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Entree


ATRIP: Architecture for Traffic Classification Based on Image Processing

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Autor(es):
Cristiani, Andre Luis ; Immich, Roger ; Akabane, Ademar T. ; Mauro Madeira, Edmundo Roberto ; Villas, Leandro Aparecido ; Meneguette, Rodolfo, I
Número total de Autores: 6
Tipo de documento: Artigo Científico
Fonte: VEHICLES; v. 2, n. 2, p. 15-pg., 2020-06-01.
Resumo

With the increase of vehicles in large urban centers, there is also an increase in the number of traffic jams and accidents on public roads. The development of a proper Intelligent Transport System (ITS) could help to alleviate these problems by assisting the drivers on route selections to avoid the most congested road sections. Therefore, to improve on this issue, this work proposes an architecture to aid an ITS to detect, analyze, and classify the traffic flow conditions in real time. This architecture also provides a control room dashboard to visualize the information and notify the users about the live traffic conditions. To this end, the proposed solution takes advantage of computer vision concepts to extract the maximum information about the roads to better assess and keep the drivers posted about the traffic conditions on selected highways. The main contribution of the proposed architecture is to perform the detection and classification of the flow of vehicles regardless of the luminosity conditions. In order to evaluate the efficiency of the proposed solution, a testbed was designed. The obtained results show that the accuracy of the traffic classification rate is up to 90% in daylight environments and up to 70% in low light environments when compared with the related literature. (AU)

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
Processo FAPESP: 14/50937-1 - INCT 2014: da Internet do Futuro
Beneficiário:Fabio Kon
Modalidade de apoio: Auxílio à Pesquisa - Temático