A New Path Tracking Method Based on Multilayer Model Predictive Control

Abstract

At present, many path tracking controllers are unable to actively adjust the longitudinal velocity according to path information, such as the radius of the curve, to further improve tracking accuracy. For this problem, we propose a new path tracking framework based on model predictive control (MPC). This is a multilayer control system that includes three path tracking controllers with fixed velocities and a velocity decision controller. This new control method is named multilayer MPC. This new control method is compared to other control methods through simulation. In this paper, the maximum values of the displacement error and the heading error of multilayer MPC are 92.92% and 77.02%, respectively, smaller than those of nonlinear MPC. The real-time performance of multilayer MPC is very good, and parallel computation can further improve the real-time performance of this control method. In simulation results, the calculation time of multilayer MPC in each control period does not exceed 0.0130 s, which is much smaller than the control period. In addition, when the error of positioning systems is at the centimeter level, the performance of multilayer MPC is still good.

Review and Comparison of Path Tracking Based on Model Predictive Control

“…Advanced path planning and velocity planning can make the path tracking control system avoid the case that the reference speed is high and the radius of the reference path is small, which will help to improve the performance of the two control methods. Therefore, combining path planning, speed planning, and these two MPC control methods is a feasible way to improve the performance of path tracking, such as our work [77].…”

Control Strategies on Path Tracking for Autonomous Vehicle: State of the Art and Future Challenges

“…To realize vehicle path tracking MPC control under different speed and different curvature conditions, Reference [69][70][71][72] proposed parameters adaptive MPC control strategies using fuzzy rules and multiple controllers combination to achieve adaptive adjustment of control parameters under different operating conditions. Reference [73][74][75][76][77] studied the MPC fast online solution methods of path tracking for autonomous vehicle using differential evolution algorithm, Laguerre function, and look-up table to improve the efficiency of MPC controller calculations.…”

A Model Predictive Controller with Longitudinal Speed Compensation for Autonomous Vehicle Path Tracking

“…As the basic part of autonomous vehicle motion control module, path tracking is desired to follow the reference path accurately. It is one of the research hotspots in recent research on autonomous vehicles [4,5]. This paper mainly focuses on path tracking control for autonomous vehicles.…”