Indonesian Journal of
Electrical
Engineer
ing and
Computer Science
V
o
l. 10
, No
. 3, Jun
e
20
18
, pp
. 87
5
~
88
2
ISSN: 2502-4752,
DOI: 10.
11591/ij
eecs.v10
.i3.pp875-882
8
75
Jo
urn
a
l
h
o
me
pa
ge
: http://iaescore.c
om/jo
urnals/index.php/ijeecs
Analysing Vehicu
lar Congesti
on Scenario in Kual
a L
u
mpur
Using Open Traf
fic
Muh
a
mm
ad
Al
i
,
S
aar
gu
na
w
a
th
y Ma
no
g
a
ra
n, Ka
mal
u
di
n
M
o
h
a
m
a
d
Yus
o
f,
Muha
mma
d
Ra
mdha
n Muha
mma
d
Suha
ili
Advanced Telecommunications Techno
log
y
Res
earch
Group, Faculty
of
Electrical
Engineering
,
Universiti
Tekno
logi
Malay
s
ia (UTM), Skudai, 81310
,
Johor, Mala
y
s
ia
Article Info
A
B
STRAC
T
Article histo
r
y:
Received Ja
n
9, 2018
R
e
vi
sed M
a
r
2,
2
0
1
8
Accepted
Mar 18, 2018
Traffic cong
estion on the ro
ads is mainly
the r
e
sult of over
c
rowd
ing and th
is
phenomenon happens when a great numbe
r o
f
vehicles storm the road,
resulting in the disruption
of
the
smooth
traffi
c f
l
ow. Th
is gre
a
tl
y
affe
cts t
h
e
dail
y rou
tines of
the p
e
ople
.
Not
to m
e
ntion
the
tim
e tha
t
is wast
ed while
a
person feels st
randed in such
situation and
it results in
the loss of
productivity
,
als
o
deterio
r
ates th
e societ
al b
e
hav
i
or to a certain
exten
t
and
have adverse ef
fects on the economy
.
The n
a
tural calamities add to the
m
i
series. It be
c
o
m
e
s ver
y
diff
i
c
ult to m
a
n
a
ge
the tr
affic f
l
ow in situat
ions
when there
are
flash floods or other a
ccid
e
nts. Therefor
e the
trend of the
traffic seems ver
y
unpred
ictable.
The real-time information and the pas
t
data are deemed as the si
gnificant inputs for
the pr
edictiv
e an
alysis. Moder
n
da
y
res
e
arch
ers
perform
the predictiv
e ana
l
y
s
is
us
ing the s
i
m
u
l
a
tions
as
it
does not seems to have an
y
accurate a
nd exact predictive model, main
ly
becaus
e
of th
e hi
gher com
p
lex
i
t
y
and th
e perp
lexi
ng s
ituat
ion th
e r
e
s
earch
er
s
face whi
l
e perfo
rm
ing the anal
ys
is
. Open Traff
i
c
s
eem
s
to be a viable opt
ion
,
as
it is
an open s
ource and
can b
e
linked wi
th th
e Open S
t
ree
t
. T
h
is
res
earc
h
targets to stud
y
and understand the Open
Traffic
platform. In
this
regard
th
e
real-
tim
e tr
affi
c
flow pat
t
ern
in
Kuala
Lum
pur
area
was
s
u
cc
es
s
f
ull
y
be
en
extra
c
ted and t
h
e anal
ys
is
wa
s
perform
ed using Open Traff
i
c. It was
observed and deduced from
the results
that Kual
a Lum
pur faces congestion
on ever
y
major
avenue, junction
or inters
ect
ion i
t
m
o
s
t
l
y
owes
to the offices
and the econo
mic and commercial ce
nters during the peak
hours. Some
avenues exper
i
ence the
congesti
on problem du
e to the tourism.
K
eyw
ords
:
Ope
n
Street
M
a
p
O
p
en
T
r
af
f
i
c
Traffic fl
ow analysis
Co
ng
estion
Copyright ©
201
8 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
i
ng
Autho
r
:
M
uham
m
ad Al
i
,
Ad
va
nced
Tel
e
com
m
uni
cat
i
ons Tec
h
nol
ogy
R
e
searc
h
Gr
o
u
p
,
Facu
lty of Electri
cal Engineering,
Un
i
v
ersiti Tekn
o
l
o
g
i
Malaysia (UTM),
Sku
d
a
i, 813
10
, Joh
o
r
,
Malaysia
1.
INTRODUCTION
Th
e m
o
st v
i
sib
l
e an
d
frequ
en
t
l
y h
i
g
h
lig
h
t
ed
p
r
ob
lem o
f
a city
is its
traffic co
ng
estion
,
and
it is well
kn
o
w
n
t
h
at
hi
gh
l
e
vel
s
o
f
c
o
n
g
est
i
o
n c
r
ea
t
e
si
gni
fi
cant
i
m
pact
on l
o
cal
an
d
nat
i
o
nal
GD
P.
The
r
e i
s
a
hu
ge
im
pact
on en
vi
ro
nm
ent
and t
h
e soci
et
y
due
t
o
t
h
e pr
obl
e
m
s rel
a
t
e
d t
o
trans
p
ort
a
t
i
o
n.
It
has a seri
o
u
s
t
o
l
l
o
n
th
e qu
ality of l
i
fe and
urb
a
n
produ
ctiv
ity. Some o
f
t
h
es
e imp
acts in
cl
u
d
e
co
ng
estion
,
en
erg
y
con
s
u
m
p
tio
n
,
ai
r
p
o
llu
tion
,
un
con
t
ro
lled
m
o
to
ri
zatio
n
,
m
o
b
ility o
f
urb
a
n
po
or,
d
i
sab
l
ed
an
d
sen
i
or citizen
an
d traffic safety.
