Neural-network models for classification and forecasting of freeway traffic flow stability

Artificial Neural Networks (ANN) have been shown to perform well in classifying and prediction problems. Such a peculiarity was exploited to evaluate the flow-density relationship of a motorway section so as to define the time and spacing stability or instability of its traffic flow. The data base used in this study was built up on the basis of the data collected over the Italian motorway running between Padua and Mestre. These data are suitable for the present study because they provide a sample of time and space, along with the collection of data on weather conditions.