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Guidance is an efficient crowd management measure used to save lives in emergencies because it can reduce the disorientation of pedestrians. This study investigates an optimal guidance strategy for large-scale crowd evacuations. To increase computational efficiency, a pedestrian cell transmission model is extended to create a rapid simulation of guided crowd dynamics. To solve the conflicts between the limited guidance capacity and the desire to improve evacuation efficiency, a strategic guidance model is proposed, which generates a leader location and exit selection plan. A simulation algorithm is proposed to integrate a pedestrian following model and strategic guidance model based on the follower-leader interaction. Finally, a hybrid multiscale approach for modeling guided crowd evacuations is established to evaluate the performance of the guidance strategy. The experimental results show that the required CPU time of the proposed model is much less than that of the microscopic models. Because the number of leaders is minimized and the exit is selected by taking both risk and congestion into account, the obtained guidance strategy can realize the full use of guidance capacity, information confusion reduction and uniform exit usage, all of which contribute to a reduction in evacuation time.

In this paper, we consider the problem of finding the safest evacuation route in a multi-exit exhibition center while the fire hazard spreads. We first propose a system composed of sensor nodes to collect pertinent safety data. We present a real-time dynamic evacuation system that considers the changing conditions in the risks associated with each hallway segment in terms of walking distance, heat, two major asphyxiant fire gases and congestion. Our system activates smart panels placed at major junctions of the hallways to guide evacuees towards the appropriate exit by displaying the proper escape direction. This work can pave the way towards the development of next-generation smart exhibition centers, where crowd safety is among the top priorities.

To understand the current development and status of research on emergency evacuation, the published literature in the Web of Science core database from 2008 to 2018 were taken as the research objects, and the knowledge structure and research trends in the field of emergency evacuation were visualized and analyzed by using the scientific mapping knowledge domain. It is found that research on emergency evacuations throughout the world has a basic theoretical framework, but the various research branches have not yet formed a perfect knowledge network. The results show that China's publishing volume ranks first among countries/regions, and Tsinghua University has the largest number of publications among related institutions; traffic evacuation modeling, group behavior and crowd evacuation are the main knowledge groups for emergency evacuation research; the research fields mainly include disaster emergency management, personnel evacuation simulation and emergency traffic evacuation; and the research topic of emergency evacuation mainly evolves into three core paths, namely, “disaster - management - preparation - response – information”, “evacuation - behavior - model - cellular automaton - time – design” and “evacuation - behavior - simulation - social force model - exit choice”. Crowd evacuation and exit choice have become the frontiers of current emergency evacuation research.

In the process in which people enter and exit buildings, available exits in buildings are not effectively utilized and cause overcrowding at other exits. Therefore, the effect of the locations of staircases and exits on occupant evacuation was investigated in this paper. The FDS+Evac software package was used to quantify the evacuation process. Four scenarios were simulated to investigate the detailed properties of evacuation. The results revealed that the locations of staircases had a minimal effect on evacuation. When the staircases were located in the middle of a building, flow stratification occurred. With stratification, the flow rate is not constant throughout the evacuation process. Two or more evacuation stability stages exist. The evacuation flow rate curve resembles a ladder. Stratification in the flow rate causes increasing panic during crowd evacuation as people in the rear of a building cannot locate the target that can be followed in front of them. With an equivalent exit width, the evacuation efficiency of a building with two exits was higher, and the evacuation time was shorter. When an exit was located facing the staircases, the evacuation time was lower, and the flow rate of the occupants was relatively stable. Therefore, buildings should be designed with exits facing the staircases. If feasible, large staircases should be replaced with two identical sets of staircases. These measures will facilitate evacuation.

To control overcrowded pedestrians at the exit, buffer zones are very common in densely populated areas. However, little focus has been paid on the mechanisms of buffer zone. In this paper, a tentative experiment was designed to preliminarily reveal the role of buffer zone in crowd evacuation. Then a social force based simulation model was established by Massmotion according to the properties of the experiment. The simulated results show that buffer zones may have a potential positive effect on evacuation through comparing with the experimental results. After that, via changing the buffer zone length and the desired velocity of agents in further simulations, the data, such as evacuation time, density distribution, individual waiting time, instantaneous velocity and average velocity were investigated in detail. It is found that after the buffer zone set, the evacuation efficiency is significantly improved at high desired velocity, and the evacuation time is shortened with the increase in buffer zone length. Setting buffer zone in front of the exit can effectively reduce the crowd density at the exit, alleviate the surgent transmission of density waves in crowd, so as to reduce the risk of crowd squeezing and trampling. Besides, when the desired velocity is relatively high, the relationship between the buffer zone length and the average velocity is obtained specifically, indicating that the longer the buffer zone, the more likely pedestrians can escape as quickly as possible. Based on this work, some suggestions were put forward on how to control the dense evacuation via setting suitable buffer zones.

Fatigue even increases the complexity of the pedestrian dynamics which is regarded as a kind of nonlinear system, and might have a significant negative impact on the crowd evacuation. However, it has never been investigated completely and properly. Thus, the fine discrete floor field cellular automata model is modified by integrating the fatigue function to explore the influence of fatigue on the crowd ascending evacuation. The simulation fits well with the empirical data and the observations quantitatively and qualitatively, indicating the model captures the main features of evacuation considering fatigue impact. As a prediction, without merging streams, compared with the case of walking in constant speed, when fatigue is considered, it takes 71.4% longer for all persons to enter the stairs and 87.2% longer to evacuate. With merging streams, fatigue has little impact on the inflow, while it makes the total evacuation time 84.2% longer.

