基于安全距离模型的车辆跟随控制策略研究
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摘要
针对车辆协同驾驶领域中的跟随过程,建立了安全距离控制模型,采用BP神经网络PID控制策略设计了控制器,并通过MATLAB/Simulink软件进行仿真分析,将BP神经网络PID控制与传统PID控制的控制效果进行了对比,最后运用缩微环境下的智能车辆系统试验平台设计了Update算法,完成了跟随试验验证。仿真和试验结果表明,本文设计的智能控制器减小了车间距误差,提高了控制准确性,能满足车辆安全跟随行驶要求。
A safe distance control model is established for the follow-up process in the field of vehicle coordinated driving.The controller is designed by BP neural network PID control strategy,and the simulation is carried out with Matlab/Simulink software.BP neural network PID control is compared with the traditional PID control in term of control effect.Finally,the Update algorithm is designed using the experimental platform of the intelligent vehicle system in the microenvironment,and the following experiment verification is completed.The simulation and experimental results show that the intelligent controller designed in this research reduces the inter-vehicle distance error,improves the accuracy of control,and can meet the requirement of safe follow-up driving of vehicles.
A safe distance control model is established for the follow-up process in the field of vehicle coordinated driving.The controller is designed by BP neural network PID control strategy,and the simulation is carried out with Matlab/Simulink software.BP neural network PID control is compared with the traditional PID control in term of control effect.Finally,the Update algorithm is designed using the experimental platform of the intelligent vehicle system in the microenvironment,and the following experiment verification is completed.The simulation and experimental results show that the intelligent controller designed in this research reduces the inter-vehicle distance error,improves the accuracy of control,and can meet the requirement of safe follow-up driving of vehicles.
引文
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[2]Payman Shakouri,Andrzej Ordys,Mohamad R,et al.Adaptive Cruise Control with Stop&go Function Using the State-Dependent Nonlinear Model Predictive Control Approach[J].ISA Transactions,2012,51(5):622-631.
[3]Sathiyan S P,Kumar S S,Selvakumar A I.Optimised Fuzzy Controller for Improved Comfort Level During Transitions on Cruise and Adaptive Cruise Control Vehicles[C]//International Conference on Signal Processing&Communication Engineering Systems.IEEE,2015.
[4]张向南.智能车辆队列纵向控制系统的建模与实验研究[D].贵阳:贵州大学,2015.
[5]王正林.MATLAB/Simulink与控制系统仿真[M].北京:电子工业出版社,2012.
[6]高飞.MATLAB智能算法超级学习手册[M].北京:人民邮电出版社,2014.
[7]余胜威,曹中清.基于人群搜索算法的PID控制器参数优化[J].计算机仿真,2014,31(9):347-350+373.
[8]王敬志,任开春,胡斌.基于BP神经网络整定的PID控制[J].工业控制计算机,2011,24(3):72-73.
[9]葛满强.车路协同环境下多模式通信平台设计与典型场景应用[D].北京:北京交通大学,2015.