交通流

能否准确地对城市道路交通流进行预测，便成为智能交通系统（IntelligentTransportationsystem，1TS）关键解决的问题之一。

One critical problem of the intelligent transportation system ( ITS ) is whether or not to predict traffic flow of urban roads accurately .

边界部分开放条件下改进N-S交通流模型的研究

A study on an improved N-S traffic flow model with partitive open boundary conditions

基于模糊C均值聚类和神经网络的短时交通流预测方法

A Short-term Traffic Flow Forecasting Method Based on Combination of Fuzzy C-mean Clustering and Neural Network

采用GPS探测车的城市交通流分析

Urban Traffic Flow Analysis Using GPS Vehicle Probe

其中对元胞自动机（CellularAutomaton，简称CA）交通流模型的研究受到广泛地关注。

Many scientists widely focus on investigation of Cellular Automaton ( CA ) traffic flow model .

再利用Lyapunov指数的矩形阵算法，计算出交通流时间序列的最大Lyapunov指数。

The maximum Lyapunov Exponent was get from the time series by the matrix algorithm .

元胞自动机FI和NS交通流混合模型的研究

Study of a Cellular Automaton FI-and-NS Mixed Model for Traffic Flow

基于小波消噪的ARIMA与SVM组合交通流预测

A Hybrid ARIMA and SVM Model for Traffic Flow Prediction Based on Wavelet Denoising

基于Monte-Carlo算法的交通流仿真

Traffic flow simulation based on Monte-Carlo algorithm

最后，对过渡时期交通流的构成、交通流的排列秩序、收费站车道分布特点进行分析，提出了过渡时期ETC的车道设计方案。

Finally , according to the component of interim traffic flow , array order of traffic flow and distributing characteristic of toll lane , the project of ETC lane design is put forward .

本文采用改进型BP神经网络建立起交通流的时间序列模型，该模型可用于短期内道路交通流量的预测。

In this paper , the time-sequence model of traffic flow is based on the improved BP neural network , and this model can be used for short time prediction of traffic flow .

然后运用VC++和OpenGl为手段编制出基于虚拟现实的三维微观交通流仿真软件。

And then , I have created the 3D software of microcosmic traffic flow based on virtual reality by mains of VC + + and OpenGL .

基于短时交通流的特性分析，提出两个改进的预测方法：对于非混沌短时交通流，采用小波分解重构BP神经网络预测方法；对于混沌短时交通流采用相空间重构RBF神经网络预测方法。

Based on the characteristic analysis of short-term traffic flow , BP neural forecasting method based on wavelet resolve-reconstructs and RBF neural forecasting method based on phase space reconstruction are proposed .

根据常用的高速公路交通流宏观动态模型，建立了高速公路交通流的RBF神经网络模型。

On the basis of macroscopic dynamic traffic flow model which is frequently used in traffic control , Radial Basis Function ( RBF ) neural network is designed .

基于采用ARIMA（p，d，0）模型结构的时间序列分析方法，提出一种短时交通流实时自适应预测算法。

Based on time series analysis method adopting ARIMA ( p , d , 0 ) model , a kind of real-time adaptive forecasting method for short-term traffic flow was presented .

本文提出了一种高效的短时交通流预测方法：基于蚁群聚类的RBF神经网络短时交通流预测方法。

In this paper , we put forward an efficient method of short-term traffic flow forecasting : traffic flow forecasting based on ant colony clustering algorithm and RBF neutral network .

本文在NS模型基础上建立了一个新的单车道元胞自动机模型以研究减速带对交通流的影响。

Based on the NS model of traffic flow , we propose a new single-lane cellular automaton model to study the effect of deceleration strips upon traffic flow .

用Matlab结合C++语言编写OVM模型的仿真程序来产生交通流时间序列。

The traffic flow is generated by OVM using the simulation software programmed in matlab and C ~ ( + + ) language .

对BP算法提出了分四步走的全面智能改进方法，并把这种方法应用于对战略交通流的动态时序预测，通过仿真证明了这种改进的优异效果；

This paper brings forward a kind of four steps intelligent improvement precept , and applies the precept to the prediction of strategic traffic flow . By imitation , the paper proves the excellent effect of these improvements .

基于事故影响下的双车道MCD模型，本论文讨论了事故发生后的交通流特性的演变规律。

Based on the two-lane MCD model under accident , we investigate the influence of the accident on traffic flow .

通过分析短时交通流时序特性，将灰色系统理论应用于短时交通流预测，建立了滚动GM（1,1）预测模型。

By analyzing short time traffic flow time sequence property , the gray system theory is used for short time traffic flow prediction and the scrolling GM ( 1,1 ) prediction model is set up .

在第二章，建立三车道无管制CA交通流模型：车道不作限制，三条车道都为行车道，在车道上行驶的车辆具有相同的性能，并允许车辆在任意车道上超车。

Secondly , a three-lane uncontrolled CA traffic flow model is proposed to describe the highway traffic : the model is symmetric with respect to the three lanes as well as with respect to the same type of vehicles .

对BP神经网络层数和神经元的确定，以及转移函数的优化选择进行了深入研究，并给出了基于BP神经网络交通流预测模型的建模方法。

It also carries out detail researches on determination of BP neural network levels and neural elements , as well as optimization of transition functions , and it gives modeling method based on BP neural network traffic flow prediction model .

在MATLAB环境下，根据使各交叉路口在一个周期内车辆平均延误最小的原则，通过采集的实时交通流数据，进行多次仿真实验。

Under the MATLAB environment , the method accords to the rules which make the average vehicle delay minimize in a cycle . Large amounts of simulation were executed based on the real-time traffic flow data of a practical intersection .

基于VRGS的交通流微观仿真软件的开发

Development of the VRGS based Microscopic Traffic Flow Simulation Software

Matlab的仿真实验可以验证，在驾驶员出行规则一致的前提下，系统的发布信息可以逐渐减小交通流的波动状态，使网络状态趋于系统均衡。

Matlab simulation experiment can verify that the issued information of system can decrease the fluctuation of traffic flow gradually in the premise of that the drivers travel with identical principle , and make the state of network tending to system equilibrium .

依据最大交通流导致路段最大饱和度原理将模型简化，并利用蒙特卡洛（MonteCarlo）方法，将模型应用于出现涨落后道路拥挤预测。

In terms of the principle that the utmost traffic flow can result in the greatest traffic saturation , the model is simplifies and is applied to forecast the traffic congestion associated with fluctuation by means of Monte Carlo method .

运用现代控制理论和方法，针对计算机高速互联网中最大努力服务交通流即能控交通流的调节问题，提出了一种基于速率的具有比例加微分（PD）控制器结构的拥塞控制理论和方法。

With regard to the flow regulation of the best-effort traffic , i.e. , the controllable traffic in high-speed computer communication networks , the paper proposes a novel control theoretic approach that designs a proportional-plus-derivative ( PD ) controller for congestion controlling .

概述了交通流模型的基本理论及研究现状，并概括了混杂系统建模的一些方法，然后阐释了Petri网和混杂Petri网的基本理论。

The main content of this paper is as follows : 1 . At first , this paper summarizes fundamental theory of traffic flow model and hybrid system , and then gives the basic theory of Petri Net and Hybrid Petri Net .

交通流CA模型规则简单，计算速度快，在描述交通流特性方面有着独特的优势，它必将会有非常广阔的发展前景。

The transportation flows the CA model rule to be simple , the computation speed is quick , flows the characteristic aspect in the description transportation to have the unique superiority , it will certainly to be able to have the extremely broad prospects for development .