A collective motion model based on two-layer relationship mechanism for bi-direction pedestrian flow simulation

Abstract In crowd dynamic, relations are existed among some pedestrians, which cause frequent interactions during evacuation, creating collective motion phenomena, such as the most common pattern of team-groups. Besides, collective behavior can make a beneficial effect on the evacuation process. Therefore, this paper proposes a collective motion model to simulate bi-direction pedestrian flow. First, a method of group vision sharing is proposed to help pedestrians learn the crowd around. Based on two-layer relationship mechanism proposed, aggregate force and collective collision avoidance force are added into the original social force formula. The aggregate force is the resultant of two forces, one is the attraction among the leader and team members, and the other one is that among members of groups due to the social relations. Simulation results show that the modified model can reproduce the team-groups collective pattern in real world bi-direction pedestrian flow, and can reduce the collision risk with regarding the group as collision avoidance unit. Furthermore, the evacuation efficiency is improved.

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

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

[3]  Xi Jiang,et al.  A multiagent-based model for pedestrian simulation in subway stations , 2017, Simul. Model. Pract. Theory.

[4]  T. Vicsek,et al.  Hierarchical group dynamics in pigeon flocks , 2010, Nature.

[5]  Yanqun Jiang,et al.  Macroscopic pedestrian flow model with degrading spatial information , 2015, J. Comput. Sci..

[6]  Yan-Qun Jiang,et al.  A higher-order macroscopic model for bi-direction pedestrian flow , 2015 .

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

[8]  H. Chaté,et al.  Modeling collective motion: variations on the Vicsek model , 2008 .

[9]  André Borrmann,et al.  Modeling pedestrians' interest in locations: A concept to improve simulations of pedestrian destination choice , 2016, Simul. Model. Pract. Theory.

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

[11]  Young-Jun Son,et al.  Two-level modeling framework for pedestrian route choice and walking behaviors , 2012, Simul. Model. Pract. Theory.

[12]  Chee Peng Lim,et al.  A genetic fuzzy system to model pedestrian walking path in a built environment , 2014, Simul. Model. Pract. Theory.

[13]  Taewan Kim,et al.  Modeling lane formation in pedestrian counter flow and its effect on capacity , 2016 .

[14]  Dirk Helbing,et al.  How simple rules determine pedestrian behavior and crowd disasters , 2011, Proceedings of the National Academy of Sciences.

[15]  Hui Zhao,et al.  Effect of prediction on the self-organization of pedestrian counter flow , 2012 .

[16]  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.

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

[18]  A. Schadschneider,et al.  Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram , 2012 .

[19]  Hai-Jun Huang,et al.  A mobile lattice gas model for simulating pedestrian evacuation , 2008 .

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

[21]  Dirk Helbing,et al.  Self-Organizing Pedestrian Movement , 2001 .

[22]  Xiaodong Liu,et al.  Defining static floor field of evacuation model in large exit scenario , 2014, Simul. Model. Pract. Theory.

[23]  Musong Gu,et al.  Experiment of bi-direction pedestrian flow with three-dimensional cellular automata , 2015 .

[24]  Wenjian Yu,et al.  Modeling crowd turbulence by many-particle simulations. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

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

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

[28]  Norman I. Badler,et al.  Modeling Crowd and Trained Leader Behavior during Building Evacuation , 2006, IEEE Computer Graphics and Applications.

[29]  T. Nagatani,et al.  Clogging transition of pedestrian flow in T-shaped channel , 2002 .

[30]  Andreas Schadschneider,et al.  Empirical study on social groups in pedestrian evacuation dynamics , 2017, 1703.08340.

[31]  Rui Jiang,et al.  A behaviour based cellular automaton model for pedestrian counter flow , 2016 .

[32]  Bing-Hong Wang,et al.  The escape of pedestrians with view radius , 2013 .

[33]  Tie-Qiao Tang,et al.  A simulation model for pedestrian flow through walkways with corners , 2012, Simul. Model. Pract. Theory.

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

[35]  Juntao Yang,et al.  An Extended Small-grid Lattice Gas Model for Pedestrian Counter Flow☆ , 2013 .

[36]  Lou Caccetta,et al.  An aircraft boarding model accounting for passengers' individual properties , 2012 .

[37]  L. F. Henderson,et al.  The Statistics of Crowd Fluids , 1971, Nature.

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

[39]  Xiaodong Liu,et al.  Multi-grid simulation of counter flow pedestrian dynamics with emotion propagation , 2016, Simul. Model. Pract. Theory.

[40]  Chen Yu,et al.  Exploring the Effects of Different Walking Strategies on Bi-Directional Pedestrian Flow , 2013 .

[41]  Jun Zhang,et al.  Transitions in pedestrian fundamental diagrams of straight corridors and T-junctions , 2011, 1102.4766.

[42]  Hong Liu,et al.  Crowd evacuation simulation approach based on navigation knowledge and two-layer control mechanism , 2018, Inf. Sci..

[43]  Hong Liu,et al.  Extended route choice model based on available evacuation route set and its application in crowd evacuation simulation , 2017, Simul. Model. Pract. Theory.

[44]  Serge P. Hoogendoorn,et al.  Self-Organization in Pedestrian Flow , 2005 .

[45]  Andreas Schadschneider,et al.  Quantitative analysis of pedestrian counterflow in a cellular automaton model. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[46]  Ziyang Wang,et al.  Team-moving effect in bi-direction pedestrian flow , 2012 .

[47]  A. Czirók,et al.  Collective Motion , 1999, physics/9902023.

[48]  Cécile Appert-Rolland,et al.  Traffic Instabilities in Self-Organized Pedestrian Crowds , 2012, PLoS Comput. Biol..

[49]  Pau Fonseca i Casas,et al.  Passenger flow simulation in a hub airport: An application to the Barcelona International Airport , 2014, Simul. Model. Pract. Theory.

[50]  Tobias Kretz,et al.  On Oscillations in the Social Force Model , 2015, ArXiv.

[51]  Xiaoping Zheng,et al.  Modeling crowd evacuation of a building based on seven methodological approaches , 2009 .

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

[53]  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.

[54]  Hong Liu,et al.  A grouping method based on grid density and relationship for crowd evacuation simulation , 2017 .

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

[56]  Taras I. Lakoba,et al.  Modifications of the Helbing-Molnár-Farkas-Vicsek Social Force Model for Pedestrian Evolution , 2005, Simul..

[57]  Chimay J. Anumba,et al.  Computer simulations vs. building guidance to enhance evacuation performance of buildings during emergency events , 2011, Simul. Model. Pract. Theory.

[58]  Xiwei Guo,et al.  A heterogeneous lattice gas model for simulating pedestrian evacuation , 2012 .

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

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

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

[62]  Yi Li,et al.  The Trace Model: A model for simulation of the tracing process during evacuations in complex route environments , 2016, Simul. Model. Pract. Theory.