Optimal Evacuation Research Articles

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.

Real-time evacuation route optimization in the fire scenarios of cruise ships

The optimization of evacuation routes for evacuees in fire scenarios on cruise ships directly affects evacuation efficiency. A time-varying equivalent weight Dijkstra algorithm (TVEWDA) is proposed, combining a fire dynamics simulator (FDS) to find optimal evacuation routes in case of a sudden cruise ship fire. First, the FDS software is used to simulate a cruise ship's single and multi-source fire scenarios. Second, the Dijkstra algorithm using only distance between nodes is improved by considering the effects of CO concentration, visibility, and temperature. The evacuees’ speed is taken into consideration within the TVEWDA. The effects of congestion are considered in the evacuees’ moving speed. Finally, the TVEWDA and a cruise ship evacuation network model are integrated to develop a real-time evacuation route optimization model. Simulation results show that the evacuation time achieved by the TVEWDA is 22% shorter than that of the Dijkstra algorithm using only distance between nodes and 11% shorter than that of an improved social force model in the multi-source fire scenario. This approach is well-suited to guide the evacuation of cruise ship evacuees in the event of single-source or multi-source fires, effectively ensuring the safety of passengers and the preservation of their property.

Real-time tsunami forecasting system with nonlinear effects using Green’s functions: application to near-shore tsunami behavior in complex bay topography

ABSTRACT In this study, a real-time tsunami estimation method was developed using the linear superposition of Green’s functions, which account for nonlinear tsunami effects around coastal areas. To this end, first, the nonlinear effects associated with the inundation and bottom friction and advection terms in a nonlinear long-wave model were investigated, focusing on large tsunamis around Urado Bay in Kochi Prefecture, Japan, which is at risk of future damage from tsunamis produced by the Nankai Trough earthquake. The results indicate that the effects of advection play a more significant role than those of the inundation and bottom friction in terms of accurately estimating near-shore tsunami propagation. Then, based on these results, Green’s functions were modified to account for the linearly approximated effects of the advection terms. By applying the developed method to tsunamis around Urado Bay, it was demonstrated that accurate estimations of the water surface level and flow velocity changes could be quickly obtained at any location around the bay. The developed method can be applied to real-time tsunami inundation forecasting and off-shore evacuation simulations of vessels to support optimal evacuation decisions.

Dynamic Evacuation Routes Navigation for Passenger Ship Fire Based on Intelligence Algorithms

AbstractTo explore fire hazards and provide real‐time path navigation services for passenger ships, this study proposes an improved artificial fish swarm algorithm (IAFSA) to give the optimal evacuation route for evacuees when a passenger ship is on fire. First, the PyroSim software is used to simulate the fire scene on the sixth deck of the passenger ship. Through which the real‐time temperature, carbon monoxide (CO) concentration, and visibility of each exit are obtained, and the spread speed of the fire hazard area is determined. Then, the artificial fish swarm algorithm is improved by using the dynamic Visual and step, and the optimal path planning for the evacuation of passenger ships is achieved. The Visualized Evacuation Guidance System (VEGS) is developed to provide the optimal route for evacuees on the passenger ship. Finally, VEGS is applied to the fire evacuation of passenger ships. The results show that VEGS can provide the optimal evacuation path for evacuees and avoid detours in fire hazard areas compared with other algorithms. Seventy‐five percent of the evacuees who used VEGS in the event of a passenger ship can escape in a time shortened by up to 40.8%.

GIS-based identification and analysis of suitable evacuation areas and routes in flood-prone zones of Nakhon Si Thammarat municipality

Floods are a significant issue across Southeast Asia, with Thailand, particularly the Nakhon Si Thammarat Municipality, being heavily affected due to its unique conditions such as heavy rainfall, rapid urbanization, and low-lying coastal position. This study utilizes Geographic Information Systems (GIS) to analyze the flood-prone areas of Nakhon Si Thammarat Municipality, assess its road networks, and identify optimal evacuation locations and routes. Various data layers such as slope angle, elevation, distance from roads, rainfall, TWI, NDVI, land use, soil texture, distance from rivers, stream density, and road density are integrated using the frequency ratio method. The findings reveal areas with very high flood susceptibility, which span 198.78 sq. km (56.74%) at the high frequency level, 299.43 sq. km (37.63%) at the low frequency level, and 284.62 sq. km (53.88%) at the moderate frequency level. During flood scenarios, travel times saw an average increase to 21.4 min, which is a fourfold surge compared to regular conditions, highlighting the impact of floods on evacuation strategies. Upon evaluating the road network under flood conditions and applying network analysis techniques, efficient and safe evacuation routes were determined. The results, which underscore a fourfold increase in travel time during flood scenarios, present valuable insights for emergency management authorities across Thailand and Southeast Asia to devise comprehensive evacuation plans, thereby enhancing regional resilience against future flood events. Furthermore, the methodologies and findings are adaptable and can be applied to other flood-prone regions within Southeast Asia, contributing to improved disaster preparedness and response.

