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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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An Estimation Methodology of Empirical Flow-density Diagram Using Vision Sensor-based Probe Vehicles' Time Headway Data

개별 차량의 비전 센서 기반 차두 시간 데이터를 활용한 경험적 교통류 모형 추정 방법론

  • Kim, Dong Min (Cho Chun Shik Graduate School of Mobility, KAIST) ;
  • Shim, Jisup (Department of Transport and Planning, Delft University of Technology)
  • Received : 2022.03.25
  • Accepted : 2022.04.21
  • Published : 2022.04.30
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Abstract

This study explored an approach to estimate a flow-density diagram(FD) on a link in highway traffic environment by utilizing probe vehicles' time headway records. To study empirical flow-density diagram(EFD), the probe vehicles with vision sensors were recruited for collecting driving records for nine months and the vision sensor data pre-processing and GIS-based map matching were implemented. Then, we examined the new EFDs to evaluate validity with reference diagrams which is derived from loop detection traffic data. The probability distributions of time headway and distance headway as well as standard deviation of flow and density were utilized in examination. As a result, it turned out that the main factors for estimation errors are the limited number of probe vehicles and bias of flow status. We finally suggest a method to improve the accuracy of EFD model.

본 연구에서는 개별 차량의 차두 시간(time headway) 정보를 활용하여 고속도로 환경에서의 단일 링크에 대한 교통류 모형(flow-density diagram)을 추정하는 방법에 대해 탐구한다. 차두 시간 기반 교통류 모형(empirical flow-density diagram) 연구를 위해 차량용 비전 센서가 탑재된 실험 차량에서 9개월동안 수집된 데이터의 전처리 및 GIS 기반 맵 매칭을 수행한다. 기존의 교통류 모델식을 활용한 차두 시간 기반 교통류 모형(empirical flow-density diagram)의 검증을 위해, 차량 검지기 기반의 VDS(Vehicle Detection System) 데이터(loop detection traffic data) 기반 교통류 모형과 결과 비교 및 분석을 수행한다. 차두 시간 기반 교통류 모형의 추정 오차 원인을 분석하기 위해 각 교통류 모형의 차두 시간 및 차두 거리의 확률분포와 단위시간 교통량과 차량 밀도의 표준편차를 활용하였다. 분석 결과 링크 내 제한된 샘플 차량 대수 및 수집 데이터에 대한 주행환경 편향성이 추정 오차의 주된 요인이며. 이에 따른 추정 오차 개선을 위한 방법에 대해 제안한다.

Keywords

Acknowledgement

본 연구는 한국연구재단의 이공분야 학문후속세대양성(NRF-2020R1A6A3A03037304) 사업 지원으로 수행하였습니다.

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