The c
o
n
g
est
i
o
n i
s
pe
rha
p
s t
h
e
m
o
st
vi
si
bl
e m
a
ni
fest
at
i
on
of t
h
e
seri
es
of
fai
l
u
res i
n
t
h
e
pl
an
ni
n
g
o
f
ur
ba
n t
r
a
n
sp
o
r
t
a
t
i
on a
nd i
t
al
s
o
has
qui
t
e
a si
gni
fi
cant
c
o
st
.
For
exam
pl
e, I
N
R
I
X re
p
o
rt
e
d
, t
h
at
t
h
e c
o
m
b
i
n
ed
an
nu
al co
st of
g
r
i
d
lo
ck
to
UK, Fr
an
ce, G
e
r
m
an
y and
U
S
is
ex
p
ected
to r
i
se to
$29
3.1 b
i
l
lio
n
b
y
20
30
,
w
h
ich
i
s
an ob
vi
o
u
s i
n
crease
of
50
% fr
om
2013
[1]
.
C
o
nsi
d
e
r
i
ng t
h
i
s
e
n
t
i
r
e peri
od
, t
h
e co
m
b
i
n
ed cost
cause
d by
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
502
-47
52
I
ndo
n
e
sian
J Elec Eng
& Com
p
Sci, V
o
l. 10
,
No
.
3
,
Jun
e
2
018
:
87
5 – 88
2
87
6
co
ng
estion
fo
r
th
e related econ
o
m
ies is estimated
to
b
e
a
stag
g
e
ring
$4
.4
trillio
n [1
].
Th
e
U.S ex
p
e
rien
ces a
g
r
eatest
o
v
e
rall eco
no
m
i
c i
m
p
act, wh
ere the esti
m
a
ted
cu
m
u
la
tiv
e co
st
o
f
traffic con
g
estio
n
will b
e
$
2
.8
trillio
n
b
y
2
030
-wh
i
ch
is th
e sam
e
th
at was
p
a
id
as
tax
e
s by th
e A
m
erica
n
s a year b
e
fo
re. Howev
e
r the UK
(at 6
6
%) an
d
Lo
ndo
n
(at 71
%) will see
th
e greatest an
nu
al rise in
th
e co
st
o
f
co
ng
estion
b
y
2
030
, m
a
in
l
y
d
u
e
t
o
t
h
e rapi
d u
r
bani
zat
i
o
n ex
p
e
ri
ence by
t
h
e
regi
o
n
.
At
t
h
e i
ndi
vi
dual
l
e
vel
,
t
r
af
fi
c co
nge
st
i
on c
o
st
dri
v
es
$1,740 last ye
ar
on ave
r
a
g
e
acros
s th
e
f
o
ur
co
unt
ri
es.
If
u
n
chec
ke
d,
t
h
i
s
num
b
er is e
x
pected to
grow m
o
re
th
an
60
% t
o
$
2
,90
2
annu
ally b
y
203
0 [1
].
B
e
si
des t
h
e
h
uge
am
ount
o
f
ene
r
gy
co
ns
u
m
ed by
t
h
e t
r
ans
p
o
r
t
a
t
i
on
i
n
dust
r
y
,
t
h
e m
o
t
o
r
ve
hi
cl
es
co
n
t
ribu
te m
o
re to
wards th
e air po
llu
tion
phen
o
m
en
on
.
Wh
en foc
u
se
d on
city centers, the concerne
d agencie
s
reveale
d
that, the city centers are responsible for 90
t
o
95
perce
n
t
of
t
h
e carb
o
n
m
o
no
xi
de
, d
u
e t
h
e hu
ge
am
ount
of tra
f
fic experience
d by these a
r
e
a
s. In additio
n to this, the traces of
80
to 90 perc
ent
of nitroge
n
oxi
des an
d
hy
dr
ocar
b
o
n
s
, an
d a l
a
rge
p
o
rt
i
on
of t
h
e pa
rt
i
c
ul
at
es, p
o
se a
m
a
jor t
h
reat
t
o
h
u
m
a
n heal
t
h
a
n
d
nat
u
ral
reso
u
r
c
e
s. Lead em
i
s
si
ons f
r
o
m
t
h
e
com
bust
i
on
of
leaded ga
soli
ne also ca
use
an estim
a
ted 80 to 90
p
e
rcen
t
o
f
lead
in am
b
i
en
t air.
Owi
n
g
to th
is issu
e
m
a
ny
dev
e
l
o
ped
c
o
u
n
t
r
i
e
s
ha
ve
st
art
e
d t
h
e
pra
c
t
i
ce o
f
redu
cing
th
e
gaso
lin
e lev
e
l fro
m
th
e fu
el, bu
t in
m
o
st o
f
th
e d
e
v
e
lop
i
ng
co
un
tries, a certain
o
l
d
trait is yet
bei
n
g f
o
l
l
o
wed
.
These em
i
ssions
ha
ve an al
arm
i
ng gl
o
b
al
as well as a local im
pac
t: Th
e tran
sp
ortation
sector
i
s
t
h
e m
o
st
rap
i
dl
y
gr
o
w
i
n
g s
o
u
r
ce
of
g
r
ee
n
h
o
u
se
gas
em
i
s
si
ons
t
h
at
i
s
,
e
m
i
ssi
ons
of c
h
em
i
cal
s t
h
at
have t
h
e
pot
e
n
t
i
a
l
t
o
co
nt
ri
b
u
t
e
t
o
gl
o
b
al
wa
rm
i
ng. Nar
r
o
w
i
n
g C
O
2 em
i
ssi
on fr
o
m
t
r
ansp
ort
se
ct
or i
n
So
ut
he
ast
Asi
a
,
M
a
l
a
y
s
i
a
i
s
secon
d
l
a
rge
s
t
p
e
r ca
pi
t
a
g
r
ee
nh
o
u
se
gas
e
m
i
t
t
e
r am
ong
t
h
e
gr
ou
p
o
f
ASE
A
N
c
o
u
n
t
r
i
e
s [
8
]
.
