Internal Pavement Condition Index for Evaluating Asphalt Pavement Integrity Using GPR Data

Internal structural defects are typical challenges during the service life of asphalt pavement. However, traditional pavement evaluation indicators and detection methods rely primarily on pavement surface data, making it difficult to effectively assess internal defects for pavement performance evaluation. Ground penetrating radar (GPR) can be used to identify typical defect types. However, the impact of defects on pavement performance should be thoroughly studied. This study proposed the Internal Pavement Condition Index (IPCI) using GPR data to assess the internal integrity of pavement structures. Numerical simulations were performed to illustrate the correlation between reflected signal energy and interlayer porosity. An energy spectrum classification was proposed based on in situ data. Finite element method (FEM) analyses were conducted to assess the contributions of defects at different locations to pavement structural integrity. The results demonstrated a strong correlation ( R 2 = 0.97 ) between reflected signal energy and interlayer porosity. Looseness in the upper base was found to have the most significant impact on internal structural integrity among the evaluated defects. Finally, the IPCI evaluation framework was validated across 13 highways, and specific maintenance recommendations were proposed for different score ranges: IPCI ≥ 90, 80 < IPCI < 90, and IPCI ≤ 80. The proposed IPCI could allow accurate evaluation of pavement performance using GPR.