iPPSys: A Parallel Parking System for Path Planning and Tracking Based on Multi-Obstacle Analysis and Model Predictive Control

In recent years, electric vehicles have been in the ascendant, giving rise to various related demands on autonomous driving. The advent of intelligent parking technology can effectively improve parking efficiency, alleviate traffic difficulties, and reduce the occurrence of accidents. This paper proposes an intelligent parallel parking system, namely, iPPSys, and primarily addresses two issues: path planning and path tracking. In terms of path planning, a vehicle kinematic model is first established, and multiple obstacle avoidance constraints are analyzed. Considering curvature mutation, after the turning radius suitable for a geometric method is derived, a B-spline curve method is put forward to optimize the path, so as to obtain a curvature-continuous reference path. For path tracking, a tracking controller is designed based on the principle of model predictive control (MPC), with the front wheel steering angle and the rate of speed change as constraints to obtain the optimal control solution. Finally, the model predictive controller is simulated and verified using Simulink. The simulation results demonstrate the accuracy and effectiveness of the proposed methods, and suggest potential in real-world applications.