Journal of Natural Disaster Science, Volume 31, Number 2, 2009, pp33-41

Agent-based Flood Evacuation Simulation of Lifethreatening Conditions Using Vitae System Model

Yuling LIU*
Norio OKADA*
Dayong SHEN**
Shuoqi LI****Disaster Prevention Research Institute, Kyoto University**Department of Computational and Data Sciences George Mason University, Fairfax, VA, USA***Department of Urban Management, Kyoto University(Received for 20 Apr., 2010 and in revised from 1 Jun., 2010)
ABSTRACTThe Vitae System model is referenced to provide a systematic framework for theadaptive evacuation strategy in a life-critical situation by integrating its three fundamental
elements - survivability, vitality and communication. A preliminary model is proposedin the context of evacuation from a water related hazard. A multi-agent based evacuation
simulation system is prototyped combining hydraulic model data for the case area of the
Oike underground space in Kyoto, Japan. The impact of facility arrangement on evacuation
decision-making is demonstrated.
Keyword: Vitae System model, Underground ßooding, Agent-based modeling, Evacuation
simulation, Decision-making

these concerns is significant in evacuation planning,disaster education and training.
Much research has focused on estimating lossof life due to flooding. General functions or extended
functions were derived for flood mortality (DeKay
and McClelland (1993), Jonkman et al., (2002), Koshimura et al., (2006)). Penning-Rowsell et al., (2005)
applied a method to assess the flood risk to people
taking into account flood hazard, people vulnerability
and area vulnerability that are indicated by the speedof onset, nature of the area and flood warning. Amongthem, the nature of the area is categorized according
to stories such as multi-story apartments, two-story
buildings and single-story buildings, in which anunderground space is not clearly categorized. Elders
aged 75 or over and the chronically ill were counted

I. INTRODUCTION
In many cases unexpected flooding occurs soquickly and with insufficient warning that it allows
little or no time for evacuation. There is an increasingneed to prepare for events such as flash floods, landslides, and underground inundation in urban areas.
Particular attention should be given to evacuation in
an enclosed space, where evacuation is difficult due toits complexity in structure. Early evacuation is highly
recommended for those spaces (e.g. undergroundmalls), but difficulties still exist within minority populations who either respond late, become injured orare even totally unaware of the approaching hazard.
Therefore, they are already in a life-threatening situation when they implement coping actions. Addressing
33

YULING LIU, N. OKADA, DAYONG SHEN, SHUOQI LI

to measure people vulnerability. This method is suitable for risk assessment of non-critical situations.
Evacuations under life-threatening conditions inurban areas have not received much attention in theliterature. A life-threatening situation is a very critical life and death situation. In general, there is no
systematic analysis of different events particularly
deaths caused by a flood disaster connected with facility configuration and design. In Fukuoka in 1999,
for instance, a female employee who worked in anunderground restaurant was killed by the intrusion offlood water. The female employee called the manager
for help at 10:30am. The manager then rushed to thescene and contacted the emergency center at 11:15am.
The rescue team arrived at 11:24am but the woman
had drowned. Regarding this event, on the one hand,
given the rapid rate with which a flood can develop,
time becomes the overriding critical factor in emergency egress and rescue. Therefore, the communication mechanism needs to be discussed to improve theefficiency. On the other hand, what and how to do inorder to survive after calling for help produces the
problem of evacuation strategy in critical situations.
This issue in many agent-based simulations for floodevacuation is simply omitted. People usually are
considered dead or placed in the “difficult to evacuate” group once the hazard reaches a certain level. In
terms of water depth, the level is widely defined as 70
cm or 1 m according to physical evacuation experiments (Ishigaki et al., 2005). For example, Takahashi
T. (1989) used 70 cm as the walking threshold in theevacuation system. Toda K. (2006) grouped evacuees
into “difficult to evacuate” when inundation reaches
50 cm and “impossible” when the inundation is over
1 m or the overflow on the staircase is over 30 cm.
Multi-agent based modeling is an increasingly
powerful modeling technique for simulating individual interactions in a dynamic system and is distinctive
in its ability to simulate a situation where the future isunpredictable (Lampert 2002). For this reason, multiagent technology is widely used in various disastermanagement and community preparedness issues. So
far, there is no generally accepted theory that is able
to provide a framework for agent-based evacuation
simulation. In this paper, the Vitae System model isreferenced to provide a systematic framework for theadaptive evacuation strategy in a critical situation by
integrating its three fundamental elements - surviv-

