Road traffic noise prediction models: a review

Rajakumara, H. N.; Gowda, R. M. Mahalinge

doi:10.2495/sdp-v3-n3-257-271

Cited by 23 publications

(10 citation statements)

References 7 publications

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“…However, the majority of L10 differences values in Djuanda road segment less than the maximum limit of 3 dBA as suggested by the Federal Highway Administration and fairly consistent with the measured noise levels at corresponding measurement points and time as seen in Figure 3. Earlier studies conducted in Taiwan, India, Vietnam, Thailand, and Macau have applied CoRTN models to predict traffic noise in urban areas of which motorcycles occupied more than half of the total traffic volume (13,35,37) . These studies report the good performance of the CoRTN models since the differences between the measured and predicted noise level of <3 dBA (37) .…”

Section: Predicted Traffic Noise Level By Cortn Modelmentioning

confidence: 99%

Traffic-related Noise at Roadside Schools: Assessment and Prediction in Urban Setting

et al. 2021

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ABSTRAK Kebisingan lalu lintas adalah salah satu ancaman bagi kesehatan masyarakat perkotaan. Paparan bising memberikan efek kesehatan jangka pendek dan panjang, dan efeknya berpotensi lebih buruk pada anak-anak yang belajar di sekolah pinggir jalan. Penelitian ini bertujuan untuk mengkarakterisasi kebisingan lalu lintas jalan di sekolah-sekolah yang terletak di jalan-jalan utama di Bandung, Indonesia serta memberikan rekomendasi mitigasi dan adaptasi untuk pengendalian kebisingan. Kebisingan lalu lintas diperoleh di dua sekolah pinggir jalan terletak di dua jalan utama (Jalan Suci dan Djuanda), beserta data volume dan komposisi lalu lintas, serta kecepatan kendaraan. Pengukuran dilakukan antara jam sekolah selama satu hari yang mewakili lokasi trotoar jalan, depan sekolah, dan halaman sekolah. Parameter tingkat kebisingan yang penting (Leq, L10, L50, L90) diukur, dan dilakukan analisis korelasi antara masing-masing parameter kebisingan. Model CoRTN digunakan untuk memprediksi kebisingan lalu lintas pada jarak tertentu dari jalan raya. Sepeda motor merupakan jenis kendaraan dominan secara berturut 79,1% dan 67,1% dari total volume kendaraan di ruas jalan Suci dan Djuanda. Kendaraan berat menyumbang <1%. Mayoritas kebisingan lalu lintas yang diukur sebagai Leq, L10, L50, L90 melebihi batas maksimum untuk pinggir jalan dan zona sekolah menurut standar internasional dan nasional <55 dBA). Model tersebut berkinerja lebih baik di ruas jalan Djuanda daripada Suci. Jumlah lokasi dan waktu pengukuran yang lebih banyak dapat memberikan penilaian paparan tingkat kebisingan lalu lintas yang lebih baik dengan menggunakan model CoRTN. Hasil penelitian ini diharapkan dapat menjadi masukan kebijakan berbasis pengetahuan bagi pemerintah kota dan lembaga untuk mengurangi dampak bising bagi anak didik. Kata kunci: kebisingan lalu lintas jalan, tingkat kebisingan, Model CoRTN ABSTRACT Noise from road traffic is one of the most ubiquitous threats to the public health in urban setting. Its exposures have proven short-and long-term health effects. and potentially worse for vulnerable population such as children studying at roadside schools. This study aimed to characterize the road traffic noise at schools located at major roads in Bandung, Indonesia. Traffic noise were obtained at 2 roadside schools located at two major roads (Suci and Djuanda roads), along with data on traffic volume and composition, and vehicles speed. The measurement was conducted between school hours during one day-time only at locations representative of roadside, front of the schools, and schoolyard. Important noise level parameters such as Leq, L10, L50, L90 were recorded, and correlation analysis between each parameter was conducted. The CoRTN model was then applied to predict the traffic noise at particular distances from the road. Motorcycles were the predominant vehicle type on both road segments: 79.1% and 67.1% of the total vehicle volume on Suci on Djuanda segments, respectively. Conversely, heavy vehicles accounted <1%. The majority of measured traffic noise determined as Leq, L10, L50, L90 exceeded the maximum limit for roadside and school zone set by the international and national standard (>55 dBA). The model performed better in Djuanda road segment than in Suci segment. More measurement locations and time could provide better assessment of exposure to traffic noise levels at roadside schools using the CoRTN model. Keywords: road traffic noise, noise level, CoRTN model

