首页 | 本学科首页   官方微博 | 高级检索  
     

智能车逆向超车控制算法
引用本文:阮仕峰,惠飞,于建游,张志刚,杜绎如,郭星.智能车逆向超车控制算法[J].计算机与现代化,2022,0(5):119-126.
作者姓名:阮仕峰  惠飞  于建游  张志刚  杜绎如  郭星
作者单位:长安大学信息工程学院,陕西 西安 710064,河北省高速公路延崇筹建处,河北 张家口 075400
基金项目:陕西省重点研发计划项目;国家重点研发计划;河北省省级科技计划项目;中央高校基本科研业务费资助项目
摘    要:针对双向车道因受限于道路条件及交通特性仅能借用对向车道完成超车(逆向超车)的问题,通过采用车联网以及车载传感器获取环境车辆的速度、加速度等全局信息,将多车场景中各个实体所造成的影响纳入超车决策中,从而提出一种基于图搜索和模型预测控制(Model Predictive Control, MPC)的逆向超车控制方法。首先,根据车车通信获取的全局信息,结合非合作博弈,对各车在整个时段内的行为进行预测,并根据预测情况对道路的各个区域进行安全评估,评估依据为该区域在下一时刻出现车辆的概率。对道路完成评估后,得到碰撞概率热区图,之后采用A*算法搜索安全路径,根据安全路径完成目标车辆的轨迹规划,并设计模型预测控制器来对主车进行实时控制,使车辆按照既定轨迹行驶。最后,借助Carsim与MATLAB/Simulink搭建联合仿真平台,对提出的算法进行验证。仿真实验结果表明,该模型的控制误差最大不超过0.15 m,平均误差率约为1.7%,能实现对车辆的精准控制,保证被控车辆安全完成逆向超车。

关 键 词:逆向超车    有向图    A*算法    车车通信    博弈论    模型预测控制  
收稿时间:2022-06-08

Reverse Overtaking Control Algorithm for Autonomous Vehicles
RUAN Shi-feng,HUI Fei,YU Jian-you,ZHANG Zhi-gang,DU Yi-ru,GUO Xing.Reverse Overtaking Control Algorithm for Autonomous Vehicles[J].Computer and Modernization,2022,0(5):119-126.
Authors:RUAN Shi-feng  HUI Fei  YU Jian-you  ZHANG Zhi-gang  DU Yi-ru  GUO Xing
Abstract:In order to solve the problem that two-way lanes are limited by road conditions and traffic characteristics, a reverse overtaking control strategy based on graph search and model predictive control (MPC) is proposed. The strategy obtains global information such as speed and acceleration of the environment vehicles with the help of telematics and in-vehicle sensors, and incorporate the impact of each entity in the multi-vehicle scenario into the overtaking decision. Firstly, based on the global information obtained from vehicle-vehicle communication, combined with a non-cooperative game, each vehicle is predicted within the action of the entire time period, and each area of the road is evaluated for safety based on the prediction, and the evaluation is based on the probability of a vehicle appearing in that area at the next moment. After completing the assessment of the road, the collision probability hot zone map is obtained, and then the safe path is searched by the A* algorithm, and the trajectory planning of the main vehicle is completed according to the safe path. After that, the model prediction controller is designed to control the main vehicle in real time so that the vehicle follows the established trajectory. Finally, the proposed algorithm is verified by building a joint simulation platform with the help of Carsim and MATLAB/Simulink. The simulation test results show that the maximum control error of the model does not exceed 0.15 m, and the average error rate is about 1.7%, which can realize the accurate control of the vehicle and ensure the controlled vehicle to complete the reverse overtaking safely.
Keywords:reverse overtaking  directed graph  A* algorithm  Vehicle-vehicle communication  game theory  model predictive control  
本文献已被 万方数据 等数据库收录!
点击此处可从《计算机与现代化》浏览原始摘要信息
点击此处可从《计算机与现代化》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号