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With public safety receiving widespread attention from society, the question of how to effectively evacuate crowds has become a key issue. Leaders can provide pedestrians with clear and accurate route information and play an important role in daily crowd management and emergency safety evacuation. In this study, an evacuation model with static guidance considering the leader's influence and the pedestrians' decision-making behavior is proposed. The model is validated using experimental data, including evacuation behavior, evacuation time, and the percentage of the cumulative number of evacuees over time, and the simulation results match the experimental results well. Then, the model is applied to investigate the effect of different locations, numbers of static leaders, and different pedestrian distributions on evacuation efficiency in a room with unavailable exits. The results show that a leader located in the center of each potential exit can improve the overall evacuation efficiency, and the farther the guided pedestrian was from the correct exit, the better the overall evacuation performance of pedestrians. The distance parameter of multiple leaders is defined, and an optimal number of leaders exists in each specific scenario due to the overlap of leaders' influencing areas. Furthermore, whether the pedestrians are uniformly or non-uniformly distributed, the evacuation time is shorter when the guided pedestrians are located farther from the correct exit. These findings can provide suggestions for crowd management and the arrangement of leaders in emergency evacuations. [ABSTRACT FROM AUTHOR]

After a fire breaks out, pedestrians simultaneously move towards the exit and quickly form a crowded area near the exit. With the intensification of pedestrians' tendencies towards unfair competition, there is an increase in pushing and collisions within the crowd. The possibility of stampedes within the crowd also gradually increases. Analyzing the causes and psychological tendencies behind pedestrian pushing and collisions has a positive effect on reducing crowd instability and improving evacuation efficiency. This research proposes a modified social force model considering the unfair competition tendency of pedestrians. The model considers factors such as the gap between pedestrians' actual and maximum achievable speed, effective radius, and their distance from the exit. In order to overcome the shortage of "deadlock" in the classical social force model in a high-density environment, this research introduces the feature of variable pedestrian effective radius. The effective radius of pedestrians dynamically changes according to the density of the surrounding crowd and queuing time. Through validation, the evacuation efficiency of this model aligns well with the actual situation and effectively reflects pedestrians' pushing and squeezing behaviors in high-density environments. This research also analyzes how to strategically arrange obstacles to mitigate the exacerbating effect of unfair pedestrian competition on exit congestion. Five experiments were conducted to analyze how the relative position of obstacles and exits, the number of evacuation paths, and the size of the obstacle-free area before the exit affect evacuation efficiency in the presence of unfair pedestrian competition. The results show that evacuation efficiency can be improved when obstacles play a role in guiding or reducing the interaction of pedestrians in different queues. However, when obstacles hinder pedestrians, the evacuation efficiency is reduced to a certain extent. [ABSTRACT FROM AUTHOR]

To decrease liquid ammonia leakage-induced casualties of ammonia chemical enterprises, a simulation comparison method of liquid ammonia toxicity leakage and crowd evacuation was proposed, a spatial model was constructed with Pyrosim software, using 8 liquid ammonia tanks as a layout example. The ammonia diffusion path under eight leakage scenes was analysed with FDS software by setting eight ammonia leakage points. The personnel evacuation model was built with the Pathfinder software, obtaining the crowd evacuation time under the eight scenes. Finally, the optimal site for liquid ammonia tanks in this case was determined through a comparison of ammonia diffusion path and evacuation time. Results show that among the eight candidate sites for ammonia tanks, the Leakage Scene 4 shows the longest time (78 s) for diffusion to the two evacuation exits, which is longer than the crowd emergency evacuation time (73 s) in the scene. Therefore, the Leakage Scene 4 can be used for the setting of liquid ammonia tanks. The obtained conclusions provide a safe suggestion for the scientific planning of the liquid ammonia storage sites of chemical enterprises. [ABSTRACT FROM AUTHOR]

Deep reinforcement learning (DRL) is suitable for solving complex path-planning problems due to its excellent ability to make continuous decisions in a complex environment. However, the increase in the population size in the crowd evacuation path-planning problem causes a substantial computational burden for the algorithm, which leads to an unsatisfactory efficiency of the current DRL algorithm. This paper presents a path planning method based on DRL for crowd evacuation to solve the problem. First, we divide crowds into groups based on their relationship and distance from each other and select leaders from them. Next, we expand the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) to propose an Optimized Multi-Agent Deep Deterministic Policy Gradient (OMADDPG) algorithm to obtain the global evacuation path. The OMADDPG algorithm uses the Cross-Entropy Method (CEM) to optimize policy and improve the neural network's training efficiency by applying the Data Pruning (DP) algorithm. In addition, the social force model is improved, incorporating the relationship between individuals and psychological factors into the model. Finally, this paper combines the improved social force model and the OMADDPG algorithm. The OMADDPG algorithm transmits the path information to the leaders. Pedestrians in the environment are driven by the improved social force model to follow the leaders to complete the evacuation simulation. The method can use a leader to guide pedestrians safely arrive the exit and reduce evacuation time in different environments. The simulation results prove the efficiency of the path planning method. [ABSTRACT FROM AUTHOR]

