摘 要：为缩短自动驾驶车辆行程时间并确保行驶安全与平稳性，本文综合考虑路面附着条件与道路曲率的影响，提出一种融合几何微分法与二次规划的最优路径规划方法。该方法基于点质量模型施加动力学约束，在保证平稳性的前提下，通过优化加速、制动及转向控制，充分利用轮胎抓地力。Car-Sim与Simulink联合仿真结果表明，在不同附着条件下，本方法均具备良好的鲁棒性。在双移线工况下，相较于最短路径与最优曲率路径法，本方法能显著缩短行程时间。在赛车线工况下，其行程时间较最短路径方法至少缩短3.7%。该方法能有效兼顾行驶安全与通行效率，在不同道路附着条件下实现接近时间最优的自动驾驶路径规划。
关键词：二次规划；路径规划；最优速度；自动驾驶汽车
中图分类号：U463.6；TP18 文献标志码：A DOI：10.15917/j.cnki.1006-3331.2026.03.001
Research on Time-optimal Path Planning Method for Autonomous Vehicles
ZHU Kang, ZHOU Huan, TANG Jiaming
Abstract: To reduce the travel time of autonomous vehicles while ensuring driving safety and smoothness,this paper proposes an optimal path-planning method that integrates the geometric differential method with quadratic programming and accounts for road adhesion and curvature.The method introduces a point-mass model as a dynamic constraint to optimize acceleration,braking,and steering control,thereby maximizing the utilization of tire-road friction without compromising ride comfort.The results of co-simulation using CarSim and Simulink show that the method exhibits strong robustness under varying adhesion conditions.In the double lane change scenario,compared to the shortest path and optimal curvature path methods,it significantly reduces travel time.In the racing line scenario,the travel time is at least 3.7% shorter than that of the shortest path method.This method effectively balances driving safety and efficiency,achieving near-time-optimal path planning for autonomous vehicles under diverse road adhesion conditions.
Key words: quadratic programming; path planning;optimal speed; autonomous vehicles