Al
t
h
o
u
g
h
,
M
a
l
a
y
s
i
a
shares o
n
l
y
0.
3% of gl
obal
GH
G
em
ission t
h
e m
a
jor concern lies in the e
v
er i
n
creasing
t
r
en
d
of
G
H
G
em
i
ssi
on. M
o
st
o
f
t
h
i
s
o
w
es t
o
co
nge
st
i
o
n
sce
n
ari
o
.
Fu
el sub
s
i
d
ies, in
du
ction
of so
m
e
p
o
licie
s wh
ic
h
artifi
c
ially
lo
wer t
h
e prices of th
e fu
el, are
est
i
m
a
t
e
d t
o
cost
s a heft
y
am
ount
on t
h
e
go
ver
n
m
e
nt
and m
a
jor eco
nom
i
e
s arou
nd
t
h
e gl
obe
, a ro
u
g
h
esti
m
a
te
o
f
500
b
illio
n
d
o
llars was g
i
v
e
n
b
y
th
e ex
p
e
rts [3]. Besid
e
s ad
d
i
n
g
the surp
l
u
s
co
sts, fu
el subsid
ies
i
n
d
u
ces
seve
ra
l
ot
he
r
pr
o
b
l
e
m
s
whi
c
h
bri
n
g i
n
vari
ous
n
e
gat
i
v
e i
m
pact
s o
n
t
h
e ec
o
n
o
m
y
so
m
e
of
t
h
ese
i
n
cl
ude e
n
co
u
r
agi
n
g wast
ef
ul
energy
co
ns
u
m
pti
on, creat
i
ng fi
scal
b
u
r
d
ens o
n
de
vel
o
pi
n
g
co
unt
ry
bud
get
s
,
di
sp
ro
p
o
rt
i
o
nat
e
l
y
bene
fi
t
i
ng
weal
t
h
y
h
o
u
se
hol
ds,
an
d i
n
cr
easi
n
g
heal
t
h
a
n
d
en
vi
r
o
nm
ent
a
l
cost
s o
f
fuel
s.
Vari
o
u
s
effo
rts h
a
v
e
b
e
en
do
ne in
o
r
d
e
r to
mitig
ate
th
is issu
e. Differen
t sug
g
e
stio
n
s
h
a
v
e
b
een
g
i
ven
whic
h leads to a num
b
er
of a
p
proach
es
.
At
di
ffe
re
nt
pl
ace
s sens
o
r
s a
n
d
act
u
a
to
rs are in
stalled
to co
ll
ect th
e
data. Beside
s t
h
is, cam
eras are also
use
d
to find t
h
e
real time traffic fl
ow
Du
ri
n
g
t
h
e em
erge
ncy
si
t
u
at
i
o
n
,
t
h
e
beha
vi
or
of t
r
af
fi
c al
way
s
de
vi
at
es fr
om
t
h
e norm
and i
t
t
e
n
d
s
to
ch
ang
e
drastically in
o
t
h
e
r situ
ation
.
This b
e
h
a
v
i
o
r
resu
lts in th
e d
i
srup
tion
o
f
the traffic fl
o
w
. Thu
s
,
creates co
m
p
licatio
n
s
for th
e con
cern
e
d
d
i
saster m
a
n
a
g
e
men
t
au
tho
r
ities, to
carry
out th
e relief
operatio
ns
effectively. Traffic congestion is consi
d
ere
d
as a
m
e
n
ace which is unavoi
dable
during
fe
stive season and also
d
u
r
i
ng
ph
eno
m
en
on
su
ch
as, accid
e
n
t
s, f
l
oods and
etc
[
2
].
Using the
real-tim
e data to perform
the analysis
and
de
duct
i
o
n seem
s qui
t
e
an
u
phi
l
l
t
a
sk as t
h
e
traffic
de
viates from
the norm
drasti
cally. The
nature
of t
h
e tra
ffic
flow
in
Kuala L
u
mpur
follows t
h
e sam
e
t
r
en
d. The
r
ef
o
r
e, a sol
u
t
i
o
n sh
oul
d be s
u
g
g
es
t
e
d i
n
or
der t
o
cope
wi
t
h
t
h
e pr
o
b
l
e
m
.
Therefo
r
e, i
t
has be
en t
h
e
m
o
ti
vat
i
on i
n
t
h
e rese
arc
h
t
o
st
udy
a
nd t
o
c
o
l
l
ect
t
h
e r
eal-t
im
e traffic be
havior and a
n
al
yzing it with t
h
e hel
p
of
O
p
e
n
T
r
af
fic so
ftwa
re.
The
or
ga
ni
zat
i
o
n
o
f
t
h
e
pa
pe
r
co
nsi
s
t
s
o
f
5 s
ect
i
ons.
Sect
i
o
n
1
prese
n
t
s
t
h
e i
n
t
r
od
uct
i
o
n
of t
h
e
wo
r
k
.
A detailed
pre
f
ace of the problem
was discusse
d in the
section. Secti
o
n 2
prese
n
ts the literature revie
w
related to the platfo
rm
. Firstly
,
a re
vi
ew of
t
r
affi
c m
oni
t
o
ri
n
g
an
d t
r
affi
c analysis from other researchers i
s
descri
bed
.
