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This paper describes a general framework called Hybrid Dynamic Mixed Networks (HDMNs) which are Hybrid Dynamic Bayesian Networks that allow representation of discrete deterministic information in the form of constraints. We propose approximate inference algorithms that integrate and adjust well known algorithmic principles such as Generalized Belief(More)
With the proliferation of wireless communication technologies, inter-vehicle communication (IVC) could potentially be applied to solve ever-worsening transportation problems around the world. In this paper, we study impacts of network vehicular traffic on IVC, apply IVC to route-guidance, and report preliminary field tests. These studies are intended to(More)
This work was performed as part of the ATMS Testbed Research and Development Program of the University of California, Irvine. The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views of polices of the State of(More)
This paper describes a method for storing, modeling, and processing an individual’s travel history collected with a GPS enabled device. The technique uses a general framework called Hybrid Dynamic Mixed Networks (HDMNs), which are Hybrid Dynamic Bayesian Networks that allow representation of discrete deterministic information in the form of constraints. We(More)
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