Walkers on the circle

Jezbera, Daniel; Kordek, David; Křı́ž, Jan; Šeba, P.; Šroll, Petr

doi:10.1088/1742-5468/2010/01/l01001

Cited by 11 publications

(6 citation statements)

References 22 publications

(31 reference statements)

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“…arXiv:1207.0832v2 [physics.soc-ph] 23 Oct 2012 Seyfried et al [4,9,10] have performed experiments with pedestrians following an oval path. Similar studies have been reported in references [11,12]. These experiments have been performed either by using video analysis of the individual trajectories along one straight portion of the set-up [10], or by measuring times at which each participant passes a given measuring point [12].…”

Section: Introductionmentioning

confidence: 99%

Properties of pedestrians walking in line. II. Stepping behavior

et al. 2012

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In human crowds, interactions among individuals give rise to a variety of self-organized collective motions that help the group to effectively solve the problem of coordination. However, it is still not known exactly how humans adjust their behavior locally, nor what are the direct consequences on the emergent organization. One of the underlying mechanisms of adjusting individual motions is the stepping dynamics. In this paper, we present first quantitative analysis on the stepping behavior in a one-dimensional pedestrian flow studied under controlled laboratory conditions. We find that the step length is proportional to the velocity of the pedestrian, and is directly related to the space available in front of him, while the variations of the step duration are much smaller. This is in contrast with locomotion studies performed on isolated pedestrians and shows that the local density has a direct influence on the stepping characteristics. Furthermore, we study the phenomena of synchronization-walking in lock step-and show its dependence on flow densities. We show that the synchronization of steps is particularly important at high densities, which has direct impact on the studies of optimizing pedestrians' flow in congested situations. However, small synchronization and antisynchronization effects are found also at very low densities, for which no steric constraints exist between successive pedestrians, showing the natural tendency to synchronize according to perceived visual signals.

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Section: Introductionmentioning

confidence: 99%

Properties of pedestrians walking in line. II. Stepping behavior

et al. 2012

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“…Such experiments have indeed already been performed in the past. In [12], the distribution of time headways was measured. Seyfried et al [13] have measured the density and velocity of pedestrians following an oval trajectory.…”

Section: Introductionmentioning

confidence: 99%

Properties of pedestrians walking in line: Fundamental diagrams

Jelić

Appert-Rolland²,

Lemercier³

et al. 2012

Phys. Rev. E

152

127

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We present experimental results obtained for a one-dimensional pedestrian flow using high precision motion capture. The full pedestrians' trajectories are obtained. In this paper, we focus on the fundamental diagram, and on the relation between the instantaneous velocity and spatial headway (distance to the predecessor). While the latter was found to be linear in previous experiments, we show that it is rather a piecewise linear behavior which is found if larger density ranges are covered. Indeed, our data clearly exhibits three distinct regimes in the behavior of pedestrians that follow each other. The transitions between these regimes occur at spatial headways of about 1.1 and 3 m, respectively. This finding could be useful for future modeling.

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“…Pedestrian traffic flow has been studied empirically in a wide variety of situations, using both experimental methods and motion tracking of real crowds. The simplest case is uni-directional flow in a corridor, in which properties such as the dependence of speed on density have been analyzed [19][20][21][22][23][24]. Collision avoidance between pedestrians has been investigated in pairs of walkers [25,26] and multiple walkers [27].…”

Section: Introductionmentioning

confidence: 99%

Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of `stripe' formation in human data

Mullick¹,

Fontaine²,

Appert-Rolland³

et al. 2021

Preprint

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When two streams of pedestrians cross at an angle, striped patterns spontaneously emerge as a result of local pedestrian interactions. This clear case of self-organized pattern formation remains to be elucidated. In counterflows, with a crossing angle of 180°, alternating lanes of traffic are commonly observed moving in opposite directions, whereas in crossing flows at an angle of 90°, diagonal stripes have been reported. Naka (1977) hypothesized that stripe orientation is perpendicular to the bisector of the crossing angle. However, studies of crossing flows at acute and obtuse angles remain underdeveloped. We tested the bisector hypothesis in experiments on small groups (18-19 participants each) crossing at seven angles (30°intervals), and analyzed the geometric properties of stripes. We present two novel computational methods for analyzing striped patterns in pedestrian data: (i) an edge-cutting algorithm, which detects the dynamic formation of stripes and allows us to measure local properties of individual stripes; and (ii) a pattern-matching technique, based on the Gabor function, which allows us to estimate global properties (orientation and wavelength) of the striped pattern at a time T . We find an invariant property: stripes in the two groups are parallel and perpendicular to the bisector at all crossing angles. In contrast, other properties depend on the crossing angle: stripe spacing (wavelength), stripe size (number of pedestrians per stripe), and crossing time all decrease as the crossing angle increases from 30°to 180°, whereas the number of stripes increases with crossing angle. We also observe that the width of individual stripes is dynamically squeezed as the two groups cross each other. The findings thus support the bisector hypothesis at a wide range of crossing angles, although the theoretical reasons for this invariant remain unclear. The present results provide empirical constraints on theoretical studies and computational models of crossing flows.

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Walkers on the circle

Cited by 11 publications

References 22 publications

Properties of pedestrians walking in line. II. Stepping behavior

Properties of pedestrians walking in line. II. Stepping behavior

Properties of pedestrians walking in line: Fundamental diagrams

Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of `stripe' formation in human data

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