Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm

Abstract

Due to the growing number of vehicles using the national road networks that link major urban centers, traffic noise is becoming a major issue in relation to the transportation system. Thus, it is important to determine noise model parameters to predict road traffic noise levels as part of an environmental assessment, according to traffic volume and pavement surface type. To determine the parameters of a noise prediction model, statistical pass-by and close proximity tests are required. This paper provides a parameter determination procedure for noise prediction models through an adaptive particle filter (PF) algorithm, based on using a weigh-in-motion system, which obtains vehicle velocities and types, as well as step-up microphones, which measure the combined noises emitted by various vehicle types. Finally, an evaluation of the adaptive noise parameter determination algorithm was carried out to assess the agreement between predictions and measurements.