Efficient crowd evacuation from railway platforms is critical for passenger safety during emergencies. This study introduces a novel dynamic emergency evacuation route generator using the Proximal Policy Optimization (PPO) algorithm within a custom-built 3D simulation environment developed in Unity. We independently created a detailed digital twin of Krung Thep Aphiwat Central Terminal, Thailand’s largest train station, and implemented all elements of the simulation, including the Social Force Model, to accurately replicate crowd behaviors and interactions during evacuation scenarios. Through extensive training over 3,000,000 episodes, our PPO-based model achieved significant improvements in evacuation efficiency. The results indicate that in a major emergency scenario, increasing the number of agents in the station reduced the number of remaining passengers from 111 to just 6, highlighting the model’s effectiveness. Similarly, in a minor emergency scenario, the average number of remaining passengers dropped from 38 to 1 with the addition of more agents. These findings confirm the model’s ability to adapt to different emergency conditions, offering a practical and scalable solution for enhancing evacuation strategies in high-density environments. Furthermore, increasing the agents’ sight range also improved evacuation efficiency, with a 20-meter sight range yielding the best results.

To avoid crowd evacuation simulations depending on 2D environments and real data, we propose a framework for crowd evacuation modeling and simulation by applying deep reinforcement learning (DRL) and 3D physical environments (3DPEs). In 3DPEs, we construct simulation scenarios from the aspects of geometry, semantics and physics, which include the environment, the agents and their interactions, and provide training samples for DRL. In DRL, we design a double branch feature extraction combined actor and critic network as the DRL policy and value function and use a clipped surrogate objective with polynomial decay to update the policy. With a unified configuration, we conduct evacuation simulations. In scenarios with one exit, we reproduce and verify the bottleneck effect of congested crowds and explore the impact of exit width and agent characteristics (number, mass and height) on evacuation. In scenarios with two exits and a uniform (nonuniform) distribution of agents, we explore the impact of exit characteristics (width and relative position) and agent characteristics (height, initial location and distribution) on agent exit selection and evacuation. Overall, interactive 3DPEs and unified DRL enable agents to adapt to different evacuation scenarios to simulate crowd evacuation and explore the laws of crowd evacuation.

Copyright of Journal of Southeast University (English Edition) is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We propose an enhanced floor field model (FFM) to analyze the behavioral characteristics of crowds with varying attributes proportions during evacuation. This model governs pedestrian movement through the Dynamic Floor Field (DFF) and the Static Floor Field (SFF). The DFF takes into account individual factors such as the gender, familiarity with the environment, and social relationships of evacuees, which influence safe evacuation. Concurrently, the SFF encapsulates the impact of environmental factors like obstacles, exits, and guidance effects. Subsequently, this refined FFM was applied and validated using a sports center evacuation scenario. The results demonstrated that the enhanced FFM accurately replicated evacuees' asymmetric behavior and queuing, and aligned well with other models when the number of evacuees fluctuated over time. In the absence of guidance, both environmental familiarity and gender emerged as primary factors influencing partial evacuation. Additionally, the gender of pedestrians significantly affected the overall evacuation. Notably, compared to pre-existing environmental information available to evacuees, the implementation of guidance to augment pedestrians' environmental familiarity resulted in a more efficient evacuation. The FFM model and these findings could be instrumental in simulating personnel evacuation and formulating emergency management strategies in crowded areas.

Guidance signs are generally considered to be key in improving the efficiency of emergency building evacuations. During a group evacuation, how obedient is the group to the evacuation signs? Would different evacuation signs affect the judgment of evacuated groups? Evacuation experiments were conducted to explore the influence of evacuation signs on the path selection of evacuation groups. Fourteen classes with 514 participants participated in these experiments, and each class participated in one experiment. Six classes conducted the experiments without guidance signs, and the rest conducted the experiments with guidance signs. The influences of the sign's color (red and green), pattern (arrow and running man), and status (whether it flashes) on the route selection were studied. The results show that (1) the evacuation signs significantly affect the route choices of the evacuated groups. (2) The herding effect during the evacuation process does not influence the guiding effect of evacuation signs. (3) Evacuation signs of different colors and patterns have different guiding effects, and the Green running man sign has the best effect. (4) The constant bright, or flashing evacuation sign corresponding to the flashing Red running man has a significant impact on the route selection of the evacuated group. The results may provide a reference for improving the emergency evacuation guidance model of office buildings or other buildings with a large flow of people and optimize ideas for the design and layout of emergency evacuation signs.

