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Dynamic Origin-Destination Demand Estimation Using Traffic Data of VDS and AVI  

Kim, Ju-Young (서울시립대학교 교통공학과)
Lee, Seung-Jae (서울시립대학교 교통공학과)
Lee, Young-Ihn (서울대학교 환경대학원)
Son, Bong-Soo (연세대학교 도시공학과)
Publication Information
Journal of Korean Society of Transportation / v.23, no.7, 2005 , pp. 125-136 More about this Journal
Abstract
The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using VDS and AVI data. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a kalman filter algorithm. The proposed dynamic OD estimation model use ilk and off-ramp volumes collected from VDS and partial OD collected from AVI data to raise the accuracy of dynamic OD estimation. The proposed model is evaluated by using the real-time data of SOHAEAN freeway, South Korea. The result of the proposed dynamic OD estimation model based on VDS and AVI data is better than that of based on VDS data. The more AVI systems are equipped at on and off-ramp, the more excellent result of estimation accuracy is expected.
Keywords
OD; VDS; AVI; Bi-Level Proplem;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 김주영 . 이승재(2005), 교통관리시스템의 실시간 교통 자료를 이용한 고속도로 동적OD 추정기법의 개발, 대한교통학회지, 제23권 제4호, 대한교통학회, pp.57-69
2 강정규(1996), 칼만필터를 이용한 도시고속도로 교통량예측 및 실시간O-D 추정, 대한교통학회지, 제14권 제3호, 대한교통학회, pp.7-26
3 Dixon, M. and Rilett, L.R.(2000), Real-Time Origin-Destimation Estimation Using Automatic Vehicle Identification Data. TRB 79th Annual Meeting
4 Garcia, R.C. (2002) Implementing a Dynamic OD Estimation Algorithm within the Microscopic Traffic Simulator Paramics, University of California at Irvine, 94720 CA
5 Antoniou, C., Ben-Akiva, M. and Koutsopoulos, H.N.(2004) Incorporating Automated Vehicle Identification Data into Origin-Destination Estimation. TRB 2004 Annual Meeting
6 Muthuswamy, S., Davis, G.A., Levinson, D.M. and Michalopoulos, P.G.(2002) Freeway Origin Destination Matrix, not as simple as they seem, TRB 2004 Annual Meeting
7 Van der Zijpp, N.(1997), Dynamic OD matrix Estimation from Traffic Counts and Automated Vehicle Identification Data, TRB 1607
8 Iida Y., Kurauchi, F. and Li, L.(2000) A Simple Method for Estimating Dynamic Origin-Destination Matrix on the Urban Expressway: the Extension of the Combined MLS Model, Kyoto Uni
9 Okutani, I. (1987) The Kalman Filtering Approaches in Some Transportation and Traffic Problems. Proceeding of the 10th International Symposium on Transportation and Traffic Theory, Elsevier, Newyork. pp.397-416
10 Ashok, K. and Ben-Akiva, M.E. (2002) Estimation and Prediction of Time-Dependent Origin-Destination Flows with a Stochastic Mapping to Path Flows and Link Flows, Transportation Science Vlo.36 No.2
11 Ashok, K. (1996) Estimation and Prediction of Time-Dependent Origin-Destination Flows, PhD. thesis, Uni. of MIT
12 Hellinga, B.R. and Van Aerde, M.(1996) Estimating Dynamic O-D Demands for a Freeway Corridor Using Loop Detector Data, Uni. of Waterloo
13 Nihan, N.L. and Davis, G.A. (1987) Recursive Estimation of Origin-Destination Matrices from Input/Output Counts. Transportation Research Vol. 21B, No. 2. pp.149-163