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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
권호 표지
DOI QR코드

DOI QR Code

Artificial Intelligence Based LOS Determination for the Cyclists-Pedestrians Mixed Road Using Mobile Mapping System

인공지능 기반 MMS를 활용한 자전거보행자겸용도로 서비스 수준 산정

  • Tae-Young Lee (Center of Infrastructure Asset Management, Hanbat National University) ;
  • Myung-Sik Do (Dept. of Urban Engineering, Hanbat National University)
  • 이태영 (한밭대학교 인프라자산관리센터(CIAM)) ;
  • 도명식 (한밭대학교 도시공학과)
  • Received : 2023.04.05
  • Accepted : 2023.05.17
  • Published : 2023.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Recently, the importance of monitoring and management measures for bicycle road related facilities has been increasing. However, research on the monitoring and evaluation of users' safety and convenience in walking spaces including bicycle path is insufficient. In this study, we would like to construct health monitoring data for cylists-pedestrians mixed road using a mobile mapping system, and propose a plan to calculate the level of service of the mixed roads from the perspective of pedestrians and cyclists using artificial intelligence based object detection techniques. The monitoring and level of service calculation method of cylists-pedestrians mixed roads proposed in this study is expected to be used as basic information for planning and management such as maintenance and reconstruction of walking spaces in preparation for the increase of electric bicycles and personal mobility in the future.

최근, 자전거도로 관련 시설 등의 모니터링과 관리 방안에 대한 중요성이 증가하고 있다. 그러나 자전거도로를 포함한 보행공간에 대한 이용자의 안전 및 편의성에 대한 모니터링과 평가에 대한 연구는 미흡한 실정이다. 본 연구에서는 모바일매핑시스템(Mobile Mapping System, MMS)을 활용하여 자전거보행자겸용도로의 상태 모니터링 데이터를 구축하고, 인공지능 기반객체인식 기법을 이용하여 보행자와 자전거 이용자들의 관점에서 겸용도로의 서비스 수준 산정방안을 제시하고자 한다. 본 연구를 통해 제시한 자전거보행자겸용도로의 모니터링과 서비스 수준 산정 방안은 향후 전기자전거와 개인형 이동수단(personal mobility, PM)의 증가에 대비한 보행공간의 정비와 재구조화(reconstruction) 등 계획과 관리에 기초 자료로 활용될 수 있을 것으로 기대된다.

Keywords

References

  1. Arcos-Garcia, A., Soilan, M., Alvarez-Garcia, J. A. and Riveiro, B.(2017), "Exploiting Synergies for Mobile Mapping Seonsors and Deep Learning for Traffic sign Recognition System", Expert System with Application, vol. 89, pp.286-295. https://doi.org/10.1016/j.eswa.2017.07.042
  2. Ban, J. H., Lee, T. M. and Yoo, J. H.(2019), "Safe2Walk4Blind: DNN-based Walking Assistance System for the Blind", Journal of Institute of Control, Robotics and System, vol. 25, no. 5, pp.565-571. https://doi.org/10.5302/J.ICROS.2019.19.0033
  3. Beura, S. K., Kumar, N. K. and Bhuyan, P. K.(2017), "Level of Service for Bicycle Through Movement at Signalized Intersections Operating Under Heterogeneous Traffic Flow Conditions", Transportation in Developing Economies, vol. 3, no. 2, pp.1-16. https://doi.org/10.1007/s40890-016-0030-9
  4. Bhuyan, P. K. and Rao, K. V.(2012), "Defining LOS Criteria of Urban Streets using GPS data: K-means and K-medoid Clustering in Indian Context", Transport, vol. 27, no. 2, pp.149-157. https://doi.org/10.3846/16484142.2012.692354
  5. Choi, I. H. and Kim, E. M.(2021), "Automatic Construction of Deep Learning Training Data for High-Definition Road Maps Using Mobile Mapping System", Journal of the Korean Society of Surveying Geodesy, Photogrammetry and Cartography, vol. 39, no. 3, pp.133-139. https://doi.org/10.7848/KSGPC.2021.39.3.133
  6. Choi, J. S. and Kim, W. W.(2010), "A Study on a measure of Asset Management Information Systems for Highway Transportation Facilities using AHP", Korean Society of Civil Engineers, vol. 30, no. 6, pp.663-673.
  7. Choi, S. H., Do, M. S., You, S. H. and Cho, C. S.(2018), "Determination of Visual Based Asphalt Pavement Crack Condition Using Deep Learning", International Journal of Highway Engineering, vol. 20, no. 5, pp.75-83. https://doi.org/10.7855/IJHE.2018.20.5.075
  8. Choi, S. H., Park, J. G. and Do, M. S.(2021), "Infrastructure Health Monitoring and Economic Analysis for Road Asset Management: Focused on Sejong City", The Journal of the Korea Institure of Intelligent Transportation System, vol. 20, no. 4, pp.71-82. https://doi.org/10.12815/kits.2021.20.4.71
  9. Ministry of Security and Public Administration(MOSPA)(2015), A Study on the Improvement of Bicycle Pedestrian Road Considering Safety and Convenience.
  10. Oh, S. H. and Namgung, J. H.(2013), "A Study on the Improvement of Bicycle Roads Considering Pedestrians", Auri Brief, no. 66, pp.1-12.
  11. Park, S. L. and Song, A. R.(2021), "Updating Obstacle Information Using Object Detection in Street-View Images", Journal of the Korean Society of Surveying Geodesy, Photo Grammetry and Cartography, vol. 39, no. 6, pp.599-607.
  12. Pitchard, R., Froyen, Y. and Sniek, B.(2019), " Bicycle Level of Service for Route Choice-A GIS Evaluation of Four Existing Indicators with Empirical Data", International Journal of Geo-Information, vol. 8, no. 214. doi: 10.3390/ijgi8050214
  13. Shu, S., Bian, Y., Rong, J. and Li, S.(2018), "Bicycle Level of Service Evaluation Method for Urban Road Segment", Open Journal of Applied Sciences, vol. 8, no. 2, pp.80-88. https://doi.org/10.4236/ojapps.2018.82007