To optimize signal control plans, this study investigates a phase-based signal control design methodology incorporating both phase structure and sequencing. A signal phase matrix is proposed to formally represent phase configurations and sequencing patterns. By defining the signal phase matrix and effective green times as decision variables, a phase sequence optimization model is developed with the objective function of minimizing total intersection delay. Through analysis of traffic flow characteristics, constraints including traffic saturation degree and effective green time boundaries are established, with penalty functions introduced to handle constraint violations. A genetic algorithm is implemented in MATLAB to solve the optimization model. Using real-world intersection traffic data, the model processes input traffic volumes and related parameters to generate optimized signal phase matrices and effective green times. Comparative analysis with existing signal control plans demonstrates approximately 22% reduction in total traffic delay, validating the model’s effectiveness and practical applicability.