Development of a Virtual Weigh-In-Motion System for Enhanced Pavement System Management

This research project proposes to leverage the data collected by P-WIM developed by the PI Wang and streams captured by the traffic surveillance video from the state DOTs to develop a low-cost, powerful Virtual Weigh-In-Motion (V-WIM) system based on analytical, computer vision, and machine learning techniques. This proposed system is capable of capturing a diversity of actionable information of moving vehicles on roadways that will enhance the pavement management system. In addition to the P-WIM system that captures weights of passing vehicles, the proposed V-WIM system provides functions including vehicle detection, speed measurement, identification of vehicle’s axle configurations, recognition of vehicle types, and measurement of volumes of different types of vehicles that have passed the installation location of the system within certain period of time. This proposed system will eliminate the need of the induction loop installation in the pavement for vehicle presence detection. A wireless transmission module will be included in the package of the proposed system to enable wireless data transmission to transportation agencies. The V-WIM will be powered by the energy harvested from pavement deformations and vibrations, developed as a function in the P-WIM system. If the system is successfully developed, it will allow better pavement maintenance practices by determining a diversity of useful parameters of the passing vehicles over the pavement where the system is installed. The developed low-cost system will enrich the functionalities of the current WIM system and generate actionable information for transportation agencies in support of achieving enhanced pavement system management.

    Project

    Subject/Index Terms

    Filing Info

    • Accession Number: 01766870
    • Record Type: Research project
    • Source Agency: Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)
    • Files: UTC, RiP
    • Created Date: Mar 12 2021 11:40AM