| 高速公路RBF神经网络限速控制 |
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| 引用本文： | 梁新荣,刘智勇,毛宗源. 高速公路RBF神经网络限速控制[J]. 计算机工程与应用, 2005, 41(6): 194-195,201 |
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| 作者姓名： | 梁新荣 刘智勇 毛宗源 |
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| 作者单位： | 华南理工大学自动化科学与工程学院,广州,510640;五邑大学信息学院,广东,江门市,529020;五邑大学信息学院,广东,江门市,529020;华南理工大学自动化科学与工程学院,广州,510640 |
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| 基金项目： | 广东省自然科学基金项目(编号:010486)资助 |
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| 摘 要： | 针对高速公路限速控制是一个非线性时变系统、难以用数学模型准确建模这一特点,提出了RBF神经网络控制方法。阐述了RBF神经网络的结构和训练方法,根据高速公路主线上车辆数目以及路面状况、气象条件等信息,建立交通流速度控制RBF神经网络模型,并进行了仿真研究。该网络学习速度快、自适应强,泛化能力好,对交通流限速控制的在线建模具有重要意义。
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| 关 键 词： | RBF神经网络 高速公路 速度限制 仿真 |
| 文章编号： | 1002-8331-(2005)06-0194-02 |
RBF Neural Network Control for Speed Limitation on Freeway |
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| Liang Xinrong,Liu Zhiyong,Mao Zongyuan. RBF Neural Network Control for Speed Limitation on Freeway[J]. Computer Engineering and Applications, 2005, 41(6): 194-195,201 |
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| Authors: | Liang Xinrong Liu Zhiyong Mao Zongyuan |
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| Affiliation: | Liang Xinrong 1,2 Liu Zhiyong 2 Mao Zongyuan 11 |
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| Abstract: | The control for speed limitation on freeway is a nonlinear and time variable system,it is difficult to model with a mathematical model.A control method based on RBF Neural Network is put forward.The network structure and train algorithm are formulated.The RBF network model for speed limitation of freeway traffic is built according to such information as the number of vehicles on freeway,the performance of road surface,and the weather conditions.Simulation research is also carried out by taking full advantage of a computer.The fast learning ability,strong adaptability,and good generality are of great importance to realize on-line modeling for speed limitation of traffic flow. |
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| Keywords: | RBF neural network freeway speed limitation simulation |
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