On the Short-term Prediction of Traffic State: An Application on Urban Freeways in ROME

Abstract This paper explores the traffic state estimation on freeways in urban areas combining point-based and route-based data in order to properly feed a second order traffic flow model, recursively corrected by an Extended Kalman Filter. In order to overcome the possible lack of real-time information, authors propose to use simulation-based data in order to improve the accuracy of the traffic state estimation. This model was tested on a urban freeway stretch in Rome, for which a set of real-time data during the morning of a typical