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，由人类在不确定性下的决策驱动，并受到社会，技术，空间和时间的限制。 该项目采取了一个整体的方法来建模的过程中集成的行为建模的家庭决策与方法的基础上新兴的概念，在网络科学，随机建模和基于代理的模拟。将通过科学电话调查收集数据，调查采用定性方法，并将其纳入时间GIS框架，包括2010年人口普查人口数据、空间风险区和运输路线信息。疏散警报的沟通和同化将使用新兴的复杂网络方法，包括随机网络上的社会传染建模。由此产生的影响，警告传播的风险感知将是一个输入到家庭代理为基础的疏散决策模型，将纳入社会和时间的限制。由此产生的疏散旅行（包括时间，潜在的路线/目的地），然后将分析和评估使用随机优化模型，包括非传统的目标，如疏散到安全和确定最佳路线，出发时间，该项目的重要性在于，它将社会科学和工程学结合起来，模拟一个社会和技术方面不能孤立研究的过程。 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，它应该开辟新的途径，在跨学科的研究和教学应用于既复杂又对社会有影响的问题。

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.