Statistical and semi-dynamical road traffic noise models comparison with field measurements
Autor(a) principal: | |
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Data de Publicação: | 2018 |
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/10773/26267 |
Resumo: | The need for road traffic noise monitoring is growing in urban areas due to the growth of vehicles number and to the consequent increase of risk for human health. Noise measurements cannot be performed everywhere, or even in a large number of sites, because of high costs and time consumption. For this reasons, Road Traffic Noise predictive Models (RTNMs) can be implemented to estimate the noise levels at any distance, knowing certain parameters needed as input of the RTNM. In this paper, the main statistical RTNMs are presented, together with the implementation of two innovative and advanced models: the EU suggested model (CNOSSOS-EU) and a research model presented by Quartieri et al. (2010). These models will be compared with noise measurements performed in different sites and with different traffic conditions, in order to avoid bias from geometry or other features of the area under study. The main conclusion is that the application of innovative models and the inclusion of dynamical information about traffic flow, will lead to better results with respect to statistical models. |
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Statistical and semi-dynamical road traffic noise models comparison with field measurementsThe need for road traffic noise monitoring is growing in urban areas due to the growth of vehicles number and to the consequent increase of risk for human health. Noise measurements cannot be performed everywhere, or even in a large number of sites, because of high costs and time consumption. For this reasons, Road Traffic Noise predictive Models (RTNMs) can be implemented to estimate the noise levels at any distance, knowing certain parameters needed as input of the RTNM. In this paper, the main statistical RTNMs are presented, together with the implementation of two innovative and advanced models: the EU suggested model (CNOSSOS-EU) and a research model presented by Quartieri et al. (2010). These models will be compared with noise measurements performed in different sites and with different traffic conditions, in order to avoid bias from geometry or other features of the area under study. The main conclusion is that the application of innovative models and the inclusion of dynamical information about traffic flow, will lead to better results with respect to statistical models.American Institute of Physics2019-06-28T15:49:19Z2018-07-01T00:00:00Z2018-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/26267eng0094-243X10.1063/1.5045445Guarnaccia, ClaudioBandeira, JorgeCoelho, Margarida C.Fernandes, PauloTeixeira, JoãoIoannidis, GeorgeQuartieri, Josephinfo: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:RCAAP2024-02-22T11:50:49Zoai:ria.ua.pt:10773/26267Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:59:17.412338Repositório 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 |
Statistical and semi-dynamical road traffic noise models comparison with field measurements |
title |
Statistical and semi-dynamical road traffic noise models comparison with field measurements |
spellingShingle |
Statistical and semi-dynamical road traffic noise models comparison with field measurements Guarnaccia, Claudio |
title_short |
Statistical and semi-dynamical road traffic noise models comparison with field measurements |
title_full |
Statistical and semi-dynamical road traffic noise models comparison with field measurements |
title_fullStr |
Statistical and semi-dynamical road traffic noise models comparison with field measurements |
title_full_unstemmed |
Statistical and semi-dynamical road traffic noise models comparison with field measurements |
title_sort |
Statistical and semi-dynamical road traffic noise models comparison with field measurements |
author |
Guarnaccia, Claudio |
author_facet |
Guarnaccia, Claudio Bandeira, Jorge Coelho, Margarida C. Fernandes, Paulo Teixeira, João Ioannidis, George Quartieri, Joseph |
author_role |
author |
author2 |
Bandeira, Jorge Coelho, Margarida C. Fernandes, Paulo Teixeira, João Ioannidis, George Quartieri, Joseph |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Guarnaccia, Claudio Bandeira, Jorge Coelho, Margarida C. Fernandes, Paulo Teixeira, João Ioannidis, George Quartieri, Joseph |
description |
The need for road traffic noise monitoring is growing in urban areas due to the growth of vehicles number and to the consequent increase of risk for human health. Noise measurements cannot be performed everywhere, or even in a large number of sites, because of high costs and time consumption. For this reasons, Road Traffic Noise predictive Models (RTNMs) can be implemented to estimate the noise levels at any distance, knowing certain parameters needed as input of the RTNM. In this paper, the main statistical RTNMs are presented, together with the implementation of two innovative and advanced models: the EU suggested model (CNOSSOS-EU) and a research model presented by Quartieri et al. (2010). These models will be compared with noise measurements performed in different sites and with different traffic conditions, in order to avoid bias from geometry or other features of the area under study. The main conclusion is that the application of innovative models and the inclusion of dynamical information about traffic flow, will lead to better results with respect to statistical models. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-07-01T00:00:00Z 2018-07 2019-06-28T15:49:19Z |
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/10773/26267 |
url |
http://hdl.handle.net/10773/26267 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0094-243X 10.1063/1.5045445 |
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 |
American Institute of Physics |
publisher.none.fl_str_mv |
American Institute of Physics |
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 |
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1799137647296249856 |