Emergency Evacuation Model Research Articles

A situation-aware emergency evacuation (SAEE) model using multi-agent-based simulation for crisis management after earthquake warning

ABSTRACT Earthquake is a disastrous natural hazard that threatens numerous cities worldwide. The interval between the foreshock and the main event can sometimes last several minutes. Meanwhile, crowd emergency evacuation and finding shelter are vital for search and rescue managers. At the same time, many unpredicted challenges, such as the sudden increase in travel demand, shifts in public behavior, and the change in the regular transport supply, may arise due to evacuation conditions, which lead to different situations. This paper aims to introduce an approach for quick decision-making and timely evacuation response required by establishing a situation-aware system to minimize these risks and ensure the success of the evacuation plans, to support and predict current and future actions within the dynamic space of the crisis. The main contribution is innovating a Situation-Aware Emergency Evacuation (SAEE) model to enable crisis managers and evacuees to make the right decisions by providing timely and reliable information about the situation. This method is utilized in two situations: designing the emergency evacuation plan and finding the shortest/safest routes to reduce travel time for evacuees. Therefore, a hybrid approach is introduced, which involves a Fuzzy Inference System (FIS) and Deep Long Short-Term Memory (DLSTM) algorithm to identify, infer, and extract the existing situation at different levels (e.g. people, vehicles, and surroundings) after a foreshock using multi-agent-based simulation. The method proposed was simulated in the traffic network of District 6 of Tehran, the capital of Iran. The model results show that the evacuees’ spatial knowledge and perception, as well as awareness of the situation of other agents and their surroundings, led to a significant (40%) reduction in the complete evacuation time. This time is considered the most pivotal factor in saving human lives and their arrival in safer areas. The role of situation awareness systems and increasing human cognition and perception can significantly help in this matter.

Modeling of emergency evacuation in high rise buildings considering congestion at stairs based on Markov chains

High-rise buildings are vulnerable to encountering fires or other emergencies at any time, requiring an immediate evacuation of occupants. In the context of building evacuations, various engineering parameters are often utilized to evaluate the time required for people to reach a safe place when descending a staircase. A discrete-time Markov chain model is proposed to evaluate the evacuation time of the occupants in such circumstances by taking into consideration factors like merging at the stairs and congestion on the floor. Based on the congestion probabilities with respect to the number of evacuees in the building and other human behavior factors that slow down the rate of evacuation, non-congested and congested scenarios are evaluated. The effect of the critical parameters that influenced the evacuation process in the high-rise building, such as walking speed, number of evacuees, and effective stair width, is evaluated in both scenarios. The findings indicate an optimal evacuation speed of 0.7–1.4 m/s. The effective width of the stair is suggested to be between 1.6 and 2.4 m using the model. The simulation results are in good accordance with the SFPE method, the NIST egress simulator, and the agent-based model results.

Dynamic Dose-Based Emergency Evacuation Model for Enhancing Nuclear Power Plant Emergency Response Strategies

The safe evacuation of residents near a nuclear power plant during a nuclear accident is vital for emergency response planning. To tackle this challenge, considering the dynamic dispersion of radioactive materials in the atmosphere and its impact on evacuation routes under different meteorological conditions is crucial. This paper develops a dynamic dose-based emergency evacuation model (DDEEM), which is an efficient and optimized nuclear accident evacuation model based on dynamic radiological dose calculation, utilizing an improved A* algorithm to determine optimal evacuation routes. The DDEEM takes into account the influence of radiological plume dispersion and path selection on evacuation effectiveness. This study employs the DDEEM to assess radiological consequences and evacuation strategies for students residing 5 km from a Chinese nuclear power plant. Under various meteorological conditions, including the three typical meteorological conditions, random ordered and random unordered meteorological sequences, optimal routes obtained through the DDEEM effectively reduce radiological dose exposure and mitigate radiation hazards. The results indicate that all evacuation paths generated by the DDEEM have a maximum dose of less than 1 mSv. Through simulations, the model’s effectiveness and reliability in dynamic radiological environments in terms of radiological consequences and evacuation analysis is verified. The research provides valuable insights and a practical tool for nuclear power plant emergency decision-making, enhancing emergency management capabilities during nuclear accidents. The DDEEM offers crucial technical support and a solid foundation for developing effective emergency response strategies.

