Evacuation Demand
CE 4780 – Hurricane Engineering
Spring 2003
1
Introduction
• Evacuation – what it is and why we do it.
• What it is – its ‘getting out of Dodge’
• Why we do it – avoid injury or death,
sometimes to protect
property
• Pre-event and post-event evacuation.
2
Types of Evacuation
• Pre-event evacuation:
–
–
–
–
When there is warning of an event
When negative effects are avoided by moving
When movement is possible and feasible
When information regarding the hazard and the
opportunity for evacuation are adequately
conveyed.
3
Types of Evacuation
• Post-event evacuation:
– When conditions caused by the event are
lasting and harmful
– When harmful conditions can be avoided by
moving away
4
Travel Demand
• Term used in transportation to describe the
amount of travel generated by people.
• Travel demand is expressed in terms of
TRIPS and, in regular transportation
planning, is expressed as the number of
vehicles per day that will travel on
individual links in the network.
• The demand on each link determines the
needed size of the link.
5
Evacuation Demand
• Is different from normal travel demand
because trips are:
–
–
–
–
Less discretionary
Involves larger volumes of traffic
Timing is more important
More opportunity for intervention in travel
decisions (e.g. evacuation orders, routing
directives.
6
Evacuation Demand
• In normal travel demand, link volumes are
important.
• In evacuation demand, link volume, the
time when evacuation occurs, and the
location from which it takes place, is
important.
7
Example
road
d1
t1 d
Zone 1
t2
Zone 2
d2
t3
d3
Zone 3
The load on the road network is dependent on the
dynamic loading
rates
at
each
zone,
the
relative
dd4
timing (sequencing) of the loading among zones,
8
and the relative location of the zones.
Evacuation Demand
• Is different from normal travel demand
because the factors driving the decision to
make a trip (evacuate) are different:
– Normal trips are made in order to participate in
an activity (work, shop, school, recreation, etc.)
– Evacuation trips are made to avoid danger and
are influenced by factors such as level of threat,
vulnerability of the individual, imminence of
threat, and opportunity to avoid danger.
9
Evacuation Demand
• Evacuation demand = f(threat level,
imminence of threat, vulnerability to threat,
opportunity to evade threat)
• Some causal factors are static (e.g.
vulnerability to threat) and others are
dynamic (e.g. threat level).
10
Why Do We Want to Estimate
Evacuation Demand?
• To be able to “model” evacuation travel
under alternative scenarios.
• With the ability to model we can:
– Estimate impact of alternative policies and
strategies with different storm scenarios
– Identify optimum contingency plans
– Estimate impact of alternative investment
strategies
11
Before we proceed into
modeling, lets look at the
behavioral analysis that has been
conducted in the past and what
has been learned.
12
Behavioral Analysis
How people have behaved during
past evacuations (revealed behavior)
Or
How they say they would behave
under alternative hypothetical
situations (stated behavior)
13
Revealed and Stated Behavior
• Revealed behavior:
– Requires that an event first occur
– The characteristics of the event are fixed
– Not all information can be gathered (e.g. speed,
delay, route)
• Stated behavior, on the other hand:
– Can be gathered at any time
– Characteristics of event are not fixed
– Even less information can be gathered than in
the revealed behavior case because variables
describing scenarios must be limited.
14
Revealed Behavior in the Past
15
Past Incidence of Hurricanes on
Central Gulf Coast
16
Conclusion From Previous Slide
• No location more prone to hurricanes than
another, other than in a regional sense.
• While general alignment of hurricane tracks
are discernible, individual tracks are
unpredictable.
17
Evacuation Rates
18
Factors Motivating Evacuation
• 1. Risk of flooding:
– High risk – elevation < 10 foot above sea level
– Moderate risk – elevation 10-15 feet above sea
level
– Low risk – elevation > 15 feet above sea level
• Evacuation rates in high risk areas are often
3 times those in low risk areas.
• People in low risk areas may not need to
evacuate at all – those that do are shadow
evacuees.
19
Factors Motivating Evacuation
• 2. Evacuation Orders:
– Precautionary or voluntary evacuation order
– Recommended evacuation
– Mandatory evacuation
• Dependent on means of dissemination
– Of those who hear a mandatory evacuation
order, over 80% have evacuated in the past.
– Of those who do not hear, less than 20% have
evacuated in the past
20
Factors Motivating Evacuation
• 3. Housing:
– Mobile home dwellers are more likely to
evacuate than persons in other home types.
– People in high-rise buildings are less likely to
evacuate than those in regular houses, all else
being equal.
21
Factors Motivating Evacuation
• 4. Storm Threat Information:
• The National Hurricane Center issues storm
advisories (storm watches and storm
warnings).
• Storm watches are issued when a storm is
expected to make landfall within 36 hours.
• Storm warnings are issued when a storm is
expected to make landfall within 24 hours.
