Distributed Services for Pavement Anomaly Detection in Smart Roads

Digital transition is characterizing all the components of our world. Considering transport infrastructures, for maximizing safety and comfort of users while driving, the exploitation of multiple powerful sensors and data analysis capabilities is a primary research and development goal. In this context, the digital road transport infrastructures (“Smart Roads”) will represent complex and integrated systems combining physical and digital assets for ensuring roads with information, sensing, and acting capabilities. In view of these goals and this transition, the management of the asset condition plays a strategic role, especially considering road physical components and, mainly, the pavement, on which vehicles move. In this paper, accordingly, the authors describe a methodological approach for implementing an innovative architecture of advanced digital services in Smart Roads, based on the distributed computing paradigms of Edge and Cloud. This approach combines continuous and multiple data acquired by reliable, simple, smart, and connected sensors in vehicles on a cloud-based management platform to estimate the pavement “health-state”. This may significantly improve control of condition of the asset critical segments, for optimizing planning of more accurate high-performance survey and, thus, implement maintenance and rehabilitation programs.