Title :
Combined short-term traffic flow forecast model for Beijing Traffic Forecast System
Author :
Dong, Shen ; Sun, Linguang ; Chang, Tanghsien ; Lu, Huapu
Author_Institution :
Res. Inst. of Civil Aviation Safety, Civil Aviation Univ. of China, Tianjin, China
Abstract :
A short-term traffic flow forecasting model is studied for Beijing Traffic Forecast System. From a practical view, a combined forecast model is considered, including Discrete Fourier Transform model, Autoregressive model and Neighborhood Regression model. In order to update weight real-timely, the Bayesian approach is utilized to adjust weights of each sub-model. A large amount of data test is carried out among all sub-models and combined model. It shows advantages of combined model.
Keywords :
Bayes methods; autoregressive processes; discrete Fourier transforms; forecasting theory; regression analysis; road traffic; Bayesian approach; Beijing traffic forecast system; autoregressive model; combined model; discrete Fourier transform model; neighborhood regression model; short-term traffic flow forecasting model; Conferences; Intelligent transportation systems; USA Councils;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2011 14th International IEEE Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4577-2198-4
DOI :
10.1109/ITSC.2011.6083041
