Abstract
The article presents a dynamic data-driven simulation of pedestrian movement based on the generalized Social Distances Model, where a simulation system is continuously synchronized with current flow data, gained from Microsoft Kinect depth map. Both simulation and data analysis are real-time processes. Agent appears in simulation, as soon as consecutive pedestrians leave sensors tracking zone. Due to system architecture containing feedback loop, automatic validation and parameters calibration is possible. A new method of depth map based pedestrian tracking is proposed as well as a new algorithm of pedestrian parameters extraction for short trajectories. The paper describes in detail the proposed algorithms, system architecture and an illustrative experiment.
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Porzycki, J., Lubaś, R., Mycek, M., Wąs, J. (2015). Dynamic Data–Driven Simulation of Pedestrian Movement with Automatic Validation. In: Chraibi, M., Boltes, M., Schadschneider, A., Seyfried, A. (eds) Traffic and Granular Flow '13. Springer, Cham. https://doi.org/10.1007/978-3-319-10629-8_15
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DOI: https://doi.org/10.1007/978-3-319-10629-8_15
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