Understanding the mechanisms for road surface degradation requires an examination of asphalt layer responses under realistic rolling tire loads. In this study, we proposed a novel tire-sensor-pavement coupling chain for integrating the realistic distribution of tire contact stress into the mechanical modelling of the asphalt layer. The tire contact stress distributions under different tire loading conditions including tire loads and tire inflation pressures are obtained by using a sensor measuring system. The temperature- and frequency-dependent material behaviour of asphalt mixes is described through the VENoL (NOnLinear Viscoelastic) model. The model reliability is validated by numerical/experimental confrontation via a series of complex modulus tests. A new algorithm is developed to achieve the coupling simulation of the tire–pavement interaction system. Finally, the dynamic responses of the asphalt mixture including external force, displacement fields and surface deflection were investigated depending on rolling tire loads. The proposed method provides a fundamental requirement for understanding the structural behaviour of asphalt pavement loaded by rolling tires, which can be used to get insights into asphalt pavement surface design.

Steel bridge deck pavements (SBDPs) are susceptible to complex mechanical and service environmental conditions, yet current design methods often struggle to simultaneously capture global bridge system behavior and local pavement responses. To address this issue, this study develops a multi-scale finite element modeling framework that integrates a full-bridge model, a refined girder-segment model, and a detailed pavement submodel. The framework is applied to an extra-long suspension bridge to evaluate the mechanical responses of five typical pavement structural configurations—including double-layer SMA, double-layer Epoxy Asphalt (EA), EA-SMA combinations, and a composite scheme with a thin epoxy resin aggregate overlay. By coupling global deformations from a full-bridge model to the local pavement submodel, the proposed method enables a consistent assessment of both bridge-level effects and pavement-level stress concentrations. The analysis reveals that pavement structures significantly alter the stress and strain distributions within the deck system. The results indicate that while the composite configuration with a thin overlay effectively reduces shear stress at the pavement–deck interface, it results in excessive tensile strain, posing a high risk of fatigue cracking. Conversely, the double-layer EA configuration exhibits the lowest fatigue-related strain, demonstrating superior deformation coordination, while the optimized EA-SMA combination offers a robust balance between fatigue control and interfacial stress distribution. These findings validate the effectiveness of the multi-scale approach for SBDP analysis and highlight that rational structural configuration selection—specifically balancing layer stiffness and thickness—is critical for enhancing the durability and long-term performance of steel bridge deck pavements.