Evacuation Model Research Articles

Psychological impatience in pedestrian evacuation: modelling, simulations and experiments

The study of psychological impatience has provided new insights into pedestrian behaviour and evacuation dynamics. However, previous works have mostly focused on investigating the impatience of the individual pedestrian, and there is a lack of research on the effect of impatience on different groups of pedestrians. This paper introduces an evacuation model considering both the self-growth and contagion of impatience for different groups of pedestrians. We apply the model to the scenario of two rooms separated by a corridor and conduct a series of parameter analyses of the rates of impatience self-growth and contagion. We first analyse the case that two groups of pedestrians have the same impatience self-growth rate. The results show that impatience contagion has a crucial effect on evacuation efficiency. In the no-contagion scenario, both too high and too low an impatience level lead to lower evacuation efficiency. In the contagion scenario, an increasing impatience level leads to lower efficiency. We then analyse the case that two pedestrian groups have different impatience self-growth rates. The results indicate that pedestrian groups with different self-growth rates have different evacuation efficiencies, where the pedestrian group with a higher impatience self-growth rate has a lower evacuation efficiency. A higher contagion rate results in a greater difference in evacuation efficiency between the pedestrian groups with different self-growth rates. Increasing the main exit width reduces the evacuation efficiency gap. Furthermore, we conducted a series of experiments under different impatience treatments to verify the model and found that the numerical results of our model agreed with the experimental results. The findings demonstrate that the proposed impatience model has the potential to accurately predict evacuation processes.

A data-driven, scenario-based human evacuation model for passenger ships addressing hybrid uncertainty

In a disaster at sea, the safe and timely removal of passengers from the ship is paramount. Here, a human evacuation plan enables passengers to be swiftly displaced from a risk area to one less so. Despite existing research on evacuation planning, there is a need for a more comprehensive model that considers various uncertainties and factors. This paper proposes an optimization evacuation model that balances uncertain variables, including passenger walking speed and travel distance, and deterministic factors like deck layout, door capacity, initial density, and corridor traffic flow. The model also accounts for varying starting locations and two levels of awareness—alert and non-alert. The model utilizes a data-driven technique, i.e., the k-means algorithm, to cluster historical data on speeds and generate scenarios. An adjustment scheme is applied to account for the ship's rolling motion, affecting passenger speeds during the evacuation planning period. Travel distance scenarios are produced to capture the impact of different route choices per passenger. A risk-neutral two-stage programming model is constructed to handle uncertainties. The model is tested on multiple problems for a passenger ship deck in day and night modes, revealing valuable managerial insights for the maritime safety sector.

Integrated tsunami risk framework considering agent-based evacuation modelling: The case of Saga, Kochi Prefecture, Japan

This study develops an integrated tsunami risk framework combining stochastic tsunami hazard and agent-based evacuation modelling. The framework is applied to the case of Saga, Kochi, Japan, with a population of ∼ 2,200 anticipated to experience significant tsunami events (∼ M9.0). First, stochastic earthquake source models are generated for two values of magnitudes (M8.8 and M9.0) and used to carry out stochastic tsunami inundation simulations. Agent-based tsunami evacuation modelling using MATSim is then performed by considering four mode scenarios: single mode (pedestrian and car) and two multimodal scenarios (mix of car and pedestrian). The stochastic tsunami simulations and agent-based evacuation modelling results are integrated to estimate the risk. The effect of existing tsunami evacuation points and tsunami evacuation towers on risk reduction is also assessed. Such an integration framework is finally used to recommend tsunami mitigation strategies in the tsunami-prone regions. Results show that a significant tsunami hazard (i.e., tsunami depth up to 15 m) is expected in the Saga district, with an arrival time between 5 and 30 min. In addition, the evacuation points on higher grounds effectively save local residents' lives, as shown by the small number of affected people, specifically for the pedestrian and multimodal models (i.e. 10-100 people, excluding the car model). However, up to ∼ 1,000 people may get affected if car is the sole mode of evacuation. Therefore, the coastal community is recommended to evacuate on foot. Finally, identifying and securing sufficient higher grounds and vertical evacuation points are essential for risk reduction.

