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Active Traffic Management (ATM) is the ability to dynamically manage recurrent and nonrecurrent congestion based on prevailing traffic conditions. Focusing on trip reliability, it maximizes the effectiveness and efficiency of freeway corridors. ATM relies on fast and trustworthy traffic simulation software that can assess a large number of control strategies for a given road network, given various scenarios, in a matter of minutes. Effective traffic density estimation is crucial for the successful deployment of feedback algorithms for congestion control. Aurora Road Network Modeler (RNM) is an open-source macrosimulation tool set for operational planning and management of freeway corridors. Aurora RNM employs Cell Transmission Model (CTM) for road networks extended to support multiple vehicle classes. It allows dynamic filtering of measurement data coming from traffic sensors for the estimation of traffic density. In this capacity, it can be used for detection of faulty sensors. The virtual sensor infrastructure of Aurora RNM serves as an interface to the real world measurement devices, as well as a simulation of such measurement devices.