Update of the Montevideo Traffic Noise Prediction Model

Abstract

Urban areas continue to grow steadily, leading to increases in vehicular traffic and urban noise levels, which may affect public health and quality of life. In this context, it is essential to develop tools capable of estimating and analyzing traffic-related noise. This work presents an update of the urban noise prediction model developed for Montevideo in 2000, incorporating new data obtained from the acoustic map of Montevideo 2024–2025 and recalibrating its parameters to current traffic conditions. To this end, variables such as traffic flow and composition, vehicle speed, and the presence of anomalous acoustic events (e.g., horns, braking, or modified exhaust systems) were analyzed. A statistical analysis of the recorded sound levels was also carried out to identify anomalous acoustic events and evaluate their influence on noise levels. Based on this analysis, correction factors related to these events and to traffic speed were incorporated into the model. The results show that the updated model improves predictive performance compared with the original formulation, reducing the percentage of errors outside the ±3 dBA range. Overall, the model constitutes a useful tool for estimating urban noise in Montevideo during daytime hours for traffic densities between 200 and 3000 veh/h, although challenges remain due to the high variability of the acoustic environment.

The authors' abstract, as published at the source. Urban Science, 2026 · DOI ↗