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With the rapid economic development of our society , the accelerating process of urbanization , the urban population and the amount of motor vehicles has increased dramatically , growing traffic demand and road network contradiction between the lack of supply levels , major urban traffic congestion problems have become increasingly prominent . Shiqiao city of Panyu District in recent years, as the socio-economic development , people's living standards improve , vehicle ownership rapid development ; With the accelerated pace of the Guangzhou urban space \held and other factors , the the Shiqiao city traffic pressure growing , all kinds of traffic problems also will be increasing rapidly . For this reason, to ease the Shiqiao urban traffic congestion the status quo , optimize the layout of the Shiqiao urban trunk road network , improve the road network structure , improve road capacity , problem solved . Traffic demand forecast is the core of modern transportation planning , is key to the planning of road network traffic is a prerequisite and an important basis of the urban road network optimization research . In this paper, the Shiqiao road network traffic demand forecast , for example , the introduction of advanced information processing technologies - GIS , optimization of the road network data model ; predictive modeling with today 's mainstream transportation planning software TransCAD ; combination Shiqiao city uses three-phase traffic forecasting method , modeling and prediction of the the Shiqiao city road network traffic demand . The main content of this paper is as follows: 1 , the transport needs of the study area, the status quo analysis : population land use , socio-economic , motor vehicle ownership ; 2 study area status quo road data collection ; 3 , city road network traffic demand forecasting principles, theories and model ; 4 , the study area traffic survey and GIS - based traffic forecast underlying data processing ; 5 , socio-economic development in the study area prediction research , including population , gross domestic product ( GDP ) forecast , and motor vehicle ownership predict three parts ; 6 base year OD based on the status quo road network traffic flow thrust reversers research; 7 , the combined population of the study area , the gross domestic product ( GDP ) and motor annual vehicle growth in the number as well as the base year OD matrix in TransCAD by comparative analysis of a variety of models , predicted characteristics of the years 2008 and 2010 , traffic generation , traffic distribution and traffic assignment prediction .
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