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Bayesian inference for vehicle speed and vehicle length using dual-loop detector data

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journal contribution
posted on 01.12.2011, 15:49 authored by Baibing LiBaibing Li
A dual-loop detector consists of two connected single-loop detectors placed several feet apart. Compared with a single-loop detector, it is able to provide more useful information on traffic flow with a higher precision. In this paper we investigate statistical inference for vehicle speed and vehicle length using dual-loop detector data. A Bayesian analysis is performed to combine current observations on traffic flow with prior knowledge, which results in a set of simple formulas for the online estimation of both vehicle speed and vehicle length. As a by-product, vehicle classification is also investigated on the basis of posterior classification probabilities. The computational overhead of updating the estimates is kept to a minimum when new information on traffic flow becomes available. The method is illustrated using real traffic data.

History

School

  • Business and Economics

Department

  • Business

Published in

Transportation Research Part B: Methodological

Volume

44

Issue

1

Pages

108 - 119

Citation

LI, B., 2010. Bayesian inference for vehicle speed and vehicle length using dual-loop detector data. Transportation Research Part B: Methodological, 44 (1), pp.108-119

Publisher

© Elsevier

Version

AM (Accepted Manuscript)

Publication date

2010

Notes

This article was published in the journal,Transportation Research Part B: Methodological [© Elsevier]. The definitive version is available from: http://www.sciencedirect.com/science/article/pii/S0191261509000782

ISSN

0191-2615

Language

en