## 1 Introduction
In order to effectively track the desired trajectory, researchers have proposed a series of tracking control algorithms. The current motion control algorithms mainly include PID control, SMC control and MPC control. Among them, sliding mode variable structure control has a strong robustness to nonlinear systems and unknown disturbances, so researchers have made different improvements to it. [PERSON] et al. used the enhanced variable structure based on sliding mode to realize the trajectory tracking control of the robot [17]. Moreover, he designed the shear control and sliding mode control of the non-holonomic wheeled mobile robot. [PERSON] et al. constructed a new variable-structure sliding mode by designing the update law of the sliding mode parameters [18]. This improved the convergence speed of the system. The chattering of the sliding mode controller seriously affects the accuracy of the controller. Therefore, [PERSON] et al. proposed a composite sliding mode controller [19]. The controller consists of a novel sliding mode control based on hybrid reaching law and an extended sliding mode disturbance observer. Experiments show that this method can effectively suppress chattering and shorten the approach time. [PERSON] et al. proposed a method using a fuzzy sliding mode variable structure [20]. This method can suppress the chattering of the actuated joints and minimize the pose error of the robot end effector. In order to make the sliding mode controller approach the sliding mode surface quickly in a limited time, and improve the convergence speed, [PERSON] et al. proposed a backstepping global fast terminal sliding mode control method for the trajectory tracking control problem of industrial robots [21]. This method makes the control error of the controller converge in a short time. [PERSON] et al. designed a hierarchical controller based on a model predictive control and sliding mode control that could simultaneously track the reference trajectory and the desired vehicle speed [22]. The method adopted a new reaching law, which further reduced the chattering of the system while ensuring that the system converged quickly to the sliding mode surface. Aiming at the accuracy of intelligent vehicle tracking the desired trajectory, this paper designs a trajectory plan based on improved RRT algorithm and an improvedterminal sliding mode intelligent vehicle tracking control strategy. Improved motion planning and motion control methods have many advantages. Firstly, the traditional RRT algorithm was improved by using the goal bias strategy and the separation axis theorem to improve the planning efficiency of the algorithm. Secondly, an improved terminal sliding mode controller was designed, which comprehensively considered the lateral error and heading error of the tracking control to improve the accuracy of the system tracking control. The rest of the paper is organized as follows: Section 2 discusses trajectory planning based on the improved RRT algorithm; Section 3 discusses building the controller model; Section 4 discusses the design of the improved terminal sliding mode controller; Section 5 discusses the trajectory planning simulation experiments and Matlab-Carsim HIL simulation platform experiments; Section 6 discusses the conclusions of this study.