Humans use social information to improve their decisions in scenarios that involve uncertainty. Previous research has shown that this social influence can have positive or negative outcomes depending on the context of decision and characteristics of the system. A particular scenario where the social information matters is the collective escape where behaviour of others could be used as an extra source of information and thus, influence the decision-making. The question is whether there could be any benefit for escaping human crowds to display imitative tendencies (or the so-called ‘herd’ behaviour) in their decision making. Here, we investigate this question in relation to exit direction decision-making through extensive computer simulation analyses. Using parameteric models of decision making, we increased the imitative tendency of (behaviourally) homogenous crowds on a continuum, simulated the escape process and outputted measures of system efficiency. We examined a broad range of simulated scenarios in terms of the shape of the environment, exit visibility and spatial distribution of exit capacities. Results showed that for none of the scenarios we tested, the escaping crowd could benefit from amplified tendencies to imitate peers. Our numerical analyses suggested that, at least when familiar with escape routes, there is no rationale for blindly following the direction choices of the crowd in emergency scenarios. Strong tendency to copy direction choices of the crowd could substantially hinder the process of evacuations and increase the risk of casualty. These findings have potential implications for evacuation training guidlines. They provide insights into how individuals should be guided/instructed to conduct themselves in case of an emergency in order to facilitate and optimise the evacuation process. A question for future research is how imitation (herding) in other aspects of escape behaviour (such as movement initiation or adapting (changing) direction choices) can influence the system.

When it comes to emergency evacuations of a big number of individuals from a certain room or a building, it is crucial that they should be able to exit the under study place in a quick and safe manner. Nevertheless, crowd behavior can be affected from various factors, among which are the distance from the exit, the visibility of the exit, the density of the crowd and how uncomfortable the conditions are inside the room for the crowd. In this study, we propose an evacuation model, in order to achieve a computationally enhanced simulation, based on Cellular Automata modeling, coupled with a Spatial Game to solve conflict situations among the anxious crowd. Additionally, aiming to a more realistic model, we added not only topological, but also behavioral characteristics coupled with the incorporation of different moving velocities and memory features to the evacuees.

Congestion in pedestrian crowds is a critical issue for evacuation management. This paper presents an approach based on arch formation to alleviate congestion formed by crowds gathering at a bottleneck. In this approach, analyzing a specific self-organized motion pattern, namely, arch formation, the position of the arch formation has a great influence on congestion alleviation. Specifically, an arch formation at an outer position is beneficial for congestion alleviation because it is unstable and collapses easily. The symmetrically placed obstacles, which have a similar role as anti-slide piles, are used to change the position of the arch formation in a crowd. The spacing between the symmetrically placed obstacles is an important parameter for adjusting an arch formation. We present a modified model that originates from the soil mechanics in civil engineering to calculate the proper spacing between the symmetrically placed obstacles. This model analyzes the static attributes of an arch formation and improves the spacing calculation. The proper spacing between symmetrically placed obstacles can alleviate congestion and increase evacuation efficiency. In this paper, the social force model is used to conduct an evacuation simulation, and the simulation results illustrate the effectiveness of the proposed approach.

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.

In this paper, according to the characteristics of evacuation in high-density crowd, a new triangular grid cellular automata model is proposed. In this model, the maximum density of crowd can reach to 8 person/m2 which is measured by the experiment. And pedestrians can move to 14 directions if there are no obstructions around them. Meanwhile, this paper proposes the concept and calculation rules of moving potential in the moving field. The moving potential provides reference for the movement of a pedestrian. Through the comparison of the measured values and the simulated values of an evacuation process in a building, it is proved that the model can accurately simulate the evacuation process of high density crowd.

Modern buildings have become larger in scale and function, and the complexity has also increased considerably. For these reasons, there are more difficulties in evacuation and rescue when an emergency occurs, so effective evacuation methods and risk should be predicted and applied to building design, safety training, and education. We have developed an active route choice model based on human body organs and characteristics that detects risks and route conditions, communicates with neighboring occupants, determines the bottleneck point, and selects evacuation routes according to each occupant's personal characteristics. In this study, we introduce the implementation process and characteristics of the active route choice model, and by applying the model to the occupants, we compared the evacuation times according to the route condition, number of occupants, and corridor width in a virtual environment. We believe that realistic and valid results can be obtained by applying the active route choice model in crowd evacuation simulation.

A social force model is developed in this paper to study the crowd evacuation when a terrorist attack occurs in the public place. The persons in the model are divided into two groups—terrorists and pedestrians. On one hand, each terrorist chooses the nearest pedestrian as the target. Once the distance between him and his target is small enough, the terrorist will launch attacks on his target and the target will be killed with a certain probability. On the other hand, each pedestrian tries to avoid the terrorists and reach the exits. An emergency exit choice strategy which emphasizes the security risk factor is developed for pedestrians. The main simulation results are summarized as follows. First, the number of deaths in the terrorist attack increases with the number of terrorists and with the density of pedestrians. If the number of exits decreases, the death toll will become more sensitive to the change of the density of pedestrians. Second, adding the number of exits can significantly reduce casualties. Third, more pedestrians will be killed and the evacuation speed will be reduced if terrorists start the attack from the positions of the exits. Fourth, the emergency exit choice strategy has an advantage over the ordinary exit choice strategy in daily life for reducing casualties. The more unbalanced the terrorists’ initial distribution around the exits is, the more noticeable this advantage will be. Fifth, the number of deaths will decrease obviously if at least half of the exits are available and safe. Our study is valuable for developing an effective evacuation scheme to reduce casualties in a terrorist attack.

