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Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors

Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for v...

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Detalles Bibliográficos
Autores principales: Lamas-Seco, José J., Castro, Paula M., Dapena, Adriana, Vazquez-Araujo, Francisco J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634484/
https://www.ncbi.nlm.nih.gov/pubmed/26516855
http://dx.doi.org/10.3390/s151027201
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author Lamas-Seco, José J.
Castro, Paula M.
Dapena, Adriana
Vazquez-Araujo, Francisco J.
author_facet Lamas-Seco, José J.
Castro, Paula M.
Dapena, Adriana
Vazquez-Araujo, Francisco J.
author_sort Lamas-Seco, José J.
collection PubMed
description Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for vehicle classification based on only one signature acquired from a sensor single-loop, in contrast to standard methods using two sensor loops. Our proposal will be evaluated by means of real inductive signatures captured with our hardware prototype.
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spelling pubmed-46344842015-11-23 Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors Lamas-Seco, José J. Castro, Paula M. Dapena, Adriana Vazquez-Araujo, Francisco J. Sensors (Basel) Article Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for vehicle classification based on only one signature acquired from a sensor single-loop, in contrast to standard methods using two sensor loops. Our proposal will be evaluated by means of real inductive signatures captured with our hardware prototype. MDPI 2015-10-26 /pmc/articles/PMC4634484/ /pubmed/26516855 http://dx.doi.org/10.3390/s151027201 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lamas-Seco, José J.
Castro, Paula M.
Dapena, Adriana
Vazquez-Araujo, Francisco J.
Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors
title Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors
title_full Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors
title_fullStr Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors
title_full_unstemmed Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors
title_short Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors
title_sort vehicle classification using the discrete fourier transform with traffic inductive sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634484/
https://www.ncbi.nlm.nih.gov/pubmed/26516855
http://dx.doi.org/10.3390/s151027201
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