Model predictive control strategy for smooth path tracking of autonomous vehicles with steering actuator dynamics

Abstract

Path tracking control is one of the most important functions for autonomous driving. In path tracking control, high accuracy and smooth tracking are required for safe and comfort driving. In order to meet these requirements, model predictive control approaches, which can obtain an optimized solution with respect to a predefined path, have been widely studied. Conventional predictive controllers have been studied based on a simple bicycle model. However, the conventional predictive controllers have a performance limitation in practical challenges due to the difference between the simple bicycle model and the actual vehicle. To overcome this limitation, the actuator dynamics of the steering system should be incorporated into the control design. In this paper, we propose a model predictive control based path tracking control algorithm to achieve the accurate and smooth tracking by incorporating the dynamic characteristics of the steering actuation system. In the proposed control algorithm, an optimal trajectory of the steering command is calculated by applying a quadratic programming optimization method. The proposed controller was verified by computer simulation with various driving scenarios. The simulation results show that the proposed controller can improve the tracking performance.

A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles

“…To leverage this, the complex vehicle model is often linearized to obtain an approximate linear model. Linearization approaches typically differ in the reference about which the linearization is computedcurrent operating point [148]- [150], reference path [151] or more generally, about a reference trajectory, which results in the following approximate linear model:…”

“…2) Path Tracking Controllers: In [151], a predictive control is investigated using a center of mass based linear dynamic model (assuming constant velocity) for path tracking and an approximate steering model. The resulting integrated model is validated with a detailed automatic steering model and a 27 degree-of-freedom CarSim vehicle model.…”

Perception, Planning, Control, and Coordination for Autonomous Vehicles

“…• Path Tracking Model Predictive Controller : with a center of mass based linear model, Kim et al [290] formulated an MPC problem for a path tracking and steering controller. The resulting integrated model is simulated with a detailed automatic steering model and a vehicle model in CarSim.…”

An Online Approach to D2D Trajectory Utility Maximization Problem

“…For the time-varying setting that is of interest here, the standard approaches are based upon graph theory [16]- [22], Markov decision process based techniques [23], [24], and model predictive control [9], [10], [25], [26]. Other advances in the path planning and robotics areas include dealing with uncertainties, dynamics, or multiple robots [27]- [29].…”