Nowadays, most of the countries around the world encounter affect of disasters. Disaster can occur anytime and anywhere, without giving any alarm or message. During the disaster, the rapid response and recovery activities are critical issues to save lives and properties. The effective response actions play vital role in the disaster situation because the large amount of properties and valuable lives are depending on it. But, the rescue teams and emergency organizations have many problems and delays to give the effective response to the victim areas. To reduce the risk and damage, identifying the best evacuation routes for the recuse teams is vital. The proposed system provides not only the recuse teams which locate near the victim area but also the best evacuation routes to move people from the hazard place to the safe places. This paper describes a web-based application for the best evacuation route assessment during natural disaster

Phyo, K-zin

Sein, Myint Myint

English

Proceedings of the Asia-Pacific Advanced Network

Proceedings of the APAN – Research Workshop 2017
ISBN 978-4-9905448-7-4
 
Abstract— Nowadays, most of the countries around the world 
encounter affect of disasters. Disaster can occur anytime and 
anywhere, without giving any alarm or message. During the 
disaster, the rapid response and recovery activities are critical 
issues to save lives and properties. The effective response actions 
play vital role in the disaster situation because the large amount 
of properties and valuable lives are depending on it. But, the 
rescue teams and emergency organizations have many problems 
and delays to give the effective response to the victim areas. To 
reduce the risk and damage, identifying the best evacuation 
routes for the recuse teams is vital. The proposed system provides 
not only the recuse teams which locate near the victim area but 
also the best evacuation routes to move people from the hazard 
place to the safe places. This paper describes a web-based 
application for the best evacuation route assessment during 
natural disaster.
Index Terms— Best evacuation route assessment, disaster 
situation, effective response.
I. INTRODUCTION
Over the past years, almost countries around the world 
have suffered many disasters including flood, hurricanes, 
earthquakes, landslide, fire, etc. These can cause huge damage 
for people and loss a large amount of properties. The effective 
emergency response systems are essential to reduce the large 
amount risk by natural disaster. Today, all of the countries 
struggle and emphasize to recover and response the hazardous 
areas immediately. To give the effective response actions, 
emergency response system are needed to identify the risky 
area directly, provide the services or rescue teams located 
close with the victim location and the best evacuation route to 
go safe place.
In Myanmar, the major natural disaster such as floods, 
earthquakes, tsunamis, cyclones and landslides have been 
25th June 2017
“This work was supported in part by the University of Computer Studies,
Yangon”
K-zin Phyo is with the Geographical Information System Lab., University of
Computer Studies, Yangon, Myanmar. (e-mail:kzinphyo@ucsy.edu.mm)
Prof. Myint Myint Sein is with the Head of Geographical Information System
Lab., University of Computer Studies, Yangon, Myanmar. 
(email:myintucsy@gmail.com)
occurred. The impact of Cyclone Nargis that occurred in 2008 
affected 2,400,000 people left 138,000 fatalities and estimated 
damage cost of US$4,000,000 to Myanmar. During this 
disaster situation, emergency rescue teams have some 
difficulties to give the effective operations of evacuation in 
time. To overcome the difficulties during natural disaster, the 
best evacuation route estimation is developed and tested. The 
main goal is to evacuate the people from the disaster area to the 
safe area in the situation of earthquake or flood.
In the case of any disaster, it is the most important to make 
respond and recovery actions and reach the victim area in time. 
Many researches and previous researches were carried in the 
application of exiting studies for route guidance systems. 
Urban fire is a violent problem for both the developing and 
developed countries. For effective firefighting, GIS based 
effective route discovery system for fire event is developed by 
using Dijkstra’s Algorithm and the system is implemented 
base on the landmarks of the tested region [1].The bus route 
information system for public transportation is developed to 
calculate the shortest route by using A* algorithm. This system 
provides the shortest route and bus number with information of 
public bus transport for Yangon Region [4-6]. R. Fadlalla, et 
al. [7] proposed the system for producing the digital route 
guided maps and improving services in case of emergencies 
such as accidents. They had been done by utilizing the 