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.

A methodology based on Dijkstra's algorithm and mathematical programming for optimal evacuation in process plants in the event of major tank fires

A methodology based on Dijkstra's algorithm and mathematical programming for optimal evacuation in process plants in the event of major tank fires

A quantitative study of the factors influencing human evacuation from ships

Due to the constraints of various factors influencing human evacuation on board, it remains a challenging problem to accurately quantify the impact of these factors on the evacuation process. To analyse the multiple influential factors of human evacuation from ships, a specific framework based on orthogonal experiments is proposed in this paper to comprehensively investigate the impact of multiple factors on the evacuation time and the efficiency of the evacuation process. Heeling angles, unavailable stairs, and priorities of evacuees are identified as influential factors according to the characteristics of human evacuation from ships. The analysis results show that the heeling angle has a very significant effect on both evacuation time and efficiencies, and the efficiencies decrease as the heeling angle increases. Unavailable stairs also have a significant effect on evacuation results, the magnitude of which depends on the number of stairs nearby. While the effect of priorities of evacuees on evacuation results is relatively less important, it can be found that priority evacuation of pedestrians with impaired mobility will aid to achieve optimal evacuation results. In conclusion, the findings of this study can help managers quickly develop effective evacuation strategies in emergencies to further improve the safe operation of passenger ships.

A GIS-Based Evacuation Route Planning in Flood-Susceptible Area of Siraha Municipality, Nepal

Flood is one of the most frequently occurring and devastating disasters in Nepal. Several locations in Nepal are at high risk of flood, which requires proper guidance on early warning and safe evacuation of people to emergency locations through optimal routes to minimize fatalities. However, the information is limited to flood hazard mapping only. This study provides a comprehensive flood susceptibility and evacuation route mapping in the Siraha Municipality of Nepal where a lot of flood events have occurred in the past and are liable to happen in the future. The flood susceptibility map was created using a Geographic Information System (GIS)-based Analytical Hierarchy Process (AHP) over nine flood conditioning factors. It showed that 47% of the total area was highly susceptible to flood, and the remaining was in the safe zone. The assembly points where people would gather for evacuation were selected within the susceptible zone through manual digitization while the emergency shelters were selected within a safe zone such that they can host the maximum number of people. The network analysis approach is used for evacuation route mapping in which the closest facility analysis proposed the optimum evacuation route based on the walking speed of evacuees to reach the emergency shelter place considering the effect of slope and flood on the speed of the pedestrian. A total of 12 out of 22 suggested emergency shelters were within 30 min, 7 within 60 min, and 2 within 100 min walk from the assembly point. Moreover, this study suggests the possible areas for further shelter place allocations based on service area analysis. This study can support the authorities’ decision-making for the flood risk assessment and early warning system planning, and helps in providing an efficient evacuation plan for risk mitigation.

Performance-Based Evacuation Optimization for Teaching Building with Heterogeneous Populations: Simulation and Numerical Studies

