The forecasting of traffic flow is an important thesis of the research of intelligent transportation systems (ITS). A good method of traffic flow forecasting can play a very important role in traffic control and transportation programming. This paper first analyzed the Kalman filter theory in detail considering the following features of the Kalman filter method: choose the forecast factors flexibly, forecast accurately, and calculate expediently. Then a short-term traffic volume forecast model based on the Kalman filter theory was established. At last, the paper simulated one segment of the Jing-Jin-Tang freeway using the traffic flow data from a historical monitoring database in order to verify the availability of the advanced model. This research may provide a basis for traffic data analysis and a support for traffic management and traffic control.
Research of Short-Term Traffic Flow Forecast Method Based on the Kalman Filter
11th International Conference of Chinese Transportation Professionals (ICCTP) ; 2011 ; Nanjing, China
ICCTP 2011 ; 960-968
2011-07-26
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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