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• Investigate the crowd movement characteristics within merging structures in subway stations. • Analyze the impact of obstacle positions and flow levels on the crowd merging process. • Provide a feasible way to improve the efficiency and safety level of pedestrian merging process. Mass passenger flow and crowd gathering in subway stations raise the potential of crowd accidents. To improve the safety level in subway stations, it is crucial to investigate the crowd movement characteristics within specific structures with higher risk levels and regulate the passenger flow. The merging structure is common in subway stations with a larger scale of complex multi-directional movements and always be considered a potential bottleneck. It has been proven that specific geometric constraints in merging structures can significantly reduce traffic efficiency and expedite the formation of congestion by aggravating the conflicts among the crowds. However, there is still a lack of research on measures to improve the performance of existing merging structures. Previous findings show that properly set obstacles may increase the performance of bottleneck regions, which provides an opportunity to consider whether the obstacle effect can also be observed during the merging process. From this perspective, we carried out 39 groups of controlled experiments to investigate the impact of obstacle positions on the merging process under three different flow levels. A real human was used as the obstacle, and the distribution of different obstacle positions was divided into three regions. Our results demonstrate that setting the obstacle in certain regions will increase the performance of merging structures in terms of average outflow, velocity, and local density. The average velocity and outflow are increased by up to 6.82 % and 11.26 %, while the local density within the merging area is kept below 3.5 m−2. In contrast, some other regions will generate less efficient outcomes and cause a higher probability of jamming on the merging process. The maximum reduction of average velocity and outflow is 30.99 % and 19.45 %, and the local density can exceed 5 m−2. The performance of different obstacle positions is also affected by the flow level, and controlling the flow at a lower level is more beneficial for the merging process. Other microscopic parameters, such as channel utilization, detour degree, and personal distance, are also introduced to compare the impact of obstacle setups on pedestrian behaviors. The results provide a feasible way to improve the efficiency and safety level of merging structures in subway stations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• Explores enhancing evacuation efficiency through behavioural modifications. • Focusing on behaviour at bottlenecks, reaction time, and movement speed (pace). • Incremental behavioural adjustments significantly improve evacuation efficiency. • Observing a nearly linear relationship between behaviour adoption rate and efficiency gains. • Interventions targeting physical movement are more straightforward to implement and yield higher efficiency returns than decision-making interventions. In the context of evacuating crowded spaces during acute crises, every second is pivotal and can be the determinant in life-or-death situations. It is, therefore, important to explore and implement any measures or interventions that could streamline and expedite the evacuation process in such scenarios. This study aims to explore how the modification of individual behaviours can be leveraged to improve the efficiency of crowd evacuations, with a specific focus on the physical aspects of movement. We examine three crucial elements of physical movement: behaviours at bottlenecks, the initiation time of individual movement, and the pace of movement. A series of dedicated experiments, each tailored to one of these behavioural aspects, has been conducted. In these experiments, the behaviour of interest is modified incrementally within the crowd, with increases of 20% at each stage. This methodology allows for a detailed assessment of system efficiency at varying levels of instructed behaviour adoption/injection. The findings reveal that changes in each aspect of physical movement significantly influence overall efficiency. Most notably, the relationship between the uptake and increase in efficiency is nearly linear, and the rate of efficiency increase does not notably diminish with uptake, unlike interventions pertaining decision-making aspects of behaviour. This suggests that behavioural interventions targeting physical aspects of movement will likely yield higher efficiency returns. Moreover, in comparison with a related study focusing on decision-making aspects of evacuation behaviour, this research observes that modifying physical aspects of behaviour is generally more straightforward. The success rates of individuals in implementing physical movement instructions are higher, and the impact on the system is more pronounced than that observed in decision-making modifications. These results provide insights for developing simple, actionable instructions that can be effectively communicated to the public. These instructions can be disseminated as part of training and education programs or even provided on the spot during an evacuation. [ABSTRACT FROM AUTHOR]

• Investigates the impact of simple behavioural modifications on crowd evacuation efficiency. • Significant improvements in evacuation efficiency through behavioural interventions. • Influencing exit choice adaptation resulted in higher efficiency gains compared to exit choice. • Partial adoption of beneficial strategies can still enhance evacuation outcomes. • Poor strategies can have more detrimental effects than the benefits of good strategies. Crowded environments are inherently vulnerable to a range of risks, including earthquakes, fires, violent attacks, and terrorism. In such scenarios, every second counts in an evacuation, as it can significantly impact the number of lives saved. This paper introduces a novel approach to optimising crowd evacuation processes, focusing on behavioural modification rather than traditional methods such as mathematical optimisation models or architectural adjustments. We propose that by altering the behaviours of individuals within a crowd, overall system efficiency can be enhanced from within. We explore the effects of imparting simple, easily understandable strategies or instructions to individuals that can improve evacuation efficiency. The current work concentrates on how modifications in individual decision-making— namely, exit-choice and exit-choice-changing behaviour — can influence evacuation dynamics. We present the results of six major evacuation experiments, encompassing nearly 100 experimental scenarios and repetitions, which specifically investigate the effect of influencing exit choice and adaptation in exit-choice behaviour. The investigation revolves around three core questions: (a) the impact of effective strategies (b) the potential consequences of detrimental strategies, indicative of common misconceptions or poor advice, and (c) the influence of varying levels of strategy adoption, examining how system efficiency changes as more individuals embrace either beneficial or harmful strategies. The findings indicate that behavioural modification can substantially influence evacuation efficiency. Interestingly, the negative impact of poor strategies outweighs the benefits of effective ones. With respect to beneficial strategies, a significant increase in efficiency is observed at initial and intermediate levels of strategy adoption/uptake, suggesting that complete compliance is not necessary to enhance overall system performance. The benefit of influencing decision adaptation behaviour is considerably more tangible than influencing exit choice behaviour. These insights establish a novel perspective in evacuation safety. They lay a foundational framework for developing targeted public education and training programs based on empirical evidence. They highlight the importance of awareness and self-regulation among crowds, showcasing their potential to significantly increase both efficiency and safety in evacuation scenarios, potentially saving lives. [ABSTRACT FROM AUTHOR]

Previous studies indicate that the movement of pedestrians under poor visibility conditions is significantly different from that under good visibility conditions. To investigate the influence of visibility factor on the longitudinal movement of pedestrian, series of single-file experiments were performed under the quantitative control of visibility level. Based on the extracted trajectories, typical evacuation behavior and movement characteristics of pedestrians under different visibility conditions are explored. It is found that the lateral swing amplitude of pedestrians during movement is within 20 cm under low densities while it is close to 30 cm at high densities. The free velocity under the light transmission of 100 %, 2.2 %, 0.5 % and 0.1 % is 0.856 m/s, 0.823 m/s, 0.741 m/s and 0.712 m/s respectively. Individuals cannot accurately perceive the surrounding situations with the worsening of visual condition, therefore the movement speed decreases under the poor visibilities. Besides, two regimes including the constrained regime and free regime are identified in the headway-velocity relation at different visibility levels. The maximum specific flow under the light transmission of 100 %, 2.2 %, 0.5 % and 0.1 % is 0.70 s−1, 0.67 s−1, 0.62 s−1 and 0.55 s−1 respectively. The study is helpful to reveal the pedestrian dynamics of single-file movement under the limited visibility conditions. • Single-file experiments were performed under the quantitative control of visibility. • Typical behavior and movement properties at different visibilities are explored. • Two regimes are identified in the headway-velocity relation at different visibilities. • Fundamental diagrams are obtained under different visibility levels. [ABSTRACT FROM AUTHOR]

