Pedestrian Evacuation Dynamics 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

Pedestrian evacuation dynamics considering terrorist attack on-site control action differences between police and security guards

In recent years, terrorist attacks all over the world caused many civilian casualties seriously. Under the knife and axe terrorist attack, there are usually four groups of event-related persons, that is, pedestrians, terrorists, police, and safety guards in the scene. The behavior of them is different, but they are rarely considered together in existing litterateurs, especially the police and safety guards. In this paper, we propose the FFPS (extended floor-field model combined with on-site control actions of police and safety guards) model to study pedestrian evacuation dynamics considering terrorist attack on-site control action differences between police and security guards. The FFPS model consists of three aspects. First, pedestrian evacuation dynamics in terrorist attack environment is modeled. Second, the behavior of terrorists, police and safety guards is studied. Third, the differences of on-site control actions between police and safety guards are studied. We set up the scenario for simulation. The influence of terrorists’ number and location, police and security guards’ different actions, police entering time, police shooting distance, police and safety guards’ spatial position, and police control strategy on evacuation dynamics are analyzed in detail. Those results provide valuable insights to quickly control terrorists, and sharply reduce casualties in terrorist attack environment.

Fast trajectory extraction and pedestrian dynamics analysis using deep neural network

Pedestrian evacuation dynamics research is crucial for safety engineering and crowd management. Accurate and fast extraction of pedestrian trajectories from experimental videos is essential for reliable evacuation data and effective strategy development. In this paper, we propose a novel method for extracting pedestrian trajectories from evacuation experiment videos based on deep learning techniques. The method consists of two modules: pedestrian detection and location prediction, which use Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, respectively. Experimental results show that our method achieves high accuracy with short time compared to traditional methods. Furthermore, our experiments demonstrate that our method can accurately extract information on pedestrian evacuation dynamics. The proposed method provides a fast and reliable approach to extracting pedestrian evacuation dynamics information, which has the potential to be utilized by researchers, urban planners, and emergency management personnel to develop more effective evacuation strategies, improve crowd management, and ultimately enhance public safety.

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.

Effects of exit obstacles on the evacuation dynamics of blind people

The modeling of blind people’s behavior is an important topic in pedestrian evacuation dynamics. In order to study movement characteristics of blind people in evacuation process and the effect of indoor obstacles on the evacuation efficiency of blind people, an extended cellular automata model is proposed to simulate blind people evacuation by considering the influence of obstacles. The control variable method is adopted to study the effect of indoor obstacles on the blind evacuation efficiency rule. The numerical simulation is applied to analyze the evacuation process of blind people under different setting (e.g. the location, size and other factors) of obstacles and different evacuation scenarios. The shunt effect of obstacles is discussed and the layout strategy of obstacles is optimized. The results show that the longitudinal obstacles in front of the exit can effectively play the diversion role of obstacles when the obstacle is at a certain distance from the exit, which will improve the evacuation efficiency of the blind. Furthermore, a horizontal obstacle of appropriate length can constrain the trajectory of the blind people and improve the efficiency of evacuation, but when the horizontal obstacle is too long, it will induce extra jam on both sides of the obstacle and hinder the evacuation of the blind. The finding can provide the theoretical basis for the blind people’s organization, management and the optimization of evacuation strategies during an emergency.

Modified social force model considering emotional contagion for crowd evacuation simulation

Pedestrian behavior in emergency situations is an important part of emergency management, and crowd evacuation simulation provides a low-cost and low-risk method for investigating pedestrian evacuation dynamics by describing pedestrian evacuation behavior and predicting evacuation outcomes under hypothetical situations. This study proposed a modified social force model that combines dynamic hazard and emotional contagion frameworks to investigate the effect of panic on pedestrian evacuation dynamics under heterogeneous personality trait distributions. First, the emotional contagion framework was improved, and an updated emotional model was developed considering personality characteristics. Second, the individual self-driving force in the social force model was transformed from a physical drive mode to a psychological drive mode by introducing panic factors. Lastly, new rules for the spread of panic within small groups were formulated based on the important influence of small group behavior on evacuation. The simulation results confirmed the feasibility of analyzing crowd evacuation from the perspective of social psychology, and revealed that the spread of panic was closely related to the distribution of personality characteristics, individual walking speed, exit usage, evacuation efficiency, and small groups. In addition, the model could reproduce self-organizing behavior in crowd evacuation, such as fast is slow and herd behavior. Further, the results revealed that moderate panic can help improve evacuation efficiency, whereas excessive panic can result in uneven utilization of exits. In addition, the presence of small groups in panic crowds increased the crowd evacuation time.

