Applying Social Networking to Enhance Urban Mobility Management
Abstract
The Advanced Traffic Management System (ATMS) is increasingly used by urban mobility managers to improve vehicular traffic management. Many ATMS employ centralized solutions because of the difficulty of selecting the most relevant vehicles in highly dynamic networks to detect congestion and suggest alternative routes. Moreover, such solutions are not always scalable. On the other hand, the distributed solution needs to segment the entire scenario before selecting vehicles. In addition, such a solution selfishly suggests alternative routes that can lead to secondary congestion. Based on these gaps, a distributed urban mobility management system based on the vehicular social networks (VSNs) paradigm called MAESTRO was proposed. This paradigm arose from the integration of wireless communication devices and social networks in the vehicular environment. Thus two different approaches can be explored in VSNs: Social Network Analysis (SNA) and Social Network Concepts (SNC). Both approaches were applied in the MAESTRO system. Simulation results showed that the use of ANS and CNS in the vehicular environment has great potential to increase system scalability and also improve efficiency in urban mobility management.
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