Evacuation Time Research Articles

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.

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.

Rethinking limb tourniquet conversion in the prehospital environment.

Limb tourniquets are among the most effective lifesaving interventions after severe injury. Tourniquets used for less than two hours have proven safe, even when in hindsight the tourniquet was determined not to have been necessary. However, tourniquets used for longer than 2 hours may result in severe ischemic changes, fasciotomy rhabdomyolysis, renal failure, amputation and death.Given their frequent use after even minor limb injury (>50%), as soon as safely feasible all limb tourniquets must be reassessed. They may be transitioned to a hemostatic dressing with tourniquet release, (tourniquet conversion, TC), or moved to just above the injury site (tourniquet replacement, TR). Their near ubiquitous application by medical and non-medical personnel has resulted in significant discussion regarding who should perform TC/TR if arrival at a forward medical location is delayed. In the ongoing war in Ukraine, the first near peer large scale combat operation in 80 years, prolonged evacuation times are common and have highlighted the need for early TC/TR prior to hospital arrival. Similar concerns exist in the austere rural and wilderness civilian setting where prolonged tourniquet application is common, given the long distances to a trauma center.This article describes proposed changes in tourniquet use and how the anticipated duration of tourniquet application dictates increased training requirements. Increased emphasis on who needs a tourniquet and then TC/TR is necessary to maximize benefit while minimizing potential harm.Level of Evidence and Study Type: N/A.

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.

Directional analysis of community wildfire evacuation capabilities

Wildfires are a natural part of forest ecosystems, but sometimes pose a threat to communities. In Canada, when public safety is threatened by a wildfire encroaching into the wildland-urban interface (WUI), fire management agencies will recommend that local authorities evacuate the area. If a fire spreads quickly towards a community and egress capacity is insufficient, public safety can be compromised. This paper presents an interdisciplinary approach for assessing community directional vulnerabilities for wildfire evacuation, combining techniques from wildland fire science and transportation engineering. For a selection of communities in Alberta that were assessed as being potentially vulnerable to wildfire, we explored the directional configuration of the transportation network in relation to a directional assessment of wildfire exposure. We first plotted the viable fire pathways and transportation facility characteristics, and then compared estimated fire encroachment times against estimated community egress times, directionally around each community to show evacuation vulnerabilities. Our results show that some communities, mainly within the Boreal Forest, Foothills and Rocky Mountain natural regions, have egress routes that are highly exposed to potential wildfire encroachment. Our findings also indicate that the evacuation timing for some larger communities needs attention, given relationships between estimated fire travel times and evacuation times. The results can be used to inform evacuation preparedness planning and proactive mitigation efforts.

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.

Simulation Study of Pedestrians Evacuation Considering Aggressive Behavior

Conflict during an evacuation may turn into aggressive behavior and create problems for evacuation. To study the influence of attack behaviors such as pushing and shoving on evacuation and the evacuation law, an extended cellular automata model is developed in this paper. In the model, pedestrian movement is influenced by static, dynamic, and attack floor fields. In addition, pedestrian vision is influenced by the direction and location of movement of surrounding pedestrians, and pedestrians adopt different coping strategies for attacks: avoidance detour, or imitation. Attacker movement and aggressive behavior are also studied. Numerical simulations are conducted to discuss the pedestrian evacuation problem under attack behavior. The effects of the evacuation process, attack field sensitivity coefficient, location of fallen pedestrians, pedestrian density, number of initial attackers, initial attacker location, and pedestrian imitation ratio on evacuation time and number of fallen pedestrians are analyzed. The simulation results show that an appropriate increase in the impact of the attack field can slow down the congestion, that is, the evacuation time is the fastest at kA = 0.5. The evacuation time is faster when the room is full of normal pedestrians or full of attacking pedestrians. The number of casualty pairs is high when the initial position of the attacker is in the middle of the inner side of the room. The results of the study can provide recommendations and guidance for the formulation of evacuation strategies for pushing and shoving type attacks and reducing casualties.

The impact of subway car interior design on passenger evacuation and boarding/alighting efficiency

This study investigated the impact of subway car interior design on passenger evacuation and boarding/alighting efficiency. The usability of pedestrian agent models was verified through real-life experiments. A seven-factor orthogonal simulation experiment was designed, using key geometric features of the subway car interior as variables. The results of the computer simulation showed that the impact of subway car interior design factors on evacuation and boarding/alighting time was not entirely consistent, with seat layout and door width being the most important factors affecting passenger movement. In the evacuation scenario, only the connectivity of the subway car has no effect on evacuation time, while in the boarding and alighting scenario, seat layout, car type, door width, and foyer width all significantly affect boarding and alighting time. Multivariate regression models were established to predict evacuation and boarding/alighting times through design features, which can explain 86.7% and 58.9% of the time variation, respectively. The research results were used to guide subway car design, and the proposed new scheme demonstrated better performance.

