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