Assessment of automated technologies in Texas for pavement distress identification, texture, and cross slope measurement

dc.contributor.advisorProzzi, Jorge Alberto
dc.creatorBurton, Maria Christinaen
dc.date.accessioned2014-09-11T21:16:43Zen
dc.date.accessioned2018-01-22T22:26:24Z
dc.date.available2018-01-22T22:26:24Z
dc.date.issued2014-05en
dc.date.submittedMay 2014en
dc.date.updated2014-09-11T21:16:43Zen
dc.descriptiontexten
dc.description.abstractAutomated technologies can be beneficial for collecting data on the condition of pavements. As opposed to a traditional manual survey of the road, automated data collection can provide a safer alternative that is objective, repeatable, and consistent, while traveling at highway speeds. Though the automated method is preferred, it still needs to be reliable enough to accurately model the current pavement performance. The Texas Department of Transportation (TxDOT) initiated a project to allow an independent assessment of the accuracy and repeatability of new automated distress data measurements. In this study, 20 550-ft. pavement sections were tested with automated data collection technologies. The sections were located in Austin and Waco Districts. The accuracy and repeatability was evaluated for cracking and other distress measurements, cross slope measurements, and texture measurements. Known manual methods were used as a reference, and a 3D system developed by TxDOT was compared with three systems of other vendors (Dynatest, Fugro, and Waylink-OSU). With the data provided for the texture and cross slope, an additional investigation was done to evaluate hydroplaning potential. This thesis reports in the latter investigation.en
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/25855en
dc.language.isoenen
dc.subjectAutomated data collectionen
dc.subjectTexasen
dc.subjectPavementen
dc.subjectDistressen
dc.subjectTextureen
dc.subjectCross slopeen
dc.subjectPavement managementen
dc.titleAssessment of automated technologies in Texas for pavement distress identification, texture, and cross slope measurementen
dc.typeThesisen

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