Estimation of Dynamic Assignment Matrices and OD Demands Using Adaptive Kalman Filtering

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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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