Abstract
Vehicular noise is a significant source of noise pollution in urban environments, affecting the health and well-being of the inhabitants. Here, we propose a mathematical model to predict and mitigate vehicular noise levels, integrating key variables such as traffic volume, speed, and composition. The methodology included data collection at four points in the city of Milagro, Ecuador, and analysis using QGIS and MATLAB tools under the RLS 90/DIN standard with linear regression equations. We estimated a 15% noise reduction with the implementation of noise barriers. The model showed greater accuracy and replicability compared to previous studies. We acknowledge the omission of factors such as vegetation and meteorological conditions as limitations of the study. The model can contribute to the design of public policies on urban planning and noise pollution control.
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