Under low-speed conditions, the focus of different path tracking control algorithms research is usually on the impact of system constraints on tracking accuracy, which include speed constraints, acceleration constraints, front wheel turning angle constraints and front wheel turning angle acceleration constraints. Among them, the speed constraint is the constraint that the vehicle maintains the driving state, the acceleration constraint affects the driving comfort, while the front wheel turning angle and its acceleration constraint have a greater impact on the path tracking control accuracy. According to the automotive theory, the front wheel turning angle determines the turning radius of the vehicle. If the radius of the planned path is smaller than the minimum turning radius of the vehicle, then the vehicle will deviate from the planned path because it cannot achieve tracking, while the front wheel turning angle acceleration constraint affects the steady-state steering characteristics of the vehicle, resulting in the vehicle not being able to accurately track the planned path.
Unlike the control of low-speed conditions, the problems of control accuracy and vehicle driving stability faced by path tracking control under high-speed conditions cannot be solved by simple PID, PP and Stanley algorithms, etc. Table 2 shows the commonly used path tracking algorithms under high-speed conditions and their advantages and disadvantages. As the path tracking control in the dynamics level, the position error, heading angle error and lateral speed, lateral acceleration and other optimization objectives have a coupling relationship, that is, in reducing the position error, heading angle error while the lateral speed or lateral acceleration will increase, so only rely on the fixed optimization objective function is unable to take into account the tracking accuracy and vehicle driving stability, that is, the algorithm listed in Table 2 is difficult to solve the coupling problem alone. The coupling problem. In order to achieve the purpose of controlling the path tracking accuracy and vehicle driving stability, most of the studies have applied two or more path tracking algorithms optimally combined, except for a few studies that use improved LQR, MPC, ADRC, SMC and other algorithms alone.
Table2.Path tracking algorithm at high speed conditions