The Advanced Traffic Management System (ATMS) has been increasingly used by urban mobility managers to improve vehicular traffic management. Many ATMSs employ centralized solutions because of the difficulty of selecting the most relevant vehicles, in highly dynamic networks, to detect congestion and suggest alternative routes. Furthermore, such solutions are not always scalable. On the other hand, the distributed solution needs to previously segment the entire scenario to select the vehicles. Moreover, such a solution suggests alternative routes, in a selfish fashion, which can lead to secondary congestions. Based on the found open issues, this work proposes a distributed urban mobility management system based on the vehicular social networks paradigm (VSNs) named MAESTRO. The VSNs paradigm emerged from the integration of intelligent wireless communication devices and social networks in the vehicular environment. Two different approaches can be explored in VSNs, i.e., the Social network analysis (SNA) and the Social Network Concepts (SNC). The proposed MAESTRO system adopts a combined use of both SNA and SNC approaches. Simulation results showed that the use of SNA and SNC, in a vehicular environment, has great potential in increasing the scalability of the system and also improving efficiency in the management of urban mobility.