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On selecting an optimal wavelet for detecting singularities in traffic and vehicular data

Zheng, Zuduo & Washington, Simon (2012) On selecting an optimal wavelet for detecting singularities in traffic and vehicular data. Transportation Research Part C : Emerging Technologies, 25, pp. 18-33.

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Abstract

Serving as a powerful tool for extracting localized variations in non-stationary signals, applications of wavelet transforms (WTs) in traffic engineering have been introduced; however, lacking in some important theoretical fundamentals. In particular, there is little guidance provided on selecting an appropriate WT across potential transport applications. This research described in this paper contributes uniquely to the literature by first describing a numerical experiment to demonstrate the shortcomings of commonly-used data processing techniques in traffic engineering (i.e., averaging, moving averaging, second-order difference, oblique cumulative curve, and short-time Fourier transform). It then mathematically describes WT’s ability to detect singularities in traffic data. Next, selecting a suitable WT for a particular research topic in traffic engineering is discussed in detail by objectively and quantitatively comparing candidate wavelets’ performances using a numerical experiment. Finally, based on several case studies using both loop detector data and vehicle trajectories, it is shown that selecting a suitable wavelet largely depends on the specific research topic, and that the Mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data.

Impact and interest:

1 citations in Scopus
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1 citations in Web of Science®

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ID Code: 50318
Item Type: Journal Article
Keywords: Wavelet transform, Singularity detection, Traffic data analysis, The Mexican hat wavelet, Short-time Fourier transform
DOI: 10.1016/j.trc.2012.03.006
ISSN: 0968-090X
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500)
Divisions: Current > Schools > School of Civil Engineering & Built Environment
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright Elsevier 2012
Copyright Statement: This is the author’s version of a work that was accepted for publication in Transportation Research Part C : Emerging Technologies. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Transportation Research Part C Emerging Technologies, [VOL 25, (2012)] DOI: 10.1016/j.trc.2012.03.006
Deposited On: 16 May 2012 12:00
Last Modified: 03 Jan 2014 05:39

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