This paper presents a sensor system for traffic data acquisition capable of discriminating vehicles into two classes (cars and trucks). The system is based on a bio-inspired `silicon retina' optical sensor in a compact embedded system and has been exhaustively evaluated in a real world environment at a highway test site. We further present the classification approach, data from the evaluation of the system under different lighting conditions and analyze sources of classification errors. The System achieves a 94.4% classification rate for cars and 92.2% classification rate for trucks under average daylight conditions.


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    Title :

    Real-Time Vehicle Classification using a Smart Embedded Device with a `Silicon Retina' Optical Sensor


    Contributors:


    Publication date :

    2008-10-01


    Size :

    508477 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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