A discrete-time linear model predictive control for motion planning of an autonomous vehicle with adaptive cruise control and obstacle overtaking

Abstract

Motion planners for autonomous driving improve traffic safety through collision-free motion generation along the path. However, conventional motion planners render passengers uncomfortable as a result of jerky motion. To overcome this, we propose a model predictive control (MPC) based motion planner that not only ensures safety but also improves driving comfort. The proposed planner generates path tracking and collision-free maneuvers to ensure safety, and improve driving comfort by minimizing acceleration and jerk. Collision-free maneuvers include vehicle following and overtaking. The target speed is determined by comprehensively considering path tracking performance improvement and whether overtaking is possible. The speed of the vehicle is controlled by considering longitudinal acceleration and jerk minimization. The steering command is determined by considering both path tracking error reduction, and lateral acceleration and jerk minimization. In cases where vehicle overtaking is required and during high-speed driving conditions, the consideration of lateral acceleration and jerk minimization increases to improve driving comfort. The proposed planner is formulated as a convex optimization problem. The effectiveness of the proposed planner was evaluated in path tracking and collision avoidance simulations. The simulation results confirm that the proposed planner ensures vehicle safety through lane keeping and collision avoidance, and improves driving comfort.

A Tube Linear Model Predictive Control Approach for Autonomous Vehicles Subjected to Disturbances

“…The framework of the tube MPC can be divided into two parts. The first part is the nominal system control, which computes the feedforward input of system (7) without disturbance:…”

“…By putting Equations ( 9) and (11) into System (7), we can express the actual system with e k as follows:…”

“…With the increase in the number of vehicles, traffic safety and efficiency have become a severe issue for governments and humans [1][2][3][4][5]. Autonomous vehicles can provide more excellent safety benefits and improve traffic efficiency, and they are assumed to be an efficient solution for traffic safety and efficiency issues [6][7][8]. The control layer for automatic vehicles has a significant effect on traffic safety and efficiency issues, and many scholars have devoted themselves to creating effective control methods for automatic vehicles [9][10][11][12].…”