ability, vitality and communication.
This article is structured as follows: Section 2
contains an overview of the Vitae System and a preliminary model for its three elements. The application of this model is demonstrated in an agent-based
study in Section 3. Concluding remarks are presented
in Section 4.
II. VITAE SYSTEM MODEL
The Vitae System Model is a new conceptual
framework for integrated disaster risk management(Okada, 2006). This model is intended to view cities, regions and communities as vital integrity withrobustness and resiliency in its coping capacity. The
model is depicted as a triangular diagram with threenodes as fundamental functions i.e., (i) survivability,(ii) vitality and (iii) communication.
In this paper, the Vitae System Model is applied
to address people’s instinctive capacity to respondinstantaneously to an external shock in the context
of disaster evacuation. It provides systematic logic tointerpret a special type of evacuation decision-making
in a critical situation where people have to survive
first for a relatively short period of time. When survivability is at least temporally guaranteed, we assume that vitality (such as one’s stamina and energy,
spiritual perseverance, etc.) counts so as to maintainthe survival status. In the entire process, interactive
communication with the surrounding environmentand other agents determines the success of self–help
and mutual aid.
The chance of survival under very critical situations is considered to rely very much on accessible
surrounding facilities and people’s sensibility. In
many actual cases people may eventually survive aflood disaster if they instantaneously make an appropriate decision and action, for example, jumping
onto a stage or hanging onto a pole which happens tobe there as a part of the environment. Such a facilityor place may be regarded and used as a provisional
shelter. It is evident that the capability of creatively
using the surrounding facilities is instrumental tothis choice. The success of making such a decision
and action is considered to depend very much on theknowledge and capability of the evacuee’s “sensibility” so as to immediately judge the situation andperform adaptive actions. Without such sensibility,
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AGENT-BASED FLOOD EVACUATION SIMULATION OF LIFE-THREATENING CONDITIONS USING VITAE SYSTEM MODEL

There is another moment when people face thecritical state leading to death as shown in Equation(1). Besides the case in which they have no sensibility (σ＝0 ), people will also be killed (even if people
have sensibility (σ＝1 ) and have so far successfully
survived by taking instantaneous refuge in a nearby
provisional shelter) if the overwhelming flood hazard
exceeds the level of. On the contrary, if people
have sensibility (σ＝1 ) and the hazard level is notas high as, then survivability is considered to beequal to ε.
Given the environmental layout of the surroundings, if an evacuee finds an instantaneous refuge, thenthe evacuee will shelter in it while waiting for help. In
this case, the chance that is provided for an evacuee
who has sensibility to survive depends totally on the
progress of inundation. However, if no facilities orplaces serving as a provisional shelter are available,
the only choice is to resort to others for help.
In a critical situation, there may be many instantaneously adaptive strategies to survive flooding inan underground space. As presented by S.N. Jonkman (2008), one basic empirical fact of flood eventsis that there are always survivors even if the wateris extremely deep; people tend to find debris, trees,
attics, roofs, and other ways to stay alive. In this research, two types of instinctive refuge are considered
including a platform (e.g. auto vending machine,
locker) and a pole. It should be noted that each evacuation strategy has its specific limitations determinedby the physically enduring hazard level. Hereum min[hp he , hc ]- h f in whichis the height ofan evacuee,is the height of instinctive refuge,is the height of the ceiling in an underground space,and is the vertical length of a person’s face. Details
are illustrated in Fig. 1. For the case of a platform, theenduring leveis equal to the sum of the height ofthe platform and the height of the evacuee minus thelength of his or her head. But if
exceeds theheight of the ceiling , then um hc - h f . For the caseof a pole, we assume that people can climb up to the
top of the pole and the pole connects to the ceiling, sothat the enduring level is not determined by the heightof the evacuee but by the height of the ceiling, .
Therefore, how long an evacuee can stay alive after
sheltering in a chosen provisional place is determinedby the time interval before the hazard reaches the level of . We use
to represent the effective interval

people will be killed immediately once the hazard
reaches the level of a life-threatening situation. To address these concerns, the structure and facility layout
inside a building, as well as people’s evacuation decision –makings and behavioral aspects are consideredin the modeling of its three elements.
A.Survivability (S)As shown in Table Ⅰ , the inundation depth isused to measure the hazard level. The characteristics
of existing facilities in size (height, width), mass andlayout reflect the environmental vulnerability, andpeople’s vulnerability resides in their sensibility.
TABLE I. Indicators of survivability for undergroundevacuation
Factors
HazardVulnerability

