Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors

Abstract

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.

Keywords

• analytical methods
• data acquisition
• inductive loop detectors
• intelligent transportation systems
• sensor applications
• sensor devices
• sensor modeling
• signal processing
• software for sensors
• traffic applications