22
Factors Motivating Evacuation
• 5. Storm severity:
• High correlation with evacuation orders and
flooding.
• Few studies have been conducted following
weak storms, so information on low storm
severity is sparse.
23
Factors Influencing Decision to
not Evacuate
•
•
•
•
•
Protect property from storm
Protect property from looters
Fulfill obligation to employer
Sometimes, peer pressure from neighbors
< 5% said they did not have transportation
24
Louisiana-Mississippi
2002 Hurricane
Behavioral Response Survey
Telephone survey
Jan-Feb 2002
Earl J. Baker presentation to S.E. Louisiana officials, 2002
25
Sample Design
Louisiana
• Orleans Parish
• Jefferson Parish
• SE Louisiana
N=400
N=400
N=400
– St. Tammany So. of I-10/I-12
– St. Bernard
– Plaquemines
N=134
N=133
N=133
Earl J. Baker presentation to S.E. Louisiana officials, 2002
26
Sample Design
Mississippi
Hancock
Harrison
Jackson
TOTAL
Cat 1-2
25
64
45
134
Cat 3-5
20
60
53
133
Non-surge
20
63
50
133
TOTAL
65
187
148
Earl J. Baker presentation to S.E. Louisiana officials, 2002
27
Evacuation Rates
Georges and Hypotheticals
Jefferson
Orleans
SE La.
Miss.
Georges
47
44
52
37*
Cat 3, So.
58
73
62
50
Cat 3, SW
48
60
53
42
Cat 4, So.
70
80
72
64
Cat 4, SW
62
72
66
53
Earl J. Baker presentation to S.E. Louisiana officials, 2002
28
Destinations in Georges
from Louisiana
Jefferson
Orleans
SE La.
Own Parish
21
30
16
Other La.
42
29
48
Mississippi
15
24
17
Thru Miss.*
11
10
11
Earl J. Baker presentation to S.E. Louisiana officials, 2002
29
Cat 3, So., Intended Destinations
Own Parish
Other La.
Miss.
Thru Miss.
TX/OK
Other
Don’t Know
Jefferson
Orleans
SE La.
23
33
15
9
10
3
9
38
20
16
7
10
1
8
23
37
17
12
4
1
7
Earl J. Baker presentation to S.E. Louisiana officials, 2002
30
Cat 3, SW, Intended Destinations
Own Parish
Other La.
Miss.
Thru Miss.
TX/OK
Other
Don’t Know
Jefferson
Orleans
SE La.
25
26
17
17
5
1
11
38
17
19
11
4
1
11
24
34
18
12
3
2
8
Earl J. Baker presentation to S.E. Louisiana officials, 2002
31
Cat 4, So., Intended Destinations
Own Parish
Other La.
Miss.
Thru Miss.
TX/OK
Other
Don’t Know
Jefferson
Orleans
SE La.
20
30
16
13
9
1
12
33
18
17
10
8
2
13
22
31
17
12
5
2
11
Earl J. Baker presentation to S.E. Louisiana officials, 2002
32
Cat 4, SW, Intended Destinations
Own Parish
Other La.
Miss.
Thru Miss.
TX/OK
Other
Don’t Know
Jefferson
Orleans
SE La.
22
27
18
14
4
1
14
31
17
20
13
3
1
15
22
31
17
12
5
2
11
Earl J. Baker presentation to S.E. Louisiana officials, 2002
33
Routes in Georges
I-10 E
I-10 W
I-12 E
I-12 W
I-55 N
I-59 N
I-49 N
US 49
Jefferson
Orleans
SE La.
Miss.
7
53
3
3
30
7
3
2
27
45
3
12
17
15
3
2
16
27
6
15
19
16
3
<1
27
13
0
2
4
4
0*
27*
Earl J. Baker presentation to S.E. Louisiana officials, 2002
34
Cat 3, So., Intended Routes
I-10 E
I-10 W
I-12 E
I-12 W
I-55 N
I-59 N
I-49 N
US 49
Jefferson
Orleans
SE La.
Miss.
15
44
<1
<1
29
8
5
0
23
48
2
4
15
12
2
2
19
33
4
7
19
21
4
0
21
14
0
1
6
10
0*
50*
Earl J. Baker presentation to S.E. Louisiana officials, 2002
35
Cat 3, SW, Intended Routes
Jefferson
Orleans
SE La.
Miss.
I-10 E
22
30
27
19
I-10 W
29
36
24
12
I-12 E
0
2
5
0
I-12 W
1
4
5
0
I-55 N
34
18
16
9
I-59 N
10
14
17
14
I-49 N
3
4
5
0*
US 49
<1
<1
<1
58*
Earl J. Baker presentation to S.E. Louisiana officials, 2002
36
Would Use Alternate Route
if Asked by Officials
Jefferson
Orleans
SE La.
