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As one of the most effective models for human collective motion, the social force model (SFM) simulates the dynamics of crowd evacuation from a microscopic perspective. However, it treats pedestrians as the homogeneous rigid particles, whereas pedestrians are diverse and heterogeneous in real life. Therefore, this paper develops a pedestrian heterogeneity-based social force model (PHSFM) by introducing physique and mentality coefficients into the SFM to quantify physiology and psychology attributes of pedestrians, respectively. These two coefficients can affect the self-driven force by changing the desired speed, thus characterizing the pedestrian heterogeneity more realistically. Simulation experiments demonstrate that the PHSFM designs a more general and accurate theoretical framework for the expression of pedestrian heterogeneity, which realizes special behavior patterns caused by individual diversity. Furthermore, our model provides effective guidelines for the management of crowds in potential research fields such as transportation, architectural science and safety science.

Emergency signage systems provide effective route guidance and evacuation information for pedestrians in case of emergencies such as fire, blackout, and explosion. This paper proposes a modified social force (SF) model to investigate crowd evacuation dynamics taking into account the influence of emergency signs. The perceiving probability model is formulated for the quantitative description of the probability that pedestrians can successfully notice the sign and clearly perceive the guidance information. Simulation experiments and controlled experiments are designed to calibrate the parameters of the proposed model. The effectiveness of the modified SF model is preliminarily verified by comparing the simulation results with experimental data and/or empirical results such as fundamental diagrams and self-organization phenomena. A case study of crowd evacuation simulations at a typical Beijing subway station is conducted to evaluate evacuation performance of three signage distribution schemes, i.e., Maximal Covering (MaxCover), Uniform, and Random, which are proposed by the maximal covering location and empirical approaches, as well as contrasted scheme without emergency signs. The effects of the quantity and distribution of emergency signs on crowd evacuation efficiency are studied quantitatively by simulations. The results show that installing emergency signs can improve evacuation efficiency no matter what distribution scheme is adopted. By choosing an appropriate distribution scheme i.e., MaxCover, the evacuation performance can be further improved and the evacuation time can be significantly reduced.

Crowd evacuation simulation is an important research topic for designing reasonable building layout and effective evacuation routes. The reciprocal velocity obstacles (RVO) model is a pedestrian motion model which is used, but it does not work when complex and multiple obstacles are present in the scene. This paper proposes an improved RVO model with path planning and emotion contagion for crowd evacuation simulation. The model uses the vertices of the obstacles to construct pedestrian path nodes for planning pedestrian evacuation paths. To make the pedestrian evacuation paths simulation results more reasonable, the safety and congestion of the path nodes are considered, to plan the shortest evacuation path. Finally, a contagious disease model is introduced to study the impact of emotion contagion on the evacuation process. A crowd evacuation simulation system is developed, and simulations have been carried out in a variety of scenarios. Experiments show that the model can effectively simulate crowd evacuation, providing a powerful reference for building and layout design.

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.

In an emergency route planning technique, simulating the dynamic crowd has route capacity constraints and global target of evacuating all crowd evacuees. To stimulate the crowd, the new arena is developed to know the real-time situation to face the crowd evacuation on exit point. The crowd evacuation is done with the process of Hybrid Agent Reinforcement Learning (HARL) algorithm consisting of Improved Multi-Agent Reinforcement Learning (IMARL) and State-Action-Reward-State-Action (SARSA). In the proposed work, the appropriate route selection mechanism focused on finding optimum evacuation route(s) is done in the first phase. Dynamic crowd can also be evacuated to find its way with the support of the HARL process in the second phase. The proposed HARL method can also be implemented with multi-objective improved particle swarm optimization (IPSO) technique for crowd simulation. The experimented results demonstrate the effectiveness of stability in the HARL process, which provides an improved performance for crowd simulation

Crowd evacuation simulation is an essential element when it comes to planning and preparation in evacuation management. This paper presents the survey based on systematic literature review (SLR) te...