Pedestrian small group behaviour and evacuation dynamics on metro station platform

Crowd at metro stations is usually a mixture of individuals and small groups of families or friends. However, limited research has focused on small group behaviours for metro safe evacuation evaluation and planning. In this study, a field observation at metro stations and a questionnaire survey were conducted to reveal the small group behaviour characteristics with different decision patterns and compactness. A cellular automaton (CA) based simulation model was proposed to reproduce small group behaviours of independent or joint decision pattern, with loose or close contact, reflecting the real-time trade-off between individual efficiency and group coherence. Impacts of small group behaviours on crowd dynamics were investigated by simulation experiments under diverse scenarios. Simulation experiments revealed that joint decision pattern and close contact of small groups were more likely to lead to longer evacuation time, lower average speed and stronger interference on the individuals. Deviations of estimated evacuation time due to small group behaviours were investigated and found to be common and widespread with different group decision pattern and compactness, congestion levels, proportions of groups in the crowd and exit layouts.

Application of the dynamic Monte Carlo method to pedestrian evacuation dynamics

In this study, we investigate a two-dimensional lattice model for crowd evacuation dynamics by using a dynamic Monte Carlo (DMC) method. This model is built on the microscopic Arrhenius dynamics along with the exclusion rule in which stochastic processes govern the individual movements depending on the relative distance to the room exit. Even though individual decision-making procedures can be complicated during the evacuation in an emergency, our model can quantitatively estimate the time for them to evacuate and predict the emerging patterns of the crowds during the process. The results exhibit the phenomena such that pedestrians spontaneously gather at the exit and form an arched shape close to the door. The DMC simulations and observations agree with the corresponding study in the literature. The DMC algorithm is computationally efficient due to its major property —“rejection-free”, which makes it a suitable tool to simulate evacuation dynamics for a large group of pedestrians.

How stair configurations in buildings affect pedestrian dynamics on stairs? A simulation study via an extended three-dimensional force-based model

Pedestrian movement on stairs is a complex three-dimensional dynamic process. However, previous models are inherently limited in that they ignored the significant effect of stair configurations. This paper presents an extended three-dimensional force-based model to describe pedestrian movement and evacuation dynamics on stairs. By calibrating with previous real-human experiments, this unique model is able to accurately reproduce the velocity/density relation under a wide range of inclination stairways. Then, we explored the basic questions about pedestrian dynamics on complex stair configurations. The results demonstrated that: (1) this unique model shows good universality for simulating pedestrian dynamics on stairs; (2) under the combined effect of narrow exit and stairway, the stair part is the primary factor that affects the specific flow; (3) the optimal stair dimension is a set of tread depth and riser height; (4) pedestrian density and the geometric layout of the stairwell significantly influence pedestrian merging ratio at the merging zone.

Pedestrian evacuation dynamics considering information guidance

Suitable information of routes and exits can help guide evacuees to approach the expected destinations more efficiently in case of emergencies, such as fire accidents, terrorist attacks and power failures. Therefore, the purpose of this paper is to provide an overview of the dynamics of two patterns of guided crowd evacuation. One is source-guided crowd evacuation, and the other is leader-guided crowd evacuation. In source-guided crowd evacuation, sources located in fixed positions diffuse information to evacuees around them in a certain form such as light, sound and smell. However, in the leader-guided crowd evacuation, leaders convey information to evacuees they encounter along their trajectories by means of word-of-mouth communication. First, considering wall-following, herding, and inertia behaviors, a mesoscopic model is established to formulate the movement of uninformed pedestrians without information guidance. Then, considering information guidance, a set of movement rules are constructed to describe the evolution dynamics of crowds comprising uninformed and informed pedestrians. Further, the implementation of the simulation models reveals the subtle effects of the initial position of information sources, the propagation velocity of information sources, and the initial distribution of leaders on the evacuation efficiency of crowds. This study gives new insights into the design of information guidance systems in pedestrian walking facilities.

