Overtaking Trajectory Planning Based on Model Predictive Control

被引：0
|
作者：
Yuan, Zihan [1 ]
Xu, Jun [1 ,2 ]
机构：
[1] Harbin Inst Technol, Sch Mech Engn & Automat, Shenzhen, Peoples R China
[2] Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai, Peoples R China
来源：
INTELLIGENT ROBOTICS AND APPLICATIONS (ICIRA 2022), PT III | 2022年 / 13457卷
基金：
中国国家自然科学基金;
关键词：
Model predictive control; Motion planning; Collision avoidance;
D O I：
10.1007/978-3-031-13835-5_50
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Autonomous driving technology can greatly increase road safety and reduce accidents, and has become a hot research topic in academia and industry today. However, traditional vehicle motion planning methods often have difficulty in balancing real-time performance with trajectory quality. This paper designs a trajectory planning method based on model predictive control technology, which transforms the motion planning problem into a quadratic planning problem. Compared with previous methods, the proposed method can generate trajectories that meet the requirements of vehicle kinematics and satisfy the requirements of comfort and energy saving while ensuring obstacle avoidance and real-time, and verifies the feasibility of this method in simulation experiments.
引用
收藏
页码：553 / 563
页数：11
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