MobiWise: eco-routing decision support leveraging the internet of things
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/15542 |
Resumo: | Eco-routing distributes traffic in cities to improve mobility sustainability. The implementation of eco-routing in real-life requires a diverse set of information, including different kinds of sensors. These sensors are often already integrated in city infrastructure, some are technologically outdated, and are often operated by multiple entities. In this work, we provide a use case-oriented system design for an eco-routing service leveraging Internet-of-Things (IoT) technologies. The methodology involves six phases: (1) defining an eco-routing use case for a vehicle fleet; (2) formulating a routing problem as a multi-objective optimisation to divert traffic at a relevant hub facility; (3) identifying data sources and processing required information; (4) proposing a microservice-based architecture leveraging IoT technologies adequate to a multi-stakeholder scenario; (5) applying a microscopic traffic simulator as a digital twin to deal with data sparsity; and (6) visually illustrating eco-routing trade-offs to support decision making. We built a proof-of-concept for a mid-sized European city. Using real data and a calibrated digital twin, we would achieve hourly total emissions reductions up to 2.1%, when applied in a car fleet composed of 5% of eco-routing vehicles. This traffic diversion would allow annual carbon dioxide and nitrogen oxides savings of 400 tons and 1.2 tons, respectively. |
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MobiWise: eco-routing decision support leveraging the internet of thingsEco-routingInternet of thingsMulti objective optimisationDecision supportEco-routing distributes traffic in cities to improve mobility sustainability. The implementation of eco-routing in real-life requires a diverse set of information, including different kinds of sensors. These sensors are often already integrated in city infrastructure, some are technologically outdated, and are often operated by multiple entities. In this work, we provide a use case-oriented system design for an eco-routing service leveraging Internet-of-Things (IoT) technologies. The methodology involves six phases: (1) defining an eco-routing use case for a vehicle fleet; (2) formulating a routing problem as a multi-objective optimisation to divert traffic at a relevant hub facility; (3) identifying data sources and processing required information; (4) proposing a microservice-based architecture leveraging IoT technologies adequate to a multi-stakeholder scenario; (5) applying a microscopic traffic simulator as a digital twin to deal with data sparsity; and (6) visually illustrating eco-routing trade-offs to support decision making. We built a proof-of-concept for a mid-sized European city. Using real data and a calibrated digital twin, we would achieve hourly total emissions reductions up to 2.1%, when applied in a car fleet composed of 5% of eco-routing vehicles. This traffic diversion would allow annual carbon dioxide and nitrogen oxides savings of 400 tons and 1.2 tons, respectively.ElsevierRCIPLAguiar, AnaFernandes, PauloGuerreiro, Andreia P.Tomás, RicardoAgnelo, JoãoSantos, José LuísAraújo, FilipeCoelho, Margarida C.Fonseca, Carlos M.D'Orey, PedroLuís, MiguelSargento, Susana2023-02-10T13:38:37Z2022-102022-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/15542engA. Aguiar, P. Fernandes, A. Guerreiro, R. Tomás, J. Agnelo, J. L. Santos, F. Araújo, M. Coelho, C. Fonseca, P. d'Orey, M. Luís, S. Sargento, MobiWise: Eco-Routing Decision Support Leveraging the Internet of Things, in Sustainable Cities and Society, vol. 87, December 2022. DOI:10.1016/j.scs.2022.1041802210-670710.1016/j.scs.2022.104180info: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:RCAAP2023-08-03T10:13:11Zoai:repositorio.ipl.pt:10400.21/15542Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:23:11.691078Repositório 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 |
MobiWise: eco-routing decision support leveraging the internet of things |
title |
MobiWise: eco-routing decision support leveraging the internet of things |
spellingShingle |
MobiWise: eco-routing decision support leveraging the internet of things Aguiar, Ana Eco-routing Internet of things Multi objective optimisation Decision support |
title_short |
MobiWise: eco-routing decision support leveraging the internet of things |
title_full |
MobiWise: eco-routing decision support leveraging the internet of things |
title_fullStr |
MobiWise: eco-routing decision support leveraging the internet of things |
title_full_unstemmed |
MobiWise: eco-routing decision support leveraging the internet of things |
title_sort |
MobiWise: eco-routing decision support leveraging the internet of things |
author |
Aguiar, Ana |
author_facet |
Aguiar, Ana Fernandes, Paulo Guerreiro, Andreia P. Tomás, Ricardo Agnelo, João Santos, José Luís Araújo, Filipe Coelho, Margarida C. Fonseca, Carlos M. D'Orey, Pedro Luís, Miguel Sargento, Susana |
author_role |
author |
author2 |
Fernandes, Paulo Guerreiro, Andreia P. Tomás, Ricardo Agnelo, João Santos, José Luís Araújo, Filipe Coelho, Margarida C. Fonseca, Carlos M. D'Orey, Pedro Luís, Miguel Sargento, Susana |
author2_role |
author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Aguiar, Ana Fernandes, Paulo Guerreiro, Andreia P. Tomás, Ricardo Agnelo, João Santos, José Luís Araújo, Filipe Coelho, Margarida C. Fonseca, Carlos M. D'Orey, Pedro Luís, Miguel Sargento, Susana |
dc.subject.por.fl_str_mv |
Eco-routing Internet of things Multi objective optimisation Decision support |
topic |
Eco-routing Internet of things Multi objective optimisation Decision support |
description |
Eco-routing distributes traffic in cities to improve mobility sustainability. The implementation of eco-routing in real-life requires a diverse set of information, including different kinds of sensors. These sensors are often already integrated in city infrastructure, some are technologically outdated, and are often operated by multiple entities. In this work, we provide a use case-oriented system design for an eco-routing service leveraging Internet-of-Things (IoT) technologies. The methodology involves six phases: (1) defining an eco-routing use case for a vehicle fleet; (2) formulating a routing problem as a multi-objective optimisation to divert traffic at a relevant hub facility; (3) identifying data sources and processing required information; (4) proposing a microservice-based architecture leveraging IoT technologies adequate to a multi-stakeholder scenario; (5) applying a microscopic traffic simulator as a digital twin to deal with data sparsity; and (6) visually illustrating eco-routing trade-offs to support decision making. We built a proof-of-concept for a mid-sized European city. Using real data and a calibrated digital twin, we would achieve hourly total emissions reductions up to 2.1%, when applied in a car fleet composed of 5% of eco-routing vehicles. This traffic diversion would allow annual carbon dioxide and nitrogen oxides savings of 400 tons and 1.2 tons, respectively. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-10 2022-10-01T00:00:00Z 2023-02-10T13:38:37Z |
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/10400.21/15542 |
url |
http://hdl.handle.net/10400.21/15542 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
A. Aguiar, P. Fernandes, A. Guerreiro, R. Tomás, J. Agnelo, J. L. Santos, F. Araújo, M. Coelho, C. Fonseca, P. d'Orey, M. Luís, S. Sargento, MobiWise: Eco-Routing Decision Support Leveraging the Internet of Things, in Sustainable Cities and Society, vol. 87, December 2022. DOI:10.1016/j.scs.2022.104180 2210-6707 10.1016/j.scs.2022.104180 |
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.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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