Building evacuation safety has been one of the focal points of researchers, and there is a wealth of research findings for certain places (e.g., buildings with a high population density) or for particular research subjects (e.g., the physically challenged ethnic group). However, current publications are relatively rare in analyzing the features of physically impaired individuals in crowded places and their impact on the effectiveness of the whole evacuation process, including non-disabled people. Additionally, only such studies tend to concentrate on the behavioral characteristics of disabled people, which lack exploring and comparing evacuation optimization strategies and evaluation of comprehensive evacuation performance. This paper proposed a computer simulation-based method that combined horizontally phased evacuation and vertically phased evacuation, supplemented with the use of handicapped ramps and a reasonable arrangement of class locations, to achieve the optimal evacuation performance of a teaching building with special consideration of the heterogeneous population. And then, a simulated building model was constructed to test and compare the effectiveness and applicability of these approaches through 33 evacuation scenario studies. The results found that (1) component design can improve evacuation effectiveness, with the arrangement of ramps and the location of stair doors successfully reducing evacuation time by 12% and 6.6%, respectively; (2) a combination of two ramps and separate handicap access can decrease evacuation time by 18%; (3) the horizontal-phased evacuation approach drops evacuation time by 7.1%, but the vertical-phased evacuation strategy is not very efficient. When the two are successfully combined, evacuation time is further reduced to 9.2%; and (4) based on the above measures, the evacuation time can be finally shortened by 19% if the veteran teachers are concentrated in the classrooms on the lower floors. These obtained conclusions will provide significant reference and methodological support for the safe evacuation of other similar buildings with heterogeneous populations.

Decision-support system for safety and security assessment and management in smart cities

Counter-terrorism measures and preparedness play a critical role in securing mass gatherings, soft targets, and critical infrastructures within urban environments. This paper introduces a comprehensive Decision Support System developed as part of the S4AllCitites project, designed to seamlessly integrate with existing legacy systems in Smart Cities. The system encompasses urban pedestrian and vehicular evacuation, incorporating predictive models to anticipate the progression of incendiary and mass shooting attacks, alongside a probabilistic model for threat assessment in the case of improvised explosive devices. A notable achievement of this research is the successful implementation and deployment of the system in operational environments through pilot studies. It empowers public and private security operators with real time decision support capabilities during both prevention and intervention stages of potential attacks. The decision support information provided encompasses various aspects, including optimal evacuation strategies, estimated egress times, pedestrian movement profiles, probability assessments, and the potential impact of different terrorist threats in terms of casualties. Additionally, the system offers real-time insights into the status of the traffic network under normal and unusual conditions, enabling efficient emergency management throughout its progression. This includes the ability to identify optimal intervention routes and assess the impact of anomalous traffic resulting from evacuations.

Study on the influence of fire alarm time on evacuation time in typical shopping malls based on pathfinder

The fire floor personnel are affected by the evacuation of non-fire floor personnel during the evacuation process. Congestion in the evacuation stairwell leads to failure to evacuate in time, which affects the evacuation efficiency. In this paper, a typical shopping mall is taken as the research object, and the Pathfinder simulation software is used to simulate the safe evacuation of personnel. In the simulation, the influence of alarm time on evacuation time is studied by setting the fire layer and delaying the alarm time of non-fire layer, and finally the optimal evacuation scheme is obtained. It can be used as a reference for typical shopping malls to formulate safety evacuation plans or for the revision of relevant specifications.

BIM based framework for building evacuation using Bluetooth Low Energy and crowd simulation

Crowd evacuation is an area that has been studied by numerous researchers over the last years. Many models have been developed to simulate the evacuation. However, most of the developed models involved emergency routing of building occupants using hypothetical assumptions of their positions without integrating their actual locations into the models. Thus, in order to increase efficiency and accuracy of evacuation models, evacuees' real locations can be identified and then integrated into the model. In this research, Building Information Modelling (BIM), agent based simulation and Bluetooth Low Energy technology are integrated together to create an evacuation framework capable of indicating locations of building occupants and identifying the optimum evacuation path based on these locations. Point cloud data of a building is collected from 3D laser scanner, then converted to 3D BIM model, which is then imported into an agent based crowd simulation software. Also, an indoor positioning module is developed, which is composed of an indoor positioning system (IPS) developed by the authors. Through the IPS, evacuees’ locations are calculated, whereas Bluetooth emitters –beacons- held by evacuees emit signals that are detected by group of gateways mounted in the building detect. The locations are then sent to the crowd simulation software, then through integrating the modules, optimum evacuation route is identified, which is then converted to directions through a dynamic signage module. A case study is presented to illustrate the proposed framework. The results of the case study show that the developed indoor positioning system has an accuracy of 1.88 m with a maximum error range of 3.934 m. Moreover, the results indicate that the implemented indoor positioning system is capable of correctly detecting the evacuees in the rooms they are actually in with an accuracy of 93%. Finally, the simulation shows that the full evacuation of the floor under study took 2 min and 48 s.

