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.

飓风对城市地区的大规模疏散是一个关键问题，需要广泛的基础和应用研究。以前的研究使用微观模拟的方法来模拟单个车辆和驾驶员的行为，但主要限于在一个小的研究区域内进行模拟。很少有研究考虑在疏散策略中使用脆弱性。需要开发一种更好的方法来整合各种信息(如漏洞)，以便更好地模拟疏散，以便我们能够及时有效地疏散人员。这一博士论文研究改进项目将开发一个集成的微观模拟模型来模拟新奥尔良的飓风疏散。该项目的第一个目标将是通过集成两个基于主体的微观模拟模型来创建一个两级区域灾难疏散模型。第一个模型将每辆车视为一个代理来模拟区域路网交通在高速公路上的移动，而第二个模型将使用每个人口普查区块质心作为代理来模拟区域路网交通的局部部分。第二个目标是评估三种不同区域疏散策略的整体疏散时间和其他指标的有效性，包括同步疏散策略、基于研究区域不同社区疏散脆弱性的分阶段疏散策略和基于不同社会-生物物理脆弱性的分阶段疏散策略。该研究项目将为动态空间建模、可视化以及灾害与脆弱性科学领域做出贡献。将漏洞纳入两种基于主体的模型将提供更真实、更准确的疏散行为如何影响不同疏散策略有效性的图景，从而为政策制定者提供有用的指导。虽然所提出的基于智能体的综合模型将以新奥尔良的飓风疏散为基础，但从本研究中开发的方法和获得的知识将适用于其他地区和其他类型的灾害。此外，本研究开发的计算机模块还将广泛应用于其他基于智能体的交通微观仿真模型。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。