A comprehensive approach in post-earthquake blockage prediction of urban road network and emergency resilience optimization

This study presents a probabilistic method for predicting urban road blockages due to the collapse of roadside buildings and develops network restoration planning through resilience optimization. Resilience analysis of a blocked network has faced two challenges: (1) blocked paths opening time estimation; and (2) network time-varying functionality evaluation. Probabilistic models, including earthquake magnitude, fault rupture location, seismic intensity, damage, debris, blockage, and debris evacuation models are utilized to determine the probability distribution of blocked paths opening time considering relevant uncertainties. A generalized network functionality metric is developed to evaluate network performance considering emergency multi-nodes such as medical centers. The optimization algorithm based on Simulated Annealing is extended for network restoration by assuming multi-location for resources pre-positioning. Three restoration scenarios are defined to identify required resources for network recovery with different restoration objectives. The proposed methodology is implemented in Region 2 of the Tehran metropolis. The results demonstrate that scenario (II) gives the highest number of required resources, so it is suitable where adequate resources are available. Scenario (III) predicts the least number of required resources; hence, it is appropriate where sufficient resources are not accessible. Subsequently, scenario (I) is an intermediate approach to determine the required resources with the lowest computational effort.

Research on the evacuation of people from a road tunnel fire based on a mathematical model

A mathematical model for the evacuation of people from a road tunnel is created, taking into account various factors such as the speed at which people move, the density of the flow of people, and the outcome of the fire. This model allows for the precise calculation of the evacuation time and the optimization of the evacuation route in a fire scenario. The constructed mathematical model was used to determine how long it would take for people to evacuate this road tunnel, and the findings of the Pathfinder simulation were compared. The findings demonstrate a relationship between the model's evacuation time and the human flow density, movement velocity, and fire product characteristics. The evacuation time is closer to the outcome of the actual fire scene when the impact of the fire environment on the speed of evacuation is quantified. The mathematical model of human evacuation's calculation of the evacuation time is essentially accurate when compared to the Pathfinder simulation's calculation, with an error of only 0.77 %. The model provides recommendations for optimizing the evacuation of people from a road tunnel in the case of a fire by not only predicting where the crowding would occur but also by calculating the duration of the crowding.

A modified social force model for sudden attack evacuation based on Yerkes–Dodson law and the tendency toward low risk areas

Various evacuation models are the internal support for the movement of pedestrians. Emergencies that occur in public places have the characteristics of suddenness, massive and unpredictability. These characteristics impact pedestrians’ psychological states, ultimately shaping their behaviors. However, the existing models do not fully consider this aspect. Therefore, for sudden attack events, based on the social force model and Yerkes–Dodson law, this paper proposes a modified model which considers the positive and negative effects of psychological state on pedestrians’ behaviors in three dimensions: the realization degree of desired speed, the proximity of attacker to pedestrian, and crowdedness. It also considers the diminishment of repulsion and the attractiveness of low risk areas. A behavioral model based on the exit-reorientation mechanism is proposed to describe the behavior of low risk exit selection according to the relative location of the attacker. The improved model is validated quantitatively and qualitatively, respectively. Simulations based on this model can effectively reproduce the behaviors of crowds in videos. The data of fundamental diagrams from our model fits well with that from videos. We find that the evacuation time is longer when the observation distance within a specific range in the simple scenario. The risk tolerance level of 8 m and 6 m are the critical points affecting the rate of change of survival rate and casualties, respectively. Simulation results indicate that the effect of rational people ratio on evacuation time will vary with risk tolerance level. This study offers insights into the dynamics of crowd evolution during an evacuation following a sudden attack, providing a foundation for exit allocation and emergency crowd guidance.

Analysis of Evacuation Efficiency for Differently-Abled People in Multi-Layered Buildings Based on Assistance Ratio

The term “differently-abled” refers to people with mobility difficulties, including the disabled and the elderly. In order to explore the optimal evacuation efficiency, in emergencies, of different floors in multi-layered buildings where differently-abled people reside, this study has established a mixed evacuation model based on the characteristics of the evacuation behavior of differently-abled people and non-differently-abled people. This model simulated the impact of evacuation strategies on different floors for differently-abled people at various assistance ratios. Through the comparative analysis of various evacuation strategies, an evacuation efficiency analysis model was constructed, which is suitable for multi-layered buildings where differently-abled people reside. The research indicates that, for stair-determined evacuation strategies, when the proportion of assisting personnel exceeds 70%, there is a noticeable improvement in overall evacuation efficiency. For elevator-determined evacuation strategies, evacuating middle floors with unrestricted methods can enhance evacuation efficiency. The analysis model for optimal evacuation efficiency on each floor that is presented in this study, using a five-story building as an example, can clearly and accurately determine evacuation strategies for multi-layered buildings where differently-abled people reside.

