Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors.
Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors.
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DOI：
10.3390/s151027201
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发表时间：
2015-10-26
期刊：
影响因子：
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通讯作者：
Vazquez-Araujo FJ
中科院分区：
文献类型：
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作者：
Lamas-Seco JJ;Castro PM;Dapena A;Vazquez-Araujo FJ
感应线圈检测器（ILD）是交通管理系统中最常用的传感器。本文表明，一些频谱特征提取的傅里叶变换（FT）的感应签名不依赖于车辆的速度。这样的属性是用来提出一种新的方法，车辆分类的基础上，只有一个签名从传感器单回路，在使用两个传感器回路的标准方法相比。我们的建议将通过我们的硬件原型捕获的真实的感应签名进行评估。
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.