Understanding how crowds behave in an emergency has long been held to be necessary to emergency response and management. Competition due to mass panic is often assumed to be a natural response during emergencies, which is in contrast with the current psychological research that evacuees rarely demonstrate competitive behaviors, but do exhibit cooperative behaviors. In this work cooperative behaviors and evacuation efficiency has been examined in detail by using a cellular automata evacuation model from a game-theoretical perspective. Simulation results show that the self-regarding evacuees are able to be cooperative to each other when faced with an emergency. It is found that during an emergency evacuation high levels of escape aspiration promote cooperation among evacuees while in non-emergency situations they inhibit cooperative behaviors, and heterogeneous learning rates for different strategies can lead to various levels of cooperation. This work provides a new insight into crowd behaviors in an emergency evacuation.

In the study of pedestrian evacuation dynamics, pedestrian aggressiveness is important to consider as it potentially impacts evacuation efficiency. A representative example is the ‘faster-is-slower’ phenomenon. In reality, a crowd is a mixture of patient and impatient pedestrians, rather than a collection of like individuals. The impact of such heterogeneity has been reported in previous studies; however, these studies are all based on handcrafted solutions. In this study, we propose a heuristic approach for incorporating a genetic algorithm into the floor field cellular automata model to investigate the optimal initial pedestrian evacuation condition. Pedestrian aggressiveness is represented by two different approaches: the revised friction function and the persisting probability. To verify our genetic algorithm approach, we compared the results with the theoretical analysis and simulation results based on handcrafted solutions. The first contribution of this study is that the initial condition, a mixture of patient and impatient pedestrians, affects evacuation efficiency. Another contribution of this study is the heuristic approach incorporating a genetic algorithm. Our approach exerts the computational efficiency advantage of the floor field cellular automata model.

The current evacuation model does not consider the impact of emotion and personality on crowd evacuation. Thus, there is large difference between evacuation results and the real-life behavior of the crowd. In order to generate more realistic crowd evacuation results, we present a method of emotion contagion for crowd evacuation. First, we combine OCEAN (Openness, Extroversion, Agreeableness, Neuroticism, Conscientiousness) model and SIS (Susceptible Infected Susceptible) model to construct the P-SIS (Personalized SIS) emotional contagion model. The P-SIS model shows the diversity of individuals in crowd effectively. Second, we couple the P-SIS model with the social force model to simulate emotional contagion on crowd evacuation. Finally, the photo-realistic rendering method is employed to obtain the animation of crowd evacuation. Experimental results show that our method can simulate crowd evacuation realistically and has guiding significance for crowd evacuation in the emergency circumstances.

Pedestrian behavior modeling plays a considerably important role in improving operational efficiency and safety of pedestrian infrastructure. In this paper, we first propose a cost potential field cellular automata model that simulates crowd evacuation dynamics on a ramp with two exits. In the model, each pedestrian navigates according to the cost potential field in the ramp domain. Evacuation behaviors of pedestrians are investigated with respect to the ramp angle and the layout of the exits. An aggregated pushing force field is introduced to capture the effects of pushing interactions among pedestrians under congested situations. The phenomenon of pedestrians’ falling down is modeled and demonstrated under various scenarios with different exit layouts and ramp angles. Numerical results show that an optimal layout strategy is to set the two exits in the center of the bottom and the top of the ramp, respectively. This typical exit layout design could effectively prevent and/or reduce crowd injury caused by the domino effect of pedestrians falling down in a stampede. Keywords:: Exit layout strategy, Stampede, Potential field, Cellular automata model

In the study of pedestrian movements, a consideration of group behaviors is important because of their potential impacts on pedestrian flow dynamics. In this paper, we investigate the group behaviors during emergency evacuation, which is a critical case for emergency crowd management but has not been fully explored and understood. It has been well recognized that in evacuation situations, some people within a crowd, especially those who are with families and friends, often move in small groups and act in particular patterns distinct from individuals. As a result, the crowd is a mixture of individuals and groups rather than a pure collection of individuals. To capture and evaluate the influence of group behaviors on crowd evacuation, we propose an extended floor field cellular automaton (CA) model that takes into account such phenomena. Our model is formulated by leveraging the leader-follower behavior rule that is evident in pedestrian group behaviors. To calibrate and validate the proposed model, a few field experiments of crowd evacuation were conducted in a university building. Through a representative case study, it is demonstrated that the proposed extended floor field CA model can replicate the well-known phenomena in crowd evacuation such as collective arch-like clogging at the exit as well as other commonly observed group behaviors in evacuation. Moreover, it is found that the total crowd evacuation time significantly increases with the presence of pedestrian groups in the crowd. The results also show that such negative effects of group behaviors in crowd evacuation intensify when the density of the crowd is higher. Subsequently, sensitivity analyses are performed to further explore how pedestrian group behaviors are influenced by model parameters that reflect the pedestrian flow dynamics in evacuation scenarios. With its capability of realistically replicating the field pedestrian evacuation, the proposed model can serve as a valuable tool for predicting crowd evacuation time and designing guidelines for pedestrian evacuation in emergency situations, in particular when group behaviors are salient.

In this study, we propose an extended route choice model based on an available evacuation route set to simulate the selection of pedestrians in selecting an appropriate route during evacuation in emergency situations. In this model, four parameters (i.e., distance to available route, length of available route, level of congestion in available route, and capacity of available exit) affect the route choice of the pedestrian and the evacuation route set. In this study, the evacuation route set is created and optimized by a modified social force model and a route learning method. Experimental results show that the extended model can effectively reproduce crowd behavior in an emergency situation, which can assist in analyzing emergency evacuation scenarios. Moreover, two important conclusions regarding increasing evacuation efficiency show that the proposed model is in line with real-world situations.