I
n
sect
i
on 3, a
n
o
v
er
vi
ew
of t
h
e
Ope
n
Traf
fi
c sy
st
em
i
s
gi
ven. I
n
sect
i
on
4
,
t
h
e resul
t
an
d t
h
e
discussi
on bas
e
d
on the
dat
a
collected
from
the Op
en T
r
affic system
.
Section
5 c
oncludes
the
res
earch
fin
d
in
gs.
2.
RELATED WORKS
The c
o
nducted researc
h
take
s
account
of
di
ffe
rent as
pects
considered
by
othe
r resea
r
c
h
ers.
In t
h
e
fol
l
o
wi
n
g
s
u
b
sect
i
ons,
p
r
e
v
i
ous
w
o
rks
relat
e
d
to th
is
wo
rk are
rev
i
ewed.
2.1.
A Glimps
e at the Open
Traffic Platform
There
are
seve
ral challenges
being faced
by
the a
g
encies a
ll arounf the
wo
rl
d which are
concerne
d
with
th
e issu
e
o
f
traffic m
a
n
a
g
e
m
e
n
t
. So
m
e
o
f
t
h
ese ch
allen
g
e
s are
bu
t no
t li
m
ited
to
, th
e co
ng
estion
an
d
t
h
e
scarce res
o
urc
e
s. The
r
e is a
need to
m
o
n
ito
r th
e real ti
me traffic flow
, bearing in m
i
nd that the
r
e are no
effectiv
e too
l
s
av
ailab
l
e to mo
n
itor
real-time traffic fl
ow,
to c
o
llect and
analyze hi
stori
cal travel tim
e
data.
Owi
ng
t
o
t
h
ese
chal
l
e
n
g
es,
C
e
bu
C
i
t
y
Go
ver
n
m
e
nt
had c
o
m
e
up
wi
t
h
a
n
ope
n s
o
urce
pl
at
form
whi
c
h c
o
l
l
ect
s,
visulaizes and
analyzes the traffic data s
p
ee
d. T
h
e data
w
a
s deri
ved
fr
o
m
t
a
xi
dri
v
er
’s
ph
o
n
e. T
h
i
s
p
r
o
j
ect
Evaluation Warning : The document was created with Spire.PDF for Python.
In
d
onesi
a
n
J
E
l
ec En
g &
C
o
m
p
Sci
ISS
N
:
2
5
0
2
-
47
52
An
al
ysi
n
g
Ve
hi
cul
a
r
C
o
nge
st
i
o
n
Sce
n
ari
o
i
n
K
ual
a L
u
mp
ur
Usi
n
g
Ope
n
…
(
M
uh
a
m
m
a
d
Al
i)
87
7
won
Ph
ilipp
i
n
e
s Nation
a
l E-Go
v
e
rn
an
ce Com
p
et
itio
n
on
20
13
[4
]. Th
e tea
m
th
en
wen
t
o
n
to co
llaborate with
an AS
EA
N fa
m
ous t
a
xi
-hai
l
i
ng a
p
p cal
l
e
d “Gra
b Ta
xi
”,
w
h
i
c
h
gene
rat
e
s GPS
dat
a
an
d wi
t
h
C
o
nvey
a
l
wh
o i
s
an
ope
n s
o
urc
e
t
r
ans
p
ort
s
o
f
t
ware
de
vel
o
p
m
ent
con
s
ul
t
a
nt
t
o
fu
rt
he
r i
m
prove t
h
e i
n
i
t
i
a
l
devel
o
pm
ent
.
T
h
e
“
W
o
r
l
d
B
a
n
k
B
i
g Dat
a
C
h
al
l
e
nge
In
n
ovat
i
on
G
r
ant
”
was
al
so w
o
n by
t
h
em
. The p
r
o
j
ect
st
art
e
d i
n
J
a
nua
ry
and
s
u
ccessf
ul
l
y
com
p
l
e
t
e
d o
n
J
u
n
e
20
1
5
w
h
i
c
h
was
ar
ou
n
d
si
x m
ont
hs
[
4
]
.
2.2.
Arc
h
itecture of
the
Ope
n
Traffic Pl
atform
T
h
e c
o
m
pone
nt
s
of
Ope
n
Tra
ffi
c s
o
ft
ware a
r
e s
h
ow
n i
n
Fi
gu
re
1.
Tra
ffi
c E
n
gi
ne,
Tra
ffi
c
Dat
a
Po
ol
,
Ope
n
St
reet
M
a
p
(OSM
-l
i
n
ke
d)
Tra
ffi
c
Dat
a
Set
an
d R
eal
-tim
e Routing API a
r
e c
o
nsidered as
the
bac
k
bone
of the a
r
chitect
ure
.
Figu
re 1.
Com
p
o
n
e
n
ts of O
p
e
n
T
r
af
fic
S
o
ft
ware
2.
3.
T
r
a
ffi
c E
n
gi
ne
T
h
e
t
r
anslation
of
t
h
e
ve
hicle
loc
a
t
i
on, t
o
t
h
e O
S
M
l
i
nked
spe
e
d est
i
m
at
es, is do
ne
by
t
h
e
Traf
fi
c
En
gi
ne.
Tra
ffi
c En
gi
ne
i
s
l
o
cat
ed i
n
side
a fleet operat
or. T
h
e m
a
in ro
le
of th
e
Traffic En
g
i
n
e
is th
e
co
nv
ersion
o
f
real ti
m
e
GPS l
o
catio
n informatio
n
t
o
an
insig
h
t
ab
le traffic
statistics.
