Dynamic Data–Driven Simulation of Pedestrian Movement with Automatic Validation

Jakub Porzycki (), Robert Lubaś (), Marcin Mycek () and Jarosław Wąs ()
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Jakub Porzycki: AGH University of Science and Technology, Department of Applied Computer Science
Robert Lubaś: AGH University of Science and Technology, Department of Applied Computer Science
Marcin Mycek: AGH University of Science and Technology, Department of Applied Computer Science
Jarosław Wąs: AGH University of Science and Technology, Department of Applied Computer Science

A chapter in Traffic and Granular Flow '13, 2015, pp 129-136 from Springer

Abstract: 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.

Keywords: Automatic Validation; Social Distances Model; Data-driven Simulation; Pedestrian Tracking; Pedestrian Description (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-10629-8_15

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DOI: 10.1007/978-3-319-10629-8_15

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