Cellular Automaton Simulation of Evacuation Process in Story

Evolution of pedestrian evacuation considering different human behaviors

An agent-based modeling approach to collaborative classrooms evacuation process

A cellular automaton (CA) model with a finer discretization of space is proposed to simulate a non-emergency evacuation process in a room with an obstacle. During the evacuation process, a triangle “evading region” phenomenon has been observed through simulation and experiment on the upstream side of the spatial obstacle. In this paper, we use a simple method to generate an obstacle floor field corresponding to the triangle. We investigate the relationship between the pedestrian trajectories and the obstacle’s position. We also study the effect of the obstacle on evacuation time and average evacuation speed. Our study provides insights into the simulation of obstacle avoidance behavior of pedestrians in simple scenarios.

A fire egress system is one of the most critical aspects of fire emergency evacuation, which is the cornerstone technology of building fire safety. The high-rise teaching buildings on campus, where vast crowds of people gather, need to be qualified for rapid evacuation in the event of a fire especially. Conventional teaching building egress system design places more emphasis on individual elements (e.g., stairwells, evacuation doors, and evacuation walkways) rather than on their co-regulation as a whole. Furthermore, there are not enough holistic and effective optimal design strategies, which is because most of the existing studies rely on experiments or simulations and often suffer from a lack of sufficient data to fully reveal the interactions of individual variables. In this study, the co-effectiveness of stairwells, walkways, and room doors in reducing total evacuation time was investigated by simulation and machine learning. We selected a typical high-rise teaching building as an example and integrated two simulation software, Pyrosim and Pathfinder, to compare the available safe evacuation time (ASET) and required safe evacuation time (RSET). Then, a framework consisting of five factors—stair flight width (SFW), stairwell door width (SDW), corridor width (CW), room door width (RDW), and location of the downward stair flight (LDSF)—was established for the optimization through statistical analysis of big data obtained by the preferred machine learning algorithm. Results indicate that (1) By modifying just one factor (SFW), the total evacuation time (TET) can be reduced by at most 12.1%, with the mortality rate dropping from 26.5% to 9.5%; (2) although ASET could not be achieved either, among 4000 cases of multi-factor combinations, a maximum TET improvement degree, 29.5%, can be achieved for the evacuation optimization compared to baseline model, with a consequent reduction in mortality to 0.15%; (3) it shows that the emphasis of the egress system optimization is on the geometric features of the evacuation stairwell; furthermore, the multi-factor combination approaches have better compromised evacuation performances than the single-factor controlled schemes. The research results can be applied as rational design strategies to mitigate fire evacuation issues in high-rise teaching buildings and, in addition, the methodology suggested in this paper would be suitable to other building types.

This study focuses on the safe evacuation strategy and evacuation process in the subway train under the fires. The subway station evacuation mode should be adopted if the power system of a subway train is normal on fire. While, the tunnel evacuation mode should be adopted if the power system of the train fails because of the effects of fire. Under the tunnel evacuation mode, the direction of tunnel smoke should be opposite to that of most passengers, and passengers should be evacuated toward the fresh wind. By using the numerical simulation software Pathfinder and PyroSim, the passenger evacuation time under different conditions is calculated, and the safety of the evacuation process is evaluated. The results show that the evacuation time of the station evacuation mode is obviously shorter than that of the tunnel evacuation mode. With the same conditions, the evacuation time of the tunnel evacuation mode is 2193 s, which is about four times as much as the evacuation time of the station evacuation mode (526 s). The total evacuation time increases with the total number of passengers and the proportion of older people and children. Under an oil pool fire, which is an extreme fire condition, the fire environment inside the train may reach a level threatening the passengers’ safety before the evacuation is complete, even before the door opens; therefore, special attention should be paid to the safety issues in stage from the fire begins to the evacuation complete.