Type of
Indicators

Indicators

Environment

Inundation situation

Environment

Facility and its characteristics in size and layout etc

PeopleLack of Sensibility

Given the above basic assumptions, the survivability function is defined as follows:Stf ( , ut , um )

0

when

1 and ulut

when

0 or ut

um

um

(1)
where is inundation level at time , is thethreshold water level above which walking against
a flood becomes almost impossible, σ＝1 if people
have sensibility and thus instantaneously take temporary refuge, and σ＝0 if people do not have suchsensibility and thus are unable to do so.
Note that survivability is defined only for lifethreatening states. It corresponds to either the dichotomous states of one’s survivability, i.e. “scarcely
surviving” as indicated by ε taking on a very small
positive value such as 0.000001, or becoming immerepresents thediately killed as indicated by zero.
maximum endurance level of flood inundation.
The critical situation is considered to start fromthe moment when the hazard reaches the level of .
According to a hydraulic experiment (Ishigaki et al.,2005), it is difficult to escape using a staircase when
the overflow is above 30 cm. When the inundation isover 70 cm, it is very difficult to walk in flooding water, so is set as 70 cm in this research.
35

YULING LIU, N. OKADA, DAYONG SHEN, SHUOQI LI

rived.

as shown in Equation (2).
actually indicates theefficiency of a specific evacuation strategy subject tothe flood hazard and surrounding environmental vulnerabilities. The higher the platform, the longer. If
the flood hazard is increasing at a constant rate, then

Vt

Platform

Platform

hc
um

he

V0 (y) when Ri

R1

V0 (y) - 0.1t when Ri

R2

(4)

Seniors and children walk slower than adults dueto their weak physical status. Therefore, the differenceof the normal average walking speed for each age
group can be viewed as initial vitality that people possess, which is defined as 1.4 m/s for the adult group(aged 18-69), 1.2 m/s for the child group (aged 6-17)
and 1.0 m/s for the senior group (aged 70 or over).
The normalization process views the adult vitality as 1,
so we obtain the normalized initial vitality:t ( is a constant) . The slower
it follows that ut
the increasing rate, the longer.
Tid T{ut um } t0(2)
Where represents the time when an evacuee
starts to shelter in a provisional place.

hp

V0 (y) - ( Ri )t

V0 ( y )1 if y is an adult
6 / 7 if y is a child5 / 7 if y is a senior(5)

V0
Shelter on a Platform
1.0
6/7
5/7

Figure 1. Calculation diagram of
B.Vitality (V)In this research, vitality is defined as physical ormental vigor or energy (Merriam Webster dictionary).
In the process of an evacuation, vitality will decreaseover time as the physical consumption of vigor. Under critical situations, vitality varies with the different
evacuation strategies. For example, it requires moreenergy to shelter on a pole than on a platform.
As there are no physical experimental data to estimate the energy cost when people shelter on a poleor a platform, we assume that evacuees are normally
healthy and they share the same linear decreasing ratio of energy cost. Therefore, the normalized level ofvitality is indicated as:
Vt V0 (y)- ( Ri )t ( t :minute)(3)
Where 0(y) records the initial vitality possessed at the beginning of an evacuation, λ( ) is
the energy decreasing ratio, which varies dependingon the evacuee’s decision in the instinctive shelter
Ri ( R1 platform, R2 pole) . In this research, we assume a short-term stay for no longer than 12 hours sothat vitality decrease due to no food and water is notconsidered. In terms of sheltering on a platform, apartfrom the energy taken to climb up, it costs almost
nothing, which means that λ( ) ＝0. For the choiceof the pole, we assume the decreasing rate of energy
cost as 0.1. Therefore, the following equation is de-

