Indonesi
an
Journa
l
of El
ect
ri
cal Engineer
ing
an
d
Comp
ut
er
Scie
nce
Vo
l.
1
3
,
No.
3
,
Ma
rch
201
9
, p
p.
1
2
4
3
~
1
2
5
1
IS
S
N: 25
02
-
4752, DO
I: 10
.11
5
91/i
j
eecs
.v1
3
.i
3
.pp
1
2
4
3
-
1
2
5
1
1243
Journ
al h
om
e
page
:
http:
//
ia
es
core.c
om/j
ourn
als/i
ndex.
ph
p/ij
eecs
Review
of
t
raffi
c
contr
ol t
ec
hn
iqu
es
f
or
e
mergen
cy
v
ehi
cles
Wan M
ohd H
af
iz
bin W
an
Hussin
,
Mars
hima
M
oh
d
Rosli
, Ros
mawa
ti Nordin
Facul
t
y
of
Com
pute
r and
Ma
them
at
ic
a
l
Sci
ences
,
Univer
si
ti T
ekn
ologi
MA
RA
,
S
hah
Alam,
Sela
n
gor,
Mal
a
y
s
ia
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
S
ep
1
5
, 201
8
Re
vised
N
ov
2
0,
2018
Accepte
d
D
ec
2
5,
2018
Tra
ffi
c
control
sy
stem
play
an
i
m
porta
nt
role
to
m
ana
ge
tra
f
fic
c
ongesti
on
on
the
ro
ad
espe
cia
lly
during
pe
ak
hours
and
pe
ak
sea
sons
.
One
of
the
m
ai
n
cha
l
le
nges
is
to
cont
rol
the
tr
aff
i
c
when
the
r
e
are
emerge
n
c
y
c
ase
s
at
tra
ff
ic
li
ght
int
erse
ctio
n
espe
c
ia
l
l
y
pe
ak
hours.
Thi
s
coul
d
aff
e
ct
t
he
rout
e
for
emerge
nc
y
veh
i
cl
es
such
as
am
bula
nc
e,
fi
re
bri
gade
and
po
li
c
e
ca
r
to
r
ea
ch
the
ir
d
esti
n
at
ion
.
Due
to
the
inc
r
ea
se
of
tra
f
fic
c
ongesti
on
during
pea
k
hours
and
pe
ak
se
asons
in
Mal
a
y
s
ia,
th
ere
is
a
ne
ed
for
furthe
r
evalua
t
io
n
of
tr
aff
i
c
cont
rol
techniqu
es.
Thi
s
p
ape
r
re
vie
wed
and
cons
o
li
dated
info
rm
at
ion
on
th
e
diffe
ren
t
t
y
pes
of
the
exi
stin
g
tra
ffi
c
cont
r
ol
s
y
stem
for
roa
d
tra
ff
i
c
m
ana
gement
suc
h
as
Radi
o
Freq
uency
Ide
n
ti
fi
cat
ion
(RFID
),
wire
le
ss
sensor
net
work
and
image
proc
essing.
Thi
s
pape
r
anal
y
sed
and
compa
red
on
the
design,
ben
ef
it
s
and
li
m
it
a
ti
ons
of
ea
ch
te
chn
iqu
e.
Through
the
r
evi
ews,
th
is
pape
r
rec
om
m
ends
the
best
tra
ffic
cont
rol
t
ec
hn
i
que
for
emerge
nc
y
veh
icl
e
tha
t
of
fer
s
low
pric
e
,
low
m
ai
n
t
ena
nc
e
and
c
an
be
used
in
var
io
us
are
as
of
appl
i
ca
t
ions.
Ke
yw
or
d
s
:
Em
erg
ency
v
e
hicle
s
Im
age
p
r
ocessi
ng
RFID
Traffic
l
ig
ht
W
i
reless
s
e
nso
r
n
et
w
ork
Copyright
©
201
9
Instit
ut
e
o
f Ad
vanc
ed
Engi
n
ee
r
ing
and
S
cienc
e
.
Al
l
rights re
serv
ed
.
Corres
pond
in
g
Aut
h
or
:
Ma
rsh
im
a Moh
d R
os
li
,
Dep
a
rtm
ent o
f C
om
pu
te
r
Scie
nce,
Un
i
ver
sit
i
Te
knol
og
i M
ARA
,
Sh
a
h Alam
Sel
ango
r
Ma
la
ysi
a
Em
a
il
:
m
arsh
im
a@t
m
sk
.u
it
m
.ed
u.
m
y
1.
INTROD
U
CTION
The
m
ajo
rity
of
the
urba
n
c
om
m
un
it
ie
s
in
Ma
la
ysi
a
hav
e
seen
sig
nifica
nt
popula
ti
on
and
fina
ncial
dev
el
op
m
ent
over
t
he
past
tw
o
de
cades
.
