There is an unmet need for a vehicle weigh-in-motion (WIM) technology to detect vehicle overweight and prevent overstress to highway infrastructure. This paper presents a novel computer vision-based non-contact WIM system. The underlining physics is that the force exerted by each tire onto the road is the product of the tire-road contact pressure and contact area. Computer vision is applied (1) to measure the tire deformation parameters so that the tire-roadway contact area can be accurately estimated; and (2) to recognize the marking texts on the tire sidewall so that the manufacturer-recommended tire inflation pressure can be found. In this research, a computer vision system is developed, which is comprised of a camera and computer vision software for measuring tire deformation parameters and recognizing the tire sidewall markings from images of individual tires of a moving vehicle. Computer vision techniques such as edge detection and optical character recognition are applied to enhance the measurement and recognition accuracy. Field experiments were conducted on fully loaded or empty concrete trucks and the truck weights estimated by this novel computer visionbased non-contact WIM system agreed well with the curb weights verified by static weighing. This research has demonstrated a novel application of the computer vision technology to solve a challenging vehicle WIM problem. Requiring no sensor installation on the roadway or the vehicle, this cost-effective non-contact computer vision system has demonstrated a great potential to be implemented.


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    Titel :

    Computer vision-based vehicle weigh-in-motion system


    Beteiligte:
    Fromme, Paul (Herausgeber:in) / Su, Zhongqing (Herausgeber:in) / Feng, Maria Q. (Autor:in) / Leung, Ryan Y. (Autor:in)

    Kongress:

    Health Monitoring of Structural and Biological Systems XVII ; 2023 ; Long Beach, California, United States


    Erschienen in:

    Proc. SPIE ; 12488


    Erscheinungsdatum :

    25.04.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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