Thi
s
bl
oc
k gu
ara
n
t
ees
t
h
e
suret
y
t
h
at
t
h
e
fet
c
he
d
dat
a
,
fr
om
t
h
e dat
a
pr
ovi
der
’
s
net
w
o
r
k
,
i
s
e
n
t
i
r
el
y
a
n
o
n
y
m
ous.
O
n
t
h
e
ot
he
r si
de
of
t
h
e
pi
ct
ure
,
t
h
e
Tr
affi
c E
n
gi
ne
S
o
ft
ware
De
vel
opm
ent
Ki
t
(
S
DK
) m
a
y
al
so be em
bed
d
e
d
ont
o t
h
e
a
ppl
i
cat
i
ons
that are user
friendly. This
thing pa
ves
the way fo
r direct calculation a
nd
by such m
eans the
traffic
in
fo
r
m
atio
n
is
sh
ar
ed
am
o
n
g
th
e
u
s
er’
s
[5
]-
[6
].
3.
OVERVIEW OF
THE OPE
N
TRAFFIC SYSTE
M
The i
m
pl
em
ent
a
t
i
on
of
t
h
e
p
r
op
ose
d
sy
st
em
re
qui
res se
ve
r
a
l
o
p
en
s
o
u
r
ce
soft
ware
. Fi
rst
l
y
, Java
a
n
d
Mav
e
n
will b
e
in
stalled
,
fo
llowing
wit
h
th
e
Traffic Eng
i
ne so
ft
ware and
Op
en
Traffic ap
p
lication
.
Th
e work
also
in
vo
lv
es d
o
wn
lo
ad
ing
th
e Op
en
Street
Map
o
f
Ku
ala Lu
m
p
u
r
th
e co
nfigu
r
ation
fi
le will b
e
ed
ited
and
th
e Traffic Eng
i
n
e
app
will b
e
u
s
ed to
ex
tract th
e real
-ti
m
e d
a
ta to
b
e
an
alyzed
at later stag
es
o
f
the
i
m
p
l
e
m
en
tatio
n
.
3.
1.
T
o
p-l
e
ve
l
Vi
ew
A com
p
reh
e
n
s
iv
e ap
pro
ach
tak
e
n
for th
e traffic d
a
ta co
llectio
n is sh
own
in
Fig
u
re 2
.
Th
e
wo
rk
is
in
itiated
b
y
in
stallin
g
Mav
e
n
wh
ich
is a well-kn
own
to
bu
i
l
d
Jav
a
related p
r
o
j
ects
[7
].
After t
h
is step
, Jav
a
JDK
v
e
rsion
1.8
is in
stalled
,
fo
llo
wi
n
g
with
t
h
e in
stalla
t
i
on
of t
h
e T
r
af
fi
c
En
gi
ne
and
OSM respectively
.
This
was fo
llo
wed
b
y
th
e ed
itin
g o
f
th
e con
f
igu
r
ation
file for Traffic Eng
i
n
e
Ap
p
licatio
n an
d
th
en
re-ru
n
it
.
Finally, the tra
ffic s
p
ee
ds ca
n be e
x
tract i
n
C
S
V
file and a
n
alyze the data.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
502
-47
52
I
ndo
n
e
sian
J Elec Eng
& Com
p
Sci, V
o
l. 10
,
No
.
3
,
Jun
e
2
018
:
87
5 – 88
2
87
8
Fi
gu
re 2.
C
o
m
p
re
he
nsi
v
e Fl
o
w
C
h
ar
t to Col
l
ect Traffic Flow
Data
3.
2.
L
oadi
n
g
o
f
th
e
GPS
D
a
t
a
o
n
to
t
h
e Ma
p
T
h
e Map of Malaysia can be accessed and can
be
downloa
d
e
d
from
the Ge
ofa
b
ri
k’s se
rve
r
. Thi
s
serve
r
p
r
o
v
i
d
e
s
m
a
ps fo
r
OSM
pr
o
j
ect
s
,
w
h
i
c
h a
r
e
up
dat
e
d
.
T
h
e
m
a
p i
n
pd
f
i
s
d
o
w
nl
oa
d
e
d
fr
om
h
ttp
://d
own
l
o
a
d
.
g
e
ofab
rik.d
e
/
a
sia/
m
a
la
ysia-sin
g
a
p
o
re-brun
e
i.h
t
ml. Sin
ce th
e scop
e of th
is wo
rk
is to tak
e
con
s
i
d
erat
i
o
n
of
Kual
a
Lum
pur
onl
y
,
so t
h
e m
a
p o
f
KL
was d
o
w
nl
oa
ded
fr
om
t
h
i
s
l
i
n
k
h
ttp
s://
m
a
p
zen
.co
m
/d
ata/
metr
o
e
x
t
racts/
m
e
tro/kuala-lum
p
ur_m
alaysia/ as sh
o
w
n i
n
Fi
g
u
re
3. T
h
e f
o
r
m
at
of
the m
a
p downloade
d
i
n
raw OSM data as
pdf form
at.
Fig
u
r
e
3
.
Map Ex
tr
acti
o
n fr
om
Map
zen
3.
3.
L
oadi
n
g
o
f
th
e GPS
D
a
t
a
o
n
to
t
h
e T
r
af
fi
c E
n
gi
ne
The l
o
adi
n
g
o
f
t
h
e G
PS
dat
a
t
o
t
h
e
Tra
ffi
c
E
ngi
ne i
s
de
pi
ct
ed i
n
Fi
g
u
r
e
4.
