Model and Simulation of Bi-Directional Pedestrian Flow Self-Organization Based on Cellular Automata

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Yongchao Song ◽  
Xueli Liu ◽  
Jie Yang ◽  
Xiaonian Xie
Keyword(s):  
Cellular Automata ◽  
Self Organization ◽  
Pedestrian Flow ◽  
Model And Simulation

A Simple Three-States Cellular Automaton for Modelling Excitable Media

1998 ◽  
Vol 12 (05) ◽  
pp. 601-607 ◽  
Author(s):  
M. Andrecut
Keyword(s):  
Wave Propagation ◽  
Partial Differential Equations ◽  
Cellular Automata ◽  
Differential Equations ◽  
Cellular Automaton ◽  
Cellular Automaton Model ◽  
Excitable Media ◽  
Self Organization ◽  
Partial Differential ◽  
Bz Reaction

Wave propagation in excitable media provides an important example of spatiotemporal self-organization. The Belousov–Zhabotinsky (BZ) reaction and the impulse propagation along nerve axons are two well-known examples of this phenomenon. Excitable media have been modelled by continuous partial differential equations and by discrete cellular automata. Here we describe a simple three-states cellular automaton model based on the properties of excitation and recovery that are essential to excitable media. Our model is able to reproduce the dynamics of patterns observed in excitable media.

Study on bi-direction pedestrian flow using cellular automata simulation

2010 ◽  
Vol 389 (3) ◽  
pp. 527-539 ◽  
Author(s):  
Hao Yue ◽  
Hongzhi Guan ◽  
Juan Zhang ◽  
Chunfu Shao
Keyword(s):  
Cellular Automata ◽  
Pedestrian Flow

scholarly journals Simulating the Gluing of Wood Particles by Lattice Gas Cellular Automata and Random Walk

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 988
Author(s):  
Carina Rößler ◽  
Felix Breitenecker ◽  
Martin Riegler
Keyword(s):  
Mathematical Model ◽  
Random Walk ◽  
Cellular Automata ◽  
Lattice Gas ◽  
Three Dimensional ◽  
Three Dimensional Model ◽  
Model And Simulation ◽  
Wood Particles ◽  
Lattice Gas Cellular Automata ◽  
Modelling Methods

In this work a mathematical model and simulation for the gluing of wood particles designated for particleboards is presented. The aim is to obtain a better understanding of the gluing process. Thus, the behaviour of wood particles during gluing is investigated and the resulting adhesive distribution across the surface of the wood particles is analysed. For developing a mathematical model, the modelling methods “lattice gas cellular automata” and “random walk” were used. The model was implemented in MATLAB and different scenarios were simulated for answering the main questions of the behaviour during gluing. The influences of different parameters on the adhesive distribution were investigated and quantitatively determined by several key figures. Based on these key figures, the effects of the mixing arm, realistic size distributions of wood particles and adhesive droplets, the transfer of adhesive, and the total mass of adhesive are discussed. Furthermore the results are compared with experimental measurements. The simulation results show that the model can feasibly be used for studying the gluing of wood particles. For a possible industrial application, additional research for developing a three-dimensional model is needed.

Experiment, model, and simulation of the pedestrian flow around a training school classroom during the after-class period

SIMULATION ◽  
2021 ◽  
pp. 003754972110254
Author(s):  
Chuan-Zhi Xie ◽  
Tie-Qiao Tang ◽  
Bo-Tao Zhang ◽  
Heng-Jun Xiang
Keyword(s):  
Operational Efficiency ◽  
Pedestrian Flow ◽  
Training School ◽  
Fine Grid ◽  
Model And Simulation ◽  
Proposed Model ◽  
Adults And Children ◽  
Training Schools ◽  
Class Period ◽  
Questionnaire Surveys

In China, training schools are ubiquitous, where heterogeneous pedestrian flow (which consists of adults and children) widely occurs during the after-class period. In this paper, we develop a fine grid cellular CA model to describe the pedestrian behaviors (e.g., pick-up behavior, searching behavior, matching behavior, waiting behavior, leading behavior, and following behavior) at a training school during the after-class period and explore the effects of the special behaviors on each pedestrian’s movement in and around a classroom. To describe the heterogeneous pedestrian flow accurately, (i) some questionnaire surveys are designed to extract some features of adult’s and child’s movement, and (ii) some video experiments are conducted to estimate/calibrate some parameters of interest in the proposed model. Finally, some strategies are designed to enhance the evacuation efficiency and the operational efficiency of training school. The numerical results indicate that the proposed model can reasonably match with reality, and the proposed strategies can enhance the evacuation efficiency and the operational efficiency of training school. The results can help the administrators to effectively manage the pedestrian evacuation at training school during the after-class period.

Consistent evolution in a pedestrian flow

2016 ◽  
Vol 27 (09) ◽  
pp. 1650104 ◽  
Author(s):  
Junbiao Guan ◽  
Kaihua Wang
Keyword(s):  
Initial Conditions ◽  
Self Organization ◽  
Pedestrian Flow ◽  
Herding Behavior ◽  
Human Behaviors ◽  
Pedestrian Evacuation ◽  
Snowdrift Game ◽  
Ca Model ◽  
Independent Behavior ◽  
Independent Thinking

In this paper, pedestrian evacuation considering different human behaviors is studied by using a cellular automaton (CA) model combined with the snowdrift game theory. The evacuees are divided into two types, i.e. cooperators and defectors, and two different human behaviors, herding behavior and independent behavior, are investigated. It is found from a large amount of numerical simulations that the ratios of the corresponding evacuee clusters are evolved to consistent states despite 11 typically different initial conditions, which may largely owe to self-organization effect. Moreover, an appropriate proportion of initial defectors who are of herding behavior, coupled with an appropriate proportion of initial defectors who are of rationally independent thinking, are two necessary factors for short evacuation time.

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