Computer Vision (CV) based surveillance in crowded scenes is one of the most significant and promising topics due to the increase of people gatherings in public places where the possibilities of disasters and stampedes is also high. Therefore, it is essential to develop a well established Crowd Disaster Avoidance System (CDAS) for the public safety. In general, CV-CDAS focuses on crowd scene analysis, crowd behavior analysis and crowd management. Either, a stampede may occur due to abnormal behavior of individuals in a crowd or a crowd may behave abnormally after the stampede. Even though behavior analysis of a crowd plays an essential role, it is inadequate to decide whether a stampede may occur or not at that instance. Despite significant progress and various surveys on crowd scene, crowd modeling and behavior analysis over the past few decades, the existing surveys still fail to discuss and delineate the crowd disaster analysis based on many key aspects as a whole. However, CV-CDAS needs to be developed based on the necessary factors such as the number of cameras (single/multiple), target of interest (an individual/group or crowd), crowd scene (structured/unstructured), crowd motion (static/dynamic), crowd behavior analysis, people count and crowd density estimation, person re-identification in crowd, crowd evacuation, forensic analysis on crowd disaster and computations on crowd analysis. Consequently, taking all these factors into an account, this survey aims to deliberate a road map to develop a stable CV-CDAS which includes recent trends and approaches in the crowd disaster analysis. In addition, behavior analysis plays a vital role and hence, an extended version of existing survey with the perspective of single and multiple cameras is elaborated. Besides, it summarizes the crowd disaster problem handled by various CV algorithms in the past and also paves a way to avoid this problem in future. Moreover, this survey presents the existing benchmark datasets with their specifications and performance evaluation metrics with special focus on dataset which will be suitable for specific application and it helps the researchers to select appropriate dataset for evaluation. Finally, this paper concludes with open issues and directions for future research which may further motivate and guide the academic and industrial personnel, involved in developing CV-based crowd disaster management systems.

In this paper, the information transmission mechanism is introduced into the social force model to simulate pedestrian behavior in an emergency, especially when most pedestrians are unfamiliar with the evacuation environment. This modified model includes a collision avoidance strategy and an information transmission model that considers information loss. The former is used to avoid collision among pedestrians in a simulation, whereas the latter mainly describes how pedestrians obtain and choose directions appropriate to them. Simulation results show that pedestrians can obtain the correct moving direction through information transmission mechanism and that the modified model can simulate actual pedestrian behavior during an emergency evacuation. Moreover, we have drawn four conclusions to improve evacuation based on the simulation results; and these conclusions greatly contribute in optimizing a number of efficient emergency evacuation schemes for large public places.

The rapid increase in demand for ecofriendly ships fueled by liquefied natural gas (LNG) has led to the proposal of floating large-capacity bunkering terminals at sea. Although computational fluid dynamics (CFD) simulations on preventing gas accidents on LNG-fueled ships and bunkering facilities have been carried out, research on evacuating humans in the event of disasters such as fire and explosion due to gas leakage has been insufficient. In this study, an algorithm was derived that considers the interaction between workers and gas accidents for evacuation to the open deck of a floating bunkering terminal, and a simulation platform was developed for visualizing gas accidents. The developed algorithm and simulation platform were applied to analyzing the evacuation characteristics considering both the gas accident and evacuation destination, and the results were compared with those of existing commercial software under the same conditions. The results demonstrated that considering the human characteristics of evacuees and their interaction with risk factors is important for simulating crowd evacuation more realistically.

An extended floor field cellular automata model considering pedestrian panic was proposed to investigate pedestrian dynamics under the threat of artificial attack. In the model, a new parameter D was introduced to reflect quantitatively the extent of the impact of panic on pedestrian evacuation. Besides, pedestrian movement is governed by the static, attack threat and herding floor field. And some modifications were made to introduce the influence of panic on the decision-making of the individual. Further, the motion and assault of the artificial attacker and the death of pedestrians were taken into account simultaneously. The simulation results show that the proposed model can reproduce some real characteristic features of escape panics, such as (1) Pedestrians become less rational. (2) At exits, arching and clogging are observed. (3) People show a tendency towards mass behavior, i.e., pedestrian herding. (4) Alternative exits are overlooked or not efficiently used. As the extent of the panic increases, pedestrians spend more time to escape from the room and are more sensitive to the movement of the crowd and the action of the attacker. The phenomenon of pedestrian herding and jamming can be clearly observed as D increases. And the results also indicate that the tension caused by moderate panic can help reduce casualties, whereas excessive panic will increase casualties. Besides, enhancing pedestrian initiative, i.e., the ability that pedestrian finds the exit independently in panic, is beneficial to the evacuation. In addition, more pedestrians would lose their lives due to attack and the evacuation efficiency would be reduced if the attacker starts the attack from the positions of the exits, so the security forces near the exits should be strengthened.

