# A Speed Tracking Method for Autonomous Driving via ADRC with Extended State Observer
## 1 Introduction  
Autonomous vehicle technology has received extensive attention because it has the potential to reduce the number of road fatalities, reduce fuel consumption, and improve transportation efficiency. Significant progress has been made in the fields of sensing, computer hardware, and software technology over the past few decades. Worldwide competitions have been held, such as the Defense Advanced Research Projects Agency (DARPA) Grand Challenge [1] and Urban Challenge [2]. The Intelligent Vehicle Future Challenge (IVFC) [3] and the World Intelligent Driving Challenge (WIDC) [4] have driven academic research and the development of associated technologies in China. This paper describes the design of the longitudinal controller for Tianjin University's autonomous vehicle which competed in the World Intelligent Driving Challenge competition. The architecture of an autonomous driving system typically consists of three layers: The environmental perception layer, the decision-making and planning layer, and the driving control layer [5]. The driving control layer is responsible for tracking the desired trajectory, which is obtained from the decision-making and planning layer. Driving control is a complex task that must guarantee vehicle stability and ensure certain levels of performance. The lateral and longitudinal controllers are vital components of the driving control layer. The lateral controller adjusts the steering wheel of the vehicle to track the target trajectory. The longitudinal controller delivers the control commands to the accelerator pedal and brake pedal of the vehicle so that the trajectory matches the longitudinal speed profile that has been created. The performance of the longitudinal controller essentially determinesthe drivability, fuel economy, and safety of the vehicle. We focus on the longitudinal controller in this study. One of the most critical challenges associated with the longitudinal control of the vehicle is dealing with disturbances. \"Total disturbance\" includes both internal unmodeled vehicle dynamics and external disturbances in the system. Since the engine and powertrain are time-delayed and strong non-linear systems of which the dynamics are difficult to model or measure, the challenges exist in controlling the acceleration pedal depth according to the desired drive torque. In addition, external disturbances come from Global Positioning System (GPS)/ Inertial measurement unit (IMU) sensor, variations in rolling resistance, air resistance, and resistance from the road incline also cause the control challenges to vehicle speed tracking control. Various solutions to the aforementioned problems have been studied for speed tracking control. Proportional integral derivative (PID) controllers are popular because they are convenient to implement. [PERSON] et al. [6] designed a simple linear PID controller to track set speed. [PERSON] et al. [7] used a nonlinear PID controller to improve the performance of the controller. Fuzzy PID [8] and adaptive fuzzy PID [9] controllers have both been used in existing research. However, these controllers require a large calibration effort, and one set of control parameters often fails to solve the vehicle speed tracking problem under operational conditions. A resource-intensive gain-scheduling algorithm for the PID controller is necessary to improve its performance. Linear or nonlinear model predictive control (MPC) [10; 11; 12; 13; 14] provides another solution because it can handle multiple constraints on both inputs and states, as shown by [PERSON] et al. [15]. [PERSON] et al. [16] showed that the vehicle set speed or desired acceleration is commonly used as inputs to the controller for the simplicity of controller design. On the one hand, MPC is a time-consuming control method, and it needs much calculation resource to guarantee the real-time control in a real vehicle system. On the other hand, the controller actuators are, in real vehicle, the accelerator pedal and the brake pedal.