Fast Evacuation Method: Using an effective dynamic floor field based on efficient pedestrian assignment

Abstract The problem of pedestrian evacuation can be addressed through cellular automata incorporating a floor field that indicates promising movements to pedestrians. The two main types of floor field are the static, which represents the shortest path from each cell to an exit (and is usually combined with dynamic measures such as the density or distribution of pedestrians), and the dynamic, which represents the quickest path from each cell to an exit. The second type has been widely used recently, since it gives rise to more efficient and realistic simulations of pedestrian dynamics. The goal of these two types of floor field is to minimize the travel time for each pedestrian; however, this paper tackles the evacuation problem from a different perspective: The time taken by the whole evacuation process is optimized. For that purpose, a floor field is constructed by assigning pedestrians to exits such that the estimated time for complete evacuation is minimized. An experimental evaluation is conducted to compare the new fast evacuation method with competitive methods using floor fields based on quickest paths: Flood Fill and the Fast Marching Method. The results show that the new method is effective in terms of the number of time steps for complete evacuation and efficient regarding the total simulation runtime.

[1]  Haiying Li,et al.  Social force models for pedestrian traffic – state of the art , 2018 .

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

[3]  D. Helbing,et al.  Lattice gas simulation of experimentally studied evacuation dynamics. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Nirajan Shiwakoti,et al.  A review on the performance of an obstacle near an exit on pedestrian crowd evacuation , 2019, Safety Science.

[5]  J. Zittartz,et al.  Cellular Automaton Approach to Pedestrian Dynamics - Applications , 2001, cond-mat/0112119.

[6]  Charitha Dias,et al.  Towards Microscopic Calibration of Pedestrian Simulation Models Using Open Trajectory Datasets: The Case Study of the Edinburgh Informatics Forum , 2017, Traffic and Granular Flow '17.

[7]  T. Nagatani,et al.  Scaling of pedestrian channel flow with a bottleneck , 2001 .

[8]  Nirajan Shiwakoti,et al.  A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement , 2018, Journal of Advanced Transportation.

[9]  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.

[10]  T. Nagatani,et al.  Scaling behavior of crowd flow outside a hall , 2001 .

[11]  Weifeng Yuan,et al.  An evacuation model using cellular automata , 2007 .

[12]  Lubos Buzna,et al.  Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions , 2005, Transp. Sci..

[13]  Tommaso Toffoli,et al.  Cellular automata machines - a new environment for modeling , 1987, MIT Press series in scientific computation.

[14]  Jie Li,et al.  A Landscape of Crowd-management Support: An Integrative Approach , 2016 .

[15]  M. Fukui,et al.  Traffic Flow in 1D Cellular Automaton Model Including Cars Moving with High Speed , 1996 .

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

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

[18]  Tobias Kretz,et al.  The use of dynamic distance potential fields for pedestrian flow around corners , 2009, ArXiv.

[19]  Serge P. Hoogendoorn,et al.  Continuum modelling of pedestrian flows - Part 2: Sensitivity analysis featuring crowd movement phenomena , 2016 .

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

[21]  Tobias Kretz,et al.  Pedestrian traffic: on the quickest path , 2009, ArXiv.

[22]  Ekaterina Kirik,et al.  The shortest time and/or the shortest path strategies in a CA FF pedestrian dynamics model , 2009, 0906.4265.

[23]  Robert A. Kosinski,et al.  Models of Pedestrian Evacuation based on Cellular Automata , 2012 .

[24]  James A. Sethian,et al.  Level Set Methods and Fast Marching Methods , 1999 .

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

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

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

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

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

[30]  Fernando Fernández,et al.  Modeling, Evaluation, and Scale on Artificial Pedestrians , 2017, ACM Comput. Surv..

[31]  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.

[32]  Marcelo Luis Errecalde,et al.  Evacuation simulations using cellular automata , 2007 .

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

[34]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[35]  Lim Eng Aik,et al.  Simulating Evacuations with Obstacles Using a Modified Dynamic Cellular Automata Model , 2012, J. Appl. Math..

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

[37]  Song Xiang,et al.  Investigating pedestrian navigation in indoor open space environments using big data , 2018, Applied Mathematical Modelling.

[38]  Charitha Dias,et al.  Calibrating cellular automaton models for pedestrians walking through corners , 2018 .

[39]  Serge P. Hoogendoorn,et al.  State-of-the-art crowd motion simulation models , 2013 .

[40]  R. Alizadeh,et al.  A dynamic cellular automaton model for evacuation process with obstacles , 2011 .

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

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