The st
e
p
s a
r
e
m
e
nt
i
oned:
(i) csv
l
o
a
d
e
r.jar file
d
o
wn
lo
aded
fro
m
h
ttp
s://g
ith
ub
.co
m
/o
p
e
n
t
raffic/csv-load
e
r site.
(i
i
)
t
h
e
fi
l
e
na
m
e
d “K
ual
a
_L
um
pur.cs
v
” i
s
in the
sam
e
folder as
of “
jar fil
e”.
(iii) at term
in
al
, g
e
t t
h
e csv
l
o
a
d
e
r fo
ld
er.
Fi
gu
re
4.
Scree
n
sh
ot
of
L
o
adi
n
g
C
S
V
fi
l
e
Evaluation Warning : The document was created with Spire.PDF for Python.
In
d
onesi
a
n
J
E
l
ec En
g &
C
o
m
p
Sci
ISS
N
:
2
5
0
2
-
47
52
An
al
ysi
n
g
Ve
hi
cul
a
r
C
o
nge
st
i
o
n
Sce
n
ari
o
i
n
K
ual
a L
u
mp
ur
Usi
n
g
Ope
n
…
(
M
uh
a
m
m
a
d
Al
i)
87
9
The co
ng
re
gat
e
d sp
ot
s i
n
Fi
g
u
re 5 s
h
o
w
s t
h
e poi
nt
s o
f
i
n
t
e
rest
(PO
I) w
h
i
c
h were l
o
a
d
e
d
fr
om
C
S
V
file in
Traffic
Eng
i
n
e
. Si
n
ce th
e lo
ad
ing
of th
e d
a
ta, th
e n
u
m
b
e
r of th
e traffic statisti
cs th
at were co
un
ted
al
on
g t
h
e
p
r
oc
ess are
di
s
p
l
a
y
e
d
by
t
h
e “
D
a
t
a Loa
d
er
St
at
us B
a
r”.
It
wi
l
l
keep
o
n
u
p
d
a
t
i
ng as
l
o
ng
as t
h
e
Traffic E
ngi
ne
App
rem
a
ins connected wit
h
the serve
r
.
Fi
gu
re 5.
Scree
n
sh
ot
of
K
L
Ar
ea
wi
t
h
PO
I
At th
e en
d, after th
e ex
tractio
n
of d
a
ta fr
om
the GPS and e
x
tracting the traffic speed in CSV
form
at the platform
is ready to c
o
llect the
da
ta
and the i
n
terface looked like as s
h
own in
Figure
6.
Fi
gu
re
6.
Sc
re
ens
hot
of
O
p
e
n
Tra
ffi
c Pl
at
f
o
r
m
4. RES
U
LTS AN
D DIS
C
US
SION
S
4.
1.
T
r
af
fi
c
An
al
ysi
s
fo
r
Kual
a L
u
m
p
u
r
App
r
ox
im
ate
l
y
two
m
ill
io
n
data sa
m
p
les, wh
ich
were relat
e
d
with
th
e speed
m
e
tric, were ex
t
r
acted
fr
om
the Ope
n
Traffic s
o
ft
wa
re. Th
e average traffic spee
d
for whole
Ku
a
l
a Lum
pur wa
s depi
ct
ed
usi
n
g t
h
e
bar
graphs as
shown in Figure 7. T
h
e tra
ffi
c data as s
h
own in
Figure
7 i
s
an a
v
era
g
e
for all m
a
jor a
r
eas in
Ku
ala Lu
m
p
u
r
. Th
e d
i
stricts in
clu
d
e
, Buk
it Bin
t
an
g,
W
a
n
g
sa Maj
u
, Batu, Kepo
ng
, Titiwang
s
a, Setiawang
sa
Segam
but, Le
m
b
ah Pantai, Seputeh, Ba
ndar Tun Razak
and C
h
eras
. Fi
gure 8 s
h
ows com
p
rehe
nsive
l
y, that
the ave
r
a
g
e tra
ffic s
p
ee
d is more
tha
n
e
xpect
ed
du
ri
n
g
wee
kday
s
an
d a
bi
t
calm
du
ri
n
g
w
eeken
ds
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
502
-47
52
I
ndo
n
e
sian
J Elec Eng
& Com
p
Sci, V
o
l. 10
,
No
.
3
,
Jun
e
2
018
:
87
5 – 88
2
88
0
Fi
gu
re
7.
Tra
f
f
i
c Anal
y
s
i
s
F
o
r
w
hole Kuala Lum
pur
a
r
ea
i
n
Nov 2016
It
i
s
obse
r
ve
d
t
h
at
on Sat
u
r
d
ay
s an
d S
u
n
d
ay
s, t
h
e a
v
er
age spee
d fal
l
s bet
w
ee
n 4
4
-
49
km
/
h
fo
r
Novem
b
er. On
11th Novem
b
er
and 18th Novem
b
er,
the sp
e
e
d
i
s
t
h
e mi
n
i
mu
m.
T
h
i
s
deduces that t
h
e s
p
eed is
the slowest on
Fridays as t
h
e
Muslim
s offe
r
the prayers in l
a
rge
num
b
ers
and i
n
co
n
g
re
ga
t
i
on. T
h
e
ot
he
r
m
a
i
n
reason
for t
h
e l
o
w s
p
eed is that the
m
a
jori
t
y
of
t
h
e pe
opl
e
a
r
e goi
ng
t
o
t
h
ei
r hom
et
own
af
t
e
r
t
h
e day
has been
called
.
