Identifier

etd-11022011-165822

Degree

Doctor of Philosophy (PhD)

Department

Civil and Environmental Engineering

Document Type

Dissertation

Abstract

Revealed preference is the traditional method to collect hurricane evacuation behavior data. However, revealed preference surveys, as they are currently administered, have the disadvantage that they are unable to collect time-sensitive and policy-sensitive data needed to test evacuation policies. In contrast, data collected from a time-dependent, stated-choice survey will allow researchers to collect not only time-sensitive and policy-sensitive data but also information that will allow testing potential new evacuation policies. However, no research has been conducted to establish the methodology of such a survey. To fill the gap, this study was conducted to develop a new time-dependent, audio-visual, stated-choice method to collect evacuation behavior data. To achieve the objective, nine animations of hypothetical storms were developed based on recent hurricane history. To test the new methodology and its effectiveness, data was collected using both new and traditional methods and their cost and ability to produce good evacuation models were compared. In the new method survey respondents had to watch animations of storm scenarios and answer questions related to their intended behavior while in the traditional method they reported on their behavior in hurricane Gustav that made landfall near New Orleans in 2008. Results indicate that the new stated-choice method is easy to use and effective in collecting time-dependent and policy-sensitive data but costs 25 percent more than the traditional method. The new method appears to have the potential of evolving into a survey instrument that can be used by researchers and practitioners working in hurricane evacuation modeling.

Date

2011

Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Wilmot, Chester

DOI

10.31390/gradschool_dissertations.550

Download

Share

COinS