Most existing crowd evacuation methods focus on internal factors and do not consider the influence of the external environment factors, producing unrealistic global behavior occurs when individuals are moving through the crowded space. As an essential part of a building, safety indication signs (SISs) are a form of environmental information and perceptual access that play an important role in promoting wayfinding by virtue of their guiding role in movement direction and route selection by providing guidance, warning and mandatory message to people. In this paper, we propose an innovative crowd simulation method guided by SISs with reinforcement learning strategy for use in emergencies. To illustratethe guiding function of the SISs, we establish a guidance field for each SIS and add the attractive force to the guidance field. Besides, we formulate the multi-agent (crowd) navigation problem as an action-selection problem and design a novel reinforcement learning strategy for driving individuals to accomplish collision-free movement more efficiently. Particularly, we define a state transition strategy between the SIS area and the non-SIS area to achieve continuity of guidance. We use extensive simulations to highlight the potential of our method in different scenarios and evaluate the results in terms of evacuation efficiency and the reasonableness of SIS placement. In practice, our system runs at interactive rates and can solve complex planning problems involving one or more groups. [ABSTRACT FROM AUTHOR]

A kinetic modeling of crowd evacuation with leaders and followers is considered in this paper, in which the followers may not know the full information about the walking environment and the evacuation strategy, but they follow the leaders and learn the walking strategy to get out of the walking venue. Based on the kinetic theory of active particles, the learning dynamics are considered by introducing an activity variable u , which represents the learning level of the followers and measures how much knowledge a follower has learned about the walking strategy, the walking environment, or the geometry of the walking venue. Several fundamental factors are considered in this leader–follower learning system of crowd evacuation, including: (1) the rational motion of all pedestrians, i.e. the trend to the exit or to a preferred direction, the ability to avoid collisions with walls or obstacles, and the tendency to search for less crowded direction with minimal density gradient, (2) the irrational motion of followers to follow other pedestrians induced by panic, (3) the learning dynamics of the followers who learn the walking strategy during interaction with others, and, (4) the transition from a follower to a leader when one's activity reaches the highest level of learning. A numerical comparison of a metro platform evacuation with and without learning shows a reasonably good predictive ability of the model that the learning effect plays a significant role in the evacuation dynamics. [ABSTRACT FROM AUTHOR]

Emergency signs play an important role in evacuation guidance, and some works show that the behavior of the crowd in the process of evacuation is easily affected by emotion and personality. However, existing crowd simulation methods rarely involve the interaction between emotion and emergency signs. Thus, a crowd evacuation simulation method considering emotion and emergency signs is proposed to simulate the crowd evacuation behavior under the guidance with signs, and it is verified by simulation experiments through Unity3D. The method provides a novel research perspective for guided crowd evacuation simulation, and it can make simulation results more real to the actual scenes. [ABSTRACT FROM AUTHOR]

• The fire risk model is established. • The Dynamic Avoid Smoking A-Star (DASA-Star) algorithm is constructed. • The evacuation path planning of subway station fire environment is simulated. • The algorithm simulation verifies the effectiveness of DASA-Star algorithm. Considerable casualties can easily be caused once a fire occurs in a metro station, and a safe and effective evacuation path in time should be provided, taking on critical significance in the rapid evacuation of the crowd. In existing research, crowd evacuation paths have been generally planned without considering the fire environment and the real-time effect of fire products on the evacuation paths, such that the planned paths do not fit the realistic environment of crowd evacuation. An algorithm is proposed in this study to dynamically plan evacuation paths in fire scenarios in metro stations. First, the equivalent length of the path under the effect of fire on evacuation speed is determined in accordance with the effects of ambient temperature, visibility, and CO concentration, and then the fire risk model is built. Second, the fire risk model is incorporated into the A-Star algorithm, and the evaluation function of the A-Star algorithm is optimized, such that the determined path is capable of avoiding areas with higher fire risk. Subsequently, a dynamic update mechanism considering time factor is introduced to update the search environment information data of the algorithm in real time for dynamic path planning, with the aim of coping with the dynamically changing fire environment. Lastly, the A-Star algorithm is optimized, and the Dynamic Avoid-Smoke A-Star (DASA-Star) algorithm is built. As indicated by the simulation results, the DASA-Star algorithm is capable of making a trade-off between the fire risk and geometric length of the path in an underground station fire scenario and achieving dynamic planning of evacuation paths based on FDS fire simulation results. Accordingly, the algorithm conforms to the real-time requirements of path planning under fire conditions, and it is capable of more effectively planning the optimal evacuation path under the effect of fire. [ABSTRACT FROM AUTHOR]

Social force model is a classic model in crowd movement simulation.The model expresses the subjective wishes of pedestrians and the interaction between pedestrians in the form of “force”.The model is concise and easy to explain.However,there are many factors that affect pedestrian movement,and the calculation of self-driving force and social psychological force in the primitive social force model is insufficient.In order to enable the model to simulate the real movement process,many researchers have improved the social force model.This paper mainly studies the subject in the process of crowd evacuation,pedestrians.Pedestrians are modeled from two aspects:pedestrian characteristics and pedestrian roles.The characteristics of pedestrians include the social relationship between pedestrians,the personality of pedestrians and individual emotions.The degree of interference between pedestrians with different levels of intimacy is different,and pedestrian emotions will also affect the judgment of pedes-trians.The role of pedestrians considers leaders and ordinary pedestrians,and analyzes the impact of different pedestrian roles on the evacuation process.Leaders can help ordinary pedestrians to evacuate.Crowd self-organization simulation experiments verifies that the improved model can simulate the real crowd evacuation situation and retain the advantages of the original model.At the same time,the evacuation efficiency and exit utilization rate of the crowd under four simulation models are counted,and the average value and distribution of the experimental data are analyzed.Experimental results show that the main reasons for the long evacuation time are the time-consuming search for exits and the unbalanced utilization rate of exits.Generally,pedestrian characteristics and leaders have a positive impact on pedestrian evacuation efficiency.Pedestrian characteristics can accelerate pedestrian aggregation and optimize pedestrian expectation speed.On the basis of helping pedestrians to find exits,leaders can balance pedestrian’s use of exits,and ensure that thenumber of evacuees at each exit is basically the same.

