自适应神经模糊推理的方向驾驶员模型研究  

Research on Directional Driver Model Based on Adaptive Neural Fuzzy Inference

作　　者：曹艳玲 张琦 CAO Yan-ling;ZHANG Qi(College of Vehicle and Traffic Engineering Henan University of Science and Technolog,He’nan Luoyang471003,China)

机构地区：[1]河南科技大学车辆与交通工程学院,河南洛阳471003

出　　处：《机械设计与制造》2021年第1期185-187,192,共4页Machinery Design & Manufacture

基　　金：国家自然科学基金资助项目(61473115)。

摘　　要：以方向驾驶员模型为研究对象,讲解了自适应神经模糊推理系统的原理和结构,并基于自适应神经模糊推理系统建立了一种两输入单输出的方向驾驶员模型。输入变量是道路参考线到预瞄点的横向偏差和道路参考线与车辆X轴之间面积偏差,输出是车辆方向盘转角。首先,通过车辆动力学仿真软件Carsim获取车辆的仿真数据。其次,自适应神经模糊推理系统通过仿真数据能够自动获取模糊控制规则并建立方向驾驶员模糊控制器。最后,将基于自适应神经模糊推理系统建立的方向驾驶员模型和Carsim中的车辆动力学模型进行联合仿真。仿真结果表明:基于自适应神经模糊推理系统所建立的方向驾驶员模型能够对路径进行良好的跟踪。In this paper,the direction driver model is taken as the research object,and the principle and structure of the adaptive neuro-fuzzy inference system are explained.Based on the adaptive neuro-fuzzy inference system,a two-input and single-output direction driver model is established.The input variables are the lateral deviation from the road reference line to the preview point and the area deviation between the road reference line and the X axis of the vehicle,and the output is the steering wheel angle of the vehicle.Firstly,the vehicle simulation data are obtained by the vehicle dynamics simulation software Carsim.Secondly,The adaptive neural fuzzy inference system can automatically obtain the fuzzy control rules and establish the directional driver fuzzy controller through the simulation data.Finally,the directional driver model based on adaptive neural fuzzy inference system and the vehicle dynamics model in Carsim are simulated.The simulation results show that the directional driver model based on the adaptive neural fuzzy reasoning system can track the path well.

关 键 词：驾驶员模型 自适应 神经模糊推理 路径跟踪 

分 类 号：TH16[机械工程—机械制造及自动化] U461[机械工程—车辆工程]