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A Stochastic Cellular Automata for Modeling Pedestrian Groups Distribution
Lorenza Manenti, Sara Manzoni and Stefania

Cellular Automata approach has already been used in the literature to develop computational models for the controlled generation of granulometric distribution. In this work, we present a model based on a Stochastic Cellular Automata to generate granulometric distribution of pedestrian groups in structured spaces, taking into account morphological properties of groups and basic behavioral rules. The main scope of the model is to produce plausible initial configurations for pedestrian simulations, giving a discussion about the calibration and the possible validation of the tool based on the CA-model.

Keywords: Stochastic CA, groups, pedestrians, crowd, granulometric distributions, percolation, simulation

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