TRAFFIC FORECAST IN LARGE SCALE FREEWAY NETWORKS

Traffic flow in large and complex freeway networks is a highly nonlinear phenomenon, which makes traffic forecast a difficult task. In this article an approach to traffic forecast is presented, which uses a micro-simulator for traffic flow combined with current and historical traffic data. The micro-simulator and locally measured current traffic data are used to reconstruct the current network-wide traffic state. Then, this state is combined with historical traffic data to forecast the traffic development. This framework is applied to the freeway network of the German state North Rhine-Westphalia. The micro-simulator uses an advanced cellular-automaton model for traffic flow, and the data are supplied from more than 4,000 locally installed loop-detectors, which deliver information on the (local) traffic state online minute by minute.