LAUSR

Abstract Pavement-surface characteristics should be considered during road maintenance for safe and comfortable driving. A detailed and up-to-date report of road-pavement network conditions is required to optimize a maintenance plan. However, manual road inspection methods, such as periodic visual surveys, are time-consuming and expensive. A common technology used to address this issue is SmartRoadSense, a collaborative system for the automatic detection of road-surface characteristics using Global Positioning System receivers and triaxial accelerometers contained in mobile devices. In this study, the results of the SmartRoadSense surveys conducted on Provincial Road 2 (SP2) in Salerno, Italy, were compared with the Distress Cadastre data for the same province and the pavement condition indices of different sections of the SP2. Although the effectiveness of the crowdsensing-based SmartRoadSense was found to vary with the distress type, the system was confirmed to be very efficient for monitoring the most critical road failures.