Collaborative Research: The Role of Stress in Human Crowd Dynamics during Emergency Situations

这项拨款旨在了解压力是如何在从一个空间撤离的人之间传播的。在紧急情况下快速安全地撤离一个空间可以挽救生命，但众所周知，压力会影响一个人快速离开建筑物的能力。人们不太了解的是，一个人自己的压力状态如何传染给群体中的其他人，可能会加剧群体压力水平和有效的群体运动。该奖项支持解决这一复杂问题的实验和数学研究。实验将在一个可控的空间进行，在那里人们的运动、压力生理（如心率）和情绪将被仔细测量，目的是确定压力传染对群体的影响。然后，实验数据将用基于计算机的方法进行检查，以发现一个人的生理和情绪状态如何影响他们自己的疏散行为，以及小组中其他人的压力状态和疏散行为的模式。然后，这些结果将用于创建和测试一个模型，该模型可以预测在高压情况下疏散人群的行为。该模型将提供对控制人类在压力下如何一起行动的复杂因素的见解，这可以为人群管理策略提供信息，以确保人们与同伴和环境安全有效地互动。重要的是，数学模型可以用来测试人们在实验室实验中不可行的情况下的行为，但在真实的紧急情况下可能会发生。项目团队包括来自工程、数学和心理学的不同研究人员，以应对这一挑战，同时培养学生和博士后，作为跨学科合作的一部分。研究成果将通过同行评议的出版物、会议报告和在当地科学博览会上的非正式公共科学经验进行分享。现有的数学模型虽然能够定性地匹配疏散人群的整体运动，但它们只能部分地复制个人的运动，这表明它们缺乏关键变量。该项目将使用最先进的设备来跟踪多个人的位置，并采用多模式测量来索引生理和情绪状态，以高保真度重建个人的压力状态及其对他人压力和运动动态的影响。该项目将跨越数学、工程学和心理学，阐明生理和情绪因素（特别是压力状态和传染）在紧急疏散期间群体动力学中的作用。首先，收集行人实验的多模态数据。通过对实验数据的信息论分析，可以量化疏散人群中应力信息跨多个动态特征的流动。这将允许解剖压力状态（生理和情绪）、压力传染和运动之间的因果影响。这些关系将为一个新的基于主体的模型提供信息，该模型包括个体的压力特征，并根据实验进行校准。模型预测将在更多人群的实验中得到验证。这个经过验证的模型将为疏散实验提供一个道德代理，而不会引起过度的高压力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This grant seeks to understand how stress spreads among people who are evacuating from a space. Evacuating a space quickly and safely during an emergency has life-saving consequences, but it is known that feeling stressed impacts a person’s ability to exit a building quickly. Less understood is how one’s own stress state can contagiously spread to others in a group, potentially exacerbating group stress levels and efficient group movement. This award supports experimental and mathematical research that addresses this complex problem. Experiments with small and large groups will be performed in a controlled space where people’s motion, stress physiology, e.g., heart rate, and emotions will be carefully measured with the aim of determining stress contagion effects on the group. Experimental data will then be examined with computer-based methods to find patterns in how a person’s physiology and emotional state influence their own evacuation behaviors, as well as the stress states and evacuation behaviors of others in the group. These results will then be used to create and test a model that predicts the behavior of an evacuating crowd in high-stress scenarios. This model will offer insight into the complex factors that govern how humans move together under stress, which can inform crowd management strategies to ensure that people interact safely and efficiently with both peers and their environments. Importantly, the mathematical model can be used to test how people behave in scenarios that are unfeasible in laboratory experiments, but which can occur during real emergencies. The project team includes a diverse group of researchers from engineering, mathematics, and psychology to address this challenge while training students and a post-doc as a part of an interdisciplinary collaboration. Research results will be shared via peer-reviewed publications, conference presentations, and informal public science experiences at local science fairs. Existing mathematical models, while able to qualitatively match the overall motion of an evacuating crowd, they can only partially replicate an individual’s movement, suggesting that they lack critical variables. This project will use state-of-the-art facilities that track multiple people’s positions, with multi-modal measures which index physiological and emotional states, to reconstruct an individual’s stress state and its influence on others’ stress and movement dynamics with high fidelity. Bridging insights across mathematics, engineering, and psychology, this project will clarify the role of physiological and emotional factors–specifically, stress states and contagion–in group dynamics during emergency evacuation. First, multi-modal data from pedestrian experiments will be collected. Information-theoretic analyses of experimental data will quantify the flow of stress information within the evacuating crowd across multiple dynamic features. This will allow dissection of causal influences between stress state, both physiological and emotional, stress contagion, and movement. These relationships will inform a novel agent-based model that includes individuals’ stress features, calibrated to experiments. Model predictions will be tested in further experiments with large crowds. This validated model will provide an ethical proxy for evacuation experiments without inducing undue high stress.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.