Crowd evacuation simulation using active route choice model based on human characteristics

Modern buildings have become larger in scale and function, and the complexity has also increased considerably. For these reasons, there are more difficulties in evacuation and rescue when an emergency occurs, so effective evacuation methods and risk should be predicted and applied to building design, safety training, and education. We have developed an active route choice model based on human body organs and characteristics that detects risks and route conditions, communicates with neighboring occupants, determines the bottleneck point, and selects evacuation routes according to each occupant's personal characteristics. In this study, we introduce the implementation process and characteristics of the active route choice model, and by applying the model to the occupants, we compared the evacuation times according to the route condition, number of occupants, and corridor width in a virtual environment. We believe that realistic and valid results can be obtained by applying the active route choice model in crowd evacuation simulation.     

建筑物火灾中的人群疏散研究

建筑物火灾是我国频发的安全事故,所以应研究建筑物火灾人群安全疏散问题。由于在建筑物火灾中,人群疏散时出现拥堵,存在不安全因素,造成人员伤亡。针对在现有的研究中未考虑人员行为的影响,提出了智能体(Agent)的人群行为建模技术在建筑物火灾中的人群疏散仿真中的应用方法。仿真结果显示基于Agent的行为模型可以仿真出人员特性及决策过程对人群疏散的影响,弥补现有的人群疏散模型的不足。仿真结果证明,Agent的行为建模技术具有仿真火灾全过程中人员疏散行为的功能,适用于建筑物火灾中的人群优化疏散策略。     

基于物理的真实感火灾疏散仿真

人员的疏散是目前防火防灾研究的热点,但是传统的人员疏散研究多集中于人群疏散的离散仿真及可视化显示,无法逼真地表现个体的疏散行为.从火灾时人员疏散的物理特点出发,考虑不同人在火灾情况下的行为特征,采取几何连续的疏散空间,可较准确地计算人员安全疏散的时间及路径;建立了建筑物、火焰和角色动画的三维模型,动态交互地模拟火灾疏散过程,仿真效果逼真.     

Towards a customizable immersive virtual reality serious game for earthquake emergency training

Earthquake emergencies require a variety of behavioral responses in order to ensure the safety of occupants, which is different from simply exiting a building in fire emergencies. This makes it more complex to train building occupants in order to acquire skills that align to best practices for immediate earthquake response and post-earthquake evacuation. In recent years, Immersive Virtual Reality (IVR) and Serious Games (SGs) have become popular as training tools for earthquake emergencies. IVR SGs have been introduced to train individuals for specific building layouts or settings with fixed training objectives. However, the lack of flexibility in existing IVR SGs makes it challenging to have widespread uptake as trainees require different training objectives, pedagogical strategies, context, and content. As a result, the effectiveness of IVR SGs training is jeopardized if the customization ability is limited. To overcome this limitation, this paper presents a customization framework for IVR SGs suited to earthquake emergency training, using the concept of adaptive game-based learning. Trainees can receive training in context by customizing virtual environments, storylines, and teaching methods. A case study was undertaken to validate the proposed framework. Results showed the potential to carry out the customization process with ease, to generate a customized training experience, and to deliver the customized training for optimum learning.     

Lessons from the evacuation of the world trade centre, 9/11 2001 for the development of computer-based simulations

This paper reviews the state-of-the-art in evacuation simulations. These interactive computer based tools have been developed to help the owners and designers of large public buildings to assess the risks that occupants might face during emergency egress. The development of the Glasgow Evacuation Simulator is used to illustrate the existing generation of tools. This system uses Monte Carlo techniques to control individual and group movements during an evacuation. The end-user can interactively open and block emergency exits at any point. It is also possible to alter the priorities that individuals associate with particular exit routes. A final benefit is that the tool can derive evacuation simulations directly from existing architects, models; this reduces the cost of simulations and creates a more prominent role for these tools in the iterative development of large-scale public buildings. Empirical studies have been used to validate the GES system as a tool to support evacuation training. The development of these tools has been informed by numerous human factors studies and by recent accident investigations. For example the 2003 fire in the Station nightclub in Rhode Island illustrated the way in which most building occupants retrace their steps to an entrance even when there are alternate fire exits. The second half of the paper uses this introduction to criticise the existing state-of-the-art in evacuation simulations. These criticisms are based on a detailed study of the recent findings from the 9/11 Commission (2004). Ten different lessons are identified. Some relate to the need to better understand the role of building management and security systems in controlling egress from public buildings. Others relate to the human factors involved in coordinating distributed groups of emergency personnel who may be physically exhausted by the demands of an evacuation. Arguably, the most important findings centre on the need to model the ingress and egress of emergency personnel from these structures. The previous focus of nearly all-existing simulation tools has been on the evacuation of building occupants rather than on the safety of first responders. Thanks are due to J. Appleby, P. Cooper, A. Foss, S. Hailey and B. Jenks who were responsible for the design and implementation of the GES application. They also drove the development of the Boyd Orr evacuation scenarios that are used to illustrate the opening sections of this paper.     

