Spatio-temporal forecasts for bike availability in dockless bike sharing systems

Detalhes bibliográficos
Autor(a) principal: Meer, Lucas van der
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/67512
Resumo: Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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spelling Spatio-temporal forecasts for bike availability in dockless bike sharing systemsDockless bike sharing systemsBike availabilityForecastingTime series analysisSustainable transportDissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesForecasting bike availability is of great importance when turning the shared bike into a reliable, pleasant and uncomplicated mode of transport. Several approaches have been developed to forecast bike availability in station-based bike sharing systems. However, dockless bike sharing systems remain fairly unexplored in that sense, despite their rapid expansion over the world in recent years. To fill this gap, this thesis aims to develop a generally applicable methodology for bike availability forecasting in dockless bike sharing systems, that produces automated, fast and accurate forecasts. To balance speed and accuracy, an approach is taken in which the system area of a dockless bike sharing system is divided into spatially contiguous clusters that represent locations with the same temporal patterns in the historical data. Each cluster gets assigned a model point, for which an ARIMA(p,d,q) forecasting model is fitted to the deseasonalized data. Each individual forecast will inherit the structure and parameters of one of those pre-build models, rather than building a new model on its own. The proposed system was tested through a case study in San Francisco, California. The results showed that the proposed system outperforms simple baseline methods. However, they also highlighted the limited forecastability of dockless bike sharing data.Pebesma, EdzerMateu Mahiques, JorgeSilva, Joel Dinis Baptista Ferreira daRUNMeer, Lucas van der2019-04-24T10:12:40Z2019-02-042019-02-04T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/67512TID:202227626enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:31:55Zoai:run.unl.pt:10362/67512Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:34:37.751743Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Spatio-temporal forecasts for bike availability in dockless bike sharing systems
title Spatio-temporal forecasts for bike availability in dockless bike sharing systems
spellingShingle Spatio-temporal forecasts for bike availability in dockless bike sharing systems
Meer, Lucas van der
Dockless bike sharing systems
Bike availability
Forecasting
Time series analysis
Sustainable transport
title_short Spatio-temporal forecasts for bike availability in dockless bike sharing systems
title_full Spatio-temporal forecasts for bike availability in dockless bike sharing systems
title_fullStr Spatio-temporal forecasts for bike availability in dockless bike sharing systems
title_full_unstemmed Spatio-temporal forecasts for bike availability in dockless bike sharing systems
title_sort Spatio-temporal forecasts for bike availability in dockless bike sharing systems
author Meer, Lucas van der
author_facet Meer, Lucas van der
author_role author
dc.contributor.none.fl_str_mv Pebesma, Edzer
Mateu Mahiques, Jorge
Silva, Joel Dinis Baptista Ferreira da
RUN
dc.contributor.author.fl_str_mv Meer, Lucas van der
dc.subject.por.fl_str_mv Dockless bike sharing systems
Bike availability
Forecasting
Time series analysis
Sustainable transport
topic Dockless bike sharing systems
Bike availability
Forecasting
Time series analysis
Sustainable transport
description Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
publishDate 2019
dc.date.none.fl_str_mv 2019-04-24T10:12:40Z
2019-02-04
2019-02-04T00:00:00Z
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 http://hdl.handle.net/10362/67512
TID:202227626
url http://hdl.handle.net/10362/67512
identifier_str_mv TID:202227626
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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