Pedestrian flow dynamics in a lattice gas model coupled with an evolutionary game.

This paper studies unidirectional pedestrian flow by using a lattice gas model with parallel update rules. Game theory is introduced to deal with conflicts that two or three pedestrians want to move into the same site. Pedestrians are either cooperators or defectors. The cooperators are gentle and the defectors are aggressive. Moreover, pedestrians could change their strategy. The fundamental diagram and the cooperator fraction at different system width W have been investigated in detail. It is found that a two-lane system exhibits a first-order phase transition while a multilane system does not. A microscopic mechanism behind the transition has been provided. Mean-field analysis is carried out to calculate the critical density of the transition as well as the probability of games at large value of W. The spatial distribution of pedestrians is investigated, which is found to be dependent (independent) on the initial cooperator fraction when W is small (large). Finally, the influence of the evolutionary game rule has been discussed.

[1]  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.

[2]  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.

[3]  Serge P. Hoogendoorn,et al.  Pedestrian Behavior at Bottlenecks , 2005, Transp. Sci..

[4]  Y. F. Yu,et al.  Cellular automaton simulation of pedestrian counter flow considering the surrounding environment. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Josef Hofbauer,et al.  Evolutionary Games and Population Dynamics , 1998 .

[6]  D. Helbing,et al.  The outbreak of cooperation among success-driven individuals under noisy conditions , 2009, Proceedings of the National Academy of Sciences.

[7]  Daichi Yanagisawa,et al.  Mean-field theory for pedestrian outflow through an exit. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  M. Nowak Five Rules for the Evolution of Cooperation , 2006, Science.

[9]  Dirk Helbing,et al.  Dynamics of crowd disasters: an empirical study. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Matjaž Perc,et al.  Premature seizure of traffic flow due to the introduction of evolutionary games , 2007 .

[11]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[12]  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.

[13]  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.

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

[15]  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 .

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

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

[18]  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.

[19]  Henry Been-Lirn Duh,et al.  A Simulation of Bonding Effects and Their Impacts on Pedestrian Dynamics , 2010, IEEE Transactions on Intelligent Transportation Systems.

[20]  Daniel R. Parisi,et al.  A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions , 2009 .

[21]  T. Nagatani,et al.  Jamming transition of pedestrian traffic at a crossing with open boundaries , 2000 .

[22]  A. C. Barato,et al.  Boundary-induced nonequilibrium phase transition into an absorbing state. , 2008, Physical review letters.

[23]  B. Wang,et al.  Phase transition in random walks coupled with evolutionary game , 2010 .

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

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

[26]  K. Nishinari,et al.  Introduction of frictional and turning function for pedestrian outflow with an obstacle. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[27]  Xiaoping Zheng,et al.  Conflict game in evacuation process: A study combining Cellular Automata model , 2011 .

[28]  Yuhong Wu,et al.  Responses of ground-dwelling spiders to four hedgerow species on sloped agricultural fields in Southwest China , 2009 .

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

[30]  Rui Jiang,et al.  Pedestrian flow in a lattice gas model with parallel update. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[31]  M. Nowak,et al.  A strategy of win-stay, lose-shift that outperforms tit-for-tat in the Prisoner's Dilemma game , 1993, Nature.

[32]  Michael Schreckenberg,et al.  Characterizing correlations of flow oscillations at bottlenecks , 2006, ArXiv.

[33]  D. E. Matthews Evolution and the Theory of Games , 1977 .