Total Evacuation Time Research Articles

Nuclear Accident Emergency Response System: Radiation Field Estimation and Evacuation

In this paper, a nuclear accident emergency response system based on unmanned aerial vehicles (UAVs) and bus collaboration is designed for radiation field estimation and evacuation. When a nuclear accident occurs, the radiation field is estimated firstly using the measurements acquired by UAVs. Based on the Cramer–Rao Lower Bound (CRLB), the coordinate optimization combined with UAV routing is formulated as a nonconvex mixed integer nonlinear programming (MINLP) problem to maximize the estimation accuracy. Further, a two-stage solution procedure based on genetic algorithm (GA) is proposed to solve the above problem. Then, taking the predicted radiation field as input, personnel in the emergency planning zone (EPZ) are evacuated to shelters by buses. The evacuation routing problem for minimizing both the total radiation exposure and evacuation time is formulated as a mixed integer linear programming (MILP) problem, which is solvable with efficient commercial solvers, such as Gurobi and CPLEX. The simulation results indicate that the system can provide effective help for emergency management under the nuclear accident scenarios.

Traffic management for large-scale evacuation with public transportation and calculation of appropriate operating ratio

In 2013, the International Atomic Energy Agency (IAEA) changed the recommended maximum range of the Emergency Planning Zone (EPZ) to 30 km, and the Kori Nuclear Power Plant in Republic of Korea has also expanded the EPZ to 30 km, following the recommendation. As a result, metropolitan cities with a high population density are contained within the EPZ, and evacuating millions of people should be considered if the 30 km range of evacuation is to take place. This study proposes an evacuation plan using buses (public transportation) to transport people outside of the EPZ, quickly and efficiently. To verify the appropriate mode share ratio of buses that can guarantee the right of vulnerable road users and reduce traffic congestion, a model was built simulating the Kori Nuclear Power Plant in Ulsan Metropolitan City. The scenarios were established by changing the mode share ratio of buses and passenger cars by 10%. Considering a large-scale network analysis at the city level, a cell transmission model was applied to calculate the evacuation time in each scenario. The result shows that the optimal mode share ratio of buses is 40%, with a total evacuation time of 132 min, considering feasible bus fleets in Ulsan Metropolitan City.

Simulation Pedestrian Flow Under Vertical Bottleneck Constraints: How Stair Configuration Affects Pedestrian Movement Efficiency

As a result of the geometric constraints of the stairs, pedestrian movement features on stairways are different from level ambulation. Therefore, it is necessary for us to consider the stairs' three-dimensional geometry when we try to explore how the stair configuration affects pedestrian movement efficiency. Based on the pedestrian fundamental features from a previous pedestrian single-file movement experiment on stairs, we investigated pedestrian flow under various stair configurations with an improved agent-based model. Our simulated indicates that both stair inclinations and tread depth of stair step are sensitive to the pedestrian dynamic on stairs. Generally speaking, pedestrian flow decreases with the increasing slope of stairs. When the stairs slope increased 5, 10, 15 and 20 degree, the evacuation efficiency dropped 5.8%, 12.8%, 19.3% and 28.4%. Besides, the effect of the tread depth on pedestrian total evacuation time is not changed monotonously. Scenarios with 0.3m tread depth size present the optimal evacuation efficiency. Other scenarios differ from 3% to 27.9% in terms of the total evacuation time.

Evacuation Optimization Strategy for Large-Scale Public Building Considering Plane Partition and Multi-Floor Layout.

Large-scale public buildings (e.g., stadiums and comprehensive hospitals) in modern cities provide places for various social activities. However, all of these public places encounter the scenario of large passenger flow and crowd gathering, which is highly likely to induce serious safety problems, such as stampedes. Previous studies have shown that efficient evacuation is an important way to ensure the safety of dense crowds in public places. This study aims to explore the optimization methods to improve the evacuation efficiency of public buildings. Two strategies considering plane partition and multi-floor layout are proposed for plane evacuation and vertical evacuation, respectively. Simulation scenarios and models of large stadiums and high-rise hospitals are established to verify the strategies. The results show that plane partition could effectively shorten the total evacuation time, which is due to the optimization of the initial exit choice of individuals and the avoidance of regional congestion in some evacuation channels or exits. Multi-floor layout optimization is an effective management method to arrange the different features of different floors, which could improve the evacuation efficiency for the whole multi-floor building. This study is helpful for building designers and managers to improve the building space layout design and the daily safety management mode.

