Detalhes bibliográficos
| Ano de defesa: |
2015 |
| Autor(a) principal: |
Freitas, Anderson Tavares de |
| Orientador(a): |
Não Informado pela instituição |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Não Informado pela instituição
|
| Programa de Pós-Graduação: |
Não Informado pela instituição
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: |
|
| Link de acesso: |
http://www.repositorio.ufc.br/handle/riufc/19099
|
Resumo: |
The Automated Fare Collection (AFC) produces information about the trips made in the Public Transportation System (PTS). The storage of such data produces time series which can be used to calculate statistics, yielding travel behavior patterns. Indeed, the AFC produces quality and easily reproducible data and its use is well established in the PTS of several cities in Brazil. However, it is used only for controlling the board and the collection of public transit. Thus, considering the difficulty of characterizing the PTS due to data collection and before the potential available for the use of AFC information, this work proposes to investigate the AFC's ability to provide relevant information on the characterization step in the planning transportation process. To sum up, the main goal of this research is to propose a methodology for characterization of the Public Transportation System from the Automated Fare Collection. Furthermore, we also seek to trace the origin-destination matrix which brings together the observed flows. Using the methodology proposed to characterize the PTS along with data validations of trips made on the public transport in the city of Fortaleza, we obtained specific results about public transport in the city. In addition, we confirmed the effectiveness of the methodology, by validating the matrix obtained from the AFC. In this way, we obtained the following results: demand behavior over time and space; number of trips made by line of bus and by user type; comparison between the origin of trip and the user's domicile; and recovery of the origin-destination matrix of public transport |