How do students apply systems thinking to make sense of a computational model of crowd evacuation? We developed a participatory simulation in which users play the role of evacuees that move through a narrow passageway. This simulation demonstrates that when exceeding a certain speed, moving through narrow bottlenecks, is more likely to create clogs, leading to a slower passing rate. The participatory simulation was introduced in a lesson about school evacuation in a group of 9th graders. Their explanations of crowd evacuation, were compared to a similar group of 9th graders who learned the same ideas in a lecture without using the simulation. We found that using the simulation did not improve students’ system thinking about crowd evacuation compared to lecture-based instruction. About 80% of the students in both groups suggested partial/incomplete explanations of the inverse relationship between the desire to move faster as individuals and the opposite consequence of slower evacuation. Interviews with students revealed that some of them perceived the simulation scenario to be different from the organized and coordinated evacuation drills that they partook. Others, were engrossed in their own experiences as evacuees, that obscured their ability to relate the motion of individual evacuees and the overall evacuation rate of the crowd. In a second study, we examined whether prior learning of a different emergent process (spread of a disease) with a computational model, can prepare students for learning the counterintuitive phenomenon of crowd evacuation. We found that introducing a participatory simulation of the spread of a disease in a different group of 9th graders, increased their appreciation of the evacuation simulation as a learning tool, and consequently–their explanations. We conclude that computational models have the potential to enhance systems thinking, but their affordances depend on prior preparation for learning with other complex systems models.

In order to cope with limited land availability and the increasing urban population, more high-rise buildings are being built throughout cities, but this has also led to new challenges in the emergency evacuation of people. Therefore, we conducted an evacuation experiment of a group of people in the stairwells of high-rise buildings to explore the movement law of groups in stairwells. The experiment had 18 scenes, including the evacuation movement of an independent group and the crowd evacuation movement of different groups. Analyzing the independent groups' movement showed that regardless of the type of group, the average speed of the crowd was more than 1.2 m/s, which was longer than that of previous studies. The more constraints in the evacuation process, the smaller the speed difference between males and females. Group cohesion was mostly concentrated at about 1 s. Moreover, group velocity and cohesion were found to have no significant correlation in stairwell movement. Analyzing the crowd evacuation time of eight different scenes showed that it took longer for crowds bearing weight to evacuate than those not bearing weight. According to the spatiotemporal evolution of crowd evacuation in stairwells, the crowd moves intermittently in the evacuation process, especially in the early and middle stages of evacuation, and the influence of group factors on this process was not obvious. Regardless of the kind of scene or stairwell, the number of pedestrians generally first increased and then decreased to a significantly low value, and the number of pedestrians reached about 30 in the scenario of people without any load. Additionally, the speed of the pedestrians entering the stairwell in the back of the group was not faster than that of the pedestrians in the front, which showed that pedestrians rarely engaged in overtaking behavior. The research results of this paper not only enrich evacuation research but also provide support for the design of high-rise stairs. [ABSTRACT FROM AUTHOR]

To avoid crowd evacuation simulations depending on 2D environments and real data, we propose a framework for crowd evacuation modeling and simulation by applying deep reinforcement learning (DRL) and 3D physical environments (3DPEs). In 3DPEs, we construct simulation scenarios from the aspects of geometry, semantics and physics, which include the environment, the agents and their interactions, and provide training samples for DRL. In DRL, we design a double branch feature extraction combined actor and critic network as the DRL policy and value function and use a clipped surrogate objective with polynomial decay to update the policy. With a unified configuration, we conduct evacuation simulations. In scenarios with one exit, we reproduce and verify the bottleneck effect of congested crowds and explore the impact of exit width and agent characteristics (number, mass and height) on evacuation. In scenarios with two exits and a uniform (nonuniform) distribution of agents, we explore the impact of exit characteristics (width and relative position) and agent characteristics (height, initial location and distribution) on agent exit selection and evacuation. Overall, interactive 3DPEs and unified DRL enable agents to adapt to different evacuation scenarios to simulate crowd evacuation and explore the laws of crowd evacuation. [ABSTRACT FROM AUTHOR]

