农业装备与车辆工程2026，Vol.64Issue(7)：52-57,66,7.DOI:10.3969/j.issn.1673-3142.2026.07.008
融合改进势场与模糊预测控制的智能车轨迹规划
Trajectory planning of intelligent vehicles based on the integration of improved potential field and fuzzy predictive control
何剑 1何洋1
作者信息
- 1. 辽宁工业大学 汽车与交通工程学院,辽宁 锦州 121001
- 折叠
摘要
Abstract
To address the challenge of integrating trajectory planning and stability control for intelligent vehicles in complex dynamic environments,a trajectory planning and control method that combines a Modified Artificial Potential Field(MAPF)with Fuzzy Model Predictive Control(FMPC)was proposed.The MAPF improved the smoothness of path planning and obstacle avoidance capability by optimizing the repulsive force function and introducing a virtual target point and an equilibrium point strategy.The FMPC dynamically adjusted weighting coefficients using fuzzy rules,thereby enhancing the controller's adaptability to nonlinearities and uncertainties.Furthermore,an integrated closed-loop architecture of"perception-planning-control-stability"was constructed to achieve online collaborative optimization of obstacle-avoidance trajectory generation and stability constraints.Co-simulations were carried out based on CarSim and MATLAB/Simulink platforms.The results showed that within a speed range of 60～80 km/h,the proposed method reduces the lateral tracking error by 43.0%and the heading error by 59.6%under dynamic obstacle conditions compared with the traditional APF-MPC method,while the convergence of phase-plane trajectories is significantly improved,verifying its superiority and robustness under complex operating conditions.关键词
智能汽车/轨迹规划/模糊模型预测控制/改进人工势场法/稳定控制/联合仿真Key words
intelligent vehicle/trajectory planning/fuzzy model predictive control/improved artificial potential field/stability control/co-simulation分类
信息技术与安全科学引用本文复制引用
何剑,何洋..融合改进势场与模糊预测控制的智能车轨迹规划[J].农业装备与车辆工程,2026,64(7):52-57,66,7.