This paper presents an approach for evasive maneuver against dynamic obstacles in multi-agent navigation in a crowd evacuation scenario. Our proposed approach is based on reciprocal velocity obstacles (RVO) with a different manner to treat the obstacles. We treat all possible hindrances in velocity space reciprocally thus all collision cones generated by other agents and obstacles are treated in the same RVO manner with the key difference in the effort of avoidance. Our approach assumes that dynamic obstacles bear no awareness of navigation space unlike agents thus the avoidance effort lies on behalf of the mobile agents, creating unmutual effort in an evasive maneuver. We display our approach in an evacuation scenario where a crowd of agents must navigate through an evacuation area trespassing zone filled with dynamic obstacles. These dynamic obstacles consist of random motion built based on Brownian motion thus posses an immense challenge for the mobile agent in order to overcome this hindrance and safely navigate to their evacuation area. Our experimentation shows that 51.1% fewer collisions occurred which is denote safer navigation for agents in approaching their evacuation point.

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.

Proactive management at mass gatherings is vital to ensure safe crowd evacuation during emergencies. The increasing number of crowd incidents and casualties during the Hajj season is one of the major concerns for authorities in Saudi Arabia. This study aims to explore and analyze crowd dynamics visiting the Prophet's (PBUH) tomb at the visiting (Ziara) corridor in the Holy Mosque of Madinah under continuous flow conditions. MassMotion was used to optimize the crowd flow rate with density restricted to a safe threshold value for efficient crowd management. A robust regression model has been developed to guide the authorities for the safe and efficient operation of the visiting corridor. The study results showed that the crowd flow beyond 9200 persons/h and waiting time in excess of 42 s in front of Moajha might lead to breakdown condition. The output of this study can be utilized by decision-makers and concerned authorities to take appropriate and timely remedial actions to ensure safe, smooth, and efficient crowd management.

In emergency evacuations, crowds often become congested and stampeded because of extreme panic, resulting in injuries and fatalities. Safety officers can spread positive emotions and reduce crowd panic by issuing information or appeasement, which is an effective way to ensure evacuation safety. However, how to deploy safety officers appropriately and maximize positive emotional contagion to cover the largest number of chaotic individuals is still a challenging problem. To solve this problem, we propose an IoT-based positive emotional contagion (IoT-PEC) method for crowd evacuation. First, we employ IoT technologies to capture the attributes of crowd movement, such as position and velocity. Based on these attributes, the crowd chaos can be quantified by calculating the macroscopic and microscopic entropies. Second, we propose an entropy-based anisotropic emotional contagion model (E-AECM) to achieve the nonuniform positive emotional contagion considering the influence of chaos on the propagation rate. Third, we formulate the problem of safety officer placement as an optimization problem to maximize the positive emotional contagion on the chaos individuals. Finally, we implement a simulation system for crowd evacuation to visualize the results of positive emotion contagion. The proposed method can provide guidance for emergency response management.

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.

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.

The simulation of a crowd evacuating public buildings can be an important reference in planning the layout of buildings and formulating evacuation strategies. This paper proposes an agent-based crowd model; a crowd evacuation navigation simulation model is proposed for the multi-obstacle environment. We introduce the concept of navigation factor to describe the proximity of the navigation point to the exit. An algorithm for creating navigation points in multi-obstacle environment is proposed along with the global navigation and local navigation control algorithms of the crowd. We construct a crowd evacuation simulation prototype system with different simulation scenes using the scene editor. We conduct the crowd evacuation simulation experiment in the multi-obstacle scene, recording and analyzing the relevant experimental data. The simulation prototype system can be used to derive the evacuation time of the crowd and analyze the evacuation behavior of the crowd. It is expected to provide a visual deduction method for crowd management in an evacuation emergency.

