Traffic noise and pavement distresses: Modelling and assessment of input parameters influence through data mining techniques

Abstract

A B S T R A C TTraffic noise affects greatly health and well-being of people, consequently the knowledge and control of the factors affecting it is very important. In this study models to predict tyre-pavement noise acoustic and psychoacoustic indicators based on type of pavement, texture, pavement distresses and speed were developed and used to assess the importance of each factor. By applying data mining techniques, in particular artificial neural networks and support vector machines, models with good predictive capacity of both acoustic and psychoacoustic noise indicators were obtained, constituting a precious tool to reduce the tyre-pavement noise. Moreover, the proposed models allowed for the assessment of the influence of the input parameters controlling noise such as: type of pavement, texture, speed and pavement distresses for the first time. It was found that pavement distresses and, as expected, speed influence strongly tyre-pavement noise. In this way it is clearly shown that preventive maintenance of road pavements by authorities, which eliminates distresses, can have an important effect on tyre-road noise, promoting the well-being of the populations.

The Effect of Port Gate Location and Gate Procedures on the Port-City Relation

“…[ 43,44] Larger traffic volumes, higher speeds, greater numbers of trucks and their weight, or any faulty vehicle part (eq. mufflers) increase the loudness of traffic related noise.…”

Selected Approaches to the Assessment of Environmental Noise from Railways in Urban Areas

“…Assessing the negative impact of noise on humans is also challenging because the sensitivity (subjective but also objective) of each individual to noise is different. For this reason, generally accepted methodological procedures for its assessment were developed with the selection of suitable parameters and their maximum permissible values [ 9 , 10 , 11 , 12 ].…”

Evaluation and Improvement of the Sound Quality of a Diesel Engine Based on Tests and Simulations

“…The sharpness calculation is based on the specific loudness [19]. To date, only the sharpness generated from the Zwicker specific loudness has been standardized (as DIN 45692:2009 [22]) and applied in numerous SQ studies [23][24][25][26][27][28][29]. To calculate the sharpness using the Moore-Glasberg specific loudness, the method proposed by Swift and Gee [30,31] was applied in this study.…”