Stochastic user equilibrium path planning for crowd evacuation at subway station based on social force model

Evacuation path of pedestrians at subway station can directly affect the evacuation efficiency, and then affect the service level of the station. A Fisk stochastic user equilibrium model considering the congestion factor is established to assist evacuation path planning, which could avoid the bottleneck area and dangerous situation in advance. By comparing the field statistical data with simulation data of the number of pedestrians at the entrance gate of subway station, it is verified that the social force model and the minimum cost model can basically reproduce the movement law and path selection behavior of pedestrians at the subway station. Simulation experiment is carried out to compare the evacuation efficiency at the subway station under the stochastic user equilibrium model and the minimum cost model. The results indicate that the number of pedestrians at each gate is relatively balanced which can avoid overcrowding under the stochastic user equilibrium model. The total evacuation time can be reduced by 15%, and the individual evacuation time can be saved about 0.57 min. By comparing the 3D overall pedestrian trajectory and the 2D local pedestrian trajectory, it is found that the stochastic user equilibrium model is of great significance for evacuation path optimization at the subway station. The quantitative relationship between the number of pedestrians and evacuation time at the subway station is given through regression analysis under stochastic user equilibrium model and minimum cost model. The suspension of escalators can obviously result in congestion at the gate and increase the total evacuation time. When pedestrian density at the station is low, closing a certain exit can significantly improve the pedestrian traffic efficiency at the gate and greatly reduce the total evacuation time. The stochastic user equilibrium evacuation path planning model constructed in this paper provides a guidance strategy for pedestrian evacuation, which could improve the efficiency and safety of subway evacuation system.

Large-Scale Evacuation Shelter Selection Method Through Iterations of Pedestrian Simulations With Dynamic Congestion Reproduction

It is necessary to optimize evacuation guidance to shelters in short evacuation time. The state-of-the-art method based on an idea of combinatorial optimization problems related to evacuees’ locations and the capacities of nearby shelters has been developed, while it cannot mitigate the effect of congestion on roads/streets after evacuation starts. In this study, to cover this problem, we develop a new method that utilizes simulations for estimating the effect of congestion on roads/streets during evacuation and reassigning shelters to evacuees based on the simulation results. By iterating this step, our method derives the congestion-aware solutions for shelter selection that can realize more smooth evacuation. To evaluate our method, we conducted multi-agent simulations assuming a disaster situation in a sightseeing spot. Specifically, we examined a hypothetical case scenario involving the evacuation of 30,000 visitors from the Gion Festival. We compared the proposed method with conventional methods, such as the nearest shelter selection method and our previous method. We found that our proposed method reduced average and total evacuation time and congestion on roads compared to the conventional methods including the nearest shelter selection method and our previous method that only employs combinatorial optimization without estimating congestion. From this result, our idea of simulation-based congestion estimation has an impact of easing congestion during evacuation and preventing overcapacity of shelters at the same time. It shows the possibilities of help in developing congestion-aware evacuation strategies in emergency situations of crowded areas like huge cities or sightseeing spots.

An Agent-Based Dynamic Framework for Population Evacuation Management

Evacuating the population during crises to safe zones via optimal paths is vital. The evacuation planning process makes two main decisions: which shelter to reach and which path to take towards the chosen shelter. These decisions correspond to shelter allocation and traffic assignment problems, respectively. Many studies tackled these problems with a static formulation in the literature, while only a few considered a dynamic context. We conduct a comprehensive literature review and highlight that most studies independently solve these two problems while both are correlated with traffic conditions. To fill this gap, we propose a new framework to couple the shelter allocation problem (SAP) and the dynamic traffic assignment (DTA) problem and solve them. To capture traffic dynamics, we use a dynamic agentbased simulator. We assume the system determines the evacuees’ shelters to minimize the total evacuation time. However, each evacuee’s concern is reaching a shelter as fast as possible. Therefore, we formulate the DTA problem under stochastic user equilibrium (SUE) principles, i.e., every evacuee aims to minimize his own perceived travel time. We apply the proposed methodology to the network of Luxembourg City and compare its performance with other advanced methods that solve SAP and DTA separately. The comparison shows that solving the dynamic shelter allocation improves the mean evacuation time and significantly decreases the network clearance time compared to other methods with a fixed plan for SAP. The simulation results prove that considering the network state in the SAP can provide a more effective evacuation plan. Moreover, we perform a sensitivity analysis on optimization parameters and evaluate the computation cost of our methodology.

