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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Microscopic Traffic Analysis of Freeway Based on Vehicle Trajectory Data Using Drone Images

드론 영상을 활용한 차량궤적자료 기반 고속도로 미시적 교통분석

  • Ko, Eunjeong (The Cho Chun Shik Graduate School of Green Transportation, KAIST) ;
  • Kim, Soohee (Transportation Research Division, Korea Expressway Corporation Research Institute) ;
  • Kim, Hyungjoo (Advanced Institute of Convergence Technology)
  • 고은정 (한국과학기술원 조천식녹색교통대학원) ;
  • 김수희 (한국도로공사 도로교통연구원 교통연구실) ;
  • 김형주 (차세대융합기술연구원 첨단교통체계)
  • Received : 2021.11.09
  • Accepted : 2021.11.23
  • Published : 2021.12.31
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Abstract

Vehicles experience changes in driving behavior due to the various facilities on the freeway. These sections may cause repetitive traffic congestion when the traffic volume increases, so safety issues may be raised. Therefore, the purpose of this study is to perform microscopic traffic analysis on these sections using drone images and to identify the causes of traffic problems. In the case of drone image, since trajectory data of individual vehicles can be obtained, empirical analysis of driving behavior is possible. The analysis section of this study was selected as the weaving section of Pangyo IC and the sag section of Seohae Bridge. First, the trajectory data was extracted through the drone image. And the microscopic traffic analysis performed on the speed, density, acceleration, and lane change through cell-unit analysis using Generalized definition method. This analysis results can be used as a basic study to identify the cause of the problem section in the freeway. Through this, we aim to improve the efficiency and convenience of traffic analysis.

고속도로를 주행하는 차량은 다양한 시설로 인한 주행행태 변화를 경험한다. 이러한 구간은 교통량 증가 시에 반복적인 교통 정체를 유발할 수 있어 이에 따른 안전성 문제가 제기될 수 있다. 따라서 본 연구는 드론 영상을 활용하여 고속도로 내 반복적인 정체가 발생하는 구간에 대한 미시적인 교통분석을 수행하고 교통문제의 원인을 파악하는 것을 목적으로 한다. 드론영상의 경우 기존 검지기 기반 교통분석 수집체계에서 취득 가능한 집합 형태의 자료에서 벗어나 개별 차량의 궤적자료를 얻을 수 있기 때문에 차량주행행태에 대한 실증 분석이 가능하다. 본 연구의 분석 구간은 차량주행행태 변화가 심한 판교 IC 엇갈림구간과 서해대교 경사구간으로 선정하였다. 드론 영상을 통해 문제 구간을 통과하는 차량의 궤적자료를 추출하고, 일반화 된 정의(Generalized Definition)를 활용한 셀 단위 분석을 통해 속도, 밀도, 가속도, 그리고 차로변경에 대한 미시적인 교통분석을 수행하였다. 본 연구 결과는 고속도로 내 문제 구간의 원인 파악을 위한 기초 연구로 활용될 수 있으며, 이를 통해 교통분석 업무의 효율성과 편의성 향상을 도모하고자 한다.

