Simulation Of Pedestrian Evacuation Research Articles

Assessing and Improving Fire Safety Measures of Healthcare Facilities with Special Reference to Pedestrian Flow Evacuation Simulation and Evacuation Dynamics

Assessing and Improving Fire Safety Measures of Healthcare Facilities with Special Reference to Pedestrian Flow Evacuation Simulation and Evacuation Dynamics

Simulation of pedestrian evacuation with reinforcement learning based on a dynamic scanning algorithm

Simulation of pedestrian evacuation with reinforcement learning based on a dynamic scanning algorithm

Agent-based simulation of seismic crisis including human behavior: application to the city of Beirut, Lebanon

Earthquake simulations at the urban scale usually focus on estimating the damages to the built environment and the consequent losses without fully taking into account human behavior in crisis. Yet, human behavior is a key element for improving crisis disaster management; therefore, it is important to include it in seismic crisis simulations. In this study, an agent-based model for the simulation of pedestrian evacuation during earthquakes at the city scale is developed following an interdisciplinary approach. The model recreates the urban conditions using Geographic Information System (GIS) and a synthetic population, in addition to the earthquake consequences on the urban fabric. Moreover, the model integrates realistic human behaviors calibrated using quantitative survey results. We simulate pedestrian outdoor mobility with the different constraints that affect it such as the topography and the presence of debris. The simulator is applied to the case of Beirut, Lebanon. A what-if approach is adopted to analyze the population’s safety in case of earthquakes in Beirut, particularly the open spaces’ capacity to provide shelters and the effect of debris and realistic human behaviors on people’s safety. The simulation results show that less than 40% of the population is able to arrive at an open space within 15 min after an earthquake. This number is further reduced when some open spaces are locked. Debris and realistic human behaviors significantly delay the arrivals to safe areas and, therefore, should not be neglected in earthquake simulations.

A simulation evacuation framework for effective disaster preparedness strategies and response decision making

The damage and destruction of homes, buildings, and other infrastructure after a major earthquake makes it necessary for a segment of the population to be evacuated to emergency shelters. However, since areas prone to earthquakes face a major strike at highly unpredictable and infrequent times, disaster and evacuation management can and should be enhanced through the development and effective utilization of useful simulation models. We utilize the Stochastic Pedestrian Cell Transmission Model (SPCTM), a real data-based pedestrian evacuation simulation framework built in collaboration with the National Science and Technology Center for Disaster Reduction (NCDR) in Taiwan to carry out various statistical analyses to gain useful insights for disaster management decision makers. In particular, SPCTM is used to (1) examine how evacuee compliance rate with the current government evacuation protocol (as opposed to SPCTM) affects the total evacuation time (2) compare the results of the evacuation process for different neighborhoods and compliance rates in Da’an district, and (3) determine how allocating different subsets of shelters to be opened affects the evacuation response time. The analysis results are insightful for government officials to formulate effective evacuation guidelines and strategies in the preparedness or response phases.

Groups in pedestrian evacuation: Survey data on attitudes

Pedestrian evacuations can occur during special events where people gather in buildings or sporting arenas. People might attend such events with friends and family. The study of pedestrian behavior has evolved with many new studies that include pedestrian group behavior within their models to help determine the relevance of groups on the overall evacuation. This paper focuses on better understanding an individual's decision-making during an evacuation when they are responsible for leading others to safety, especially regarding group composition. Data were collected using questionnaires about an evacuation scenario of a church in the USA (Norfolk, Virginia), of which there were approximately 350 parishioner respondents. Analysis of results shows several interesting results: group leaders take fewer risks and want closer group cohesion when leading groups that include vulnerable members (i.e., children, disabled adults, or older persons); male leaders, though normally risk-takers are shown to want closer group cohesion during road interactions; and leaders of vulnerable groups were shown to be less likely to search for alternative exits when faced with a congested area. The results can potentially inform pedestrian evacuation simulation models to help better depict crowd behavior.

Large scale simulation of pedestrian seismic evacuation including panic behavior

Understanding human behavior and predicting evacuation processes subsequently to an earthquake are critical aspects to provide valuable information to support disaster response activities. One possible and relevant aspect that characterizes human behavior in emergency situations is panic reactions, which can lead to dysfunctional and irrational responses by fugitives. Given the relevance of this component, this paper implements a panic behavior model in a large-scale agent-based model considering phenomenal parameters, such as seismic damage to the built environment, disruption of roads by earthquake-induced falling debris, and injuries of individuals. The proposed model is applied and tested in IdealCity, a virtual city simulation environment which resembles the geometry of the city of Turin, with about 900,000 inhabitants. The numerical simulations show that the inclusion of a panic behavior model increases the evacuation time despite the increased speed of agents during the evacuation process and this is probably caused by the fact that pedestrians tend to perform random actions before reaching their destination. Furthermore, existing human relationships between agents tend to convert the crowd from individual agents to group of agents that move together, and this behavior might affect the shelter saturation time of both shelters and hospitals as shown in the simulations analyzed in this paper.

