Research and Implementation of Path Tracking Using QPSO Algorithm in Intelligent Networked Vehicles

Path tracking is an important topic for intelligent vehicles, and the performance of its path tracking algorithm will have a great impact on the stability of intelligent vehicles during driving. On this basis, aiming at the accuracy and lateral stability of path tracking, a motion control system and a path tracking system with degrees of freedom are respectively constructed. The required deflection angular rate formula is obtained by back-calculation method, and the path-following controller is researched by applying the quadratic optimization algorithm. The QPSO algorithm is used to optimize the C1, C2, k parameters in the ideal deflection rate equation. By simulating typical working conditions such as lane changes and curves, the influence of the optimal control strategy on lane change performance is analyzed.