Evaluation of pollutant exposure using virtual walkers and large-eddy simulation: Application to an idealised urban neighbourhood

Urban air quality studies have primarily focused on pollutant dispersion; however, spatial or temporal concentrations collected at discretely distributed grid points (or fixed receptors) do not reflect the actual pollutant exposure of pedestrians. Using large-eddy simulation (LES) with virtual walkers implemented, this study investigates pollutant exposure of walking agents (or moving receptors) in an urban turbulent boundary-layer flow developed over an aligned building array under the influence of different wind directions. The spatial variability of the exposure risks are found to be better captured by the moving receptors than the fixed receptors along the same agent walking tracks. We demonstrate that the actual exposure can differ significantly from results interpreted from data recorded by the fixed receptors (corresponding to Eulerian estimates) and show that large discrepancies occur in avenues near the source, wherein dispersion of the point release has not occurred on larger spatiotemporal scales. In most scenarios, optimal evacuation routes are shown to be ones that deviate as much as possible from the dominant wind direction; however, one needs to decide the priority of moving to further avenues first or immediately adjusting the walking direction. The results should serve as a useful baseline reference for environmental health impact assessment and evacuation route planning against hazardous releases of air pollutants in more complex urban environments.

Emergency Escape Route Design and Application

This paper uses k-means clustering algorithm, single objective optimization model and multisource multi-sink problem shortest path algorithm to obtain the optimal path algorithm for emergency evacuation and the shortest time model.Firstly, a code of conduct for the division of terrorist attacks has been established. The number of casualties in various incidents and the scope of destructive power to public areas are counted. A three-dimensional cluster core is selected. All terrorist at- tacks are classified into three levels: level 1-3 by the k-means clustering algorithm, and the degree of harm is gradually increasing.Secondly, the optimal path from each venue to the stairway is calculated. The re- lationship between the speed of flow and the number of evacuees is given in the case of three situations. The multi-source multi-sink problem is transformed into a single- source shortest path problem by adding a virtual node to all venues on the second floor of the Louvre, and the Dijkstra algorithm is called once to obtain the optimal path from the venue to all stairs.The Final step is to establish an emergency evacuation optimization model with the minimum evacuation time as the objective function. The overall evacuation time is divided into the personnel response time, the horizontal road walking time, the time down the stairs, and the waiting time when congestion occurs. the open number of emergency exits can be judging by different levels of terrorist events, and the optimal evacuation path and the shortest time for different emergency events are given. At the same time, we also analyzed the changing trend of velocity in different cases, which can be adjusted according to the actual conditions.

FlowLoc problems with maximum excess flow

In order to reduce huge losses from natural and human caused disasters, an appropriate strategy of evacuation planning, preparedness, response and recovery is very essential. The placement of facilities in appropriate arcs of a network plays an important role for the optimal evacuation planning. Such an efficient assignment should respect the least decreases on the arc capacity and hence should minimize the reduction of the optimal flow value. On the other hand, due to the bottleneck capacity, not all flows out from the sources may reach to the sinks. To maximize the flow value, the resulting excess flow can be stored at intermediate nodes that are comparatively safer than the sources.By integrating both concepts, we introduce the single-source single-sink maximum static and dynamic flow location (FlowLoc) problems with excess flow storage allowed. Our objective here is to minimize the reduction of maximum flow in an evacuation network where given facilities are placed on arcs and excess flow is stored at intermediate nodes. We provide their mathematical models and also present polynomial time algorithms to solve them. For the maximum static and dynamic multi-FlowLoc problems where multiple facilities are located, we give their mathematical models and present polynomial time heuristics. These solutions here are practically important, especially in evacuation planning, to maximize the flow value out of the disastrous places by locating the facilities.

EVACUATION ROUTE PLANNING MODEL BASED ON THE FUZZY ANT COLONY OPTIMIZATION ALGORITHM

The construction of evacuation routes from urban areas has become an urgent task in the modern world, as the number of emergencies is constantly increasing. Standard route planning algorithms do not meet the requirements of fast and efficient evacuation because they do not fully consider the environmental parameters and have a high computational complexity, and erroneous results can have critical consequences, including loss of life. The paper proposes a model of finding an optimal evacuation route in emergencies in urban areas based on a modified ant colony optimization algorithm: an ant (a person or a vehicle) is allowed to start moving from several possible vertices of the graph, as well as to end the route at several available vertices. It is connected with the fact that there are usually multiple evacuation start points and destinations. The transitions matrix is built using additional parameters, the uncertainty of which is taken into account using the methods of computing with words and the theory of type-2 fuzzy sets and systems. For modeling, in the paper such additional parameters as the quality of the road surface, the number of road lanes, the level of traffic jams, and the distance to the epicenter of the emergency were used. The proposed model was implemented and applied in one of the quarter of Kyiv.

