Nonlinear regression model for predicting environmental traffic noise

Authors

  • Alana Corsi Universidade Tecnológica Federal do Paraná
  • Franciely Velozo Aragão
  • Daiane Chiroli
  • Márcia Santos
  • Eniuce Souza
  • Marcia Sahmed
  • Paulo Soares

DOI:

https://doi.org/10.22279/navus.2020.v10.p01-12.1035

Keywords:

Sound Equivalent Level. Traffic noise. Mathematical Optimization Model.

Abstract

Transport is an essential activity for urban life and for the economy, however, bad planning of the city script causes some movement in some places, causing excessive noise levels generated by road traffic. We aim to present a mathematical model that represents the relationship between the equivalent level of sound and vehicle volume quantities using the nonlinear logistic regression model in order to facilitate decision-making in relation to urban planning. We collected the data of sound pressure and vehicle volume for ten days during five hours totaling a collection of 50 hours, with a total of 180 thousand data of sound pressure level. The place of data collection is a highway that passes through the city of Maringá, in Paraná, being an intense traffic highway. The results show the performance of the proposed model were differences between measured and predicted traffic noise levels ranged from -0.3 dB (A) to +0.3 dB (A) and the mean difference was -0.006 dB (A). The proposed road traffic noise forecasting model can be used as a decision support tool in urban planning, considering the same boundary conditions as the road study.

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Published

2020-02-07

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Articles