• Behavioural study investigated transmission risks and mitigations for UK mass events in 2021. • Explored non-pharmaceutical interventions (NPIs); e.g. social distancing and face coverings. • 21 events observed. Data collection method presented with overview of data. The Events Research Programme (ERP) was a multi-disciplinary study undertaken during the COVID-19 pandemic to investigate SARS-CoV-2 transmission risks and mitigations around the reopening of mass events in the UK in 2021 – including a behavioural study, exploring how non-pharmaceutical interventions (NPIs), such as social distancing, pre-event virus testing, and the use of face coverings might enable people to attend events safely. This behavioural study is discussed here. A total of 21 pilot events were involved in the study between April and July 2021. The venues used for the pilots varied in size, layout, occupancy level, and crowd management approaches. Data was extracted from manual qualitative observations and venue CCTV cameras which recorded routinely at venues. In addition, 890 cameras were installed during the events to capture attendee movement outside the venues, during arrival, in event areas, circulation spaces, bars and restaurants, and on exiting. A mixed method approach was adopted to ensure locations and activities of interest were captured, quantitative data gathered, and that this data could be placed in context. This enabled a behavioural study, quantifying crowd performance behaviours for comparison between and within events. This paper describes the background to this work, the method adopted and provides a brief overview of the data collected, relating primarily to (i) crowd densities, (ii) social distancing (captured here as contact distancing), and (iii) the use of face coverings. [ABSTRACT FROM AUTHOR]

Well-structured pedestrian experiments in a long corridor have been carried out to explore the influence of obstacle shape and size on individual and crowd level pedestrian movement characteristics. Results indicate that for individual pedestrians, the number of right-turning pedestrians and the target drift angle show clear changes with the increase of the obstacle size, while the speed only changes significantly when the obstacle size is greater than 1.5 m. For the crowd movement scenarios, a small obstacle can speed up the pedestrian flow, then, with the increase of the obstacle size, the movement time increases. The increase rate has a relation with the obstacle shape. The obstacle shape influence becomes more obvious when the individual and crowd movement scenarios are compared. The results of this paper are expected to provide practical basis for modeling pedestrian under the influence of obstacle. [ABSTRACT FROM AUTHOR]

Walking is one of the fundamental forms of human gross motor activity in which spatiotemporal movement coordination can occur. While considerable body of evidence already exists on pedestrian movement coordination while walking in pairs, little is known about gait control while walking in more complex topological arrangements. To this end, this study provides some of the first evidence of spontaneous gait synchronisation while walking in a group. Nine subjects covered the total distance of 40 km at different speeds while assembled in a three-by-three formation. Two experimental protocols were applied in which the subjects were either not specifically asked to or specifically asked to synchronise their gait. To obtain results representative from the point of view of gait control, the movement coordination was quantified using the indirectly measured vertical component of ground reaction force, based on output from a network of wireless motion monitors. Bivariate phase difference analysis was conducted using wavelet transform, synchronisation strength measures derived from Shannon entropy, and circular statistics. A fundamental relationship describing the influence of the group walking speed on individuals' pacing frequency was established, showing a positive correlation different from that previously reported for walking in solitude. A positive correlation was found between the average synchronisation strength within a group and group's walking speed. The most persistent coordination patterns were identified for pedestrians walking front-to-back and side-by-side. Overall, the spontaneous gait synchronisation while walking in a group is relatively weak, well below the levels reported for walking in pairs. [ABSTRACT FROM AUTHOR]

Heavy casualties in stampede accidents in recent years have brought new challenge to crowd management and public safety as well. Therefore, a series of controlled experiments were conducted to investigate traffic dynamics of pedestrians in this paper. The fundamental diagrams for unidirectional flow, bidirectional counter flow, bidirectional cross flow and four-directional cross flow are surveyed by using the improved Voronoi diagram measurement method. The maximum specific flow and the optimal density are obtained from the density–flow relation. Furthermore, difference of fundamental diagrams for different pedestrian flows is also discussed. Evolution of individual density and individual velocity in the Voronoi cell is explored and the dangerous area for pedestrians is identified. Movement efficiency under different densities is investigated when passing through the intersection. The study is helpful to develop a modular approach that serves as a basis for the planning and evaluation of large scale public events. • An improved Voronoi diagram method where moving back is considered as negative contribution to flow is proposed. • Fundamental diagrams for different flows under all states and steady state are discussed. • The dangerous area is identified through the individual Voronoi cell. [ABSTRACT FROM AUTHOR]

Pedestrian dynamics in emergent situations such as stampedes and fire hazards have been widely studied, while few studies are focusing on human behavior in terrorist attack events. The research is vitally important for guiding efficient evacuation of the attacked crowd and reducing casualties. However, the research is insufficient due to the lack of researching materials. Besides, it is unconvincing for researchers to carry out these types of experiments. In this paper, the recorded video of the 3 ⋅ 1 Kunming terrorist attack event in China is analyzed. The instantaneous velocity field of the attacked crowd in the ticket hall is extracted from the video material, which is based on an image processing method. By analyzing the statistical characteristics of crowd velocity, crowd movement frequency and crowd entropy, several phenomena are found including crowd oscillating phenomenon, self-organizing grouping phenomenon. These discoveries will benefit the understanding of crowd dynamic in close-range attacks which is essential for the evacuation guidance efficiency, better design of architecture layout, and better defending strategies against the terrorists. • Crowd velocity peak is oscillating back and forth within the attacked crowd. • The velocity entropy of crowd is shown oscillating around the mean value 6.7. • The characteristic frequency of crowd movement is about 0.4 Hz. • Crowd in different area who have different movement behavior patterns show grouping phenomenon. [ABSTRACT FROM AUTHOR]

Abstract Recent advances in bottleneck studies have highlighted that different architectural adjustments at the exit may reduce the probability of clogging at the exit thereby enhancing the outflow of the individuals. However, those studies are mostly limited to the controlled experiments with non-human organisms or predictions from simulation models. Complementary data with human subjects to test the model's prediction is limited in literature. This study aims to examine the effect of different geometrical layouts at the exit towards the pedestrian flow via controlled laboratory experiments with human participants. The experimental setups involve pedestrian flow through 14 different geometrical configurations that include different exit locations and obstacles near exit under normal and slow running conditions. It was found that corner exit performed better than middle exit under same obstacle condition. Further, it was observed that the effectiveness of obstacle is sensitive to its size and distance from the exit. Thus, with careful architectural adjustment within a standard escape area, a substantial increase in outflow under normal and slow running conditions could be achieved. However, it was also observed that placing the obstacle too close to the exit can reduce outflow under both normal and slow running conditions. Moreover, we could not observe "faster-is-slower" effect under slow running condition and instead noticed "faster-is-faster" effect. In addition, the power law fitted headway distribution demonstrated that any architectural configurations that enhanced the outflow have higher exponent value compared to the other configuration that negates the outflow. The findings from this paper demonstrate that there is a scope to adjust the architectural elements to optimize the maximum outflow at the egress point. Further, the output from the experiments can be used to develop and verify mathematical models intended to simulate crowd evacuation. Highlights • Careful adjustments of structural features can increase the outflow of pedestrians. • Obstacles have different performance at middle and corner exits. • Column size and distance to the exit affect the outflow of pedestrians. • "Faster-is-faster" effect is observed under slow running condition. [ABSTRACT FROM AUTHOR]