The construction and application of event logic graph for pedestrian flow evacuation in typical scenarios

An event logic graph is a kind of knowledge mapping technology for knowledge inference and simulation analysis, which takes events as the core and portrays the hierarchical system and logical evolution pattern between events. In order to apply it to further improve the accuracy of related studies, such as pedestrian flow evacuation, simulation model optimization and risk prediction. In this paper, we use social network resources, media resources and journal database resources to build our corpus and adopt the explicit event relationship extraction method based on syntactic dependency and the implicit event relationship extraction method based on BERT+Bi-LSTM+Attention+Softmax for the characteristics of explicit event relationship and implicit event relationship, respectively. This paper constructs a pedestrian flow evacuation matter mapping for three typical scenarios and discusses its application path. It is found that once a sound knowledge base of logical reasoning and event logic graph is established, both research on optimization of pedestrian flow evacuation simulation models and research on identification and assessment of pedestrian flow evacuation safety risks will receive excellent support.

Pedestrian evacuation simulation in multi-exit case: An emotion and group dual-driven method

This paper analyzes the characteristics of emotion state and group behavior in the evacuation process. During the emergency evacuation, emotion state and group behavior are interacting with each other, and indivisible. The emotion spread model with the effect of group behavior, and the leader–follower model with the effect of emotion state are proposed. On this basis, exit choice strategies with the effect of emotion state and group behavior are proposed. Fusing emotion spread model, leader–follower model, and exit choice strategies into a cellular automata (CA)-based pedestrian simulation model, we simulate the evacuation process in a multi-exit case. Simulation results indicate that panic emotion and group behavior are two negative influence factors for pedestrian evacuation. Compared with panic emotion or group behavior only, pedestrian evacuation efficiency with the effects of both is lower.

Pedestrian emergency evacuation model based on risk field under attack event

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

A Data Driven Approach to Simulate Pedestrian Competitiveness Using the Social Force Model

The research of pedestrian evacuation dynamics is of significance to understanding and preventing human stampedes. Since empirical approach of reproducing true emergency evacuations is impossible due to safety issues. Theoretical approach based on numerical simulation has called the attention from researchers. In the simulation of pedestrian evacuation, a critical problem is how to simulate pedestrian competitiveness to reproduce emergency evacuation. Based on the social force model, researchers have tried to simulate pedestrian competitiveness through adjusting some model parameters. However, in most cases handcrafted values are adopted without calibration, thus unrealistic results might be produced. In this study, we applied a differential evolutionary algorithm to determine the optimal parameter specifications of the social force model by adjustment to empirical data. We conducted pedestrian experiments where five participants including patient and impatient individuals proceeded through a narrow corridor. Taking the distance between simulation results and empirical data as objective function, a minimization problem was generated. A differential evolutionary algorithm was adopted to search for the optimal combination of parameters. We found that though at initialization all the parameter values were randomly determined, the difference between patient and impatient pedestrians could be captured by adjustment to empirical data. This highlights the need to better understand and research pedestrian heterogeneity in terms of competitiveness.

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

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

Research on Path Planning Algorithm for Crowd Evacuation

In recent years, crowded stampede incidents have occurred frequently, resulting in more and more serious losses. The common cause of such incidents is that when large-scale populations gather in a limited area, the population is highly unstable. In emergency situations, only when the crowd reaches the safe exit as soon as possible within a limited evacuation time to complete evacuation can the loss and casualties be effectively reduced. Therefore, the safety evacuation management of people in public places in emergencies has become a hot topic in the field of public security. Based on the analysis of the factors affecting the crowd path selection, this paper proposes an improved path-planning algorithm based on BEME (Balanced Evacuation for Multiple Exits). And pedestrian evacuation simulation is carried out in multi-exit symmetrical facilities. First, this paper optimizes the update method of the GSDL list in the BEME algorithm as the basis for evacuating pedestrians to choose an exit. Second, the collision between pedestrians is solved by defining the movement rule and collision avoidance strategy. Finally, the algorithm is compared with BEME and traditional path-planning algorithms. The results show that the algorithm can further shorten the global evacuation distance of the symmetrical evacuation scene, effectively balance the number of pedestrians at each exit and reduce the evacuation time. In addition, this improved algorithm uses a collision avoidance strategy to solve the collision and congestion problems in path planning, which helps to maximize evacuation efficiency. Whether the setting of the scene or the setting of the exit, all studies are based on symmetric implementation. This is more in line with the crowd evacuation in the real scene, making the experimental results more meaningful.

