Integrated Vehicle–Tire–Pavement Approach for Determining Pavement Structure–Induced Rolling Resistance under Dynamic Loading

Abstract

Pavement-related rolling resistances, caused by pavement–vehicle interaction, are important components of pavement life-cycle assessment (LCA). Structure-induced rolling resistance (SRR) is caused by dissipated vehicle kinetic energy in the pavement structure. This paper presents an integrated vehicle–tire–pavement approach to evaluate asphalt pavement SRR under dynamic loading. A three-dimensional (3D) semitrailer-truck model was used to calculate dynamic wheel loads on various pavement surface-roughness profiles. The dynamic wheel loads were then transformed into 3D tire–pavement contact stresses using a deep-learning tire model. Next, an advanced 3D finite element pavement model, validated in previous studies, was used to simulate pavement structure under moving tire–pavement contact stresses. The dynamic load coefficient of axle forces was found to increase linearly with truck speed. The increasing trend became more significant as pavement roughness increased. Ignoring the dynamic loading effect resulted in 12% error in predicting SRR. A case study was performed to illustrate the computation procedures of asphalt pavement SRR under static and dynamic loading. Dynamic loading accounted for 4.74%, 7.37%, 10.73%, and 14.02% of SRR for four pavement surface-roughness levels at a truck speed of 40 mph. In addition, SRR was found to be highly nonlinear and increased as speed decreased and axle load increased. A modified Illinois Center for Transportation SRR model was developed to quickly assess the SRR component of the pavement LCA’s use stage. This study demonstrates the importance of vehicle–tire–pavement interaction in SRR prediction, which may not be overlooked.

Effects of Pavement Characteristics on Rolling Resistance of Heavy Vehicles: A Literature Review

“…They argued that a thicker AC layer would imply a larger volume of integration for energy dissipation, which results in a higher SRR ( 88 ). The latest studies use the concept of maximum pavement deflection (at certain baseline conditions) for SRR analysis, which is implicitly related to AC thickness, but also to all pavement structure stiffnesses ( 84 , 91 ).…”

“…The effect of load proximity from the different heavy vehicle tires has been investigated numerically in the literature and it was found that SRR can be accurately calculated by simulating one tire and multiplying the output by the number of tires on the vehicle ( 58 , 87 ). Recently, the effect of dynamic load on SRR was investigated numerically by Liu and Al-Qadi ( 91 ) and it was shown that ignoring dynamic loading effect could result in 12% error in SRR prediction. The latter result seems to indicate that road roughness can interact with SRR.…”

“…The effect of the four parameters mentioned above (temperature, speed, layer thicknesses/stiffnesses, and load characteristics) can be summarized in a straightforward regression equation ( 84 , 90 , 91 ). Estaji et al ( 90 ) calculated the SRR from 720 FEM simulations with various input values to develop different versions of a regression model.…”

“…One of the regression models predicted a higher SRR with a thicker top layer, which is contrary to what the literature usually indicates ( 58 , 82 ), and no validation tests were performed on the model ( 90 ). Another similar approach was developed by the Illinois Center for Transportation (ICT) with an exponential regression model ( 84 , 91 ). This nonlinear regression model showed good agreement with the FEM ( 84 ) and considered the dynamic load caused by road roughness ( 91 ).…”

“…Another similar approach was developed by the Illinois Center for Transportation (ICT) with an exponential regression model ( 84 , 91 ). This nonlinear regression model showed good agreement with the FEM ( 84 ) and considered the dynamic load caused by road roughness ( 91 ). Overall, SRR depends strongly on the experimental conditions, and FEM simulations showed that EFC of a heavy vehicle caused by SRR is between 0.03% and 6.5% ( 84 ).…”