CellEVAC: An adaptive guidance system for crowd evacuation through behavioral optimization

Aim: The main aim of the study was to investigate the possibility to use the Pathfinder simulation software to determine the duration of an evacuation and to plan its course for various scenarios of evacuation organisation, for specific profiles and behaviours of passengers and on-board personnel, and for a specific geometrical arrangement of the passenger cabin of a selected passenger aircraft. In addition, the paper discusses selected factors that affect the evacuation from the passenger aircraft. Project and methods: The Pathfinder software used in the research has the graphical interface to create an evacuation simulation model (2D and 3D) as well as tools to visualise the results. Pathfinder is based on artificial intelligence algorithms, in which each passenger has a number of individual features that can influence his/her movements and decisions during the simulation. The simulation of people's movement is determined by their profiles and behaviours, the parameters of which can be entered by means of probability distributions, which makes it possible to take into account the stochastic nature of the evacuation process. Results: The Boeing 787 Dreamliner was selected for the study, for which six options for simulating the evacuation of 252 passengers and eight members of on-board personnel were conducted. The shortest evacuation time was achieved by changing the even distribution of the number of passengers to the individual emergency exits, thus avoiding congestions in sensitive areas of the passenger cabin. The increase in passengers' maximum speed has paradoxically increased evacuation times, as it has increased the intensity of passenger collisions. It was found that one of the key issues affecting the timing of an evacuation is the proper organisation of the evacuation by on-board personnel, who, by guiding passengers through the geometrically most advantageous passageways, results in the fastest possible evacuation. The simulations in variants five and six have achieved satisfactory evacuation times, which are within the emergency aircraft evacuation time limit required in a certification process. Conclusions: The presented simulation models, the results obtained, and the wide range of possibilities of three-dimensional visualisation of research results give a rational basis for the use of Pathfinder software for testing the evacuation process and thus: for the usage in the aircraft design process, for preparing aircrafts for tests, for shaping evacuation procedures, for on-board personnel training and for air accident investigation.

Integration of cumulative prospect theory in cellular automata model for building evacuation

Effect of uncertain information on pedestrian dynamics under adverse sight conditions

Vehicle-Augmented Evacuation Integer Programming Model for Improving Safety and Efficiency in Underground Mines

This study presents a novel impatience-based model on the route choice simulations. Two parameters: self-growth rate and propagation speed of impatience are introduced to calculate the dynamic impatience level. The target cell is determined by comprehensively considering distance, density around exits, and the impatience level. At each time step, pedestrians will move into the target cell in turn depending on the descending order of their impatience level. To test the feasibility of this model, we apply this model into the typical scenario (i.e., square room with two exits) and conduct the sensitivity analysis of two model parameters. The simulation results illustrate that this proposed model can successfully reproduce typical collective behaviour (i.e., clogging). Compared with the previous model in which only distance is considered, this model has two exits fully used and then improves evacuation efficiency. The parameter analysis results show that in this simulation scenario, self-growth speed is the dominated factor. With the increase of self-growth rate, evacuation time is shortened. In addition, scatter plots of evacuation time against maximum impatience level shows both no impatience and an excessive impatience level will lead to an increase in evacuation time. The comparison between impatience-determined model and Pathfinder illustrates the impatience-determined model leads to a smoother evacuation process, and this model is applicable in predicting the evacuation process with multiple exits.

