Team-moving effect in bi-direction pedestrian flow

We propose a cellular automation model to simulate team-moving behavior in bi-directional pedestrian flow. The moving rules for double-pedestrian teaming include the constraint that pedestrians remain on adjacent cells. Phase transition, critical density — team number, velocity–density, and flow–density relationships are key component parts of the analysis. Simulations show that team-moving produces significant corridor capacity effects, and effects highly depend on the type of teaming behavior. In daily life, pedestrians prefer traverse teaming; under this bias, as teaming pedestrians increase in number, critical density reduces; that means traverse teaming will weaken the capacity of the corridor. The effect of traverse team-moving is nonlinear, and capacity will continually reduce as the team numbers increase; however, reduction rate will decay. We call this phenomenon, “the marginal utility of team-moving.”

[1]  Reza Malekzadeh,et al.  Verbal Autopsy: Reliability and Validity Estimates for Causes of Death in the Golestan Cohort Study in Iran , 2010, PloS one.

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

[3]  Takashi Nagatani,et al.  Jamming transition in counter flow of slender particles on square lattice , 2006 .

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

[5]  W. Weng,et al.  Cellular automaton simulation of pedestrian counter flow with different walk velocities. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

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

[8]  Takashi Nagatani,et al.  Sidle effect on pedestrian counter flow , 2007 .

[9]  D. Helbing,et al.  The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics , 2010, PloS one.

[10]  Hai-Jun Huang,et al.  A modified floor field cellular automata model for pedestrian evacuation simulation , 2008 .

[11]  Hui Zhao,et al.  Reserve capacity and exit choosing in pedestrian evacuation dynamics , 2010 .

[12]  T. Nagatani,et al.  Experiment and simulation of pedestrian counter flow , 2004 .

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

[14]  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.

[15]  Jian Li,et al.  Simulation of the kin behavior in building occupant evacuation based on Cellular Automaton , 2005 .

[16]  Hao Yue,et al.  Simulation of pedestrian flow on square lattice based on cellular automata model , 2007 .

[17]  Xingli Li,et al.  Analysis of pedestrian dynamics in counter flow via an extended lattice gas model. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Yuan Cheng,et al.  Thermodynamic analysis of protein sequence-structure relationships in monomer and dimer forms , 2005 .

[19]  Li Jian,et al.  Simulation of bi-direction pedestrian movement in corridor , 2005 .

[20]  Takashi Nagatani,et al.  Pattern formation and jamming transition in pedestrian counter flow , 2002 .

[21]  Weiguo Song,et al.  Experiment and multi-grid modeling of evacuation from a classroom , 2008 .

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

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

[24]  W. Weng,et al.  A behavior-based model for pedestrian counter flow , 2007 .

[25]  T. Nagatani,et al.  Jamming transition in two-dimensional pedestrian traffic , 2000 .

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

[27]  Bing-Hong Wang,et al.  Simulation of evacuation processes using a multi-grid model for pedestrian dynamics , 2006 .

[28]  Ulrich Weidmann,et al.  Transporttechnik der Fussgänger , 1992 .

[29]  Takashi Nagatani,et al.  Effect of partition line on jamming transition in pedestrian counter flow , 2002 .

[30]  Victor J. Blue,et al.  Cellular automata microsimulation for modeling bi-directional pedestrian walkways , 2001 .

[31]  Juan Zhang,et al.  Study on bi-direction pedestrian flow using cellular automata simulation , 2010 .