SearcharxivSearch

arXiv subjects

Sarah Paetzke

Publications and source records attributed to Sarah Paetzke.

4 recordsLinked to original sources

Pedestrian Flow Analysis in High-Density Crowds: Continuity Equation with Voronoi-Based Fields

Since the beginning of the century, capturing trajectories of pedestrian streams precisely from video recordings has been possible. To enable measurements at high density, the heads of the pedestrians are marked and tracked, thus providing a complete representation of the phase space. However, classical definitions of flow, density, and velocity of pedestrian streams are based on different segments in phase space. In addition, traditional methods fail with high densities of people, as heads move even when a crowd is blocked and standing still. In this article, Voronoi decomposition is used to construct density and velocity fields from pedestrian trajectories to solve this problem. Combined with the continuity equation, a flow equation on the basis of trajectories is derived satisfying the conservation of particle numbers exactly. The proposed method allows definitions of all quantities in the same segment of phase space even on scales smaller than the dimensions of a pedestrian. It is shown that these new definitions of flow, density, velocity are consistent with classical measurements and make it possible to determine standstill in pedestrian flows even when individual body parts are moving. These properties allow to scrutinize inconsistencies in the state of the art of pedestrian fundamental diagrams.

physics.soc-ph

Pedestrian Crowd Management Experiments: A Data Guidance Paper

Understanding pedestrian dynamics and the interaction of pedestrians with their environment is crucial to the safe and comfortable design of pedestrian facilities. Experiments offer the opportunity to explore the influence of individual factors. In the context of the project CroMa (Crowd Management in transport infrastructures), experiments were conducted with about 1000 participants to test various physical and social psychological hypotheses focusing on people's behaviour at railway stations and crowd management measures. The following experiments were performed: i) Train Platform Experiment, ii) Crowd Management Experiment, iii) Single-File Experiment, iv) Personal Space Experiment, v) Boarding and Alighting Experiment, vi) Bottleneck Experiment and vii) Tiny Box Experiment. This paper describes the basic planning and implementation steps, outlines all experiments with parameters, geometries, applied sensor technologies and pre- and post-processing steps. All data can be found in the pedestrian dynamics data archive.

physics.soc-ph

Influence of Gender Composition in Pedestrian Single-File Experiments

Various studies address the question of what factors are relevant to the course of the fundamental diagram in single-file experiments. Some indicate that there are differences due to group composition when gender is taken into account. For this reason, further single-file experiments with homogeneous and heterogeneous group compositions were conducted. A Tukey HSD test was performed to investigate whether there are differences between the mean of velocity in different density ranges. A comparison of different group compositions shows that the effect of gender can only be seen, if at all, in a small density interval. Regression analyses were also conducted to determine whether, at high densities, the distance between individuals depends on the gender of the neighboring pedestrians and to establish what human factors have an effect on the velocity. An analysis of the distances between individuals at high densities indicates that there is no effect of the gender of the neighboring pedestrians. Taking into account additional human factors in a regression analysis does not improve the model.

physics.soc-ph

Influence of individual factors on fundamental diagrams of pedestrians

In recent years, numerous studies have been published dealing with the effect of individual characteristics of pedestrians on the fundamental diagram. These studies compared cumulative data on individuals in a group homogeneous in terms of one human factor such as age but heterogeneous in terms of other factors for instance gender. In order to examine the effect of all determined as well as undetermined human factors, individual fundamental diagrams are introduced and analyzed using multiple linear regression. A single-file school experiment with students of different age, gender, and height is therefore considered. Single individuals appearing in different runs are analyzed to study the effect of human factors such as height, age and gender and all other unknown individual effects such as motivation or attention to the individual speed. The analysis shows that for students age and height are strongly correlated and, consequently, age can be ignored. Furthermore, the study shows that gender has a weak effect and other nonmeasurable individual characteristics have a stronger effect than height. In a further step, a mixed model is used as well as the multiple linear model. Here, it is shown that the mixed model that considers all other unknown individual effects of each person as a random factor is preferable to the model where the individual speed only depends on the variables of headway, height, and all other unknown individual effects as fixed factors.

physics.soc-ph