Cel: The article presents the results of research on the evacuation process of people from the building of the Faculty of Environmental and Power Engineering of the Silesian University of Technology, including the evacuation of people with a temporary limitation of independent movement, who are evacuated using an evacuation chair. The travel times and the time needed to prepare an evacuation chair were examined. Based on the research, the average speeds of movement of the studied populations were determined. Projekt i metody: Twelve evacuation experiments were carried out in three different user populations of the building. The experiments included the analysis of the times of movement of people without disabilities; people with temporary disabilities who move independently on crutches and a population in which there was one person with temporary reduced mobility, who was evacuated using an evacuation chair. Six of the experiments concerned the evacuation from the fourth floor of the building, three of which were proceeded through the main staircase and the remaining three through the side staircase. The next six experiments were carried out from the second floor, also split into two different staircases. Each experiment ended when all people reached the meeting point near the building. Wyniki: The lowest values of the average total travel time were recorded for the population without disabilities. The shortest average travel time was 83 seconds and concerned the evacuation of the population without disabilities from the second floor, evacuating through a side staircase (K1). In all the experiments, the person on crutches was the slowest to move, for whom the evacuation times were the longest. The maximum average time for a person on crutches was 342 seconds to evacuate from the fourth floor via the main staircase. Evacuation with an emergency chair improved the process by 10.47% for the evacuation from the second floor using K1 staircase, and for the evacuation with this staircase from the 4th floor by 28.71%. For the main staircase (K2), the experiments conducted from the second floor using an evacuation chair took 40.02% less time than an independent evacuation of a person with crutches and 47.07% less time when evacuating from the fourth floor. Wnioski: Interpreting the results obtained in the experiments, it can be stated that the evacuation using an evacuation chair improved the evacuation process compared to the experiments in which a person temporarily disabled was walking independently on crutches. People without disabilities evacuate the fastest. The analysis of the time of travel made it possible to determine the average speed of movement of the analyzed populations, which can be used as a model value to perform an evacuation simulation. Słowa kluczowe: evacuation, evacuation time, people with disabilities, evacuation chair

The paper explores the usage of agent-based modeling in the context of large event halls evacuation during music festivals and cultural events. An agent-based model is created in NetLogo 6.2.2 for better representing the human behavior when involved in such situations. A series of characteristics have been set for the agents in order to preserve their heterogeneity in terms of speed, age, locomotion impairment, familiarity with the environment, evacuating with another person, choosing the closest exit or not, selecting the closest path to the exits. An “adapted cone exit” approach has been proposed in the paper in order to facilitate the guidance of the agents in the agent-based model to the closest exit and its advantages have been proved in comparison with the classical “cone exit” approach. Different evacuation scenarios have been simulated and analyzed for better observing the capabilities of evacuation modeling in the case of evacuation emergencies. Besides the overall evacuation time, an average evacuation time has been determined for the agents based on the individual evacuation time, which can be easily connected with a risk indicator associated to each situation. Due to the visual interface offered by the agent-based model, coupled with the evacuation indicators, the proposed model can allow the identification of the main factors that may contribute to a prolonged evacuation process (e.g. overcrowding at one of the exits, not choosing the appropriate door, evacuating with a friend/parent) and the potential measures to be considered for insuring a safe evacuation process.

In the emergency evacuation of pedestrians in subway stations, most people do not know the correct evacuation routes and methods, and tend to follow others blindly, resulting in herding behavior. To study the process of pedestrian evacuation with herding behavior in subway stations, a cellular automata pedestrian evacuation model is established to simulate the pedestrian evacuation with herding behavior in subway stations, and the effects of the weight coefficients of the parameters in the model on the overall evacuation time and the distribution of people’s positions are investigated to quantify the effects of herding on the efficiency of the pedestrian evacuation and the movement behavior. The simulation results show that moderate (kC < 40) crowd behavior can play a beneficial role in reducing reaction time and guiding the direction of evacuation; on the contrary, excessive crowd behavior (kC > 40) will lead to an increase in evacuation time and a decrease in evacuation efficiency. The conclusions presented in this paper can help to improve the efficiency of pedestrian evacuation in emergencies and provide a theoretical basis and practical guidance for the management of safety evacuation in subway stations.

With the progress of construction technology, the modern buildings become more and more complicated and large-sized. It is difficult to avoid sudden and catastrophic emergency events for interior buildings. Hence, it is very important to establish an evacuation model to simulate evacuation behavior of pedestrians under real condition and make a scientific and effective evacuation plan. For handling with the problems of emergency evacuation path in buildings, an improved cellular automata model based on ant colony optimization algorithm (ACO) is proposed. The proposed model considers the neighbors moving rules of cellular automata and law of export selection rule is used as heuristic information of ant colony optimization algorithm, it reflects the behavior of personnel path choice more really. Finally, the model has been applied to simulate the whole evacuation process in a classroom. By simulating the process of pedestrian evacuation with the model, the results show that the proposed model could achieve shorter evacuation time than basic ACO, it's feasible for solving evacuation planning problem.