Optimal Control of Path Tracking for Vehicle-Handling Dynamics

Aimed at solving the problem of minimum-time path tracking in inverse vehicle-handling dynamics, a hybrid optimization based on the Gaussian pseudospectral method (GPM) and a genetic algorithm (GA) was proposed. The basic idea is to identify the optimal steering angle input by the driver as a vehicle travels along a pylon course slalom test road so that the vehicle completes the course using the minimal amount of time. Based on this purpose, the problem of path tracking to achieve the minimum time, which was treated as an optimal control problem, was first converted into a nonlinear programming problem by GPM and then the GA was solved using sequential quadratic programming (SQP). The results were compared with those achieved using other traditional methods, where it was shown that the hybrid optimization algorithm had a higher calculation accuracy. It is hoped that the results of this study can help drivers easily identify safe lane-keeping trajectories and areas.