Using recorded sound spectra profile as input data for real-time short-term urban road-traffic-flow estimation.
Sci Total Environ
; 435-436: 270-9, 2012 Oct 01.
Article
em En
| MEDLINE
| ID: mdl-22858535
ABSTRACT
Road traffic has a heavy impact on the urban sound environment, constituting the main source of noise and widely dominating its spectral composition. In this context, our research investigates the use of recorded sound spectra as input data for the development of real-time short-term road traffic flow estimation models. For this, a series of models based on the use of Multilayer Perceptron Neural Networks, multiple linear regression, and the Fisher linear discriminant were implemented to estimate road traffic flow as well as to classify it according to the composition of heavy vehicles and motorcycles/mopeds. In view of the results, the use of the 50-400 Hz and 1-2.5 kHz frequency ranges as input variables in multilayer perceptron-based models successfully estimated urban road traffic flow with an average percentage of explained variance equal to 86%, while the classification of the urban road traffic flow gave an average success rate of 96.1%.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Automóveis
/
Cidades
/
Ruído dos Transportes
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Sci Total Environ
Ano de publicação:
2012
Tipo de documento:
Article
País de afiliação:
Espanha