When evacuees directly confront a life-endangering situation in a fire accident, the raised stress created by the physical threat of fire tends to affect evacuees' escape behaviours (i.e., shifting from a calm exit mannerism to a stressful escape behaviour). This behavioural phenomenon inevitably affects crowd movement patterns and subsequently, the overall evacuation characteristics. However, limited works address the impact of stress variation on evacuees under the pressure of a fire emergency. In this paper, we propose an evacuation model to numerically determine the stress level of evacuees according to their specific surrounding environment. Hence, it enables evacuees to perceive the fire risk and acts in response to the fire hazard. Rather than solely placing emphasis on representing the physical movement of evacuees only, as are the common approach used in previous works, this study focuses on the influence of stress factor on the crowd evacuation performance. Our proposed model contributes to a better understanding of the crowd evacuation dynamics by investigating the effect of stress variation on evacuees, which provides an additional aspect of insight to existing evacuation frameworks.

Empirical evidence suggests that evacuees tend to break down their well-coordinated motion and adopt competitive egress behaviour when they are confronting life-endangering situations (e.g., fire accident, earthquake). This phenomenon significantly influences crowd dynamics, and subsequently, the overall evacuation time. In this paper, a novel evacuation model has been developed, which takes the detailed cooperative and competitive egress movements of evacuees into consideration. The proposed model has been conducted to simulate crowd (i.e., with different proportion of competitive individuals within the crowd) evacuating from a single-exit compartment room (i.e., the exit width varies from 0.8 to 2.0m). Simulation results show that competitive evacuees exhibit an arc-shape formation in front of the bottleneck area (i.e., the exit). This is notably distinct from the cooperative evacuees generated shape formation. In addition, the evacuation performance (i.e., evacuation time, trajectories, density and flow rate) of competitive and cooperative evacuees over time are successfully captured for analysis. This study contributes to a better understanding of the crowd evacuation dynamics by considering the impact of competitive and cooperative egress movements.

This paper analyzes literatures on crowd evacuation based on data extracted from Web of Science by applying bibliometric approaches. In specific, reference co-citation analysis, author co-citation analysis, and keyword co-occurrence analysis are adopted to analyze the data with CiteSpace and VOSViewer. This paper makes the following contributions. First, reference co-citation analysis identifies five clusters in the studies on crowd evacuation. Second, author co-citation analysis identifies highly cited authors and categorizes them into three groups. Third, keyword co-occurrence analysis identifies the hotpots in the field of crowd evacuation and points out the directions for future studies.

The problem of evacuating crowded closed spaces, such as discotheques, public exhibition pavilions or concert houses, has become increasingly important and gained attention both from practitioners and from public authorities. This kind of problem can be modeled using Agent-Based Model techniques and consequently simulated in order to study evacuation strategies. In this paper, we show the Fira of Barcelona evacuation model implemented with Care HPS. As a main contribution: i) we extend and added new partitioning approaches and other features in Care HPS to carry on this model; and ii) we figured out that crowd evacuation problem has bottlenecks in reality, such as exits, that required more deep optimization in code in order to decrease the total execution time. Finally, we draw some conclusions and point out ways in which this work can be further extended.

A crowd usually tends to move in small groups during evacuation. Small group has a large proportion in crowd evacuation, and small group effect affects crowd evacuation significantly. In this work, we propose a novel methodology for calculating movement profit based on cellular automaton model. Specifically, this methodology calculates the movement profit for a target at the next moment by comprehensively combining distance profit, density profit, and average velocity profit. In particular, this paper defines three types of small-group formation with totally six different forms of small group in terms of the size, and sets the corresponding movement velocity. At last, we simulate the evacuation process of small groups, and discuss the relationship among evacuation time, average movement velocity, and pedestrian density, and analyze the efficiency of small group evacuation in terms of evacuation strategies. As the simulation results demonstrated, the evacuation efficiency of different types of small groups is greatly different, and the same type of small groups with different forms is also different.

Evacuation leaders (individuals guiding the crowd) can make crowd evacuation more efficient. Selecting their number and positions within the crowd is particularly important when the other evacuees are not familiar with the internal layout of the building. This paper investigates the effects of leadership on crowd evacuation in rooms with limited visibility range by an extended social force model. We find that, (i) For a large evacuees crowd, a small proportion of the evacuation leaders is already sufficient to guide the whole crowd efficiently, even if the visibility range of the room is very limited. And the smaller the crowd size, the larger the proportion of the leaders is needed to achieve a satisfactory evacuation guidance. (ii) The optimal proportion or number (i.e., the proportion or number that is necessary for guiding the crowd) of the leaders in an evacuees crowd to achieve a satisfactory guidance is related to the visibility range of the room and the distribution range of the evacuees crowd. (iii) Leadership is not always positive to the crowd evacuation. It may have a negative effect on crowd evacuation when the visibility range of the room and the size of the evacuees crowd are large enough. The findings provide a new insight into the effects of leadership on crowd evacuation.

The presence of social groups in pedestrian crowds can have a substantial effect on the overall evacuation process. However, crowds are mostly simplified as a collection of individuals, and the influence of grouping has not been widely considered in pedestrian crowd simulations. In this study, a novel model that accounts for social groups was implemented based on a social force framework to investigate evacuation dynamics in pedestrian crowds. The associated model parameters were calibrated via two group experiments to provide more credible and realistic simulation results. The effects of certain variables (e.g., group size, desired speed, exit width) on the overall evacuation performance and local group behaviour were investigated. The simulation results indicate that group effects facilitated overall crowd evacuation, especially when the exit was wide. The total evacuation time of a pedestrian crowd was shorter when the groups within the crowd were larger. The time intervals for groups of various sizes did not show a significant difference. The group shape was approximated as a rectangle, and the group features were therefore quantified by shape-related parameters (e.g., aspect ratio and area). The rectangle was shown to orient itself along the moving direction. An elongated configuration of the group became increasingly notable when the leader–follower relationship intensified, resulting in a queue-like formation that facilitated the overall evacuation. A certain trend was found that showed an increase in the aspect ratio and a decrease in the normalised area over time. The larger-sized group often seemed to have a smaller aspect ratio but required more space per person during movement. This study deepens the understanding of crowd evacuation dynamics featuring social groups.

