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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/9163

Title: Bayesian inference for vehicle speed and vehicle length using dual-loop detector data
Authors: Li, Baibing
Keywords: Bayesian analysis
Dual-loop detector
Vehicle classification
Vehicle length
Vehicle speed
Issue Date: 2010
Publisher: © Elsevier
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
Abstract: 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.
Description: 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
Version: Accepted for publication
DOI: 110.1016/j.trb.2009.06.006
URI: https://dspace.lboro.ac.uk/2134/9163
Publisher Link: http://www.sciencedirect.com/science/article/pii/S0191261509000782
ISSN: 0191-2615
Appears in Collections:Published Articles (Business School)

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