Abstract
Pavement management systems rely on accurate distress measurements to support transportation agency officials in making decisions on budget planning and allocation as well as on the design of maintenance and rehabilitation strategies. Errors in distress data measurements lead to inappropriate project prioritization and increased maintenance and rehabilitation costs. This paper presents an independent evaluation of the accuracy and precision of high-speed field measurements of pavement cracking taken by three different automatic three-dimensional (3D) systems that represent the state of the practice. Cracking data were collected from a field experiment designed to represent typical conditions encountered in Texas highway network and comprised twenty 550-ft pavement sections. Three vendors participated in the experiment; two of them used the same hardware (i.e., INO LCMS sensors) but different proprietary algorithms to detect and quantify surface distresses. The third vendor used PaveVision sensors. The high-speed measurements were compared to manual measurements taken statically by experienced certified raters. Further, each service provider was asked to report their results with different levels of manual intervention in order to capture the change in accuracy due to manual postprocessing of the data. The large number of false positives and low overall accuracy and precision showed by the three automated systems highlights the need for improvements on the available high-speed data collection technologies. The accuracy, along with the amount of false positives, significantly improved after applying manual postprocessing. The precision, on the other hand, was similar. In addition, a weak association between cracking measurement accuracy and surface texture was observed for every automated system.
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Published In
Journal of Transportation Engineering
Volume 142 • Issue 6 • June 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Jul 7, 2015
Accepted: Dec 8, 2015
Published online: Feb 25, 2016
Published in print: Jun 1, 2016
Discussion open until: Jul 25, 2016
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