Highlights • Experimenting the dynamics of pedestrian crowds in shared space. • Investigating how movement is impacted by the physical space. • Investigating how the effect of physical space is moderated by movement speed. • Different configurations were associated with different levels of movement trajectory mixture. • Identifying the relation between space configuration and stop-and-go formation. Abstract The motion dynamics of humans in crowded built environments during evacuations are impacted by individuals' interactions with the physical environment particularly when the geometric space of the movement is restrictive. Controlled laboratory experiments have recently been employed as a reliable data provision approach in this field. Using this approach and based on data obtained from 54 experimental scenarios, this study investigates a range of questions in relation to the collective motion of pedestrian crowds in restricted shares spaces. This includes the role of the layout of the spatial constraints as well as the influence of the movement speed level in the evacuation performance of pedestrian facilities. We explored these questions particularly for dense crowds and based on both micro-scale and macro-scale measures of pedestrian traffic. Our analyses showed that traffic efficiency is demonstrably sensitive to the physical features of the merging passages as well as the desired speed level of the crowd. The patterns of influence of the geometric constraints on traffic efficiency were by and large common across all three speed regimes that we examined. Our results also showed that under specific geometric constraints, the formation of blockages (i.e., longer queue or longer time interval between the passage of two consecutive pedestrians) is more likely. An inspection of the trajectory patterns revealed that this could be attributable to the extent to which the two flows had to mix up with each other in order to be able to merge and share the space. Certain layouts, particularly symmetric layouts, allowed the two flows to keep their separate ways after the entered the shared space, whereas other setups engendered a more noticeable mixture of movement trajectories in order for the two flows to be able to travel through the shared area. The findings have applications for the design of safe passageways when dense crowd flows enter restrictive areas. [ABSTRACT FROM AUTHOR]

It is always challenging to seek external rescue assistance in high-rise building fires. Therefore, it is critical for individuals to master survival skills. For crowd dynamics modeling, previous research focused on numerical simulations and building designs with little attention to the self-rescue mechanism. It is critical to understanding crowd evacuations and better response strategies. We modeled the Grenfell Tower (a high-rise building with a complicated structure) case in 2017. Based on the percolation and social force models, we build an agent-based model to simulate individual behaviors inside. We obtain the optimal solution and robust paralleled outcomes under all counterfactual situations based on precisely matching tangible case outcomes (fire duration, deaths, and injuries). For individuals, mastering self-rescue skills is better at reducing social losses (deaths & injuries). In terms of high-rise buildings design, the central alarm system is also useful to reduce them. Besides, the crowd evacuation guided by the social force model also reduces deaths & injuries. This work provides insight into better high-rise building design and practical response strategies for societies. The central alarm system and fire-proof materials should be used in high-rise buildings. The residents should have routine training in social force-based evacuations and survival (self-rescue) skills to better the evacuation process and outcome under natural disasters and social emergencies. [ABSTRACT FROM AUTHOR]

Highlights • Large uncertainty on the situations on which the positive effect of obstacle near exit could be observed. • No established relationship between the exit width, obstacle distance and obstacle size/shape. • Verification of the model's prediction with empirical data with humans is largely unexplored. • Researchers have questioned the implementation of obstacles at bottlenecks in real life scenario. • Testing of "obstacles effects" is largely unexplored for outdoor scenarios. Abstract In a pioneering work in Nature journal, a counter-intuitive prediction that escape rates of people under panic conditions will be enhanced if an obstacle such as a column or a barrier is placed on the "upstream" side of an exit was demonstrated through a simulation model. However, the prediction lacked empirical verification. Despite the substantial works in this topic in the past decade, there is currently a lack of knowledge on how and to what extent the obstacle near an exit can enhance the pedestrian outflow at the bottlenecks during emergency escape. Therefore, the aim of this paper is to present a critical review on the performance of an obstacle near an exit and identify future research directions. It is found that although there is a general consensus on the beneficial effect of an obstacle, there is a large uncertainty on the situations on which the positive effect of obstacle could be observed. In addition, verification of the model's prediction with empirical data with humans is still largely unexplored. There is no clear established relationship between the exit width, obstacle distance and obstacle size/shape. Also, quantitative understanding of the nature of the clogging transition due to obstacle is a challenging task. Further, researchers have questioned the implementation of such obstacles at bottlenecks in real life scenario. A systematic approach of optimising architectural adjustments that enhances escape dynamics of pedestrians' crowd in indoor and outdoor public spaces needs to be conducted in future. [ABSTRACT FROM AUTHOR]

Abstract In this paper a porous flow approach on a cul de sac is proposed to understand the dynamics of crowd at ghat regions (banks of the sacred river) in mass religious gatherings. Kumbh Mela, one of the mankind's largest religious gathering encompassing almost all possible crowd scenarios, provides a unique opportunity to explore the crowd dynamics along all facets. Here, Cul-de-sac refers to the ghat region where people gather with the intention to take holy dip. The data used for this study was collected during Kumbh Mela held during 22nd April to 21st May 2016. Visual observations from the video data shows a high degree of complexity probably due to the nature of activities at the study location, e.g., lane formation, creeping behavior etc. The proposed porous flow approach divides the entire study area into pores, and it is assumed that pilgrims traverse this network through interconnected vacant pores. The pedestrian data from video sequences (entry time, exit time, and flow) is extracted manually and time series analysis of pore occupancy is done to get an approximate measure of local density. Further, using Poisson regression analysis it was found that both the inflow and the duration of holy dip are significant factors in influencing the number of arrivals into the pore. Since behavioral aspects of a pedestrian is a significant governing factor of crowd dynamics, these microscopic parameters can be used to get a measure of criticality of the system in terms of crowd risk. Highlights • Real field data was collected from Kumbh Mela, largest religious mass gathering. • A high degree of complexity was observed in the movement of crowd. • Porous flow approach is proposed to study crowd dynamics at ghat regions. • Pedestrian microscopic behavior is studied using occupancy, holy dip duration etc. [ABSTRACT FROM AUTHOR]

We introduce and analyze a class of models with nonlocal point constraints for traffic flow through bottlenecks, such as exit doors in the context of pedestrians traffic and toll gates in vehicular traffic. Constraints are defined based on data collected from non-local in space and/or in time observations of the flow. We propose a theoretical analysis and discretization framework that permits to include different data acquisition strategies; a numerical comparison is provided. Nonlocal constraint allows to model, e.g., the irrational behavior (“panic”) near the exit observed in dense crowds and the capacity drop at tollbooth in vehicular traffic. Existence and uniqueness of solutions are shown under suitable and “easy to check” assumptions on the constraint operator. A numerical scheme for the problem, based on finite volume methods, is designed, its convergence is proved and its validation is done with an explicit solution. Numerical examples show that nonlocally constrained models are able to reproduce important features in traffic flow such as self-organization. [ABSTRACT FROM AUTHOR]

