A real-time freeway network traffic surveillance toolA real-time freeway network traffic surveillance tool Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2015-11-202006enThis paper presents a real-time freeway network traffic surveillance tool RENAISSANCE. Based on a stochastic macroscopic freeway network traffic flow model and the extended Kalman filter, RENAISSANCE is fed with a limited amount of real-time traffic measurements to enable a number of freeway network traffic surveillance tasks, including traffic state estimation and prediction, travel time estimation and prediction, queue tail/head/length estimation and prediction (queue tracking), and incident alarm. The paper first introduces the stochastic macroscopic freeway network traffic flow model and a real-time traffic measurement model, upon which a complete dynamic system model for freeway network traffic is established, with a special attention to the handling of some important model parameters. The addressed traffic surveillance tasks are described along with the functional architecture of RENAISSANCE. A simulation test was conducted for the tool with respect to a hypothetical freeway network example, while the traffic state estimator of RENAISSANCE was also tested with real traffic measurement data collected from a Bavarian freeway.http://creativecommons.org/licenses/by/4.0/Control Systems Technology11418 - 32 Yibing Wang Papageorgiou Markos Παπαγεωργιου Μαρκος Messmer, A. Institute of Electrical and Electronics Engineers Extended Kalman filter on-line model parameter estimation stochastic macroscopic freeway network traffic