Crowd Evacuation Research Articles

Discrete modeling approach for emergency guidance signage system design in underground spaces: A case study in transportation hubs

Emergency guidance signage systems (EGSSs) are widely used to guide crowd evacuation in underground spaces. However, the absence of signs often reduces the evacuation efficiency. Current methods for EGSS design suffer from challenges associated with complex evacuee-signage interactions, guidance demand determination and numerous potential sign locations. The present article investigates a discrete approach to EGSS design. To this end, a cell-based discretization method is proposed to abstract the guidance demand and potential sign locations. To design an EGSS that can efficiently convey guidance information to evacuees, an interaction model, which is determined by the cognitive capabilities of moving evacuees and the characteristics of signs, is proposed for analyzing the guidance relationship between evacuees and signs with different locations and orientations. An EGSS design model is formulated to recommend the optimal number, location, and installation orientation of signs, and a wayfinding simulation model is proposed to validate the obtained design plan. Finally, a real-world case study is used to demonstrate the effectiveness and advantages of the proposed methods.

Crowd Emergency Evacuation Simulation Time Analysis via Obstacle Optimization Strategy

The crowd evacuation simulation is essential to provide important results for occupants, especially in the large capacity building compared to the human fire drill exercise. The strategy of evacuation such as the use of obstacles may need to be adapted by many organizations as an aid to help in visualizing and estimating the evacuation time during an emergency. During certain crowd events, they may consider the various setting of the object to ensure smoothness and effective crowd evacuation flow. In this paper, it aims to provide the simulation with 100-1000 agents and testing with obstacle using Anylogic tool and analysis of evacuation time validated using SPSS. The results show that the placement of obstacles near the exit way indeed can reduce the evacuation time and complies with the anti-arching phenomenon during evacuation.

State-of-the-Art Development of Complex Systems and Their Simulation Methods

The research on complex systems is different from that on general systems because the former must consider self-organization, emergence, uncertainty, predetermination, and evolution. As an important method to transform the world, a simulation is one of the most important skills to discover complex systems. In this study, we provide a survey on complex systems and their simulation methods. Initially, the development history of complex system research is summarized from two main lines. Then, the eight common characteristics of the most complex systems are presented. Furthermore, the simulation methods of complex systems are introduced in detail from four aspects, namely, meta-synthesis methods, complex networks, intelligent technologies, and other methods. From the overall point of view, intelligent technologies are the driving force, and complex networks are the advanced structure. Meta-synthesis methods are the integration strategy, and other methods are the supplements. In addition, we show three complex system simulation examples: digital reactor simulation, simulation of a logistics system in the industrial site, and crowd evacuation simulation. The examples show that a simulation is a useful means and an important method in complex system research. Finally, the future development prospects for complex systems and their simulation methods are suggested.

Crowd Evacuation Simulation Research Based on Improved Reciprocal Velocity Obstacles (RVO) Model with Path Planning and Emotion Contagion

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.

Research on the influence of building convex exit on crowd evacuation and its design optimization

Research on the influence of building convex exit on crowd evacuation and its design optimization

Research and realization of parallel algorithms for large scale crowd evacuation in emergency

Based on the cellular automata evacuation model which is on the basis of triangular meshing, the CPU-based parallel algorithm is applied to enhance the efficiency of the evacuation simulation algorithm which analyzes the model from the aspects of correctness, speedup, and scalability. Compared its operation results with those of the existing software pathfinder based on Agent algorithm, the results show that the cellular automata model is more efficient in evacuation of high-density and high-traffic scenes with an acceleration ratio of 300% without congestion. The scalability of the parallel algorithm makes large-scale scenarios more confronted with actual status, real-time monitoring, and a simulation plan for evacuation providing in time.