Miss.
84
85
77
88
Earl J. Baker presentation to S.E. Louisiana officials, 2002
37
Would Avoid Interstates
if Asked by Officials
Jefferson
Orleans
SE La.
Miss.
79
84
77
87
Earl J. Baker presentation to S.E. Louisiana officials, 2002
38
Intended Use if
I-10, I-55 One-Way
Jefferson
Orleans
SE La.
Def. Yes
48
55
52
Prob. Yes
30
25
29
Prob. Not
4
6
7
Def. Not*
9
8
6
Don’t Know
8
6
6
Earl J. Baker presentation to S.E. Louisiana officials, 2002
39
Intended Use if
I-10, I-59 One-Way
Jefferson
Orleans
SE La.
Def. Yes
39
50
47
Prob. Yes
27
28
28
Prob. Not
15
6
11
Def. Not*
11
9
8
Don’t Know
9
8
7
Earl J. Baker presentation to S.E. Louisiana officials, 2002
40
Intended Use if
I-10, I-49 One-Way
Jefferson
Orleans
SE La.
Def. Yes
39
48
46
Prob. Yes
30
26
26
Prob. Not
11
11
13
Def. Not*
9
8
7
Don’t Know
11
8
8
Earl J. Baker presentation to S.E. Louisiana officials, 2002
41
Intended Use if I-55 One Way
Mississippi
Definitely Yes
36
Probably Yes
24
Probably Not
16
Definitely Not/Won’t
Evac
Don’t Know
14
11
Earl J. Baker presentation to S.E. Louisiana officials, 2002
42
Intended Use if I-59 One Way
Mississippi
Definitely Yes
36
Probably Yes
22
Probably Not
16
Definitely Not/Won’t
Evac
Don’t Know
14
12
Earl J. Baker presentation to S.E. Louisiana officials, 2002
43
Effect on One-Way Flow on
Decision to Evacuate
Jefferson Orleans
SE La.
Miss.
Evac. More Likely
47
43
41
37
Evac. Less Likely
4
3
3
4
No Effect
42
49
50
54
Don’t Know
7
6
7
5
Earl J. Baker presentation to S.E. Louisiana officials, 2002
44
Concerned About Being Trapped in
Traffic in Georges
Jefferson
Orleans
SE La.
Miss.
41
46
35
27
Earl J. Baker presentation to S.E. Louisiana officials, 2002
45
Heard Evacuation Information While on
the Road in Georges
Jefferson
Orleans
SE La.
Miss.
38
37
38
27
Earl J. Baker presentation to S.E. Louisiana officials, 2002
46
Type of Refuge Used in Georges
Jefferson Orleans
SE La.
Miss.
Public Shelter
9
7
9
8
Hotel/Motel
31
26
28
17
Friend/Relative
50
56
56
62
Other
90
11
7
13
Earl J. Baker presentation to S.E. Louisiana officials, 2002
47
Type of Refuge Intended in Cat 3, So.
Jefferson Orleans
SE La.
Miss.
Public Shelter
16
21
18
14
Hotel/Motel
32
25
25
17
Friend/Relative
30
37
38
53
Other/Don’t Know
22
17
19
16
Earl J. Baker presentation to S.E. Louisiana officials, 2002
48
Effect of Hearing That Shelters, Lodging
Are Full Before Evacuating
Mississippi
Stay Home
Go to Frnd/Rel in Same Loc.
Go to Different Location
Go Farther in Same Direction
Leave Earlier to Avoid That
Don’t Know
Other
15
25
8
23
20
9
1
Earl J. Baker presentation to S.E. Louisiana officials, 2002
49
Effect of Hearing That Roads Are
Heavily Congested Before Evacuating
Mississippi
Stay Home
Use That Route Anyhow
Use Different Route
Leave Early to Avoid That
Don’t Know
Other
18
6
31
34
10
<1
Earl J. Baker presentation to S.E. Louisiana officials, 2002
50
Summary
• 25% to 30% of SE La evacuees to go to or
thru Mississippi
• Higher than average in storms from SW
• Higher than average in stronger storms
Earl J. Baker presentation to S.E. Louisiana officials, 2002
51
Summary
• People receptive to using alternate routes
• People receptive to one-way routes
• One-way routes could increase number
evacuating
• 1/3 of evacuees already hearing evacuation
information via car radio after evacuating
• Full roads, refuges could deter some from
leaving
Earl J. Baker presentation to S.E. Louisiana officials, 2002
52
Evacuation Demand Modeling
53
Historical Development
• Three-mile Island nuclear accident
(threatened meltdown) in 1979 introduced
interest in modeling evacuation.
• Interest spread to other events such as
chemical spills, hurricanes, and wildfires.
• Current interest is in security of
transportation infrastructure and evacuation
from the aftermath of terrorist attacks.
