Empirical analysis of the lane formation process in bidirectional pedestrian flow.

This paper presents an experimental study on pedestrian bidirectional streams and the mechanisms leading to spontaneous lane formation by examining the flow formed by two groups of people walking toward each other in a mock corridor. Flow ratio is changed by changing each group size while maintaining comparable total flow and density. By tracking the trajectories of each pedestrian and analyzing the data obtained, five different phases were recognized as contributing to the transition from unidirectional to bidirectional flow including the spontaneous creation and dissolution of lanes. It has been shown that a statistical treatment is required to understand the fundamental characteristics of pedestrian dynamics and some two-dimensional quantities such as order parameter and rotation range were introduced to allow a more complete analysis. All the quantities observed showed a clear relationship with flow ratio and helped distinguishing between the different characteristic phases of the experiment. Results show that balanced bidirectional flow becomes the most stable configuration after lanes are formed, but the lane creation process requires pedestrians to laterally move to a largest extent compared to low flow-ratio configurations. This finding allows us to understand the reasons why balanced bidirectional flow is efficient at low densities, but quickly leads to deadlock formation at high densities.

[1]  Vladimir G. Ivancevic,et al.  Turbulence and shock-waves in crowd dynamics , 2011, 1105.3274.

[2]  Myung-Hoon Chung,et al.  Collective behaviors of two-component swarms. , 2009, Journal of theoretical biology.

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

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

[5]  Wael K.M. Alhajyaseen,et al.  Quality of pedestrian flow and crosswalk width at signalized intersections , 2010 .

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

[7]  William H. K. Lam,et al.  Pedestrian speed/flow relationships for walking facilities in Hong Kong , 2000 .

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

[9]  A. Seyfried,et al.  Basics of Modelling the Pedestrian Flow , 2005, physics/0506189.

[10]  A. Seyfried,et al.  The fundamental diagram of pedestrian movement revisited , 2005, physics/0506170.

[11]  Riad I. Hammoud,et al.  Pedestrian tracking by fusion of thermal-visible surveillance videos , 2010, Machine Vision and Applications.

[12]  Daichi Yanagisawa,et al.  Anticipation effect in pedestrian dynamics: Modeling and experiments , 2012 .

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

[14]  Christian Bauckhage,et al.  Loveparade 2010: Automatic video analysis of a crowd disaster , 2012, Comput. Vis. Image Underst..

[15]  A. Huth,et al.  The simulation of the movement of fish schools , 1992 .

[16]  M. Schreckenberg,et al.  Experimental study of pedestrian counterflow in a corridor , 2006, cond-mat/0609691.

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

[18]  Claudio Feliciani,et al.  Phenomenological description of deadlock formation in pedestrian bidirectional flow based on empirical observation , 2015 .

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

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

[21]  I Zuriguel,et al.  Flow and clogging of a sheep herd passing through a bottleneck. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Daichi Yanagisawa,et al.  Study on Efficiency of Evacuation with an Obstacle on Hexagonal Cell Space , 2010 .

[23]  Dirk Helbing,et al.  Crowd disasters as systemic failures: analysis of the Love Parade disaster , 2012, EPJ Data Science.

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

[25]  Ioannis Karamouzas,et al.  Universal power law governing pedestrian interactions. , 2014, Physical review letters.

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

[27]  Armin Seyfried,et al.  Collecting pedestrian trajectories , 2013, Neurocomputing.

[28]  Osama Masoud,et al.  A novel method for tracking and counting pedestrians in real-time using a single camera , 2001, IEEE Trans. Veh. Technol..

[29]  Wael K.M. Alhajyaseen,et al.  Effects of Bi-directional Pedestrian Flow Characteristics upon the Capacity of Signalized Crosswalks , 2011 .

[30]  Jodie Y S Lee,et al.  A study of the bi-directional pedestrian flow characteristics at Hong Kong signalized crosswalk facilities , 2002 .

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

[32]  Anthony Chen,et al.  Modeling Emergency Evacuation of Individuals with Disabilities in a Densely Populated Airport , 2011 .

[33]  Alexander John,et al.  Collective effects in traffic on bi-directional ant trails. , 2004, Journal of theoretical biology.

[34]  Dirk Helbing,et al.  Keep-Left Behavior Induced by Asymmetrically Profiled Walls , 2016 .

[35]  L. Henderson,et al.  Sexual Differences in Human Crowd Motion , 1972, Nature.

[36]  A. Seyfried,et al.  Methods for measuring pedestrian density, flow, speed and direction with minimal scatter , 2009, 0911.2165.

[37]  M. Rex,et al.  Lane formation in oppositely charged colloids driven by an electric field: chaining and two-dimensional crystallization. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.