Fire emergencies impose significant threats to building occupants. During evacuation, fire has significant impacts on evacuees' behaviors, by e.g., changing their route availability, disturbing their perception of the environment due to reduced visibility, impairing their mobility that is usually associated with severe injuries, and causing significant mental stress that may lead to complicated and unpredictable navigation decisions. Despite the detrimental effects of fire on crowd evacuation, most existing building evacuation simulation models and tools do not account for the impacts of fire on the evacuation process; at most they rely on oversimplified assumptions and simulation settings. In this study, a new fire evacuation simulation model, named FREEgress (Fire Risk Emulated Environment for Egress), is developed to simulate the dynamic influences of heat, temperature, toxic gas and smoke particles on evacuees' mobility, navigation decision making and health conditions. FREEgress (1) introduces evacuee agents who are aware of and able to assess the fire hazards, and can make fire risk-informed navigation decisions; and (2) models the interactions between evacuee agents and the dynamic fire emergency environments and the consequent evacuation process. The verification of FREEgress is conducted by comparing its simulation results with two existing simulation tools, SAFEgress and FDS + Evac. In addition, a case study using FREEgress is carried out to simulate the evacuation in a museum for 30 different fire emergency scenarios. The simulation results are analyzed to assess the impacts of three important factors, namely initial fire location, evacuation delay time and evacuee behavior, on the evacuation process and evacuation outcomes. The case study demonstrated the potential value of FREEgress to support both the safety design of new buildings and maintenance and emergency management of constructed facilities.

Knowledge and emotion play important roles in the process of crowd evacuation. Knowledge determines the moving direction of an individual, and emotion determines the moving speed of an individual. However, the existing works lack consideration of knowledge and emotion at the same time, which results in unreasonable simulation of crowd evacuation. To solve this problem, we propose a knowledge and emotion dual-driven method for crowd evacuation simulation. First, the knowledge representation and knowledge transmission are modeled to quantify the knowledge of evacuees. In this step, the knowledge representation is modeled by differentiating the hazard source knowledge and the scenario knowledge and the factors affecting knowledge transmission are combined with the susceptible infected (SI) model to simulate the process of knowledge transmission. Second, the emotion model is constructed to quantify the individual emotion in the evacuation process. In this paper, the quantification of emotion takes into account two factors: (1) the influence of individual knowledge on emotion is quantified by using Siminov’s psychology model; (2) the influence of emotional contagion among individuals is also considered. Then, quantitative individual knowledge and emotion are combined with the reciprocal velocity obstacles (RVO) model to build the knowledge and emotion dual-driven crowd evacuation model. Finally, we implement a 3D crowd simulation system based on the knowledge and emotion dual-driven model to visualize the results of our theoretical analysis. The experimental results show that the proposed method can more realistically simulate crowd evacuation in an emergency situation.

The metro has become an important component of the urban traffic system. Due to the dense crowd, if sudden accidents occurred during rush hours in station, such as fires, explosions or natural disasters, the casualty and injury would be very enormous. Accidents happening in the underground station are prone to trigger domino effect, causing complex multi-hazards consequence. Therefore, more attention should be focused on the crowd evacuation strategy in underground stations. In this paper, for studying the temporal and spatial distribution characteristics of evacuation in dense subway stations under node failure caused by multi-hazard coupling conditions, a large-scale evacuation model was established by Massmotion based on the social-force, combined with the on-site measured data of Nanjing Xinjiekou subway station, one of the largest stations in Asia. A series of key node failures in the station that represents the bad impact of multi-hazards is set in the model. Through analyzing the evacuation time and the occupant density, etc, the results show that if pedestrians tend to escape by the lowest cost, it will cause extreme pressure on some narrow region. If those nodes fail unfortunately, the global evacuation efficiency will be seriously affected. Yet, an excessively scattered targets strategy obviously wastes traffic capacity and delay evacuation process. Therefore, it is necessary to balance the global evacuation time and local density in the process of crowd evacuation. The current conclusion will be useful to prompt the administrators to formulate a reasonable evacuation strategy and disperse the regional evacuation risk.

The growing need for more and more complicated underground urban systems has resulted to the development of a challenging environment for the setting up of effective evacuation procedure. The special circumstances and complexity, which characterize the underground spaces, as well as the severity of the consequences if an accident occurs, stimulated the research for different evacuation approaches in urban environments, in order to improve the efficiency of emergency evacuation and prevent crowd casualties in potential accidents, especially in the case of fire. The paper presents the most well respected standards, guidelines and regulations enforced worldwide, aiming to preserve the safeguarding of life and property against fire, explosion, and related hazards associated with developed subterranean spaces. Moreover, the evolution of underground evacuation approaches, from prescriptive methods to contemporary performance methods is displayed, followed by the examination of the approaches in crowd evacuation practices. Finally, the paper presents and analyses the factors being taken into account for planning the evacuation process, as illustrated through cases where modeling is conducted with special software codes.

In this paper we propose a novel technique termed miSFM for the simulation of crowd evacuation. miSFM take merits of both Mutual Information (MI) and Social Force Model (SFM). More specifically, MI of interacting agents is adopted to determine the level of order within a crowd during an evacuation. In such a way, SFM can be improved by adapting the forces involved at microscopic level between mutually interacting agents. The key innovation lies in highlighting how the dynamic adjustment of SFM parameters reveals much more realistic crowd movements for the evacuation simulation. Extensive experiments over several alternative and state-of-the-art works demonstrate the advantages of the proposed algorithm.