It is of crucial importance whether or not evacuees follow the evacuation signs during building evacuation. It is necessary for effective evacuation signs to be designed in a way that helps the occupants follow building safety guidelines. In this paper, 658 evacuation experiments with wearable eye tracking devices were carried out to test the effectiveness of both the setting positions and design of evacuation signs in buildings. There are four factors considered in this paper: (1) position, (2) colour, (3) graphics, and (4) (or flashing). The results show that the effect of the green “arrow” evacuation sign is the best. The effect of low (corridor) signs works better than those of high (room) signs, but the signs of low (corridor) could be blocked by the front evacuees. Obtaining the ratio of people obeying the evacuation signs under different conditions provides an effective basis for the improvement in design for building safety, and provides data support for computer simulation modelling of crowd evacuation.

Behavioral modification using active instructions is a promising interventional method to optimize crowd evacuations. However, existing research efforts have been more focused on eliciting general principles of optimal behavior than providing explicit mechanisms to dynamically induce the desired behaviors, which could be claimed as a significant knowledge gap in crowd evacuation optimization. In particular, we propose using dynamic distancekeeping instructions to regulate pedestrian flows and improve safety and evacuation time. We investigate the viability of using Model Predictive Control (MPC) techniques to develop a behavioral controller that obtains the optimal distance-keeping instructions to modulate the pedestrian density at bottlenecks. System Identification is proposed as a general methodology to model crowd dynamics and build prediction models. Thus, for a testbed evacuation scenario and input?output data generated from designed microscopic simulations, we estimate a linear AutoRegressive eXogenous model (ARX), which is used as the prediction model in the MPC controller. A microscopic simulation framework is used to validate the proposal that embeds the designed MPC controller, tuned and refined in closed-loop using the ARX model as the Plant model. As a significant contribution, the proposed combination of MPC control and System Identification to model crowd dynamics appears ideally suited to develop realistic and practical control systems for controlling crowd motion. The flexibility of MPC control technology to impose constraints on control variables and include different disturbance models in the prediction model has confirmed its suitability in the design of behavioral controllers in crowd evacuations. We found that an adequate selection of output disturbance models in the predictor is critical in the type of responses given by the controller. Interestingly, it is expected that this proposal can be extended to different evacuation scenarios, control variables, control systems, and multiple-input multiple-output control structures., Ministerio de Economía y Competitividad

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.

Cellular Automata (CA) remain actively used to model phenomena as diverse as crowd evacuation, urban planning, or tumors. In their simplest form, CA use a synchronous approach such that cells are updated all together. This perfectly synchronous update has been criticized for lack of realism, as it produces outcomes that may not be obtained with less synchronization. Consequently, CA may use an asynchronous update to overcome some of these artifacts. While numerous works have shown how to scale CA models by parallelizing their synchronous updates, a paucity of research has explored the asynchronous case. We present and empirically evaluate algorithms for efficient parallel executions of two types of asynchronous updates: random order and cyclic order. Our algorithms select random orderings that suit parallel execution and are therefore approximate in nature. Our results suggest that they can effectively leverage parallelism while keeping results well aligned with the sequential baseline implementation.

It is difficult for pedestrians with limited vision to obtain comprehensive environmental information during evacuations, so they cannot always make a proper evacuation plan to escape. For this pur...

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.

Evacuation leaders and&#x002F or equipment provide route and exit information for people and guide them to the expected destinations, which could make crowd evacuation more efficient in case of emergency. The purpose of this paper is to provide an overview of recent advances in guided crowd evacuation. Different guided crowd evacuation approaches are classified according to guidance approaches and technologies. A comprehensive analysis and comparison of crowd evacuation with static signage, dynamic signage, trained leader, mobile devices, mobile robot and wireless sensor networks are presented based on a single guidance mode perspective. In addition, the different evacuation guidance systems that use technology automated methods of evacuation are reviewed from a system&#x02BC s perspective. Future research in the area of crowd evacuation are also discussed.

