Crowd Dynamics Research Articles

Experimental study on the synchronization mechanism and trigger characteristic density of vertical evacuation in crowds.

Due to simultaneous horizontal and vertical displacement during vertical evacuation, the consequences of stampede congestion accidents can be more severe. Generally, pedestrians trigger a synchronization mechanism at some point during the vertical evacuation process. This synchronization behavior helps prevent stampede congestion and improves evacuation efficiency. This paper designs a well-controlled single-file vertical evacuation experiment. After the experiment, the video footage is imported into the TRACKER system to extract the coordinates of pedestrian step movements, after which the experimental data undergo calculations and visual analysis. The research findings indicate the following: Firstly, when the crowd coordinates trigger the synchronization mechanism, this behavior remains stable as long as pedestrian speed and direction are unchanged; Secondly, the variation in footstep speed over time is not directly related to the footstep synchronization rate of the crowd; Lastly, this study calculated the characteristic density value most likely to trigger the synchronization mechanism during vertical evacuation. This research deepens our understanding of crowd dynamics, reveals the characteristics of pedestrian movement during vertical evacuation, and proposes evacuation guidance strategies based on these features.

Understanding human-obstacle interaction dynamics on staircases: Implications for emergency evacuation and fire safety in high-rise buildings

Interactions between system components, including human-obstacle, human-building, human-robot, and human-human, significantly impact public safety, system efficiency, and functionality. A deeper understanding of these systems is essential to enhance their resilience and effectiveness. Despite the significance of these interactions, empirical research is limited, particularly regarding behavioral mechanisms when interacting with obstacles on stairways. Our study examines the evacuation behavior of 90 evacuees on the staircase of a high-rise building under different temporary obstacle conditions to understand how key factors affect decision-making and motion behavior during stairway descent. The experiments considered obstacle shapes as control variables and analyzed evacuation time, inner and outer stair route choices, regional speed fluctuations, velocity-relative displacement, evacuation efficiency, and biomechanical analysis of occupants’ comfort. Results show that larger obstacle shapes, increased evacuation urgency time, and closer proximity to the wall lead to a higher proportion of the splitting to merging state before and after obstacle interaction. A strong inner stair route preference emerges in no-obstacle conditions, with significant mean speed differences in downward movements when encountering temporary obstacle. Three phases of average speed variations are observed: deceleration, acceleration, and continued deceleration for the outer route; and deceleration followed by uniform speed for the inner route. A method was developed to calculate regional speed fluctuation using average speeds from trajectories. Comfort analysis revealed that temporary obstacle on building stairways significantly impact safe evacuation. Overall, these findings enhance the understanding of crowd dynamics in high-rise building emergency evacuations, with implications for model development, architectural design, building operations, emergency preparedness, behavioral cognition, and fire safety.

The effect of building bottlenecks on crowd dynamics involving individuals with simulated disabilities

With the development of urbanization and the growth of population, there is a growing demand for safety in public building facilities. As one of the essential building components of urban architecture, bottlenecks have a significant impact on the evacuation efficiency of crowds. Furthermore, the heterogeneity of crowds also contributes to the complexity of crowd movement through bottlenecks, while aggravating the magnitude of congestion induced by bottlenecks. The objective of this paper is to explore the movement characteristics of heterogeneous crowds passing through a corridor with a bottleneck by conducting a controlled experiment. There were three variables in this experiment, namely the individual categories (i.e., able-bodied individuals, simulated individuals on crutches and simulated wheelchair users), bottleneck width (i.e., 1.2, 1.6 and 2.0 m) and proportion of simulated disabilities in crowds (i.e., 0 %, 5 % and 10 %). Then offset angle, passing efficiency, fundamental diagram, etc., were analyzed. In trials involving simulated individuals on crutches, a higher detouring degree is observed compared to trials involving simulated wheelchair users or mixed groups of two types of simulated disabilities. There is an increase in flow rate induced by increasing the bottleneck width and decreasing the proportion of simulated disabilities. The passing efficiency at the upstream of the bottleneck in all tests is primarily influenced by the bottleneck width, while by the type and proportion of simulated disabilities at the downstream or inside the bottleneck. The findings are intended to complement the dynamic theory of heterogeneous crowds at building bottlenecks, while providing a reference for congestion control of crowds at bottlenecks.

An overview of the psychological complexities in sports performance

Our special issue comprises a diverse collection of ten research and review articles, each offering unique insights into the psychological dimensions of athletic performance. From studies examining the role of resilience in overcoming extreme score shifts to explorations of the mental toll caused by external crises like the COVID-19 pandemic and geopolitical conflict, these papers provide a broad spectrum of perspectives. The issue digs into critical topics such as the influence of crowd dynamics, athlete-coach relationships, and the psychological challenges of breaking long-standing records, all while highlighting innovative methodologies like ecological approaches and creative non-fiction. Together, these ten papers underscore the complexity of the psychological factors that impact athletes’ success and well-being, offering both theoretical advances and practical applications for the sporting world.

