APOLO: A Mobility Pattern Analysis Approach to Improve Urban Mobility

Autor(es)

Akabane, Ademar T. ; Gomes, Rafael L. ; Pazzi, Richard W. ; Madeira, Edmundo R. M. ; Villas, Leandro A. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE; v. N/A, p. 6-pg., 2017-01-01.

Resumo

Urban mobility becomes one of the most challenging issues in large urban centers, since traffic congestion is a daily problem. In order to address this issue, a number of researchers, from both academia and industry, have studied several Traffic Management Systems (TMS) approaches to improve urban mobility. However, the existing approaches do not consider an essential factor: the population information. Within this context, this work proposes a new approach, called APOLO, that employs historical knowledge of mobility patterns of the drivers to obtain a global view of road network. APOLO is different from others research approaches that need constant information exchange among the vehicles and the central server in order to obtain a global view of road traffic condition. These existing approaches can lead to network overload and have a high data processing cost in real-time. Results show that APOLO improves vehicles' mobility compared to well-known approaches, which indicates that APOLO could be a potential alternative for providing TMS services with valuable mobility knowledge. (AU)

• 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: 15/25588-6 - Gerenciamento distribuído de informação em redes sociais veiculares
• Beneficiário: Ademar Takeo Akabane
• Modalidade de apoio: Bolsas no Brasil - Doutorado