• Contemporary issues in crowd safety research and practice are delineated. • The Swiss Cheese Model of Crowd Safety is introduced and its layers are explained. • Challenges of implementation and the overlook layers of this model are discussed. • A call is made to set a global Vision Zero target in crowd safety. • Avenues of furthering stakeholder collaboration in crowd safety are discussed. Crowds can be subject to intrinsic and extrinsic sources of risk, and previous records have shown that, in the absence of adequate safety measures, these sources of risk can jeopardise human lives. To mitigate these risks, we propose that implementation of multiple layers of safety measures for crowds—what we label The Swiss Cheese Model of Crowd Safety —should become the norm for crowd safety practice. Such system incorporates a multitude of safety protection layers including regulations and policymaking, planning and risk assessment, operational control, community preparedness, and incident response. The underlying premise of such model is that when one (or multiple) layer(s) of safety protection fail(s), the other layer(s) can still prevent an accident. In practice, such model requires a more effective implementation of technology, which can enable provision of real-time data, improved communication and coordination, and efficient incident response. Moreover, implementation of this model necessitates more attention to the overlooked role of public education, awareness raising, and promoting crowd safety culture at broad community levels, as one of last lines of defence against catastrophic outcomes for crowds. Widespread safety culture and awareness has the potential to empower individuals with the knowledge and skills that can prevent such outcomes or mitigate their impacts, when all other (exogenous) layers of protection (such as planning and operational control) fail. This requires safety campaigns and development of widespread educational programs. We conclude that, there is no panacea solution to the crowd safety problem, but a holistic multi-layered safety system that utilises active participation of all potential stakeholders can significantly reduce the likelihood of disastrous accidents. At a global level, we need to target a Vision Zero of Crowd Safety , i.e., set a global initiative of bringing deaths and severe injuries in crowded spaces to zero by a set year. [ABSTRACT FROM AUTHOR]

As urban public spaces attract more pedestrians, it is essential to prevent excessive pedestrian aggregation. Use of a walking behavior model is crucial to predict the distribution of pedestrian density. In earlier studies, the modeling of walking behavior generally focused on straight walking or aimless strolling. In recent years, more complex models of walking behavior, including turning behavior, have increasingly gained attention. Because the majority of models are calibrated using data gathered from experimental settings, research on the prediction of turning behavior of multi-scale walking passages in life scenarios remains in its development. The aim of this paper is to develop a turning behavior model suitable for multi-scale pedestrian passages. The expected walking direction was predicted by combining the global path planning model with a gradually changing expected direction with the local path planning model based on the attention field. Then, it was integrated with social force model to predict the pedestrian walking behavior and density distribution. Settings in the turning behavior model such as adaptively changing the expected walking direction according to the particular circumstance, approaching the inner curve upstream of the passage intersecting space, and appropriate pedestrian heterogeneity traits were found to help make predictions more accurately. The proposed turning behavior model is applicable to physical environments with different widths without recalibrating parameters and is suitable for predicting the distribution of pedestrian density in urban life scenarios with a variety of passage widths, which helps in the effective design and renovation of pedestrian space. [ABSTRACT FROM AUTHOR]

• Content analysis of witness statements of the 2010 Love Parade disaster in Duisburg, Germany. • A combination of falls (often after people had fainted) and transversal waves of the crowd are the most dangerous dynamics. • In the tightly packed crowd, fallen people create a "hole" into which more people are pushed. • Helping behavior is the most prominent behavior, but visitors also tried to get out of the crowd without regard for others. • Witnesses describe feelings of intense fear while disagreeing with the idea of mass panic. During the Love Parade disaster in 2010 in Duisburg, Germany, twenty-one visitors lost their lives and more than five hundred were injured in a very dense crowd on the route to and from the festival area. Approximately nine hundred visitors who had been among this crowd were subsequently interviewed by police officers as eyewitnesses. This paper analyzes a random sample of 136 of these witness statements, focusing on how those present perceived the crowd, how they behaved, how they experienced the event emotionally, what happened to their bodies, and which collective dynamics they described. This approach provides a perspective from within crowd dynamics which are usually observed from a top-view perspective. Almost all the attendees became strongly focused on the staircase and the pole—the only visible ways out of the crowd. In some cases, they tried to reach these destinations by all means and at the expense of others. But at the same time, helping behavior is the behavior most frequently mentioned. Although witnesses described feelings of intense fear, they reject the idea of mass panic. As the most dangerous dynamics, a combination of falls (often after people had fainted) and transversal waves (which made people fall on top of each other) could be reconstructed. When people fall in a tightly packed crowd, a hole can form which pulls in more people due to the pressure on those standing around the edge of the hole, thus creating a pile of wedged bodies. [ABSTRACT FROM AUTHOR]

This paper concerns the mathematical modeling of the motion of a crowd in a non connected bounded domain, based on kinetic and stochastic game theories. The proposed model is a mesoscopic probabilistic approach that retains features obtained from both micro- and macro-scale representations; pedestrian interactions with various obstacles being managed from a probabilistic perspective. A proof of the existence and uniqueness of the proposed mathematical model’s solution is given for large times. A numerical resolution scheme based on the splitting method is implemented and then applied to crowd evacuation in a non connected bounded domain with one rectangular obstacle. The evacuation time of the room is then calculated by our technique, according to the dimensions and position of a square-shaped obstacle, and finally compared to the time obtained by a deterministic approach by means of randomly varying some of its parameters. [ABSTRACT FROM AUTHOR]

The study of the discharge of active or self-driven matter in narrow passages has become of the growing interest in a variety of fields. The question has particularly important practical applications for the safety of pedestrian human flows notably in emergency scenarios. It has been suggested predominantly through simulation in some theoretical studies as well as through few experimentations that under certain circumstances, an elevated vigour to escape may exacerbate the outflow and cause further delay although the experimental evidence is rather mixed. The dimensions of this complex phenomenon known as the “faster-is slower” effect are of crucial importance to be understood owing to its potential practical implications for the emergency management. The contextual requirements of observing this phenomenon are yet to be identified. It is not clear whether a “do not speed up” policy is universally beneficial and advisable in an evacuation scenario. Here for the first time we experimentally examine this phenomenon in relation to the pedestrian flows at merging sections as a common geometric feature of crowd egress. Various merging angles and three different speed regimes were examined in high-density laboratory experiments. The measurements of flow interruptions and egress efficiency all indicated that the pedestrians were discharged faster when moving at elevated speed levels. We also observed clear dependencies between the discharge rate and the physical layout of the merging with certain designs clearly outperforming others. But regardless of the design, we observed faster throughput and greater avalanche sizes when we instructed pedestrians to run. Our results give the suggestion that observation of the faster-is-slower effect may necessitate certain critical conditions including passages being overly narrow relative to the size of participles (pedestrians) to create long-lasting blockages. The faster-is-slower assumption may not be universal and there may be circumstances where faster is, in fact, faster for evacuees. In the light of these findings, we suggest that it is important to identify and formulate those conditions so they can be disentangled from one another in the models. Misguided overgeneralisations may have unintended adverse ramifications for the safe evacuation management, and this highlights the need for further exploration of this phenomenon. [ABSTRACT FROM AUTHOR]

