Traffic Flow Prediction And Bi-level Programming Model For Estimating Origin Destination

With the development of economy,the contradiction between the growth of traffic volume and the road condition is becoming prominent,which has greatly restricted the development of social economy.The research of traffic prediction model can benefit the control and decision,and become the precondition of Intelligent Transportation System.Origin-Destination estimation,as one of the process in making transportation net programming and managing,can reduce the effort needed for frequent large scale Origin-Destination surveys.This thesis consists mainly of two parts:In the traffic prediction part,based on the analysis of the characteristics of real traffic system and traffic flow,which are complex,nonlinear and noise,a new approach is proposed for traffic flow prediction.Firstly wavelet transform is employed to eliminate the noise of observed data in order to reflect the essence of traffic flow.Then a hybrid methodology is proposed that exploits the unique strength of the ARIMA model and the SVM model in forecasting traffic flow with the worked data.Finally,numerical examples are given on the field to testify the precision of the model.Results show that the hybrid model,which takes advantage of the unique strength of the two models in linear and nonlinear model,can produce more accurate predictions than that of single model;the hybrid model that uses the method of is more efficient and reliable.The hybrid model based on wavelet denoising can be an efficient method to the short-term traffic flow prediction.In the Origin-Destination estimation part,a bi-level programming model is used to describe the public transit network.The upper optimization model which using the EM(Maximum Entropy) model can make use of the old OD matrix.The lower optimization model programming model use the improved SUE(Stochastic User Equilibrium) model which based on Logit distribution.The improved SUE model make a combined consideration of the factors like interaction among traffic modes on mixed traffic network,congested network and elastic OD demand.For the model is a NP problem,a IOA algorithm has present and an experimental research on the OD estimation based on the bi-level programming was carried out.