Event-driven modeling of elevator assisted evacuation in ultra high-rise buildings

In the past few decades, numerous ultra high-rise buildings have been erected in the metropolitan areas of many cities around the world. For the related building designers, building occupants and the governments, fire safety problem is certainly a major concern, especially after the collapse of World Trade Center in the 9/11 event. That disaster makes people reconsider ultra high-rise building evacuation strategies. Of the current strategies, using elevators in ultra high-rise buildings to assist evacuation seems to be promising in improving evacuation efficiency. To quantitatively evaluate elevator assisted evacuation process, an event-driven agent-based modeling approach is proposed in the present paper. This modeling approach could capture not only the movement characteristics of stair-using occupants but also the detailed elevator motion features. The combined effects of occupants’ and elevators’ parameters on the evacuation efficiency have been investigated. Results indicated that the model is helpful to reveal the dynamics of elevator assisted evacuation, and sometime, using elevators to move all occupants to ground safety point may not be an optimal solution.     

基于改进Dijkstra算法的人群反馈调节疏散

针对苏州市金鸡湖城市广场在突发情况下的人群疏散问题,建立了基于实时动态的疏散网络路径规划模型,分析了大型公众区域复杂环境对人群疏散效率的影响.同时提出以人群逃离危险区域的终止时间作为权值参数改进Dijkstra算法,并且利用反馈补偿机制合理分配各出口的疏散人数,实现人群疏散的动态调整和路径规划.通过Pathfinder...     

人群应急疏散可视仿真研究进展和问题

人群应急疏散可视仿真是用智能体来模拟具有自主感知、情绪和行为能力的人群个体,并采用3维可视的方式来直观呈现人群应急疏散情景,可以为制定人群应急预案提供形象直观的分析方法。本文从人群仿真数据的来源、人群导航模型的构建、人群行为模型、人群情绪感染、人群渲染5个方面概述目前研究的进展,然后从仿真模型的可验证性、人群疏散导航模型的构建、人与环境的物理模型、动物逃生实验与仿真、疏散中的社会行为表现以及人群情绪的可视计算6个角度讨论需要进一步研究的问题。针对需要深入研究的问题,指出借助于紧急事件的视频监控分析和虚拟人群情景的用户调查,有助于完善人群仿真模型。结合物理模型,可以更准确地描述人群应急疏散场景。开展动物逃生实验分析,有助于完善人群运动导航算法。建立人群社会行为模型,可以更详细描述疏散中人群行为的多样性。构建基于多通道感知的人群情绪感染计算方法,可以详尽描述情绪感染的过程。人群应急疏散行为的可视仿真研究在城市的安全管理方面具有重要的应用前景,但其研究仍存在很多亟待解决的问题,综合地运用多学科知识,完善实验手段是进一步推动研究的关键所在。     

Concurrent consideration of evacuation safety and productivity in manufacturing facility planning using multi-paradigm simulations

Manufacturing facilities are expected to maintain a high level of production and at the same time, employ strict safety standards to ensure the safe evacuation of the people in the event of emergencies (fire is considered in this paper). These two goals are often conflicting. This paper presents a methodology to evaluate evacuation safety versus productivity concurrently for various, widely known manufacturing layouts. While the safety performance indicators such as evacuation times are inferred from the crowd (agent based) simulation, the productivity performance indicators (e.g. throughput) are analyzed using the discrete event simulation. To this end, this research focuses on creating innovative techniques for developing accurate crowd simulations, where Belief-Desire-Intention (BDI) agent framework is employed to build each person’s individual actions and the interactions between them. The data model and rule based action algorithms for each agent are reverse-engineered from the human-in-the-loop experiments in the immersive virtual reality environments. Finally, experiments are conducted using the constructed simulations to compare safety and productivity for different layouts. To demonstrate the proposed methodology, an automotive power-train (engine and transmission) manufacturing plant was used. Initial results look quite promising.     

A review of behavior mechanisms and crowd evacuation animation in emergency exercises

Emergency exercises are an efficient approach for preventing serious damage and harm, including loss of life and property and a wide range of adverse social effects, during various public emergencies. Among various factors affecting the value of emergency exercises, including their design, development, conduct, evaluation, and improvement planning, this paper emphasizes the focal role of evacuees and their behavior. We address two concerns: What are the intrinsic reasons behind human behavior? How do we model and exhibit human behavior? We review studies investigating the mechanisms of psychological behavior and crowd evacuation animation. A comprehensive analysis of logical patterns of behavior and crowd evacuation is presented first. The interactive effects of information (objective and subjective), psychology (panic, small groups, and conflicting roles), and six kinds of behavior contribute to a more effective understanding of an emergency scene and assist in making scientific decisions. Based on these studies, a wide range of perspectives on crowd formation and evacuation animation models is summa- rized. Collision avoidance is underlined as a special topic. Finally, this paper highlights some of the technical challenges and key questions to be addressed by future developments in this rapidly developing field.     