Introduction The safety of humans in crowded environments has been recognised as an important and rapidly growing research area with significant implications for urban planning, event management, building design, fire safety engineering and rescue service to name a few. This stream of research is aimed at guiding safe designs and effective evacuation plans by simulating emergency scenarios and estimating measures such as total evacuation time. A large body of research has also been dedicated to the development of modelling tools with the capability to identify (and thus prevent) circumstances that lead to crowd discomfort, crashes or disasters in mass gatherings and public facilities. It has, however, been argued that the empirical knowledge in this area has lagged behind the theoretical developments and computational capabilities. This has left the descriptive power of the existing models for reproducing the natural behaviour of humans questionable given that in many cases there is a lack of reliable and well-conditioned data for model validation or calibration purposes. Methods With the vast majority of the empirical knowledge in this fast-growing and interdisciplinary field being very recent, a survey of the existing literature is still missing. Here, we gather together the existing empirical knowledge in this area in a comprehensive review (based on surveying more than 160 studies restricted to those published in peer-reviewed journals since 1995) in order to help bridge this gap. We introduce for the first time a categorisation system of the relevant data collection techniques by recognising seven general empirical approaches. We also differentiate between various aspects of human behaviour pertinent to crowd behaviour by putting them into perspective in terms of three general levels of “decision making”. We also discuss the advantages and disadvantages offered by each data collection technique. Major gaps and poorly-explored topics in the current literature are discussed. Findings and applications Our major conclusion is that the empirical evidence in this area is largely disperse and even in some cases mixed and contradictory, requiring a more unified system of terminologies and problem definitions as well as unified measurement methods in order for the findings of different studies to become replicable and comparable. We also showed that the existing body of empirical studies display a clear imbalance in addressing various aspects of human behaviour with certain (but crucial) aspects (such as “pre-movement time” and “choice of activity”) being poorly understood (as opposed to our knowledge and amount of data about “walking behaviour” for example). Our review also revealed that previous studies have predominantly displayed a stronger tendency to study the behaviour based on aggregate measures as opposed to individual-level data collection attempts. We hope that this collection of findings sets clearer avenues for advancing the knowledge in this area, guides future experiment designs and helps researchers form better-informed hypotheses and choose most suitable data collection methods for their question in hand. [ABSTRACT FROM AUTHOR]

Data processing for Smart Cities become more challenging, facing with different handling steps: data collection from different heterogeneous sources, processing sometimes in real-time and then delivered to high level services or applications used in Smart Cities. Applications used for intelligent transportation systems, crowd management, water resources management, noise and air pollution management, require different data processing techniques. The main subject of this paper is to propose an architecture for data processing in Smart Cities. The architecture is oriented on the flow of data from the source to the end user. We describe seven steps of data processing: collection of data from heterogeneous sources, data normalization, data brokering, data storage, data analysis, data visualization and decision support systems. We consider two case studies on crowd management in smart cities and on Intelligent Transportation Systems (ITS) and we provide experimental highlights. [ABSTRACT FROM AUTHOR]

It is well known that a large percentage of occupants in a building are evacuated together with their friends, families, and officemates, especially in China. Small group behaviors are therefore critical for crowd movement. This paper aims to study the crowd dynamic considering different social relations and the impacts of small groups on crowd dynamics in emergency evacuation. Three experiments are conducted in an 11-storey office building. In the first two experiments, all participants are classmates and know each other well. They are evacuated as individuals or pairs. In the third experiment, social relations among the participants are complex. Participants consist of 8 families, 6 lovers and several individuals. Space–time features, speed characteristics and density–speed relations for each experiment are analyzed and compared. Results conclude that small group behaviors can make positive impacts on crowd dynamics when evacuees know each other and are cooperative. This conclusion is also testified by four verified experiments. In the third experiment, speeds of evacuees are lowest. Small groups form automatically with the presence of intimate social relations. Small groups in this experiment slow down the average speed of the crowd and make disturbance on the crowd flow. Small groups in this case make negative impacts on the movement of the crowd. It is because that evacuees do not know each other and they are competitive to each other. Characteristics of different types of small groups are also investigated. Experimental data can provide foundational parameters for evacuation model development and are helpful for building designers. [ABSTRACT FROM AUTHOR]

Predicting crowd dynamics in real-time may allow the design of adaptive pedestrian flow control mechanisms that prioritize attendees' safety and overall experience. Single-Input-Single-Output (SISO) AutoRegresive eXogenous (ARX) prediction models of crowd dynamics have been effectively used in Linear Model Predictive Controllers (MPC) that adaptively regulate the movement of people to avoid overcrowding. However, an open research question is whether Multiple-Input, State-space, and Nonlinear modeling approaches may improve MPC control performance through better prediction capabilities. This paper considers a simulated controlled evacuation scenario, where evacuees in a long corridor dynamically receive speed instructions to modulate congestion at the exits. We aim to investigate Multiple-Input-Single-Output (MISO) prediction models such that the inputs are the control action (speed recommendation) and pedestrian flow measurement, and the output is the local density of the pedestrian outflow. State-space and Input–output MISO models, linear and neural, are identified using a data-driven approach in which input–output datasets are generated from strategically designed microscopic evacuation simulations. Different estimation algorithms, including the subspace method, prediction error minimization, and regularized AutoRegressive eXogenous (ARX) model reduction, are evaluated and compared. Finally, to investigate the importance of measuring and modeling the pedestrian inflow, the case in which the models' structure is defined as a Single-Input-Single-Output (SISO) system has been explored, where the pedestrian inflow is considered an unmeasured input disturbance. This study has important implications for the design of more effective MPC controllers for regulating pedestrian flows. We found that the prediction error minimization algorithm performs best and that nonlinear state-space modeling does not improve prediction performance. The study suggests that modeling the inner state of the evacuation process through a state-space model positively influences predicting system dynamics. Also, modeling pedestrian inflow improves prediction performance from a predefined prediction horizon value. Overall, linear state-space models have been deemed the most suitable option in corridor-type scenarios. • Linear State-space modeling of crowd dynamics is the first choice in predicting crowd dynamics for MPC control of pedestrian flows. • Nonlinear ARX prediction models of crowd dynamics are highly dependent on the prediction horizon of the MPC controller. • Pedestrian inflow measurements provide a significant improvement in crowd dynamics predictions. [ABSTRACT FROM AUTHOR]

Previous investigations have indicated that the cascading effect or domino effect, caused by microscopic interactions and collisions between pedestrians, is the true reason for crowd turbulence and can lead to crowd disasters. In this paper, a modified social force model considering the collision dynamics was proposed to model the domino effect of physical interactions along the queue, as well as the macroscopic dynamics of crowded pedestrians in the periodic boundary corridor Compared to the original social force model, the results of the modified model, such as the accumulation of the maximum momentums and contact forces via the transmission of collisions, show more consistency with previous empirical data. Moreover, we discussed the influence of several basic factors on the domino effect within and beyond experimental scale, such as pedestrian distance, initial impulse, and queue size. Further verification was given by comparing the transmission pattern with other experiments. Finally, the modified model proves its effectiveness and benefits in modeling high-density crowds by comparing with the empirical data in Hajj. This work provided a new insight to reproduce the domino effect, and could be extended to large-scale simulation to reproduce the velocity–density fundamental diagrams. • A modified social force model was proposed to model the domino effect of physical interactions. • The simulated momentums and contact forces are consistent with previous experimental data. • The transmission pattern of the collision was statistically fitted by an exponential relation. • The fundamental diagram is aligned with the Hajj empirical data in the high-density region. [ABSTRACT FROM AUTHOR]

