Prediction of Pavement Damage under Truck Platoons Utilizing a Combined Finite Element and Artificial Intelligence Models

The characterization of platoon configuration encompasses three fundamental parameters: the lateral positioning of trucks, the spacing between them, and the total number of trucks within the platoon. The quantification of pavement damage stands as a paramount concern for roadway agencies, which is pivotal for the formulation of effective maintenance and rehabilitation strategies, ensuring the prolonged serviceability of roadways. Consequently, the development of a comprehensive framework capable of calculating pavement distresses as a direct function of these parameters becomes imperative. Therefore, the objective of this study is to introduce an innovative framework tailored to the investigation of pavement damage induced by truck platooning: (1) developing a new framework to simulate repetitive loading and predict accumulating pavement responses, including rutting prediction via a mechanistic model, and (2) proposing a physics-guided artificial intelligence (AI) model to predict pavement responses using the extensive 3D pavement finite element (FE) response database.


  • English


  • Status: Active
  • Funding: $254996
  • Contract Numbers:


  • Sponsor Organizations:

    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 Michigan Transportation Research Institute

    2901 Baxter Road
    Ann Arbor, Michigan  United States  48109
  • Project Managers:

    Stearns, Amy

  • Performing Organizations:

    University of Illinois, Urbana-Champaign

    Illinois Center for Transportation
    1611 Titan Drive
    Rantoul, IL  United States  61866
  • Principal Investigators:

    Al-Qadi, Imad

  • Start Date: 20230601
  • Expected Completion Date: 20240531
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01906156
  • Record Type: Research project
  • Source Agency: Center for Connected and Automated Transportation
  • Contract Numbers: 69A3552348305
  • Files: UTC, RIP
  • Created Date: Jan 28 2024 12:35PM