Monte Carlo simulation of traffic noise dynamics at a bus stop based on real sound signals

Abstract

Noise from vehicular traffic is the main source of noise pollution in cities. Sound power variations from this kind of noise are caused by instabilities in traffic due to crossings, speed bumps, bus stops, and idiosyncratic driver behavior. This study aims to estimate the impact from vehicular traffic noise dynamics in the vicinity of a bus stop. Simulations were done using a probabilistic model based on the Monte Carlo method. The hypothesis is that the variability of noise due to bus arrivals and departures at a bus stop increases the level of local noise impact. Therefore, Traffic Noise Index (TNI) and Noise Pollution Level (LNP) were adopted as the main acoustic parameters. Methodological procedures were the following: selection of the study object, a bus stop; recording sound signals for passing vehicles; acquisition of geometric parameters, acoustic and traffic cues; simulations and analysis of traffic noise scenarios with different times between bus arrivals at the bus stop. It was found that smaller values of the average interval between bus arrivals were associated with higher levels of noise impact. The simulation method adopted seems to be a promising tool for evaluating the influence of bus stops on traffic noise.