Pedestrian dynamics in single-file movement of crowd with different age compositions

An aging population is bringing new challenges to the management of escape routes and facility design in many countries. This paper investigates pedestrian movement properties of crowd with different age compositions. Three pedestrian groups are considered: young student group, old people group and mixed group. It is found that traffic jams occur more frequently in mixed group due to the great differences of mobilities and self-adaptive abilities among pedestrians. The jams propagate backward with a velocity 0.4 m/s for global density around 1.75 m-1 and 0.3 m/s for higher than 2.3 m-1. The fundamental diagrams of the three groups are obviously different from each other and cannot be unified into one diagram by direct non-dimensionalization. Unlike previous studies, three linear regimes in mixed group but only two regimes in young student group are observed in the headway-velocity relation, which is also verified in the fundamental diagram. Different ages and mobilities of pedestrians in a crowd cause the heterogeneity of system and influence the properties of pedestrian dynamics significantly. It indicates that the density is not the only factor leading to jams in pedestrian traffic. The composition of crowd has to be considered in understanding pedestrian dynamics and facility design.Comment: 11 pages, 13 figures, 3 table

Data archive for exploring pedestrian dynamics and its application in dimensioning of facilities for multidirectional streams

In this paper an overview of an open data archive with data from experiments investigating pedestrian dynamics is presented. As an example of the use of this data the analysis of recently published data about the capacity of crossings is shown

Impact of Vehicle Pedestrian Interaction on Traffic Flow: Midblock and Intersections

Several studies are there to understand the pedestrian movement and all the studies are based on fundamental diagrams only. These studies construct a base to characterize pedestrian flow. Several experiments have conducted to understand the pedestrian flow, likewise some field observations have done to represent fundamental diagrams. Therefore, before going to analyze the data from the observation, it is necessary to note down the pedestrian flow parameters carefully. The aim of the paper is to build up the base to fundamental diagrams and for characterization of pedestrian. And derive the required flow diagrams and results from the field observations. Field survey is conducted to know the vehicle pedestrian interaction, and this field data with respect to pedestrian crossing at signalized, Unsignalized or at midblock sections is aimed to be observed. And the impact of vehicle pedestrian interaction at several intersections/midblock sections is to be studied. To do this, several places are chosen from Rourkela. It is aimed to observing whether the pedestrian fundamental diagram is different in alternate locations or not. In this study it is found that fundamental diagrams are different in different locations of Rourkel

High-statistics pedestrian dynamics on stairways and their probabilistic fundamental diagrams

Staircases play an essential role in crowd dynamics, allowing pedestrians to flow across large multi-level public facilities such as transportation hubs, and office buildings. Achieving a robust understanding of pedestrian behavior in these facilities is a key societal necessity. What makes this an outstanding scientific challenge is the extreme randomness intrinsic to pedestrian behavior. Any quantitative understanding necessarily needs to be probabilistic, including average dynamics and fluctuations. In this work, we analyze data from an unprecedentedly high statistics year-long pedestrian tracking campaign, in which we anonymously collected millions of trajectories across a staircase within Eindhoven train station (NL). Made possible thanks to a state-of-the-art, faster than real-time, computer vision approach hinged on 3D depth imaging, and YOLOv7-based depth localization. We consider both free-stream conditions, i.e. pedestrians walking in undisturbed, and trafficked conditions, uni/bidirectional flows. We report the position vs density, considering the crowd as a 'compressible' physical medium. We show how pedestrians willingly opt to occupy fewer space than available, accepting a certain degree of compressibility. This is a non-trivial physical feature of pedestrian dynamics and we introduce a novel way to quantify this effect. As density increases, pedestrians strive to keep a minimum distance d = 0.6 m from the person in front of them. Finally, we establish first-of-kind fully resolved probabilistic fundamental diagrams, where we model the pedestrian walking velocity as a mixture of a slow and fast-paced component. Notably, averages and modes of velocity distribution turn out to be substantially different. Our results, including probabilistic parametrizations based on few variables, are key towards improved facility design and realistic simulation of pedestrians on staircases

High-statistics pedestrian dynamics on stairways and their probabilistic fundamental diagrams