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Section: Predicted Traffic Noise Level By Cortn Modelmentioning

confidence: 99%

Traffic-related Noise at Roadside Schools: Assessment and Prediction in Urban Setting

et al. 2021

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“…Therefore, additional trips were required and the demand for fast and efficient trips increased 3 . Motorized vehicles massively occupied the cities [4][5][6][7][8] with the popularization of transport technologies. Gradually, the movements of people and goods became noisy and harmful 9 , and noise levels above a healthy threshold for human beings became usual 10 .…”

Section: Introductionmentioning

confidence: 99%

Exposição de ciclistas ao ruído em uma cidade média brasileira

Ramos

Silva

Souza

et al. 2020

Ciênc. saúde coletiva

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Resumo O objetivo deste estudo foi avaliar a exposição dos ciclistas ao ruído em uma cidade média brasileira. Um sensor móvel foi utilizado para as medições de ruído em ruas com e sem infraestruturas cicloviárias segregadas. O método proposto contempla as seguintes etapas: i) caracterização da área de estudo; ii) coleta e validação de dados; iii) cálculo dos indicadores de exposição; e iv) comparação e representação de resultados em mapas. Dois tipos de análises foram realizadas, por agregação espacial e por agregação temporal. Para isto, as medições foram inicialmente organizadas em 1.200 nós distribuídos nos percursos considerados. Os resultados apontam que os ciclistas que percorrem alguns trechos na cidade de São Carlos podem estar expostos a uma proporção considerável de ambientes com altos níveis de ruído. Nos dois trechos selecionados para este estudo, o ciclista esteve exposto à níveis acima do valor adotado (> 75dBA) em 33,2% e 18,9% dos nós. Além disso, observou-se que a possibilidade de trabalhar concomitantemente dois indicadores relacionados amplia os critérios de classificação dos trechos quanto à exposição do ruído.

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“…In each street canyon, noise measurements were taken simultaneously at street level and at each floor level for 15 min (Table 2). At the street level, the sound level meter was mounted on a tripod placed 1 m in front of the facade 3 . At each floor level, the readings were taken in the balcony at approximately 1 m from the building.…”

Section: Introductionmentioning

confidence: 99%

Study of Traffic Noise in Urban Street Canyons of Bengaluru City

Koti¹,

Ranganath²,

Rajakumara

2016

Current Science

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31. Government of UK (n.d.), Retrieved from https://www.gov.uk/ driving-eyesight-rules 32. Optometry Victoria Strategic Plan 2015-18 (n.d.). Optometry Australia, Retrieved from www.optometry.org.au; http://www. optometrists.asn.au/vic/practiceinfo/driving-vision-standards.aspx 33. Verma, A., Velmurugan, S. and Chakrabarty, N., Recommendations for driver licensing and traffic law enforcement aiming to improve road safety.

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Road traffic noise prediction models: a review

Cited by 23 publications

References 7 publications

Traffic-related Noise at Roadside Schools: Assessment and Prediction in Urban Setting

Traffic-related Noise at Roadside Schools: Assessment and Prediction in Urban Setting

Exposição de ciclistas ao ruído em uma cidade média brasileira

Study of Traffic Noise in Urban Street Canyons of Bengaluru City

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