A brigde toward mathematics theory in living systems: the thermostatted kinetic theory method for crowd dynamics: Comment on the review paper “A decade of thermostatted kinetic theory models for complex active matter living systems” by Carlo Bianca

A brigde toward mathematics theory in living systems: the thermostatted kinetic theory method for crowd dynamics: Comment on the review paper “A decade of thermostatted kinetic theory models for complex active matter living systems” by Carlo Bianca

How behavioural changes in social groups affect evacuation efficiency of crowds

Consider an incident of acute emergency—such as a violent attack—necessitating swift evacuation of a crowd primarily made up of social groups. Is it possible to identify simple strategies that the groups can implement to facilitate collective movement efficiency? There has been some research, though not extensive, aimed at understanding unique evacuation dynamics of crowds of social groups, but mostly from a descriptive or observational perspective. Here, we introduce and explore a prescriptive or interventional approach. The aim is to establish effective behavioural interventions. Experiments are conducted with crowds of solo individuals as well as crowds composed of groups of three or groups of five. The results demonstrate a clear decrease in evacuation efficiency as crowd composition shifts from solo to groups, with a more pronounced effect observed with larger groups. We demonstrate how this inefficiency is attributable to the larger spatial footprint associated with groups. The findings also reveal that instructing groups to hold hands does not enhance evacuation efficiency. However, instructing them to form a line (i.e., platooning) leads to significant improvements, reducing evacuation times to levels comparable to crowds of solo individuals. These findings suggest that simple and easily communicable behavioural modifications for social groups can have substantial impacts on their evacuation efficiency. Making such strategies common knowledge has the potential of helping more people survive acute crises, an important aspect of collective resilience.

A Study on the Influencing Factors of the Vitality of Street Corner Spaces in Historic Districts: The Case of Shanghai Bund Historic District

The revitalization of historic districts is crucial for the sustainable development of cities, with street corner spaces being a vital component of the public space in these districts. However, street corner spaces have been largely overlooked in previous research on crowd dynamics within historic districts. This study investigates the key factors influencing crowd dynamics in street corner spaces within historic districts. First, a hierarchical model of vitality-influencing factors was developed based on prior research. Potential factors influencing the vitality of street corners were quantified using multi-source data collection methods, including deep learning algorithms, and crowd vitality within these spaces was assessed through multidimensional measurements. The impact of each element on crowd vitality was then analyzed through a multivariate linear regression model. The findings revealed that eight factors—corner building historicity, first-floor functional communality, transparency, openness, density of functional facilities, greenness, functional variety of buildings, and walkability—significantly influence the vitality of corner spaces, collectively explaining 77.5% of the vitality of these spaces. These conclusions offer new perspectives and scientific evidence for the revitalization and conservation of historic districts.

Crowd dynamics analysis and behavior recognition in surveillance videos based on deep learning

Crowd dynamics analysis and behavior recognition in surveillance videos based on deep learning

Crowd behavior detection: leveraging video swin transformer for crowd size and violence level analysis

In recent years, crowd behavior detection has posed significant challenges in the realm of public safety and security, even with the advancements in surveillance technologies. The ability to perform real-time surveillance and accurately identify crowd behavior by considering factors such as crowd size and violence levels can avert potential crowd-related disasters and hazards to a considerable extent. However, most existing approaches are not viable to deal with the complexities of crowd dynamics and fail to distinguish different violence levels within crowds. Moreover, the prevailing approach to crowd behavior recognition, which solely relies on the analysis of closed-circuit television (CCTV) footage and overlooks the integration of online social media video content, leads to a primarily reactive methodology. This paper proposes a crowd behavior detection framework based on the swin transformer architecture, which leverages crowd counting maps and optical flow maps to detect crowd behavior across various sizes and violence levels. To support this framework, we created a dataset comprising videos capable of recognizing crowd behaviors based on size and violence levels sourced from CCTV camera footage and online videos. Experimental analysis conducted on benchmark datasets and our proposed dataset substantiates the superiority of our proposed approach over existing state-of-the-art methods, showcasing its ability to effectively distinguish crowd behaviors concerning size and violence level. Our method’s validation through Nvidia’s DeepStream Software Development Kit (SDK) highlights its competitive performance and potential for real-time intelligent surveillance applications.Graphical abstract

Safe Path: Energy Harvesting from Pedestrian Movement in Karbala- Spatial Suitability and Crowd Dynamics Towards Sustainability

Safe Path: Energy Harvesting from Pedestrian Movement in Karbala- Spatial Suitability and Crowd Dynamics Towards Sustainability

