Uni- and bidirectional pedestrian flows through zigzag corridor in a tourism area: a field study

Nowadays, the famous tourist attractions are becoming more and more popular for people from all over the world. Thus, to ensure the safety of tourists is a tough task in such crowded area. The study of pedestrian’s characteristics in crowd movement is essential for safety management. In this article, both uni- and bidirectional observational experiments were conducted to quantitatively analyze the movement properties of pedestrians in a zigzag corridor which is located in a tourism area named Yuyuan business district in Shanghai. Several phenomena have been found during the tourists’ movement process: congestion at boundary, competing and bypassing behavior, and flow gap. As indicated by the transit time of pedestrians in both uni- and bidirectional scenarios, pedestrians in bidirectional pattern (>10 s) spend more time on going through the corridor than that in unidirectional one (<10 s). Besides, the fundamental diagrams in both uni- and bidirectional scenarios are significantly different from data in a controlled experiment, and obvious differences are observed within the density regime from 1.5 to 2.5 ped/m2 between the uni- and bidirectional scenarios. In addition, spatial distributions of density and velocity demonstrate that pedestrians would like to cluster at the boundary of straight corridors in both uni- and bidirectional scenarios. The results could enrich the database of fundamental diagrams, and then be used for model calibration by taking the actual situation into consideration in similar scenarios.

[1]  Mohcine Chraibi,et al.  Experimental study of pedestrian flow through right-angled corridor: uni- and bidirectional scenarios , 2019, Journal of Statistical Mechanics: Theory and Experiment.

[2]  Wenguo Weng,et al.  Empirical study of crowd behavior during a real mass event , 2012 .

[3]  Jia Li,et al.  Propagation characteristics of the pedestrian shockwave in dense crowd: Experiment and simulation , 2019, International Journal of Disaster Risk Reduction.

[4]  Jing Bai,et al.  The dynamics of pedestrians' evacuation during emergency situations , 2016, Adapt. Behav..

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

[6]  Farid Nouioua,et al.  An approach for emotions and behavior modeling in a crowd in the presence of rare events , 2016, Adapt. Behav..

[7]  Serge P. Hoogendoorn,et al.  Pedestrian Free Speed Behavior in Crossing Flows , 2007 .

[8]  Jian Ma,et al.  An experimental study on four-directional intersecting pedestrian flows , 2015 .

[9]  Robert T. Collins,et al.  Vision-Based Analysis of Small Groups in Pedestrian Crowds , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Weiguo Song,et al.  The effect of a directional split flow ratio on bidirectional pedestrian streams at signalized crosswalks , 2018, Journal of Statistical Mechanics: Theory and Experiment.

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

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

[13]  Dirk Helbing,et al.  From Crowd Dynamics to Crowd Safety: a Video-Based Analysis , 2008, Adv. Complex Syst..

[14]  Jian Ma,et al.  New insights into turbulent pedestrian movement pattern in crowd-quakes , 2013 .

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

[16]  Ashish Verma,et al.  Understanding crowd dynamics at ghat regions during world's largest mass religious gathering, Kumbh Mela , 2018, International Journal of Disaster Risk Reduction.

[17]  Rui Ye,et al.  Experimental study on walking preference during high-rise stair evacuation under different ground illuminations , 2017 .

[18]  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.

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

[20]  Weiguo Song,et al.  Experimental study of pedestrian behaviors in a corridor based on digital image processing , 2012 .

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

[22]  Weiguo Song,et al.  Characteristics of pedestrian's evacuation in a room under invisible conditions , 2019 .

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

[24]  Lei Chen,et al.  Experimental study on characteristics of pedestrian evacuation on stairs in a high-rise building , 2016 .

[25]  Mohamed H. Dridi Simulation of High Density Pedestrian Flow: Microscopic Model , 2015, 1501.06496.

[26]  Harri Ehtamo,et al.  Pedestrian behavior and exit selection in evacuation of a corridor – An experimental study , 2012 .

[27]  David Johannes Wüpper,et al.  An empirical analysis , 2015 .

[28]  Hongyong Yuan,et al.  Empirical study of a unidirectional dense crowd during a real mass event , 2013 .

[29]  Bastien Chopard,et al.  A Multiparticle Lattice Gas Automata Model for a Crowd , 2002, ACRI.

[30]  Giuseppe Vizzari,et al.  Effects of Initial Distribution Ratio and Illumination on Merging Behaviors During High-Rise Stair Descent Process , 2018 .

[31]  H. Laborit,et al.  [Experimental study]. , 1958, Bulletin mensuel - Societe de medecine militaire francaise.

[32]  Armin Seyfried,et al.  Fundamental diagrams for multidirectional pedestrian flows , 2017 .

[33]  Wenguo Weng,et al.  New insights into the crowd characteristics in Mina , 2014 .

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

[35]  Majid Sarvi,et al.  Pedestrian crowd dynamics in merging sections: Revisiting the “faster-is-slower” phenomenon , 2018 .

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

[37]  Jian Ma,et al.  Experimental study on evacuation process in a stairwell of a high-rise building , 2012 .

[38]  Nirajan Shiwakoti,et al.  Video-based analysis of school students' emergency evacuation behavior in earthquakes , 2016 .

[39]  Ashish Verma,et al.  A review of studies on understanding crowd dynamics in the context of crowd safety in mass religious gatherings , 2017 .