Anti-lock braking systems (ABS) are crucial for maintaining vehicle stability during emergency braking, yet traditional ABS control methods are often limited by fixed slip ratio thresholds and insufficient adaptability to complex road conditions. These limitations can lead to increased braking distances and instability, particularly under varying surface friction. This study proposes a novel ABS control strategy integrating dynamic threshold adaptation with an anti-windup PID controller to enhance braking performance across diverse road conditions. The dynamic threshold algorithm adjusts the target slip ratio in real-time based on road surface information, while the anti-windup PID controller mitigates actuator saturation and ensures smoother braking. The proposed control strategy was evaluated using multi-scenario simulations on the Simulink platform. Results demonstrate an 8.6% reduction in braking time compared to conventional control methods, alongside improved slip ratio stability with deviations limited to ±0.02. These findings indicate that the integration of dynamic threshold adaptation with anti-windup PID control significantly enhances braking stability and efficiency, particularly in scenarios involving sudden road surface changes. The study highlights the potential for this approach to be applied in intelligent vehicle braking systems, offering a robust solution to address the challenges posed by fluctuating road conditions. Future research should focus on further optimizing the dynamic threshold algorithm and exploring its implementation in real-world testing environments for broader application in autonomous driving systems.