Prediction of road traffic noise in the vicinity of trunk roads in Japan using Digital Road Map Platform

Areas in the vicinity of trunk roads are exposed to high levels of noise and may pose high health risks to residents. To assess the health risks and formulate effective noise mitigation measures, prediction of road traffic noise is crucial. Addressing this issue, the author has developed a road traf...

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Published inAcoustical Science and Technology Vol. 46; no. 4; pp. 480 - 485
Main Author Tagusari, Junta
Format Journal Article
LanguageEnglish
Published ACOUSTICAL SOCIETY OF JAPAN 01.07.2025
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ISSN1346-3969
1347-5177
DOI10.1250/ast.e24.50

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Abstract Areas in the vicinity of trunk roads are exposed to high levels of noise and may pose high health risks to residents. To assess the health risks and formulate effective noise mitigation measures, prediction of road traffic noise is crucial. Addressing this issue, the author has developed a road traffic noise prediction system that allows prediction of sound levels using a database of road network. The objective of the present study was to predict road traffic noise in the vicinity of the trunk roads using a Digital Road Map Platform (DRM-PF) database, which contains nationwide road geometries and traffic settings of trunk roads. Predicted sound levels were compared with actual measurements and noise maps were created to demonstrate the feasibility of assessing noise exposure and associated health risks in the vicinity of trunk roads in Japan. The results show a generally good agreement between predicted and measured levels, while challenges remain in accurate prediction in a number of environments, mainly due to the lack of accurate geometries. The extensive coverage of the DRM-PF database throughout Japan enables noise mapping in arbitrary regions near trunk roads, which would contribute to making noise policy.
AbstractList Areas in the vicinity of trunk roads are exposed to high levels of noise and may pose high health risks to residents. To assess the health risks and formulate effective noise mitigation measures, prediction of road traffic noise is crucial. Addressing this issue, the author has developed a road traffic noise prediction system that allows prediction of sound levels using a database of road network. The objective of the present study was to predict road traffic noise in the vicinity of the trunk roads using a Digital Road Map Platform (DRM-PF) database, which contains nationwide road geometries and traffic settings of trunk roads. Predicted sound levels were compared with actual measurements and noise maps were created to demonstrate the feasibility of assessing noise exposure and associated health risks in the vicinity of trunk roads in Japan. The results show a generally good agreement between predicted and measured levels, while challenges remain in accurate prediction in a number of environments, mainly due to the lack of accurate geometries. The extensive coverage of the DRM-PF database throughout Japan enables noise mapping in arbitrary regions near trunk roads, which would contribute to making noise policy.
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Author Junta Tagusari
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Cites_doi 10.3390/acoustics5040062
10.3390/ijgi8030130
10.21105/joss.06023
10.1265/jjh.19014
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References 7) World Health Organization Regional Office for Europe, Environmental Noise Guidelines for the European Region (World Health Organization Regional Office for Europe, Copenhagen, 2018).
12) R. Imai, D. Kamiya, Y. Yamamoto, W. Jiang, M. Nakahara, K. Nakahata and S. Tanaka, "Measurement of motor-vehicle traffic volume using camera images and artificial intelligence," J. Digit. Life, 3, 2023.3.4 (2023).
1) J. Tagusari and T. Matsui, "Estimation of health risk posed by road traffic noise in Japan based on the environmental noise guidelines for the European region," Jpn. J. Hyg., 76, 19014 (2021) (in Japanese).
11) Ministry of Land, Infrastructure, Transport and Tourism of Japan, "PLATEAU," https://www.mlit.go.jp/plateau/ Retrieved 2024-04-11.
5) S. Kephalopoulos, M. Paviotti and F. Anfosso-Lédée, Common Noise Assessment Methods in Europe (CNOSSOS-EU) (Publications Office of the European Union, Luxembourg, 2012).
