Análise da densidade do fluxo de veículos no centro de Belo Horizonte, Minas Gerais

• Ano de defesa: 2019
• Autor(a) principal: Gabriel Luís Nogueira de Oliveira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; IGC - INSTITUTO DE GEOCIENCIAS; Programa de Pós-Graduação em Análise e Modelagem de Sistemas Ambientais; UFMG
• Palavras-chave em Português: Trânsito; Fluxo; Centro de Belo Horizonte; Coleta de dados; Google Maps; Modelo
• Link de acesso: http://hdl.handle.net/1843/31004

Belo Horizonte is the brazilian capital with largest number of vehicles per inhabitant. One the biggest discontent of its passersby is the intense traffic they face daily. In view of that problem and every its causer factors, like automotive vehicles popularization, disordered urbanization, demand attendance capacity, among others, it’s necessary to engage efforts to better understand the phenomenon of traffic in Brazilian cities. The objective of this work is to propose an alternative to collect data about the traffic of Minas Gerais’ capital downtown in an automated way, besides analyzing the dataset. The gathering model works through a bot capable of performing any computational task, but it has been programmed to take and save screenshots of the traffic layer available on Google Maps. A total of 8050 images were obtained during an uninterrupted month, from which qualitative data about the traffic in the downtown were extracted. The analysis was divided into two parts: a summary /descriptive analysis of cutouts, and one with a simple regression model, for a specific period of time. The result of the summarization confirm the traffic situation perceived by the inhabitants, but more accurately it points some crucial information for understanding the phenomenon, such as the time of rise and decline of the range of peaks. The regression model, in its turn, presented a satisfactory adjustment and an indicator of the rise of traffic flow intensity for the afternoon period on business days.