Stochastic Transition Model for Pedestrian Dynamics

Michael Schultz ()
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Michael Schultz: Technische Universität Dresden, Department of Air Transport Technology and Logistics, Faculty of Transport and Traffic Sciences “Friedrich List”

A chapter in Pedestrian and Evacuation Dynamics 2012, 2014, pp 971-985 from Springer

Abstract: Abstract The proposed stochastic model for pedestrian dynamics is based on existing approaches using cellular automata, combined with substantial extensions, to compensate the deficiencies resulting of the discrete grid structure. This agent motion model is extended by both a grid-based path planning and mid-range agent interaction component. The stochastic model proves its capabilities for a quantitative reproduction of the characteristic shape of the common fundamental diagram of pedestrian dynamics. Moreover, effects of self-organizing behavior are successfully reproduced. The stochastic cellular automata approach is found to be adequate with respect to uncertainties in human motion patterns, a feature previously held by artificial noise terms alone.

Keywords: Pedestrian dynamics; Cellular automaton; Stochastic transition; Navigation; Dynamic motion field (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-02447-9_81

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DOI: 10.1007/978-3-319-02447-9_81

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