Adult
Child
SeniorShelter on a Pole

50/7 60/7

10Time
Figure 2. Vitality change upon evacuation strategy
and time

It should be noted that how long people can endure given the chosen strategy depends upon not only
but also vitality. Therefore, the enduring time
takes on the smaller value of the above two periods oftime as shown in Equation (6).
(6)
T min[Tv 0 , Tid ]Where represents the enduring time, and ν＝0
represents the period of time when people used up
their energy.
is calculated as shown in Equation (2).
C.Communication (C)In the context of an evacuation from an underground flooding, the communication is classified into
four types:(1) Accessibility and escapable capacity to staircase or emergency exits(2) Evacuation guidance(3) External resources and information(4) Voluntary help and rescue
36

AGENT-BASED FLOOD EVACUATION SIMULATION OF LIFE-THREATENING CONDITIONS USING VITAE SYSTEM MODEL

The mechanism of communication is presented
in Fig. 3. From an individual agent’s viewpoint, communication can occur with the surrounding environment, nearby evacuees and outsiders. The communication with the surrounding environment is a one way
communication mode, which determines the successof self help. The process illustrates how people sense
the signals (i.e. hazard progress and facilities) fromthe environment and make instantaneous decisions
on a provisional refuge in order to survive the flood.
The communication results for different people vary
greatly depending on their sensibility. The interactive communication between evacuees is embodied inpossible mutual help, which provides a mechanism bywhich information can progress through the population (Gwynne et al., 2006).

to provide a strategic change in the evacuation decision. If an evacuee finds an instinctive refuge, thenthe evacuee will shelter in it while waiting for help.
The enduring time
is calculated by Equation (2)and vitality is calculated by Equation (4). If external
help is available during this time period, then a successful evacuation will be claimed. If someone nearby
willingly provides voluntary help, then the evacuee
and the help provider will form a group sharing thesame fate. But if neither external help nor nearby help
arrives in time, people will be killed eventually.
Instantaneous Decision Making

Hazard, Facility

An Evacuee

Ask for help

No

Instantaneous Refuge?
YesT

Environment

min[Tv 0 ,Tid ]t T
Other Evacuees

No

Failure End

Yes

Provide/No help
Ask for help

External Help?

Outsiders

An Evacuee

Failure End

No

Instinctive Search
An Evacuee

Yes

S =0

Come to the rescue
Yes

Figure 3. Communication behavior

Success End

The voluntary help provider needs to satisfy
three conditions that the helper should be in a young
age group, be under a non-critical situation and be
willing to provide voluntary help. Moreover, anevacuee may resort to asking for help from outsiders
such as the police, NGOs, the fire brigade and family
members. But the external help is effective only up to
the point where people can no longer endure the flood
water. Otherwise, people will be killed even with external help.

Nearby help?
YesGroup Evacuation

Figure 4. Modeling for evacuation in critical situation
B.Case Study
Hydraulic experiment
The Oike underground space in the center of
Kyoto city, Japan is used as the case area. The Kamo
River runs on its near east side. The Oike underground space is a structure of multiple stories including a shopping mall, a subway station concourse anda parking lot (B1F), another parking lot on the second
basement floor (B2F), and a subway platform on thethird basement floor (B3F) as shown in Fig.5. The
horizontal area of B1F and B2F is about 650 m*40
m and the B3F is about 100 m*8 m with the ceilingheight as 2.7 m. In this research, the hydraulic experiment data in the Oike underground space in Kyoto,
Japan is combined to indicate how a hazard progresses in the entire location. As explained in the paper byToda et al. (2005), the inundation flow is configured
by means of a 1/100 scaled hydraulic model where
the discharge of 100 m3/s overflows from the Kamo
River at the upstream site of Oike Bridge. This over-

III. VITAE SYSTEM BASED AGENT MODELING ANDSIMULATION
A.Agent modeling
Agent modeling is based on the behavioral understanding of underground evacuation in criticalsituations. The survivability is firstly calculated atevery simulation step. If the survivability is equal to
0 then it will lead to a failed evacuation. If not, themodel shows an image of how people try to survive.
The three functions in the Vitae System are integrated
37

