Modern Advanced Driver Assistance Systems (ADAS) provide emerging capabilities for detecting the quality of roadway infrastructure assets to enable new customer features and analytics capabilities for road management authorities. This paper proposes measures to assess traffic sign health based on crowd sourced vehicle perception data, which to our knowledge has not been previously explored and for which there are no existing measures. We propose the following measures: (1) Euclidean Distance measurement of paint color deviation compared to the ideal condition, (2) Contrast Ratio assessment of visibility contrast of detected traffic signs colors and (3) Environmental Contrast Ratio to assess visibility contrast of detected traffic signs with respect to the background. We validated our approach against FHWA recommendation guidelines and the federally recommended CIE Chromacity diagram.


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    Titel :

    Traffic Sign Health Quality Assessment


    Beteiligte:
    Ahmed, Fahim (Autor:in) / Grimm, Donald K (Autor:in) / Bai, Fan (Autor:in)


    Erscheinungsdatum :

    24.09.2024


    Format / Umfang :

    674585 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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