household-level model for hurricane evacuation destination type choice using hurricane ivan data...
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Household-Level Model for Hurricane Evacuation Destination Type Choice Using Hurricane Ivan
Data Rodrigo Mesa-Arango, Samiul Hasan, Satish V. Ukkusuri, and Pamela Murray-Tuite
Group 4
Background• Hurricanes are one of the most dangerous and
costly weather-related natural hazards in the United States.
• The average fatalities per year related to hurricanes increased
• Considering these devastating impacts and the role of evacuation on their mitigation, it is the responsibility of public agencies to understand all the dimensions of an evacuation process. Comprehensive evacuation plans must integrate transportation theory with evacuation behavior.
Previous Literature• Models are classified into three major groups: trip
generation, departure timing, and destination and/ or route choice. But the destination choice has only been studied by a small number of researchers.
• Three types of zonal-level models have been used : gravity model, intervening opportunity model and MNL.
• they focus on zonal trip distribution without incorporating the choice among destination types and considering the percentage of evacuees traveling to each destination type as a given input.
• Destination only include houses of friends and relatives and hotels.
Some definitions important for
evacuation models• Proximate destination- the point in the transportation network where the evacuee exits the risk area
• Ultimate destination refers to both the town and/or city and the type of accommodation where the evacuees will stay until they can return to their homes
• This paper focuses on the second part of the ultimate destination
In This Paper• Destination: houses of friends and relatives, hotels, public shelters
and churches; and other.
• Variables influencing this choice include: hurricane position at evacuation time, household geographic location, race, income, preparation time, changes in evacuation plans, previous experiences with major hurricanes, household members working during the evacuation, and evacuation notices.
• Using a nested logit model.
• Data from Hurricane Ivan 2004 is used to calibrate the model.
• Application: findings can be used to develop evacuation strategies
How does this research relate back to Policy
making?• Recognizing public shelter demand and improving their locations and settings
• Developing better evacuation notices per population segment, giving advice on what destination types to choose
• Developing cooperative programs with hotels guaranteeing some levels of demand
• Recognizing potential regions that are attractive for evacuees to anticipate traffic congestion
Modeling framework
NL model⇒overcomes the IIA assumption problem by nesting alternatives and cancelling out their shared unobserved effects
Fig.?? Nested logit structure for hurricane evacuation destination type choice
←First level : destination type
←Second level : each destination
Estimation flow
𝑃h (𝑖 )=𝑒𝛽𝑖 𝑥h𝑖+𝜑𝑖𝐿𝑆h𝑖
∑∀ 𝐽
𝑒𝛽𝐼 𝑥h𝑖+¿𝜑 𝐼 𝐿𝑆h𝐼 ¿
𝐿𝑆h𝑖=𝐿𝑁 (∑∀𝐼
𝑒𝛽 𝐽∨𝑖𝑥h𝐽 )Logsum value
Unconditional Probability function of destination type
𝑃h ( 𝑗∨𝑖 )= 𝑒𝛽 𝑗∨𝑖𝑥h
∑∀ 𝐽
𝑒𝛽 𝐽 𝑥h𝐽Conditional probability of each destination
𝑃h❑𝑚 ( 𝑗 )=∫
𝑥
❑ 𝑒𝑉 h𝑗
∑∀ 𝐽
𝑒𝑉 h𝐽𝑓 (𝛽|𝜙 )𝑑 𝛽
The probability of household h choosing destination type j
(1)
(2)
(3)
(4)
variables
11 variables among 116 potential explanatory variables
Previous experienceAverage distance between the hurricane and the centroid
of the zip code where the house hold is located Indicator variables for White race dummy Indicator variables for Low income Indicator variables for evacuation notice Indicator variables for work during the evacuation
Example of explanatory value which have high t value
Implication to Our Research• Research flow should be followed:
Data Analysis→Model Formulation (sorting out significant factors)→Model Estimation (including considering which model to use)→Elasticity Calculation (evaluating or drawing up policy)
• NL Model can be applied to our destination choice model.
• Destination choice model focusing on individuals seems difficult to apply to our research focusing on visitors, whose characteristics is difficult to assume to some extent.
MNL
Sta-dium
Public shel-ter
EmbassyHotel
NL
Sta-dium
Public shel-ter
EmbassyHotel
Evacuation spot
NL
Sta-dium
Public shel-ter
EmbassyHotel
Evacuation spot
Implication to Our Research• Research flow should be followed:
Data Analysis→Model Formulation (sorting out significant factors)→Model Estimation (including considering which model to use)→Elasticity Calculation (evaluating or drawing up policy)
• NL Model can be applied to our destination choice model.
• Destination choice model focusing on individuals seems difficult to apply to our research focusing on visitors, whose characteristics is difficult to assume to some extent.