The execution force of the autonomous driving system, also known as motion control, is the process of converting intent into action. Its main purpose is to provide the necessary input to the hardware to execute the planned intent, thereby generating the required motion. Vehicle motion control can be roughly divided into two tasks: Steering control of the vehicle’s lateral motion and control of the accelerator and brake pedals for longitudinal motion. The lateral control system aims to control the vehicle’s position on the lane and perform other lateral actions, such as lane changes or collision avoidance actions. Longitudinal control can control the vehicle’s acceleration, maintain an ideal speed on the road, keep a safe distance from the previous vehicle, and avoid rear-end collisions. Section 9.1 first introduces the kinematics and dynamics models of the vehicle, which are the basis of vehicle control; Sect. 9.2 introduces traditional control algorithms, namely PID and MPC; Sect. 9.3 discusses the control algorithms for path and trajectory stabilization commonly used in autonomous driving. Finally, Sect. 9.4 discusses autonomous driving control algorithms based on deep learning.