The Perfect Med Bag is One that Doesn't Fall Off a Cliff: A Combat Mass Casualty Case.

Military trauma provides a unique pattern of injuries due to the high velocity, high kinetic energy ammunition utilized, and the high prevalence of blast injury. To further complicate this, military trauma often occurs in austere environments with limited logistical support. Therefore, military medical providers are forced to learn nonstandard techniques and when necessary, practice a level of improvisation not commonly seen in other medical fields. The case presented in this manuscript is a prime example of these challenges. At the onset of fighting both the medic's rucksack, carrying with it the primary source of medical gear and the precious supply of cold-stored blood products are lost. The scenario was further complicated by rough mountainous terrain and a prolonged evacuation time. The medical provider was forced to utilize nonstandard devices such as an improvised junctional tourniquet which used a rock to focus the devices pressure. They also adapted their basic understanding of surgical procedures to conduct a vascular cutdown procedure for wound exposure and effectively pack an otherwise non-compressible wound to a major artery. Despite a significant loss of equipment, the medic and their team were able to successfully care for a number of patients in this mass casualty scenario.

Association of Prehospital Neck Wound Survivability and Battlefield Medical Evacuation Time in Afghanistan.

The U.S. Military's Golden Hour policy led to improved warfighter survivability during the Global War on Terror. The policy's success is well-documented, but a categorical evaluation and stratification of medical evacuation (MEDEVAC) times based on combat injury is lacking. We queried the Department of Defense Joint Trauma System Prehospital Trauma Registry for casualties with documented penetrating neck trauma in Afghanistan requiring battlefield MEDEVAC from June 15, 2009, through February 1, 2021. Casualties were excluded if the time from the point of injury to reach higher level medical care was not documented, listed as zero, or exceeded 4 hours. They were also excluded if demographic data were incomplete or deemed unreliable or if their injuries occurred outside of Afghanistan.We designed a logistic regression model to test for associations in survivability, adjusting for composite injury severity score, patient age group, and type of next higher level of care reached. We then used our model to interpolate MEDEVAC times associated with 0.1%, 1%, and 10% increased risk of death for an incapacitated casualty with penetrating neck trauma. Of 1,147 encounters, 444 casualties met inclusion criteria. Of these casualties, 430 (96.9%) survived to discharge. Interpolative analysis of our multivariable logistic regression model showed that MEDEVAC times ≥8 minutes, ≥53 minutes, and ≥196 minutes are associated with a 0.1%, 1%, and 10% increased risk of mortality from baseline, respectively. Our data characterize the maximum MEDEVAC times associated with 0.1%, 1%, and 10% increased risk of death from baseline survivability for penetrating battlefield neck trauma in Afghanistan.

The study of self-organised behaviours and movement pattern of pedestrians during fire evacuations: virtual experiments and survey

In this study, Minecraft was adopted to investigate pedestrian behaviours and evacuation processes in non-fire (normal) and fire conditions involving multiple simultaneous players. We built a PaddlePaddle-based deep learning platform for the automatic recognition of pedestrian coordinates from the Minecraft background database. To verify the virtual experiments in Minecraft, we conducted a series of experiments under identical conditions in a real (physical) room and virtual environment on the Minecraft platform. The pedestrian behaviour, flow patterns and evacuation time in the Minecraft experiments fit well with the results of the real-life experiments, indicating the potential of Minecraft for realistically simulating evacuation processes. To further demonstrate the feasibility of using Minecraft for evacuation studies, we conducted a series of virtual evacuation experiments with different fire configurations and room geometries in Minecraft. The pedestrians were found to keep higher distance towards fire and greater detour angle during the fire emergency in a square room. Furthermore, in the scenario of a fire in a corridor, in addition to the aforementioned fire avoidance behaviours, the pedestrians exhibited orderly queuing and exited the room one by one, resulting in increased walking speeds and thus a faster evacuation for most pedestrians. Finally, one post-experiment survey was designed to assess participants' perceptions of the Minecraft environment and the pedestrian behaviours and related psychological factors. The results show that the Minecraft can generate considerate realistic real-life situations, and pedestrians chose self-organised behaviours including away from fire, along the wall and detour towards fire in both survey and evacuation experiments.

Trauma THOMPSON: Clinical Decision Support for the Frontline Medic.