Exposure risk and emergency evacuation modeling of toxic gas leakage in urban areas under the influence of multiple meteorological factors

Frequent toxic gas leakage accidents in urban environments cannot be timely controlled and often cause great harm due to the many factors affecting gas diffusion. In this study, based on the coupling method of the Weather Research and Forecasting Model (WRF) and the open source OpenFOAM software platform, the chlorine gas diffusion process at different temperatures, wind speeds, and wind directions in a chemical laboratory and nearby urban areas in Beijing was studied numerically. A dose-response model was used to calculate chlorine lethality and assess exposure risk at the pedestrian level. To predict the evacuation path, an improved ant colony algorithm, a greedy heuristic search algorithm based on the dose-response model, was applied. The results demonstrated that the combination of WRF and OpenFOAM could consider the effects of various factors such as temperature, wind speed, and wind direction on the diffusion of toxic gases. The direction of chlorine gas diffusion was affected by wind direction, and the range of chlorine gas diffusion was affected by temperature and wind speed. The area of high exposure risk (fatality rate above 40%) at high temperatures was 21.05% larger than that at low temperatures. When the wind direction was opposite the building, the high exposure risk area was 78.95% smaller than that under the building direction. The present work provides a promising approach for exposure risk assessment and evacuation planning for the emergency response to urban toxic gas leakage.

Emergency Evacuation Simulation Study Based on Improved YOLOv5s and Anylogic

With the development of the social economy and the continuous growth of the population, emergencies within field stations are becoming more frequent. To improve the efficiency of emergency evacuation of field stations and further protect people’s lives, this paper proposes a method based on improved YOLOv5s target detection and Anylogic emergency evacuation simulation. This method applies the YOLOv5s target detection network to the emergency evacuation problem for the first time, using the stronger detection capability of YOLOv5s to solve the problem of unstable data collection under unexpected conditions. This paper first uses YOLOv5s, which incorporates the SE attention mechanism, to detect pedestrians inside the site. Considering the height of the camera and the inability to capture the whole body of the pedestrian when the site is crowded, this paper adopts the detection of the pedestrian’s head to determine the specific location of the pedestrian inside the site. To ensure that the evacuation task is completed in the shortest possible time, Anylogic adopts the principle of closest distance evacuation, so that each pedestrian can leave through the exit closest to him or her. The experimental results show that the average accuracy of the YOLOv5s target detection model incorporating the SE attention mechanism can reach 94.01%; the constructed Anylogic emergency evacuation model can quickly provide an evacuation plan to guide pedestrians to leave from the nearest exit in an emergency, effectively verifying the feasibility of the method. The method can be extended and applied to research related to the construction of emergency evacuation aid decision-making systems in field stations.

Visualization of Emergency Evacuation Physical Behavior under Multi-Agent Decision-Making

Emergency evacuation simulation is significant for architectural design and emergency plan implementation. To explore the influence of evacuees’ physical behavior and evacuees’ decisions on the evacuation process, as well as to address the problems of traditional emergency evacuation models with insufficient detail of the situation (realism), low reusability, poor operability, and lack of subsequent scalability, this paper first analyzed pedestrian characteristics in emergencies. To describe pedestrian decision-making in an emergent evacuation situation, a multi-agent design based on decision theory was proposed, solving the multi-agent decision-making problem in an emergency evacuation environment by the A* algorithm. Then the designed multi-agent was embedded into the social force model by AnyLogic software. Finally, the model reproduces the pedestrian evacuation process in an emergency evacuation situation on the built platform, depicting three kinds of typical behaviors: pedestrian partnering, obstacle avoidance, and exit competition. In addition, this study also analyzed a large student apartment building by example and proposed corresponding optimization solutions to improve its evacuation capacity through simulation results.