Understanding pedestrian crowd dynamics on ramps: An empirical study triggered by Seoul Halloween crowd crush

Pedestrian safety on ramps demands greater attention compared to flat surfaces, as exemplified by a tragic crowd crush accident that claimed the lives of over 150 individuals on a densely populated ramp in South Korea in 2022. Understanding the dynamics of pedestrian movement on ramps is crucial for effectively managing mass events and daily pedestrian transportation. This paper presents an empirical study investigating bidirectional pedestrian flows on a simulated ramp with varying inclinations. Flow ratios, indicating the group size of major and minor flows in both directions, were examined. Results show that bidirectional pedestrian streams exhibit self-organizing behavior, characterized by the emergence of distinct lane formation phenomenon in both level and ramp walking scenarios. The shortest overall time required for pedestrians to exit the ramp was observed at a 3° inclination. As the ramp inclination increases, the disparities between upward and downward directions become more pronounced. Specifically, the uphill flow consistently exhibits a lower average speed compared to the downhill flow at the same inclination. In general, an increase in inclination is associated with a decrease in forward speed, an increase in lateral speed, and a greater utilization of handrails. Handrail plays a particularly important role in assisting pedestrians down very steep ramps. Furthermore, we found that the influence of flow ratio on walking parameters undergoes a change from level walking to ramp walking scenarios. Notably, for the same flow ratio, the results can vary significantly depending on whether the major flow is uphill or downhill. Our findings provide valuable insights into crowd management on ramps and hold significant implications for the safer design of ramps in subway stations, underpasses, and overpasses.

AI-Enhanced Tools and Strategies for Airborne Disease Prevention in Cultural Heritage Sites.

In the wake of the COVID-19 pandemic, the surveillance and safety measures of indoor Cultural Heritage sites have become a paramount concern due to the unique challenges posed by their enclosed environments and high visitor volumes. This communication explores the integration of Artificial Intelligence (AI) in enhancing epidemiological surveillance and health safety protocols in these culturally significant spaces. AI technologies, including machine learning algorithms and Internet of Things (IoT) sensors, have shown promising potential in monitoring air quality, detecting pathogens, and managing crowd dynamics to mitigate the spread of infectious diseases. We review various applications of AI that have been employed to address both direct health risks and indirect impacts such as visitor experience and preservation practices. Additionally, this paper discusses the challenges and limitations of AI deployment, such as ethical considerations, privacy issues, and financial constraints. By harnessing AI, Cultural Heritage sites can not only improve their resilience against future pandemics but also ensure the safety and well-being of visitors and staff, thus preserving these treasured sites for future generations. This exploration into AI's role in post-COVID surveillance at Cultural Heritage sites opens new frontiers in combining technology with traditional conservation and public health efforts, providing a blueprint for enhanced safety and operational efficiency in response to global health challenges.

Together Apart: the Influence of Increased Crowd Heterogeneity on Crowd Dynamics at Bottlenecks

Individual differences in mobility (e.g., due to wheelchair use) are often ignored in the prediction of crowd movement. Consequently, engineering tools cannot fully describe the impact of vulnerable populations on egress performance. To contribute to closing this gap, we performed laboratory experiments with 25 pedestrians with varying mobility profiles. The control condition comprised only participants without any additional equipment; in the luggage condition and the wheelchair condition, two participants at the center of the group either carried suitcases or used a wheelchair. We found that individuals using wheelchairs and to a lesser degree those carrying luggage needed longer to pass through the bottleneck, which also affected those walking behind them. This led to slower times to fully clear the bottleneck in the wheelchair and luggage condition compared to the control group. The results challenge the status quo in existing approaches to calculating egress performance and other key performance metrics in crowd dynamics.

Revisiting the paper ”Simulating dynamical features of escape panic”: What have we learnt since then?

The paper ”Simulating dynamical features of escape panic” by Helbing, Farkas, and Vicsek, published over two decades ago in Nature, has left an indelible mark on the field of crowd dynamics. With nearly 3,000 citations to date, according to the Web of Science records, and significant influence, it has shaped the crowd dynamics field. This analysis investigates the overall influence of this paper through a variety of indicators, mapping its reach across research areas. The intellectual foundation of the paper is traced, examining the references cited. The terminological impact is also explored, showing how the paper made use of terms like ”panic” and ”herding”. Moreover, the alignment of the assumptions of the paper with empirical evidence is discussed, finding discrepancies in key assertions about panic behaviour. The numerical simulations of the paper and observations have significantly influenced the field, such as for the case of the ”faster-is-slower” phenomenon. The paper remains a key pillar in crowd dynamics, nevertheless, we advocate for a new course of the field shifting away from the terminology adopted in the paper and focusing more on empirical evidence.

