Step styles of pedestrians at different densities

Stepping locomotion is the basis of human movement. The investigation of stepping locomotion and its affecting factors is necessary for a more realistic knowledge of human movement, which is usually referred to as walking with equal step lengths for the right and left leg. To study pedestrians' stepping locomotion, a set of single-file movement experiments involving 39 participants of the same age walking on a highly curved oval course is conducted. The microscopic characteristics of the pedestrians including 1D Voronoi density, speed, and step length are calculated based on a projected coordinate. The influence of the projection lines with different radii on the measurement of these quantities is investigated. The step lengths from the straight and curved parts are compared using the Kolmogorov–Smirnov test. During the experiments, six different step styles are observed and the proportions of different step styles change with the density. At low density, the main step style is the stable-large step style and the step lengths of one pedestrian are almost constant. At high density, some pedestrians adjust and decrease their step lengths. Some pedestrians take relatively smaller and larger steps alternately to adapt to limited space.

[1]  Jun Zhang,et al.  Extraction and quantitative analysis of microscopic evacuation characteristics based on digital image processing , 2009 .

[2]  Armin Seyfried,et al.  Tracking People in Crowded Scenes , 2014 .

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

[4]  Felix Dietrich,et al.  Is Slowing Down Enough to Model Movement on Stairs , 2016 .

[5]  Felix Dietrich,et al.  The effect of stepping on pedestrian trajectories , 2015 .

[6]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[7]  D. Cunningham,et al.  Age-related changes in speed of walking. , 1988 .

[8]  Wei Lv,et al.  A continuous distance model (CDM) for the single-file pedestrian movement considering step frequency and length , 2012 .

[9]  Gerta Köster,et al.  Natural discretization of pedestrian movement in continuous space. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Andreas Schadschneider,et al.  Congestion Dynamics in Pedestrian Single-File Motion , 2016, 1602.03053.

[11]  Mohcine Chraibi,et al.  Generalized centrifugal-force model for pedestrian dynamics. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Felix Dietrich,et al.  A Study of Pedestrian Stepping Behaviour for Crowd Simulation , 2014 .

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

[14]  Serge P. Hoogendoorn,et al.  Pedestrian Behavior at Bottlenecks , 2005, Transp. Sci..

[15]  D. Manocha,et al.  Pedestrian Simulation Using Geometric Reasoning in Velocity Space , 2014 .

[16]  Cécile Appert-Rolland,et al.  Properties of pedestrians walking in line. II. Stepping behavior. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Bernhard Steffen,et al.  New Insights into Pedestrian Flow Through Bottlenecks , 2009, Transp. Sci..

[18]  Hubert Klüpfel,et al.  Evacuation Dynamics: Empirical Results, Modeling and Applications , 2009, Encyclopedia of Complexity and Systems Science.

[19]  D. Versluis,et al.  Microscopic interaction behavior between individual pedestrians , 2010 .

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

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

[22]  Andreas Schadschneider,et al.  Phase Coexistence in Congested States of Pedestrian Dynamics , 2010, ACRI.

[23]  Isabella von Sivers,et al.  How Stride Adaptation in Pedestrian Models Improves Navigation , 2014, ArXiv.

[24]  Andreas Schadschneider,et al.  Automatic Extraction of Pedestrian Trajectories from Video Recordings , 2010 .

[25]  Fei Peng,et al.  The influence of random slowdown process and lock-step effect on the fundamental diagram of the nonlinear pedestrian dynamics: An estimating-correction cellular automaton , 2015, Commun. Nonlinear Sci. Numer. Simul..

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

[27]  James M. Finley,et al.  A marching-walking hybrid induces step length adaptation and transfers to natural walking. , 2015, Journal of neurophysiology.

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