A neural network approach for freeway traffic flow prediction

Traffic flow modeling is an essential component of any traffic control or monitoring system. This paper presents a new short term traffic flow prediction model based on a feedforward neural network. The structure determination of this neural network is viewed as a system identification problem, and the model performances are validated using both simulation and real traffic data obtained from the I-880 freeway in Hayward, California.