Experimental study of movement characteristics for different walking postures in a narrow channel

In the event of a fire, the smoke produced by the fire will not only affect the visibility of pedestrians but also change the pedestrians’ walking posture. The pedestrians’ motion characteristics of stoop walking have not been systematically studied in pedestrian evacuation dynamics. Therefore, a series of single-file movement experiments under controlled laboratory conditions were performed by a transparent protective net which is used to limit the pedestrians’ height to change the walking posture. The probability density distribution of density and speed, the fundamental diagram, headway-speed relation and the lateral sway will be analyzed. The maximum flow rate of pedestrians in stoop walking is 26% lower than that of normal walking in speed-flow relation. Three states (free regime, weakly constrained regime, and strongly constrained regime) can be observed in the relationship between headway and speed, the free speed of pedestrians follows a Gaussian distribution. In addition to discussion of the longitudinal motion characteristics, lateral movement characteristics of the pedestrian will further be analyzed. The study found that the average lateral sway of normal walking is greater than that of stoop walking. The results of this study provide valuable information for the effects of different walking postures and help to develop precise models about different walking postures, which can finally contribute to the design of related pedestrian facilities.

Analysis of Indoor Guided Pedestrian Evacuation Dynamics in Single- and Multiple-Exit Scenarios: Toward a Unified Scheme for Guide Assignment

Indoor pedestrian evacuation processes could be significantly affected by the presence of guides, that is, safety management staff; how to assign guides properly remains a challenging task. This question is deconstructed into single- and multiple-exit scenarios for analysis in this study. The mechanisms behind the evacuation dynamics are explored via a two-layer guided pedestrian evacuation model and the corresponding guide assignment strategies are proposed. The upper layer model deals with guide assignment, where random and uniform guide assignment schemes, and a newly proposed distribution-based guide assignment scheme, are embedded, while the lower layer model controls the movement of evacuees based on a cellular automata model. Results show that there are bifurcate mechanisms governing evacuation dynamics. Only in single-exit scenarios could an increased number of guides lead to a “sharp decrease–long steady tail” tendency in total evacuation time, whereas evacuation efficiency in multiple-exit scenarios is consistent with exit use equilibrium. The three different guide assignment schemes bring about highly case-specific performances depending on the initial pedestrian distribution and the number of exits. The distribution-based guide assignment scheme is preferable in most cases, especially in spaces with a highly biased pedestrian distribution and multiple exits.

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.

Pedestrian Small Group Behaviour and Evacuation Dynamics on Metro Station Platform

Pedestrian Small Group Behaviour and Evacuation Dynamics on Metro Station Platform

Modeling the dynamics of pedestrian evacuation in a complex environment

The study of crowd evacuation dynamics is important for the management of public safety, and crowd evacuation dynamics models can be used to simulate the behaviors of pedestrians during an evacuation. In this paper, we propose a new force model for simulation of the evacuation of complex environments. In comparison to existing models, this model considers more environmental factors to make it applicable to complex emergency environments. By verification using real data, the model is demonstrated to be able to predict evacuation efficiency and better reproduce the microscopic behavior of pedestrians under extreme conditions. We discuss the impact of the presence of different kinds of hazards and different types of obstacles in the environment on pedestrian evacuation performance and put forward suggestions for crowd evacuation management.

Incorporating genetic algorithm to optimise initial condition of pedestrian evacuation based on agent aggressiveness

In the study of pedestrian evacuation dynamics, pedestrian aggressiveness is important to consider as it potentially impacts evacuation efficiency. A representative example is the ‘faster-is-slower’ phenomenon. In reality, a crowd is a mixture of patient and impatient pedestrians, rather than a collection of like individuals. The impact of such heterogeneity has been reported in previous studies; however, these studies are all based on handcrafted solutions. In this study, we propose a heuristic approach for incorporating a genetic algorithm into the floor field cellular automata model to investigate the optimal initial pedestrian evacuation condition. Pedestrian aggressiveness is represented by two different approaches: the revised friction function and the persisting probability. To verify our genetic algorithm approach, we compared the results with the theoretical analysis and simulation results based on handcrafted solutions. The first contribution of this study is that the initial condition, a mixture of patient and impatient pedestrians, affects evacuation efficiency. Another contribution of this study is the heuristic approach incorporating a genetic algorithm. Our approach exerts the computational efficiency advantage of the floor field cellular automata model.