capabilities of GIS in network analysis and visualization to 
enhance decision making in route selection to the nearest 
hospital by mapping the services area based on travel time.
Route Analysis for Decision Support System is suggested to 
find shortest route between one facility to another at the time 
of disaster situation [8]. The research part of this work will 
comprise of Geographic Information Systems (GIS) 
technologies, GIS Web services and how these interact with 
each other. The problem of finding the best evacuation route 
along road network is a main issue in the effective route 
navigation system. In this paper, best evacuation route 
assessment to provide effective migration processes in disaster 
situation is developed and tested.
II. BACKGROUND THEORIES
In many route finding processes, the road network is 
considered as the graph, the locations or points of interest are 
nodes or vertices, the connection between the locations are the 
edges and the distance between nodes are regarded as weight 
Effective Evacuation Route Strategy during 
Natural Disaster
K-zin Phyo and Myint Myint Sein
value. Most of the graphs that represented the road networks 
consisted of millions of nodes and edges. When the size of 
road network is growing, the route finding processes take a 
large amount of time and the accuracy of algorithm becomes 
more difficult to measure. To solve the path finding problems, 
the shortest path algorithms are used and it might not be a 
simple task to find on large graphs. In fact, the path finding 
algorithm must respond the shortest path result with high 
accuracy. The optimal path finding algorithms are usually used 
in many researches and can be seen in a lot of applications used 
in our daily life. In this paper, modified Dijkstra’s algorithm is 
proposed to improve the accuracy in route finding process.
Dijkstra’s algorithm computes the shortest paths from the 
start node to all other nodes in the graph. The main weakness 
of this algorithm is that it traverses through all nodes in the 
graph. So, it takes much iteration and consumes a lot of time. 
Generally, the shortest path algorithm must produce the result 
as fast as possible. Dijkstra’s Algorithm can find the shortest 
path of the road network, but does not consider the road 
condition. To avoid the close and one-ended road, the new 
variable n_state is added to the algorithm. To reduce the 
memory usage and processing time, the new condition d[n] 
== ∞ is added to original code. The proposed method is 
developed to reduce the visited number of nodes which are not 
reached from source node. It is intended to improve the 
performance of the algorithm and to reduce the consumption of 
memory space. In this work, Modified Dijkstra’s is used to 
find the optimal route for emergency vehicles. The pseudo 
code of proposed algorithm is described as follow:
function MD(G,source,destination)
int n_state;
d[source]:=0;
q:=the set of all nodes in G;
while q is not empty:
n := vertex in Q with minimum distance in d[ ] ;
if n_state= =1
remove u from q ;
else if d[n] == ∞ || n_state == 0:
break ;
end if
end if
for each neighbor v of n
temp_d := d[n] + d_between(n, v) ;
if temp_d < d[v]:
d[v] := temp_d ;
previous[v] := n ;
decrease-key v in q;
end if
end for
end while
return d[destination];
In route finding processes, the proposed method will 
eliminate the nodes which are not reached from the source 
node and the nodes with state value ‘0’. By applying this 
method in optimal route calculation, the number of iteration 
time will reduce and the performance of the algorithm will 
increase and the consumption of memory space will decrease 
significantly. 
Computing the distance between locations is an important 
part of many researches which are related with geographical 
information system. In order to calculate the distance between 
two locations, two geographical coordinates are required. The 
appropriate method for distance calculation will depend on the 
objectives of the study, the nature of the data, and the type of 
coordinates. To calculate the distance on the spherical shape, 
the main issue is to account for the curvature. On the flat 
surface, calculating the distance between points is simple. The 
haversine formula is an appropriate equation to calculate 
distance between two points in navigation. It gives great-circle 
distances between two points on a sphere from their longitudes 
and latitudes and uses a constant r that represents the radius of 
the Earth.
 The earth curvature, Haversine formula is described as follow:
𝑑 = 2𝑟arcsin ( 𝑠𝑖𝑛(𝜙1 ‒ 𝜙22 )2 + 𝑐𝑜𝑠(𝜙1)𝑐𝑜𝑠(𝜙2)𝑠𝑖𝑛(𝜆1 ‒ 𝜆22 )2)
                                                                                                                                                        (1)
In above formula, r is the radius of the Earth and d is the 
distance between two points with longitude 𝜆1 ,𝜆2 and latitude 
μ1, μ2 respectively.
 