An automatic decision algorithm and simulation performance analysis for public safety

As the current society is increasingly facing major challenges from extremism and terrorism, protecting key urban public facilities and important targets from destruction is an important challenge facing the security departments of all countries. Based on real scene, this paper conducts researches on anti-terrorism security game algorithms and emergency response models in response to the three key links of before, during and after terrorist attacks. First of all, this paper constructs a multi-round joint attack game and emergency response model based on cooperation, establishes the optimization problem of solving the defender’s optimal strategy in mathematical form, and then obtains the optimal defense strategy. Secondly, in response to the fact that terrorists are not completely rational, a new hybrid model is constructed to propose an efficient allocation and scheduling algorithm for safe resources in response to terrorist attacks. Thirdly, a model of crowd evacuation strategy after a terrorist attack is built based on the problem of crowd evacuation in multiple rounds of premeditated cooperative attacks. Finally, taking the area of the first ring of a certain city as a real scene, a complete game system of the whole process is constructed, and the game effectiveness evaluation of the existing security resource allocation scheme in the first ring area is carried out. Through the research of this thesis, the author puts forward some new technical ideas for the current society’s anti-terrorism governance, and hopes to provide some technical references for the decision-making of security agencies.

Synchronized Data Collection for Human Group Recognition.

It is commonplace for people to perform various kinds of activities in groups. The recognition of human groups is of importance in many applications including crowd evacuation, teamwork coordination, and advertising. Existing group recognition approaches require snapshots of human trajectories, which is often impossible in the reality due to different data collection start time and frequency, and the inherent time deviations of devices. This study proposes an approach to synchronize the data of people for group recognition. All people’s trajectory data are aligned by using data interpolating. The optimal interpolating points are computed based on our proposed error function. Moreover, the time deviations among devices are estimated and eliminated by message passing. A real-life data set is used to validate the effectiveness of the proposed approach. The results show that 97.7% accuracy of group recognition can be achieved. The approach proposed to deal with time deviations was also proven to lead to better performance compared to that of the existing approaches.

Fast Crowd Evacuation Planning System for Disaster Management

Last few decades witnessed the occurrence of various natural and man-made disasters that were difficultto control, thereby leading to heavy casualties. To overcome these, preventive measures likethe design of the building, coordinated pre-planning, etc., needs to be done. To reduce the casualtiesduring fire disaster and to enhance the evacuation efficiency, it is important to consider the impactof factors which influence the evacuation. The effect of human and fire factors depend on strategiesused for evacuation in the building architecture. This paper presents a method for fast crowd evacuationand safety management, thereby improving the efficiency of evacuation.

Macroscopic View: Crowd Evacuation Dynamics at T-Shaped Street Junctions Using a Modified Aw-Rascle Traffic Flow Model

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

Emergency Planning for UAV-Controlled Crowd Evacuations

One of the most challenging problems during disasters involving crowds is pedestrian evacuation. It is very important in such situations to improve survival rates by getting all or most of the people out in the shortest possible time. Technological intervention through augmenting the evacuation process using an unmanned aerial vehicle (UAV) exhibits great potential in improving survival rates, but the exploration of this method is still in its infancy. Therefore, this study explores the potential of utilizing UAVs for crowd management during emergency evacuations. We conducted a rigorous study, using a simulation model featuring four UAVs and differing numbers of pedestrians, with use of two UAV guidance approaches: partial guidance and full guidance. The experimental results suggest that exploiting UAVs in crowd evacuation and following the partial guidance approach can lead to a more efficient evacuation process.

Experiment and simulation study of emergency evacuation during violent attack in classrooms

In recent years, as a disaster, terrorist attacks have occurred throughout the world. However, emergency evacuation behaviors during these incidents were not clear, and the traditional emergency plans were not suitable for such incidents. In this paper, evacuation behaviors under armed assault attack in a classroom were studied based on evacuation experiments. A total of 103 participants took part in three experiments. In each experiment, the attacker's attacking route was set differently to study the impact of the attacking route on evacuation behaviors. Pre-evacuation delay, panic of the evacuees, exit choices, evacuation time, and evacuees’ trajectories in the experiments were all analyzed. The results of the experiments showed that when a terrorist attack occurs, there is a long delay before evacuation, and most of the evacuees were in the state of “observation” before they moved. When one of the participants started to evacuate or shout, other participants would begin to recognize the danger and escape quickly. These three experiments showed that the route of the attacker had a significant impact on the routes and exit choices of the evacuees. Rather than searching for the nearest exit, the primary purpose of evacuees was to keep a safe distance from the attacker. The average speed of the evacuees in these three experiments was 1.07 m/s, 0.81 m/s, and 0.84 m/s, respectively. The density distribution during the crowd evacuation process was uneven, with the highest density occurring at the area from the seats to the aisles. The research can provide data support for the design of emergency plans and the computer simulation of the armed assault attack.

