Treating Uncertain Demand Information in Origin–Destination Matrix Estimation with Traffic Counts
Publication: Journal of Transportation Engineering
Volume 134, Issue 8
Abstract
This paper investigates the problem of estimating dynamic origin–destination trip matrices in large-scale transportation networks, using automatic link traffic counts and uncertain prior demand information, to facilitate the real-time monitoring of network traffic conditions through intelligent transportation systems. The paper proposes and evaluates the performance of two algorithms to estimate the temporal distribution of trip departures used to produce dynamic matrices, through several test experimentations in a real case study. The accuracy and the computing speed of the proposed algorithms is investigated in relation to different bounds, wherein trip departure estimates are sought to be included, levels of link count availability and network sizes. Results show that an optimization algorithm proposed for the fast estimation of trip departure rates with incorporated lower and upper bound constraints lead to dynamic matrices with considerably increased reliability, in comparison to the algorithm that intrinsically excludes demand constraints.
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Acknowledgments
The writers are grateful to the anonymous reviewers who made several constructive and helpful comments on earlier versions of this paper.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 134 • Issue 8 • August 2008
Pages: 327 - 337
Copyright
© 2008 ASCE.
History
Received: Oct 24, 2006
Accepted: Dec 27, 2007
Published online: Aug 1, 2008
Published in print: Aug 2008
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