Staircases play an essential role in crowd dynamics, allowing pedestrians to flow across large multi-level public facilities such as transportation hubs, shopping malls, and office buildings. Achieving a robust quantitative understanding of pedestrian behavior in these facilities is a key societal necessity. What makes this an outstanding scientific challenge is the extreme randomness intrinsic to pedestrian behavior. Any quantitative understanding necessarily needs to be probabilistic, including average dynamics and fluctuations. To this purpose, large-scale, real-life trajectory datasets are paramount. In this work, we analyze the data from an unprecedentedly high statistics year-long pedestrian tracking campaign, in which we anonymously collected millions of trajectories of pedestrians ascending and descending stairs within Eindhoven Central train station (The Netherlands). This has been possible thanks to a state-of-the-art, faster than real-time, computer vision approach hinged on 3D depth imaging, sensor fusion, and YOLOv7-based depth localization. We consider both free-stream conditions, i.e. pedestrians walking in undisturbed, and trafficked conditions, unidirectional/bidirectional flows. We report on Eulerian fields (density, velocity and acceleration), showing how the walking dynamics changes when transitioning from stairs to landing. We then investigate the (mutual) positions of pedestrian as density changes, considering the crowd as a “compressible” physical medium. In particular, we show how pedestrians willingly opt to occupy fewer space than available, accepting a certain degree of compressibility. This is a non-trivial physical feature of pedestrian dynamics and we introduce a novel way to quantify this effect. As density increases, pedestrians strive to keep a minimum distance d≈0.6m (two treads of the staircase) from the person in front of them. Finally, we establish first-of-kind fully resolved probabilistic fundamental diagrams, where we model the pedestrian walking velocity as a mixture of a slow and fast-paced component (both in non-negligible percentages and with density-dependent characteristic fluctuations). Notably, averages and modes of velocity distribution turn out to be substantially different. Our results, of which we include probabilistic parametrizations based on few variables, are key towards improved facility design and realistic simulation of pedestrians on staircases.</p

Experimental Study of Collective Pedestrian Dynamics

We report on two series of experiments, conducted in the frame of two different collaborations designed to study how pedestrians adapt their trajectories and velocities in groups or crowds. Strong emphasis is put on the motivations for the chosen protocols and the experimental implementation. The first series deals with pattern formation, interactions between pedestrians, and decision-making in pedestrian groups at low to medium densities. In particular, we show how pedestrians adapt their headways in single-file motion depending on the (prescribed) leader’s velocity. The second series of experiments focuses on static crowds at higher densities, a situation that can be critical in real life and in which the pedestrians’ choices of motion are strongly constrained sterically. More precisely, we study the crowd’s response to its crossing by a pedestrian or a cylindrical obstacle of 74cm in diameter. In the latter case, for a moderately dense crowd, we observe displacements that quickly decay with the minimal distance to the obstacle, over a lengthscale of the order of the meter

Properties of pedestrians walking in line without density constraint

This article deals with the study of pedestrian behaviour in one-dimensional traffic situations. We asked participants to walk either in a straight line with a fast or slow leader, or to form a circle, without ever forcing the conditions of density. While the observed density results from individual decisions in the line case, both density and velocity have to be collectively chosen in the case of circle formation. In the latter case, interestingly, one finds that the resulting velocity is very stable among realizations, as if collective decision was playing the role of an average. In the line experiment, though participants could choose comfortable headways, they rather stick to short headways requiring a faster adaption - a fact that could come from a ``social pressure from behind''. For flows close to the jamming transition, the same operating point is chosen as in previous experiments where it was not velocity but density that was imposed. All these results show that the walking values preferred by humans in following tasks depend on more factors than previously considered.Comment: Main paper (11 pages, 13 figures) + Suppl. Mat. (8 pages, 9 figures

Exploring crowd persistent dynamism from pedestrian crossing perspective: An empirical study

Crowd studies have gained increasing relevance due to the recurring incidents of crowd crush accidents. In addressing the issue of the crowd's persistent dynamism, this paper explored the macroscopic and microscopic features of pedestrians crossing in static and dynamic contexts, employing a series of systematic experiments. Firstly, empirical evidence has confirmed the existence of crowd's persistent dynamism. Subsequently, the research delves into two aspects, qualitative and quantitative, to address the following questions:(1) Cross pedestrians tend to avoid high-density areas when crossing static crowds and particularly evade pedestrians in front to avoid deceleration, thus inducing the formation of cross-channels, a self-organization phenomenon.(2) In dynamic crowds, when pedestrian suffers spatial constrained, two patterns emerge: decelerate or detour. Research results indicate the differences in pedestrian crossing behaviors between static and dynamic crowds, such as the formation of crossing channels, backward detours, and spiral turning. However, the strategy of pedestrian crossing remains consistent: utilizing detours to overcome spatial constraints. Finally, the empirical results of this study address the final question: pedestrians detouring causes crowds' persistent collective dynamism. These findings contribute to an enhanced understanding of pedestrian dynamics in extreme conditions and provide empirical support for research on individual movement patterns and crowd behavior prediction.Comment: 31pages, 17figure