Large-scale Crowd Evacuation Research Articles

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.

Assessment model for the Stability Situation of Crowd Evacuation based on Thermodynamic Map

To solve the shortcomings of the conventional assessment methods for crowd evacuation stability, such as over-reliance on the experience of the judges, obvious subjectivity and time-space limitations, this paper proposes an assessment model for judgment on the stability situation of crowd evacuation. Furthermore, the scenarios of large-scale crowd evacuation is diverse, and the compositions of crowd, the causes of crowd trampling are different. So it is particularly important to analyze specific problems for different scenarios. However, different data acquisition and poor real-time performance are main practical problems of judgment on the stability situation of large-scale crowd evacuation. With regard to shortcomings and problems above, the assessment model proposed in this paper uses big data technology to figure out a real-time crowd distribution thermodynamic map and obtain the crowd distribution density data. According to the criterion of crowd stability proposed by the Green Guide in Britain, the assessment model is further constructed to judge the stability situation of large-scale crowd evacuation in real-time.

Control Strategies for Crowd Emotional Contagion Coupling the Virtual and Physical Cyberspace in Emergencies

Crowd emotional contagion occurs in both virtual and physical cyberspace at the same time. To realistically simulate the process of crowd emotional contagion, the influences of virtual cyberspace and physical cyberspace should be considered comprehensively. In addition, control strategies significantly affect the speed and scale of emotional contagion in a crowd. However, control strategies described by existing studies are inaccurate since few of them consider both physical and virtual cyberspace to jointly study the influence of control strategies on crowd emotional contagion. To achieve more accurate control, we first establish a novel personalized emotional contagion computational (NP-ECC) model to study control strategies of crowd emotional contagion coupling the physical and virtual cyberspace. Second, we construct a personalized BA scale-free network to calculate the phase transition threshold of the proposed NP-ECC model more accurately. Finally, we propose two algorithms, control strategies-BA (CS-BA) and threshold-BA (T-BA), to verify the stability of the NP-ECC model and the accuracy of the phase transition threshold, respectively. The experimental results show that our method can better control the speed and scale of crowd emotional contagion and thus can provide guidance for a large-scale crowd evacuation.

A Vehicle Route Planning Method of Two-Phase Large-Scale Crowd Evacuation in Typhoon Relief Activities

Large-scale crowd evacuation is an important measure guaranteeing the safety of disaster-stricken victims in typhoon relief activities. Decision-making related to antityphoon crowd evacuation must take full consideration of the destructive effect of typhoons and their secondary disasters, time urgency, and resource limitation. To give full play to limited vehicle resources, the influence of a typhoon and its secondary disasters on antityphoon evacuation are mainly manifested during the execution of evacuation tasks in this article. The shortest time spent in completing all evacuation tasks was taken as the objective. Then, a vehicle route selection model for two-phase large-scale antityphoon crowd evacuation was built under an uncertain environment, and a matrix encoding–based genetic algorithm was designed to solve the model. Under the background of Super Typhoon Meranti in 2016, the model and algorithm were applied to crowd evacuation in a typhoon in Xiamen for a simulated analysis. Results indicate that in typhoon relief activities, emergency decision makers can use the proposed method to acquire a scientific and reasonable route selection scheme for antityphoon crowd evacuation according to related typhoon disaster data.

Study on large-scale crowd evacuation method in cultural museum using mutation prediction RFID

The cultural museum is one of the places with a large flow of people. Once an emergency occurs, if the people are not evacuated in time, the consequences will be unimaginable. In the event of an emergency, the population speed and evacuation effect are linear in the case of a small population density. However, when the population density is large, the population speed and evacuation effect are nonlinear. The traditional method is aimed at evacuation control with a small density and a smooth change in a large flow of people. When the density is large, the evacuation speed cannot be too fast, and once the pedalling event occurs, the stability of the model is destroyed. In order to solve the above problems, this paper takes a large-scale crowd of cultural museum as the studied object and proposes a large-scale crowd evacuation method based on the mutation theory of RFID (radio frequency identification). The algorithm uses the mutation prediction RFID to judge the arrival rate change trend by the arrival rate reverse mutation rule, so that the modelling length can dynamically adapt to the RFID tag arrival rate change and overcome the contradiction between the prediction accuracy and the tracking speed. The accuracy of the algorithm to predict the flow of large-scale people is improved, making the evacuation model more relevant to the actual situation. Through the experiment tests on typical scenes, the evacuation control problems of four groups of people are analysed and discussed. The results prove that the evacuation method proposed in this paper can provide guidance for crowd evacuation in the cultural museum.

Fuzzy neural network based scenario features extraction and mapping model for crowd evacuation stability analysis

The scenario features of large-scale crowd evacuation are complex and uncertain, leading to difficulties in making intelligent decisions for crowd evacuation stability. Therefore, this paper utilizes a fuzzy neural network method to analyze and extract main crowd scenario features. Subsequently, the stability characteristics as evacuation historical backtracking can be the attributes for evacuation stability judgment. Finally, we can obtain mechanism causes of instability and state evolution law of crowd evacuation, to intervene and guide the large-scale crowd evacuation.

Can cooperative behaviors promote evacuation efficiency?

This study aims to get insight into the question whether cooperative behaviors can promote the evacuation efficiency during an evacuation process. In this work, cooperative behaviors and evacuation efficiency have been examined in detail by using a cellular automata model with behavioral extension. The simulation results show that moderate cooperative behaviors can result in the highest evacuation efficiency. It is found that in a mixture of cooperative and competitive individuals, more cooperative people will lead to relatively high evacuation efficiency, and the larger subgroup will play a leading role. This work can also provide some new insights for the study of cooperative behaviors and evacuation efficiency which can be a scientific decision-making basis for emergency response involving large-scale crowd evacuation in emergencies.

Crowd Evacuation Simulation Based on WebGIS

In order to improve the efficiency of people evacuation from hazardous regions and reduce the ill effects of disasters, a distributed decision support system for large scale crowd evacuation is proposed. The system is supported by the technology of Web Geographic Information System (WebGIS). Basically, by analyzing the system framework we may acquire a novel approach to establish a distributed large-scale crowd evacuation platform for emergency management. Research results show that the proposed system is useful for devising evacuation plans in advance as well as real-time management under disaster.

Principal Aspects Regarding to the Emergency Evacuation of Large-scale Crowds: A Brief Review of Literatures Until 2010

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.

Risk of Large‐Scale Evacuation Based on the Effectiveness of Rescue Strategies Under Different Crowd Densities

Crowd density is a key factor that influences the moving characteristics of a large group of people during a large-scale evacuation. In this article, the macro features of crowd flow and subsequent rescue strategies were considered, and a series of characteristic crowd densities that affect large-scale people movement, as well as the maximum bearing density when the crowd is extremely congested, were analyzed. On the basis of characteristic crowd densities, the queuing theory was applied to simulate crowd movement. Accordingly, the moving characteristics of the crowd and the effects of typical crowd density-which is viewed as the representation of the crowd's arrival intensity in front of the evacuation passageways-on rescue strategies was studied. Furthermore, a "risk axle of crowd density" is proposed to determine the efficiency of rescue strategies in a large-scale evacuation, i.e., whether the rescue strategies are able to effectively maintain or improve evacuation efficiency. Finally, through some rational hypotheses for the value of evacuation risk, a three-dimensional distribution of the evacuation risk is established to illustrate the risk axle of crowd density. This work aims to make some macro, but original, analysis on the risk of large-scale crowd evacuation from the perspective of the efficiency of rescue strategies.