Using recorded sound spectra profile as input data for real-time short-term urban road-traffic-flow estimation

Torija Martinez, AJ; Ruiz, DP

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%.

Citation

Torija Martinez, A., & Ruiz, D. (2012). Using recorded sound spectra profile as input data for real-time short-term urban road-traffic-flow estimation. Science of the Total Environment, 435-43, 270-279. https://doi.org/10.1016/j.scitotenv.2012.07.014

• Journal Article Type: Article
• Acceptance Date: Jul 2, 2012
• Online Publication Date: Aug 1, 2012
• Publication Date: Oct 1, 2012
• Deposit Date: Dec 2, 2019
• Journal: Science of the Total Environment
• Print ISSN: 0048-9697
• Publisher: Elsevier
• Volume: 435-43
• Pages: 270-279
• DOI: https://doi.org/10.1016/j.scitotenv.2012.07.014
• Publisher URL: https://doi.org/10.1016/j.scitotenv.2012.07.014
• Related Public URLs: https://www.sciencedirect.com/journal/science-of-the-total-environment
• Additional Information: Additional Information : Patent based on this paper: see: https://patentimages.storage.googleapis.com/56/99/77/a61a18fa51ef04/WO2014020213A1.pdf; Funders : CONSEJERIA DE INNOVACION, CIENCIA Y EMPRESA. JUNTA DE ANDALUCIA; Grant Number: P07-TIC-03269