Influence of the exits’ configuration on evacuation process in a room without obstacle

The floor field model is the most popular cellular automata (CA) model which is used to simulate the pedestrian’s behaviors. In the floor field model, the interaction between pedestrians is expressed by the dynamical field. In this paper, we proposed an improved and simple method to calculate the floor field. In our method, the pedestrians are treated as the movable obstacles which will increase the value of the floor field. The additional value is interpreted as the blocking effect of preceding pedestrians. And then, the influence of the exits’ configuration on evacuation process in a room without obstacle is simulated. The evacuation time for different widths and positions of the exits is investigated.

[1]  Katsuhiro Nishinari,et al.  Simulation for pedestrian dynamics by real-coded cellular automata (RCA) , 2007 .

[2]  Dirk Helbing.  A Fluid-Dynamic Model for the Movement of Pedestrians , 1992, Complex Syst..

[3]  S. Dai,et al.  Centrifugal force model for pedestrian dynamics. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Hai-Jun Huang,et al.  A new pedestrian-following model for aircraft boarding and numerical tests , 2012 .

[5]  T. Nagatani,et al.  Jamming transition in pedestrian counter flow , 1999 .

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

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

[8]  Hubert Klüpfel,et al.  Evacuation Dynamics: Empirical Results, Modeling and Applications , 2009, Encyclopedia of Complexity and Systems Science.

[9]  Jian Li,et al.  The application of a two-dimensional cellular automata random model to the performance-based design of building exit , 2008 .

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

[11]  Takashi Nagatani,et al.  Evacuation of crawlers and walkers from corridor through an exit , 2006 .

[12]  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.

[13]  Yoshihiro Ishibashi,et al.  Jamming Transition in Cellular Automaton Models for Pedestrians on Passageway , 1999 .

[14]  Lou Caccetta,et al.  An aircraft boarding model accounting for passengers' individual properties , 2012 .

[15]  Fan Weicheng,et al.  Simulation of bi-direction pedestrian movement using a cellular automata model , 2003 .

[16]  Michael Schultz,et al.  Solving the Direction Field for Discrete Agent Motion , 2010, ACRI.

[17]  Middleton,et al.  Self-organization and a dynamical transition in traffic-flow models. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[18]  Vicsek,et al.  Freezing by heating in a driven mesoscopic system , 1999, Physical review letters.

[19]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[20]  Akihiro Nakayama,et al.  Instability of pedestrian flow and phase structure in a two-dimensional optimal velocity model. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  D. Helbing.  Traffic and related self-driven many-particle systems , 2000, cond-mat/0012229.

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

[23]  Dirk Hartmann,et al.  Adaptive pedestrian dynamics based on geodesics , 2010 .

[24]  E. Ben-Jacob.  From snowflake formation to growth of bacterial colonies II: Cooperative formation of complex colonial patterns , 1997 .

[25]  Hai-Jun Huang,et al.  Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exits. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  R. Hughes.  The flow of human crowds , 2003 .

[27]  Yoshihiro Ishibashi,et al.  Self-Organized Phase Transitions in Cellular Automaton Models for Pedestrians , 1999 .

[28]  Lizhong Yang,et al.  Exit dynamics of occupant evacuation in an emergency , 2006 .

[29]  L. F. Henderson,et al.  The Statistics of Crowd Fluids , 1971, Nature.

[30]  Mohcine Chraibi,et al.  Generalized centrifugal-force model for pedestrian dynamics. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[31]  Hai-Jun Huang,et al.  A MACRO MODEL FOR BICYCLE FLOW AND PEDESTRIAN FLOW WITH THE CONSIDERATION OF THE HONK EFFECTS , 2011 .

[32]  Daniel R. Parisi,et al.  Experimental evidence of the "Faster is Slower" effect in the evacuation of ants , 2012 .

[33]  David J. Low,et al.  Following the crowd , 2000 .

[34]  Peter Vortisch,et al.  Comparison of Various Methods for the Calculation of the Distance Potential Field , 2008, ArXiv.

[35]  Debashish Chowdhury,et al.  Stochastic Transport in Complex Systems: From Molecules to Vehicles , 2010 .

[36]  Weiguo Song,et al.  A cellular automata evacuation model considering friction and repulsion , 2005 .

[37]  José Rogan,et al.  Cellular automaton model for evacuation process with obstacles , 2007 .

[38]  Stefan Holl,et al.  Modeling the Dynamic Route Choice of Pedestrians to Assess the Criticality of Building Evacuation , 2011, Adv. Complex Syst..

[39]  Wang Bing-Hong,et al.  Evacuation behaviors at exit in CA model with force essentials: A comparison with social force model , 2006 .

[40]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.