U.S. Military healthcare providers increasingly perform prolonged casualty care because of operations in settings with prolonged evacuation times. Varied training and experience mean that this care may fall to providers unfamiliar with providing critical care. Telemedicine tools with audiovisual capabilities, artificial intelligence (AI), and augmented reality (AR) can enhance inexperienced personnel's competence and confidence when providing prolonged casualty care. Furthermore, implementing offline functionality provides assistance options in communications-limited settings. The intent of the Trauma TeleHelper for Operational Medical Procedure Support and Offline Network (THOMPSON) is to develop (1) a voice-controlled mobile application with video references for procedural guidance, (2) audio narration of each video using procedure mentoring scripts, and (3) an AI-guided intervention system using AR overlay and voice command to create immersive video modeling. These capabilities will be available offline and in downloadable format. The Trauma THOMPSON platform is in development. Focus groups of subject matter experts will identify appropriate procedures and best practices. Procedural video recordings will be collected to develop reference materials for the Trauma THOMPSON mobile application and to train a machine learning algorithm on action recognition and anticipation. Finally, an efficacy evaluation of the application will be conducted in a simulated environment. Preliminary video collection has been initiated for tube thoracostomy, needle decompression, cricothyrotomy, intraosseous access, and tourniquet application. Initial results from the machine learning algorithm show action recognition and anticipation accuracies of 20.1% and 11.4%, respectively, in unscripted datasets "in the wild," notably on a limited dataset. This system performs over 100 times better than a random prediction. Developing a platform to provide real-time, offline support will deliver the benefits of synchronous expert advice within communications-limited and remote environments. Trauma THOMPSON has the potential to fill an important gap for clinical decision support tools in these settings.

Simulation of bi-directional pedestrian flow in corridor based on direction fuzzy visual field

Bi-directional pedestrian flow in corridors is a complex dynamic system due to the diversity in pedestrian psychological characteristics. Incorporating individual differences of pedestrians is vital for improving pedestrian flow models. However, due to the inherent complexity and variability of pedestrian movement, model parameter calibration remains challenging. Controlled experiments are needed to collect empirical pedestrian movement data under different environments. This enriches the database on pedestrian movement patterns and provides necessary support for improving pedestrian flow models. To address this issue, we conducted controlled experiments to quantify pedestrian heterogeneity by defining the direction of fuzzy visual field (DFVF). The DFVF incorporates various static and dynamic pedestrian factors. We used it to modify the traditional cellular automata model. This improved model simulates bi-directional pedestrian movements in the corridors, reproduces density-speed and density-volume relationships, and reveals self-organization phenomena. Furthermore, an analysis was conducted to examine the impacts of pedestrian density and facility spatial layout on evacuation time. Pedestrian interactions were also studied to uncover fundamental bi-directional flow properties. As pedestrian density increased, the evacuation time showed an exponential upward trend. Corridor length significantly impacts evacuation time, while increasing corridor width helps control it. As crowd density increases, pedestrian flows exhibit three distinct steady states: the strolling flow at low densities, directional separated flows at medium densities, and dynamic multi-lane flows at high densities. In summary, the modified cellular automata model successfully incorporates pedestrian heterogeneity and reveals intrinsic bi-directional pedestrian flow patterns. This study provides valuable insights for pedestrian facility design and optimizing pedestrian flow organization.

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.

Features of determining the time of evacuation of people from buildings in case of fire

The object of the study is the safe evacuation time of people in case of fire from a typical secondary education institution. The problem was solved, which consisted in the inconsistency of the quantitative assessment of «pre-evacuation time» set out in DSTU 8828:2019, which is regulated by the requirements of DBN B.2.5-56:2014, with today’s conditions, when determining the safe time of evacuation from buildings and structures. Thanks to the obtained results, features were revealed that fully determine the dependence of the relationship between the pre-evacuation time and warning systems on the example of a typical secondary education institution. The evacuation time was determined according to DSTU 8828:2019, taking into account the requirements of DBN B.2.5-56:2014. The total evacuation time from the building was 687 s. The time of blocking evacuation routes and evacuation exits by dangerous fire factors is determined. The results of the recorded temperature did not exceed 46 оC, the value of oxygen was not recorded lower than ≥0,226 kg/m3, the density of carbon monoxide was not more than ≤1,16•10-3 kg/m3 during the total evacuation time, which meets the requirements of fire safety. The results of the recorded visibility exceed the maximum permissible values. Thus, the path to evacuation exit № 1 using stairwell № 1 takes place through door № 7. Movement through this door lasts for 531 s, therefore, now when the last person passes through stairwell and door № 7, the visibility is already ≤6 m. Therefore, evacuation through stairwell № 1 is dangerous. In addition, the last person passes through the door of the evacuation exit № 1 for 550 s, where the visibility value is ≤9 m, which is also an excess of the maximum permissible values, according to the requirements.

