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。     

基于深度时空Q网络的机器人疏散人群算法

针对目前人群疏散方法中机器人灵活性低、场景适应性有限与疏散效率低的问题,提出一种基于深度强化学习的机器人疏散人群算法。利用人机社会力模型模拟突发事件发生时的人群疏散状态,设计一种卷积神经网络结构提取人群疏散场景中复杂的空间特征,将传统的深度Q网络与长短期记忆网络相结合,解决机器人在学习中无法记忆长期时间信息的问题。实验结果表明,与现有基于人机社会力模型的机器人疏散人群方法相比,该算法能够提高在不同仿真场景中机器人疏散人群的效率,从而验证了算法的有效性。     

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。     

Behavioral,data-driven,agent-based evacuation simulation for building safety design using machine learning and discrete choice models

To improve occupant safety during building emergencies, evacuation simulations have been widely used for building safety design. Since occupant behavior is a determining factor for the outcome of building emergencies, accurately capturing how occupants make decisions and integrating occupants’ decision-making processes in evacuation simulations is important. In this study, based on the results of fire evacuation experiments in a virtual metro station, how different social (crowd flow) and environmental (visual access and vertical movement) factors would affect individuals’ wayfinding behavior was predicted using machine learning and discrete choice models. The trained models were further employed in agent-based evacuation simulations to examine crowd evacuation performance under different building design scenarios. Both the machine learning and discrete choice models could accurately predict individuals’ directional choices during emergency evacuations. Different building attributes could collectively influence occupant behavior, leading to distinct exit choices and evacuation times. While both the trained machine learning and discrete choice models generated similar results, the discrete choice model had better interpretability. Moreover, by comparing the trained models in this study with a model developed in a prior study, it was found that agents had significantly distinct responses to different building designs. Critical factors (e.g., type and size of buildings, occupants’ familiarity with the building) for the applicability of evacuation models were identified. Furthermore, recommendations were provided for future research that aims at employing evacuation simulations for building design evaluation and optimization.     

结合最短路径改进的社会力人群疏散仿真模型

社会力模型广泛应用于人群疏散仿真,针对该模型在仿真过程中存在行人停滞不前、无法通过非凸边形障碍物和疏散路径与行人实际选择的路径不相符等问题,提出了一种社会力改进模型。该模型基于场景中的障碍物生成路径节点,利用这些节点生成无向图,同时考虑了节点的安全系数和拥挤系数对节点通行性的影响生成最短疏散路径。通过改进后的社会力模型进行了多种场景的仿真实验,实验结果显示行人在复杂障碍物场景中能有效绕过障碍物,生成合理的疏散路径,表明该模型有效改善社会力模型,使人群疏散仿真更加真实。     

Crowd simulation for emergency response using BDI agents based on immersive virtual reality

This paper presents a novel methodology involving a Virtual Reality (VR)-based Belief, Desire, and Intention (BDI) software agent to construct crowd simulation and demonstrates the use of the same for crowd evacuation management under terrorist bomb attacks in public areas. The proposed BDI agent framework allows modeling of human behavior with a high degree of fidelity. The realistic attributes that govern the BDI characteristics of the agent are reverse-engineered by conducting human-in-the-loop experiments in the VR-based Cave Automatic Virtual Environment (CAVE). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes (e.g., maps, demographics, evacuation management parameters). The validity of the proposed data models are tested with two different evacuation scenarios. Finally, experiments are conducted to demonstrate the effect of various crowd evacuation management parameters on the key performance indicators in the evacuation scenario such as crowd evacuation rate and densities. The results reveal that constructed simulation can be used as an effective emergency management tool.     

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。     

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。     

基于元胞自动机和模糊理论的人群疏散仿真

基于元胞自动机和模糊理论建立了人群疏散模型,对教学楼内的人群疏散过程进行了模拟。该模型根据人员对建筑物的熟悉程度、周围人员的吸引力设计元胞行为准则,并且采用模糊隶属度定义人员的体能状态及人员对环境的熟悉程度。实验结果表明,该仿真模型能够较好地模拟紧急状况下的人群疏散过程。     

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.     

A BIM-based simulation framework for fire safety management and investigation of the critical factors affecting human evacuation performance

Fire hazards are a big threat to human life and property safety. The U.S. fire statistics reveal that, in 2017 alone, 1,319,500 fires caused 3400 deaths and 14,670 injuries, which resulted in a loss of $23 billion [1]. Effective evacuation planning in densely occupied buildings should be primarily put in place if both the number of injuries/fatalities and the level of property loss are to be minimized. However, it is not realistic, and is unethical to study human evacuation performance under a burning building. For this reason, computational tools tend to be the best approach for simulating fire growth as well as human response to fire hazards. This study aims to develop a BIM-based simulation framework that implements the Fire Dynamic Simulator (FDS) and agent-based modeling (ABM) for simulating fire growth and evacuation performance for different building layout scenarios. An experimental implementation is conducted to validate the proposed framework, which verified the benefits of (1) using BIM to offer a platform for conducting simulation design and visualizing the simulation results of (a) hazardous fire zones and (b) effective escape routes; (2) simulating fire growth using the FDS tool; (3) developing an agent-based model that accounts for the critical factors affecting evacuation performance; and (4) applying a statistical analysis for investigating the effects of influential parameters from the proposed model. As a result, the simulation outputs can be used to optimize the building design and to investigate the influential factors on human evacuation efficiency. The proposed framework contributes to building fire safety management by enabling to minimize both injuries/fatalities and property loss.     

