Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types
Autor(a) principal: | |
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Data de Publicação: | 2021 |
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/10773/32425 |
Resumo: | The environmental impact of connected and autonomous vehicles (CAVs) is still uncertain. Little is known about how CAVs operational behavior influences the environmental performance of network traffic, including conventional vehicles (CVs). In this paper, a microscopic traffic and emission modeling platform was applied to simulate CAVs operation in Motorway, Rural, and Urban road sections of a medium-sized European city, assuming different configurations of the car-following model parameters associated with a pre-determined or cooperative adaptative behavior of the CAVs. The main contribution is to evaluate the impact of the CAVs operation on the distribution of accelerations, Vehicle Specific Power (VSP) modal distribution, carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for different road types and Market Penetration Rates (MPR). Results suggest CAVs operational behavior can affect CVs environmental performance either positively or negatively, depending on the driving settings and road type. It was found network-wide CO2 varies between savings of 18% and an increase of 4%, depending on the road type and MPR. CAVs adjusted driving settings allowed minimization of system NOx up to 13-23% for MPR ranging between 10 and 90%. These findings may support policymakers and traffic planners in developing strategies to better accommodate CAVs in a sustainable way. |
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Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road typesCar-following adjustment parametersConnected and automated vehiclesDriving behaviorMicrosimulationPollutant emissionsThe environmental impact of connected and autonomous vehicles (CAVs) is still uncertain. Little is known about how CAVs operational behavior influences the environmental performance of network traffic, including conventional vehicles (CVs). In this paper, a microscopic traffic and emission modeling platform was applied to simulate CAVs operation in Motorway, Rural, and Urban road sections of a medium-sized European city, assuming different configurations of the car-following model parameters associated with a pre-determined or cooperative adaptative behavior of the CAVs. The main contribution is to evaluate the impact of the CAVs operation on the distribution of accelerations, Vehicle Specific Power (VSP) modal distribution, carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for different road types and Market Penetration Rates (MPR). Results suggest CAVs operational behavior can affect CVs environmental performance either positively or negatively, depending on the driving settings and road type. It was found network-wide CO2 varies between savings of 18% and an increase of 4%, depending on the road type and MPR. CAVs adjusted driving settings allowed minimization of system NOx up to 13-23% for MPR ranging between 10 and 90%. These findings may support policymakers and traffic planners in developing strategies to better accommodate CAVs in a sustainable way.IEEE2021-10-19T16:50:29Z2021-09-15T00:00:00Z2021-09-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/32425eng10.1109/OJITS.2021.3112904Bandeira, Jorge M.Macedo, EloísaFernandes, PauloRodrigues, MónicaAndrade, MárioCoelho, Margarida C.info: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:RCAAP2024-02-22T12:02:29Zoai:ria.ua.pt:10773/32425Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:04:05.218756Repositório 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 |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types |
title |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types |
spellingShingle |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types Bandeira, Jorge M. Car-following adjustment parameters Connected and automated vehicles Driving behavior Microsimulation Pollutant emissions |
title_short |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types |
title_full |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types |
title_fullStr |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types |
title_full_unstemmed |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types |
title_sort |
Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types |
author |
Bandeira, Jorge M. |
author_facet |
Bandeira, Jorge M. Macedo, Eloísa Fernandes, Paulo Rodrigues, Mónica Andrade, Mário Coelho, Margarida C. |
author_role |
author |
author2 |
Macedo, Eloísa Fernandes, Paulo Rodrigues, Mónica Andrade, Mário Coelho, Margarida C. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Bandeira, Jorge M. Macedo, Eloísa Fernandes, Paulo Rodrigues, Mónica Andrade, Mário Coelho, Margarida C. |
dc.subject.por.fl_str_mv |
Car-following adjustment parameters Connected and automated vehicles Driving behavior Microsimulation Pollutant emissions |
topic |
Car-following adjustment parameters Connected and automated vehicles Driving behavior Microsimulation Pollutant emissions |
description |
The environmental impact of connected and autonomous vehicles (CAVs) is still uncertain. Little is known about how CAVs operational behavior influences the environmental performance of network traffic, including conventional vehicles (CVs). In this paper, a microscopic traffic and emission modeling platform was applied to simulate CAVs operation in Motorway, Rural, and Urban road sections of a medium-sized European city, assuming different configurations of the car-following model parameters associated with a pre-determined or cooperative adaptative behavior of the CAVs. The main contribution is to evaluate the impact of the CAVs operation on the distribution of accelerations, Vehicle Specific Power (VSP) modal distribution, carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for different road types and Market Penetration Rates (MPR). Results suggest CAVs operational behavior can affect CVs environmental performance either positively or negatively, depending on the driving settings and road type. It was found network-wide CO2 varies between savings of 18% and an increase of 4%, depending on the road type and MPR. CAVs adjusted driving settings allowed minimization of system NOx up to 13-23% for MPR ranging between 10 and 90%. These findings may support policymakers and traffic planners in developing strategies to better accommodate CAVs in a sustainable way. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10-19T16:50:29Z 2021-09-15T00:00:00Z 2021-09-15 |
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/10773/32425 |
url |
http://hdl.handle.net/10773/32425 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1109/OJITS.2021.3112904 |
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 |
IEEE |
publisher.none.fl_str_mv |
IEEE |
dc.source.none.fl_str_mv |
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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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1799137696489144320 |