Cellular automata model for pedestrian evacuation in fire spreading conditions

In this paper, a two-dimensional cellular automata model presented to simulate pedestrians evacuation in fire spreading conditions.In this proposed model, the movement of pedestrians is represented as “chaotic”, mimicking panic egress behaviors during a fire evacuation.This model includes a fire circular front shape based on the spiral movement technique. Simulation results show that this model can be used to predict the number of pedestrians who have evacuated safely or have been killed

Overview of crowd simulation in computer graphics

High-powered technology use computer graphics in education, entertainment, games, simulation, and virtual heritage applications has led it to become an important area of research. In simulation, according to Tecchia et al. (2002), it is important to create an interactive, complex, and realistic virtual world so that the user can have an immersive experience during navigation through the world. As the size and complexity of the environments in the virtual world increased, it becomes more necessary to populate them with peoples, and this is the reason why rendering the crowd in real-time is very crucial. Generally, crowd simulation consists of three important areas. They are realism of behavioral (Thompson and Marchant 1995), high-quality visualization (Dobbyn et al. 2005) and convergence of both areas. Realism of behavioral is mainly used for simple 2D visualizations because most of the attentions are concentrated on simulating the behaviors of the group. High quality visualization is regularly used for movie productions and computer games. It gives intention on producing more convincing visual rather than realism of behaviors. The convergences of both areas are mainly used for application like training systems. In order to make the training system more effective, the element of valid replication of the behaviors and high-quality visualization is added

Two-dimensional cellular automation model to simulate pedestrian evacuation under fire-spreading conditions

A pedestrian evacuation under fire-spreading conditions is simulated by using a two-dimensional cellular automaton model.The proposed model presents a non-static fire-spreading behavior to avoid considerable discrepancies between reality and simulation.The proposed model adopts a circular fire front shape based on spiral fire movement.Moreover, four dynamic parameters are introduced to simplify the decision-making process of a pedestrian’s movement inside the layout during fire spreading.In addition, the proposed model includes the number of victims (i.e., caught in the fire) and the number of pedestrians who were evacuated safely.By analyzing these variables, a suitable evacuation plan enabling the control of crowd movements in different situations such as fire disasters can be consequently designed

A Comprehensive Study on Pedestrians' Evacuation

Human beings face threats because of unexpected happenings, which can be avoided through an adequate crisis evacuation plan, which is vital to stop wound and demise as its negative results. Consequently, different typical evacuation pedestrians have been created. Moreover, through applied research, these models for various applications, reproductions, and conditions have been examined to present an operational model. Furthermore, new models have been developed to cooperate with system evacuation in residential places in case of unexpected events. This research has taken into account an inclusive and a 'systematic survey of pedestrian evacuation' to demonstrate models methods by focusing on the applications' features, techniques, implications, and after that gather them under various types, for example, classical models, hybridized models, and generic model. The current analysis assists scholars in this field of study to write their forthcoming papers about it, which can suggest a novel structure to recent typical intelligent reproduction with novel features

Role of opinion sharing on the emergency evacuation dynamics

Emergency evacuation is a critical research topic and any improvement to the existing evacuation models will help in improving the safety of the evacuees. Currently, there are evacuation models that have either an accurate movement model or a sophisticated decision model. Individuals in a crowd tend to share and propagate their opinion. This opinion sharing part is either implicitly modeled or entirely overlooked in most of the existing models. Thus, one of the overarching goal of this research is to the study the effect of opinion evolution through an evacuating crowd. First, the opinion evolution in a crowd was modeled mathematically. Next, the results from the analytical model were validated with a simulation model having a simple motion model. To improve the fidelity of the evacuation model, a more realistic movement and decision model were incorporated and the effect of opinion sharing on the evacuation dynamics was studied extensively. Further, individuals with strong inclination towards particular route were introduced and their effect on overall efficiency was studied. Current evacuation guidance algorithms focuses on efficient crowd evacuation. The method of guidance delivery is generally overlooked. This important gap in guidance delivery is addressed next. Additionally, a virtual reality based immersive experiment is designed to study factors affecting individuals\u27 decision making during emergency evacuation