Human crowds have become hotspot research, particularly in crowd analysis to ensure human safety. Adaptations of machine learning (ML) approaches, especially deep learning, play a vital role in the applications of evacuation, detection, and prediction pertaining to crowd analysis. Further development in the analysis of crowd is needed to understand human behaviors due to the fast growth of crowd in urban megacities. This article presents a comprehensive review of crowd analysis ML-based systems, where it is categorized with respect to its purposes, viz. crowd evacuation that provides efficient evacuation routes, abnormality detection that could detect the occurrence of any irregular movement or behavior, and crowd prediction that could foresee the occurrence of any possible disasters or predict pedestrian trajectory. Moreover, this article reviews the applied techniques of machine learning with a brief discussion on the used software and simulation platforms. This work also classifies crowd evacuation into data-driven methods and goal-driven learning methods that have attracted significant attention due to their potential to adopt virtual agents with learning capabilities. This review finds that convolutional neural networks and recurrent neural networks have shown superiority in abnormality detection and prediction, whereas deep reinforcement learning has shown potential performance in the development of human level capacities of reasoning. These three methods contribute to the modeling and understanding of pedestrian behavior and will enhance further development in crowd analysis to ensure human safety. [ABSTRACT FROM AUTHOR]

In this paper, the crowd evacuation experiments with 180 participants were conducted to study the effectiveness of sound-guiding and light-guiding in a 1:1 full-scale experimental tunnel. The participants were divided into 9 groups, with 20 participants in each group, each of which included different experimental scenarios of sound-guiding and light-guiding. The experimental results of evacuation speed showed that sound-guiding and light-guiding were both beneficial to improve evacuation efficiency. It is shown that the scenarios with the combination of unilateral lamp strip and outline lamps with non-flashing state had a better effect on improving the evacuation speed. As for exit selection, the results showed that the outline lamps is conducive to improving the identification of the exit, and when the outlet lamps is turned on at the same time as the lamp strips, the identification of the exit is higher. According to the comprehensive experimental results, the induction effect of exit outline lamps and unilateral lamp strip is the best, which has the most obvious effect on increasing the identification of exit and increasing evacuation speed. Furthermore, when the guiding pattern has a guiding effect on individuals, this effect will be transmitted in the crowd due to the following behavior of others, and then affect the evacuation behavior of the crowd. [ABSTRACT FROM AUTHOR]

This work deals with the optimal design for the location of the exit doors at meeting places (such as sports centers, public squares, street markets, transport stations, etc.) to guarantee a safer emergency evacuation in events of a sporting, social, entertainment or religious type. This problem is stated as an optimal control problem of nonlinear partial differential equations, where the state system is a reformulation of the Hughes model (coupling the eikonal equation for a density-weighted walking velocity of pedestrians and the continuity equation for conservation of the pedestrian density), the control is the location of the exit doors at the domain boundary (subject to several geometric constraints), and the cost function is related to the evacuation rate. We provide a full numerical algorithm for solving the problem (a finite element technique for the discretization and a gradient-free procedure for the optimization), and show several numerical results for a realistic case. [ABSTRACT FROM AUTHOR]

For safety planning in crowd evacuation, it is important to predict the evacuation decisions made by different individuals and understand the reasons behind these decisions. To this end, this paper proposes an automated approach that can learn prioritized fuzzy decision rules from crowd data to predict and understand the evacuation decisions of a real human. A coevolutionary fuzzy rule miner based on genetic fuzzy-system is designed to select necessary decision features from available ones and learn both rule structure and associated rule parameters from training data. The learned fuzzy rule contains multiple sub-rules, each of which can represent evacuation strategies of different individuals in a given scenario and the features in the fuzzy condition of the sub-rule are organized and evaluated in a sequential order to reflect the priorities of different features. Based on training and testing on four evacuations scenarios of two real-world datasets, it is shown that our proposed approach can learn decision rules that are competitive to the existing evacuation decision models in terms of prediction accuracy. More importantly, it is also demonstrated that our learned rules complying with the proposed prioritized fuzzy rule representation can facilitate the interpretation of evacuation behaviors, such as “herding under zero visibility of exit” and “diminished importance on the distance to exit”, which are aligned to the field observations from real crowd evacuation. [ABSTRACT FROM AUTHOR]

With the increasing scale of crowds in public places, the study of modeling crowd evacuation has become a significant research field. However, most previous research ignores to incorporate behavioral heterogeneity of individuals into the modeling framework, making it hard to replicate more realistic evacuation processes. Therefore, a behavioral heterogeneity-based social force model (BHSFM) is proposed to reveal the heterogeneity characteristics from the aspect of individual behavior. Numerical experiments show that the BHSFM provides a general mathematical framework for describing behavioral heterogeneity and forms a more reasonable and elaborate evacuation process. Notably, some interesting evacuation phenomena can emerge by integrating the behavioral heterogeneity coefficient with temporal-spatial dynamic risk indexes. Compared with the social force model (SFM), higher frequencies of small-scale displacements are performed by BHSFM due to more pushing behaviors. Furthermore, the periods and areas of a potential crowd disaster are revealed by our model under different numbers of pedestrians, which has important guiding significance for formulating reasonable evacuation schemes in specific scenarios. [ABSTRACT FROM AUTHOR]

