Análise da rede de transporte público de Curitiba como rede complexa

• Ano de defesa: 2017
• Autor(a) principal: Silva, Emerson Luiz Chiesse da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial; UTFPR
• Palavras-chave em Português: Transporte urbano - Curitiba (PR); Teoria dos grafos; Análise por agrupamento; Projeto de sistemas; Análise de sistemas; Engenharia elétrica; Urban transportation - Curitiba (PR); Graph theory; Cluster analysis; System design; System analysis; Electric engineering; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::MATEMATICA DA COMPUTACAO::MODELOS ANALITICOS E DE SIMULACAO; Engenharia Elétrica
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/2818

Public transportation systems (PTS) are complex entities composed by many different subsystems (administration, vehicles management and maintenance, security, taxing, trafic engineering, urbanism, human resources and others). PTS offers various routes using public sharing vehicules to serve users, and the route planning is one of the issues that demand attention and has hard performance assessment. This routes form meshes in many types of representation, e. g., vehicle stops as nodes and a route as a sequence of links that connect their nodes. From PTS representation as graphs, it is possible to extract valuable informations from metrics as dimensions, centralities, weight and others, and to classify this PTS within some model already studied. Towards established models, system enhancements can be proposed and posterior re- analysis of such improved systems can justify or not their implementation in the real system. At this work a public transport system was analysed as Complex Network, specifically Curitiba’s PTS, (Paraná, Brazil). Here it was demonstrated that this system, represented in l-space, has network characteristics of scale-free networks. This system has eleven bus routes categories, in which main categories were analysed as complex networks to assess their influence on whole system metrics. Additionally, combining both complex network metrics and k-means method on this PTS, geographic areas of the city showing best and worst connectivity characteristics for the inhabitants of Curitiba were identified, which allows detecting potential transportation system weakness. This study revealed that Curitiba’s central region is best served, and some periphericals areas at southeast and northeast have low public transportation service.