A modified social force model for crowd evacuation considering collision predicting behaviors

The social force model is one of the most common models used in the study of pedestrian dynamics. In the social force model, there are oscillation in the movement of pedestrians. To address the oscillation phenomenon, this paper modifies the way of setting psychological forces and judgment conditions based on previous research. By comparing the simulation results with the real experimental results, the evacuation time results are basically the same, which validates the effectiveness of the modified social force model. The simulation results show that the modified social force model eliminates the phenomenon of evacuee velocity oscillations near fixed obstacles in the original model and fixes the phenomenon of abnormal behavior of evacuees during collisions. In addition, we simulate different numbers of evacuees (i.e.,25,50,100,200) and the results show that the modified social force model successfully replicates the phenomenon of arch congestion during evacuation.

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 staged and simultaneous evacuation during a volcanic crisis of La Soufrière of Guadeloupe (France)

The seismic and fumarollic activity of La Soufrière de Gaudeloupe increased in 1992. Continuing unrest led the Observatoire volocanologique et sismologique of Guadeloupe (OVSG-IPGP) to recommend in July 1999 to the authorities that the volcano alert be set to “Vigilance” (yellow). The OVSG-IPGP has been particularly vigilant and reinforced its monitoring following another significant increase of unrest in 2017 that culminated in magnitude 4.1 felt earthquake and a probable failed phreatic eruption. Volcanic activity remains difficult to forecast precisely, so the only way to stay safe, in case of an impending eruption, is to move away from the threatened area. This can be a major problem for the authorities and the population. In the French overseas departments, despite the presence of several volcanoes, there is limited experience in managing volcanic emergencies, especially in areas with a high population density and strategic assets, such as the Basse-Terre region of Guadeloupe. Therefore, it is crucial to devise and assess an emergency management strategy to identify potential problems and dangers that may arise during a mass evacuation. Crisis exercises can be planned to prepare the authorities and the population, but they are rarely carried out due to the human and resource costs involved. A series of evacuation scenarios are evaluated through simulations. The scenarios model staged and simultaneous evacuations with different speeds of individual response times. The aim of this research is to evaluate the two main evacuation strategies defined in the current volcano emergency response plan for La Soufrière of Guadeloupe, revised in 2018 by the authorities. This paper describes a calibrated agent-based model of mass evacuation and its exploration focusing on the potential staged evacuations of the southern Basse-Terre area. The overall objectives of this research are to: (1) test the evacuation strategy of the current emergency plan, and (2) provide relevant information to stakeholders. The results of these simulations suggest that there is no significant difference between the two evacuation strategies. It is estimated that 95% of the population will be evacuated within 20 h with a simultaneous or a staged evacuation. Whatever the scenario, the simulation results show high levels of road congestion. However, the staged evacuation will significantly reduce the number of vehicles on the network during the peak time of the evacuation and therefore reduce dangerous situations and the potential for adding crises within a volcanic crisis.

Dynamic coupling model of FDS and cellular automata considering trampling behavior

Fire accidents usually cause large casualties. In this paper, a fire evacuation model based on the dynamic coupling of FDS and CA, which dynamically couples disaster data and evacuation behavior, is designed to reflect the impact of disaster factors on the pedestrian evacuation process in real-time. Furthermore, pedestrians are divided into two categories, one type of pedestrians will choose to move against the wall to reduce the risk of stampede accidents, and the other type of pedestrian will evacuate to the exit according to the normal movement method. And considering the role of information transmission between pedestrians, the two types of pedestrians will transform into each other. In addition, the concept of pedestrian crowding, support, and friction is introduced and viewed as an influencing factor of normal pedestrian falls. Set the panic value as the influencing factor of the efficiency of pedestrian information transmission and the death probability of downed pedestrians. The impact of pedestrian density, pedestrian walking behavior towards walls, evacuation response time, information propagation radius, heat release rate of the fire source, and the interference of smoke on the pedestrians' visibility range on evacuation outcomes has been discussed through numerical simulations. The analysis shows that although the presence of pedestrians walking against the wall will slightly increase the evacuation time, when the available evacuation time allows, the risk of a stampede will be greatly reduced; The increase in evacuation response time will aggravate the panic psychology of pedestrians and increase the risk of stampede accidents; The increase of the pedestrian information transmission radius will reduce the risk of a stampede, and the effect is more obvious when the pedestrian density is smaller; Selecting building materials with lower heat release rates can effectively reduce the risk of fire incidents; The restriction of visibility range by smoke seriously endangers pedestrian safety and reduces the efficiency of evacuation.Our research results can play a reference and guide for future building disaster prevention design and public safety research.

