Assessment of Parcel Delivery Systems Using Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are enabling innovative multimodal freight delivery strategies, in addition to collecting traffic data in the process of delivery. As examples, Amazon and Google have recently taken explored systems for drone-based parcel delivery, including delivery approaches where UAVs function independently of ground vehicle delivery trucks, and approaches using UAV in combination with moving vehicles, where the vehicle deploys the UAV to deliver certain parcels while it traverses the network delivering other parcels. The aim of this research is to evaluate alternative delivery systems, considering varying demand levels and UAV capabilities. In addition, the research team will assess the value of traffic information that could be obtained from using a UAV. A UAV equipped with a camera can measure the density of roads it observes using image processing techniques. This information could then be incorporated into traffic models to predict traffic conditions within the network, information which can improve both routing of delivery vehicles or be transmitted to the general public.


    • English


    • Status: Active
    • Sponsor Organizations:

      Center for Advanced Multimodal Mobility Solutions and Education

      University of North Carolina, Charlotte
      Charlotte, NC  United States  28223

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Managing Organizations:

      University of North Carolina, Charlotte

      Department of Civil and Environmental Engineering
      9201 University City Boulevard
      Charlotte, NC  United States  28223-0001
    • Project Managers:

      Fan, Wei

    • Performing Organizations:

      University of Texas at Austin

      Austin, TX  United States  78712
    • Principal Investigators:

      Boyles, Stephen

    • Start Date: 20171001
    • Expected Completion Date: 20180930
    • Actual Completion Date: 0

    Subject/Index Terms

    Filing Info

    • Accession Number: 01652819
    • Record Type: Research project
    • Source Agency: Center for Advanced Multimodal Mobility Solutions and Education
    • Files: UTC, RiP
    • Created Date: Dec 3 2017 9:58AM