In groups and crowds, individuals have a propensity to replicate the actions of their immediate neighbours, often disregarding rational considerations. This phenomenon is known as herd behaviour, which has been extensively investigated in biological and economic contexts to comprehend the dynamics of fragile systems. Examples of herd behaviour scenarios include the bubble effect in the stock market, animal coordination, and individuals congregating together during emergency situations to avert peril. The understanding of the underlying causes and consequences of individual decision-making in crowd dynamics can mitigate the negative outcomes of these situations. Consequently, models are utilized to propose effective stock market controls and design emergency exits that enable swift responses to crises. This paper presents a spatial game that induces a level of herding in the population, whereby a multiplayer public good game serves as the platform for interaction among individuals. Herding behaviour arises when individuals shift from emulating the most successful strategy to copying the predominant strategy in their neighbourhood. The objective of the game is to investigate how the induced level of herding and the return on investment affect the total wealth, wealth distribution, and level of cooperation in the population. In summary, when herd behaviour is more prevalent, it leads to reduced cooperation and increased wealth inequality. Nonetheless, the outcome is contingent on the initial concentration of states in the simulation. [ABSTRACT FROM AUTHOR]

The study of crowd dynamics has provided new insights into the understanding of human collective motion. However, most previous studies treated large-scale crowds as consisting of isolated individuals, but ignored the fact that pedestrian subgroups are prevalent in reality. With the increasing advancement of computer simulations, the critical role of subgroups in crowd modeling has been gradually recognized. Here, we develop a force-based model to reproduce the walking behaviors of pedestrian subgroups, in which the quantitative laws extracted from public datasets are incorporated for controlling their spatial configurations at different non-extreme densities. Numerical simulations indicate that our model achieves the simulation of pedestrian subgroups that coincides with empirical observations, and presents better simulation performance than existing subgroup models. The presence of pedestrian subgroups has also been confirmed to have certain effects on both fundamental diagrams and lane formation. Overall, this paper contributes a valuable framework to the modeling of pedestrian subgroups for guiding relevant implementations in potential application areas. • Extract the quantitative laws of subgroup configurations from six public datasets. • Develop a model for simulating pedestrian subgroups at non-extreme densities. • Realize better simulation performance than existing subgroup models. • The effect of subgroups on fundamental diagrams is significant as density raises. • A high proportion of subgroups increases disorder and congestion in lane formation. [ABSTRACT FROM AUTHOR]

Overcrowding in mass rapid transit stations is a chronic issue affecting daily commute in Metro Manila, Philippines. As a high-capacity public transportation, the Metro Rail Transit has been operating at a level above its intended capacity of 350,000 passengers daily. Despite numerous efforts in implementing an effective crowd control scheme, it still falls short in containing the formation of crowds and long lines, thus affecting the amount of time before they can proceed to the platforms. A crowd dynamics model of commuters in one of the high-volume terminal stations, the Taft Ave station, was developed to help discover emergent behavior in crowd formation and assess infrastructure preparedness. The agent-based model uses static floor fields derived from the MRT3 live feed, and implements a number of social force models to optimize the path-finding of the commuter agents. Internal face validation, historical validation and parameter variability-sensitivity analysis were employed to validate the crowd dynamics model and assess different operational scenarios. It was determined that during peak hours, when the expected crowd inflow may reach up to 7,500 commuters, at least 11 ticket booths and 6 turnstiles should be open to have low turnaround times of commuters. For non-peak hours, at least 10 ticket booths and 5 turnstiles are needed to handle a crowd inflow reaching up to 5,000 commuters. In the current set-up, the usual number of ticket booths open in the MRT Taft Station is 11, and there are usually 6 turnstiles open. It was observed that as the crowd inside the station increases to 200-250 commuters, there is a significant increase in the increase rate of the turnaround times of the commuters, which signifies the point at which the service provided starts to degrade and when officials should start to intervene. [ABSTRACT FROM AUTHOR]

Pedestrian stampede happened more and more often during these years, such as Love Parade disaster in Germany 2010, trampling in Shanghai bund 2014 and crowd stampede in pilgrimages. Love Parade disaster 2010 stands out for well recorded videos, which are HD quality and available for researchers. There were totally seven surveillance cameras capturing the whole festival progress and the video we study is just before the disaster happened. Pedestrian motion was special and a small disturbance would lead the group to an avalanche in this kind of critical situation. Here we focus on the individual movement pattern. The trajectories of each pedestrian involved were extracted by a mean-shift algorithm. We analyzed the space–time patterns of the pedestrians involved in the Love Parade stampede by using the detrended fluctuation analysis and the coefficient of variation. Our results reveal that the pedestrians’ movement in crowd-quakes is persistent in space, globally time-clusterized but locally regular or quasi-periodic behavior. Pedestrian movement was treated as stop and go state by point process-based representation. When the threshold increases, this means that the “go” state is longer and pedestrians keep on walking in several consecutive time frames; this is difficult in crowded situations and lead to special time-clustering behavior of the sequence of “go” events. The study reveals pedestrian motion characteristics in critical situations, which will enhance the understanding of pedestrian behaviors and supply early warning features for not only Love Parade Disaster, but also other similar large events. [ABSTRACT FROM AUTHOR]

This paper explores the likely behaviours of train passengers in an emergency evacuation and examines four crucial theoretical issues on the passengers’ evacuation, including reactive vs. proactive behaviours, cooperative vs. competitive behaviours, symmetry breaking, and route/exit choice. A survey of 1134 train passengers shows that respondents are not homogeneous in their likely behaviours. Overall, they are more likely to be reactive (e.g., wait for instruction from station staff) than proactive (e.g., move to exit) in an emergency situation. We also find that people are more likely to be co-operative (e.g., helping other people) than competitive (e.g., push other passengers). Although passengers are likely to show herding or symmetry breaking behaviour (e.g., following other passengers) than symmetric behaviour (e.g., choose least crowded exit), the degree of symmetry breaking behaviour is not as high as assumed in previous mathematical models. They are also unlikely to use escalators, lifts and train tunnels in their exit/route choice during an emergency escape. In terms of demographic differences in behaviours, results from the ordered logit models demonstrate that there are significant differences in the evacuation behaviours between males and females but not among the different age groups. Besides providing valuable information for developing mathematical models intended to simulate passengers’ evacuation in a train station, our findings can assist managers of emergency response in developing appropriate strategies and training, and in designing solutions and education campaigns for effective evacuation. [ABSTRACT FROM AUTHOR]

