Abstract: In order to investigate the influence of embedded strain sensors on the mechanical properties of bituminous mixture, a discrete element model of bituminous mixture with embedded strain sensors was established based on the discrete element method. This model allowed for an analysis at the microscopic level of the impact of different embedding depths and quantities of sensors on the mechanical performance of the bituminous mixture. The research indicated that as the embedding depth of the sensor (6 cm and 4 cm from the bottom of the beam) increased, the mechanical performance of the beam specimen improved accordingly, hence the optimal embedding depth was determined to be 4 cm away from the bottom of the beam. With the increase in the number of sensors installed (single versus double sensors), the continuity and integrity of pavement structure decreased, suggesting that it should be avoided to install sensors simultaneously at the same locations in the middle and lower layers of the pavement. Based on the previous study, a discrete element model of the bituminous mixture with a single sensor was constructed at an embedding depth of 4 cm away from the bottom of the beam, and the effect of the material composition on the mechanical properties of the built-in sensor bituminous mixture was analyzed in terms of mechanical response and contact interface. The research showed that with the decrease in the nominal maximum particle size of the mixture (AC-20, AC-16, AC-13), the working condition of the sensor became more stable, so the best nominal maximum particle size was 13.2 mm; with the coarsening of the gradation, the fewer load transfer paths, and the uneven distribution of contact force, will lead to poorer working stability of the sensor; the enhancement of the adhesive strength (tensile strength, cohesive strength) could improve the working stability of the sensor. The research results provide a theoretical basis for revealing the service performance evolution of pavement materials with built-in sensing devices.