Abstract
Even though companies that assess pavement condition compete to innovate by providing better software for automatic analysis and diagnosis, the industry as a whole remains limited, and data collection and storage methods are disparate. In fact, software and handling procedures are proprietary—each vendor has its own automated technology to detect, classify, and quantify surface distresses. In a research effort sponsored by the Ministry of Transportation of Ontario, Canada, the performance of sensor- and image-based pavement condition assessment was compared. First, a data management plan was created to allow efficient data manipulation. Second, a suitable set of similar distresses was selected as response variables of interest to design and conduct statistical experiments. Third, advanced analysis of variance was performed to allow statistical data comparisons among companies and among automated technologies. Finally, results were discussed and recommendations made. Overall, service provider measurements ...
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More From: Transportation Research Record: Journal of the Transportation Research Board
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