This report describes a developmental feasibility study for the automatic guidance of a lane restriping system to automatically apply paint on top of worn traffic lane boundary striping with a lateral tolerance of +/-13mm and a longitudinal tolerance of +/-102mm for dashed lane striping. This system would assist the California Department of Transportation in their effort to enhance safety, reduce worker stress, improve restriping efficiency, and reduce traffic flow impacts of striping maintenance. Machine vision recognition systems employing both hardware and software based neural network land strip recognition were evaluated. Preliminary results show potential for automatic machine vision location of worn traffic lane boundary striping, however additional study is needed to fully evaluate the accuracy of this system. A non-contact radar displacement sensor was found to be an acceptable alternative to a traditional ground-driven encoded wheel sensor for longitudinal control of dash length.


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    Titel :

    Vision-Based Low Cost Field Demonstrable Paint Restriping Guidance System (on CD-ROM)


    Erscheinungsdatum :

    2002


    Format / Umfang :

    pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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