Keywords

References

  1. Barmpounakis E. N., Vlahogianni E. I. and Golias J. C.(2016a), "Extracting Kinematic Characteristics from Unmanned Aerial Vehicles," Proceedings of the 95th Annual Meeting of the Transportation Research Board.
  2. Barmpounakis E. N., Vlahogianni E. I. and Golias J. C.(2016b), "Unmanned Aerial Aircraft Systems for Transportation Engineering: Current Practice and Future Challenges," International Journal of Transportation Science and Technology, vol. 5, no. 3, pp.111-122. https://doi.org/10.1016/j.ijtst.2017.02.001
  3. Coifman B. and Lizhe L.(2017), "A Critical Evaluation of the Next Generation Simulation (NGSIM) Vehicle Trajectory Dataset," Transportation Research Part B: Methodological, vol. 105, pp.362-377. https://doi.org/10.1016/j.trb.2017.09.018
  4. Coifman B., McCord M., Mishalani R. G. and Redmill K.(2004), "Surface Transportation Surveillance from Unmanned Aerial Vehicles," In Proceedings of the 83rd Annual Meeting of The Transportation Research Board, pp.11-20.
  5. Coifman B., McCord M., Mishalani R. G., Iswalt M. and Ji Y.(2006a), "Roadway Traffic Monitoring from an Unmanned Aerial Vehicle," IEEE Proceedings-Intelligent Transport Systems, vol. 153, no. 1, pp.11-20. https://doi.org/10.1049/ip-its:20055014
  6. Coifman B., McCord M., Mishalani R. G., Iswalt M. and Ji Y.(2006b), "Traffic Flow Data Extracted from Imagery Collected Using a Micro Unmanned Aerial Vehicle," Applications of Advanced Technology in Transportation, 9th International Conference, ASCE, pp.298-303.
  7. Daamen W., Loot L. and Hoogendoorn S.(2010), "Empirical Analysis of Merging Behavior at a Freeway On-ramp," Proceedings of the 89th Annual Meeting of the Transportation Research Board, vol. 2188, no. 1, pp.108-118.
  8. Daganzo C. F.(1997), Fundamentals of Transportation and Traffic Operations, Pergamon Oxford, pp.66-77.
  9. Edie L. C.(1963), Discussion of Traffic Stream Measurements and Definitions, Port of New York Authority, pp.139-154.
  10. Gao H., Kong S. L., Zhou S., Lv F. and Chen Q.(2014), "Automatic Extraction of Multi-Vehicle Trajectory Based on Traffic Videotaping from Quadcopter Model," Applied Mechanics and Materials, vol. 552, pp.232-239. https://doi.org/10.4028/www.scientific.net/amm.552.232
  11. Khan M. A., Ectors W. and Bellemans T.(2018), "Unmanned Aerial Vehicle-Based Traffic Analysis: A Case Study for Shockwave Identification and Flow Parameters Estimation at Signalized Intersections," Remote Sensing, vol. 10, no. 3, 458. https://doi.org/10.3390/rs10030458
  12. Khan M. A., Ectors W., Bellemans T., Janssens D. and Wets G.(2017a), "UAV-Based Traffic Analysis: A Universal Guiding Framework Based on Literature Survey," Transportation Research Procedia, vol. 22, pp.541-550. https://doi.org/10.1016/j.trpro.2017.03.043
  13. Khan M. A., Ectors W., Bellemans T., Janssens D. and Wets G.(2017b), "Unmanned Aerial Vehicle based Traffic Analysis: Methodological Framework for Automated Multivehicle Trajectory Extraction," Transportation Research Record: Journal of the Transportation Research Board, vol. 2626, no. 1, pp.25-33. https://doi.org/10.3141/2626-04
  14. Lu X. Y. and Skabardonis A.(2007), "Freeway Traffic Shockwave Analysis: Exploring NGSIM Trajectory Data," Presented at 86th Annual Meeting of the Transportation Research Board.
  15. Lu X. Y., Varaiya P. and Horowitz R.(2009), "Fundamental Diagram Modeling and Analysis based NGSIM Data," IFAC Proceedings Volumes, vol. 42, no. 15, pp.367-374.
  16. Punzo V., Borzacchiello M. T. and Ciuffo B.(2009), "Estimation of Vehicle Trajectories from Observed Discrete Positions and Next-generation Simulation Program (NGSIM) Data," Presented at 88th Annual Meeting of the Transportation Research Board.
  17. Punzo V., Borzacchiello M. T. and Ciuffo B.(2011), "On the Assessment of Vehicle Trajectory Data Accuracy and Application to the Next Generation SIMulation (NGSIM) Program Data," Transportation Research Part C: Emerging Technologies, vol. 19, no. 6, pp.1243-1262. https://doi.org/10.1016/j.trc.2010.12.007
  18. Puri A.(2005), A Survey of Unmanned Aerial Vehicles (UAV) for Traffic Surveillance, Department of Computer Science and Engineering, University of South Florida, p.1.
  19. Thiemann C., Treiber M. and Kesting A.(2008), "Estimating Acceleration and Lane-changing Dynamics Based on NGSIM Trajectory Data," Presented at 87th Annual Meeting of the Transportation Research Board.
  20. Treiterer J. and Myers J. A.(1974), "The Hysteresis Phenomenon in Traffic Flow," In Proceedings of the Sixth International Symposium on Transportation and Traffic Theory, vol. 6, pp.13-38.