III.GENERAL ARCHITECTURE
Routing applications on urban road networks for vehicles 
are so useful in daily life. Effective evacuation planning and 
well structure road network are the essential component in 
disaster situation. Transportation of road network is required to 
search and rescue operation, to deliver the emergency supplies 
and services, to carry and move the victims from the collapsed 
shelters in case of disaster etc. Such strategies can save lives, 
decrease sufferings, and provide substantial savings and 
benefits to humanity. The general architecture of effective 
evacuation route response system is shown in Fig. 1. This 
system will provide the evacuation route not only for the 
people who needed to move from the risk place to safe place 
but also for the emergency vehicles to go the hazard place to 
save lives and properties in time.
Fig.1. General Architecture
IV.SYSTEM DESIGN AND DATA CREATION
Fig.2. System Overview
The proposed system is intended to provide the best 
evacuation route for people and emergency vehicles during 
disaster situation. According to the complex structure road 
network and absence of best evacuation route guiding system, 
there are many difficulties in many developing countries. Road 
network transportation is important for evacuation processes, 
to provide the emergency facilities, to bring and transport the 
people from the disaster affected area to the safe places. To 
save valuable lives and properties, the emergency vehicles are 
needed to reach to the hazard area as fast as possible. Effective 
respond actions and evacuation processes are a vital role 
during natural disaster. The proposed system will provide the 
hazard location and close services discovery components and 
the best evacuation route calculation by using our proposed 
modified method. Overview of proposed system is described 
in Fig.2. 
The data of road network, emergency services locations and 
damaged locations are prepared and stored in the database. The 
data used in this system are collected from related emergency 
service departments of Yangon Region, Google Map and GPS 
GARMIN etrex-10 device. The number of 41 fire stations, 47 
police stations and 80 medical services are collected and used 
for emergency services location points. The sample data of 
emergency services are describes as sample in Table 1 with 
related geolocation. Table 2 shows the example data for 
incident location identification. In this work, the street names 
are used as address. The road network table is created to 
calculate the optimal route. Sample data creation of road 
network is shown in Table 3.
Table 1. Emergency Services Location
Emergency Service Name Latitude Longitude
Dagon Seikkan Fire Station 16.845701 96.265748
Hlaingtharyar_B Fire Station 16.875918 96.068839
Mingalardon Fire Station 17.046965 96.140114
South Dagon Fire Station 16.854688 96.223212
North Dagon Fire Station 16.959331 96.295907
Shwepyithar Fire Station 16.97397 96.076451
Thaketa_B Fire Station 16.807593 96.21824
Shwpaukkan Fire Station 16.928111 96.184485
Rose Hill Hospital 16.809522 96.155364
Thaketa Hospital 16.805619 96.217417
La Gabar Hospital 16.901581 96.160019
Min Ga Lar Don Hospital 16.921114 96.133447
Kan Thar Yar Hospital 16.841681 96.203544
Yangon General Hospital 16.778903 96.148975
Orthopedic Hospital 16.819436 96.122583
Workers' Hospital 16.797989 96.172372
Yangon University Hospital 16.825747 96.134581
Yangon Children Hospital 16.788158 96.136464
Bayint Naung Police Station 16.864288 96.101723
Pazundaung Police Station 16.7786903 96.1719782
Pabedan Police Station 16.7753184 96.154622
Thingangyun Police Station 16.830411 96.186589
Thuwunna Police Station 16.847473 96.186586
Botahtaung Police Station 16.7715459 96.1726236
Mingalar Taung Nyunt  
Police Station 16.796389 96.152754
 