Examining ant colony optimization performance for ship evacuation

Masteroppgave i informasjons- og kommunikasjonsteknologi IKT590 2013 – Universitetet i Agder, GrimstadEvacuating passengers during a fire on board ships is a difficult task and any improvements on current procedures can help save lives. This report describes how an Ant Colony Optimization (ACO) pathfinding algorithm could possibly be used to lead passengers out of this dangerous situation. The ships were modeled from blueprints of real ships and represented as graphs with nodes and vertices. In the simulation passengers were equipped with a smart phone running an application which showed them the way out. The passengers could end up panicking given close proximity to fire or other stressing factors, in which case they would stop following directions. Additionally, high density of passengers in rooms and corridors slowed down the speed of evacuation. The results produced by ACO were compared to Dijkstra’s pathfinding algorithm and were promising. They showed that ACO performed well in dynamic environments and could be used in a crisis situation to guide people out of danger

Simulating crowd evacuation with socio-cultural, cognitive, and emotional elements

In this research, the effects of culture, cognitions, and emotions on crisis management and prevention are analysed. An agent-based crowd evacuation simulation model was created, named IMPACT, to study the evacuation process from a transport hub. To extend previous research, various socio-cultural, cognitive, and emotional factors were modelled, including: language, gender, familiarity with the environment, emotional contagion, prosocial behaviour, falls, group decision making, and compliance. The IMPACT model was validated against data from an evacuation drill using the existing EXODUS evacuation model. Results show that on all measures, the IMPACT model is within or close to the prescribed boundaries, thereby establishing its validity. Structured simulations with the validated model revealed important findings, including: the effect of doors as bottlenecks, social contagion speeding up evacuation time, falling behaviour not affecting evacuation time significantly, and travelling in groups being more beneficial for evacuation time than travelling alone. This research has important practical applications for crowd management professionals, including transport hub operators, first responders, and risk assessors

Development of a Dynamical Egress Behavioural Model under Building Fire Emergency

Building fire accidents, as a continuing menace to the society, not only incur enormous property damage but also pose significant threats to human lives. More recently, driven by the rapid population growth, an increasing number of large-capacity buildings are being built to meet the growing residence demands in many major cities globally, such as Sydney, Hong Kong, London, etc. These modern buildings usually have complex architectural layouts, high-density occupancy settings, which are often filled with a variety of flammable materials and items (i.e., electrical devices, flammable cladding panels etc.). For such reasons, in case of fire accidents, occupants of these buildings are likely to suffer from an extended evacuation time. Moreover, in some extreme cases, occupants may have to escape through a smoke-filled environment. Thus, having well-planned evacuation strategies and fire safety systems in place is critical for upholding life safety. Over the last few decades, due to the rapid development in computing power and modelling techniques, various numerical simulation models have been developed and applied to investigate the building evacuation dynamics under fire emergencies. Most of these numerical models can provide a series of estimations regarding building evacuation performance, such as predicting building evacuation time, visualising evacuation dynamics, identifying high-density areas within the building etc. Nevertheless, the behavioural variations of evacuees are usually overlooked in a significant proportion of such simulations. Noticeably, evacuees frequently adjust their egress behaviours based on their internal psychological state (i.e., the variation of stress) and external stimulus from their surrounding environments (i.e., dynamical fire effluents, such as high-temperature smoke). Evidence suggests that evacuees are likely to shift from a low-stress state to a high-stress state and increase their moving speed when escaping from a high-temperature and smoke-filled environment. Besides, competitive behaviours can even be triggered under certain extremely stressful conditions, which can cause clogging at exits or even stampede accidents. Without considering such behavioural aspects of evacuees, the predicted evacuation performance might be misinterpreted based on unreliable results; thereby, misleading building fire safety designs and emergency precautions. Therefore, to achieve a more realistic simulation of building fire evacuation processes, this research aims to advance in modelling of human dynamical behaviour responses of each evacuee and integrating it into building fire evacuation analysis. A dynamical egress behaviour-based evacuation model that considering the evacuee’s competitive/cooperative egress movements and their psychological stress variation is developed. Furthermore, a fire hazard-integrated evacuation simulation framework is established by coupling with the fire dynamics simulator (i.e., FDS). By means of tracking dynamical interactions between evacuees and the evolutionary fire dynamics within the building space, evacuees’ local fire risks and stress levels under the impacts of locally encountered fire hazards (i.e., radiation, temperature, toxic gas, and visibility) can be effectively quantified. In this study, the developed simulation tool can provide a further in-depth building fire safety assessment. Thus, it contributes to performance-based fire safety engineering in designs and real applications, including reducing budgets and risks of participating in evacuation drills, supporting emergency evacuation strategy planning, mitigating fire risks by identifying risk-prone areas associated with building fire circumstances (e.g., putting preventative measures in place beforehand to intervene or mitigate safety risks, such as mass panic, stampede, stress evoked behaviours)