A day-to-day evacuation model to maximise transport resilience under dynamic hazards

ABSTRACT A transport network may face damage due to a disaster. Some roads may be wholly or partially closed, and the system cannot satisfy the whole demand. Critical considerations include transferring evacuees from dangerous zones to safe zones. This paper presents a novel optimization method that will allow a transport network to run more efficiently during a dynamic hazard that will change through the periods. The objective is to minimize the maximum time needed to evacuate the last group of people from critical and intermediate zones. Regarding the complexity class of evacuation problems, a Genetic Algorithm (GA) approach is designed to solve large-size problems. Also, the Sioux Falls network and Dublin Transportation Network case studies are defined to validate the proposed model and GA approach. This study assesses the system’s resilience during a critical event by comparing the system’s behavior before and during the hazard, which helps improve the recovery process.

Modelling and interpreting evacuation time and exit choice for large-scale ancient architectural complex using machine learning

The intricate spatial structures of large-scale ancient architectural complexes, combined with their complex crowd compositions, hinder evacuation efficiency. However, research on the evacuation of such complexes is limited. Moreover, among the existing evacuation studies, most solely rely on either simulation models or machine learning techniques. Few integrate the strengths of simulation modeling in capturing otherwise inaccessible evacuation data with the advantages of machine learning in addressing complex problems. This study aims to utilize random forest algorithm, based on Pathfinder simulation evacuation data, to model the evacuation time and exit choice of occupants within such complexes. Additionally, we employ tools to interpret the random forest models, analyzing the influence of various factors on evacuation time and exit choice. Specifically, this methodology was applied to examine evacuation time and exit choice of 4800 occupants, comprising both tourists and residents, within the Xidi ancient architecture complex that spans nearly 130,000 square meters. The reliability of the random forest evacuation models is validated using real experimental data. The results indicate that the impact of environmental factors on evacuation time is often nonlinear. Compared to environmental factors, individual factors tend to have a lesser influence on evacuation time. For exit choice, the influence of environmental factors varies in significance at different scales. Individual factors have a notably higher influence on exit choice than on evacuation time. We also discern that evacuation distance affects the degree to which other factors influence exit choice. Overall, this research contributes to a deeper understanding of evacuation time and exit choice in such complexes, offering decision-makers more comprehensive evacuation strategies.

Analysis of walking speeds of Brazilian primary school children descending stairs freely

The analysis of the typical values of unimpeded walking speed of primary school children in descending movement in stairs, the differences on walking speeds on the flights and landings and the impact of anthropometrical data (weight, height and bideltoid) in the walking speed of a children population are presented. The experiments were carried out with students of three primary schools in Brazil (ages 6 to 10). The objective was to get data to be used in evacuation modelling, free from influencing factors that can be found in data from fire drills, such as speed reduction due to crowds or adults controlling the flow. A new method of calculating walking routes in stairs was adopted in order to retrieve the walking speeds. Anthropometrical characteristics or age were not determinant for students' movement in free walking condition in this study. The mean value of speed obtained was 1.02 m/s on landings and 0.85 m/s on flights. The coefficients of variation (greater than 20 %) show that the distribution of values are quite wide, demonstrating a large dispersion of individual values. The reduction factor on flights for children, obtained in this study (0.81–0.9) is higher than those adopted in simulation models in general today (0.5–0.8).

Physics-based model and data dual-driven approaches for predictive evacuation

Physics-based models or data-driven methodologies can help acquire the evacuation process for optimizing evacuation and rescue plans. However, neither of these methodologies can predict the process rapidly and precisely. Physics-based models rely on physical rules of human behavior but are computationally expensive. Data-driven approaches need a significant amount of diverse data but lack an understanding of underlying human behavior in spinning emergencies. This short communication aims to initiate systematic discussions about a physics-based model and data dual-driven approach, combining both approaches’ strengths. This combined approach puts forward iterative updating loops, using physics-based models to identify evacuation stages, capture operational mechanisms, and act as rational boundaries while using data-driven methods to process each stage’s results rapidly. The authors synthesize a roadmap highlighting bottlenecks and potential research directions for achieving such a combined approach, calling for attention and collaboration in predictive evacuation for disaster response.

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.