Besid
e
s th
is p
e
op
le also
g
o
fo
r sho
p
p
i
ng
wit
h
th
ei
r fam
ily. Th
is alto
g
e
th
er results in
a con
g
e
stio
n
scenari
o
. H
o
w
e
ver
,
t
h
e t
r
en
d
i
s
t
h
e qui
t
e
opposi
t
e
i
n
t
h
e w
eeken
ds w
h
e
r
e
m
o
st
of t
h
e peopl
e are rest
i
ng a
nd
the wee
k
e
n
ds
alm
o
st expe
rience
no activity as com
p
are
d
t
o
th
e weekd
a
ys. It is
ob
serv
ed
th
at t
h
e traffic is
heavy on weekdays b
ecause
m
o
st of the
bus
i
nesses a
r
e
ope
rated
during t
h
at tim
e
.
4.
2.
T
r
af
fi
c An
al
ysi
s
of
M
a
j
o
r
T
o
w
n
s
Som
e
m
a
jor t
o
w
n
s o
f
K
u
al
a
Laum
pur we
r
e
t
a
ken i
n
t
o
c
onsi
d
erat
i
o
n f
o
r t
h
e a
n
al
y
s
i
ng t
h
e t
r
a
ffi
c
beha
vi
o
u
r
spa
nni
ng a
week
.
These t
o
wns
were Se
nt
ul
, P
u
d
u
,
Kam
pun
g
bar
u
, Se
ksy
e
n
10, B
a
ng
sar,
C
h
i
n
a
Town
and
th
e Starh
ill. A slo
w
trait was ex
p
e
rien
ced
at th
e to
wn
s od
Ban
g
s
ar, Ch
i
n
ato
w
n
and
Starh
ill as
depicted i
n
Figure
9. T
h
e average tr
af
fi
c spee
d va
ri
es bet
w
e
e
n 2
6
-
3
4k
p
h
.
M
o
st
of t
h
i
s
sl
ow s
p
ee
d o
w
es
t
o
t
h
e
strateg
i
c lo
catio
n
o
f
t
h
e Bang
sar, wh
ich
is
co
nn
ected
t
o
Petalin
g
Jaya by
m
ean
s o
f
th
e Fed
e
ral
Highway. It
also c
o
nnecte
d
to t
h
e
Ne
w Pantai Express
w
ay a
n
d th
e
Spri
nt E
x
press
w
ay. Besi
des t
h
is, May
b
ank
towe
r,
Ban
g
s
ar
v
illage and
so
m
e
au
to
m
o
tiv
e sho
w
ro
o
m
s are also
s
itu
au
ed
in
t
h
e
v
i
cin
ity o
f
Bang
sar. Th
is all facto
r
s
co
n
t
ribu
tes and
m
a
k
e
Ban
g
s
ar a ho
tspo
t o
f
activ
ities. Ch
in
ato
w
n
on
th
e
oth
e
r h
a
nd
is a v
e
ry fam
o
u
s
tou
r
ist’s
attraction beca
use it is surrounde
d by
hotels
and it is th
ronged
by the ha
wke
r
s es
pcially at night. Thi
s
place
altern
ativ
ely is also
kno
wn
as Petalin
g
Street wh
ich attr
acts th
e v
i
sitors.
On
t
h
e
o
t
h
e
rsid
e, Starh
ill h
a
s lu
xu
ry
shopping m
a
lls such as Pa
vilion, Sungei Wang Pl
aza and Tim
e
s Square. Moderate
traffic spee
da are
obs
erved for Sentul, Kam
p
ung Baru a
nd Se
ksyen 10. T
h
is
is because th
ese places have
shopping complexe
s
and busi
ness a
r
eas in t
h
eir
vicinity.
Fig
u
r
e
8
.
Tr
af
fic
A
n
alysis f
o
r
Maj
o
r
Tow
n
in
4
t
h W
e
ek
of
O
c
tob
e
r
201
6
Evaluation Warning : The document was created with Spire.PDF for Python.
In
d
onesi
a
n
J
E
l
ec En
g &
C
o
m
p
Sci
ISS
N
:
2
5
0
2
-
47
52
An
al
ysi
n
g
Ve
hi
cul
a
r
C
o
nge
st
i
o
n
Sce
n
ari
o
i
n
K
ual
a L
u
mp
ur
Usi
n
g
Ope
n
…
(
M
uh
a
m
m
a
d
Al
i)
88
1
Th
e abo
v
e
m
e
n
tio
n
e
d
spo
t
s ex
p
e
rien
ces co
ng
estion
m
o
st o
f
th
e ti
m
e
s
when
th
e p
u
b
lic activ
ities are
at their
peak.
4.
3.
T
r
af
fi
c An
al
ysi
s
per Hour
B
a
si
s
An hou
rly d
a
t
a
co
llectio
n
app
r
o
a
ch
was tak
e
n at an im
p
o
rtan
t lo
cation i.e. Masj
id
Ind
i
a. Fi
g
u
re
9
sh
ow
s the an
al
ysis
m
a
d
e
o
n
ho
ur
ly b
a
sis at Masj
id
Ind
i
a ro
ad
on
24
th
Octo
b
e
r
20
16
.
Heav
y tr
af
f
i
c
f
l
ow
w
a
s
o
b
s
erv
e
d after
9
.
0
0
am
u
n
til mid
n
i
g
h
t
.
Fi
gu
re 9.
Tra
f
f
i
c
Anal
y
s
i
s
on
Ho
url
y
B
a
si
s
a
t
M
a
sji
d
I
ndi
a R
o
ad
o
n
2
4
t
h
Oct
o
ber
2
0
1
6
5. CO
N
C
L
U
S
I
ON
In this
work a
v
era
g
e Tra
ffic
Spee
d was
obs
e
rve
d
at
selected locations of the
m
a
jor a
r
e
a
s of
Kuala
Lum
pur a
r
ea f
o
r t
h
e w
h
ol
e
m
ont
h of
N
o
v
e
m
b
er (
f
r
o
m
1st
t
o
3
0
t
h
) an
d
t
h
e l
a
st
wee
k
of
Oct
o
be
r 2
0
1
6
.
