Dynamic Systems for Individual Tracking via Heterogeneous Information Integration and Crowd Source Distributed Simulation
Technical Report,14 Mar 2013,31 Aug 2015
Georgia Institute of Technology Atlanta United States
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Tracking the movement of individuals in complex urban environments using mobile sensors is a challenging, but important problem in applications such as law enforcement, homeland security and defense. The Dynamic Data Driven Application Systems DDDAS paradigm offers a natural approach to attacking this problem. This two-year research project explored new computational technologies based on the DDDAS paradigm that could be applied to track vehicles in real time. Research accomplishments from this project include 1 the development of approaches to improve the transient response of data driven distributed simulations, 2 development of methods for on-line data driven calibration of traffic simulations, 3 development of data analytics for real-time prediction of vehicle trajectories, 4 development of algorithms for efficient execution of replicated transportation simulations, 5 analyses of data distribution methods, 6 energy analysis of synchronization algorithms for distributed simulations, and 7 development of parallel algorithms for non-negative matrix factorization for vehicle detection.