河南科技大学学报（自然科学版）2024，Vol.45Issue(1)：1-11,11.DOI:10.15926/j.cnki.issn1672-6871.2024.01.001
基于MPC的智能车辆路径规划与跟踪控制
Intelligent Vehicle Path Planning and Tracking Control based on MPC
摘要
Abstract
The dynamic planning effect of obstacle avoidance paths in obstacle environments was poor and the tracking control effect was still not ideal when facing complex working conditions and high curvature road conditions.Taking intelligent vehicles as the research object,a path planning and tracking system was proposed by combining model predictive control(MPC)algorithm with artificial potential field(AMF)algorithm.The improved potential field model function was intrduced into the objective function and constraints of MPC.The dynamic obstacle avoidance path planner based on MPC and improved APF was designed.Fuzzy control was used to optimize the weight coefficients in the MPC path tracking controller.The simulation results show that the maximum lateral deviation of the fuzzy MPC path tracking controller is reduced by 19.14％compared with the MPC controller on dry road.The maximum lateral deviation of the fuzzy MPC controller is reduced by 0.55 m on wet road.The joint simulation model of obstacle avoidance path planning and tracking control is built based on MATLAB/Simulink and Carsim software.Dynamic obstacle path planning and tracking control simulation experiments are conducted under different speeds of dynamic obstacles.The experimental results show that the maximum lateral deviation in the process of tracking the planned path is about 0.170 m,which indicates that the planned obstacle avoidance path can avoid obstacles safely and effectively.关键词
智能驾驶/模型预测控制/人工势场法/模糊控制Key words
intelligent driving/model predictive control/artificial potential field method/fuzzy control分类
信息技术与安全科学引用本文复制引用
张丽霞,田硕,潘福全,严涛峰,李宝刚..基于MPC的智能车辆路径规划与跟踪控制[J].河南科技大学学报（自然科学版）,2024,45(1):1-11,11.基金项目
国家自然科学基金项目(52202508) （52202508）
山东省自然科学基金项目(ZR2020MG021) （ZR2020MG021）