Pedestrian evacuation modeling and simulation in multi-exit scenarios

This paper proposes a multi-exit evacuation model based on a continuous model for the pedestrian evacuation problem. Firstly, it is determined that the distance between pedestrians and exits, the pedestrian density near exits, and the width of exits are the main factors for exit selection. A pedestrian multi-exit selection model is defined by taking the three factors into account. Secondly, a pedestrian evacuation model is constructed by considering the impact of pedestrian psychological factors on expected speed and exit attractiveness. Finally, the multi-exit evacuation is simulated, and the pedestrian evacuation process is tested on three conditions. The effects of pedestrian density near the exit and the width of exit are analyzed on the final simulation. The simulation results show that the evacuation model can effectively simulate the pedestrian evacuation process in multi-exit scenarios.

Pedestrian evacuation simulation in indoor emergency situations: Approaches, models and tools

Pedestrian evacuation simulation (PES) provides a low-cost and low-risk method to facilitate safety design and emergency management in indoor environment by describing pedestrian evacuation behaviors and predicting evacuation outcomes in what-if scenarios. The area of PES has witnessed rapid growth over the past few decades, but there lacks an up-to-date review of the existing literature that could comprehensively reflect the latest advancements in this area. To address this need, this paper proposes a three-layer analytical framework for synthesizing the abundant literature on PES approaches, PES models and PES tools, and presents a systematic review of the state of the art in the PES area. The findings point out that (1) the use of high-fidelity PES approaches has become more prevalent over time; (2) the adaptability of PES models to different evacuation scenarios is relatively limited; (3) modeling of human behavioral mechanism is the driving force for PES model advancement; and (4) verification and validation are the major challenges for PES tools. Finally, the paper outlines possible directions for future research and discusses specific challenges to address for each direction. This paper is expected to benefit academics and professionals whose work requires the use of PES tools, provoke innovative studies that would push the boundaries of this area, and advance the understanding of pedestrian evacuation behavioral mechanisms and behavioral intervention measures, which would ultimately lead to enhanced human safety in indoor emergencies.

A hierarchical agent-based approach to simulate a dynamic decision-making process of evacuees using reinforcement learning

Simulation models are an undeniable tool to help researchers and designers forecast effects of definite policies regarding pedestrian social and collective movement behaviour. Considering both the environment's details and the complexity of human behaviour in choosing paths simultaneously is the main challenge in micro-simulation pedestrian dynamics models. This paper aims to present a novel comprehensive hierarchical agent-based simulation of pedestrian evacuation from a dynamic network of the environment using reinforcement learning, which is the closest to human behaviour among the other machine learning algorithms. In the approach, agents autonomously decide through a three-layer hierarchical model, including goal, node, and cell selection layers. A multinomial logit model is used to model the process of choosing the main movement direction at each time-step. The proposed model was successfully tested to simulate the pedestrian evacuation process from the Britomart Transport Centre platforms in Auckland during an abstract destructive event. Maximum evacuation flow, total evacuation time, average evacuation time, and average evacuation flow were investigated as dependent variables through different evacuation scenarios. The results from the approach can be used by designers and managers to optimise the quality of evacuation; also, the proposed model has the potential of becoming a potent tool for constructional management if coupled with other constructional tools.

Adaptive Agent-Based Modeling Framework for Collective Decision-Making in Crowd Building Evacuation

Crowd evacuation in different situations is an important topic in the research field of safety. This paper presents a hybrid model for heterogeneous pedestrian evacuation simulation. Our adaptive agent-based model (ABM) combines the strength of human crowd behavior description from classical social force models with discrete dynamics expression from cellular automaton models by extending the conception of floor field. Several important factors which may influence the results of decision-making of pedestrians are taken into consideration, such as the location of sign, the attraction of exit, and the interaction among pedestrians. To compare the effect of information on the pedestrians, we construct three decision-making mechanisms with different assumptions. To validate these three simulation models, we compare the numerical results from different perspectives with rational range in the case study where the Tampere Theater evacuation was carried out. The ABM framework is open for rules modification and could be applied to different building plans and has implication for architectural design of gates and signs in order to increase the evacuation efficiency.

