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Identification of Road Irregularities via Vehicle Accelerations
Date Issued
2010
Date Available
2013-01-16T16:31:16Z
Abstract
A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the
resources available for maintenance of the road infrastructure network. The task can be
accurately carried out using profilometers, but such an approach is generally expensive. This
paper presents a method to collect information on the road profile via accelerometers mounted in
a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It
proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities.
The Cross Entropy algorithm estimates the height of the road irregularities from vehicle
accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is
simulated over a range of road profiles to obtain accelerations of the vehicle sprung and
unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative
procedure that searches for the best solution to the inverse problem of finding road irregularities.
In each iteration, a sample of road profiles is generated and an objective function defined as the
sum of squares of differences between the ‘measured’ and predicted accelerations is minimized
until convergence is reached. The reconstructed profile is classified according to ISO and IRI
recommendations and compared to its original class. Results demonstrate that the approach is
feasible and that a good estimate of the short-wavelength features of the road profile can be
detected, despite the variability between the vehicles used to collect the data.
Type of Material
Conference Publication
Language
English
Status of Item
Not peer reviewed
Conference Details
Transport Research Arena Europe 2010, 7-10th June, Brussels, Belgium
This item is made available under a Creative Commons License
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