Investigation of pedestrian evacuation scenarios through congestion level and crowd dang

In this paper, we present two quantities aimed at numerically describing the level of congestion and the intrinsic risk of pedestrian crowds. The congestion level allows to assess the smoothness of pedestrian streams and recognize regions where self-organization is difficult or not possible. This measure differs from previous attempts to quantify congestion in pedestrian crowds by employing velocities as vector entities (thus not only focusing on the absolute value). The crowd danger contains elements related to congestion, but also includes the effect of density, consequently allowing to asses the risks intrinsically created by the dynamics of crowds. Details on the computational methods related to both quantities are described in the paper and their properties are discussed. As a practical application, both measures are used to investigate supervised experiments where evacuation (or similar conditions) are considered. Results for small room sizes and limited number of pedestrians show that the crowd danger distribution over the space in front of the exit door has similar patterns to typical quantities used in the frame of pedestrian dynamics (density and flow) and symmetrical shapes are obtained. However, when larger scenarios are considered, then congestion map and crowd danger become unrelated from density and/or flow, showing that both quantities express different aspects of pedestrian motion

Unidirectional and bidirectional flow in a narrow corridor with body rotation

In this paper, we developed a new pedestrian model, where pedestrians are represented with three circles and rotate their body to avoid others. In most pedestrian models, the body posture of pedestrians is statically connected with the walking direction; however, they may become different in our model, in other words, pedestrians can walk sideways. We conducted simulation on bidirectional flow in a narrow corridor where body rotation is necessary to avoid collisions and succeeded to reproduce realistic fundamental diagram

Trends in crowd accidents based on an analysis of press reports

Crowd accidents – defined as situations where mass gatherings of people lead to deaths or injuries – have become a frequent occurrence on a global scale. Given the recurring nature of these accidents, it is essential that their characteristics are analyzed. To this end, an important step would be documenting these records. Here, a database of crowd accidents is developed for the period of 1900–2019 through a comprehensive investigation of the press and media reports. The analyses focus mainly on temporal trends of their frequency and injury/casualty in each accident, as well as their geographical distribution and classification based on the purpose of gathering. Results show that the frequency of crowd accidents has been unambiguously on the rise over the last 120 years. Also, there was no indication that larger crowd sizes increase the risk of injury or death per person. In fact, the opposite was the case, although a causal relation between crowd size and risk of injury/death is impossible to establish. Over time, the share of sport events in crowd accidents has declined, and instead, religious gatherings have become more notably present in the statistics. An interesting observation is the association of accident rates to the income level of the countries where they happen, with low-and-middle-income countries being more represented in the records. India and (to a lesser extent) West Africa, in particular, appear to be hot spots for crowd accidents. Finally, it is argued that the exponential increase in crowd accidents of the last century was only partially real, with technology also playing a role in making information more accessible for recent accidents. After the internet (and SNS) became widespread, the trend for reported crowd accidents does not show anymore an exponential increase although it is difficult to conclude whether their frequency is stable or not. The insights obtained from this study can pave the way for developing diagnostic knowledge and raising awareness about the ubiquity of crowd accidents.</p

Experimental study on the evading behaviour of single pedestrians encountering an obstacle

Present simulation and experimental research still have deficiency in depicting the evading behaviour of single pedestrians confronting with an obstacle, which is the basis for the study of crowd dynamics affected by obstacles in real life. Therefore, this study will conduct experiments with a bar-shaped obstacle in the middle of a corridor and explore the corresponding general and particular features of single pedestrians. Particularly, the variation of pedestrian velocity and trajectory under different-sized obstacles will be illustrated. By taking the average velocity and trajectories of the 32 participants, it could be concluded that pedestrians would walk at a velocity of about 1.5 m/s without being affected by the size of obstacle. Besides, pedestrians tend to pass a location about 0.4 meters away from the obstacle edge that is perpendicular to walking direction. Furthermore, pedestrians tend to begin and finish evading the obstacle at locations respectively about 4.40 meters and 4.85 meters away from the obstacle. We also found a heterogeneity in the evading behaviour and pedestrians could be classified into four types accordingly. Results of this study are expected to provide reliable evidence for agent-based modelling in the future