• A FFCA model considering the stampede accidents on inclined staircases is proposed. • Stampede phenomena are based on crowd forces, slopes, and derived probabilities. • The arching, clogging and pedestrian domino effect were observed and analyzed. • The effects of unbalance and stampede of pedestrians on evacuation was revealed. • Certain supplements are made to the research in existing stampede incidents. An extended floor field cellular automata (FFCA) model considering the stampede accidents on inclined staircases is proposed to study shoving behavior and pedestrian dynamics. In this model, two stampede evolution pathways are investigated: Pedestrians falling after losing balance, and falling directly due to being crowded. The results show that this model could trigger some characteristics of real irrational evacuation processes, such as: (1) the mutual crowding and shoving among pedestrians; (2) the unbalance phenomenon on inclined staircases; (3) the effect of pedestrians falling like dominoes, which is consistent with the findings of most stampede investigations to some extent. The proposed model considers the impact of fallen pedestrians on the movement of ordinary pedestrians, which shows a reduction in the overall evacuation efficiency. Moreover, the steeper the slope, the greater the risk and severity of injuries during the crowded evacuation in this scenario. Additionally, falling phenomena of pedestrians show a certain lag related to the state of unbalance. Unbalanced pedestrians tend to appear from the rear to the front successively, and fallings often occur some time later the onset of unbalance, progressing from front to rear. This pattern reflects the "domino effect" among pedestrians. Lastly, unbalanced pedestrians constitute a significant portion of the total injured pedestrians. Considering the time delay of fallings after being unbalanced, the importance of early emergency response and intervention during crowded evacuations is emphasized. It is expected to provide some theoretical support for safety management. [ABSTRACT FROM AUTHOR]

The evacuation of human crowds consisting of several groups in complex venues is studied, in this paper, by the kinetic theory of active particles. We consider a complex venue that consists of several chambers which are separated by interior walls and doors, for which the geometrical effects may come from the walls both on the boundary and inside the domain, the exits, and the doors connecting the chambers. The geometrical properties are incorporated in the geometrical preferred direction, which is specified such that an individual can avoid the wall and approach the exit through the evacuation vector. The notion of group is corresponding to the concept of functional subsystem in the mathematical theory of active particles. In the present framework of several groups, the rules of interactions can be specified for both the interactions among the same group and the interactions between different groups. Furthermore, the motility is assigned for each group, which serves as the average activity of a group. Some interesting features and phenomena are shown in the numerical tests of the evacuation of a crowd with one, two or three groups. [ABSTRACT FROM AUTHOR]

During an earthquake, interior nonstructural components of a building will be damaged. The damaged objects will obstruct pedestrians' evacuation routes and increase casualties. But this issue has received scant attention in evacuation simulation research. This paper focuses on this issue and proposes an indoor seismic evacuation model to simulate crowd evacuation in a dynamic environment. A physical model of nonstructural components is presented to simulate the dynamics of the indoor scenario. The flow field algorithm is constructed to guide pedestrian's avoidance behaviors globally to reflect the impact of environmental changes on indoor crowd path selection, and a modified social force model is built to simulate the joint influence of seismic forces and the environment on pedestrian motion states. The results of the experiments shows that the proposed model can generate realistic evacuation scene and rational evacuation routes in the earthquake. [ABSTRACT FROM AUTHOR]

Emergency crowd evacuation, especially in congested indoor scenes, is an important issue in public areas' daily management. Computer simulation is a widely adopted technique to study crowd evacuations and help design reasonable emergence plans due to its flexibility, convenience, and cost-effectiveness. In this paper, we propose ECEM, a novel evacuation model based on agent simulation. In ECEM, we consider a special individual behavior in the evacuation, called seeking behavior, which happens when relatives or friends (i.e., social groups) are in the crowd, and the members within a group may tend to seek each other once separated instead of evacuating alone. Moreover, we incorporate the crowd chaos based on Boltzmann entropy (i.e., crowd entropy) into ECEM to measure the evacuating population's disorder level and present an adaptive velocity smoothing method using crowd entropy for updating individual's velocity. Extensive simulation results demonstrate the effectiveness of ECEM and provide several insights on designing the evacuation strategies.

