Figure 3.Schematic diagram of geometric relation of PP
2.3 Stanley’s algorithm
The principle of Stanley algorithm is to control the front wheel turning
angle φ according to the lateral position error ye and heading angle
error from the front axle center control point to the nearest reference
trajectory point (gx, gy), and Figure 4 shows the geometric relationship
diagram of Stanley algorithm.Stanley algorithm has good low-speed
driving stability and small path tracking error, but there is the
problem of not being able to meet the path tracking accuracy and smooth
line requirements at the same time. problem, and in order to further
improve the control performance of the algorithm, the Stanley algorithm
is usually improved [36].
For example, in the literature [37], the Stanley controller was
optimized by genetic algorithm; Ahmed AbdElmoniem et al. proposed to add
a predictive Stanley controller that mimics the driver’s behavior under
low-speed operating conditions [38]; Sun et al. proposed an improved
fuzzy Stanley model based on particle swarm optimization for unmanned
operation of agricultural machines [39]; Wang et al. designed an
improved Stanley algorithm [40]. These improved Stanley controllers
are usually able to reduce lateral errors and improve yaw stability
compared to the original Stanley controller, resulting in a large
improvement in control performance.
The Stanley algorithm requires a higher degree of path smoothing and is
prone to the problem of excessive vehicle response overshoot in the case
of unsatisfactory road curvature smoothness, and the tracking
performance is poor when the vehicle has high lateral acceleration due
to the neglect of vehicle dynamics and steering actuator dynamic
characteristics.