Do people follow the crowd in building emergency evacuation? A cross-cultural immersive virtual reality-based study

This study aimed to examine the influence of crowd flow on human evacuation behavior during building fire emergencies, when evacuees perceive high uncertainty in the environment and experience mental stress. Evacuation experiments were conducted in an immersive virtual metro station, in which each participant was presented with one of three different patterns of crowd flow and asked to complete an evacuation task. The patterns of crowd flow were represented by non-player characters that split differently at each wayfinding decision point in the metro station. The experiments were conducted in Beijing, Los Angeles and London. The results showed that uneven splits of crowd flow motivated participants under mental stress to follow the majority of the crowd. This influence of crowd flow was generally consistent over the course of evacuation, and such consistency could be reinforced by stronger directional information conveyed by the crowd flow as well as positive feedback from the outcomes of previous wayfinding decisions. The results also indicated that the influence of crowd flow was significant in all three cultures represented by the three cities, however, the impact of culture on how participants would respond to the directional information conveyed by the crowd flow was insignificant.     

An enhanced model for evacuation vulnerability assessment in urban areas

Rapid urbanization has led to a massive influx of people into cities. When many people congregate in urban areas, crowd crushing emergencies are likely to occur. If vulnerable areas with potential evacuation problems are detected in advance, crowd crushing emergencies may be minimized or even avoided. Thus, an evacuation vulnerability assessment from a precautionary perspective is fundamental. However, the current evacuation vulnerability assessment models are limited in spreading time estimation and evacuation capacity evaluation. To mitigate these limitations, in this study, we propose an enhanced model to quantitatively assess the evacuation vulnerability in urban areas. Our model enhances the current models in two ways. First, we employ a hexagon gridding scheme to construct a network to meet the prerequisite of evacuation spreading at the equal time intervals. Second, we quantify the grid connectivity on the network by considering the grid capacity to avoid underestimation of the evacuation vulnerability. Using a mobile phone location dataset of Shanghai, we systematically investigate the evacuation vulnerability of urban areas in a fine-grained spatio-temporal scale. Areas that may encounter evacuation problems to various degrees can be identified in advance. This information can support emergency management agencies in monitoring dense crowds and ensure early warnings of potential crowd crushing emergencies.     

复杂条件下多层建筑人员协作疏散仿真

研究具有复杂多层协作过程条件下的人员疏散控制系统,就能够比较准确地模拟突发情况下人员的疏散情况。本文对元胞自动机进行了改进,综合人员个体特征和从众心理等各种复杂因素,对具有复杂障碍物的多层建筑中人员疏散过程进行了计算机仿真分析,并给出了人员疏散效率与人员的从众系数、障碍物及出口位置等因素的关系。该仿真能够很好地模拟大型公共场所发生突发事件时人员疏散的情况,对在复杂地理环境及人员特性条件下的多层建筑突发事件疏散策略制定具有一定的实际参考意义。     

基于突发事件影响力传播的双向人流疏散仿真

当突发事件发生时,行人行走行为会因为突发事件本身以及突发事件在人群中的传播而改变。对于突发事件影响下的行人行走特征的研究能够提高人流疏散的效率。针对现有研究中数据获取方式的不足,对真实行人场景视频进行图像处理,提取相关数据后分析了无突发事件时行人一般行走特性。针对突发事件下的行人流,利用k-邻近算法和合力的思想描述了突发事件的影响传播和突发事件下行人流的自组织现象,并由此提出一种新的元胞自动机模型,该模型中的行人元胞会受到正常行走、突发事件、安全标识这三个因素所抽象产生的三个作用力的影响。利用模型对突发情况下的双向人流疏散进行仿真,实验结果表明,当安全标识的距离为0、10、20个元胞时,在小范围行人通道中安全标识分布的距离对人群疏散作用不明显;通过对人群间是否存在影响力的研究发现,疏散的效果主要受到附近行人对突发事件传播的影响;突发事件的影响程度太大或影响范围过小都会引发拥堵,不利于人群的疏散。仿真结果与真实世界中的双向行人流疏散情况基本吻合。     

Computer simulations vs. building guidance to enhance evacuation performance of buildings during emergency events

Computer technologies can play an important role in the establishment of dynamic building information by introducing predictive modelling where behaviours of structures or groups of people can be simulated and observed. This way they can facilitate the design of the built environment to cope with emergency events. Modelling and simulation applications can be particularly useful at pre-planning, predicting possible damage, training responders, raising public awareness, and performance evaluation for reconstruction. They can be used for the development of virtual scenarios that include aspects of rescue operations, social behaviour of building occupants, and basic design requirements to test the current building codes and regulations. Within this context, the contribution of crowd simulation to improving the design of the built environment and guidelines is highlighted in this paper. Current building guidance for emergencies are summarised and the methodology developed to use crowd modelling to define design information associated with exit preferences of people during evacuations is explained. The results of the case studies underlined that there is a difference between the assumptions used for static information in current building guidance.     

