港口公路集疏运货运交通量预测及交通配流研究

发布时间：2018-12-06 16:20

【摘要】：近年来,我国港口物流快速发展,港口货物吞吐量、港口集装箱吞吐量快速增长,已经形成了环渤海、长江三角洲、东南沿海、珠江三角洲和西南沿海5大区域港口群。2011年,全国港口货物吞吐量为832452万吨,在港口物流货物吞吐量快速增长的同时,已经形成了港口码头、后方物流节点及其物流园区之间的功能分工与协作关系,形成了以码头与物流园区等间货物运输格局的港城概念与现实,使得港口货物集疏运带来的货运交通量对港口内部、港口所在城市的交通造成的影响日益凸显。本论文着重研究港口货运交通流的预测和配流问题。首先,论文分析了港口货运交通流特性。具体分析了港口货运交通的构成、港口货运交通流的时间分布特征、路网功能导向特征,并以黄骅港为例,具体分析了针对大型港口发展趋势的港城港口货运交通流的时间不均匀性、集疏运路网功能导向性。其次,论文研究港口公路集疏运货运交通量预测方法。具体分析了影响港口公路集疏运货运交通流的因素,建立了港口货运交通量的BP人工神经网络预测模型,并采用黄骅港公路集疏运系统实际业务数据,采用Matlab仿真平台,进行了具体的验证分析。再次,论文研究了港口公路集疏运货运交通配流,具体根据港口公路集疏运路网交通流的时间分布特性、路网功能导向性,对配流模型中路阻函数进行了改进,并采用黄骅港港口集疏运网络的预测数据和TransCAD仿真平台进行了具体的验证分析。
[Abstract]:In recent years, the rapid development of port logistics, port cargo throughput and port container throughput have formed five regional port groups around the Bohai Sea, the Yangtze River Delta, the southeast coast, the Pearl River Delta and the southwest coast. The national port cargo throughput is 8.32452 billion tons. With the rapid growth of port logistics cargo throughput, the functional division of labor and cooperation between port terminals, rear logistics nodes and their logistics parks have been formed. The concept and reality of port city is formed in the pattern of freight transportation such as wharf and logistics park, which makes the traffic volume brought by the collection and distribution of port cargo to the interior of the port and the traffic of the city where the port is increasingly prominent. This paper focuses on the prediction and distribution of port freight traffic flow. Firstly, the characteristics of port freight flow are analyzed. The composition of port freight traffic, the time distribution characteristics of port freight traffic flow, the function guidance characteristics of road network are analyzed in detail, and the Huanghua Port is taken as an example. The time inhomogeneity of port freight traffic flow and the function guidance of collecting and distributing network are analyzed concretely in view of the development trend of large port. Secondly, the paper studies the forecasting method of port highway transportation volume. This paper analyzes the factors that affect the traffic flow of port highway transportation, establishes the BP artificial neural network forecasting model of port freight traffic volume, and adopts the actual operation data of Huanghua Port highway transportation system, and adopts the Matlab simulation platform. The concrete verification analysis is carried out. Thirdly, the paper studies the distribution of port highway traffic, and improves the road resistance function according to the time distribution characteristics of the traffic flow and the function of the road network. The prediction data of Huanghua Port port transportation network and the TransCAD simulation platform are used to verify and analyze it.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：U491.113;F552;F542

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