Modeling the dynamics of pedestrian evacuation in a complex environment

The study of crowd evacuation dynamics is important for the management of public safety, and crowd evacuation dynamics models can be used to simulate the behaviors of pedestrians during an evacuation. In this paper, we propose a new force model for simulation of the evacuation of complex environments. In comparison to existing models, this model considers more environmental factors to make it applicable to complex emergency environments. By verification using real data, the model is demonstrated to be able to predict evacuation efficiency and better reproduce the microscopic behavior of pedestrians under extreme conditions. We discuss the impact of the presence of different kinds of hazards and different types of obstacles in the environment on pedestrian evacuation performance and put forward suggestions for crowd evacuation management.

A chain navigation grid based on cellular automata for large-scale crowd evacuation in virtual reality

Large-scale crowd evacuation simulation in virtual reality is of great significance for emergency response. However, the existing large-scale crowd evacuation simulation methods are challenging to apply to the virtual reality scene. Thus, the efficiency of large-scale crowd rendering in virtual reality needs to be improved. Here we proposed a chain navigation grid for virtual reality large-scale crowd evacuation simulation. The objective of this study was to apply traditional cellular automata crowd evacuation simulation algorithms to virtual reality scenes through a chain navigation grid. Combined with the characteristics of crowd movement, we proposed the vertex raster rendering method to efficiently visualize large-scale crowds in virtual reality scenes. Finally, we constructed two evacuation scenes and carried out experimental analyses. The results show that the chain evacuation navigation grid can transform the discrete crowd movement of cellular automata into continuous crowd movement in virtual reality and can connect multiple cellular automata corresponding to multi-floors. Compared with the evacuation results of Pathfinder software, the chain evacuation navigation can add the factor of environmental familiarity. Therefore, this study improved evacuation simulation by increasing about 6% efficiency in time and computing process. Compared with the traditional crowd evacuation rendering method, the vertex raster rendering method increases the maximum number of people rendering from 2 times to 31 times.

Deep deterministic policy gradient algorithm for crowd-evacuation path planning

In existing evacuation methods, the large number of pedestrians and the complex environment will affect the efficiency of evacuation. Therefore, we propose a hierarchical evacuation method based on multi-agent deep reinforcement learning (MADRL) to solve the above problem. First, we use a two-level evacuation mechanism to guide evacuations, the crowd is divided into leaders and followers. Second, in the upper level, leaders perform path planning to guide the evacuation. To obtain the best evacuation path, we propose the efficient multi-agent deep deterministic policy gradient (E-MADDPG) algorithm for crowd-evacuation path planning. E-MADDPG algorithm combines learning curves to improve the fixed experience pool of MADDPG algorithm and uses high-priority experience playback strategy to improve the sampling strategy. The improvement increases the learning efficiency of the algorithm. Meanwhile we extract pedestrian motion trajectories from real motion videos to reduce the state space of algorithm. Third, in the bottom layer, followers use the relative velocity obstacle (RVO) algorithm to avoid collisions and follow leaders to evacuate. Finally, experimental results illustrate that the E-MADDPG algorithm can improve path planning efficiency, while the proposed method can improve the efficiency of crowd evacuation.

Dynamic Decision-Making Process of Evacuees during Post-Earthquake Evacuation near an Automatic Flap Barrier Gate System: A Broken Windows Perspective

The automatic flap barrier gate system (AFBGS) plays a critical role in building security, but it is more vulnerable to natural hazards than common exits (including power failure, due to earthquakes, and delayed evacuation, due to safety certification, etc.). This article considers a dynamic decision-making process of evacuees during post-earthquake evacuation near an AFBGS. An interesting metaphor, broken windows (BW), is utilized to interpret people’s actual behavior during evacuation. A multi-stage decision-making mechanism of evacuees is developed to characterize the instantaneous transition among three defined stages: Habitual, mild, and radical states. Then, we build a modified three-layer social force model to reproduce the interaction between evacuees based on an actual post-earthquake evacuation. The simulations reveal that BW provides a contextualized understanding of emergency evacuation with a similar effect to the traditional metaphor. An earlier appearance of a mild rule breaker leads to a higher crowd evacuation efficiency. If evacuees maintain the state of broken windows behavior (BWB), the crowd evacuation efficiency can be improved significantly. Contrary to the criminological interpretation, the overall effect of mild BWB is positive, but the radical BWB is encouraged under the command of guiders.