Thermodynamics of a gas of pedestrians: theory and experiment

In this paper, we perform an experiment on the interaction of pedestrians in a chaotic environment and investigate the possibility to study its results using a thermodynamic model. In contrast to simple single-file unidirectional scenarios, where only distance and time are relevant to adjust walking speed, bidirectional cases are much more complex since pedestrians can perform evading manoeuvres to avoid collisions. To better understand collision avoidance in a bidimensional environment we designed a set of experiments where people need to move chaotically for the whole time. Trajectories of moving pedestrians were obtained by tracking their head position, but a method to obtain body orientation failed, thus limiting reliable information on average quantities, i.e. average density and speed. By analysing those data, we showed that equations for thermodynamic processes can be used to describe pedestrian dynamics from medium densities or a state where interaction distances are very small. To allow combining low density cognitive aspects of collision avoidance with semi-random motion at medium densities we also developed a microscopic simulation model inspired by physics. Results show that, after calibrations, the simulation model allows to reproduce the fundamental diagram of different studies despite the very simple rules implemented. This shows that describing the statistical nature of specific crowds requires a relatively small set of rules and research should focus on cognitive/psychological aspects which are essential for understanding crowds of people

How crowd accidents are reported in the media: Lexical and sentiment analyses

The portrayal of crowd accidents by the media can influence public understanding and emotional response, shaping societal perceptions and potentially impacting safety measures and preparedness strategies. This paper critically examines the portrayal of crowd accidents in news coverage by analyzing the texts of 372 media reports of crowd accidents spanning 26 diverse news sources from 1900 to 2019. We investigate how media representations of crowd accidents vary across time and geographical origins. Our methodology combines lexical analysis to unveil prevailing terminologies and sentiment analysis to discern the emotional tenor of the reports. Contrary to anticipated results, the findings reveal the prevalence of the term "stampede" over "panic" in media descriptions of crowd accidents. Notably, divergent patterns are observable when comparing Western versus South Asian media (notably India and Pakistan), unveiling a cross-cultural dimension. Moreover, the analysis detects a gradual transition from "crowd stampede" to "crowd crush" in media and Wikipedia narratives in recent years, suggesting evolving lexical sensitivities. Sentiment analysis uncovers a consistent association with fear-related language, indicative of media's propensity towards sensationalism. This fear-infused narrative has intensified over time. The study underscores the potential impact of language and sentiment in shaping public perspectives on crowd accidents, revealing a pressing need for responsible and balanced reporting that moves beyond sensationalism and promotes a nuanced understanding. This will be crucial for increasing public awareness and preparedness against such accidents.Comment: 54 pages, 15 figures, 17 tables, 4 appendixes, 372 media report

人流の計測と数値モデリング

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 西成 活裕, 東京大学教授 神崎 亮平, 東京大学准教授 菅野 太郎, 東京大学准教授 関本 義秀, 東京大学准教授 柳澤 大地University of Tokyo(東京大学

Secondary syphilis

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Congestion Number Analysis of Cross-Flow Dynamics: Experimental Data and Simulations

We recently proposed the "Congestion Number" (CN) as a metricto evaluate the state of a pedestrian crowd. Such metric, whose definition is based on the gradient of the rotor of the crowd velocity field, appears to provide additional information with respect to traditional metrics based on pedestrian density and flow. We also published two works on the dynamics of orthogonally crossing pedestrian flows under different density regimes. In the first manuscript we analysed experimental data by using traditionalobservables such as density, velocity and relative position between pedestrians, along with less explored ones such as body orientation. In the second one we proposed a hierarchy of simulation models to reproduce the cross-flow dynamics, and used the aforementioned observables to compare such models. Based on theoretical considerations and analysis of real world data, we believe the crossing flow setting to be a good arena to test the CN metric, and in this work we perform a CN analysis on the empirical and simulation data. Results show that simulation models, which reproduced almost perfectly the density time dependence of the pedestrian crowd, fail to reproduce the CN one. Actually, models "outperform" the pedestrian crowd when analysed using CN. These preliminary results suggest that the CN metric may provide useful information not only in crowd assessment but also in model evaluation