It has been hard to model a crowd evacuation process considering different walking abilities using a synchronous cellular automaton. That is because the cross and the overlaps of routes have to be taken into consideration and the conflicts resolution between pedestrians is more complex. However, the desired velocities of evacuees might be quite different due to the discrepancies of the physiological function, including age, gender, physical state, and the psychological behavior, such as the perception and reflection to the dangers. Additionally, an evacuee might change his desired velocity constantly to adapt to the changing evacuation environment. Thus, a multi-velocities floor field cellular automaton model was established in this paper. Using little CPU time, a dense crowd evacuation simulation with tiny varied velocity can be conducted very well. Significant discrepancies between the single-velocity evacuation and the multi-velocities evacuation were observed. The plateaus, where the exit flow rate is rather low, can be well predicted by a dimensionless parameter describing the congestion level of the evacuation system. The crowd evacuation time almost depends on the low desired velocity evacuees, though the proportion is not high. We also observed that faster evacuees make the evacuation system easily approaching to the jam.

A basic cellular automaton model does not consider social forces interaction in building evacuation thus could not explain complex crowd evacuation processes. This study developed a cellular automaton model on social forces interaction in building evacuation, where the positive and negative impacts of social forces on evacuation time were simulated and analyzed. The model was verified using experimental data. The clustering attraction between people always increased the evacuation time regardless of the number of evacuees, the building size, the number of exits, and the people distribution, thus the clustering attraction is always to be avoided. When people in a room were randomly and evenly distributed, the repulsive force of obstacles, the attractiveness of evacuation direction, and the repulsive force of exit congestion played negligible roles on the evacuation time thus could be ignored. The evacuation path could be optimised by adjusting the influence coefficients of social forces to reduce the evacuation time.

Overcrowding during emergency evacuation can cause crowd stampede and trampling that will lead to serious injuries or fatalities. These situations are likely to occur in natural or man-made disasters in open or closed spaces. The inefficient building design such as the unsuitable placement of an exit door is one of the key factors that contribute to the above tragedies. Most existing works used a trial and error method for a single room scenario in finding optimal locations of the exit doors. The main limitation in these works is that it is not suitable for handling multi-room problems and more complex room arrangements, since such problems would require a tedious process. To overcome this limitation, Artificial Bee Colony (ABC) optimization algorithm based on stochastic method is proposed in this paper. Compared to other optimization techniques, this algorithm requires less control parameters to be tuned in finding the most optimal exit door locations. A crowd evacuation model based on the Social Force Model (SFM) is used in representing the crowd dynamics and becomes the basis for the cost functions for the optimizer. The presented methodology has shown that the optimum locations of exit doors for a multi-room scenario can improve the evacuation efficiency; by minimizing crowd evacuation times and maximizing the number of people being evacuated. It is also clearly demonstrated that the optimized design is remarkable in improving the evacuation efficiency under different desired speed of crowd to evacuate.

The intelligent evacuation guidance system (IEGS) is a new concept and product in China, using an intelligent inducing algorithm to get dynamic evacuation routes and improving evacuation efficiency. This paper analyzes IEGS's influences on crowd evacuation by simulating a fire scene on the experimental platform of the “black house”, and some important conclusions are obtained. These conclusions including layout of exit position, settings of evacuation channel number and width, determining of installation distance and installation position mode of the intelligent acousto-optic evacuation indicator (IAEI), and choice of sound and visual inducing, can be a guidance in practical engineering and provide a reference for national standard ‘fire emergency evacuation lighting indication system (EELIS)’ modification.

A key activity in emergency management is planning and preparation for disaster. If the right safety measures are implemented beforehand, harmful effects can be significantly mitigated. However, evaluation and selection of effective measures is difficult due to the numerous scenarios that exist in most emergency environments coupled with the high associated cost of testing such scenarios. An agent-based system employs a computational model of autonomous interacting agents in an environment with the purpose of assessing the emergent behavior of the group. This paper presents a prototype of a computer simulation and decision support system that uses agent-based modeling to simulate crowd evacuation in the presence of a fire disaster and provides for testing of multiple disaster scenarios at virtually no cost. The prototype is unique in the current literature as it is specifically designed to simulate a concert venue setting such as a stadium or auditorium and is highly configurable allowing for user definition of concert venues with any arrangement of seats, pathways, stages, exits, and people as well as the definition of multiple fires with fire and smoke dynamics included.

In recent years, deep underground buildings appear more often than ever, and stairs are the main facilities for the upward evacuation of crowds from these buildings. As one of the most essential factors, the visibility might play a dominant role in the upward evacuation on stairs. To ensure the safety of the crowd in underground spaces, a finer discrete and stochastic floor field cellular automaton (FFCA) model integrating the visibility influence is established for the simulation of the crowd upward evacuation from a 21-storey staircase. By comparison, the simulation fits well with the observation and experiment, which implies that the model captures the main features of upward evacuations on stairs. Then, from the predicted results, it is found that the visibility reduction has a significant negative impact on the temporal–spatial distribution of pedestrians, especially on the inflow and outflow, while the entrance flow rate shows little impact as long as it is higher than 1.0 ped ⋅ m−1 ⋅ s−1.