Research on Path Planning Algorithm for Crowd Evacuation

In recent years, crowded stampede incidents have occurred frequently, resulting in more and more serious losses. The common cause of such incidents is that when large-scale populations gather in a limited area, the population is highly unstable. In emergency situations, only when the crowd reaches the safe exit as soon as possible within a limited evacuation time to complete evacuation can the loss and casualties be effectively reduced. Therefore, the safety evacuation management of people in public places in emergencies has become a hot topic in the field of public security. Based on the analysis of the factors affecting the crowd path selection, this paper proposes an improved path-planning algorithm based on BEME (Balanced Evacuation for Multiple Exits). And pedestrian evacuation simulation is carried out in multi-exit symmetrical facilities. First, this paper optimizes the update method of the GSDL list in the BEME algorithm as the basis for evacuating pedestrians to choose an exit. Second, the collision between pedestrians is solved by defining the movement rule and collision avoidance strategy. Finally, the algorithm is compared with BEME and traditional path-planning algorithms. The results show that the algorithm can further shorten the global evacuation distance of the symmetrical evacuation scene, effectively balance the number of pedestrians at each exit and reduce the evacuation time. In addition, this improved algorithm uses a collision avoidance strategy to solve the collision and congestion problems in path planning, which helps to maximize evacuation efficiency. Whether the setting of the scene or the setting of the exit, all studies are based on symmetric implementation. This is more in line with the crowd evacuation in the real scene, making the experimental results more meaningful.

Modelling Route Choice in Crowd Evacuation on Passenger Ships

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.

Unidirectional pedestrian flow in a corridor involving individuals with disabilities: a modified floor field modelling approach

In this paper, a modified floor field model is presented to study crowd dynamics involving individuals with disabilities (i.e. pedestrians on crutches, seniors with sticks, pedestrians in manual wheelchairs and blind pedestrians). Multi-speed characteristics, overtaking and helping behaviors are considered in our model. Through simulations in unidirectional pedestrian flow in a corridor, it is observed that overtaking behavior has a positive effect on pedestrian flow at low density. Helping behavior can significantly improve the maximum flow rate and critical density of a system. In comparison with overtaking behavior, helping behavior is more beneficial to heterogeneous crowd movement, when density is higher than the critical density. The phenomenon that the proportion of individuals with disabilities has a negative influence on crowd movement efficiency is reproduced. It is hoped that this study will enrich movement rules and modeling approaches for individuals with disabilities, and be helpful in crowd management and evacuation organization.

Recurrent emotional contagion for the crowd evacuation of a cyber-physical society

In recent years, emotional contagion has drawn great attention in the field of public security since it often leads to stampedes and crushes during large-scale emergencies. To date, there have been many studies on emotional contagion in both cyberspace and physical space, bringing a strong impetus to the simulation of crowd evacuation in emergencies. However, due to the heterogeneity of crowds in cyberspace and physical space, emotional contagion is rarely comprehensively considered in the cyber-physical society (CPS). In addition, the characteristics of emotional recurrence prone to appear in large-scale evacuation have not yet been fully elucidated. Therefore, the existing models cannot accurately describe the real situation of emotional contagion since there is a wide deviation between it and the reality. To solve this problem, we propose a recurrent emotional contagion (REC) method for crowd evacuation of the CPS. First, we construct a CPS-oriented REC model by considering the influence of emotional recurrence on the emotional contagion process. Second, we build the degree-based Mean-Field Equations to describe the dynamic evolution of the number of individuals while considering the heterogeneity of crowds. Furthermore, we use the Finite Difference Method to derive the numerical solution. Third, we construct recurrent small-world networks, which constitute a special case of CPS-REC, to verify the effectiveness of our model. Finally, we implement a crowd simulation system based on the CPS-REC model to visualize the results of our theoretical analysis. The experimental results show that our method can more realistically simulate the emotional contagion process.