Model checking response times in Networked Automation Systems using jitter bounds

Response time (RT) of Networked Automation Systems (NAS) is affected by timing imperfections induced due to the network, computing and hardware components. Guaranteeing RT in the presence of such timing imperfections is essential for building dependable NAS, and to avoid costly upgrades after deployment in industries.This investigation proposes a methodology and work-flow that combines modelling, simulation, verification, experiments, and software tools to verify the RT of the NAS during the design, rather than after deployment. The RT evaluation work-flow has three phases: model building, modelling and verification. During the model building phase component reaction times are specified and their timing performance is measured by combining experiments with simulation. During the modelling phase, component based mathematical models that capture the network architecture and inter-connection are proposed. Composition of the component models gives the NAS model required for studying the RT performance on system level. Finally, in the verification step, the NAS formal models are abstracted as UPPAAL timed automata with their timing interfaces. To model timing interfaces, the action patterns, and their timing wrapper are proposed. The formal model of high level of abstraction is used to verify the total response time of the NAS where the reactions to be verified are specified using a subset of timed computation tree logic (TCTL) in UPPAAL model checker. The proposed approach is illustrated on an industrial steam boiler deployment.     

Incorporation of BIM-based probabilistic non-structural damage assessment into agent-based post-earthquake evacuation simulation

Earthquakes can cause severe damage to structural and non-structural elements of buildings; consequently, they pose high risks to human lives. To mitigate such risks, attention has been paid to enhancing the indoor environment for increased building safety. Yet little effort has been made to assess a building occupants' evacuation behaviors in response to damage to the indoor environment. This paper addresses this issue with a novel simulation framework that couples human behaviors with changes to the indoor building environment during post-earthquake evacuation. In particular, we present a building information modelling (BIM)-based prototype that simulates seismic damage to the non-structural indoor elements and visualizes its impacts on evacuation using a color-coded heat map. The simulated damage is then used as input to an agent-based model for post-earthquake evacuation. Using a probabilistic method to assess the non-structural elements' damage states, we are able to evaluate the impact of indoor damage on the evacuation process. We performed a trial of our prototype for a hypothetical earthquake in an educational building. The results revealed how the average evacuation time would increase as the earthquake intensity increases (from 38.6 s for the no-damage scenario to 122.9 for the highest-damage scenario). The proposed prototype has the potential to be joined with other tools, such as finite-element-based simulation, to incorporate structural analysis as well. Planners and designers can explicitly use our model's output to analyze the post-earthquake evacuation with the indoor non-structural damage to assess different building design geometries that increase the chances of a suitable evacuation process.     

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...     

基于全局路径规划的相互速度障碍物人群疏散方法

针对相互速度障碍物（RVO）模型缺少全局路径规划,只依靠局部碰撞避免不能很好地模拟复杂的疏散场景问题,提出了一种剩余路径代价尽量小的动态全局路径选择方法。该方法包含路径预处理和路径实时更新两部分:第一部分使用快速最短路径算法（SPFA）求取场景最短路径（SSP）;第二部分根据SSP快速动态地计算每个个体的最优疏散路径,并使用KD树优化障碍物阻挡判断过程。最后将方法扩展到多楼层、多障碍物、多通道、多出口的复杂场景实现了近千人的仿真实验。实验结果表明,该方法在多个场景中都取得了良好的路径规划效果。     

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.     

ACMICS: an agent communication model for interacting crowd simulation

Behavioral plausibility is one of the major aims of crowd simulation research. We present a novel approach that simulates communication between the agents and assess its influence on overall crowd behavior. Our formulation uses a communication model that tends to simulate human-like communication capability. The underlying formulation is based on a message structure that corresponds to a simplified version of Foundation for Intelligent Physical Agents Agent Communication Language Message Structure Specification. Our algorithm distinguishes between low- and high-level communication tasks so that ACMICS can be easily extended and employed in new simulation scenarios. We highlight the performance of our communication model on different crowd simulation scenarios. We also extend our approach to model evacuation behavior in unknown environments. Overall, our communication model has a small runtime overhead and can be used for interactive simulation with tens or hundreds of agents.     

基于Agent的应急疏散模型研究

根据突发事件出现的等级,选择安全区域,并采用适当的疏散方式,选择受灾区域的周边安全区域作为避难所;通过分析影响应急情况下人员选择目的地的因素,对人员疏散行为直观分析并结合人机功效评估,对疏散行为规范,建立基于Agent的应急疏散人员避难所选择模型。通过设定可能影响人员疏散的多种可能因素,该模型能够比较真实地模拟紧急情况下的人员疏散状态。仿真过程与实际情况相似,方法可广泛用于人员应急疏散过程分析研究。     

计算机辅助大规模人群疏散平台

针对现有疏散策略的不足,构建一个计算机辅助大规模人群疏散平台,为政府相关部门在城市建设和防灾规划中提供科学决策支持。该平台集成了疏散仿真模型和基于时变动态流问题的路网优化模型,引入组件式GIS技术,采用模块化多层体系结构建立了一个准确、实时的疏散引导系统。     

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.