Trajectory Tracking Control Algorithm for Unmanned Mining Transportation Vehicles
The operating environment for unmanned mining transport vehicles is challenging,characterized by unstructured roads such as high-curvature bends and slopes,which demand high requirements for unmanned transportation control.To improve the adaptability of traditional control algorithms like PID and to increase the accuracy of both lateral and longitudinal control in unmanned driving trajectory tracking,this study proposes a combined approach.It involves a multi-point preview lateral control method integrating pure pursuit with PID,and a longitudinal control method considering fuzzy control table parameter fitting.This approach is developed to reduce the number of control parameters while improving the algorithm's effectiveness.Initially,a basic controller is designed using the traditional control algorithm.And then the lateral and longitudinal control algorithms are developed based on the advantages of the basic algorithm.Finally,the performance of these algorithms is verified through hardware-in-the-loop simulation and on-vehicle deployment testing.The experimental results show that compared with the Stanley method,the lateral control algorithm significantly improves vehicle path tracking accuracy.In terms of longitudinal control,the speed tracking error is less than 1 km/h,ensuring the smoothness and comfort of the vehicle's driving performance.
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