Doctoral Dissertation Research: An Integrated Agent-Based Microsimulation Model for Hurricane Evacuation in New Orleans

博士论文研究：基于集成代理的新奥尔良飓风疏散微观模拟模型

• 批准号: 0802593
• 负责人: Nina Lam
• 金额: $ 0.78万
• 依托单位: Louisiana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2009-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0802593&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Integrated; Agent

Mass evacuation of urban areas due to hurricanes is a critical problem that requires extensive basic and applied research. Previous research used a microsimulation approach to simulate individual vehicle and driver behavior but was limited mostly to simulation in a small study area. Very few studies have considered the use of vulnerabilities in the evacuation strategies. There is a need to develop a better approach to integrate the various information (such as vulnerabilities) to better simulate evacuation so that we can evacuate people timely and efficiently. This Doctoral Dissertation Research Improvement project will develop an integrated microsimulation model to simulate hurricane evacuation in New Orleans. The first objective of this project will be to create a two-level regional disaster evacuation model by integrating two agent-based microsimulation models. The first model will treat each vehicle as an agent to simulate regional road network traffic movements on highways, while the second model will use each census block centroid as an agent to simulate the local part of the regional road network traffic. The second project objective will be to evaluate the effectiveness in terms of overall evacuation time and other metrics of three different regional evacuation strategies, including simultaneous evacuation strategy, a staged evacuation strategy based on different community-evacuation vulnerabilities over the study area, and a staged evacuation strategy based on different social-biophysical vulnerabilities.This research project will contribute to the fields of dynamic spatial modeling, visualization, and disaster and vulnerability science. The incorporation of vulnerabilities into two types of agent-based models will provide more realistic and accurate pictures of how evacuation behavior affects the effectiveness of different evacuation strategies, thus providing useful guidance to policy makers. Although the proposed integrated agent-based model will be based on hurricane evacuation in New Orleans, the methods developed and the knowledge gained from this research will be applicable for other regions and other kinds of disasters. Furthermore, the computer modules developed in this research will be widely distributed to benefit other agent-based traffic microsimulation models. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.

由于飓风而对城市地区进行大规模撤离是一个关键问题，需要广泛的基础和应用研究。 先前的研究使用了微仿真的方法来模拟单个车辆和驾驶员行为，但主要受到小型研究区域的模拟。 很少有研究认为在疏散策略中使用漏洞。 有必要开发一种更好的方法来整合各种信息（例如漏洞），以更好地模拟疏散，以便我们可以及时，有效地撤离人们。 这个博士学位论文研究改进项目将开发一个集成的微仿真模型，以模拟新奥尔良的飓风疏散。 该项目的第一个目标是通过整合两个基于代理的微仿真模型来创建一个两级区域灾难疏散模型。 第一款车型将把每辆车视为模拟高速公路上的区域道路网络交通运输的代理，而第二个模型将使用每个人口普查区块作为代理，以模拟区域道路网络交通的本地部分。 第二个项目目标是根据总体疏散时间和三种不同区域撤离策略的其他指标评估有效性，包括同时撤离策略，一种基于研究领域的不同社区撤离漏洞的分阶段撤离策略，以及分阶段基于不同社会生物物理脆弱性的撤离策略。该研究项目将有助于动态空间建模，可视化以及灾难和脆弱性科学领域。 将漏洞纳入两种类型的基于代理的模型将提供更现实，准确的图片，以了解疏散行为如何影响不同疏散策略的有效性，从而为政策制定者提供有用的指导。 尽管提出的基于综合代理的模型将基于新奥尔良的飓风疏散，但开发的方法和从这项研究中获得的知识将适用于其他地区和其他类型的灾难。 此外，本研究中开发的计算机模块将被广泛分发，以使其他基于代理的交通微仿真模型受益。 作为博士学位论文研究改进奖，该奖项还将提供支持，使有前途的学生能够建立强大的独立研究职业。