Introduction Understanding fundamental behavioural features regulating the escape wayfinding decisions of pedestrian humans in built environments has major implications for the safety planning and the risk-analysis of crowded public facilities. In contrast to the vast interest invested in modelling the momentary responses of evacuees to their immediate surroundings (i.e. the collision-avoidance models), their global navigation behaviour is poorly understood albeit believed to be a major determinant of the accuracy of the crowd simulation models. The primary challenge arises from the scarcity of reliable data suitable for modelling purposes causing the experimental knowledge in the field lagging substantially behind the corresponding model developments. Observations derived from fully natural emergency contexts (in the form of modelling material) are rare and collecting data in realistic experimental settings poses its own major challenges. Only few experimental modelling attempts have been reported thus far in relation with this problem primarily using the stated-choice (SC) methods. Modelling based on revealed choices (RC), however, has remained absent in this context leaving the findings of the SC experiments mostly unverified. It is still unclear whether we can reliably learn from the wayfinding choices made in virtually visualised environments without the decision-makers interacting with real individuals and the physical elements of the environment as they do in the real-world settings. Furthermore, the extent to which the findings of these experiments are specific to the particular characteristics of the environment visualised in the experiments is also unclear. Methods To bridge this gap, here we report on discrete-choice estimates derived from observations of both types. Three datasets of stated exit choices (4958 observations) were collected through face-to-face interviews with pedestrians in three public places with the experiments referring to the particular geometry of the place in which the participants were interviewed. Also, 3015 disaggregate real (or more precisely, “realistic”) exit choices were extracted through individual-level video analysis of the footage of a series of novel evacuation trials that simulate pedestrians’ emergency escape. The participants competed and interacted with real individuals in an actual crowd and made actual wayfinding decisions to make the quickest possible escape. Our particular interest was investigating the sample-to-sample variations and the context-dependence of the inferred estimates. Results We observed fairly similar parameter estimate patterns emerged from all four datasets, and identified many behavioural aspects upon which all models consistently agreed regardless of their context of origin. Moreover, despite the significant differences between the parameter scales of the four models, the SC-generated models made predictions that were reasonably similar to those of the RC model as well as to those of the model derived from the combined data. Applications Our findings provide promising evidence as to the potential applicability of the SC methods in particular as well as other forms of virtual-reality decision experiments in general as a practical, flexible and ethical approach for the continuation of research and advancing the state of knowledge in this field. [ABSTRACT FROM AUTHOR]

Models of pedestrian crowd behavior in panic or emergency situations rarely have complementary empirical data to calibrate or validate the model's prediction. Till date, there is no systematic study that has attempted to conduct a quantitative comparison of emergency escape with the laboratory experimental data for the underlying differences in crowd behavior. In this paper, an attempt is made to explore the differences between experimental data on pedestrian crowd egress and emergency egress at a bottleneck and their implication for crowd safety. The laboratory experiments consist of pedestrians passing through a bottleneck of varying widths. The emergency egress data has been extracted from the publicly available rare video footage of panic escape at a shopping center during an Earthquake in China. The extracted data are then used to test a force-based crowd simulation model. It was found that there are underlying differences on the crowd egress behavior (headway distribution and flow) under emergency conditions as compared to controlled laboratory experiment. There is significant number of group exits and less lone exits in emergency egress. It was observed that the force-based model was able to replicate the normal egress as well as panic egress. It is recommended that any pedestrian crowd evacuation simulation model be tested to reproduce this fundamental headway distribution as observed in this study which includes >85% of headway as short headway (≤0.5 s) with predominately group exits (0–0.1 s headway) rather than lone exits for the bottleneck widths between 1.7 and 2.1 m. [ABSTRACT FROM AUTHOR]

A recent crowd stampede during a New Year's Eve celebration in Shanghai, China resulted in 36 fatalities and over 49 serious injuries. Many of such tragic crowd accidents around the world resulted from complex multi-direction crowd movement such as merging behavior. Although there are a few studies on merging crowd behavior, none of them have conducted a systematic analysis considering the impact of both merging angle and flow direction towards the safety of pedestrian crowd movement. In this study, a series of controlled laboratory experiments were conducted to examine the safety constraints of merging pedestrian crowd movements considering merging angle (60°, 90° and 180°) and flow direction under slow running and blocked vision condition. Then, macroscopic and microscopic properties of crowd dynamics are obtained and visualized through the analysis of pedestrian crowd trajectory data derived from video footage. It was found that merging angle had a significant influence on the fluctuations of pedestrian flows, which is important in a critical situation such as emergency evacuation. As the merging angle increased, mean velocity and mean flow at the measuring region in the exit corridors decreased, while mean density increased. A similar trend was observed for the number of weaving and overtaking conflicts, which resulted in the increase of mean headway. Further, flow direction had a significant impact on the outflow of the individuals while blocked vision had an influence on pedestrian crowd interactions and merging process. Finally, this paper discusses safety assessments on crowd merging behaviors along with some recommendations for future research. Findings from this study can assist in the development and validation of pedestrian crowd simulation models as well as organization and control of crowd events. [ABSTRACT FROM AUTHOR]

One of the critical challenges in the development of evacuation models for pedestrian crowds is the lack of complementary data under emergency conditions. Specifically, the study of evacuation behavior of students in schools has been limited in the literature. This paper analyzes school students’ emergency evacuation behavior in earthquakes using data extracted from videos of real emergency evacuation. A comparison between students’ behavior under normal conditions and under emergency circumstances is made to identify the differences. These differences are quantitatively analyzed through regression modeling. Overall, students’ behavior under normal conditions is stable as expected. The cumulative curve of the number of departures can be modeled as a linear function. Differently, students’ emergency evacuation behavior is much more chaotic. Four stages – reaction, acceleration, linearity and saturation – are identified, which form a convex cumulative curve rather than a linear one. It is also found that, under emergency circumstances, students’ reaction time increases substantially, and the mean value as well as the variance of the number of departures per second becomes much larger. However, the reaction time is comparatively lower than those observed from previous studies on adults. Moreover, we could not observe the highly competitive behavior or ‘faster is slower effect’ as predicted from previous mathematical models. These results provide useful practical knowledge towards the development of mathematical models intended to simulate the emergency evacuation behavior of students in schools. [ABSTRACT FROM AUTHOR]

This paper proposes an essay concerning the understanding of human behaviours and crisis management of crowds in extreme situations, such as evacuation through complex venues. The first part focuses on the understanding of the main features of the crowd viewed as a living, hence complex system. The main concepts are subsequently addressed, in the second part, to a critical analysis of mathematical models suitable to capture them, as far as it is possible. Then, the third part focuses on the use, toward safety problems, of a model derived by the methods of the mathematical kinetic theory and theoretical tools of evolutionary game theory. It is shown how this model can depict critical situations and how these can be managed with the aim of minimizing the risk of catastrophic events. [ABSTRACT FROM AUTHOR]

Video recording right before the Love Parade, Duisburg (Germany) crowd-quake, occurred on 24 July 2010, has been analysed in order to investigate the spatial properties of the crowd (collective case) and those of the single pedestrians in the crowd (individual case). The Grassberger–Procaccia correlation dimension, well known to be able to distinguish patterns in spatial point processes, was used. Our results for this case-study reveal that crowd and single pedestrians are characterized by different spatial behaviour: the whole crowd behaves as a quasi-homogeneous spatial point process through time, with an averaged correlation dimension of about 1.92; while the single pedestrians show a quite large variation of correlation dimensions indicating different spatial patterns, ranging from clustered to quasi-homogeneous. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid simulation-assignment modeling framework for studying crowd dynamics in large-scale pedestrian facilities. The proposed modeling framework judiciously manages the trade-off between ability to accurately capture congestion phenomena resulting from the pedestrians’ collective behavior and scalability to model large facilities. We present a novel modeling framework that integrates a dynamic simulation-assignment logic with a hybrid (two-layer or bi-resolution) representation of the facility. The top layer consists of a network representation of the facility, which enables modeling the pedestrians’ route planning decisions while performing their activities. The bottom layer consists of a high resolution Cellular Automata (CA) system for all open spaces, which enables modeling the pedestrians’ local maneuvers and movement decisions at a high level of detail. The model is applied to simulate the crowd dynamics in the ground floor of Al-Haram Al-Sharif Mosque in the City of Mecca, Saudi Arabia during the pilgrimage season. The analysis illustrates the model’s capability in accurately representing the observed congestion phenomena in the facility. [ABSTRACT FROM AUTHOR]

