Emergency evacuation models based on cellular automata with route changes and group fields

In this paper, we propose an extension of cellular automata models applied to emergency evacuation pedestrian dynamics. The new extensions are the route change probabilities and group fields. The first extension allows for pedestrians to change direction when necessary to access an alternate exit route. The second extension adds a field that makes groups of pedestrians always walk close to each other and exit together. Several experiments were conducted to study the effects of these new extensions, first to verify the associated collective phenomena and to verify the effect with the security performance measures, more precisely, in the evacuation time, as well as to perform comparisons with other previous models. The main conclusions are that the effects of these new extensions effectively modify the security performance measures and can therefore be important for improving the models and providing better estimates.

[1]  Andreas Schadschneider,et al.  Friction effects and clogging in a cellular automaton model for pedestrian dynamics. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Daichi Yanagisawa,et al.  Mean-field theory for pedestrian outflow through an exit. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  Stephen Wolfram,et al.  Cellular Automata And Complexity , 1994 .

[4]  A. Seyfried,et al.  Basics of Modelling the Pedestrian Flow , 2005, physics/0506189.

[5]  Michael Schreckenberg,et al.  Simulation of competitive egress behavior: comparison with aircraft evacuation data , 2003 .

[6]  Frederico R. B. Cruz,et al.  State-dependent stochastic mobility model in mobile communication networks , 2010, Simul. Model. Pract. Theory.

[7]  John von Neumann,et al.  Theory Of Self Reproducing Automata , 1967 .

[8]  Andreas Schadschneider,et al.  Extended Floor Field CA Model for Evacuation Dynamics , 2004, IEICE Trans. Inf. Syst..

[9]  Shaobo Liu,et al.  Evacuation from a classroom considering the occupant density around exits , 2009 .

[10]  Frederico R. B. Cruz,et al.  Congested Emergency Evacuation of a Population Using a Finite Automata Approach , 2013 .

[11]  Daichi Yanagisawa,et al.  Anticipation effect in pedestrian dynamics: Modeling and experiments , 2012 .

[12]  Tom Van Woensel,et al.  A stochastic approach to traffic congestion costs , 2009, Comput. Oper. Res..

[13]  Tommaso Toffoli,et al.  Cellular Automata as an Alternative to (Rather than an Approximation of) Differential Equations in M , 1984 .

[14]  A. Schadschneider,et al.  Simulation of pedestrian dynamics using a two dimensional cellular automaton , 2001 .

[15]  Frederico R. B. Cruz,et al.  An M/G/C/C state-dependent network simulation model , 2005, Comput. Oper. Res..

[16]  Andrew Ilachinski,et al.  Cellular Automata: A Discrete Universe , 2001 .

[17]  C. Dorso,et al.  Morphological and dynamical aspects of the room evacuation process , 2007 .

[18]  Hironori Hirata,et al.  Method of crowd simulation by using multiagent on cellular automata , 2003, IEEE/WIC International Conference on Intelligent Agent Technology, 2003. IAT 2003..

[19]  Norman I. Badler,et al.  Controlling individual agents in high-density crowd simulation , 2007, SCA '07.

[20]  Andreas Schadschneider,et al.  Quantitative analysis of pedestrian counterflow in a cellular automaton model. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  Andreas Schadschneider,et al.  Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics , 2002 .

[22]  A. Schadschneider Cellular Automaton Approach to Pedestrian Dynamics - Theory , 2001, cond-mat/0112117.

[23]  Nicholas R. Jennings,et al.  Foundations of distributed artificial intelligence , 1996, Sixth-generation computer technology series.

[24]  Tony White,et al.  Macroscopic effects of microscopic forces between agents in crowd models , 2007 .

[25]  Dirk Helbing,et al.  Pedestrian, Crowd and Evacuation Dynamics , 2013, Encyclopedia of Complexity and Systems Science.

[26]  Alexander Stepanov,et al.  Production , Manufacturing and Logistics Multi-objective evacuation routing in transportation networks , 2009 .

[27]  J. MacGregor Smith,et al.  M/G/c/c state dependent travel time models and properties , 2014 .