Pedestrian emergency evacuation model based on risk field under attack event

In recent years, stabbings have occurred frequently around the world, often causing serious casualties and property losses. Therefore, using evacuation model to simulate and analyze this type of attack mode is of great significance to personnel safety and social stability. However, in the simulation process, the lack of interaction rules between pedestrians and attackers will seriously reduce the accuracy and credibility of the simulation result. Herein, this article focuses on the pedestrian evacuation under stabbings, we proposed a risk field model for pedestrian movement, its formula referred to the continuous point-source diffusion equation in unbounded space. The influence of the surrounding environment on pedestrian movement was considered comprehensively to set the direction of the force exerted by the attacker, pedestrian movement rules and exit selection mechanism were introduced in details. At the same time, we discuss two different attack strategies for attackers, and carried out virtual reality experiments to analyze the experimenter’s attack modes and compare them with the two pure strategies. Multiple simulations are conducted on the basis of the model to explore the physical significance of model parameters and the influence of attack mode and location on evacuation, and to explore the mechanism of pedestrians’ selection of exits under the condition of multiple exits. At the end of this paper, the simulation results are summarized and suggestions for evacuation under emergencies are provided, which may be helpful to the simulation of pedestrian evacuation under emergencies in the future.

Study on an emergency evacuation model considering information transfer and rerouting: Taking a simplified H-shape metro station hall as an example

Metro has already become one of the main transportation methods in big cities across the world. With the development of metro systems, lots of associated safety issues (e.g., fire accidents and terrorism attacks) have occurred in the past decades. Under such circumstances, studies on the safety evacuation of the metro station hall are very necessary. Due to high human-density, fluent evacuation is important in the metro station hall in emergencies. However, metro station hall evacuation is a complex process, filling with humans of different behavior biases. Selection of evacuation direction usually is influenced by accessing information and human decision-making inevitably. Therefore, the paper proposed an evacuation model based on information transfer and rerouting, mainly concentrating on panic propagation, human decision process and human interaction, in order to examine the effects of these factors on evacuation. Results show that emergency information transmission is crucial in accelerating evacuation since stronger information intensity brought from panic propagation improves the evacuation efficiency. The guidance of human flow during evacuation can unify evacuation behavior and the diversion of the crowd at the exits can make full use of the evacuation capacity of exits. Before the timestamp of 39, which corresponds to the time at which the people reach the exit, the human crowd walking in the corridor generally evacuate faster in the unified direction under the control of the herd mentality model. After that, masses gathered at the exit, and the social force model displays a better evacuation effect because of crowd diversion. Spontaneous rerouting may aggravate the evacuation chaos, while scientific evacuation route guidance and command is more reasonable and reliable. These conclusions will guide the process in making evacuation plans for the metro station hall and provide a new perspective to examine evacuation by considering human factors that are closer to the real situation.

A Novel Emergency Evacuation Model of Subway Station Passengers Considering Personality Traits

Subway station emergencies have caused serious casualties in recent years, so the aim of this research was to develop and establish an evacuation model that considers the OCEAN personality psychological traits to improve the credibility of the emergency pedestrian evacuation simulation. Firstly, the relationship between the personality and psychological stress was established based on the reconstruction of a passenger’s personality traits. Secondly, the relationship between the expected speed and a passenger’s personality traits was modified based on the social force model. Finally, the simulation was carried out using the Anylogic software. The results show that as the value of the personality increases, the evacuation time of personalities ψA and ψC gradually increases, but the opposite effect is observed for personalities ψN and ψE. Similarly, as the value of personality traits increases, the speed of personalities ψA and ψC gradually decreases, but the opposite effect is observed for personalities ψN and ψE. Only during peak periods, as the value of personality traits increases, the density of the connecting area of passengers with personality traits ψA and ψC gradually increases; on the contrary, that of passengers with personality traits ψN and ψE gradually decreases. The conclusion of this study is that different personality traits have different effects on evacuation behavior, which enriches the model of pedestrian evacuation further.

