基于自适应模型预测的智能网联车辆主动避障研究
Research on Active Obstacle Avoidance of Intelligent Networked Vehicles Based on Adaptive Model Prediction
刘星星 1王楠 1薛荣辉1
作者信息
- 1. 西安汽车职业大学,陕西西安 710600
- 折叠
摘要
本文以智能网联车为研究对象,设计一种自适应模型,采用MPC控制算法对整车行车过程中的避障策略和相关行为进行精准智能调度.借助PSD三角测距方式,对道路中的相关障碍物位置信息尽心采集,基于AT 89C52模块进行数据处理与控制,对车辆进行主动避障预测控制.经在不同工况下进行仿真实验表明,基于MPC自适应模型预测的智能网联车辆主动避障策略具有很好的应用价值,避障精准,验证了该方法的有效性与实用性.
Abstract
This paper takes intelligent networked vehicles as the research object,designs an adaptive model,and uses MPC control algorithm to accurately and intelligently schedule obstacle avoidance strategies and related behaviors during vehicle driving.With the help of PSD triangulation method,the position information of related obstacles in the road is collected,and the data processing and control based on AT89C52 module is carried out to carry out active obstacle avoidance predictive control for vehicles.The simulation experiments under different working conditions show that the active obstacle avoidance strategy of intelligent networked vehicles based on MPC adaptive model prediction has good application value,and the obstacle avoidance is accurate,which verifies the effective libido practicability of the method.
关键词
自适应模型/预测/智能网联车辆/主动避障/策略Key words
Adaptive model/Forecast/Intelligent networked vehicles/Active obstacle avoidance/Tactics引用本文复制引用
基金项目
西安汽车职业大学校长基金扫地机器人避障系统设计与研究项目(2023)(2023KJ042)
出版年
2024
NETL
NSTL
维普
万方数据