Mesoscopic-Wavelet Freeway Work Zone Flow and Congestion Feature Extraction Model
Publication: Journal of Transportation Engineering
Volume 130, Issue 1
Abstract
A new mesoscopic-wavelet model is presented for simulating freeway traffic flow patterns and extracting congestion characteristics. A traffic speed–density relationship is introduced with a lane drop factor to take into account lane closures in freeway work zones. Patterns of multiple parameters are inputted to a congestion feature extraction algorithm. An approximate solution for this equation is found by space-time discretization. The high frequency fluctuations of the signal are not recognizable at normal resolutions. To overcome this problem, a multi-resolution wavelet filter is introduced in the proposed model to enhance traffic features and extract congestion characteristics from the traffic data. Fourth-order Coifman wavelets are used for filtering because of their good approximation for high-resolution scaling.
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Information
Published In
Journal of Transportation Engineering
Volume 130 • Issue 1 • January 2004
Pages: 94 - 103
Copyright
Copyright © 2004 American Society of Civil Engineers.
History
Received: Apr 26, 2002
Accepted: Nov 19, 2002
Published online: Dec 15, 2003
Published in print: Jan 2004
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