Designing and Building an Intelligent Pavement Management System for Urban Road Networks

Pavement maintenance plays a significant role in megacities. Managing complaints and scheduling road reviews are the two concerns under intelligent pavement management system (PMS) plan. In contrast, if damages not treated immediately, they will increase over time. By leveraging accurate data from sensors, smart PMS improve capability, support sustainability, drive economic growth network. This research aimed to elaborate on different modules of an city network advance sustainable city. First, 3D mobile light detection ranging (LiDAR) sensor, accompanied by camera, was applied as collection tool. Although LiDAR have gained popularity, lack precise distresses, including cracks. As result, utilizing RGB imaging may help detect distresses properly. Two approaches were integrated alongside conducting analysis this paper: (1) ArcGIS pro, developed Esri Inc., which includes noise removal, digital elevation model (DEM) generation, building footprint extraction; (2) Mechanistic-Empirical Design Guide (AASHTOWare PMED), used assess site specifications such traffic, weather, subbase, current conditions effort design most appropriate for each section. For visualization module, CityEngine (a software Esri) provide model. After implementing methodology, we drew following conclusions: using AASHTOWare PMED method make decisions about rehabilitation(M&R) actions can significantly speed up decision-making process, essentially saving time money shortening project’s duration; similar, geographical information (GIS)-based consistent M&R strategies, i.e., interference human factors is less significant.