大城市高架路实测数据分析与交通流模型研究

MEASURED DATA ANALYSIS OF URBAN EXPRESSWAY AND RESEARCH ON TRAFFIC FLOW MODELS

对上海市中心延安高架路一个路段交通流进行长时间录像拍摄,提取到"车速-车头间距"有效数据26000余对.应用该批实测数据,对多种常见交通流速密关系模型进行比较研究后发现,一维管流模型在我国高速道路交通流参数计算中具有优势.提出采用变参数一维管流模型刻画交通流非线性特征的基本方法.

Traffic flow models are important to describe various complex traffic procedures on highway or road network and to establish intelligence traffic systems（ITS）.Lots of improvement has been made in traditional traffic flow models,and many new traffic flow theories have been developed. Generally the formation of a traffic flow model requires massive observation as well as in-depth analysis of real road traffic.Empirical data are indispensable to identifying parameters when the corresponding model is utilized.One of the basic demands of collecting such data is repeatability,that is,a large amount of measuring must be conducted under nearly identical circumstances to provide the data and model parameters. It is drawn in this paper that over 26000＂car velocity-headway distance＂data pairs are obtained from the long time video recordings of a section in Yanan Expressway of Shanghai with three traffic circumstances：peak hour;low traffic hour;snow day.This way to collect traffic data is different from some traditional methods in which sensors are fixed along the road or buried underground to measure the＂car velocity-traffic flow＂data pairs.The obtained＂velocity-headway distance＂data pairs have better synchronized characteristics and are easy to transform into＂velocity-density＂or＂flow-density＂data pairs for further research. After comparison study of manifold well-known traffic flow velocity-density models based on above measuring data,the superiorities of one-dimensional pipe-flow model are found in calculating the traffic flow parameters of expressway in our country. Since the key parameter in 1-D pipe-flow model,named traffic behavior parameter m,can be adjusted, a basic method is proposed to draw the non-linear characteristics of traffic flow by 1-D pipe-flow model with changing parameters.