54
Existing Hurricane Evacuation
Models
Simulation models
Analytical models
 NETVAC (MIT, 1981)  UTPP (PBS&J, 1985)
 DYNEV (KLD, 1982)
 Standard rates
 MASSVAC (VP, 1985)  ETIS (PBS&J, 2000)
 HURREVAC (COE, 1994)
 OREMS (ORNL, 1999)
 TransModeler (Caliper, 2000)
55
Main Factors Prompting Evacuation
• Post-storm Behavioral Surveys suggest the
main factors are:
Storm severity
 Storm proximity
 Vulnerability to flooding
 Evacuation orders
 Type of housing

56
Modeling the Decision to Evacuate
• Existing models:

Participation rate type
•
•
•
•

Category and speed of storm
Flooding potential
Tourist occupancy
Proportion of mobile homes
Logistic regression type
57
Participation Rate Models
• Cross-classification type models
Category 1, Slow
Mobile
home
Regular
home
Category 1, Fast
…
Mobile
home
…
Regular
home
Low
High
Low
High
Low
High
Low
High
….
tourist tourist tourist tourist tourist tourist tourist tourist
Low
flood
Med.
Flood
High
flood
58
Logistic Regression Models
 0  1 x1 ....   n xn
e
y
 0  1 x1 ....   n xn
1 e
where,
y  probabilit y hh evacuates
x1 , x2 ..  independen t variables
 0 , 1..  parameters
59
Logistic Regression Models (2)
y
 0  1 x ...   n xn
e
1 y
and ,
 y 
   0  1 x  ...   n xn
ln 
1 y 
fit with maximum likelihood
60
Logistic regression model of
Hurricane Andrew Evacuation
Variable
Constant
Mobile home
Single-family
house
Evacuation order
Age of respondent
Proximity to water
Never married
Married

1.80
2.32
-1.05
Significanc
e
0.02
0.00
0.02
1.44
-0.04
0.80
-1.3
-0.80
0.00
0.00
0.00
0.02
0.04
61
Logistic regression model of
Hurricane Andrew Evacuation (2)
Variable
Mobile home
Single-family
house
Evacuation order
Age of respondent
Proximity to water
Never married
Odds
Ratio
10.1
0.4
4.2
0.7
2.2
0.3
95% confidence
limit
2.8-36.6
0.1-0.9
2.3-7.7
0.6-0.8
1.3-3.9
0.1-0.8
62
Logistic regression model of
Hurricane Andrew Evacuation (3)
Predicted
Evacuate
d
Evacuate
d
Not
14
8
Overall
%
%
correctly
correctly
predicte
predicte
d
d
63.6
Observed
Not
12
26
68.4
66.7
63
Participation Rate Model of
Hurricane Andrew (PBS&J model of
S.W. Louisiana
Parish
Cameron
Calcasieu
Jefferson Davis
Vermillion
Acadia
Lafayette
Iberia
Iberville
Evacuation Rate (%)
Observed
Predicted
100
100
30
66
14
37
75
67
35
54
23
15
58
99
40
45
64
Comparison of Models
Observed
Mean
evacuation
probabilities
Percent
RMSE
Logistic
regression
Crossclassificatio
n
37%
41%
56
0%
48%
63%
65
Time of Departure
• Response rates based on:
Past evidence
 Stated intentions
 Functions chosen using professional judgment
 Estimates based on expected rate of diffusion of
warning messages

66
Time of departure
67
Observed Mobilization
120
• Evacuation
start time,
Hurricane
Andrew,
1992,
Louisiana
100
80
60
40
20
0
3
9
15
21
27
33
39
45
51
Hour evacuation started
57
63
69
68
81
Mobilization Start Times
15%
Percent
• Evacuation
start times,
Hurricane
Andrew,
1992,
Louisiana
20%
10%
5%
0%
3
9
15
21
27
33
39
45
51
57
63
69
81
Hour evacuation started
69
Trip Distribution
• Professional judgment based on past
evacuation patterns:
– Default dispersion factors for each county or
evacuation zone
– Spreadsheet-based model
• Spatial interaction model such as the
Gravity model
70
Trip Distribution
• Common factors determining destination:
– Relatives and friends (50-70%)
– Hotels/motels (15-25%)
– Public shelters (5-15%)
71
Trip Assignment
• Route selection paradigms:
–
–
–
–
Myopic behavior
User or System Optimal behavior
Combined myopic and imposed behavior
Imposed behavior according to evacuation plan
72
Trip Assignment
• Common methods:
– Microsimulation
– Static User Equilibrium
• Emerging methods
– Dynamic traffic assignment
73
Crucial areas for research
• Spatial and temporal data:
–
–
–
–
–
Route choice
Destination
Departure time
Clearance time
Volumes and speeds
• Real-time data
• Dynamic traffic assignment
– Large networks
74