개별 차량의 비전 센서 기반 차두 시간 데이터를 활용한 경험적 교통류 모형 추정 방법론
An Estimation Methodology of Empirical Flow-density Diagram Using Vision Sensor-based Probe Vehicles’ Time Headway Data
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초록
본 연구에서는 개별 차량의 차두 시간(time headway) 정보를 활용하여 고속도로 환경에서의단일 링크에 대한 교통류 모형(flow-density diagram)을 추정하는 방법에 대해 탐구한다. 차두시간 기반 교통류 모형(empirical flow-density diagram) 연구를 위해 차량용 비전 센서가 탑재된실험 차량에서 9개월동안 수집된 데이터의 전처리 및 GIS 기반 맵 매칭을 수행한다. 기존의교통류 모델식을 활용한 차두 시간 기반 교통류 모형(empirical flow-density diagram)의 검증을위해, 차량 검지기 기반의 VDS(Vehicle Detection System) 데이터(loop detection traffic data) 기반교통류 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 교통량과차량 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 위한방법에 대해 제안한다.
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.
참고문헌 (24)
- Anuar, K., "Estimating traffic flow rate on freeways from probe vehicle data and fundamental diagram", 2015 IEEE 18th International Conference on Intelligent Transportation Systems, pp.2921~2926 (2015), IEEE
- Boamah, S. A., "Spatial and temporal analyses of traffic flow in the city of Almelo: In search for a microscopic fundamental diagram (MFD)", Master, Faculty of Geo-Information Science and Earth Observation, pp.2010
- Cassidy, M. J., "Macroscopic fundamental diagrams for freeway networks: Theory and observation", Transportation Research Record, 2260(1), pp.8~15 (2011)
- Clairais, A., "Calibration of the fundamental diagram based on loop and probe data", Transportation Research Record, 2560(1), pp.17~25 (2016)
- Cowan, R. J., "Useful headway models", Transportation Research, 9(6), pp.371~375 (1975)
- Deng, Y., "Heterogenous trip distance-based route choice behavior analysis using real-world large-scale taxi trajectory data", Journal of Advanced Transportation, 2020 (2020)
- Dong, S., "Nonparametric modeling of vehicle-type-specific headway distribution in freeway work zones", Journal of Transportation Engineering, 141(11), pp.05015004~ (2015)
- Edie, L. C., "Discussion of traffic stream measurements and definitions", Proceedings of the 2nd International Symposium on the Theory of Traffic Flow, pp.139~154 (1965)
- Ha, D. H., "Time headway variable and probabilistic modeling", Transportation Research Part C: Emerging Technologies, 25, pp.181~201 (2012)
- Kerner, B. S., "The Physics of Traffic: Empirical Freeway Pattern Features", Engineering Applications; and Theory. Physics Today, 58(11), pp.1~86 (2005)
- "Korea Expressway Corporation" (2022)[URL]
- Li, L., "Vehicle headway modeling and its inferences in macroscopic", microscopic traffic flow theory: A survey, 2017, pp.76, 170~188
- "Mobileye an Intel Company" (2022)[URL]
- Richards, P. I., "Shock waves on the highway", Operations Research, 4(1), pp.42~51 (1956)
- Seo, T., "Fundamental diagram estimation by using trajectories of probe vehicles", Transportation Research Part B: Methodological, 122, pp.40~56 (2019)
- 심지섭, "DSRC 기반 프로브 자료를 이용한 거시 교통류 모형 추정 방법", 한국ITS학회 논문지, 16(6), pp.29~41 (2017), 한국ITS학회[DOI]
- Shim, J., "Empirical evaluation of influential factors on bifurcation in macroscopic fundamental diagrams", Transportation Research Part C:Emerging Technologies, 102, pp.509~520 (2019)
- Treiber, M., "Traffic flow dynamics, Traffic Flow Dynamics: Data, Models and Simulation", pp.13~36 (2013), Springer-Verlag
- Wardrop, J. G., "Road paper. Some theoretical aspects of road traffic research", Proceedings of the Institution of Civil Engineers, 1(3), pp.325~362 (1952)
- Xu, Z., "Macroscopic Fundamental Diagram (MFD) Estimation Based on Vehicle-to-Infrastructure (V2I) Connected Vehicle Data", pp.2016
- Yin, S., "Headway distribution modeling with regard to traffic status", 2009 IEEE Intelligent Vehicles Symposium, pp.1057~1062 (2009), IEEE
- Zhang, G., "A Gaussian kernel-based approach for modeling vehicle headway distributions", Transportation Science, 48(2), pp.206~216 (2014)
- Zhang, G., "Examining headway distribution models with urban freeway loop event data", Transportation Research Record, 1999(1), pp.141~149 (1999)
- Zhu, J., "Development of destination choice model with pairwise district-level constants using taxi GPS data", Transportation Research Part C: Emerging Technologies, 93, pp.410~424 (2018)