This paper pertains to the study of finite-time control of one dimensional crowd evacuation system. Benefiting from the research of fluid dynamics and vehicle traffic, a one dimensional crowd evacuation system is constructed, whose density-velocity relationship is represented by a diffusion model. In order to deal with the nondirectionality of crowd movement, the free flow speed is chosen as a control variable. Since the control variable is included in a partial derivative, it increases the difficulty of designing the controller. In this paper, finite-time controller is designed, which not only guarantees the effective evacuation, but also obtains the estimation of evacuation time. Then, finite-time tracking problem is solved, which makes the density converge to a given density. Finally, numerical examples illustrate the effectiveness of the controllers.

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.

This paper proposes an agent-based simulation model with route choice process to predict the crowd behaviours and evaluate the evacuation safety on passenger ships. The model focuses on the behaviours of two common types of passengers that are not typically accounted for during most evacuation analyses, namely, passengers who are not familiar with the ship layout and passengers who have family members or friends with them. In the proposed model, a marker concept is introduced to represent critical routing points of the layout and passenger agents make a route choice based on their surroundings and characteristics instead of just following the shortest routes. The simulation model is tested by two small but targeted scenarios and one comprehensive scenario on a ship deck. For ship designers, a more realistic evacuation time is provided to better assess the evacuation performance of a ship, and a heat map of crowd density is presented to identify possible bottleneck areas.

Pedestrian merging flow in the crowd gathering public places are the common movement nodes of crowd kinematics merging and psychological panic transmission. There are stochastic turbulences, disturbances and density fluctuations in the crowd merging area, with high risk of pedestrian stampede events. Based on the dynamics model of crowd merging, this study considers the psychological characteristics of the escape panic in the normal disaster conditions of the crowd in the cross-passages and the epidemic panic psychological characteristics under the public health events. With the introduction of Shanoon's information entropy theory, panic entropy is applied to measure the degrees of transient panic in the fluid grid area of the crowd, the overall transient disorder of the crowd, and the dynamic relationship with time and space changes. This study comprehensively considers the characteristics of conventional escape panic and epidemic panic, defines protective relaxation factors, forms a dynamic model of escape panic propagation, and provides a scientific theoretical basis for crowd evacuation guidance under COVID-19 epidemic situation.

Crowd stampede accident, as one of the main man-made accidents in large public gathering places, has become a problem that science must face today. In order to explore the formation mechanism of crowd stampede in public places, this paper establishes a theoretical model of crowd evacuation based on multi-agent technology. This paper adopts a combination of theory-modeling-simulation method, with the Bandatia Bridge in India as the background, analyzes the changes in various stages of large-scale crowded stampede accidents from the walking path of the crowd, rationality and irrationality. The experimental results show that the model can simulate the behavior change of the crowd during evacuation, and provide theoretical and technical support for the study of the formation mechanism of crowd stampede.

Excessive cognitive demands, fear, or stress narrow evacuees’ functional fields of view (FFV) in disaster evacuation situations. This tunnel vision hypothesis leads to a new model of evacuee behavior deviating significantly from the previously accepted understanding, and possibly altering conventional evacuation protocol designs. In this study, we analyze the impacts of narrowed vision of evacuees on crowd evacuation efficiency through simulated evacuations. The simulated room to be evacuated included multiple exits, of which only one was correct, as well as a single visual sign designating the correct exit, and an agent found the correct exit via this sign if it was within their FFV. We designed an evacuation decision model for the simulated agents based on herd behavior, including cognitive biases frequently observed during evacuations, to which evacuees were assumed to be subject.

Simulation-based immersive learning serves as an effective means for bridging in-classroom knowledge and real-world practice. Compared with classical lectures based on PowerPoint slides and verbal interpretation, simulation-based immersive learning incorporates additional channels with graphical vision and interactive modes for delivering knowledge. Using simulation technologies in true-to-life settings, students have the freedom to build up their own knowledge base and develop important individual hands-on skills. This chapter aims at investigating the implementation of simulation-based immersive learning and evaluating its benefits in one pilot course offered in the university. We will describe a platform for simulation-based immersive learning and its application to one pilot course. We will also discuss an interactive system within the platform to enable students to reinforce their knowledge through simple practices. The method for assessing learning effectiveness is also depicted. The assessment results indicate certain advantages of the developed simulation-based immersive learning platform.