Cybernetics Approach Using Agent-Based Modeling in the Process of Evacuating Educational Institutions in Case of Disasters

In the context of an emergency, evacuating people from a location in the shortest possible time is essential, as is the high degree of safety that people should expect when evacuating. Lately, in Romania there have been more and more fire events generated by different causes. This article will use agent-based modeling to simulate an emergency evacuation model in NetLogo. The model has been used to perform and analyze various scenarios. With the help of NetLogo, we managed to perform 400 simulations with the evacuation of 180 people (students, teachers, and non-teaching staff) based on which we developed several recommendations to streamline the evacuation process in order to reduce the possibility of death. The present research will help to identify the evacuation times from a school, but it will also highlight certain aspects that may occur during the evacuation. The model that was used in this research took into account the individual particularities of the people taking part in the evacuation, emphasizing the effects that form in a crowd of people when evacuating; effects such as the funnel effect, which is caused by the formation of bottlenecks around narrow areas. All these things are part of the analysis of the measurement of entropy of the exhaust system, a problem that has captured all of the specialists’ attention. Finally, solutions have been proposed to improve evacuation time in case of disasters.

Bp-ant colony algorithm: escape the Louvre

With the spread of terrorism in the new era, France has suffered many terrorist attacks in recent years. The new situation calls for a review of emergency evacuation plans for popular destinations. Taking the Louvre Museum as the research object, this paper discusses the emergency evacuation plan in detail. At the same time, in order to make effective planning, this study selects the day with the largest number of visitors to the Louvre Museum as the sample. In the establishment of emergency evacuation model, ant colony algorithm is introduced. The training time of two kinds of traffic evacuation algorithm is given, and BP neural network is used for training. In addition, the dynamic Bottleneck Identification Method Based on fuzzy set theory is used in this study. Through model optimization, the possible bottleneck location is accurately determined. Finally, this paper analyzes the advantages and disadvantages of the model, and gives the specific evacuation routes.

Fire emergency evacuation model of light rail station based on BIM technology

Urban light rail undertakes the mission of escorting passengers to arrive safely. Once a fire accident occurs, it will inevitably have a great negative impact. Therefore, how to effectively carry out emergency evacuation tasks in fire accidents has become one of the problems facing the development of urban rail transit. Based on this, this article first introduces the relevant characteristics of BIM technology and the corresponding advantages, and further its use in urban light rail stations. The application advantages of emergency evacuation strategies are briefly analyzed; then the requirements for the construction of BIM emergency evacuation models are studied; finally, through field investigations, a specific urban rail transit light rail station is taken as an example to construct a BIM building information model for this light rail station. Applying BIM technology to fire protection work in light rail stations, it is expected to improve the efficiency of emergency evacuation of passengers in light rail stations.

Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles

Efficient emergency evacuation is crucial for survival. A very successful model for simulating emergency evacuation is the social-force model. At the heart of the model is the self-driven force that is applied to an agent and is directed towards the exit. However, it is not clear if the application of this force results in optimal evacuation, especially in complex environments with obstacles. In this paper, we develop a deep reinforcement learning algorithm in association with the social force model to train agents to find the fastest evacuation path. During training, we penalize every step of an agent in the room and give zero reward at the exit. We adopt the Dyna-Q learning approach, which incorporates both the model-free Q-learning algorithm and the model-based reinforcement learning method, to update a deep neural network used to approximate the action value functions. We first show that in the case of a room without obstacles the resulting self-driven force points directly towards the exit as in the social force model. To quantitatively validate our method, we compare the total time elapsed when agents escape a room with one door and without obstacles employing the Dyna-Q model with the result obtained using the social-force model. We find that the median exit time intervals calculated using the two methods are not significantly different. We confirm that the proposed method obtains trajectories that minimize the travel time by comparing our results to results generated by geodesics-based adaptive pedestrian dynamics. Then, we investigate evacuation of a room with one obstacle and one exit. We show that our method produces similar results with the social force model when the obstacle is convex. However, in the case of concave obstacles, which sometimes can act as traps for agents governed purely by the social force model and prohibit complete room evacuation, our approach is clearly advantageous since it derives a policy that results in object avoidance and complete room evacuation without additional assumptions. We also study evacuation of a room with multiple exits. We show that agents are able to evacuate efficiently from the nearest exit through a shared network trained for a single agent. Finally, we test the robustness of the Dyna-Q learning approach in a complex environment with multiple exits and obstacles. Overall, we show that our model, based on the Dyna-Q reinforcement learning approach, can efficiently handle modeling of emergency evacuation in complex environments with multiple room exits and obstacles where it is difficult to obtain an intuitive rule for fast evacuation.

Development of a radiological emergency evacuation model using agent-based modeling

In order to mitigate the damage caused by accidents in nuclear power plants (NPPs), evacuation strategies are usually managed on the basis of off-site effects such as the diffusion of radioactive materials and evacuee traffic simulations. However, the interactive behavior between evacuees and the accident environment has a significant effect on the consequential gap. Agent-based modeling (ABM) is a method that can control and observe such interactions by establishing agents (i.e., the evacuees) and patches (i.e., the accident environments). In this paper, a radiological emergency evacuation model is constructed to realistically check the effectiveness of an evacuation strategy using NetLogo, an ABM toolbox. Geographic layers such as radiation sources, roads, buildings, and shelters were downloaded from an official geographic information system (GIS) of Korea, and were modified into respective patches. The dispersion model adopted from the puff equation was also modified to fit the patches on the geographic layer. The evacuees were defined as vehicle agents and a traffic model was implemented by combining the shortest path search (determined by an A ∗ algorithm) and a traffic flow model incorporated in the Nagel-Schreckenberg cellular automata model. To evaluate the radiological harm to the evacuees due to the spread of radioactive materials, a simple exposure model was established to calculate the overlap fraction between the agents and the dispersion patches. This paper aims to demonstrate that the potential of ABM can handle disaster evacuation strategies more realistically than previous approaches.

Emergency evacuation model assuming leakage of toxic substances in a chemical plant

Preparedness of emergency evacuation for the leakage of toxic substances in chemical plants is very important in order to reduce damage. In order to implement an emergency evacuation properly, it is necessary to comprehensively and concretely determine the conditions of the leakage and atmospheric conditions and predict the consequences of the dispersed gases. Repeated training for emergencies is also essential. In order to realize effective evacuation, a prediction model of the evacuation area that anyone can use to obtain the same results both accurately and promptly is developed in the present study. The prediction model is designed such that the wind speed and atmospheric conditions are automatically set, and the leakage rate is the only input parameter, so that anyone can use the model easily. In addition, the model can also predict the atmospheric parameters for up to 3 h and can calculate the evacuation distance so that smooth evacuation can be achieved for changing atmospheric conditions. Finally, the evacuation area is defined by statistically analysed wind fluctuations, and a series of emergency evacuation measures is implemented.