Logistics of patient evacuation in response to disease Outbreaks: Critical considerations for transportation planning

The recent outbreaks of diseases have emphasized the importance of having robust decision-making models in place to aid in the evacuation of patients, particularly from overwhelmed hospitals to alternative facilities. The sudden surge of patients during an outbreak can quickly deplete a hospital's resources, leading to compromised healthcare delivery and an increase in mortality rates. Evacuating patients to other hospitals can alleviate the burden on a single facility, but numerous factors need to be considered when making evacuation decisions, including patient acuity, transportation logistics, and bed availability at other facilities. Despite the critical role of patient evacuation in disease outbreaks, there has been a lack of systematic and comprehensive research on developing decision-making models that identify the critical factors. This paper aims to bridge this gap by providing the key factors that should be considered when creating decision models for patient evacuation in response to contagious disease outbreaks. The findings reveal that decision-making processes are influenced by a multitude of factors, including patient numbers and classifications, staff scheduling and assignments, resource availability for transportation, road traffic conditions, capacities and numbers of evacuation and receiving hospitals, as well as the behaviour of disease outbreaks. These findings provide practical insights for relevant authorities to optimize emergency strategies during disease outbreaks and enhance the overall resilience of the healthcare system against external disruptions.

A queuing evacuation model with yielding behavior

A new super queue model with yielding behavior is proposed to model the orderly evacuation process of young pupils in a classroom building. A super queue is composed of a super leader and several simple queues. Based on this, a leader-follower model is proposed to model the orderly behavior between pupils in a super queue, and an exclusive channel model is proposed to model the yielding behavior between super queues. Taking the evacuation of a classroom building as an example, the super queues and yielding behavior are reproduced and are very similar to the actual behavior (both qualitatively and quantitatively). Based on the model, scenarios are simulated to analyze the impacts of several factors on evacuation efficiency. The results show the following: (1) The stop-and-go effect greatly affects the overall evacuation efficiency. Therefore, it is necessary for students to maintain sufficient concentration to shorten their reaction time during the stopping and going process, thereby improving the evacuation efficiency. (2) Different yielding strategies have little impact on the overall evacuation efficiency. Therefore, in an actual evacuation case, flexible yielding strategies can be adopted in order to consider the needs of each class. (3) By optimizing evacuees’ behaviors, such as improving their reaction times, the efficiency of an evacuation with queuing and yielding can become close to that of a disordered evacuation. At the same time, due to its higher safety and easier management process, a queuing and yielding evacuation can be a safe and relatively efficient method for real evacuations.

Research on escalators used as evacuation stairs under fire scenarios

Shopping malls are crowded areas which makes the evacuation routes unable to meet personnel evacuation needs. Therefore, this paper proposes the idea of using escalators evacuation to increasing evacuation routes. In addition, the effects of escalator fire shutters on the use of escalator evacuation paths, and the efficiency of mall personnel evacuation under different conditions were simulated. The results show that the different states of fire shutters have different effects on the emergency evacuation. When the fire shutter is not lowered, it will result in 1 person not being evacuated to complete. However, when the fire shutter is lowered to 1.8 m from the ground or sprinklers are set, escalators can be used for evacuation routes are verified. And compared to the normal descent of the fire shutter (only the staircase evacuation, 2 people not evacuate completed), the evacuation of people is completed and the efficiency of evacuation is improved. This result can improve the new evacuation model for emergency evacuation plans of shopping malls with escalators.

Tsunami Evacuation Accessibiliyu Simulation Using Network Analysis Tools In Tsunami Prone Areas Of Tanggamus District

Geological activity in the Sunda Strait received attention through the tsunami that occurred at the end of 2018 and the tectonic earthquake in the Sunda Strait subduction zone with Magnitude 6.9 on August 2, 2019. These conditions raise concerns about the threat of earthquake and tsunami disasters in the surrounding area. Tanggamus Regency, which is located within a fairly close radius to the Sunda Strait, has a very wide tsunami-prone lowland, especially in the area around the tip of Teluk Semangka. Based on these conditions, this research generally aims to map evacuation service areas, map evacuation times, and analyze effective evacuation models. To answer these challenges, this research was conducted following several methodological stages. It started with defining the study area using spatial analysis, digitizing the road network and interlinking it with the Network Analysys tool on the ArcGIS platform. Based on the observation, it was found that the most at-risk areas are those that have the farthest distance from the Temporary Evacuation Site (TES) location when traveled without a vehicle. Each region has a TES location that can be reached using the available roadways. There are 3 sub-districts that have a travel time of more than 30 minutes to reach the TES, namely, Semaka sub-district, Wonosobo sub-district and Kota Agung Barat sub-district. It is expected that the results of this study can be one of the considerations in tsunami disaster mitigation efforts in Tanggamus Regency.