This paper works on one of the most recent pedestrian crowd evacuation models&mdash, i.e., &ldquo, a simulation model for pedestrian crowd evacuation based on various AI techniques&rdquo, &mdash, which was developed in late 2019. This study adds a new feature to the developed model by proposing a new method and integrating it into the model. This method enables the developed model to find a more appropriate evacuation area design regarding safety due to selecting the best exit door location among many suggested locations. This method is completely dependent on the selected model&rsquo, s output&mdash, i.e., the evacuation time for each individual within the evacuation process. The new method finds an average of the evacuees&rsquo, evacuation times of each exit door location, then, based on the average evacuation time, it decides which exit door location would be the best exit door to be used for evacuation by the evacuees. To validate the method, various designs for the evacuation area with various written scenarios were used. The results showed that the model with this new method could predict a proper exit door location among many suggested locations. Lastly, from the results of this research using the integration of this newly proposed method, a new capability for the selected model in terms of safety allowed the right decision in selecting the finest design for the evacuation area among other designs.

In order to study the effect of panic group behavior on the efficiency of crowd evacuation in emergencies, a crowd emergency evacuation model was constructed based on the theory of big data technology and ant colony algorithm. The panic factor and panic group factor are considered in the model, making the model closer to the actual situation. Based on the complexity of model calculation, the ant colony algorithm is used to solve the model. The research results show that in the emergency evacuation process, attention needs to be paid to the evacuation of key nodes (current restricted areas), and due to the different effects of the panic degree of the evacuated crowd in the evacuation road network on the road sections, attention should be paid to the evacuation process of key road sections to avoid occurrence Crowded stampede and other incidents.

Human relationships are a common characteristic of pedestrians and have important effects on evacuation behavior. Moreover, the presence of leaders also affects the evacuation efficiency of the crowd. Few scholars considered the influence of social relationships and leaders on group evacuation behavior. Motivated by the need an optimization model named PD-SLEM is proposed for simulating the outdoor crowd evacuation during earthquake considering the impact of social relationships and leaders. Depending on the willingness to escape together with partners, multiple social relationships are abstractly classified into three aggregation relationships. Experiment results demonstrate that leaders in the crowd, especially professional disaster relief volunteers, significantly improve the evacuation efficiency.

This paper takes Wuhan metro type A and B vehicles for example, using a simulation method to study the passenger evacuation capability of different metro vehicles. Firstly, the dimensions and interior layout of the two types of carriages have been investigated and compared. Then, passenger evacuation simulation models of these two types of vehicles have been simulated by AnyLogic software. The relationship between the occupant load and the crowd evacuation timeframe was studied under different metro vehicle type. The validation results show that the simulation models are suitable for metro carriage evacuation researches. Through model simulation, it can be seen that, the crowd evacuation time is linear with the number of passengers with correlation coefficients R2 higher than 0.99. The interior space including the number of doors, the width of the carriage, the number of grab poles and the effective area of the carriage are all affect the evacuation efficiency of passengers. Under the condition of full occupancy, the evacuation efficiency of type A vehicle is 14% higher than that of type B.

Development of crowd evacuation systems is a challenge due to involvement of complex interrelated aspects, diversity of involved individuals and/or environment, and lack of direct evidence. Evacuation modeling and simulation is used to analyze various possible outcomes as different scenarios unfold, typically when the complexity of scenario is high. However, incorporation of different aspect categories in a unified modeling space is a challenge. In this paper, we addressed this challenge by combining individual, social and technological models of people during evacuation, while pivoting all these aspects on a common agent-based modeling framework and a grid-based hypothetical environment. By simulating these models, an insight into the effectiveness of several interesting evacuation scenarios is provided. Based on the simulation results, a couple of useful recommendations are also given. The most important recommendation is not to use potential field indicating the exits dynamics as an exit strategy particularly for a spatial complexity environment.

