SHORT TERM TRAFFIC FLOW FORECASTING USING ARTIFICIAL NEURAL NETWORKS (original) (raw)

Traffic flow forecasting is a critical issue in detection of the traffic congestions. Better forecasts provide better routes, less travel time and less traffic bottlenecks. In this study, an existing traffic dataset is used for forecasting by Artificial Neural Networks (ANN), which is a commonly used method in this research area. At first, statistical analysis is conducted to reveal the structure of the data such as seasonality, trend, etc. Then for the organized data, backpropagation artificial neural network model is set up for forecasting the traffic flow. Finally, the forecast values are compared with the real data and different studies which use the same datasets.