Aiming at the problem that the current vehicle anti-lock braking system (ABS) mainly acts on the longitudinal control of the vehicle, which causes the lateral offset of the vehicle body during the braking process under complex working conditions, a fuzzy top-level controller optimized by the improved Aquila optimization algorithm was proposed to realize the coordinated control between ABS and active front wheel steering system (AFS). Firstly, the two-degree-of-freedom and seven-degree-of-freedom vehicle dynamics models were established to analyze the vehicle motion characteristics. Secondly, an improved Aquila optimization algorithm was proposed. The dynamic reverse learning strategy and the disturbance mechanism based on stagnation detection were designed to enhance the global optimization ability. Based on this, the quantization factor and scale factor of the fuzzy controller were optimized. At the same time, a top-level controller based on fuzzy control was proposed to reasonably allocate the control rights of the lower ABS and AFS to ensure the control coordination of ABS and AFS. Finally, the improved Aquila optimization algorithm was used to optimize the fuzzy top-level controller, enabling the control system to automatically adjust the quantization factor and scale factor according to different angles of the vehicle and different road conditions, thereby enhancing the controller’s adaptive learning ability. The simulation results show that compared with the traditional ABS control, basic fuzzy control and Aquila optimization algorithm for optimizing control, the proposed method reduces the peak value of yaw rate by 88.61% and the peak value of sideslip angle by 69.69%, which significantly improves the lateral stability and braking efficiency of the vehicle.