YULING LIU, N. OKADA, DAYONG SHEN, SHUOQI LI

There are two types of agents: one is a static
agent including staircase, wall, corridor, exit sign,pole and high platform, and the other type is a moving agent like individual evacuees. The dynamic
developing flooding data is linked to static agents as
attributes.
Initial settings and parameters
The spatial unit is a 2 m x 2 m grid. The simulation unit is an individual evacuee. The initial locationand inherent qualities of people like age are randomly
given to each individual. The health and mobility
status is assumed to be normal when the evacuee isgenerated. The height of an agent is set as 1.6 m andeach person occupies a 0.4 m × 0.4 m space, which is
the typical size of each person’s space (Burstedde C.
et al., 2001).
In the simulation, the parameters include sensibility (%) representing the proportion of evacueeswith sensibility, evacuation timing (minutes) after theinundation, number of evacuees for each story andage structure of evacuees (%). The evacuation startingtime as a parameter makes it possible for the simulation to start from any situation such as the beginningof the inundation, appearance of an inescapable staircase, or water depth over the upper limit of walking
capability.

Figure 5. Structure of the Oike underground space inKyoto

flow may occur due to a 100-year flood in the Kamo
River basin. It is found that when the inundation
flow invades a multi-storied underground space, theinundated area spreads rapidly, and the water depth
rises very quickly. On the subway platform on B3F,
the water depth has a rapid rise from 15 minutes to 20
minutes after the inundation. It is critically dangerous
since the staircase in the escape route is impassable inthis case. The data is 30 minutes long with intervalsof 1 second. Given the same physical settings in the
Oike underground space, we extract the hydraulicdata at 1 minute intervals (0 s, 60 s etc). The evacuation simulation step is set as 2 seconds.
Agent typeFigure 6. Interface of Vitae System based evacuation simulation system

38

AGENT-BASED FLOOD EVACUATION SIMULATION OF LIFE-THREATENING CONDITIONS USING VITAE SYSTEM MODEL

Simulation and results
Based on KKMAS, a Multi-Agent Simulator provided by Kozo Keikaku Engineering Inc., anevacuation system was developed for the case areaof the Oike underground space in Kyoto, Japan. The
simulation interface is shown in Fig. 6. It has three
independent but connective spaces. B1F left and B1F
right represent the space of B1F, and B2F right andB2F left represent the space of B2F. The staircases in
B3F connect directly to B1F. Some staircases in B2F
connect with B1F and some of them directly lead tothe ground surface. A similar arrangement also existsin B1F.
The hydraulic experiment shows that the water
depth reaches a level close to the threshold of 0.3 m
around 15 minutes after the inundation. Therefore, we
set the evacuation starting time from 15 minutes to
30 minutes. The evacuation under critical condition
is considered applicable to a small number of people.
For this reason, the total evacuees are set as 5 evacuees in B3F with the age structure being 20% child,
60% adult and 20% senior. We assume that 100% of
people have sensibility and there is no external help
within the time period that people could sustain theflood.
Liu et al. (2010) demonstrated the effectivenessof the adaptive evacuation strategy. In this paper, thefocus is given to the influence of the facility layout on
evacuation. The following three scenarios of configuration were conducted: one is the standard arrangement near the staircase; the second case is the left cornered arrangement and the third case is the scattered
set in B3F.
㻱㼚㼐㼡㼞㼕㼚㼓㻌㼠㼕㼙㼑㻔㻿㼑㼏㼛㼚㼐㻕㻡㻜㻜㻱㼢㼍㼏㼡㼑㼑㼟㻌㼡㼟㼕㼚㼓㻌㼂㻿㻌㻸㼛㼓㼕㼏㻢As shown in Fig. 7, the result of enduring timeshows that it is almost the same for the case of standard setting and scattered setting. However, enduring time is shorter for the case of left corner setting
because the staircase is located in the center and rightside of the B3F space. Due to the rapid rise of water
depth and the distance from the staircase to the provisional shelter, some evacuees were unable to reachthe instinctive shelter.
“Evacuees using Vitae System (VS) logic” means
the number of people who evacuate in an adaptableway. As shown in Fig. 8, there is a rapid rise from 15
minutes to 20 minutes after the flooding for the caseof standard setting and scattered setting, which meansthat more and more people have to take adaptive actions according to the situation in which survival isstill possible. For the case of the left corner, the rapid
trend stops at 16 minutes after the flooding and afterthat decreases until 20 minutes. The common element is that once people evacuate 21 minutes after
the flooding, those instantaneous shelters cannot help
evacuees since shelters will be submerged by the torrent, which makes them invisible to evacuees. The
simulation results illustrate the applicability and limitation of the adaptive strategy developed in the current research.
In addition, the simulation provides a clue for the
rescue team to judge whether they will arrive in time.
For example, if a person evacuates 15 minutes after
the flooding, then his or her enduring time is about
450 s. If the rescue team arrives after that, the person
will likely be already dead.

