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.

Agency
National Science Foundation (NSF)
Institute
Division of Behavioral and Cognitive Sciences (BCS)
Type
Standard Grant (Standard)
Application #
0802593
Program Officer
Thomas J. Baerwald
Project Start
Project End
Budget Start
2008-04-01
Budget End
2009-09-30
Support Year
Fiscal Year
2008
Total Cost
$7,809
Indirect Cost
Name
Louisiana State University & Agricultural and Mechanical College
Department
Type
DUNS #
City
Baton Rouge
State
LA
Country
United States
Zip Code
70803