The highway infrastructure sector increasingly relies on innovative tools and technologies such as remote sensing and computer vision to overcome challenges in inspection, such as limited experienced staff and expanding project scopes. The objective of this research is to develop a framework to utilize Uncrewed Aerial Systems (UAS) to enhance the inspection of pavements. By reducing manual inspections, which are time-consuming and can be subjective, UAS deployment facilitates efficient data collection and analysis. High-resolution optical and thermal imagery were gathered to monitor construction progress and assess the quality of pavement operation. The proposed framework enables automated progress monitoring by capturing geometric data and tracking the placement stage, providing project managers with up-to-date progress reports. In the case of Hot Mix Asphalt (HMA) pavements, thermal imaging detects potential defects like temperature segregation, which can lead to reduced pavement performance if not addressed during the paving process. The use of thermal imaging ensures that compaction is uniform, and defects can be identified in real time, preventing long-term durability issues. The proposed framework has been validated through two case studies managed by the Michigan Department of Transportation (MDOT), demonstrating its ability to improve inspection efficiency and enhance safety by reducing the need for personnel in hazardous conditions.


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    Title :

    Automated Pavement Inspection and Progress Monitoring Using Uncrewed Aerial Systems (UAS): MDOT Case Study


    Contributors:

    Conference:

    International Conference on Transportation and Development 2025 ; 2025 ; Glendale, Arizona



    Publication date :

    2025-06-05




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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