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In this paper, a dynamic macroscopic traffic simulation model was developed based on a high-order continuum-modeling scheme using a Boltzman-like analogy between traffic and gases to respond to high-density and low-density traffic flows. In addition, a queuing-based equilibrium speed-density relationship was implemented to reflect a wide scope of traffic phenomena. The developed traffic simulation model was shown to robustly predict and respond to a wide variety of traffic conditions on a real-time basis. The model provides information on expected traffic flow elements both on a statistical framework and network display format, a fundamental element in transport telematics applications. Results of the model application on the Munich network show the developed model to produce more reliable traffic performance estimates than those developed by other continuum-based simulation models.