Path Tracking of Intelligent Commercial Vehicles Based on Variable Weight Coefficient Multipoint Preview Control

Path tracking is the basis for realizing vehicle intelligence, so it is particularly important to realize accurate path tracking. In order to improve the path tracking accuracy of the intelligent commercial vehicle, an optimal preview control strategy with variable weight coefficient multipoint preview is proposed based on the lateral driver model of optimal preview theory. The control strategy improves the path tracking effect by introducing the heading angle deviation feedback control and selecting the optimal preview distance according to vehicle speed because the preview distance is important to the path tracking effect. The control strategy is proved to be more accurate by comparing it with single point preview control strategy and fixed weight coefficient multipoint preview control strategy. Finally, the double lane change path simulation experiment is carried out on variable weight coefficient multipoint preview control strategy. The results show that the control strategy has good adaptability to vehicle speed, vehicle load and road adhesion coefficient under normal driving cycle.