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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20551

    Title: Estimation of Dynamic Assignment Matrices and OD Demands Using Adaptive Kalman Filtering
    Authors: 胡守任;Hu, Shou-ren;Madanat, S. M.;Krogmeier, J. V.;Peeta, S.
    Contributors: 淡江大學運輸管理學系
    Keywords: Adaptive niters;Kalman Filtering;Optimal estimation;Origin-destination demands;Traffic simulator
    Date: 2001-01-01
    Issue Date: 2009-11-30 12:51:33 (UTC+8)
    Publisher: Taylor & Francis
    Abstract: The purpose of this research was to develop a dynamic model for the on-line estimation and prediction of freeway users’ origin-destination (OD) matrices. In this paper, we present a Kalman Filtering algorithm that uses time-varying assignment matrices generated by using a mesoscopic traffic simulator. The use of a traffic simulator to predict time-varying travel time model parameters was shown to be promising for the determination of dynamic OD matrices for a freeway system. Moreover, the issues of using time-varying model parameters, effects of incorporating different sources of measurements and the use of adaptive estimation are addressed and investigated in this research.
    Relation: Journal of Intelligent Transportation Systems 6(3), pp.281-300
    DOI: 10.1080/10248070108903696
    Appears in Collections:[Graduate Institute & Department of Transportation Management] Journal Article

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