# Improved ADRC-Based Autonomous Vehicle Path-Tracking Control Study Considering Lateral Stability
## 1 Introduction  
In recent decades, with the development of society, cars have become one of the necessary means of transportation for people's daily travel, and autonomous vehicle have received wide attention from the society by virtue of their advantages in improving road traffic safety and reducing road traffic congestion [1]. Many countries worldwide are strengthening research in areas such as autonomous vehicle, and autonomous vehicle technology has become one of the key points and hot spots of research in the automotive industry at present [2]. Meanwhile, owing to the leapfrog development of the electronic industry and control technology, autonomous vehicle technology has also made great progress [3, 4]. Autonomous vehicle technology mainly includes three parts: environment perception, path planning, and tracking control, among which path-tracking control is the research content of this paper. Path-tracking control is to achieve the desired path given by the path planning part by controlling wheel steering, and its control effect directly affects the performance and safety stability of autonomous vehicle [5]. Because of the complexity of vehicle driving conditions, it will be affected by various disturbances, and how to achieve the suppression of disturbances plays a crucial role in the autonomous vehicle path-tracking control accuracy and safety. As one of the key technologies for autonomous vehicle, path-tracking control is to eliminate the tracking deviation generated between the actual driving path and the desired path during the vehicle driving process by controlling the front-wheel steering or four-wheel steering, so that the autonomous vehicle's driving path tracks the desired path [6, 7]. In recent research literature, many various path-tracking control algorithms have been proposed: [8, 9] proposed a model predictive control (MPC)-based autonomous vehiclepath-tracking control scheme by constraining the front-wheel steering angle to control the autonomous vehicle along the desired path by front-wheel steering. In [10], two sliding-mode controllers were used to converge the lateral deviation and heading error of the vehicle to zero by four-wheel steering, so that the vehicle travels along the desired path. The results show that the control method using wheel steering has better path-tracking control effect; however, the lateral stability of the vehicle is affected when the lateral force of the tires tends to saturate under large lateral acceleration. Therefore, [PERSON] [11], [PERSON] [12], [PERSON] [13], and other scholars [14; 15; 16; 17] have fully considered the lateral stability of the vehicle while focusing on the path-tracking control effect of the autonomous vehicle. In [11; 12; 13; 14], the yaw stability problem is considered and the control method of direct yaw moment control (DYC) is used. The controllers described in the literature generate external yaw moments to improve the yaw stability so that the yaw rate of the vehicle tracks the desired value, thus achieving the purpose of improving the vehicle yaw stability. For the implementation of the external yaw moment, the method of optimal distribution of tire forces is used in [12; 13], and the method of individual wheel selection rules is used in [14]. Other studies [15; 16] consider the problem of the vehicle's roll stability and design an antiroll controller in the autonomous vehicle's path-tracking process, so that the vehicle has both higher path-tracking accuracy and better antiroll stability, which improves the lateral stability of the vehicle. In [17], yaw stability and roll stability are both considered; an integrated controller is designed using sliding-mode control method to comprehensively improve the lateral stability of the autonomous vehicle during path tracking.