Building exit has always been an emphasis of research in the field of evacuation. Existing studies on crowd flow characteristics at building evacuation bottlenecks usually focus on plane exit, but insufficient attention has been paid to the characteristics of crowd flow at the convex exit. Convex exit can be considered as such a structure like a double-bottleneck linked passage. This paper aims to study the influence of geometric structure characteristics of the convex exit on crowd evacuation and put forward the optimal design strategy of this structure, so as to improve the efficiency of evacuation in an emergency. Using social force model-based software, MassMotion, it is found that convex exit is indeed more efficient and safer than common plane exit in terms of evacuation time and pedestrians' congestion, especially when the desired speed is relatively higher, indicating that convex exits are more suitable for crowd evacuation in case of emergency. Four size-related parameters of convex exit are analyzed in detail, namely the width of the bottleneck at passage (Wp), the passage width (W), the passage length (L), and the exit width (We), to find out the optimum design of convex exit. The research shows that the optimal size ratio is that Wp:W:L:We equals 1.5:1.75:3.5:1, and as the overall magnification of building size and the number of pedestrians increases, the evacuation time gradually tends to a stable value, which indicates that this optimal ratio has good adaptability in size effect. Finally, based on the in-depth mechanism of pedestrian flow at the convex exit, three possible application scenarios are proposed to illustrate the feasible optimum design of the convex exit. The results of this study can provide new ideas for research on the structure of building exits. [ABSTRACT FROM AUTHOR]

In dense crowd evacuation, especially in emergencies such as fires, the safe evacuation of large public facilities will face major challenges. At the same time, as cluster congestion tends to occur in the space where the flow rate drops sharply, the superposition of fire incidents and bottleneck areas can easily evolve into malignant disasters and crowd stampedes with serious harm and influence. In this paper, Massmotion based on social force model is used to carry out a numerical simulation on exit position and corner exit form to find out the mechanism and influence law of the slight architectural adjustment on the flow at bottleneck. The results show that the traditional middle exit design is not the best, and the evacuation efficiency of the corner exit is higher than that of the middle exit. Compared with other corner exits, the average time interval between two adjacent persons passing through the bottleneck under the 30° corner exit is the shortest, and the probability of outlet clogging drops the fastest, exceeding 18% of the slowest descending speed. At the 0° corner exit, the waiting time cost of pedestrians is high and the risk of evacuation is high. The outcomes of this work can provide reference for the structural design of the building and the safe evacuation of personnel, so as to improve the evacuation efficiency and safety of pedestrians in the building to some extent. [ABSTRACT FROM AUTHOR]

SUMMARY Many models have been developed in recent years to describe pedestrian group behavior. Most prior research on group behavior focuses mainly on small groups and does not provide a general approach for grouping pedestrians with respect to different group sizes. They also analyze pedestrian group dynamics in normal circumstances. However, people's reactions who are aware of an emergency are not the same as how they respond to normal or usual situations. The central focus of this paper is to study pedestrian group behavior during evacuation. To accomplish these objectives, a new model is proposed with some extensions of a social force model in its emergency context. The new extensions are intended to simulate the single leader‐centered and group‐centered crowd behavior in emergencies. Besides small pedestrian groups, larger ones are also considered, and extensions are added in this direction. The model is calibrated using the results of an existing experimental study. Then, the model is verified by testing for the occurrence of certain emergent patterns. The results indicate that the proposed model can capture these trends. Additionally, the model is validated by comparing the simulation results with experimental results available in the literature. Also, several different evacuation scenarios are used to evaluate the proposed model. The simulation results show that leader‐centered behavior performs better than group‐centered behavior with respect to the evacuation time for small groups. The number of leaders also affects the evacuation time. Moreover, an increase in the number of leaders positively influences the effect of the width of the door on evacuation time, but the size of this effect depends on the number of leaders. Finally, group‐centered behavior results in less evacuation time than leader‐centered behavior in the presence of multiple exits, and leader‐centered (also called single leader‐centered in this study) behavior causes a more unbalanced use of the exits than group‐centered behavior. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A new crowd evacuation model is established to solve the stagnation problem of traditional social force models in a complex and dense scene. In the proposed model the acting forces between pedestrians, and between pedestrians and obstacles in the traditional social force model, are improved to find out the relationship in the two cases which are within the influence range and are not intersected, and those which are intersected and not greater than the maximum degree of squeezing, and to solve it for parameter optimization. The simulation platform built is used to compare the performance of the traditional social force model and the improved model, and to deeply analyze the relationship between the evacuation time and the degree of squeezing. The results show that as the evacuation time increases, the crowd in the emergency exit area is getting denser, the optimized model is distributed more evenly, and the probability of squeezing is lower. The optimized model has better stability in terms of the ability to control the intersection without exceeding the maximum degree of squeezing. Due to less squeezing, the optimized model can reduce the time of passing through the exit to a large extent. Therefore, the way to resolve the disorderly evacuation of pedestrians caused by excessive crowd density in the evacuation process is to solve optimization parameters.

