Abstract
Cellular Automata simulations of crowd dynamics can support the design of transportation facilities in terms of efficiency, comfort and safety. The development of realistic CA models requires the acquisition of empirical evidences about human individual and collective behavior. The paper reports the results of controlled experiments of personal space in static and dynamic situations: the area surrounding human body, linked to crowding due to spatial intrusion/restriction. We propose a discrete representation of personal space through discrete potentials and an innovative crowding estimation method (i.e. Cumulative Mean Crowding). Simulation results are focused on the parametric evaluation of pedestrians’ psychological stress reaction to density.
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Acknowledgement
The experimental studied were performed within the authorization of the Ethics Committee of The University of Tokyo, and they were funded by the Japan Society for the Promotion of Science. The authors thank Prof. Katsuhiro Nishinari, Kenichiro Shimura and Claudio Feliciani for their fruitful contribution.
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Gorrini, A., Crociani, L., Vizzari, G., Bandini, S. (2018). Cumulative Mean Crowding and Pedestrian Crowds: A Cellular Automata Model. In: Mauri, G., El Yacoubi, S., Dennunzio, A., Nishinari, K., Manzoni, L. (eds) Cellular Automata. ACRI 2018. Lecture Notes in Computer Science(), vol 11115. Springer, Cham. https://doi.org/10.1007/978-3-319-99813-8_44
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