Evacuating from ℓp unit disks in the wireless model

The search-type problem of evacuating 2 robots in the wireless model from the (Euclidean) unit disk was first introduced and studied by Czyzowicz et al. (2014) [13]. Since then, the problem has seen a long list of follow-up results pertaining to variations as well as to upper and lower bound improvements. All established results in the area study this 2-dimensional search-type problem in the Euclidean metric space where the search space, i.e. the unit disk, enjoys significant (metric) symmetries.We initiate and study the problem of evacuating 2 robots in the wireless model from ℓp unit disks, p∈[1,∞), where in particular robots' moves are measured in the underlying metric space. To the best of our knowledge, this is the first study of a search-type problem with mobile agents in more general metric spaces. The problem is particularly challenging since even the circumference of the ℓp unit disks have been the subject of technical studies. In our main result, and after identifying and utilizing the very few symmetries of ℓp unit disks, we design optimal evacuation algorithms that vary with p. Our main technical contributions are two-fold. First, in our upper bound results, we provide (nearly) closed formulae for the worst-case cost of our algorithms. Second, and most importantly, our lower bounds' arguments reduce to a novel observation in convex geometry which analyzes trade-offs between arc and chord lengths of ℓp unit circles as the endpoints of the arcs (chords) change position around the perimeter of the disk, which we believe is interesting in its own right. Part of our argument pertaining to the latter property relies on a computer assisted numerical verification that can be done for non-extreme values of p.

Optimization of an Airport Departure Hall Evacuation Plan Based on a Time-Varying Network Algorithm

As a highly dense area for passengers, the airport departure hall is particularly characterized by the easy gathering of passengers, irregularity, and difficulty in command, which has become a high incidence of emergencies. For the evacuation problem in case of emergencies, the vast majority of passengers randomly choose the shortest path from the exit to escape, which will lead to congestion at some nodes and prolonging of the evacuation time. Therefore, this study proposes a better evacuation method considering the dynamic change in the spatiotemporal congestion of passengers. First, this paper constructs an evacuation network diagram for the departure hall of the Shenzhen Bao’an International Airport terminal building, simplifies the evacuation process into point-to-point evacuation, and proposes a time-varying network algorithm to optimize the emergency evacuation of the airport. Second, on the premise of obtaining the number and dynamic distribution of passengers in each area in real time, a linear programming model with the shortest evacuation time as the optimization objective is established, and the current optimal evacuation path of passengers is dynamically calculated. Finally, the two evacuation methods, random evacuation and evacuation, based on a time-varying network algorithm are simulated and analyzed by AnyLogic software. The results show that the evacuation scheme based on the time-varying network algorithm can effectively relieve the passenger congestion of some evacuation paths and safety exits. The evacuation time is reduced by 74 s, the evacuation efficiency is improved by 14%, passenger congestion at some evacuation routes and safety exits can be effectively relieved, and the global optimization of the emergency evacuation of passengers is achieved.

Loss of Life Estimation using Life Safety Model for Dam Breach Flood Disaster in Malaysia

The need for an emergency disaster management related to damhas risen up in recentyears. This is dueto uncertainties in global weather predictions which also affect local Malaysian area. With unpredictable prolonged rainy weather, concerns on events that could lead to flooding has triggered the authority to review the evacuation strategies in critical locations.This paper describes an investigation on the effect of early warning system and people response delayto the rate of fatality in the event of flooding due to dam breach. The Life Safety Model is utilized as a tool for the simulation of people vehicle and building response to 2D hydraulic flow of the river originated from the dam. The study area is based on KenyirDam and its surrounding vicinity. A number of scenarios are simulatednamely cases with and without early warning system. For the case with early warning system, different triggering time is also investigated. On top of that, the effect of people responsedelay to the warning system is simulated. It was found that early warning system plays a critical role in reducing the number of fatalities due to flooding. Equally important is the time taken for the community to start evacuating whentriggered by the early warning system.From the result LSM, optimum evacuation parameters could be identified and used for the purpose of design, planning and implementation of local emergency evacuation plan in the event of dam-related flooding.