Crowd Analyzer using Trilateration and Keep Alive Signals

Tracking mobile phones in a specific area is crucial for assessing population density and understanding crowd dynamics. Traditional methods rely on Wi-Fi and GPS, but offline techniques like cell tower triangulation offer valuable insights even in areas with limited connectivity. By analyzing the number of mobile phones present, estimated through trilateration using signals from the phone's keep-alive signal, one can accurately estimate the crowd size. This information aids in urban planning, transportation management, event organization, and business strategies. Empowered with such data, decision-makers can optimize resource allocation, enhance safety measures, and improve overall societal well-being through informed decision-making.

Vibration serviceability of footbridges in crowded conditions: crowd dynamics simulations vs guidelines’ predictions

Abstract Vibration serviceability assessment in crowded conditions requires a reliable human-induced loading model taking into account pedestrian interaction. Current guidelines provide simplified procedures to determine the maximum dynamic response based on very simplified loading models. The main objective of this paper is to assess the reliability of current guidelines for vibration serviceability assessment of footbridges. With this aim, an extensive campaign of numerical simulations of bidirectional pedestrian traffic is carried out through an agent-based model, considering variable pedestrian densities and deck widths. The results of numerical simulations are first compared against the experiments available in the literature in terms of fundamental diagram of the mean walking speed as a function of pedestrian density. Then, starting from numerical simulations, the dynamic response of a class of footbridges is estimated numerically and compared with guidelines’ predictions in order to assess their reliability.

Model of coordinated crowd dynamics

Model of coordinated crowd dynamics

Classification of Pedestrian Crowds by Dimensionless Numbers

Presently, classifications of pedestrian crowds primarily rely on density. This fails to encompass the diverse behaviours and risk profiles observed. We introduce two dimensionless numbers, the Intrusion number In, based on the desire to maintain one’s personal space, and the Avoidance number Av, based on the anticipation of collisions. These two numbers delineate different flow regimes, as we intuitively expect and as we empirically demonstrate using an extensive dataset. Similarly to Fluid Mechanics, where dimensionless numbers guide the choice between different approximations, the dynamics of crowds can be approached in each regime by perturbative expansions, which yield pedestrian models applicable in the corresponding regime (and only there).

Impact of the Local Dynamics on Exit Choice Behaviour in Evacuation Model

This study investigated the interplay between exit selection models and local pedestrian movement patterns within floor field frameworks. Specifically, this investigation analysed the performance of a multinomial logit exit choice model, incorporating both expected utility theory and cumulative prospect theory frameworks when coupled with three distinct local-level pedestrian movement models (FF-Von Neumann, FF-Moore, and NSFF). The expected utility theory framework considers the deterministic component as a linear relationship, while the cumulative prospect theory framework further considers the decision-maker’s risky attitudes by transforming objective terms into subjective terms using a power value function. The core objective was to comprehend how local movement dynamics, as represented by the floor field models, influence decision-making during exit selection. Comparative analyses revealed intriguing variations between the three local models, despite their shared expected utility theory-based exit choice framework. These discrepancies stemmed from the diverse pedestrian trajectory behaviours generated by each model. Consequently, these local dynamics impacted the decision-maker’s assessment of critical factors, such as the number of evacuees close to the decision-maker (NCDM) and the number of evacuees close to an exit (NCE), which the exit choice model incorporates. These assessments, in turn, significantly affected higher-level decision-making. The integration of the three models with the multinomial logit exit choice model, using either cumulative prospect theory and expected utility theory frameworks, further strengthened the observed bilateral relationship. While the specific nature of this relationship varied depending on the chosen framework and its implementation details, these consistent findings demonstrate the robustness of the results. This reinforced the influence of local-level pedestrian dynamics on higher-level exit selection, highlighting the importance of accurate crowd dynamics modelling, especially when advanced exit choice models consider local movement factors.

Convergence of the numerical approximations and well-posedness: Nonlocal conservation laws with rough flux

We study a class of nonlinear nonlocal conservation laws with discontinuous flux, modeling crowd dynamics and traffic flow. The discontinuous coefficient of the flux function is assumed to be of bounded variation (BV) and bounded away from zero, and hence the spatial discontinuities of the flux function can be infinitely many with possible accumulation points. Strong compactness of the Godunov and Lax-Friedrichs type approximations is proved, providing the existence of entropy solutions. A proof of the uniqueness of the adapted entropy solutions is provided, establishing the convergence of the entire sequence of finite volume approximations to the adapted entropy solution. As per the current literature, this is the first well-posedness result for the aforesaid class and connects the theory of nonlocal conservation laws (with discontinuous flux), with its local counterpart in a generic setup. Some numerical examples are presented to display the performance of the schemes and explore the limiting behavior of these nonlocal conservation laws to their local counterparts.