Experimental study on the movement characteristics of pedestrians under sudden contact forces

In crowd disasters, collision among pedestrians is one of the main causes of crushing and trampling. However, in most controlled experiments, there is little physical contact among pedestrians, and microscopic human behaviors are less studied. Therefore, a series of controlled experiments where physical contact occurred were conducted to study the microscopic dynamics of a single pedestrian’s movement process and the transmission of impulse between two pedestrians. The impulse can be extracted from a flexible fabric pressure sensor that covers the pedestrian’s back. In the single-pedestrian experiment, the body postures and behaviors are analyzed. It is found that the impulse release distance increases as the impulse increases and the numerical linear relation is established to show the trend. The polynomial relation in the movement process is adopted and the numerical relations between speed, move distance and exerted impulse are established. In the two-pedestrian experiment, the transmission of impulse is studied. The transmission coefficient increases first and then decreases as the distance increases and the numerical rational relation is adopted to show the trend. The transmitted impulse increases as the exerted impulse increases in each distance and the numerical exponential relation is adopted. These equations can be used to study the impulse transmitted along the queue. The findings in this study can help us to understand pedestrian collision evacuation dynamics in a high-density crowd. Eventually, they could be used to assess the risk levels in local crowds and prevent crowd disasters involving trampling.

Pedestrian Small Group Behaviour and Evacuation Dynamics on Metro Station Platform

Pedestrian Small Group Behaviour and Evacuation Dynamics on Metro Station Platform

Fuzzy Social Force Model for Pedestrian Evacuation under View-Limited Condition

Pedestrian evacuation dynamics in a classroom is always a complex process influenced by many fuzzy factors. It is very difficult and inappropriate to quantify the impact of these fuzzy factors by using the mathematical formula. Existing microscopic simulation models have made many efforts to use accurate mathematical method to model the fuzzy interaction behaviors between pedestrians under the view-limited condition. This study tries to fill this gap by establishing a microscopic simulation model which can represent the fuzzy behaviors of pedestrians under view-limited condition. The developed fuzzy social force model (FSFM) combines fuzzy logic into conventional social force model (SFM). Different from existing models and applications, FSFM adopts fuzzy sets and membership functions to describe the pedestrian evacuation process. Seven fuzzy sets are defined for this process, such as stop/go, moving direction, desired force, force from obstacles, force from pedestrian, force from indicators, and acceleration. Membership function of each input factor is calibrated based on the observed data. Model performance is verified by comparing speed distribution, velocity-density relationship, and results of simulation and observation evacuation time. Besides, the proposed model is applied to assess the number and space distribution of exit indicators and stickers. By comparing simulation results with existing models, the paper concludes that FSFM is able to well reproduce pedestrian movement dynamics in real world under view-limited condition.

Incentive-based experiments to characterize pedestrians’ evacuation behaviors under limited visibility

Pedestrian evacuation dynamics under near zero or limited visibility conditions are usually different from normal evacuation conditions. In previous studies, the competitiveness of evacuees under limited visibility condition is mainly controlled by stimulating their physical and psychological states during evacuation, and the monetary incentive effect has not been investigated. This study aims to investigate the use of monetary incentive to mimic different emergency levels and the resulting effects in evacuation process under limited visibility condition. Two connected areas (7 m × 5 m) enclosed by an iron fence are set up for the single-exit evacuation experiment. A total of 18 evacuation experiments with 30 participants with limited vision were conducted. By controlling different amounts of monetary incentives as different emergency levels, the position of the connecting door in the middle or the edge of two fences and the opening of the exit of one room in two rooms were randomly selected as control variables to reduce the experimental behavior. The results show that the emergency level controlled by monetary incentive has a significant influence on evacuation efficiency. With the increase in incentive level, evacuation time of the participants generally decreased. The emergency level not only improved pedestrian’s walking speed by improving pedestrian’s urgency for evacuation, but also had a significant influence on pedestrian’s route choice. These results suggest that improving the incentive level can reduce the randomness and hysteresis of participants’ path and route selection decision. Findings of this study are valuable resources for proactive pedestrian crowd management under adverse conditions.