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

Principal Investigator(s):

Imad Al-Qadi, Bliss Professor of Engineering – The University of Illinois at Urbana-Champaign
Director – Illinois Center for Transportation
Director – Advanced Transportation Research and Engineering Laboratory
Director – Smart Transportation Infrastructure Initiative

Project Abstract:
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.

Institution(s): University of Illinois at Urbana-Champaign

Award Year: 2023

Research Focus: Safety

Project Form(s):