A smart spontaneous crowd evacuation system for large multi-exit exhibition centers based on IoT

Plans to mass evacuate visitors in an exhibition center in the case of emergency situations are critical for public safety and disaster management. Efficient crowd evacuation during mass gatherings has been an active research area during the past years. In this paper, we consider the challenging problem of finding in near real-time the most efficient and safest evacuation pathways 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 associated with the changing environmental conditions. We then present a spontaneous 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 crowd congestion. Our IoT-based system activates smart panels placed at major junctions of the hallways to visually guide evacuees towards the safest escape direction under the existing circumstances. The proposed algorithms aim to minimize the total evacuation time of all evacuees, while circumventing congested and perilous aisles, balancing traffic loads, and guaranteeing high scalability and reasonable computational efficiency. This work can pave the way towards the development of nextgeneration smart exhibition centers, where crowd safety is among the top priorities

Household evacuation preparation time during a cyclone: Random Forest algorithm and variable degree analysis

Household evacuation preparation time is important to ensure safe and successful evacuations and is essential for the estimation of the total evacuation time during a disaster. Previous research has shown that machine learning can provide a higher prediction accuracy, especially using the random forest model. However, no studies have investigated predictions of household evacuation preparation time considering the safe evacuation of coastal communities during cyclone disasters. This study proposes a methodology to predict household evacuation preparation time following demographic and behavioral input variables based on a random forest algorithm focusing on cyclones. In addition, this research analyzes the variable importance and partial dependence plot to identify the key influential factors that affect household evacuation preparation time. A case study was conducted in Gabura Union, Shaymnagar Upzila in Bangladesh regarding cyclone Bulbul in 2019 to gather demographic and behavioral data for a preparation time simulation. The prediction results showed efficient assessment of household evacuation preparation time prediction, meriting application for cases of future disasters. Our results show that the most important factors that impact household evacuation preparation time are evacuation companions and age, followed by shelter distance, income, and shelter type. The results of the prediction model can assist emergency response and evacuation planners and national disaster management authorities in developing and improving effective evacuation plans that take household evacuation preparation time into consideration for future disasters.

Influence factors on the passenger evacuation capacity of cruise ships: Modeling and simulation of full-scale evacuation incorporating information dissemination

The passenger evacuation capacity (PEC) of a cruise ship is a pivotal guarantee for quickly and safely evacuating all personnel on a damaged ship during an emergency. A general framework of the agent-based evacuation model is proposed in this study to simulate the entire process of cruise ship evacuation. The total evacuation time, duration of Level of Service (LOS) lower than E, effective flow rate of the escape route, density of the muster station, and usage rate of the lifeboat/life raft are used as the five evaluation indicators to quantify the PEC of cruise ships, thus providing a reference for the optimization analysis of evacuation procedures. With this framework, the PECs under different evacuation strategies of a cruise ship were evaluated in the context of ship heeling to capsizing for the Yangtze Gold 1. Evaluation results show that the increase of heeling angle when the evacuation order is issued does not affect the perception time of the first 90% of evacuees, but significantly increases the total evacuation time after more than 20°. Moreover, the degree of regional congestion is affected by several factors, including the assignment of muster stations, evacuation in batches, the place of obtaining life jackets, the heeling angle, the difference of escape route flows, and other factors. The results of this study provide PECs under different strategies as references for specific accident scenarios and evacuation targets.

Understanding total evacuation time perception in airplane emergency: A stated preference approach

It is difficult to observe people's actual evacuation behavior in case of a real aircraft accident. For one, luckily, because aircraft incidences have very low probabilities, and for another, because when faced with such extreme situations people often resort to very unexpected behavior. A way to obtain people’s responses to an airplane emergency is then to estimate people’s perceptions of the total evacuation time. In this paper, a stated preference analysis containing eight airplane evacuation attributes was carried out by nine hypothetical aircraft accident scenarios. The experiment adopted a fractional factorial design to reduce the survey size and obtained 192 effective responses. A cumulative odds ordinal logistic regression with proportional odds was performed and results showed the model has a good data fit. The following findings were revealed from this study. First, for the onboard safety briefings, the efficiency of safety broadcasting is better than crew demonstrations and safety cards, but the overall attention from passengers to the cabin safety announcements is still inadequate. Second, in passengers’ perception, the lack of crew guidance would slow the evacuation the most while more available exits reduce the evacuation time primarily. Third, being knowledgeable about and more experienced in flying has a significant effect in reducing people’s perception of evacuation time. Finally, higher self-reported levels in the ability to stay calm are associated with a shorter estimation of the evacuation time. These findings may help optimize the understanding of air passengers’ behavior in emergencies and improve the preparedness for aircraft emergency evacuation.

