Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors

被引：26

作者：

Lamas-Seco, Jose J. ^{[1
]}

Castro, Paula M. ^{[1
]}

Dapena, Adriana ^{[1
]}

Vazquez-Araujo, Francisco J. ^{[1
]}

机构：

[1] Univ A Coruna, Fac Informat, Dept Elect & Sistemas, GTEC, La Coruna 15071, Spain

来源：

SENSORS | 2015年 / 15卷 / 10期

关键词：

analytical methods; data acquisition; inductive loop detectors; intelligent transportation systems; sensor applications; sensor devices; sensor modeling; signal processing; software for sensors; traffic applications; SPEED ESTIMATION; LOOP; ALGORITHM;

D O I：

10.3390/s151027201

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

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.

引用

页码：27201 / 27214

页数：14

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