摘要
本文提出将神经网络和模糊推理用于高速公路交通控制系统的建模及多层描述的一般性方法和框架。其主要思想是：利用神经网络及其他智能方法建立高速公路稳态和动态模型；在此基础上结合交通系统的特点提出改进的多层描述方法，即把高速公路交通系统控制问题分为自组织层，自适应层，最优化层和调节层，试图解决传统方法在高速公路交通系统的分析、建模和控制中遇到的问题。
The neural network and fuzzy inference used for modeling and mulfi layer descripfions of freeway traffic control system as a generalized method and frame work are put forward in this paper.Their principal thought is:the neural network and other intelligent methods are used to establish freeway steady state and dynamic models;based on these models and in conjunction with the characteristics of traffic systems,a modified multi layer description method is proposed,i.e.the control problems of freeway traffic system are divided into self organizing layer,adaptive layer,optimizing layer and regulating layer,trying to solve the prolem of traditional methods encountered in analysis,modelling and control of freeway traffic systems.
出处
《公路交通科技》
EI
CAS
CSCD
北大核心
1998年第1期39-44,共6页
Journal of Highway and Transportation Research and Development
基金
广东省高教厅重点扶持学科项目资助
关键词
高速公路
智能交通控制
神经网络
多层描述
Freeway Intelligent traffic control Neural network Multi layer description