Optimal solutions to vertical access placement design in residential high-rise buildings based on human behavior

Human behavior at the time of building crisis should be analyzed in order to design buildings with satisfactory performance. In residential high-rise buildings, there are certain complications due to residential conditions. Given the high population density of these buildings, it is important to analyze their vertical access performance for emergency evacuations. This study aims to find the optimal placement and layout of vertical access in residential high-rise buildings. It asks: What is the most optimal solution to vertical access placement design in residential high-rise buildings? To answer this, human behavior simulation models during an emergency evacuation in residential high-rise buildings were first analyzed, and the best model was selected. Based on the human behavior models, the vertical access placement was then optimized to evaluate the optimal structures of four types of 60-story residential buildings designed and compared in SFPE and Steering simulation engines. The scenarios differ in vertical access placement. The simulations are conducted in four parts, which include how people placement on each floor, considering disabled persons along with assisted evacuation, and the fire-involved stories and the blocked stairs. According to the research results, a cost-effective core that solves structural problems and provides vertical access will not necessarily be the right solution to the emergency evacuation of high-rise buildings. Instead, placing vertical access features such as stairs and elevators on two opposite sides of a building plan can reduce the total evacuation time by 20%.

High-Rise Building Evacuation Simulation Based on Physical Stamina of Evacuees

Currently, high-rise buildings are being continuously constructed, and thus, it is necessary to predict evacuation safety in advance in case of emergency situations in high-rise buildings. However, current studies focus only on the movement of individuals in evacuation situations for predicting the final evacuation time. Therefore, in this study, a simulation of realistic evacuation in high-rise buildings was performed based on characteristics such as the physical stamina of evacuees. The evacuation simulation was performed on the world's tallest high-rise building, Burj Khalifa, and comparative verification was performed with and without consideration of the physical stamina of evacuees. The results of the simulation indicated that the total evacuation time significantly increases when physical stamina is considered. Hence, realistic evacuation in high-rise buildings is possible when the stamina of evacuees is considered.

Evacuation trials from a double-deck electric train unit: Experimental data and sensitivity analysis

Passenger trains represent a challenging environment in emergencies, with specific evacuation conditions resulting from the typical layout and interior design inherent to public transportation vehicles. This paper describes a dataset obtained in a full-scale controlled experiment emulating the emergency evacuation of a double-deck electric unit railcar carried out in Prague in 2018. 15 evacuation trials involving 91 participants were conducted under various evacuation scenarios considering different compositions of passenger crowd, exit widths, and exit types (egress to a high platform, to an open rail line using stairs, and a 750 mm jump without any supporting equipment). The study’s main goals were to collect experimental data on the movement conditions in the railcar and to study the impact of various boundary conditions on evacuation process and total evacuation time. Movement characteristics (exit flows, speeds) and human behaviour (pre-movement activities, exiting behaviours) were also analysed. The data obtained was used to validate and adjust a Pathfinder model to capture important aspects of evacuation from the railcar. Furthermore, a series of simulations using this model was performed to provide sensitivity analysis of the influence of crowd composition, exit width, and exit type on total evacuation time. As a key finding, we can conclude that for the case of a standard exit path (platform or stairs) the width of the main exit had the greatest impact on total evacuation time, however, crowd composition played the prevailing role in evacuation scenarios involving a jump.

An evacuation guidance model for pedestrians with limited vision

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 purpose, we analyze the relationship between intermediate states and evacuation efficiency and propose an evacuation guidance model to guide pedestrians to form a series of expected states, which can reduce the evacuation time caused by congestion. The model includes three major factors that affect the evacuation time: the length of routes, the congestion of routes, and the density of exits. Furthermore, we propose a method based on reinforcement learning to optimize the guidance model. Finally, we utilize reciprocal velocity obstacle technology to build an evacuation model to verify the results of our study. The simulations indicate that the optimized guidance model can make full use of all exits during an evacuation and shorten the total evacuation time.

