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Sound measurement and automatic vehicle classification and counting applied to road traffic noise characterization

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A Correction to this article was published on 07 May 2021

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Abstract

Increase in population density in large cities has increased the environmental noise present in these environments, causing negative effects on human health. There are different sources of environmental noise; however, noise from road traffic is the most prevalent in cities. Therefore, it is necessary to have tools that allow noise characterization to establish strategies that permit obtaining levels that do not affect the quality of life of people. This research discusses the implementation of a system that allows the acquisition of data to characterize the noise generated by road traffic. First, the methodology for obtaining acoustic indicators with an electret measurement microphone is described, so that it adjusts to the data collection needs for road traffic noise analyses. Then, an approach for the classification and counting of automatic vehicular traffic through deep learning is presented. Results showed that there were differences of 0.2 dBA in terms of RMSE between a type 1 sound level meter and the measurement microphone used. With reference to vehicle classification and counting for four categories, the approximate error is between 3.3% and -15.5%.

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Funding

This research was supported by the University of San Buenaventura Bogotá, which provided acoustic facilities and equipment to perform the measurements, as well as support during Oscar Acosta doctoral training.

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Authors and Affiliations

  1. Ingeniería de Sonido, Facultad de Ingeniería, Universidad de San Buenaventura Bogotá, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Oscar Esneider Acosta Agudelo

  2. Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Carlos Enrique Montenegro Marín

  3. School of Engineering and Technology, Universidad Internacional de La Rioja, Logroño, Spain

    Rubén González Crespo

Authors
  1. Oscar Esneider Acosta Agudelo
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  2. Carlos Enrique Montenegro Marín
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  3. Rubén González Crespo
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Contributions

OA and CM contributed to conceptualization. OA contributed to methodology. OA and CM contributed to software. OA, CM and RG were involved in validation. OA performed formal analysis. OA and CM conducted investigation. RG contributed resources. OA contributed to data curation. OA was involved in writing—original draft preparation. CM and RG were involved in writing—review and editing. OA contributed to visualization. CE and RG did supervision. CM and RG were involved in project administration. CM and RG contributed to funding acquisition. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Rubén González Crespo.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by Vicente Garcia Diaz.

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Agudelo, O.E.A., Marín, C.E.M. & Crespo, R.G. Sound measurement and automatic vehicle classification and counting applied to road traffic noise characterization. Soft Comput 25, 12075–12087 (2021). https://doi.org/10.1007/s00500-021-05766-6

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