The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

Detalhes bibliográficos
Autor(a) principal: Ferreira, João Carlos
Data de Publicação: 2015
Outros Autores: Almeida, José de, Silva, Alberto Rodrigues da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.21/5752
Resumo: This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.
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spelling The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery processDriver profileEco-drivingFuel efficiencyData warehouseKnowledge discovery (KD)Public transportationThis paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.IEEE-Institute Electrical Electronics Engineers INCRCIPLFerreira, João CarlosAlmeida, José deSilva, Alberto Rodrigues da2016-02-26T11:21:51Z2015-102015-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/5752engFERREIRA, João Carlos; ALMEIDA, José de; SILVA, Alberto Rodrigues da - The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process. IEEE Transactions on Intelligent Transportation Systems. ISSN. 1524-9050. Vol. 16. N.º 5 (2015), pp. 2653-26621524-905010.1109/TITS.2015.2414663metadata only accessinfo: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:RCAAP2023-08-03T09:49:37Zoai:repositorio.ipl.pt:10400.21/5752Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:14:59.562251Repositório 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 The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
title The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
spellingShingle The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
Ferreira, João Carlos
Driver profile
Eco-driving
Fuel efficiency
Data warehouse
Knowledge discovery (KD)
Public transportation
title_short The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
title_full The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
title_fullStr The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
title_full_unstemmed The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
title_sort The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process
author Ferreira, João Carlos
author_facet Ferreira, João Carlos
Almeida, José de
Silva, Alberto Rodrigues da
author_role author
author2 Almeida, José de
Silva, Alberto Rodrigues da
author2_role author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Ferreira, João Carlos
Almeida, José de
Silva, Alberto Rodrigues da
dc.subject.por.fl_str_mv Driver profile
Eco-driving
Fuel efficiency
Data warehouse
Knowledge discovery (KD)
Public transportation
topic Driver profile
Eco-driving
Fuel efficiency
Data warehouse
Knowledge discovery (KD)
Public transportation
description This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.
publishDate 2015
dc.date.none.fl_str_mv 2015-10
2015-10-01T00:00:00Z
2016-02-26T11:21:51Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/5752
url http://hdl.handle.net/10400.21/5752
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv FERREIRA, João Carlos; ALMEIDA, José de; SILVA, Alberto Rodrigues da - The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process. IEEE Transactions on Intelligent Transportation Systems. ISSN. 1524-9050. Vol. 16. N.º 5 (2015), pp. 2653-2662
1524-9050
10.1109/TITS.2015.2414663
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE-Institute Electrical Electronics Engineers INC
publisher.none.fl_str_mv IEEE-Institute Electrical Electronics Engineers INC
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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