Modeling Crowd and Trained Leader Behavior during Building Evacuation

This article considers animating evacuation in complex buildings by crowds who might not know the structure's connectivity, or who find routes accidentally blocked. It takes into account simulated crowd behavior under two conditions: where agents communicate building route knowledge, and where agents take different roles such as trained personnel, leaders, and followers     

考虑分类人群行为的建筑疏散模型研究

人员行为决定了应急疏散时人群的时空分布,是研究疏散动力学的关键。考虑疏散时人员的心理特性与身份状态,将人群分为恐慌人群、易感人群、冷静人群和管理人群四类,基于社会力模型表达各类人群的疏散行为特征,并开展不同情境的疏散动力学过程分析。研究发现行人的恐慌心理具有传播作用,对其他行人的疏散行为有明显的影响,而管理人员的引导作用对疏散有积极影响,当其比例在10%~15%的时候效果显著,且合适的位置更易提高疏散效率;人员的服从水平越大,疏散效率越高。提出的分类人群疏散行为模型能为建筑安全疏散评估与优化提供理论支持。     

基于Agent的人员疏散系统设计与实现

通过分析Agent与社会力模型在人员疏散方面的应用及疏散模拟中人和建筑物对象的存储方式,利用Agent技术结合人员疏散的动力学模型、改进的路径规划算法和人员在一般情况下的心理因素以及建筑物的不同特点,建立能够正确反映疏散时人员行为的Agent模型,运用C++语言实现基于Agent的人员疏散模拟系统。疏散结果显示,该系统能够较真实地模拟人员疏散过程。     

Understanding building occupant activities at scale: An integrated knowledge-based and data-driven approach

Buildings are our homes and our workplaces. They directly affect our well-being, and they impact the natural global environment primarily through the energy they consume. Understanding the behavior of occupants in buildings has vital implications for improving the energy efficiency of building systems and for providing knowledge to designers about how occupants will utilize the spaces they create. However, current methods for inferring building occupant activity patterns are limited in two primary areas: First, they lack adaptability to new spaces and scalability to larger spaces due to the time and cost intensity of collecting ground truth data for training the embedded algorithms. Second, they do not incorporate explicit knowledge about occupant dynamics in their implementation, limiting their ability to uncover deep insights about activity patterns in the data. In this paper, we develop a methodology for classifying occupant activity patterns from plug load sensor data at the desk level. Our method makes us of a common unsupervised learning algorithm—the Gaussian mixture model—and, in addition, it incorporates explicit knowledge about occupant presence and absence in order to preserve adaptability and effectiveness. We validate our method using a pilot study in an academic office building and demonstrate its potential for scalability through a case study of an open-office building in San Francisco, CA. Our method offers key insights into spatially and temporally granular occupancy states and space utilization that could not otherwise be obtained.     

A hybrid hierarchical agent-based simulation approach for buildings indoor layout evaluation based on the post-earthquake evacuation

In the aftermath of severe earthquakes, building occupants evacuation behaviour is a vital indicator of the performance of an indoor building design. However, earthquake evacuation has been systematically neglected in the current building design practice. Arguably, one of the primary reasons for this is that post-earthquake evacuation behaviour is complex and distinct from all other types of evacuation behaviours such as fire. Thus, a comprehensive approach to considering the integration of human evacuation behaviour and a building's indoor layout design, mainly focused on non-structural damage, has been consistently neglected in the literature. In this paper, a hierarchical hybrid Agent-Based Model (ABM) framework integrated with a Cellular Automata (CA) and a 2D Building Information Model (BIM) damage visualisation to consider an approximation of non-structural damage has been developed. The proposed ABM incorporates learning mechanisms and human psychological aspects influencing evacuees' utility during the navigation process. The proposed approach was verified by comparing the results to previous real-life post-earthquake evacuation data and a “model to model” comparison of results from the existing relevant studies. The model prototype was successfully tested to simulate the pedestrian evacuation process from one floor of the new engineering building at The University of Auckland, New Zealand. The proposed simulation approach has been carried out for two different internal layout design alternatives where five population sizes are evacuated through different scenarios. The outputs from this study can be used to improve the design's compatibility of the building's indoor layout with the occupants' post-earthquake evacuation behaviour.