Abstract: In order to reduce the occurrence of traffic accidents such as rear-end collision and improve following stability, economy and ride comfort of following the car, a vehicle adaptive cruise control (ACC) strategy was proposed. The upper controller was used to calculate the expected acceleration based on the model predictive control (MPC), and the speed and distance was controlled according to the switching of driving conditions. The lower controller was used to optimize the driving/braking switching strategy based on the established inverse longitudinal dynamics, drive motor and brake models of pure electric vehicles, and the expected motor torque or the expected brake pipeline pressure was obtained by calculating the expected acceleration output of the upper layer. The acceleration and speed of the vehicle was controlled to achieve the goal of speed control or spacing control. Four typical driving conditions were set up in CarSim/Simulink for simulation tests to verify the performance of the proposed ACC strategy. The results show that in both constant speed cruise and following cruise conditions, the vehicle can quickly and stably follow the set initial speed and maintain a safe distance from the preceding vehicle at all times. Under emergency braking conditions, the vehicle can quickly respond to deceleration to ensure driving safety.Under complex working conditions, the vehicle can track the preceding vehicle smoothly and the changes in speed and acceleration are relatively stable, which can effectively achieve the dynamic response of the vehicle following.The proposed control strategy can accurately and safely track the target vehicle under different driving conditions, and can balance the requirements of economy and comfort during vehicle operation.