Multifront Approach for Improving Navigation of Autonomous and Connected Trucks

Connected and autonomous vehicles (CAV) and autonomous and connected trucks (ACT) reduce congestion, increase efficiency, and improve safety, but they also increase pavement damage. This project will optimize the benefits and drawbacks of ACT at two levels. At the network level, ACT’s shipment routing and scheduling strategy for freight transportation that minimizes total cost will be developed. At the corridor level, real-time optimization will be performed; hence, ACT and platoons can adjust their configuration as they roll and external conditions change (e.g., wind speed, pavement condition). Accurate pavement damage prediction and ACT positioning affect successful deployment of the optimization in both levels. Accuracy of pavement damage prediction will be increased by including resting period, so the effect of truck separation in a platoon can be quantified. ACT positioning control will be enhanced by modifying material characteristics to allow better communications with the pavement.

    Language

    • English

    Project

    • Status: Completed
    • Funding: $464,020 (CCAT: $232,060 CS: $232,060)
    • Contract Numbers:

      69A3551747105

    • Sponsor Organizations:

      Department of Transportation

      Intelligent Transportation Systems Joint Program Office
      1200 New Jersey Avenue, SE
      Washington, DC  United States  20590
    • Managing Organizations:

      Center for Connected and Automated Transportation

      University of Michigan Transportation Research Institute
      Ann Arbor, MI  United States  48109
    • Project Managers:

      Tucker-Thomas, Dawn

    • Performing Organizations:

      University of Illinois, Urbana-Champaign

      Illinois Center for Transportation
      1611 Titan Drive
      Rantoul, IL  United States  61866

      Illinois Department of Transportation

      Bureau of Materials and Physical Research
      126 East Ash Street
      Springfield, IL  United States  62704-4766
    • Principal Investigators:

      Al-Qadi, Imad

      Ouyang, Yanfeng

    • Start Date: 20190101
    • Expected Completion Date: 20221231
    • Actual Completion Date: 20211130
    • USDOT Program: University Transportation Centers Program
    • Subprogram: Research

    Subject/Index Terms

    Filing Info

    • Accession Number: 01742588
    • Record Type: Research project
    • Source Agency: Center for Connected and Automated Transportation
    • Contract Numbers: 69A3551747105
    • Files: UTC, RIP
    • Created Date: Jun 18 2020 9:33AM