Simulation study on fire and evacuation of super high-rise commercial building

The construction of high-rise and multi-functional commercial buildings has emerged as a global trend, but it also introduces significant fire hazards. Consequently, there is a pressing need to examine the fire development trends in super high-rise commercial buildings and establish logical evacuation strategies. This study utilizes the Pyrosim program to simulate a typical fire scenario at the Yangtze River International Conference Center, allowing for the acquisition of essential fire parameters and available evacuation time. Subsequently, based on the complex functional zones and personnel distribution within the building, appropriate evacuation plans are devised and simulated using the Pathfinder software. The results reveal that by effectively utilizing stairs, elevators, and refuge floors in accordance with personnel distribution, evacuation efficiency can be substantially enhanced. Furthermore, the required evacuation time during nighttime fires is merely 36.6%–55.3% compared to unorganized evacuation. The findings of this study offer valuable theoretical guidance for the evacuation of super high-rise commercial buildings, holding immense significance in minimizing fire-related casualties within such structures.

Quantitative assessment of flooding risk based on predicted evacuation time: A case study in Joso city, Japan

Flooding is a frequent natural hazard, threatening people's lives and properties worldwide. Even though completely preventing damage from flooding is impossible, an appropriate evacuation can help minimize its impact and mitigate human casualties. However, analyzing various flooding information to make quick evacuation judgments is challenging for decision-makers. Therefore, a quantitative flooding risk assessment is needed to support appropriate evacuation decisions. This study introduces the travel time under ideal evacuation conditions to quantify evacuation vulnerability, with Dijkstra's algorithm finding the evacuation route and the Random Forest algorithm predicting the evacuation time. The evacuation vulnerability is then integrated with time-varying flooding hazards and estimated congestion levels to assess evacuation risk. Herein, a case study in Joso, Japan is used as an example to demonstrate the practicality and applicability of the proposed approach. As a result, the prediction model achieved high accuracy with an RMSE of 0.88min and a MAPE of 5.88 %. The proposed approach clearly illustrated the vulnerable areas and times that may hinder an efficient evacuation process. Also, this approach identified and visualized the individual evacuation risk distribution during a given flooding scenario: 49.38 % of buildings were assessed as having the highest-risk: no evacuation ability, while a maximum of 11.86 % and 3.83 % of the buildings were assessed as middle-risk and high-risk. Furthermore, the regional evacuation deadline and priorities were specified to ensure timely and effective evacuation. Overall, this study develops an approach for assessing evacuation vulnerability and risk that could facilitate awareness among the public and provide judgmental bases for evacuation preparedness and decision-making.

Effect of the Effective Clear Width of Door in a Modular Classroom on Evacuation Time

The purpose of this study was to measure and analyze the change in evacuation time according to the effective clear width of the entrance door of a modular classroom using an evacuation simulation program. In order to measure the evacuation time in this manner, a scenario was constructed to analyze the change in evacuation time owing to the increase in the effective clear width of the entrance. On the one hand, an entrance door width exceeding 140 cm did not affect the evacuation time. On the other hand, the evacuation took the longest when the door width was much narrower (60 cm). As the effective clear width of the entrance to the modular classroom increases, the evacuation time decreases. If the modular classroom is occupied by many students, it is necessary to establish a separate rule for the effective clear width of the entrance in the Rule on the Standard for Evacuation and Fire Structure of Buildings.

An efficient evacuation path optimization for passengers in subway stations under floods

The optimization of passenger evacuation paths in subway stations under flood scenarios plays an important role in improving evacuation efficiency and ensuring escape safety. Considering the impact of evacuation network failures such as gates on path planning, a two-stage passenger evacuation path optimization method under flood scenarios of subway stations is established with the objectives of minimizing total evacuation time, risk, and congestion. The black widow algorithm is proposed to optimize the BP neural network model to predict the travel time of passengers at nodes, which could improve the prediction accuracy of calculating the total evacuation time. The path optimization model is solved by the NSGA-II algorithm, and the optimal Pareto solution is determined based on the minimum total cost. Taking a subway station in Qingdao, China as an example, a passenger evacuation simulation system under flood scenarios is built using PathFinder software. The effect of the path optimization strategy is comprehensively evaluated through comparative experiments. It is found that the overall evacuation optimization degree could be increased by 18.75%, by comparing the evacuation time, congestion, and risk objectives under the situations with and without path optimization strategies.

Agent-Based Modeling of Tsunami Evacuation at Figueirinha Beach, Setubal, Portugal

Previous tsunami numerical model results show that the 1755 tsunami reached the Figueirinha beach 35 min after the earthquake, resulting in the inundation of the beach, the parking lot, and two sections of the road on the beach. Thus, an effective evacuation plan for the beach must be identified. However, conducting drills and evacuation exercises is costly and time-consuming. As an alternative, this study develops an agent-based model (ABM) to simulate the evacuation of beach users. The findings from this study reveal that, across the six considered scenarios, it is not feasible to evacuate all beach users in less than 35 min. The results also show there are only two routes available for evacuation—the left and right sides—with the left side offering a shorter evacuation time. However, both evacuation options come with advantages and disadvantages. The results of this study will be disseminated to local stakeholders.