平行应急疏散系统:基本概念、体系框架及其应用

突发事件通常具有难以预测、多成因关联、危害性大及演变复杂等特点,应急情况下如何安全高效疏散人员是应急管控领域的重要研究内容.本文将基于人工系统（Artificial systems,A）、计算实验（Computational experiments,C）、平行执行（Parallel excution,P）方法的平行系统理论引入到应急管控领域,提出平行应急疏散系统（Parallel emergency evacuation systems,PeES）基本概念,构建系统体系框架及集成平台,并介绍人工应急疏散系统、计算实验、平行执行等主要功能模块的基本功能及实现方法.通过PeES能实现虚实应急疏散系统的管理与控制、应急方案的实验与评估以及相关人员的学习与培训.最后,以轨道交通枢纽站火灾场景下的乘客应急疏散为典型应用对平行应急疏散系统进行初步验证.     

基于ACP方法的高层建筑火灾中人员疏散策略研究

高层建筑结构规模巨大、人员众多,而疏散出口数量有限,如何有效安排疏散出口人员分布,提高疏散效率,是火灾应急管理的重要研究内容. 以人为中心的疏散系统是典型的复杂系统,具有难以真实实验分析的困难. 本文基于ACP（人工系统、计算实验、平行执行）方法,以智能体技术为核心建立了人工疏散系统,基于火灾场景,利用计算实验对疏散策略进行了验证、评估,给出了实际疏散系统与人工疏散系统的平行执行实现思想. 最后,通过案例验证了方法的可行性.     

基于元胞自动机的应急疏散系统仿真研究

分析了紧急情况下人员疏散的难点,提出了应急系统人员疏散策略,设计了一种基于CA的人员疏散模型.通过模型仿真,分析模型中相关参数对疏散效果的影响,在此基础上对人员疏散模型中地场方法进行改进,模拟结果表明,基于CA的应急疏散仿真能够很好的模拟建筑内人员应急疏散行为及紧急事件的发展情况.同时该仿真方法具有直观性、灵活性和可扩展性,为应急管理研究提供了一个很好的研究思路.     

地铁车站疏散照明指示系统的引导作用研究

通过对元胞自动机模型的分析和改进,建立了适用于地铁车站人员应急疏散模型,在此基础上以西安市某地铁车站为实例进行研究,探讨了疏散照明指示在人员疏散过程中的引导作用。并运用疏散模拟软件分别进行了不同情景布设方式下的模拟仿真,得出了相应条件下的疏散人数与疏散时间关系曲线图,并对数据进行分析比较得出了相关结论以期能为地铁疏散照明指示系统的建设提供参考。     

融合多种上下文的室内应急疏散导航位置模型

针对室内应急响应中如何科学、高效地对人员进行个性化实时疏散导航问题进行了研究,构建了一种面向复杂室内环境下融合多种上下文的应急疏散导航位置模型。利用改进的Dijkstra算法,结合实际环境动态上下文计算出实时疏散导航路径,为不同类型用户提供地图导航、语音导航、短信导航等个性化服务,同时为应急指挥者提供辅助决策支持。并以医院为例进行了实验,实验表明基于该模型及算法能够高效计算出满足不同类型用户需求的实时疏散导航路径,可应用于医院、商场等环境的应急疏散导航与救援中。     

基于计算实验的煤矿火灾人员疏散研究

人员疏散是煤矿火灾应急管理的重要研究内容,然而由于其复杂性、真实实验研究的困难性,研究领域尚未对煤矿中火灾人员的疏散进行探究。基于此,提出一种基于计算实验的研究方法。采用Agent建模技术搭建计算实验环境,通过局部微观Agent实体之间相互作用的集合,以三维模拟仿真的形式将难以设想的事故发展情况动态、实时、量化地展现出来,利用计算实验着重分析、评估火灾发生地点和巷道矿工数量对人员疏散的影响。结论:火灾发生地点和巷道矿工数量对人员疏散的时间产生影响,会导致疏散时间增加。     

基于Multi-agent的地铁站内人群应急疏散交互研究

地铁是人们日常出行的重要交通工具之一,地铁站作为人员密集场所,潜藏着巨大的安全隐患,一旦发生火灾,需要快速组织疏散,避免造成大量人员伤亡。提出领导者、普通者和惊慌者三种Agent,构建了多Agent交互协作模型,以某地铁站为仿真空间对象,采用Building EXODUS平台对模型进行仿真。仿真结果表明:疏散中各角色群体的交互,尤其是领导者Agent的引导和协调作用能够提高疏散效率,缩短疏散时间。     

突发事件情景下地铁站人员应急疏散问题综述*

突发事件情景下,合理的进行地铁站人员应急疏散是减少人员伤亡和财产损失的有效途径。从地铁站人员应急疏散的仿真研究、不同规则下疏散模型的研究和智能算法在疏散建模中的应用三个角度对突发事件下地铁站人员应急疏散问题进行综述,并分析了当前疏散模型、求解算法以及行人特征数据的不完善之处。提出了把行人的心理行为特征、建筑物设施因素引入地铁站人员应急疏散问题中,并利用改进的蚁群算法求解最优疏散路径的重要价值。最后,展望了今后地铁站人员应急疏散问题研究的发展趋势。     

