Statistical Approach to Road Segmentation
Publication: Journal of Transportation Engineering
Volume 129, Issue 3
Abstract
A method for segmentation of a road based on surface measurements is presented. This method is based on a statistical model of the measurement series and acknowledges that neighboring measurements are dependent. Sudden changes in the level, in the variance, or in the autocorrelation of a series are detected. No prior knowledge about these quantities is required, and no distributional assumptions about the nature of the sudden change are made. The method allows for an assessment of the information contained in the measurements themselves. Uncertainties about the existence and possible location of a change-point are communicated to the user in terms of probabilities. The road engineer may then match the extracted information with available complementary information about, e.g., the age of the pavement and traffic volumes. The focus is on the situation where it is known beforehand that, at most, one change points is present. Thus, the suggested method is best suited to assist the engineer in a detailed study of selected parts of a given measurement series, or may be used iteratively when several change points are suspected. The application of this method is demonstrated using a measurement series for the international roughness index, collected with the Swedish road surface tester known as the laser RST-vehicle.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 129 • Issue 3 • May 2003
Pages: 300 - 308
Copyright
Copyright © 2003 American Society of Civil Engineers.
History
Received: Sep 25, 2001
Accepted: Apr 1, 2002
Published online: Apr 15, 2003
Published in print: May 2003
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