Abstract
Cellular Automata was applied to model the pedestrian flow, where the local neighbor and transition rules implemented to each person in the crowd were determined automatically by the experience of pedestrians. The experience was based on two parameters; the number of continuous vacant cells in front of the cell to proceed, and the number of pedestrian in the cell to proceed. The experience was evaluated numerically, and a pedestrian selected the cell to proceed by the evaluated index. The flow formations by pedestrians in the opposite direction on a straight pathway and on a corner were simulated, and the number of rows was discussed in relation to the density of pedestrian on the simulation space.
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References
Wolfram, S.: Cellular Automata. Los Alamos Science, 2–21 (Fall 1983)
Gutowitz, H.: Cellular Automata - Theory and Experiment, pp. 254–270. MIT Press, Cambridge (1990)
Mehta, A.: Granular Matter - An Interdisciplinary Approach, pp. 85–120. Springer, Heidelberg (1994)
Helbing, D., Farkas, I., Vicsek, T.: Simulating Dynamical Features of Escape Panic. Nature 407, 487–490 (2000)
Shiraishi, T., Morishita, S., Gavin, H.P.: Estimation of Equivalent Permeability in MR Fuid Considering Cluster Formation of Particles. Transactions of ASME, Journal of Applied Mechanics 71(2), 201–207 (2004)
Morishita, S., Nakatsuka, N.: Simulation of Emergency Evacuation by Cellular Automata. In: Proceedings of 6th International Conference on Complex Systems, pp. 92–97 (2002)
Narimatsu, K., Shiraishi, T., Morishita, S.: Acquisition of Local Neighbor Rules in the Simulation of Pedestrian Flow by Cellular Automata. In: Sloot, P.M.A., Chopard, B., Hoekstra, A.G. (eds.) ACRI 2004. LNCS, vol. 3305, pp. 211–219. Springer, Heidelberg (2004)
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Ishii, H., Morishita, S. (2010). A Learning Algorithm for the Simulation of Pedestrian Flow by Cellular Automata. In: Bandini, S., Manzoni, S., Umeo, H., Vizzari, G. (eds) Cellular Automata. ACRI 2010. Lecture Notes in Computer Science, vol 6350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15979-4_49
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DOI: https://doi.org/10.1007/978-3-642-15979-4_49
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