In order to cope with limited land availability and the increasing urban population, more high-rise buildings are being built throughout cities, but this has also led to new challenges in the emergency evacuation of people. Therefore, we conducted an evacuation experiment of a group of people in the stairwells of high-rise buildings to explore the movement law of groups in stairwells. The experiment had 18 scenes, including the evacuation movement of an independent group and the crowd evacuation movement of different groups. Analyzing the independent groups’ movement showed that regardless of the type of group, the average speed of the crowd was more than 1.2 m/s, which was longer than that of previous studies. The more constraints in the evacuation process, the smaller the speed difference between males and females. Group cohesion was mostly concentrated at about 1 s. Moreover, group velocity and cohesion were found to have no significant correlation in stairwell movement. Analyzing the crowd evacuation time of eight different scenes showed that it took longer for crowds bearing weight to evacuate than those not bearing weight. According to the spatiotemporal evolution of crowd evacuation in stairwells, the crowd moves intermittently in the evacuation process, especially in the early and middle stages of evacuation, and the influence of group factors on this process was not obvious. Regardless of the kind of scene or stairwell, the number of pedestrians generally first increased and then decreased to a significantly low value, and the number of pedestrians reached about 30 in the scenario of people without any load. Additionally, the speed of the pedestrians entering the stairwell in the back of the group was not faster than that of the pedestrians in the front, which showed that pedestrians rarely engaged in overtaking behavior. The research results of this paper not only enrich evacuation research but also provide support for the design of high-rise stairs.

This study investigates a dynamic flow model for crowd evacuation at T-shaped street junctions (TSJs) from a macroscopic view. The Aw-Rascle traffic flow model is modified by constructing an impact matrix in the street intersection area to practically describe the crowd convergence mechanism at a TSJ. For coherence, this modified model is proved to be anisotropic, similar to the original Aw-Rascle traffic flow model. To describe real scenarios with higher crowd density and lower speeds during organized pilgrimages, the initial Gaussian distribution of the crowd is improved to a higher-order smoothing function. To validate the modified Aw-Rascle traffic flow model, we reconstruct the drastic stampede that occurred at the TSJ of streets 204 and 223 during the 2015 Mecca pilgrimage. Further, the main environmental parameters that potentially lead to a stampede are discussed with numerical simulations. A valuable suggestion is that the street width ratio should be extended from 1.1 to 1.4 to prevent stampedes, matching the expansion engineering of street 204 reported by BBC News. An interesting phenomenon is that the closer the bus unloading location on street 223 is to the TSJ center, the lower the maximum crowd density and the safer the pedestrians will be. With this modified Aw-Rascle flow model at TSJs, this paper provides strategic and technical suggestions for future crowd flow control to reduce the risk of crowd stampedes. [ABSTRACT FROM AUTHOR]

Previous studies indicate that congestion is more likely to occur in the exit restriction area. Besides the background music in public places may have a potential impact on pedestrian movement. However, the influence mechanisms of low-boundary exit and background music on pedestrian evacuation are still unclear. Therefore, in this paper, the evacuation characteristics of pedestrians at a low-boundary exit were investigated with a series of controlled experiments. Different commands (listening to music while walking and following the tempo of the music) and different types of music (music and metronome) were designed in the experiment to analyze the influence of sound signal on the evacuation process. The result indicates that a larger width of low-boundary exit leads to a shorter evacuation time. The flow of low-boundary exit is higher than that of high-boundary exit. In addition, it is found that sound signal has a negative effect on evacuation efficiency, and the influence level is varied with different commands and music types. Specifically, the flow of following the beat of music is lower than that of listening to music, while the flow of walking with the beat of metronome is higher than that of walking with the beat of music. This study can contribute to understanding the evacuation dynamics of pedestrians when passing through a low-boundary exit. Furthermore, the performance of sound signal can be useful to develop management strategies for pedestrians under the emergency evacuation. [ABSTRACT FROM AUTHOR]

In order to solve the slow simulation speed of the social force model in complex indoor scenes, an improved social force model is proposed to reduce the iteration scale of obstacles. The proposed model takes into account the factor of a person's field of view (FOV) in indoor scenes, and the acting force between pedestrians and obstacles in the social force model is improved to find the optimal number of obstacle iterations without affecting the pedestrian movement law in the traditional model, so as to accelerate the simulation speed. The self-built simulation platform and real evacuation experiments are used to compare the performance indicators of traditional and optimized models and to analyze the relationship between scene complexity and machine computing efficiency. The results show that the optimized model takes less time to predict the evacuation path than traditional models, and as the number of initial pedestrians and obstacles increases, the proportion of machine computation time between the two models will gradually increase. Second, the CPU computation time of the optimized model increases gently, indicating better stability. Therefore, reducing the obstacle iteration scale based on the pedestrian's FOV factor provides an effective method to solve the slow simulation speed of traditional models. • The use of pedestrian vision factors shortens the size of obstacle iterations in social force modeling calculations. • The improved model has less impact on the evacuation metrics and pedestrian movement patterns of the traditional model. • The improved model promotes a reduction in simulation time compared to the traditional model. • The computational performance of the improved model performs well in complex scenarios. [ABSTRACT FROM AUTHOR]

In crowd evacuation simulation, a number of exit point and obstacles play an important role that can influence the result in the evacuation simulation. This paper focuses on the movement of the crowd’s emergency evacuation based on a modified social force model (SFM) via optimising the obstacles interaction parameter in one the SFM component. The simulation also compared original SFM (without obstacles) and modified SFM (with obstacles). The results show the impact can minimize the concept of arching phenomenon (faster-is-slower). For an obstacles issue, it is proven that obstacles can help to reduce evacuation time in regards to its proper position and exit width.