Evacuation dynamics with smoking diffusion in three dimension based on an extended Floor-Field model

This paper proposes an extended Floor-Field (FF) model to study the pedestrian evacuation dynamics under the influence of smoke diffusing in three-dimension (3D). In addition to static and dynamic fields, the extended model adopts the smoke and herding fields to reflect pedestrian’s smoke-avoiding behavior and herding behavior. The impact of smoke on pedestrians’ health is also considered. The smoke will reduce the pedestrians’ health point and finally impact their moving ability. Numerical simulations were carried out to study the evacuation dynamics. The influence of the smoke particles producing rate, the initial health point, the critical smoke concentration value, and the herding field on evacuation dynamics were analyzed in detail. Those results could bring some guidance to make the evacuation strategy in the smoke diffusing environment.

[1]  Rui Jiang,et al.  Evacuation dynamics considering pedestrians’ movement behavior change with fire and smoke spreading , 2017 .

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

[3]  Hideki Nakamura,et al.  Application of social force model to pedestrian behavior analysis at signalized crosswalk , 2014 .

[4]  Tie-Qiao Tang,et al.  An evacuation model accounting for elementary students’ individual properties , 2015 .

[5]  R. Colombo,et al.  A CLASS OF NONLOCAL MODELS FOR PEDESTRIAN TRAFFIC , 2011, 1104.2985.

[6]  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.

[7]  Lei Zhang,et al.  Modeling and simulating for congestion pedestrian evacuation with panic , 2015 .

[8]  Wei Wang,et al.  A study of pedestrian group behaviors in crowd evacuation based on an extended floor field cellular automaton model , 2017 .

[9]  Nan Mu,et al.  Simulation of Pedestrian Evacuation in a Room under Fire Emergency , 2014 .

[10]  Claudio O. Dorso,et al.  Evacuation under limited visibility , 2015 .

[11]  Meifang Li,et al.  The parameter calibration and optimization of social force model for the real-life 2013 Ya’an earthquake evacuation in China , 2015 .

[12]  Majid Sarvi,et al.  Social dynamics in emergency evacuations: Disentangling crowd’s attraction and repulsion effects , 2017 .

[13]  Hairong Dong,et al.  Necessity of guides in pedestrian emergency evacuation , 2016 .

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

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

[16]  Yong Song Zhan,et al.  A Smoke Simulation Technique Based on Particle System , 2011 .

[17]  Wei Lv,et al.  A multi-grid model for pedestrian evacuation in a room without visibility , 2015 .

[18]  Di Huang,et al.  Probabilistic model for safe evacuation under the effect of uncertain factors in fire , 2017 .

[19]  Xiwei Guo,et al.  Modeling of pedestrian evacuation under fire emergency based on an extended heterogeneous lattice gas model , 2013 .

[20]  Liang Chen,et al.  Modeling pedestrian movement at the hall of high-speed railway station during the check-in process , 2017 .

[21]  G. A. Frank,et al.  High pressures in room evacuation processes and a first approach to the dynamics around unconscious pedestrians , 2017 .

[22]  Hong Liu,et al.  A social force evacuation model driven by video data , 2018, Simul. Model. Pract. Theory.

[23]  Aya Hagishima,et al.  Study of bottleneck effect at an emergency evacuation exit using cellular automata model, mean field approximation analysis, and game theory , 2010 .

[24]  Jean-Daniel Zucker,et al.  Integration of Smoke Effect and Blind Evacuation Strategy (SEBES) within fire evacuation simulation , 2013, Simul. Model. Pract. Theory.

[25]  Sze Chun Wong,et al.  A macroscopic approach to the lane formation phenomenon in pedestrian counterflow , 2011 .

[26]  Yao Xiao,et al.  A pedestrian flow model considering the impact of local density: Voronoi diagram based heuristics approach , 2016 .

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

[28]  Baoming Han,et al.  Behavioral effect on pedestrian evacuation simulation using cellular automata , 2015 .

[29]  Bin Jia,et al.  Evacuation dynamics with fire spreading based on cellular automaton , 2011 .

[30]  Liang Chen,et al.  Modeling pedestrian flow accounting for collision avoidance during evacuation , 2018, Simul. Model. Pract. Theory.

[31]  Xiaodong Zhou,et al.  A floor field cellular automaton for crowd evacuation considering different walking abilities , 2015 .

[32]  Roger L. Hughes,et al.  A continuum theory for the flow of pedestrians , 2002 .

[33]  Stefania Bandini,et al.  Modelling negative interactions among pedestrians in high density situations , 2014 .

[34]  Dirk Helbing,et al.  Experiment, theory, and simulation of the evacuation of a room without visibility. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[35]  Luo-Luo Jiang,et al.  The influence of panic on the efficiency of escape , 2018 .

[36]  Lin Luo,et al.  Update schemes of multi-velocity floor field cellular automaton for pedestrian dynamics , 2018 .

[37]  Juan Wei,et al.  Study on queueing behavior in pedestrian evacuation by extended cellular automata model , 2018 .

[38]  Jiun-Jia Hsu,et al.  Long-term congestion anticipation and aversion in pedestrian simulation using floor field cellular automata , 2014 .

[39]  Tao Chen,et al.  Lattice gas simulation and experiment study of evacuation dynamics , 2008 .

[40]  Liu Tao,et al.  Agent-based simulation of fire emergency evacuation with fire and human interaction model , 2011 .

[41]  Weifeng Yuan,et al.  A model for simulation of crowd behaviour in the evacuation from a smoke-filled compartment , 2011 .

[42]  Ziyou Gao,et al.  Modeling detour behavior of pedestrian dynamics under different conditions , 2018 .

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

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

[45]  Hai-Jun Huang,et al.  Elementary Students' Evacuation Route Choice in a Classroom: A Questionnaire-Based Method , 2018 .

[46]  Hong Liu,et al.  Modified social force model based on information transmission toward crowd evacuation simulation , 2017 .

[47]  Meng Jun-xian Implementation of Occupant Evacuation Simulation System in Large Buildings , 2009 .

[48]  Sze Chun Wong,et al.  Perceived cost potential field cellular automata model with an aggregated force field for pedestrian dynamics , 2014 .

[49]  Zhang Hao,et al.  Modified two-layer social force model for emergency earthquake evacuation , 2018 .

[50]  Andreas Schadschneider,et al.  Study of Influence of Groups on Evacuation Dynamics Using a Cellular Automaton Model , 2014 .

[51]  Denise Burgarelli,et al.  Emergency evacuation models based on cellular automata with route changes and group fields , 2017 .