Pedestrian Crowd Dynamics Observed at Merging Sections: Impact of Designs on Movement Efficiency

The need for reliable crowd simulation tools has necessitated an accurate understanding of human behavior and the rules that govern their movements under normal and emergency escapes. This paper investigates the dynamics of merging streams of pedestrians. In the merging sections, the interaction between pedestrians and geometric features of merging sections can significantly impede the collective motion and can increase the possibility of flow breakdown, particularly under emergency conditions. Therefore, to create safe and efficient designs, it is important to study human movement characteristics associated with these types of conflicting geometries. In this study, empirical data collected from large numbers of high-density experiments with people at different desired speed levels were used to explore the effect of different merging configurations (i.e., design and angle) on dynamics of merging crowds. For the first time, this study examined the impact of elevated speed regimes (as a behavioral proxy of emergency escapes) on the movement efficiency of crowds in merging sections with different geometric designs. In particular, this study investigated the impact of these conflicting geometric settings on the average waiting time in the system as a measure of movement efficiency. Results suggest that the experienced delay is dramatically greater in asymmetrical setups compared with the delay in symmetrical setups and that the difference is even more pronounced at elevated levels of pedestrians’ desired speed. These findings give significant insights into the implications of inefficient designs of merging sections for pedestrians’ safety, notably when quick movement of crowds is necessary (e.g., in emergencies).

[1]  Tobias Kretz,et al.  Crowd Research at School: Crossing Flows , 2014, ArXiv.

[2]  Nirajan Shiwakoti,et al.  Using non-human biological entities to understand pedestrian crowd behaviour under emergency conditions , 2014 .

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

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

[5]  Charitha Dias,et al.  Examining the Impact of Different Turning Angles on the Collective Egress of Crowds , 2014 .

[6]  Bernhard Steffen,et al.  T-junction: Experiments, trajectory collection, and analysis , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[7]  Hai-Jun Huang,et al.  A microscopic pedestrian-simulation model and its application to intersecting flows , 2010 .

[8]  Victoria L Kendrick Introduction to crowd science , 2015, Ergonomics.

[9]  Majid Sarvi,et al.  Managing Congestion and Redirecting Passengers to Less Crowded Exits in Transport Stations through Monetary Incentives , 2017 .

[10]  Majid Sarvi,et al.  How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies , 2016, PloS one.

[11]  Majid Sarvi,et al.  Identifying Latent Classes of Pedestrian Crowd Evacuees , 2016 .

[12]  Jun Zhang,et al.  Empirical study of turning and merging of pedestrian streams in T-junction , 2011, 1112.5299.

[13]  Charitha Dias,et al.  Turning Angle Effect on Emergency Egress: Experimental Evidence and Pedestrian Crowd Simulation , 2012 .

[14]  Majid Sarvi,et al.  Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model , 2015 .

[15]  Fran H. Norris,et al.  Predicting Evacuation in Two Major Disasters: Risk Perception, Social Influence, and Access to Resources , 1999 .

[16]  Charitha Dias,et al.  Investigating Collective Escape Behaviours in Complex Situations , 2013 .

[17]  Carlos F. Daganzo,et al.  Fundamentals of Transportation and Traffic Operations , 1997 .

[18]  Omid Ejtemai,et al.  Understanding pedestrian crowd merging behavior , 2014 .

[19]  Meead Saberi,et al.  Exploring Areawide Dynamics of Pedestrian Crowds , 2014 .

[20]  Majid Sarvi,et al.  Pedestrian crowd tactical-level decision making during emergency evacuations , 2016 .

[21]  Nirajan Shiwakoti,et al.  Enhancing the panic escape of crowd through architectural design , 2013 .

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

[23]  Karen Boyce,et al.  Experimental studies to investigate merging behaviour in a staircase , 2012 .

[24]  Hitoshi Watanabe,et al.  Characteristics of merging occupants in a staircase , 2005 .

[25]  Majid Sarvi,et al.  Human exit choice in crowded built environments: Investigating underlying behavioural differences between normal egress and emergency evacuations , 2016 .

[26]  Omid Ejtemai,et al.  Random Utility Models of Pedestrian Crowd Exit Selection based on SP-off-RP Experiments , 2014 .

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

[28]  Nirajan Shiwakoti,et al.  Understanding pedestrian crowd panic: a review on model organisms approach , 2013 .

[29]  Majid Sarvi,et al.  Stated and revealed exit choices of pedestrian crowd evacuees , 2017 .

[30]  Majid Sarvi,et al.  Following the crowd or avoiding it? Empirical investigation of imitative behaviour in emergency escape of human crowds , 2017, Animal Behaviour.

[31]  Jerome M. Chertkoff,et al.  Don't Panic: The Psychology of Emergency Egress and Ingress , 1999 .

[32]  Armin Seyfried,et al.  Performance of stairs: fundamental diagram and topographical measurements , 2013 .

[33]  Chung-I Chou,et al.  Simulation of pedestrian flow through a "T" intersection: A multi-floor field cellular automata approach , 2011, Comput. Phys. Commun..

[34]  G. Courtine,et al.  Human walking along a curved path. II. Gait features and EMG patterns , 2003, The European journal of neuroscience.

[35]  Ris S. C. Lee,et al.  Exploring Trampling and Crushing in a Crowd , 2005 .

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

[37]  Majid Sarvi,et al.  Insights Toward Characteristics of Merging Streams of Pedestrian Crowds Based on Experiments with Panicked Ants , 2016 .

[38]  Charitha Dias,et al.  Experimental study on pedestrian walking characteristics through angled corridors , 2013 .

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

[40]  Dong Zhang,et al.  Study on evacuation behaviors at a T-shaped intersection by a force-driving cellular automata model , 2012 .

[41]  Takashi Nagatani,et al.  Dynamical transition in merging pedestrian flow without bottleneck , 2002 .

[42]  Majid Sarvi,et al.  Social dynamics in emergency evacuations: Disentangling crowd’s attraction and repulsion effects , 2017 .

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

[44]  Majid Sarvi,et al.  Group and Single Pedestrian Behavior in Crowd Dynamics , 2016 .

[45]  Omid Ejtemai,et al.  Modeling Pedestrian Crowd Exit Choice through Combining Sources of Stated Preference Data , 2015 .