元胞自动机地铁人员疏散模型仿真

基于元胞自动机模型对地铁人员疏散进行研究,通过对地铁的疏散个体微观建模,构建出元胞的移动规则,从而确定元胞下一时间步长的移动路径。针对地铁紧急情况下的疏散情形,提出了两种基于元胞自动机的疏散规则:概率计算方法和元胞空间场吸引法。利用VC++开发环境与OpenGL图形库对地铁的人员疏散情况进行仿真,描述不同疏散规则下的地铁疏散整个动态过程,并分别模拟得出不同的疏散效率,从而为指导地铁紧急情况下人员疏散提供理论依据。     

基于Pathfinder高校高层学生公寓火灾疏散仿真模拟研究

目前,高层建筑在高校建筑群中的数量快速增加,但出现了火灾疏散逃生的难题。因此,基于建筑信息模型(Building Information Modeling,BIM)技术和Pathfinder疏散模拟软件对某高校第23栋高层学生公寓楼进行人员疏散模拟,分析该学生公寓在应急逃生疏散中存在的安全隐患。从无人为干预下的数值模拟试验结果中得出,该高层学生公寓出口的利用率较低,疏散过程中楼道人员密度大,存在发生二次事故的风险。     

ViCTS: A novel network partition algorithm for scalable agent-based modeling of mass evacuation

Emergency evacuation is a critical response to deadly disasters such as hurricanes, floods, and earthquakes, etc. However, mass emergency evacuation itself is a complex process that sometimes could lead to chaotic situations and unintended consequences. In many emergency scenarios, mass evacuation is necessary to cope with severe public threats within tight spatiotemporal ranges. To better understand complex phenomena like mass evacuation, and study possible consequences, agent-based models (ABMs) have been widely developed in previous work. Existing models simulate individual behaviors, posing computational challenges when applied to large geographic areas and sophisticated behaviors. A key strategy for resolving such computational challenges is to partition transportation networks into smaller regions and resolve corresponding computational costs by taking advantage of advanced cyberinfrastructure and cyberGIS. In this study, a novel network partition algorithm is developed to improve the scalability of agent-based modeling of mass evacuation based on a cutting-edge cyberGIS-enabled computational framework that exploits the spatial movement patterns of emergency evacuation. Specifically, the algorithm is termed as Voronoi Clustering based on Target-Shift, or ViCTS. It is enlightened by network Voronoi diagrams and designed to resolve computational scalability challenges caused by the unique characteristics of evacuation traffic. We conducted a set of computational experiments with real street network data in various evacuation scenarios to test the effectiveness and efficiency of the algorithm. Computational experiments show that ViCTS outperforms a widely used network partition algorithm for microscopic traffic simulation in terms of achieving optimal computational performance by balancing computational loads and reducing communications across high-performance parallel computing resources.     

多层建筑应急疏散仿真

以多层建筑为背景,研究应急疏散问题,基于改进的路径规划算法,并将多智能体技术应用在模型间的通信交流上.采用机器人感知周围环境,通过设置机器人个数以及初始位置,对灾情中室内被困人员进行智能搜救,并采集现场实时数据,作出决策分析.机器人实时感知现场状况的变化,引导人员疏散,并将实时数据传输给施救人员,采取进一步救援措施.结果表明,该三维仿真技术为有效减少人员疏散中的伤亡和最佳救援方案的制定提供了参考,具有一定的现实指导意义.     

有限运力下的人员紧急转移模型

在可用运输工具种类及数量有限的条件下,研究了人员从受灾点向安置点分批紧急转移的问题,建立了人员转移及运输工具协同安排的优化模型。通过设计合理的初始解生成方法和遗传算子,提出了求解该问题的遗传算法;用两个数值例子对算法进行了验证。     

Estimating the effects of mental disorientation and physical fatigue in a semi-panic evacuation

Understanding the impossibility of replicating a real panic emergency situation and experimenting human objects in such artificially created dangerous situation, this paper focuses on the evacuation of a heterogeneous population including people with disabilities in a semi-panic simulated situation in which people tend to hurry more than those in non-panic evacuation but exhibit less urgency than those in a panic emergency. Ultimately, we intend to estimate and quantify the effects of mental disorientation and physical fatigue on the average evacuation times of six different disability groups and the entire group in a simulated environment of a 24-story building. According to our experiments, mental disorientation due to sudden emotion escalation from the recognition of unexpected dangers increases the average evacuation times up to 25 percent depending on the complexity of evacuation routes of the simulated buildings. In addition, accumulated physical fatigue of human beings during the evacuation process could also significantly delay the evacuation time. Most of all, the impact magnitudes of these two main factors vary depending on the types of disabilities of individuals, insinuating the needs of developing evacuation plans and strategies for each group.     

Efficient computation of evacuation routes on a three-dimensional geometric network

We consider a real-time emergency evacuation problem that seeks to compute a set of rapid evacuation routes in a building. Given a three-dimensional geometric structure of the evacuation network, an emergency evacuation route is a sequence of movements of people away from the threat or actual occurrence of a hazard (such as a fire, a hidden bomb) to a safe exit in the network. In such a network each room/crossing/exit in the building is designated as a node and the corridors/staircases/links between the rooms are edges. The evacuation times assigned to the edges are normally distributed random variables. This stochastic routing problem subject to deadline constraints is NP-hard. We provide a new pseudo-polynomial-time dynamic programming algorithm to solve this problem. Based on this algorithm, we construct two types of approximation algorithm, namely a fully polynomial-time approximation scheme providing “almost-optimal” solutions and a fully polynomial-time approximately feasible scheme yielding a best “almost feasible” solution. We present a case study and results of computational experiments to illustrate the working and efficacy of the proposed solution methods, respectively.