Table 2. Location Identification Sample Data
Id Street Name Latitude Longitude
1 Myanandar 1st 16.847820 96.11723
2 Myanandar 5th 16.852990 96.11611
3 Myanandar 6th 16.852390 96.11975
4 Myanandar 7th 16.852165 96.12692
5 Myanandar8th 16.851607 96.12282
6 Gantgaw 2nd 16.842031 96.12482
7 Gantgaw 3rd 16.842573 96.12632
8 Gantgaw 4th 16.842783 96.12641
9 Gantgaw 5th 16.843318 96.12559
10 Gantgaw 7th 16.844727 96.12531
11 Gonnisetyone 16.851136 96.12499
12 Hlaing Buter Yone 16.837112 96.12665
13 Hlaing Sabal 16.849316 96.11772
14 HlaingYandanar Mon 16.853857 96.11433
15 Htantapin 16.833965 96.11413
16 Kan 16.838037 96.11939
17 Kha Poung 16.838654 96.11588
18 KhaYae 16.846591 96.12651
19 KhaYae 3rd 16.846747 96.12648
20 Khine Shwe War 16.832765 96.11248
21 Padauk Shwe War 1 16.837185 96.12227
22 Padauk Shwe War 2 16.837070 96.12197
23 Padauk Shwe War 3 16.837026 96.12164
24 Padauk Shwe War 4 16.83735209 96.12113
25 Paday Tha Yazar 16.87641512 96.17377
Table 3. Sample Data for Route Calculation
From_Node To_Node Distance
21 23 8
21 17 32
22 25 85
23 21 8
23 22 35
24 34 40
24 23 140
25 19 42
26 25 34
27 82 114
28 39 29
29 33 74
30 22 8
31 33 83
32 33 41
34 32 96
35 13 49
37 38 256
38 36 42
40 41 116
41 37 44
42 754 81
43 367 123
44 28 152
45 44 42
V. SYSTEM IMPLEMENTATION
The research work is implemented and tested on the 
Yangon Region.
Fig.3. Emergency Services Locations in Tested Region
Fig.4. Damage Location Identification
Fig.5. Defining the Close Emergency Services
Fig.6. Showing Best Evacuation Route
The road network of Yangon Region consisted of the 
number of edges 87038 and the number nodes 27852. Fig.3 
shows the emergency service locations in the tested region. 
The location identification of victim area is shown in Fig. 4 
and the close services which locate near the victim area is 
illustrated in Fig. 5. The evacuation route to move people from 
disaster to go safe place or the optimal route to save people by 
rescue team is show in Fig. 6.
VI.SYSTEM EXPERIMENT
The effectiveness of the proposed work is tested by 
calculating on the road network of Yangon region with the 
number of edges 87100 and the number nodes 27900. The 
performance of the proposed method is compared with 
traditional Dijkstra’s algorithm to prove the improved 
efficiency of its. The performance evaluation of the two 
algorithms is calculated by comparing processing time as 
shown in Fig. 7 and the number of visited nodes as described in 
Table 8.
Fig. 6. Comparison of two methods in processing time
Table 4: Comparison of two algorithms in visited nodes
Proposed Algorithm Dijkstra’s Algorithm
10 25
20 36
30 45
40 61
50 92
100 137
VII.CONCLUSION
The proposed work is discussed and developed to solve 
the problems faced by the emergency rescue teams during 
natural disaster. It provides to verify the precise location of 
disaster area, to know the emergency rescue teams which 
located near the victim area and the optimal evacuation routes 
to transport people from the hazard location to the safe places. 
This system can give the significant help to the emergency 
rescue teams by supporting the best route to go the disaster 
location in time. It must improve the evacuation processes and 
recovery actions with effectively and efficiently. As future 
plan, the proposed work is advanced as mobile application 
according to be used in the world wide.
REFERENCES
[1] K.Phyo and M.M.Sein , “Effective Emergency Response System by 
Using Improved Dijkstra‟s Algorithm,” 14th International Conference 
on Computer Applications, ICCA-2017, Yangon, Myanmar.
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Region”, 12th International Conference on ComputerApplications, 
ICCA-2015, Yangon, Myanmar. 
[3] M.T.Zar and M.M.Sein, "Finding Shortest Path and Transit Nodes in 
Public Transportation System", the 9th InternationalConference on 
Genetic and Evolutionary Computing, ICGEC- 2015, Yangon, 
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[5] N. Kumar, M. Kumar and S. Kumarsrivastva,” Geospatial Path 
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[7] V.Bhanumurthy, Vinod M Bothale, Brajesh Kumar and NehaUrkude, 
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[8] R. Fadlalla, A. Elsheikh, A. Elhag, S. EddeenKhidirSideeg and A. Elhadi 
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1,pp.50-57. 
K-zin Phyo was born in Kyaiktho, Mon 
State, in 1988. She received B.C.Sc 
(Hons:) degree from Computer University, 
Mawlamyine , Myanmar in 2009 and 
M.C.Sc degree from the Computer 
University, Mawlamyine , Myanmar in 
2011. She is currently working towards the 
Ph.D. Degree at the University of 
Computer Studies, Yangon, Myanmar. Her research interests 
are Image Processing, Geographical Information System, 
Spatial Database and Android Applications. She is a student 
member of IEEE.
Myint Myint Sein received the Ph.D in 
Electrical Engineering from the Graduate 
School of Engineering, Osaka City 
University, Osaka, Japan in 2001. She 
joined the Kehanna Human Info 
Communication Research Center, Kyoto, 
Japan as a post doctor researcher, research 
fellow. She is presently serving as a Head 
of Geographical Information System Lab., University of 
Computer Studies, Yangon, Myanmar since 2005. Her research 
interests are Pattern Recognition, Image Processing, Soft 
Computing, 3D Reconstruction, 3D Image Retrieval, GIS and 
Android Applications. She is a member of IEEE.


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