How urban layout and pedestrian evacuation behaviours can influence flood risk assessment in riverine historic built environments

Riverine Historic Built Environments (HBEs) in urban centres are relevant scenarios for flood risk, due to the compact layout of their outdoor spaces, that are squares and streets, and their position in flood-prone areas. Differences in HBE layout can provide differences in flood risks, but excluding the response of exposed individuals can lead to risk underestimation or overestimation, as for other hazards. This work is a first attempt to compare how accounting or not pedestrian evacuation behaviours can affect flood risk assessment and emergency strategies evaluation. Parametric configurations of typical HBEs are provided on case-studies, and existing tools for hydrodynamic and pedestrian evacuation simulation are applied to them. Risk indexes for the whole HBE (macroscale) and each outdoor space (microscale) in it are provided. Results show how the risk indexes trends accounting or not pedestrian evacuation behaviours are similar if considering the macroscale, while differences at the microscale exist (about 15 % in absolute terms). Concerning emergency strategies, sheltering seems to decrease the risk for the whole HBE up to 33 % in comparison to leaving the flood-affected area. Results also support where/how to place gathering areas in the HBE.

Reinforcement learning for Pedestrian evacuation Simulation and Optimization during Pandemic and Panic situation

The pandemic of Covid-19 has drawn significant attention of the people around the world. The current situation has revealed that this virus infected more than 50 million people globally. On the other hand, the study on crowd simulation can demonstrate the behaviour of massive people that gather in the same location. The importance of this study can lead to safe evacuation in case an outbreak happens. This paper proposed a solution of innovative crowd simulation supported by reinforcement learning and pandemic factors. The study has successfully demonstrated the entering and leaving the various exit and entrance. The experiment is performed with a different mode such as two elevators for exit and entry, staircase and six lanes of gates. As a result of the experimental study, it reveals around 87% of agent behaviour has similarity compared to a real-life simulation performed by previous research. It means the simulation is reflecting the real-life human behaviour when the evacuation process has occurred. The future study can extend to a contagion model of crowd behaviour where an agent can influence each other in a particular situation.

Simulation and optimization of pedestrian evacuation in high-density urban areas for effectiveness improvement

Rapid urbanization has made many cities in China enter an era that increment and stock develop in parallel. Urban central area presents the characteristics of complex spatial structure and high functional complexity, resulting in the huge disaster risks and severe security issues of evacuation. This paper proposes a method of improving emergency evacuation effectiveness under the restriction of limited available land resources in high-density areas, which is combined with urban renewal planning, aiming at optimizing the layout of shelters and evacuation passageway by cyclic evacuation simulation, evaluation and optimization with Anylogic software and facility location tool based on ArcGIS. Taking the renewal planning of Jintang Road Area in Tianjin, a typical high-density urban area, as a case study. The results showed that: 1) The evacuation space system of Jintang Road Area exists potential danger that severe congestion occurred in the simulation process and the congested section spread outward with three shelters as the center. Which lasted for several hours. The rate of successful asylum in 5 min and 30 min was 13% and 34%; 2) The matching degree between spatial layout of emergency shelters and population distribution is low, which is reflected in the utilization rate of shelter: the rate of shelter No.1 is as high as 826%, while that of No 4 and No 5 is 48% and 11%, and also causes unreasonable distribution of people flow in evacuation passages during the evacuation process; 3) The research method of integrating simulation, facility location and renewal planning is an effective way to improve the effectiveness of pedestrian evacuation in high-density urban areas. After the improvement, the four indexes have been effectively improved.

Pedestrian evacuation simulation in the presence of an obstacle using self-propelled spherocylinders

We explore the role that the obstacle position plays in the evacuation time of agents when leaving a room. To this end, we simulate a system of nonsymmetric spherocylinders that have a prescribed desired velocity and angular orientation. In this way, we reproduce the nonmonotonous dependence of the pedestrian flow rate on the obstacle distance to the door. For short distances, the obstacle delays the evacuation because the exit size is effectively reduced; i.e., the distance between the obstacle and the wall is smaller than the door width. By increasing the obstacle distance to the door, clogging is reduced leading to an optimal obstacle position (maximum flow rate) in agreement with results reported in numerical simulations of pedestrian evacuations and granular flows. For further locations, however, a counterintuitive behavior occurs as the flow rate values fall again below the one corresponding to the case without obstacle. Analyzing the head-times distribution, we evidence that this new feature is not linked to the formation of clogs, but is caused by a reduction of the efficiency of the agent's instantaneous flow rate when the exit is not blocked.