Trajectory Tracking Model Predictive Controller Design for Autonomous Vehicles with Updating Constrains of Tire Characteristics

In this paper, we address the problem of trajectory tracking control autonomous vehicles by considering nonlinear characteristics tires. By influence tires’ dynamics on steering stability, proposed predictive controller can track desired and velocity in presence road curvature while minimizing lateral deviation. First all, a hierarchical structure is adopted, which upper-level used to calculate acceleration front-wheel angle maintain target, lower-level realized command through corresponding component devices. Moreover, force estimator designed based radial basis function (RBF) neural network estimate tires, incorporated into boundary conditions vehicle envelope constraint improve adaptability performance. Finally, tested co-simulation CarSim (a simulation software specifically for dynamics)/Simulink modular diagram environment multidomain as well model-based design) hardware-in-loop system. The experimental results demonstrate safely driving at vehicle’s handling limits effectively reduce slip phenomenon vehicle.