8) European Commission Working Group Assessment of Exposure to Noise, "Good practice guide for strategic noise mapping and the production of associated data on noise exposure version 2," https://sicaweb.cedex.es/docs/documentacion/Good-Practice-Guide-for-Strategic-Noise-Mapping.pdf Retrieved 2024-04-11.
3) E. Bocher, G. Guillaume, J. Picaut, G. Petit and N. Fortin, "NoiseModelling: An open source GIS based tool to produce environmental noise maps," ISPRS Int. J. Geo-Inf., 8, 3 (2019).
4) J. Tagusari, "H-RISK with NoiseModelling: A QGIS plugin to predict environmental noise and estimate health risks," J. Open Source Softw., 9, 6023 (2024).
10) Shizuoka prefecture, "VIRTUAL SHIZUOKA," https://virtualshizuokaproject.my.canva.site/ Retrieved 2024-04-11.
2) END LAB, "Environmental noise data laboratory," https://end-lab.jp/ Retrieved 2024-04-10.
13) J. Khan, E. Thysell, C. Backalarz, P. Finne, O. Hertel and S. S. Jensen, "Performance evaluation of Nord2000, RTN-96 and CNOSSOS-EU against noise measurements in Central Jutland, Denmark," Acoustics, 5, 1099–1122 (2023).
6) Japan Digital Road Map Association, "DRM-PF," https://pf.drm.jp/ Retrieved 2024-04-11.
9) World Health Organization, "Global health estimates: Leading causes of death," https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death Retrieved 2024-04-11.
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References_xml – reference: 2) END LAB, "Environmental noise data laboratory," https://end-lab.jp/ Retrieved 2024-04-10.
– reference: 6) Japan Digital Road Map Association, "DRM-PF," https://pf.drm.jp/ Retrieved 2024-04-11.
– reference: 8) European Commission Working Group Assessment of Exposure to Noise, "Good practice guide for strategic noise mapping and the production of associated data on noise exposure version 2," https://sicaweb.cedex.es/docs/documentacion/Good-Practice-Guide-for-Strategic-Noise-Mapping.pdf Retrieved 2024-04-11.
– reference: 4) J. Tagusari, "H-RISK with NoiseModelling: A QGIS plugin to predict environmental noise and estimate health risks," J. Open Source Softw., 9, 6023 (2024).
– reference: 12) R. Imai, D. Kamiya, Y. Yamamoto, W. Jiang, M. Nakahara, K. Nakahata and S. Tanaka, "Measurement of motor-vehicle traffic volume using camera images and artificial intelligence," J. Digit. Life, 3, 2023.3.4 (2023).
– reference: 1) J. Tagusari and T. Matsui, "Estimation of health risk posed by road traffic noise in Japan based on the environmental noise guidelines for the European region," Jpn. J. Hyg., 76, 19014 (2021) (in Japanese).
– reference: 9) World Health Organization, "Global health estimates: Leading causes of death," https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death Retrieved 2024-04-11.
– reference: 5) S. Kephalopoulos, M. Paviotti and F. Anfosso-Lédée, Common Noise Assessment Methods in Europe (CNOSSOS-EU) (Publications Office of the European Union, Luxembourg, 2012).
– reference: 10) Shizuoka prefecture, "VIRTUAL SHIZUOKA," https://virtualshizuokaproject.my.canva.site/ Retrieved 2024-04-11.
– reference: 13) J. Khan, E. Thysell, C. Backalarz, P. Finne, O. Hertel and S. S. Jensen, "Performance evaluation of Nord2000, RTN-96 and CNOSSOS-EU against noise measurements in Central Jutland, Denmark," Acoustics, 5, 1099–1122 (2023).
– reference: 3) E. Bocher, G. Guillaume, J. Picaut, G. Petit and N. Fortin, "NoiseModelling: An open source GIS based tool to produce environmental noise maps," ISPRS Int. J. Geo-Inf., 8, 3 (2019).
– reference: 11) Ministry of Land, Infrastructure, Transport and Tourism of Japan, "PLATEAU," https://www.mlit.go.jp/plateau/ Retrieved 2024-04-11.
– reference: 7) World Health Organization Regional Office for Europe, Environmental Noise Guidelines for the European Region (World Health Organization Regional Office for Europe, Copenhagen, 2018).
– ident: 2
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  doi: 10.3390/acoustics5040062
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  doi: 10.3390/ijgi8030130
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  doi: 10.21105/joss.06023
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Snippet Areas in the vicinity of trunk roads are exposed to high levels of noise and may pose high health risks to residents. To assess the health risks and formulate...
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SubjectTerms Digital Road Map Platform
Health risk
Noise map
NoiseModelling
Road traffic noise
Title Prediction of road traffic noise in the vicinity of trunk roads in Japan using Digital Road Map Platform
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