| dc.description.abstract | Autonomous trucks (ATs) are different from Human-driven trucks (HTs) in traffic characteristics in terms of lane choice and lateral positioning. Current design method (i.e. MEPDG) and existing highway system is to serve traditional traffic configurations. Therefore, it is crucial to develop a framework for studying the potential impact of autonomous truck and truck platooning on the long-term performance of current and future highway system (pavements and bridges).
This dissertation enhanced Pavement ME design by proposing a mechanics-based framework to evaluate autonomous truck and truck platooning impact on long-term performance of Texas highway system. The developed framework consists of input module, traffic characterization module, material property module, pavement performance module, and bridge analysis module. We adopted the traffic load spectra model developed in NCHRP 1-41 with some modifications. The modified traffic model considers axle load distribution for each axle and vehicle type, different wheel wander parameters for HTs and ATs, respectively, AT percentage, and traffic growth rate. Several models were integrated into the material property module that cover pavement temperature, asphalt aging, dynamic modulus of asphalt mixture, Thornthwaite moisture index, equilibrium soil suction for subgrade soil, moisture variation in unbound materials, stress-moisture-dependent resilient modulus of unbound materials, and pavement response. In the pavement performance module, we adopted and improved NCHRP project 1-52 model to predict TDC initiation and propagation in asphalt pavements. The primary improvements to the NCHRP 1-52 model includes the coupling of the HMA-FM-based crack initiation model, and the incorporation of a novel aging model for asphalt mixture. The bridge module was developed to conduct a high-level prioritization of about 55000 existing Texas bridges due to future platooning loads. Prioritization levels (from 5 to 1) were established for Texas bridge inventory under vertical loading of 6 different platooned truck configurations. The developed framework can be effectively implemented for assessing the potential impact of autonomous truck and truck platooning on the long-term performance of Texas highway system. | |
