 보행자의 인식률이 높은 것으로 나타났다. 이후 선행연구를 기반으로 보행자가 밀집한 대상지를 선정하여 밀집도를 측정한 결과, 단위 면적당 0.27~0.30명 수준으로 나타났다. 본 연구를 통해 드론 영상을 사용하여 대상지의 보행자 밀집도에 따른 위험수준 측정이 가능한 것으로 확인되었으며, 향후 인파사고 안전관리 대체 수단으로 활용이 가능할 것으로 판단된다.

Keywords

Acknowledgement

본 연구는 2023년도 교육부의 재원으로 한국연구재단의 지원을 받아 수행된 지자체-대학 협력기반 지역혁신 사업(재단 과제관리번호 : 광주전남플랫폼 2021RIS-002) 및 광주광역시의 지원을 받아 수행된 2023년 재난안전 전문인력 양성 교육기관 지원사업(과제관리번호 : 2023-2081-01)의 결과입니다.

References

  1. BBC NEWS Korea, https://www.bbc.com/korean/news-64260273, 2023.09.15.
  2. Feliciani, C. and Nishinari, K.(2018), "Measurement of congestion and intrinsic risk in pedestrian crowds", Transportation Research Part C: Emerging Technologies, vol. 91, pp.124-155.
  3. Jiang, P., Ergu, D., Liu, F., Cai, Y. and Ma, B.(2022), "A review of Yolo algorithm developments", Procedia Computer Science, vol. 199, pp.1066-1073.
  4. Jung, B. K., Seo, S. H., Park, B. G., Park, D. Y., Trinh T. H. and Bae, S. H.(2022), "On-road mobile source emissions estimation by traffic parameters based on UAV video", Proceedings of the KOR-KST Conference, vol. 86, pp.211-212.
  5. Kang, J. H.(2021), "Distance-based adaptive anchor box selection for object detection and localization with magnetic declination correction in drone video analysis", Journal of Institute of Control, Robotics and Systems, vol. 27, no. 10, pp.776-783.
  6. Kim, C. R., Song, J. I. and Lee, J. H.(2020), "Multi-object tracking system for disaster context-aware using deep learning", Proceedings of the Korean Society of Broadcast Media Engineering Conference, pp.697-700.
  7. Korean Law Information Center(KLIC), https://www.law.go.kr/법령/항공안전법, 2024.03.06.
  8. Mahaur, B. and Mishra, K. K.(2023), "Small-object detection based on YOLOv5 in autonomous driving systems", Pattern Recognition Letters, vol. 168, pp.115-122.
  9. Ministry of Land, Infrastructure and Transport(MOLIT)(2013), Korean Highway Capacity Manual.
  10. Ministry of the Interior and Safety(MIS), https://www.mois.go.kr/frt/bbs/type001/commonSelectBoardArticle.do;jsessionid=9vyZCruYlNTSZTbBWkIPqq-+.node10?bbsId=BBSMSTR_000000000501&nttId=105932, 2023.12.21.
  11. Shin, S. Y. and Kim, S. G.(2020), "Prospects and policy directions for new large urban disasters", The Seoul Institute Policy Report, vol. 301, pp.1-20.
  12. Still, G. K.(2000), Crowd dynamics, Doctoral dissertation, University of Warwick.
  13. Wang, J., Lo, S., Wang, Q., Sun, J. and Mu, H.(2013), "Risk of Large Scale Evacuation Based on the Effectiveness of Rescue Strategies Under Different Crowd Densities", Risk Analysis, vol. 33, no. 8, pp.1553-1563.
  14. Zhang, J. and Seyfried, A.(2013), "Empirical characteristics of different types of pedestrian streams", Procedia Engineering, vol. 62, pp.655-662.
  15. Zhen, W., Mao, L. and Yuan, Z.(2008), "Analysis of trample disaster and a case study Mihong bridge fatality in China in 2004", Safety Science, vol. 46, no. 8, pp.1255-1270.