Dynamap is a European Life project, which aims at developing a dynamical acoustic map in a large urban area such as the city of Milan and the motorway surrounding Rome. We developed a method for predicting the traffic noise in an extended area using a limited number of monitoring sensors and the knowledge of traffic flows. In the case of Milan urban area, traffic and noise measurements have been performed in order to confirm both the non-acoustic parameter chosen to attribute a generic road to a specific cluster (traffic flow) and the noise predicted by our statistical model. Comparison showed that our predictive model is, in general, affected by two sources of error: statistic and systematic. In the case of Rome, noise measurements revealed the presence systematic errors in the noise map configuration. In both cases, their origin is analyzed and a method for their compensation and reduction is proposed
Zambon, G., Cambiaghi, M., Confalonieri, C., Coppolino, C., Eduardo, R., Angelini, F., et al. (2019). Uncertainty of noise mapping prediction related to Dynamap project. In INTER-NOISE 2019 Madrid - 48th International Congress and Exhibition on Noise Control Engineering (pp.1-12). Madrid : Sociedad Espanola de Acustica - Spanish Acoustical Society, SEA.
Uncertainty of noise mapping prediction related to Dynamap project
Zambon, G
Primo
;Cambiaghi, M;Confalonieri, C;Angelini, FMembro del Collaboration Group
;Bisceglie, AMembro del Collaboration Group
2019
Abstract
Dynamap is a European Life project, which aims at developing a dynamical acoustic map in a large urban area such as the city of Milan and the motorway surrounding Rome. We developed a method for predicting the traffic noise in an extended area using a limited number of monitoring sensors and the knowledge of traffic flows. In the case of Milan urban area, traffic and noise measurements have been performed in order to confirm both the non-acoustic parameter chosen to attribute a generic road to a specific cluster (traffic flow) and the noise predicted by our statistical model. Comparison showed that our predictive model is, in general, affected by two sources of error: statistic and systematic. In the case of Rome, noise measurements revealed the presence systematic errors in the noise map configuration. In both cases, their origin is analyzed and a method for their compensation and reduction is proposedFile | Dimensione | Formato | |
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