Statistical and semi-dynamical road traffic noise models comparison with field measurements

Detalhes bibliográficos
Autor(a) principal: Guarnaccia, Claudio
Data de Publicação: 2018
Outros Autores: Bandeira, Jorge, Coelho, Margarida C., Fernandes, Paulo, Teixeira, João, Ioannidis, George, Quartieri, Joseph
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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spelling 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
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/26267
url http://hdl.handle.net/10773/26267
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language eng
dc.relation.none.fl_str_mv 0094-243X
10.1063/1.5045445
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dc.publisher.none.fl_str_mv American Institute of Physics
publisher.none.fl_str_mv American Institute of Physics
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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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