Capital investment in highway infrastructure is critical to economic growth and prosperity. The inspection and timely maintenance of such assets are crucial preventative measures against their failure. However, the need to sustain such infrastructure in acceptable working conditions is continuously challenged by the rise of road repair costs, political pressures to reduce public spending, and budget deficits. This research investigates the utilization of unmanned aerial vehicles (UAVs) in assessing highway maintenance needs while reducing labor-intensive inspection. Specifically, the main objectives of this research are to: (1) explore the capacity of UAVs to collect data for roadway maintenance assessment; (2) investigate the reliability of automating pavement distress recognition using object recognition software; and (3) evaluate the viability of assessing highway maintenance needs using UAVs as compared to the traditional technique. Field experiments on collecting data using UAVs in the State of Kuwait are presented to illustrate the fulfillment of the above objectives. The results of this study should prove useful to infrastructure asset managers and departments of transportation, and could accelerate maintenance data collection, eliminate human error, and improve the reliability of maintenance assessment.


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    Title :

    Automating Highway Infrastructure Maintenance Using Unmanned Aerial Vehicles


    Contributors:

    Conference:

    Construction Research Congress 2018 ; 2018 ; New Orleans, Louisiana



    Publication date :

    2018-03-29




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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