Architectural features such as merging corridors form an important component in floor plans of any major public infrastructure. Previous studies on documented crowd disasters have highlighted that passage restriction such as merging corridors can have negative impacts on the efficiency of evacuation process. However, limited data exists on merging process in the literature. This study aims to address this issue through empirical data collection and analysis of merging process in a controlled laboratory walking experiments. A series of experiments were conducted with different merging angles (60°, 90° and 180°) and with different desired speed (normal and slow running). The experiments indicated that pedestrians tend to reduce speeds within merging areas. With higher merging angle, there is greater reduction in speed in the merging area. Speed reduction is statistically significant with merging angles and desired speed. The speed reduction had an effect on the flow rate with reduced flow rate observed for higher merging angle. The empirical results from this study can be used to develop and test pedestrian crowd simulation models. [ABSTRACT FROM AUTHOR]

Pedestrians adjust both speed and stride length when they navigate difficult situations such as tight corners or dense crowds. They try to avoid collisions and to preserve their personal space. State-of-the-art pedestrian motion models automatically reduce speed in dense crowds simply because there is no space where the pedestrians could go. The stride length and its correct adaptation, however, are rarely considered. This leads to artefacts that impact macroscopic observation parameters such as densities in front of bottlenecks and, through this, flow. Hence modelling stride adaptation is important to increase the predictive power of pedestrian models. To achieve this we reformulate the problem as an optimisation problem on a disk around the pedestrian. Each pedestrian seeks the position that is most attractive in a sense of balanced goals between the search for targets, the need for individual space and the need to keep a distance from obstacles. The need for space is modelled according to findings from psychology defining zones around a person that, when invaded, cause unease. The result is a fully automatic adjustment that allows calibration through meaningful social parameters and that gives visually natural results with an excellent fit to measured experimental data. [ABSTRACT FROM AUTHOR]

The authors propose a new methodology for creating realistic and effective models of crowd dynamics, which takes into account the Agent-based approach combined with non-homogeneous and asynchronous Cellular Automata. The proposed methodology makes it possible to model pedestrians׳ dynamics in complex environments, like stadiums or shopping centers, and enables mimicking of the pedestrians׳ complex decision making process on different levels: strategic and tactical/operational. On the other hand, the use of the Agent-based approach makes it possible to apply different scenarios and situational contexts, namely competitive and non-competitive evacuation or free movement of pedestrians. The proposed approach was tested in large-scale test cases, namely the evacuation of the Allianz Arena football stadium in Munich and other stadiums like Wisla Krakow Stadium or GKS Tychy Stadium, as well as AGH University facilities. [ABSTRACT FROM AUTHOR]

We analyze numerically two macroscopic models of crowd dynamics: the classical Hughes model and the second order model being an extension to pedestrian motion of the Payne–Whitham vehicular traffic model. The desired direction of motion is determined by solving an eikonal equation with density dependent running cost, which results in minimization of the travel time and avoidance of congested areas. We apply a mixed finite volume-finite element method to solve the problems and present error analysis for the eikonal solver, gradient computation and the second order model yielding a first order convergence. We show that Hughes’ model is incapable of reproducing complex crowd dynamics such as stop-and-go waves and clogging at bottlenecks. Finally, using the second order model, we study numerically the evacuation of pedestrians from a room through a narrow exit. [ABSTRACT FROM AUTHOR]

The dynamics of pedestrian flows can be captured in a continuum modelling framework. However, compared to vehicular flow, this is a much more challenging task. In particular the integration of flow propagation and path choice are known to be problematic. Furthermore, pedestrian flow is characterised by different self-organised phenomena, such as the formation of dynamic lanes and diagonal stripes, which have not yet been captured in a continuum modelling framework. This contribution puts forward a novel multi-class continuum model that captures some of the key features of pedestrian flows. It considers path choice behaviour on both the strategic (pre-trip) and tactical (en-route) level. To achieve this, we present a methodology to derive a continuum model from a microscopic walker model, in this case the social forces model. In doing so, we show that the interaction term present in the social forces model introduces a local path choice component in the equilibrium velocity. Having derived the model, we analyse its properties both by means of mathematical analyses and simulation studies. This reveals the general behaviour of the model, as well as the ability of the model to reproduce self-organised structures, and phase transitions. To the best of our knowledge, this is the first continuum model that is able to reproduce these self-organised structures. [ABSTRACT FROM AUTHOR]

Highlights: [•] We test a single modelling framework to examine crowd behaviour in ants and humans. [•] The predictions of model correspond to the empirical data available for panics. [•] Obstacle near exit and homogeneity of crowd have significant effect on outflow. [•] Broader comparison of crowd behaviour among species can provide insight on crowd panic. [Copyright &y& Elsevier]

• The impact of the Covid-19 pandemic on scholarly progress in crowd science demonstrated. • Major disruptions, attributable to the pandemic, detected in crowd research productivity. • Obstacles to the progress of crowd science during the pandemic discussed. • Potential opportunities and research avenues created by the pandemic detected. • The pandemic has had a dual effect on scholarly science of pedestrians and crowds. With the issues of crowd control and physical distancing becoming central to disease prevention measures, one would expect that crowd research should become a focus of attention during the Covid-19 pandemic era. However, I will show, based on a variety of metrics, that not only has this not been the case, but also, the first two years of the pandemic have posed an undisputable setback to the development and growth of crowd science. Without intervention, this could potentially aggravate further and cause a long-lasting recession in this field. This article, in addition to documenting and highlighting this issue, aims to outline potential avenues through which crowd research can reshape itself in the era of Covid-19 pandemic, maintain its pre-pandemic momentum and even further expand the diversity of its topics. Despite significant changes that the pandemic has brought to human life, issues related to congregation and mobility of pedestrians, building fires, crowd incidents, rallying crowds and the like have not disappeared from societies and remain relevant. Moreover, the diversity of pandemic-related problems itself creates a rich ground for making novel scientific discoveries. This could provide grounds for establishing fresh dimensions in crowd dynamics research. These potential new dimensions extend to all areas of this field including numerical and experimental investigations, crowd psychology and applications of computer vision and artificial intelligence methods in crowd management. The Covid-19 pandemic may have posed challenges to crowd researchers but has also created ample potential opportunities. This is further evidenced by reviewing efforts taken thus far in pandemic-related crowd research. [ABSTRACT FROM AUTHOR]

Highlights: [•] Effects of escape area layout in panic escape is examined through ants experiment. [•] Adjustments of layout resulted more than 90% reduction in evacuation time. [•] The results were consistent when scaled up and simulated for humans crowd scenario. [•] This can have implications for developing design solutions for crowd safety. [ABSTRACT FROM AUTHOR]

Highlights: [•] The influence of standing/waiting pedestrians on pedestrian dynamics is investigated empirically and by simulation. [•] We propose a waiting zone model for microscopic simulation of pedestrian dynamics. [•] The model is calibrated and tested using data from video recordings and field experiments. [•] Applying the proposed model adds value to the realism of pedestrian simulations. [•] The model can be applied for analysis and prediction of critical situations. [ABSTRACT FROM AUTHOR]