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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

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

Texto completo
Autor(es):
Akabane, Ademar Takeo [1, 2] ; Immich, Roger [1] ; Pazzi, Richard Wenner [2] ; Mauro Madeira, Edmundo Roberto [1] ; Villas, Leandro Aparecido [1]
Número total de Autores: 5
Afiliação do(s) autor(es):
[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
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: SENSORS; v. 19, n. 16 AUG 20 2019.
Citações Web of Science: 0
Resumo

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)

Processo FAPESP: 15/25588-6 - Gerenciamento distribuído de informação em redes sociais veiculares
Beneficiário:Ademar Takeo Akabane
Modalidade de apoio: Bolsas no Brasil - Doutorado
Processo FAPESP: 14/50937-1 - INCT 2014: da Internet do Futuro
Beneficiário:Fabio Kon
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 16/24454-9 - Agregação de Dados em VANETs
Beneficiário:Ademar Takeo Akabane
Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
Processo FAPESP: 18/02204-6 - Transmissão de vídeo eficiente e resiliente em cidades inteligentes
Beneficiário:Roger Kreutz Immich
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado