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Prediction and Limitations of Noise Maps Developed for Heterogeneous Urban Road Traffic Condition: A Case Study of Surat City, India

Dipeshkumar R. Sonaviya*, Bhaven N. Tandel

Civil Engineering Department, SVNIT, Surat, India

* Corresponding Author: Dipeshkumar R. Sonaviya. Email: email

Sound & Vibration 2021, 55(1), 57-68. https://doi.org/10.32604/sv.2021.010715

Abstract

Road traffic noise pollution has been recognized as a serious issue which affects human health as well as affects urban regions. Noise maps are very beneficial to identify the impact of noise pollution. A noise mapping study performed to study the propagation of noise in tier-II city along with field measurements. The noise maps are developed using a computer simulation model (SoundPLAN essential 4.0 software). The noise prediction models like U.K’s CoRTN, Germany’s RLS-90, and their modified versions, which can be used for homogenous road traffic conditions, cannot be successfully applied in heterogeneous road traffic conditions of India. In developing country like India, road traffic noise pollution depends on the composition of heterogeneous traffic volume, variance in road geometrical, honking conditions, un-authorized parking, and varying density of the building on either side of the road. These traffic compositions contain vehicles, which have different sizes, speeds variations, a different dimension of vehicles. Because of fluctuating speeds, lack of lane disciplines, and un-authorized parking on main road lanes, honking events becomes inevitable, which changes and affects the urban soundscape of nations like India. Analysis of noise maps showed that horn honking due to un-authorized parked vehicles contributed an additional increase up to 11 dB (A) noise, which is quite significant.

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Cite This Article

Sonaviya, D. R., Tandel, B. N. (2021). Prediction and Limitations of Noise Maps Developed for Heterogeneous Urban Road Traffic Condition: A Case Study of Surat City, India. Sound & Vibration, 55(1), 57–68.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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