Building Emergency Evacuation: Innovative Modeling and Optimization

建筑紧急疏散：创新建模与优化

• 批准号: 1000495
• 负责人: Peter Luh
• 金额: $ 49.85万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1000495&HistoricalAwards=false
• 关键词: Building; Emergency; Evacuation; Innovative; Modeling

Many lessons have been learned on building emergency evacuation, with perhaps the steepest advances made through detailed analyses of the large-scale evacuations involved in events such as 1993 and 2001 World Trade Center attacks. Such studies have identified several key features of crowd evacuation behaviors, including significant delays before evacuation and the few factors that affect evacuation routes. Also, crowd disorder and blocking were well observed in events such as the nightclub fires of Rhode Island in 2003 and of Bangkok in 2009. These features have been explained through psychological theories and models, and viewed as crucial determinants for the evacuees? survival in emergency evacuation. However, one critical gap is that the wealth of such psychology-related knowledge encapsulated in the diverse and complex array of theories, models and simulation has not been integrated into the current methods for emergency evacuation. Consequently, intuitions are mostly used regarding the potential consequences of providing one set of guidance versus another to evacuees, and psychological factors that affect crowd behaviors are not systematically considered. With recent technological innovations on fire detection, crowd communication and guidance in emergencies, it is important to redress the serious gap between the state-of-the-art knowledge and our ability to effectively guide crowds to safety. In the proposed research, an innovative model of crowds will be developed to incorporate key psychological behaviors of evacuees, including initiation delay, way-finding, and disorder and blocking. It will describe how situation information (e.g., perceived hazard and guidance received) changes crowd behaviors in the collective or group sense (e.g., crowd flow delays, directions, and rates), and enable the prediction of crowd movement. An optimization problem will be established to evacuate as many people and as fast as possible while reducing relevant risks through appropriate guidance on crowds by using, for example, dynamic exit signs or audio announcements. To efficiently solve this time-critical problem, advanced optimization methods will be developed and synergistically integrated within a divide-and-conquer approach to generate effective guidance. The models and methods will then be used to generate virtual reality experiments from the first-person perspective to validate psychological behaviors of participants. In addition, a Wiki-based platform will be developed to test, validate, and enhance models and methods through open sourcing of various modules and sharing of lessons learned for broad participation and impact. With the involvement of Wiki-based platform participants, the research will have broader impacts on education, academic research, and engineering use; and the applications of the models and methods to other similar problems, e.g., emergency management of high school or university events or emergency evacuation of cities or regions. Furthermore, the research will be thesis topics for participating Ph.D. and MS students and special projects for undergraduate students, educating the next generation of engineers, psychologists, and homeland security leaders. Special efforts will be made to recruit minority and female students, including but are not limited to our participations in UConn School of Engineering?s ?da Vinci? program designed for high school mathematics and science teachers and counselor, the ?Multiply Your Options? program designed for 8th grade middle school female students, and the ?Engineering 2000? program designed for high school juniors and seniors. Our goals are to establish sound theory and methods for innovative modeling and optimization of time-critical and high-stake events while attracting and educating students. Ultimately, the proposed research will benefit society by saving lives and reducing injuries through better designed or configured evacuation systems, and through optimized crowd guidance in real time.

在建立紧急疏散方面吸取了许多经验教训，通过对1993年和2001年世贸中心袭击等事件中涉及的大规模疏散进行详细分析，可能取得了最大的进展。这些研究已经确定了人群疏散行为的几个关键特征，包括疏散前的重大延误和影响疏散路线的少数因素。此外，在2003年罗德岛和2009年曼谷夜总会火灾等事件中，人们很好地观察到了人群混乱和堵塞。这些特征已经通过心理学理论和模型得到解释，并被视为疏散人员的关键决定因素？在紧急疏散中生存。然而，一个关键的差距是，包含在各种复杂的理论、模型和模拟中的与心理学有关的丰富知识尚未纳入目前的紧急疏散方法。因此，直觉主要是关于向疏散人员提供一套指导与另一套指导的潜在后果，而没有系统地考虑影响人群行为的心理因素。随着最近在火灾探测、人群交流和紧急情况下的指导方面的技术创新，重要的是纠正最先进的知识与我们有效地引导人群到达安全地带的能力之间的严重差距。在拟议的研究中，将开发一个创新的人群模型，以纳入疏散人员的关键心理行为，包括启动延迟、找路、混乱和阻塞。它将描述情况信息(例如，感知到的危险和收到的指导)如何改变集体或群体意义上的人群行为(例如，人群流动延迟、方向和速度)，并使人群移动预测成为可能。将建立一个优化问题，以尽可能多和尽可能快地疏散人员，同时通过使用动态出口标志或音频通知等对人群进行适当指导来减少相关风险。为了有效地解决这一时间紧迫的问题，将开发先进的优化方法，并将其协同整合到分而治之的方法中，以产生有效的指导。然后，这些模型和方法将被用于从第一人称角度生成虚拟现实实验，以验证参与者的心理行为。此外，还将开发一个基于Wiki的平台，通过开放各种模块的来源和分享经验教训，测试、验证和增强模型和方法，以便广泛参与和产生影响。在维基平台参与者的参与下，这项研究将对教育、学术研究和工程使用产生更广泛的影响；并将模型和方法应用于其他类似问题，例如高中或大学活动的紧急管理或城市或地区的紧急疏散。此外，这项研究将是参与博士和硕士研究生的论文主题，以及面向本科生的特殊项目，以培养下一代工程师、心理学家和国土安全领导人。将特别努力招收少数民族和女性学生，包括但不限于我们参加康涅狄格州大学工程学院？S？达芬奇？该计划专为高中数学和科学教师和辅导员，？倍增您的选择？为八年级女生设计的课程，以及工程学2000？为高三和高年级学生设计的课程。我们的目标是建立完善的理论和方法，在吸引和教育学生的同时，对时间关键和高风险的活动进行创新建模和优化。最终，拟议的研究将通过更好地设计或配置疏散系统，以及通过优化实时人群引导来拯救生命和减少伤害，从而使社会受益。