Traffic State Forecasting of Typical Roads in Beijing

Abstract

The comprehensive analysis of traffic states are effective ways to eliminate some traffic problems and enhance the supervising ability of the traffic management departments, which includes real-time monitoring, evaluation and prediction the states of the entire city. With analyzing the traffic flow characteristic on several typical roads in Beijing and summarizing the existing traffic prediction models, this paper proposes a combination forecasting model. It is mainly based on the nonparametric regression model. The combination of Fourier's history estimated model, nonparametric autoregressive model and nonparametric neighborhood regression model are used to predict the traffic state of typical Roads. Considering the reality of the traffic flow information collection system of Beijing and the needs of predicting information released by graphical way in the future, the paper also presents the heterogeneous data fusion methods and road traffic code model.