To address the challenge of accurately characterizing the development of road cavities under vehicle disturbances, rainfall, and other factors, this study proposes a quantitative method to analyze the evolution patterns of road cavities. Electromagnetic signals of subsurface cavities were acquired using ground-penetrating radar (GPR), and the cross-sectional areas of cavities along each survey line were calculated from waveform data using MATLAB software. This measurement approach was employed to analyze the effects of moisture content and impact loading on the development behavior of road cavities in laboratory test models. The influence of load magnitude, number of load applications, and moisture content on the development of various cross-sections of road cavities was quantitatively investigated using sensitivity analysis. The experimental results indicate that the coefficient of variation for the calculated cavity cross-sectional area is only 1.73%, and the relative errors of all measurements are below 5%, demonstrating the algorithm’s significant reliability. The mean rate of change in the cross-sectional area at the cavity center is relatively small, with a noticeably narrower variation range, indicating that this region is most strongly constrained by the surrounding soil. Under high-energy impacts and multiple cumulative shocks, it consistently exhibits area contraction. In contrast, the rate of change at the edge sections is significantly higher than that at the center, especially under conditions of heavy load and high moisture content, where the change rates at both left and right boundaries exceed 100%. Therefore, the edge sections can serve as key indicators for monitoring road cavity engineering. The factors influencing the development of road cavities are ranked by severity as follows: moisture content variation, load magnitude, and number of load applications. This study provides a theoretical basis for analyzing the development of road cavities under complex environmental conditions and for formulating road maintenance strategies.