As a kind of emergency evacuation, the large-scale evacuation is an effective measure to mitigate disaster in a sudden crises. Research into the emergency evacuation of crowds has been the focus of many scholars at home and abroad for some time. In this paper, four principal aspects of current research into large-scale crowd evacuation, namely evacuation theories, evacuation modeling, evacuation decision-making and evacuation risk evaluation have been summarized. Of these, evacuation modeling has attracted the greatest interest. While some evacuation models have proved effective tools in evacuation decision-making and risk evaluation, existing evacuation models have not fully considered the uncertain factors in the process of large-scale evacuation.

Accidents and natural disasters such as fire and earthquakes post more and more threats to the transportation infrastructures. Under such circumstance, the evacuation process for the crowded pedestrians in these infrastructures may be affected by the facility failure, resulting in partially damaged evacuation network, which at last forms bottlenecks and decreases the evacuation efficiency. Thus to improve the safety and comfortable level of crowd evacuation in transportation infrastructures, a new method of bottleneck identification and evaluation for evacuation network is proposed. The proposed method takes into account the facility failure induced crowd redistribution and explores the structure importance of the evacuation network component. The method of bottleneck identification is also applicable to other similar transportation networks.

Emergency evacuation has been receiving increasing attention due to the widely concern of public security in recent years. It is a critical task to analyze how to evacuate large crowd in an efficient way. Evacuation leaders, described by a modified leader-follower model based on social force, areinvestigated in this paper aiming to reduce evacuation time, casualties and loss. Artificial system of Beijing South Station is established based on actual data to verify the lead-follower evacuation method, where a large number of simulations have been conducted. The results show that evacuation with evacuation leaders can effectively reduce the evacuation time and casualties in an emergency situation in public place with a large number of pedestrians.

As an extension of the Asymmetric Simple Exclusion Process, the floor field cellular automata model has its specific advantages in reproducing crowd self-organized phenomena, embodying individual characteristics and reducing the computing complexity by translating the long-ranged interaction to local interaction. Evacuation from a room is an important part in the study of building evacuation. In our experiment and real life observation we found the exit attraction non-uniformity. To obtain the effect of individual tendency to the exit attraction center on the crowd evacuation efficiency, the static field is modified. Compared with the control group, the exit attraction non-uniformity has a disadvantage in the crowd evacuation efficiency. The position deviation between the exit geometric center and the exit attraction center delays the crowd evacuation by generating a local merging flow. In addition, the individual tendency also increases the crowd evacuation time by increasing the static field gradient to the attraction center, leading to a low usage efficiency of exits. Compared with the influence of other factors, the inhomogeneous exit attraction has an obvious effect on the crowd evacuation efficiency.

Characteristics of different personnel have different reactions when faced fire. As large passenger flow and rich personnel types within commercial building, this paper adopt single factor variable analysis method, through the way of questionnaire analysis of social role, type, whether or not accept the training and other single factor of passengers in the commercial buildings variation on evacuation behavior. The survey results show that: the role of passengers on evacuation behavior is more worker selection confirmation of fire or try to put out the fire, while more customers choose escape. The types of passengers on evacuation behavior is more adult women, the elderly and children choose escape immediately, while adult men try to extinguish the fire; when the exit is crowed, the elderly and children choose waiting for in situ, while adult men and women choose to ease crowd evacuation for a much higher percentage than other types of passengers. Training and exercises on evacuation behavior is received fire drill or training passengers choose the nearest safe exit evacuation and active guidance of crowd evacuation in a significantly higher than the proportion of did not received.

Efficient simulation approaches help managers develop effective evacuation plans in the event of an emergency. To determine the optimal routes for rescue and evacuation in a complex building, we introduce a data model to express the topological and geometrical relationships of the building's inner structures. Compared with the other related models, our approach represents the topological relations and geometric properties of the building features more efficiently. Based on the resulting model, we present a hierarchical route-planning algorithm to find the optimal evacuation paths for quickly guiding evacuees to the exits. At the macro-level, the route-planning algorithm dynamically schedules evacuation routes and evacuation sequences and updates real-time evacuation routes. At the micro-level, individuals' behaviors are simulated during the evacuation process using the social force model, which is based on parallel computation. The experiments show that our method can support large crowd evacuation simulation, and has evacuation efficiency. It simulates evacuee movement and evacuation in complex buildings as well.

Crowd evacuation of a building has been studied over the last decades. In this paper, seven methodological approaches for crowd evacuation have been identified. These approaches include cellular automata models, lattice gas models, social force models, fluid-dynamic models, agent-based models, game theoretic models, and approaches based on experiments with animals. According to available literatures, we discuss the advantages and disadvantages of these approaches, and conclude that a variety of different kinds of approaches should be combined to study crowd evacuation. Psychological and physiological elements affecting individual and collective behaviors should be also incorporated into the evacuation models.

Understanding the characteristics of smoke flow in tunnel fire is very important for tunnel safety. The characteristics of tunnel fire were analyzed. The smoke development in different situations of an engineering example was simulated using commercial CFD software PHOENICS 3.5 by field modeling method. The spreading rules and characteristics of concentration field and temperature field of smoke flow with different longitudinal ventilation speeds were studied, which may provide the theoretical background for evacuation design in tunnel fire. The effective measures of fire rescue and crowd evacuation were also described.

The review presented by Bellomo et al. [1] addresses the modelling approaches employed to represent human behaviour in evacuation in a comprehensive manner. The authors discuss crowd evacuation modelling in light of crisis management, a relevant and current topic given the recent escalation of terrorist threats all over the world. The need for designing buildings for rapid evacuation using crowd evacuation models has been recently raised in important forums [2]. This research area is strictly linked to the field of Fire Safety Engineering.