㻞㻥

㻞㻣

㻞㻡

㻞㻟

㻜

㻞㻝

㻝

Figure 8. Simulation results for “evacuees using VS
logic”

㻝㻜㻜㻝㻥㻞㻱㼢㼍㼏㼡㼍㼠㼕㼛㼚㻌㻿㼠㼍㼞㼠㼕㼚㼓㻌㼀㼕㼙㼑㻔㻹㼕㼚㼡㼠㼑㻕

㻞㻜㻜

㻝㻣

㻟

㻝㻡 㻝㻢 㻝㻣 㻝㻤 㻝㻥 㻞㻜 㻞㻝 㻞㻞 㻞㻟 㻞㻠 㻞㻡 㻞㻢 㻞㻣 㻞㻤 㻞㻥 㻟㻜

㻟㻜㻜

㻝㻡

㻠

㻿㼠㼍㼚㼐㼍㼞㼐㻌㻭㼞㼞㼍㼚㼓㼑㼙㼑㼚㼠㻸㼑㼒㼠㻌㻯㼛㼞㼚㼑㼞㻿㼏㼍㼠㼠㼑㼞㼑㼐㻌㻌㻿㼑㼠㻜㻿㼠㼍㼚㼐㼍㼞㼐㻌㻭㼞㼞㼍㼚㼓㼑㼙㼑㼚㼠㻸㼑㼒㼠㻌㻯㼛㼞㼚㼑㼞㻿㼏㼍㼠㼠㼑㼞㼑㼐㻌㻌㻿㼑㼠㻠㻜㻜㻡㻱㼢㼍㼏㼡㼍㼠㼕㼛㼚㻌㻿㼠㼍㼞㼠㼕㼚㼓㻌㼀㼕㼙㼑㻔㻹㼕㼚㼡㼠㼑㻕

Figure 7. Simulation results for “enduring time”

39

YULING LIU, N. OKADA, DAYONG SHEN, SHUOQI LI

IV. CONCLUSIONSREFERENCES[１]

As an application of the Vitae System Model indisaster evacuations, the Vitae System provides a newperspective for the evacuation simulation particularly
for life-threatening situations. The integration of threefunctions in the Vitae System helps to interpret theevacuation strategy for disasters including but notlimited to an underground flood. Based on this logic,
an elementary model was proposed and a multi-agent
based evacuation simulator was developed combining
the hydraulic experiment data for the case of the Oike
underground space in Kyoto, Japan. The simulation
result shows the effectiveness and limitation of theadaptive evacuation strategy developed in the current
research. It reveals the need to develop more in-depth
knowledge on the adaptive and feasible strategies
to cope with sudden critical situations and pass theknowledge to people in order to build their adaptive
capability.
There is a need to extend the above modelthrough a systematic analysis of life-threatening situations by incorporating more water characteristics(e.g. flow velocity and experiment results of humanstability in water) and people’s vulnerabilities (e.g.
mobility, health status). Physical and psychologicalexperiments plus literature survey in related fields forvitality change, and empirical and physical interpretation of communication mechanisms are also requiredfor information classification, sharing and transfer.
These issues will be addressed in our future research.

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ACKNOWLEDGMENT

America, 99:7195-196.
[10]

We are grateful to Kozo Keikaku Engineering
Inc. for providing research-oriented use of KKMAS.
We are also grateful to Prof. Keiichi Toda, at Kyoto
University, Prof. Taisuke Ishigaki at Kansai University and Mr. Kawanaka, PhD student at Kansai University, Japan for sharing hydraulic experiment dataon the Oike underground space.

Liu Y.L., Okada N., Shen D.Y. and Li S.Q., Vitae System Based Agent Modeling and Simulation of Lifecritical Evacuation in Underground Flooding, Proceedings of the 2010 IEEE International Conference on
Systems, Man, and Cybernetics, Istanbul, Turkey October 2010 (Accepted).

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