A
s
a
resu
lt
of
t
his
dev
el
op
m
ent,
there
was
a
n
i
nc
rease
in
t
he
num
ber
of
re
gistere
d
ve
hicle
s
on
t
he
ro
a
d.
T
her
e
f
ore,
in
2
017,
the
r
e
wer
e
m
or
e
than
28
m
i
ll
ion
reg
ist
ered
ve
hicle
s
i
n
Ma
la
ysi
a
[1
]
.
This
ind
ic
at
es
the
crit
ic
al
diffi
culti
es
and
al
so
issues
to
a
na
ti
on
with
j
us
t
m
or
e
than
8
m
illi
on
hous
e
hold es
pe
ci
al
ly
f
or
t
he
tr
ans
por
ta
ti
on
pr
ob
le
m
s in
the
urba
n
a
reas
.
On
e
of
t
he
ge
ner
al
tra
ns
po
rtat
ion
pro
blem
s
for
the
urb
a
n
areas
in
Ma
la
ysi
a
is
wh
en
there
are
e
m
erg
ency
ca
s
es
at
the
t
raffic
li
gh
t
i
ntersec
ti
on
wh
ic
h
a
re
al
ways
bu
sy
with
m
any
ve
hi
cl
es.
This
will
cause
the
em
erg
ency
veh
ic
le
s
di
ff
i
cult
to
reac
h
the
desti
nation
on
ti
m
e
du
e
to
the
traff
ic
c
onge
sti
on
par
ti
c
ularly
durin
g
pea
k
hours.
In
s
om
e
cases,
the
e
m
erg
ency
vehi
cl
es
su
ch
as
fire
bri
ga
de
and
am
bu
la
nc
e
face
diff
ic
ulti
es
w
he
n
they
ha
ve
t
o
wait
f
or
oth
e
r
ve
hicle
s
to
gi
ve
way
at
inter
sect
ion
s
with
t
raffic
li
gh
ts
[
2].
T
his
c
an
ca
us
e
dela
y
e
m
erg
ency
ve
hicle
s
su
c
h
a
s
fire
br
i
ga
de
t
o
re
scue
the
pe
op
le
,
poli
ce
c
ar
to
cat
c
h
t
he
thief
,
a
m
bu
la
nce
to
reach
ho
s
pital
on
tim
e
.
M
or
e
over,
the
c
olli
sion
s
with
oth
e
r
ve
hicle
s
fr
om
oth
er
w
ay
s
of
directi
on
m
igh
t
al
so
occur
at
the
intersect
io
n
s
with
t
raffic
li
gh
t.
T
his
al
so
will
cause
a
de
la
y
of
tim
e
and
m
ay
aff
ect
the
em
er
gen
cy
case
su
c
h
as
loss
of
li
f
e
and
pro
pe
rty
[2
]
.
Im
pr
ovin
g
the
existi
ng
traf
fic
con
tr
ol
s
yst
e
m
is t
her
e
fore si
gnific
antly
im
po
rtant to
so
l
ve
t
he diffic
ulti
es fa
ced
by the
em
erg
e
ncy
veh
ic
l
es.
In
rece
nt
ye
ar
s,
there
ha
s
be
en
an
inc
reasi
ng
inte
rest
in
the
sm
art
traff
ic
con
tr
ol
syst
em
by
us
ing
RFID, wireless
sen
sor n
et
w
or
k
an
d
i
m
age p
r
ocessin
g
that st
ud
ie
d
the
al
te
rn
at
ive w
ay
s to e
nh
a
nce th
e e
xi
sti
ng
traff
ic
c
on
tr
ol
syst
e
m
[
3]
.
T
he
se tec
hnologi
es able to supp
or
t t
he
tra
ff
ic
c
on
t
ro
l sy
ste
m
t
o
m
ake traf
fic
routin
g
decisi
on
w
hen
e
m
erg
ency
cas
es
occur.
F
or
e
xam
ple,
a
s
m
ar
t
traff
ic
co
ntro
l
syst
e
m
can
rep
la
ce
the
poli
ce
m
an
or traf
fic m
arsh
al
s
that
c
ontr
ol
the
r
ou
ti
ng
de
ci
sion
durin
g con
gestio
n
at
t
he
inte
rsecti
on
with tra
ff
ic
li
ght [
3].
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
1
3
, N
o.
3
,
Ma
rc
h
201
9
:
1
2
4
3
–
1
2
5
1
1244
In
this
stu
dy,
we
pr
e
sent
a
r
eview
on
the
te
chn
i
qu
e
s
of
t
he
traf
fic
con
t
ro
l
syst
em
fo
r
ro
ad
tra
ff
ic
m
anag
em
ent.