In recent years, people’s demand for data analysis and knowledge acquisition from big data is becoming more urgent. Large-scale crowd evacuation also requires a wealth of decision-making knowledge to provide emergency solution guidance. This paper corresponds the crowd size to the granularity of knowledge objects, and proposes a variablegrained knowledge acquisition model for the evolution mechanism of crowd evacuation stability. The rough set matrix calculation model is used to generate the meta-rules. Through the rigorous discretization of the reversible process analysis logic, the meta-rules are automatically simplified into generalized rules with evacuation guiding significance. The explicit knowledge of stability situation in crowd evacuation is discovered. This study provides a scientific decision-making method for timely and accuratejudgment of the crowd stability, rational organization and guidance of safe evacuation, and also provides scientific basis for the prevention of malignant crowding and trampling events with important theoretical and social significance.

Evacuation can be the most necessary and effective method to save human lives in emergency scenarios due to natural or human-caused disasters. The emergency egress behavior of humans is not...

Simulation on crowd evacuation has attracted plenty of attention in the past few years. Emotion plays a significant role in human decision making processes and on the behaviors during the evacuation. Moreover, grouping is a common phenomenon in crowds, and there are a lot of roles included in a group. In this paper, we present a unified framework to model the structure aspect of the groups with emotion for a crowd suffering fires and explosions in public areas. The proposed evacuation framework consists of two components: (1) an emotion model for various roles in the case of an emergency. Emotional changing is a complex process where different roles are influenced by different factors. (2) Both intra-group structure and inter-group relationship are considered to simulate the herd phenomenon in emergency. The structure and behaviors of a group are related to the emotions of different roles. A follower can decide whether to leave the group or not according to the emotion of the group leader and the one of his own, thus the members of the group may always dynamically change. Simulation results show that the developed framework can practically model the emotion changing and different group structures of evacuation crowds.

In the last decades, a series of terrible accidents happened within pedestrian crowds, which makes crowd dynamic a significant issue to be investigated. Literature reviews show that pedestrian flow presents different features within different architectural layout. In this paper, pedestrian movement properties at bottleneck are studied by carrying out series of experiments under laboratory condition. The influence of door sizes and exit locations on pedestrian crowd flow is investigated. It was found that larger door width resulted in shorter evacuation time and faster flow rate. By comparing the fundamental diagram among crowd evacuation, the average velocity increases as the width increases under the same density condition. Interestingly, the influence of the boundary layer, as well as the effective width on pedestrian crowd dynamic, was clearly observed. Our results suggest that the combination of exit width and location resulted in a synergistic effect, but the exit widths gradually became the most important factor influencing the flow rate.

Crowd evacuation has attracted great attention, the number of emergencies continues to increase. Thanks to the technology, it is possible to deduce the behavior of the crowd in emergencies, improving security. The multitude enters into a state of panic, so it is necessary to have action protocols for these situations. This work tries to establish a multi-agent model of emotional contagion that simulates the behavior of the crowd in an evacuation. The method is proposed for closed areas such as supermarkets, stadiums, soccer, stadiums, etc. The emotional contagion will accelerate the evacuation, but the congestion will occur if the panic emotion is spread too fast.

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.

Understanding the evacuation mechanism has been important subject nowadays in order to model the simulation on the pedestrian behavior in crowd evacuation for the case study of fire emergency scenario in the building. Almost two decades the interest of Social Force Model (SFM) in pedestrian traffic increased significantly as a microscopic model to have a realistic simulation model. The social interactions between the pedestrian is emergent phenomena and very hard to capture, rare and evasive maneuvers in order to avoid collisions between the agents or so called as pedestrians. SFM has been chosen to simulate and modeling the case study based on the crowd dynamic, pedestrian dynamic and evacuation dynamic.