T
h
e
traffic s
p
eeds
and a
rri
val time were
observed by the
he
lp of
Ope
n
T
r
affic softwa
re. T
h
e work si
gni
fies the
im
portance
o
f
Ope
n
Tra
ffic p
l
atform
.
It
also focus
s
es at t
h
e proces
s
of c
o
llecting t
h
e
real tim
e
traffic flow
d
a
ta an
d th
en
an
alyzin
g it. B
a
sed
on
the resu
lts ob
tain
ed
, th
e con
g
e
stion
scen
ari
o
o
c
cu
rs th
e m
o
st durin
g th
e
weekdays c
o
m
p
ared to
we
ekends
. It
wa
s de
picted th
at th
e Op
en
Traffic is h
e
l
p
fu
l in
an
alyzing
an
d
un
de
rst
a
n
d
i
n
g
t
h
e real
t
i
m
e
vehi
cul
a
r t
r
af
fi
c fl
ow
f
o
r
t
h
e gi
ven a
r
ea. T
h
e
r
efore, it is recommended that
Ope
n
Traffic ca
n
be
use
d
for t
r
affic analysis in
the future
w
o
r
k
s.
B
e
si
des
t
h
i
s
,
t
h
e dat
a
ca
n be use
d
fo
r
t
h
e
pre
d
i
c
t
i
on
of t
h
e ve
hi
cul
a
r t
r
affi
c be
havi
or
and al
s
o
, t
h
e d
a
t
a
can al
so b
e
used
by
t
h
e pri
v
at
e or t
h
e
pu
bl
i
c
sector
for t
h
e traffic m
a
nagement.
REFERE
NC
ES
[1]
Peter Samuel, Traffic Congestio
n: A
Solvable Problem, Issue in Science a
nd Technologies, Volume XV Issue 3
,
Springer 1999.
[2]
Traffic
congestion and r
e
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ends and
advan
ced
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estion m
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e
ral
Highway
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[3]
Hossa
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z
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”Integrated
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t
e
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llig
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Roopa, T., An
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aman Naray
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I
S
SN
:
2
502
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52
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ndo
n
e
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2
88
2
BIOGRAP
HI
ES
OF AUTH
ORS
M
uhammad Ali
com
p
leted
his
M
a
s
t
er of e
ngineering (Electron
i
cs and
Tel
ecom
m
unicat
ions) from
Uni
v
ersiti T
echnol
ogi Mala
y
s
ia i
n
2016. He receiv
e
d his
Bache
l
ors
of S
c
ienc
e in El
ec
tric
al Engin
eer
i
ng f
r
om University
of Lahore Pakis
t
an. He is
current
l
y
doing
PhD in depart
m
e
nt of ele
c
tri
cal
engine
ering
in Universiti
Techno
logi
Malay
s
ia. His to
pics of interest
are big data
an
al
yt
ics
,
m
ach
ine
l
earning
, Int
e
rnet
of Things
(IoT), image pro
cessing and
sign
al pro
cessing.
Saargunaw
a
thy
is working as an Assistant
Manager in
Te
lekom
Mala
ysi
a
. W
a
t
h
y
graduat
e
d from
Multim
edia Uni
v
ersit
y
, C
y
ber
j
a
y
a
,
Mala
ysi
a
, wi
th a Bache
l
or of Elec
troni
c
Majoring in Telecommunication
s
Engineering
.
She then continued to earn her Master from
Universiti T
e
kn
ologi Mala
ysi
a
in Tel
ecom
m
unica
tions Engin
eering
.
She has
published
paper on
title “An Investigation
on the Use
of I
T
U-R P.1411-7
in IEEE 802
.11
N
Path Loss
Modelling” during her b
ach
elors
.
K
a
maludin M
o
hamad Yu
sof
rece
ived
the
B.Eng degr
ee
i
n
Ele
c
tri
cal
-
Ele
c
troni
cs
Engineering an
d M.Eng degr
ee in Electri
cal Engineering f
r
om Universiti Teknolog
i
M
a
la
y
s
ia
. He re
ceiv
e
d P
h
.D deg
r
ee from
Univer
s
i
t
y
of Es
s
e
x
,
U.
K. He is
current
l
y
a s
e
n
i
or
lecturer in
the Department
of Communica
tion Engin
eerin
g, Faculty
of
Electrical
Engineering an
d member of
Advanced Te
lecommunication
Technol
og
y
at
Universiti
Teknologi Malay
s
ia. His current research intere
s
t
s include Intern
et-of-Th
i
ngs, Big Data and
Software-Defin
ed Networks.
M
uhammad Ra
mdhan M
.
S
rec
e
ived
the
B.S
.
de
gree
in
Ele
c
tri
c
a
l
-El
ectron
i
c
Eng
i
neer
ing
from Universiti
Teknologi Malay
s
ia in
2016
and
he
is curr
entl
y
enrolled
in
the M.S. degree
in Facu
lty
of
Electrical Eng
i
neer
ing at Universiti
Teknologi Malay
s
ia. His
curren
t
research
inter
e
s
t
s
ar
e in
t
h
e ar
ea
of wir
e
l
e
s
s
networ
ks including wireless sens
or networks (
W
SN),
sports and saf
e
ty monitoring
engineering
.
Evaluation Warning : The document was created with Spire.PDF for Python.