A Novel Stanley Algorithm Based on Model Prediction

In this paper, a novel Stanley control algorithm (MP-Stanley) for park logistics vehicles based on model prediction is proposed. Firstly, a vehicle dynamics model and a tire model are established, and then the kinematic error, dynamics error and each state quantity of the position of the vehicle at the future moment are calculated by the model prediction principle, and the steering angle at the current moment is calculated by the gain coefficient. Finally, the test conditions are set according to the actual operation scenario of the logistics vehicle, and the algorithm is verified in the real vehicle test on the closed road section. The test results show that the control effect of the new MP-Stanley algorithm is more stable than that of the traditional Stanley algorithm, with an average error of no more than 0.158 m and a maximum error of no more than 0.466 m, and it meets the requirements for practical use in the park at the commonly used speeds of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$15-30 ~\text{km} / \mathrm{h}$</tex>.