Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining.
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/3/3138/tde-29032022-100650/ |
Resumo: | Smart Card Data (SCD) allow us to understand and to analyze mobility at an exceptional level of detail. However, they can be considered restricted when analyzing users trip purposes. Identifying travel patterns may provide better context to smart card data. More specifically, this identification may allow the understanding of travel patterns of transit users from precarious settlement areas, a portion of the population that historically has limited and unequal access to financial resources and opportunities. This work aims to understand the temporal and spatial patterns of urban transit movements of residents of precarious settlements in the city of São Paulo, through smart card data mining. For this, we apply three distinct clustering algorithms: K-means, TwoStep, and Self Organizing Maps (SOM). Residents of middle-class areas of the city are also included to compare the behavioral differences in urban displacements in the studied areas as a function of their residents household income. The results showed that the clusters formed by the three methods show similar results, and clusters with high number of commuters mostly composed by precarious settlement residents suggest an association of this residents with low-paid employment, with their smart card transactions, mainly registered in residential medium / high-income and residential low-income land use areas. |
id |
USP_37cc00af941c61a7f8dad4e9cbc3aac7 |
---|---|
oai_identifier_str |
oai:teses.usp.br:tde-29032022-100650 |
network_acronym_str |
USP |
network_name_str |
Biblioteca Digital de Teses e Dissertações da USP |
repository_id_str |
2721 |
spelling |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining.Análise de padrões de viagens de usuários de transporte público de assentamentos precários em São Paulo através da mineração de dados de bilhetagem.Clustering algorithmsEngenharia de transportesMineração de dadosMobilidade urbanaPlanejamento de transportesPrecarious settlementsSmart card dataTransportation planningTransporte públicoTravel patternsSmart Card Data (SCD) allow us to understand and to analyze mobility at an exceptional level of detail. However, they can be considered restricted when analyzing users trip purposes. Identifying travel patterns may provide better context to smart card data. More specifically, this identification may allow the understanding of travel patterns of transit users from precarious settlement areas, a portion of the population that historically has limited and unequal access to financial resources and opportunities. This work aims to understand the temporal and spatial patterns of urban transit movements of residents of precarious settlements in the city of São Paulo, through smart card data mining. For this, we apply three distinct clustering algorithms: K-means, TwoStep, and Self Organizing Maps (SOM). Residents of middle-class areas of the city are also included to compare the behavioral differences in urban displacements in the studied areas as a function of their residents household income. The results showed that the clusters formed by the three methods show similar results, and clusters with high number of commuters mostly composed by precarious settlement residents suggest an association of this residents with low-paid employment, with their smart card transactions, mainly registered in residential medium / high-income and residential low-income land use areas.Dados de bilhetagem permitem compreender e analisar a mobilidade em um nível de detalhe excepcional, porém podem ser considerados restritos para analisar as motivações de viagens dos usuários. A identificação de padrões de viagens pode dar complementariedade semântica aos dados de bilhetagem. Mais especificamente, esta análise de padrões de viagens, aplicada a usuários de transporte público residentes em áreas de assentamentos precários, auxilia uma melhor compreensão das características de mobilidade de uma parcela da população que, historicamente, tem acesso restrito e desigual aos recursos financeiros e às oportunidades no contexto urbano da cidade. O objetivo deste trabalho é compreender padrões temporais e espaciais dos deslocamentos urbanos por transporte público de residentes de assentamentos precários no município de São Paulo, através da mineração de dados de bilhetagem. Para tal, são aplicados três algoritmos de clusterização distintos: K-means, TwoStep e Self Organizing Maps (SOM). Também são incluídos residentes de áreas de classe média da cidade para analisar as diferenças de comportamento nos deslocamentos urbanos nas áreas estudadas em função da renda domiciliar de seus moradores. Os agrupamentos formados pelos três procedimentos apresentam resultados semelhantes. Grupos com passageiros com evidências de fluxo pendular de trabalho, compostos em sua maioria por moradores de assentamentos precários, sugerem uma associação desses moradores com empregos de baixa remuneração, com suas bilhetagens de atividade principalmente registradas em usos do solo residenciais de média / alta renda e residenciais de baixa renda.Biblioteca Digitais de Teses e Dissertações da USPGiannotti, Mariana AbrantesPieroni, Caio De Borthole Valente2018-12-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/3/3138/tde-29032022-100650/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2022-03-29T14:25:09Zoai:teses.usp.br:tde-29032022-100650Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212022-03-29T14:25:09Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. Análise de padrões de viagens de usuários de transporte público de assentamentos precários em São Paulo através da mineração de dados de bilhetagem. |
title |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. |
spellingShingle |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. Pieroni, Caio De Borthole Valente Clustering algorithms Engenharia de transportes Mineração de dados Mobilidade urbana Planejamento de transportes Precarious settlements Smart card data Transportation planning Transporte público Travel patterns |
title_short |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. |
title_full |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. |
title_fullStr |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. |
title_full_unstemmed |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. |
title_sort |
Analysis of travel patterns from precarious settlements transit users in São Paulo through smart card data mining. |
author |
Pieroni, Caio De Borthole Valente |
author_facet |
Pieroni, Caio De Borthole Valente |
author_role |
author |
dc.contributor.none.fl_str_mv |
Giannotti, Mariana Abrantes |
dc.contributor.author.fl_str_mv |
Pieroni, Caio De Borthole Valente |
dc.subject.por.fl_str_mv |
Clustering algorithms Engenharia de transportes Mineração de dados Mobilidade urbana Planejamento de transportes Precarious settlements Smart card data Transportation planning Transporte público Travel patterns |
topic |
Clustering algorithms Engenharia de transportes Mineração de dados Mobilidade urbana Planejamento de transportes Precarious settlements Smart card data Transportation planning Transporte público Travel patterns |
description |
Smart Card Data (SCD) allow us to understand and to analyze mobility at an exceptional level of detail. However, they can be considered restricted when analyzing users trip purposes. Identifying travel patterns may provide better context to smart card data. More specifically, this identification may allow the understanding of travel patterns of transit users from precarious settlement areas, a portion of the population that historically has limited and unequal access to financial resources and opportunities. This work aims to understand the temporal and spatial patterns of urban transit movements of residents of precarious settlements in the city of São Paulo, through smart card data mining. For this, we apply three distinct clustering algorithms: K-means, TwoStep, and Self Organizing Maps (SOM). Residents of middle-class areas of the city are also included to compare the behavioral differences in urban displacements in the studied areas as a function of their residents household income. The results showed that the clusters formed by the three methods show similar results, and clusters with high number of commuters mostly composed by precarious settlement residents suggest an association of this residents with low-paid employment, with their smart card transactions, mainly registered in residential medium / high-income and residential low-income land use areas. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-05 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/3/3138/tde-29032022-100650/ |
url |
https://www.teses.usp.br/teses/disponiveis/3/3138/tde-29032022-100650/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
_version_ |
1809091169346387968 |