Simulation Modeling Practice on Occupant Evacuation in a Medium-sized Supermarket

The research mainly focused on the effect of staff density and exit conditions on total evacuation time. The results showed that with the increase of staff density, evacuation time often increases non-linearly. The function equation of evacuation time and number of occupants in case A was obtained through computer simulation. The augment of exit number or total export width can reduce the total evacuation time to improve evacuation efficiency. While, if the number of evacuees reaches to a certain value, evacuation time may increase non-linearly after being affected by the internal structure and the random distribution of occupant. Export position also has impact on total evacuation time. The results of the simulation have guiding significance on the design of building structures and personnel evacuation in emergency.

A Multi-Zone Staged Indoor Emergency Evacuation Algorithm Based on Time Equalization

Most of the existing staged evacuation algorithms only consider the impact of crowd density on evacuation partition, but do not take into account the influence of the spatial distribution of occupants and the capacity of exits on the total evacuation time (TET). Therefore, a novel indoor emergency evacuation algorithm based on time equalization is proposed in this paper. All factors affecting TET such as the position and size of each group and the capacity of exits are fully considered in the proposed algorithm, which are uniformly converted into the occupancy time of each exit. An improved Dijkstra algorithm is used to generate evacuation zones according to the proximity relationship and the occupancy time of different exits. The strategy of waiting at the starting point is adopted to ensure that all evacuees are free from congestion during the escape process. In addition, the method of group merging is proposed to further increase the balance among all zones during the partitioning process. The objectives of the proposed algorithm include minimizing the TET of all evacuees, the path length of each escape group, avoiding congestion during the escape process. The experimental results show that the proposed algorithm effectively reduces TET and the path length of groups compared with existing algorithms, which improves the efficiency of evacuation and utilization of all exits and can be applied to the various distribution and density of evacuees.

Emergency evacuation from multi-exits rooms in the presence of obstacles

To facilitate emergency evacuation, it is essential and important to investigate how system dynamics govern collective behaviors of pedestrians in panic. Although it has already been pointed out that appropriate arrangement of obstacles in a single-exit room can substantially improve evacuation efficiency, whether this conclusion can be carried over to multi-exits scenario still remains puzzling. Motivated by this, we propose an improved social force model to study the influence of the total number of pedestrians, their desired velocity and the specific locations of obstacles on evacuation efficiency for multi-exits configurations. Simulation results show that evacuation efficiency sensitively depends on the arrangement of obstacles. Specifically, there exists an optimal location for the obstacle where the total evacuation time is minimized, but not all the locations have a favorable impact on evacuation. This conclusion also holds for the dependence of evacuation efficiency on obstacles length. More importantly, the effect of obstacles, irrespective of being positive or negative, can be enhanced by increasing the number of pedestrians or the desired velocity. This work may shed some light on the drawing up of emergency scheme for multi-exits public-gathering places like stadiums and shopping malls.

Classification of the Socio-Psychological Aspects of Protecting Soft Targets: a Case Study for Evacuation of the Railway Terminals

Current crisis management approaches to protect soft targets make assumptions about average visitors/listeners/viewers or passengers. They do not give much consideration to impacts of diversity of potentially evacuated persons with regard to socio-psychological parameters/factors that may lead to practical problems and complications during the evacuation itself. At the same time, the soft target operators have various means of machine vision tools at their disposal, but do not use these records for more thorough analysis of evacuation planning needs. Based on this observation, the article identifies and analyzes the socio-psychological aspects that may significantly affect behavior and decisions of persons during the evacuation and thus total evacuation time.

A Staged Evacuation Methodology for Emergency Preparedness Plan

ABSTRACT Early public protection measures play an important role in reducing the health effects of radiation exposure. In particular, a staged evacuation is recognized as the most important strategy. However, studies on segmenting an evacuation region with non-uniform population density are lacking; therefore, the purpose of this study is to gain insight regarding this topic. First, the evacuation region was determined by comparing the level 3 probabilistic safety assessment (PSA) results with the generic-dose limit. Second, we performed mathematical approaches to calculate the evacuation and delay time. We then scored staged evacuation strategies and selected the best strategy. Through this study, we found some features as follows: (1) the evacuation and delay time have a trade-off relationship, (2) there is no significant difference in total evacuation time except for the preparation time, and (3) there is a big difference in total delay time despite the same segmentations. Namely, even if the evacuation time may be the same, the delay time may differ. The delay time can be defined as the period that people spend on the road, and so the longer the delay time, there is an increased likelihood of receiving unnecessary exposure.