Exploiting Vehicular Social Networks and Dynamic Clustering to Enhance Urban Mobility Management

Author(s)

Akabane, Ademar Takeo ^{[1, 2]} ; Immich, Roger ^[1] ; Pazzi, Richard Wenner ^[2] ; Mauro Madeira, Edmundo Roberto ^[1] ; Villas, Leandro Aparecido ^[1]

Affiliation

^[1] Univ Estadual Campinas, UNICAMP, IC, 1251 Albert Einstein Av, BR-13083 Campinas, SP - Brazil

^[2] Ontario Tech Univ, FBIT, 2000 Simcoe St N, Oshawa, ON L1H 7K4 - Canada

• Document type: Journal article
• Source: SENSORS; v. 19, n. 16 AUG 20 2019.
• Web of Science Citations: 0

Abstract

Transport authorities are employing advanced traffic management system (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the abovementioned ones, such as vehicular networks and 5G. In ATMS, the centralized approach to detect congestion and calculate alternative routes is one of the most adopted because of the difficulty of selecting the most appropriate vehicles in highly dynamic networks. The advantage of this approach is that it takes into consideration the scenario to its full extent at every execution. On the other hand, the distributed solution needs to previously segment the entire scenario to select the vehicles. Additionally, such solutions suggest alternative routes in a selfish fashion, which can lead to secondary congestions. These open issues have inspired the proposal of a distributed system of urban mobility management based on a collaborative approach in vehicular social networks (VSNs), named SOPHIA. The VSN paradigm has emerged from the integration of mobile communication devices and their social relationships in the vehicular environment. Therefore, social network analysis (SNA) and social network concepts (SNC) are two approaches that can be explored in VSNs. Our proposed solution adopts both SNA and SNC approaches for alternative route-planning in a collaborative way. Additionally, we used dynamic clustering to select the most appropriate vehicles in a distributed manner. Simulation results confirmed that the combined use of SNA, SNC, and dynamic clustering, in the vehicular environment, have great potential in increasing system scalability as well as improving urban mobility management efficiency. (AU)

• FAPESP's process: 15/25588-6 - Distributed Information Management in Vehicular Social Networks
• Grantee: Ademar Takeo Akabane
• Support type: Scholarships in Brazil - Doctorate
• FAPESP's process: 14/50937-1 - INCT 2014: from the Internet of the Future
• Grantee: Fabio Kon
• Support type: Research Projects - Thematic Grants
• FAPESP's process: 16/24454-9 - In-network Data Aggregation in VANETs
• Grantee: Ademar Takeo Akabane
• Support type: Scholarships abroad - Research Internship - Doctorate
• FAPESP's process: 18/02204-6 - Efficient and resilient video delivery in smart cities
• Grantee: Roger Kreutz Immich
• Support type: Scholarships in Brazil - Post-Doctorate