Collaborative Research: From Warnings to Evacuation in Hurricanes: a Holistic Investigation using an Interdisciplinary Approach

飓风疏散是一个复杂的过程，受社会、技术、空间和时间约束，由人类在不确定条件下的决策驱动。该项目采用了一种整体的方法来对过程进行建模，将家庭决策的行为建模与基于网络科学的新兴概念、随机建模和基于代理的模拟的方法相结合。将通过使用定性方法开发的科学电话调查收集数据，并将其纳入时态地理信息系统框架，包括2010年人口普查数据、空间风险区和交通路线信息。疏散警告的通信和同化将使用新兴的复杂网络方法进行建模，包括在随机网络上的社会传染。由此产生的警报传播对风险感知的影响将成为基于家庭代理的疏散决策模型的输入，该模型将纳入社会和时间限制。这样产生的疏散行程(包括时间、潜在路线/目的地)将使用结合非传统目标(如疏散到安全)的随机优化模型进行分析和评估，并确定最优路线、出发时间和安全目的地。该项目的重要性在于，它将社会科学和工程学相结合来模拟一个不能单独研究社会和技术方面的过程。预报员和应急管理人员以及多个学科的研究人员都面临着这种相互联系。因此，它应该在跨学科研究和教学中开辟新的道路，应用于既复杂又对社会产生影响的问题。

Hurricane evacuation is a complex process driven by human decision-making under uncertainty and governed by social, technical, spatial, and temporal constraints. This project takes a holistic approach to modeling the process by integrating behavioral modeling of household decision making with methodologies based on emerging concepts in network science, stochastic modeling and agent based simulation. Data will be collected through scientific telephone surveys developed using qualitative methods and integrated into a temporal GIS framework including 2010 Census demographic data, spatial risk zones, and transportation route information. Communication and assimilation of evacuation warnings will be modeled using emerging complex network approaches including social contagion on random networks. The resulting impact of warning propagation on risk perception will be an input to household agent-based evacuation decision models that will incorporate social and temporal constraints. Evacuation trips thus generated (including timing, potential routes/destinations) will then be analyzed and evaluated using stochastic optimization models incorporating nontraditional objectives such as evacuation to safety and determine optimal routes, departure time, and safe destinations.The importance of this project is that it will integrate social science and engineering to model a process in which social and technical aspects cannot each be studied in isolation. This interconnection is faced by forecasters and emergency managers as much as by researchers in multiple disciplines. As such it should open new paths in cross-disciplinary research and teaching applied to problems that are both complex and of consequence to society.