Emergency Evacuation Model and Simulation Analysis of Urban Metro Passenger Flow Based on Emergency Events

Emergency Evacuation Model and Simulation Analysis of Urban Metro Passenger Flow Based on Emergency Events

Multimodal evacuation after subway breakdown: A modeling framework and mode choice behavior

Subway is the backbone of the urban transportation system. However, because of its superior and high-capacity performance, it is difficult to evacuate the stranded passengers through other modes when unexpected disruptions happen. Previous studies paid much attention to the evacuation by gapping buses, but little attentions to the potential of the subway network and the transfers with other transport modes. This paper proposed a multimodal emergency evacuation modeling framework in response to subway breakdowns. The multinomial logit model was employed to analyze the evacuees alternative mode choice behavior. A case study of Longyang road subway station was analyzed by the proposed modeling framework, an SP (Stated Preference) survey of alternative evacuation modes was conducted for the calibration of the multinomial logit model. The results showed that a multimodal emergency evacuation based on the subway network could meet the requirements of evacuees, and make full use of all transport modes and improve evacuation efficiency. The research enriches the existing theory of multimodal emergency evacuation of the subway, and the conclusions can be used as a reference for emergency management and decision-making of subway emergencies.

Providing an Emergency Evacuation Model for the Stadium

Addressing the issue of providing emergency evacuation models is inevitable due to the growth of urban populations and their development, which requires the different usages of places with high population density. The decision on the emergency evacuation model will be more difficult when we want them all to exit at the same time, so without paying attention to other issues involved in planning, emergency evacuation has become more chaotic and this is more worrisome than the unexpected accident itself. Be Hence, a timed schedule for evacuating each sector based on priority is important to avoid the simultaneous presence of all people at the site of a node. Also, the identification and determination of the type and criteria of emergency evacuation of the population, providing an emergency population evacuation plan and emergency evacuation simulation software of the population, based on the plans for emergency evacuation, are of special importance for saving the lives of the users of the important buildings and places. In order to investigate and improve stadium evacuation plans, this essay proposes evacuation simulators to predict population behaviors for population evacuation scenarios based on multi-factor dynamic walking software solutions. The simulation model reflects the characteristics, laws, regulations and population evacuation standards, and the simulation model will be provided, which is able to change dynamically for local conditions. This model can generate valuable statistical graphs of population dynamics and provide data such as demographic bottlenecks, population density, and average population velocity. The content of this essay allows analyzing population evacuation in the stadium.The simulation results show that it takes about 20 minutes to evacuate the entire population from the stadium building when the stadium is completely full. Using a histogram or condensation texture, creation of a population bottleneck in the region with accumulation can be specified. According to the results, the access routes and exits of the stadium have enough space to evacuate the population from the building, but some places, such as access stairs to the platforms will not operate easily during a full scale deployment, and tend toward closing. This study shows that the simulation results, approximately represent the real evacuation in Naghshe Jahan stadium.

Research on Personnel Emergency Evacuation Model Based on Multi-agent

As it is impossible to simulate the whole process of evacuation in case of emergencies, based on the analysis and comparison of existing evacuation simulation models, considering the intelligence, interaction and autonomy of agents, multi-agent technology is introduced to model the emergency evacuation model. In this model, the evacuation space is divided into equal squares. In the decisionmaking process of selecting the evacuation exit, the distance from the individual to the exit, the number of people in the field of vision, the number of obstacles and the relevant density are comprehensively considered. No guide, fixed instructions and guidance for the three cases of evacuation process simulation, in the simulation, considering the number of the position and exit, simulation results showed that increasing the exit quantity and the width , In the process of evacuation, guides are added to make real-time direction guidance for agents, which can greatly improve the efficiency of evacuation. The research has very important reference significance for formulating scientific and reasonable emergency evacuation plan and reducing various losses caused by disasters.

Evacuation and Settlement Model of Personnel in Major Flood Disasters and Its Application

In order to select the most suitable rescue boat stop and personnel resettlement point for rapid evacuation and placement of “isolated island” victims. According to the characteristics of “isolated island” problem, considering the factors of total evacuation time and total evacuation cost, a dual-objective emergency evacuation model is constructed. By using the method of fuzzy matrix, the dual-objective problem is transformed into a single-objective problem. Finally, the Hungarian method is used to solve the problem. The results of an example show that the model can realize the selection of the best berth point and personnel placement point.