现代制造工程Issue(1)：74-86,13.DOI:10.16731/j.cnki.1671-3133.2026.01.009
基于多模型障碍物轨迹融合预测的自动驾驶横纵向联合运动规划算法
A coordinated motion planning control algorithm for autonomous vehicles considering multi-model obstacle trajectory fusion prediction
摘要
Abstract
To address the problem that trajectory predictions for traffic participants produced by traditional motion planning algo-rithms are unsuitable for complex driving scenarios and are not effectively integrated with subsequent motion planning,resulting in incomplete utilization of obstacle position information,a longitudinal and lateral joint motion planning algorithm for autonomous driving is proposed based on multi-model fusion prediction of obstacle trajectories.First,the Constant Acceleration(CA)model and the Constant Turn Rate and Velocity(CTRV)model are selected respectively as the long-term and short-term prediction models for traffic participants,and the prediction results are fused using a method based on the Kalman filter.Second,the spatio-temporal occupancy within the prediction horizon is gridded,and,using the obstacle trajectories obtained from the fusion predic-tion,a dynamic programming algorithm is executed to obtain new feasible boundaries.Third,a Linear Time-Varying(LTV)ve-hicle dynamics model is established and the ego vehicle's global trajectory is parameterized;a classical Model Predictive Control(MPC)problem is then formulated and solved via quadratic programming to achieve joint longitudinal and lateral motion planning that yields the desired collision-free motion.Finally,joint simulations are performed on a verification platform built with CarSim software and Simulink software in a three-lane driving scenario.The results indicate that the proposed longitudinal and lateral joint motion planning algorithm based on multi-model fusion prediction of obstacle trajectories can effectively integrate obstacle vehicle trajectory prediction with the ego vehicle's joint motion generation task.The multi-model fusion prediction algorithm dem-onstrates faster response and smaller prediction errors in continuous lane-change scenarios,providing a reference for research on motion planning of autonomous vehicles in dynamic obstacle environments.关键词
自动驾驶车辆/轨迹融合预测/卡尔曼滤波器/动态规划/可行边界/车辆动力学/模型预测控制Key words
autonomous vehicles/trajectory fusion prediction/Kalman filtering/Dynamic Programming(DP)/feasible boundary/vehicle dynamics/Model Predictive Control(MPC)分类
信息技术与安全科学引用本文复制引用
刘本学,左富豪,张红军,侯俊峰,吴涛,李霞..基于多模型障碍物轨迹融合预测的自动驾驶横纵向联合运动规划算法[J].现代制造工程,2026,(1):74-86,13.基金项目
2024年河南省科技攻关项目(242102221014) （242102221014）
