A Study On The Comparative Of Traffic Distribution Models

China's urbanization and motorization is advancing at an unprecedented rate. Followed by it, the super-urban land development, traffic congestion, environmental pollution and traffic accident are increasing the pressure in the cities. With the urban population growth and urban expansion, the city's traffic volume will have a relatively large increase, followed by that the distribution of the population and jobs are changed. So the city's transportation infrastructure and transportation facilities will be corresponding changed. Therefore, an effective urban transport planning is imperative. Urban transport systems must have certain forward-looking and first developed before the social and economic. Only in that way can we really play the role of transport planning, so predicting the city's traffic distribution is particularly important.Traffic distribution forecast is very important. Once we obtained the higher precision OD matrix, traffic demand forecasting will have guarantee. Traffic distribution model has been developed for a good variety and also achieved good results in the actual planning, but still have lots of problems. For example, the model with the same item in different terms the result is different. That is because the actual situation undermined the accuracy of the modeling process. So it's difficult for planning staff to choose the model correctly. They choose the model only rely on the accumulation of practical experience in the process, which would make the final result of the persuasive greatly discount.Because of the importance of traffic distribution in transportation planning for urban development, we should make higher prediction. So we are choosing the popular models: gravity model, growth factor models and maximum entropy model to give a comparative analysis. It's important to obtain the reliable data. So firstly we introduce how to improve the data accuracy in a traffic survey. Secondly, we use traffic survey data of Benxi transportation planning in 2004 to do a lot of numerical experiments to compare the differences between the three models. Thirdly, we give a depth comparative analysis of the three models from a theoretical level and prove the consistency of these models. Finally, we describe the relationship between the traffic distribution and the urban space and give some guiding principles and recommends on the use of traffic distribution model.