Abstract: The pursuit of intelligence and smartness in road infrastructure is critical for the advancement of road engineering. Embedded strain sensors serve as a vital tool for sensing strain within pavement structures. To explore the influence of these embedded strain sensors on the mechanical properties of asphalt mixtures, this study established a mesoscopic model of asphalt mixtures with embedded strain sensors using the discrete element method. The effects of embedment depth and quantity of strain sensors on the mechanical properties of asphalt mixtures were examined, and the impact of the asphalt mixture characteristics (such as nominal maximum particle size, grading, friction coefficient, and asphalt–aggregate bond strength) on the operational performance of the embedded strain sensors was analyzed. The results of the study show that as the embedment depth of the sensors (6 and 4 cm from the bottom of the beam) increases, the horizontal tensile stress at the three monitoring points at the bottom of the beam also increases by 56.9%, 43.5%, and 43.8%. This finding indicates that the closer to the bottom of the beam specimen, the more uniform the distribution of the internal horizontal stress field, which is conducive to the working stability of the sensors. The crack growth rate of the beam specimen embedded with double sensors is faster than that of the beam specimen embedded with a single sensor. When the deflection is 0.8 mm, the number of detected cracks reaches 267 for the double sensors and only 93 for the single sensor. Sensors should not be buried simultaneously in the middle and lower layers of the same point on the pavement. For the asphalt mixtures, large nominal maximum particle sizes (AC-13, AC-16, and AC-20) are associated with few force chains. Compared with that for AC-13, the average force chains for AC-16 and AC-20 are 4.9% and 11.4% lower, respectively, indicating an optimal nominal maximum particle size of 13.2 mm for the mixture. The coarser the grading, the fewer the load transfer paths, resulting in a 77.7% reduction in the number of contact force systems and a decrease in the uniformity of contact force distribution. Furthermore, the maximum contact force increases by 74.6%, leading to the poor operational stability of the sensors. An increase in bond strength (tensile strength and cohesion strength) reduces the maximum contact force by 11%, thereby enhancing the operational stability of the sensors. These outcomes provide a theoretical basis for elucidating the evolution of the service performance of pavement materials with embedded sensing devices.