Pedestrian dynamics in a heterogeneous bidirectional flow: Overtaking behaviour and lane formation

Abstract We propose an optimization-based counterflow model to simultaneously investigate the pedestrian lane formation and overtaking behaviour in a heterogeneous bidirectional pedestrian flow. A comparison of pedestrian flow patterns in bidirectional flows with overtaking behaviour between the proposed model and a counterflow-based active decision model is performed with real collected data. Furthermore, the fundamental diagram of heterogeneous pedestrian counterflows with different corridor widths is compared with the experimental data. The effects of personal preferences regarding evading behaviour, going straight ahead and the right-hand traffic norm on lane formation are also studied for different corridor geometries with various pedestrian densities. The numerical results show that both overtaking behaviour in sparse bidirectional crowds and personal preference for the right-hand traffic norm in a wide corridor may reduce the specific flow of a pedestrian counterflow. Simultaneously, a strong personal preference for the right-hand traffic norm can determine lane formation in a counterflow scenario regardless of differences in corridor widths, pedestrian densities or other personal preferences. Additionally, lane formation may enhance not only the traffic efficiency of the whole counterflow but also the mobility of fast pedestrians in a heterogeneous bidirectional pedestrian flow.

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

[2]  Eric Wai Ming Lee,et al.  The effect of overtaking behavior on unidirectional pedestrian flow , 2012 .

[3]  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.

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

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

[6]  Dawei Zhang,et al.  An optimization-based overtaking model for unidirectional pedestrian flow , 2018, Physics Letters A.

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

[8]  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.

[9]  Andreas Schadschneider,et al.  Fundamental Diagram and Validation of Crowd Models , 2008, ACRI.

[10]  Andreas Schadschneider,et al.  Evacuation Dynamics: Empirical Results, Modeling and Applications , 2008, Encyclopedia of Complexity and Systems Science.

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

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

[13]  Jonathan D. Nelson,et al.  Simple Heuristics and the Modelling of Crowd Behaviours , 2014 .

[14]  Claudio Feliciani,et al.  Empirical analysis of the lane formation process in bidirectional pedestrian flow. , 2016, Physical review. E.

[15]  W. Song,et al.  Effect of traffic rule breaking behavior on pedestrian counterflow in a channel with a partition line. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Weng-Fai Wong,et al.  Extended social force model with a dynamic navigation field for bidirectional pedestrian flow , 2017, 1705.03569.

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

[18]  Takayuki Kanda,et al.  A Microscopic “Social Norm” Model to Obtain Realistic Macroscopic Velocity and Density Pedestrian Distributions , 2012, PloS one.

[19]  Gunnar Flötteröd,et al.  Bidirectional pedestrian fundamental diagram , 2015 .

[20]  Michael Batty,et al.  Predicting where we walk , 1997, Nature.

[21]  Fang Guo,et al.  Effect of psychological tension on pedestrian counter flow via an extended cost potential field cellular automaton model , 2017 .

[22]  Dai Shi-qiang,et al.  Subconscious Effect on Pedestrian Counter Flow , 2008 .

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

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

[25]  Lizhong Yang,et al.  Simulation of pedestrian counter-flow with right-moving preference , 2008 .

[26]  Claudio Feliciani,et al.  An improved Cellular Automata model to simulate the behavior of high density crowd and validation by experimental data , 2016 .

[27]  Meead Saberi,et al.  Spatial fluctuations of pedestrian velocities in bidirectional streams: Exploring the effects of self-organization , 2015 .

[28]  M. Schreckenberg,et al.  Experimental study of pedestrian flow through a bottleneck , 2006, physics/0610077.

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

[30]  Harri Ehtamo,et al.  Counterflow model for agent-based simulation of crowd dynamics , 2012 .

[31]  Stefania Bandini,et al.  Mobility analysis of the aged pedestrians by experiment and simulation , 2014, Pattern Recognit. Lett..

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

[33]  Dirk Helbing,et al.  Experimental study of the behavioural mechanisms underlying self-organization in human crowds , 2009, Proceedings of the Royal Society B: Biological Sciences.

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

[35]  A. Schadschneider,et al.  Enhanced Empirical Data for the Fundamental Diagram and the Flow Through Bottlenecks , 2008, 0810.1945.

[36]  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.

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

[38]  Weiguo Song,et al.  Simulation of emotional contagion using modified SIR model: A cellular automaton approach , 2014 .

[39]  Jun Zhang,et al.  Comparison of intersecting pedestrian flows based on experiments , 2013, 1312.2475.