The
obj
e
ct
ive
of
this
re
view
is
to
up
date
th
e
sta
tus
of
the
deg
ree
to
wh
i
ch
te
chn
i
qu
e
s
on
th
e
traff
ic
c
ontr
ol
syst
em
are
addresse
d
i
n
the
te
ch
nolo
gy
researc
h.
T
he
rev
ie
w
a
ddress
es
tw
o
r
esearc
h
obj
ect
ives:
(1)
To
c
om
par
e
t
he
a
dv
a
ntage
s
and
disa
dvanta
ges
of
each
te
chn
i
qu
e
that
ha
s
bee
n
us
e
d.
(2)
T
o
su
ggest
a
n
a
pp
ropr
ia
te
tec
hn
i
qu
e
to
im
pr
ove
the c
u
r
ren
t
syst
e
m
.
The
rem
ai
nin
g
of
this
pa
pe
r
is
or
gan
iz
e
d
as
f
ollows:
Se
ct
ion
2
desc
ribes
t
he
bac
kgrou
nd
an
d
m
ot
ivati
on
an
d
Sect
ion
3
des
cribes
the
m
eth
od
ology
to
pe
rfor
m
the
rev
ie
w.
Sect
io
n
4
presents
the
res
ults
of
the
rev
ie
w
an
d
sect
ion
5
desc
ribes
the
pro
po
se
m
et
ho
d
to
im
pr
ov
e
the
cu
r
ren
t
traf
fic
cont
ro
l
syst
e
m
.
Se
ct
ion
6
disc
us
s
on
th
e
i
m
po
rtanc
e
of
the
rev
ie
w
re
su
lt
s.
Fin
al
ly
,
this
pa
pe
r
co
nc
lud
es
a
nd
s
ugge
sts
fu
t
ur
e
w
ork
i
n
sect
ion
7.
2.
B
AC
K
G
ROU
ND AN
D MO
TIVATI
ON
Ther
e a
re s
om
e o
ther fact
ors that
m
igh
t
caus
e traff
ic
con
ge
sti
on
on th
e r
oa
d
an
d
the r
ese
arch
e
rs
nee
d
to do som
e res
earch
on h
ow to red
uce c
onge
sti
on
on the
ro
ad
s
uc
h
as:
2.1.
W
eakness i
n
the exis
ting tr
affic li
ght c
ontr
ol s
ys
tem
Ba
sic
al
ly
,
the
m
ai
n
fu
nctio
n
of
tra
ff
ic
li
gh
t
con
t
ro
l
is
to
co
ntr
ol
the
flo
w
of
tra
ff
ic
.
T
he
norm
al
fo
rm
of
t
raffic
li
gh
t
is
com
pr
ise
s
of
sim
ple
three
colo
rs
f
or
tra
ffi
c
sign
al
wh
ic
h
are
re
d
m
eans
sto
p,
ye
ll
ow
m
eans
read
y
t
o
st
op
and
gr
ee
n
m
eans
m
ov
e.
T
his
ge
ner
al
traf
fi
c
li
gh
t
c
ontr
ol
syst
em
cann
ot
giv
e
pri
ori
ti
ze
an
d
rec
og
nize
the
e
m
erg
ency
ve
hi
cl
e
and
no
rm
a
l
car.
As
an
e
xam
ple,
the
del
ay
of
the
am
bu
la
nce
to
reac
h
at
the
ho
s
pital
b
eca
use
of the
traf
fic
congesti
on m
ay
cause da
ng
e
r
to pati
ent’s
li
fe.
On
a
no
t
her
sid
e,
the
norm
al
f
or
m
of
the
traf
fic
m
anag
em
e
nt
is
req
ui
res
pol
ic
e
traff
ic
on
the
ro
a
d
to
con
t
ro
l
the
tra
ff
ic
co
ngest
io
n.
T
he
poli
ce
traff
ic
will
co
ntr
ol
the
flo
w
of
tra
ff
ic
dur
ing
tra
ff
ic
co
ngest
io
n
occurre
d
by
gi
ves
the
si
gn
al
t
o
the
r
oa
d’
s
use
r
w
hethe
r
to
dr
i
ve
or
sto
p.
The
poli
ce
traf
fic
can
rec
ogni
ze
and
giv
e
pri
or
it
y f
or the
em
erg
enc
y veh
ic
le
s
by
gi
vin
g way t
o
th
e em
erg
ency v
ehicl
es
.
2.2.
Weakness i
n
the exis
ting em
ergenc
y vehicl
es sy
s
tem.
The
e
xisti
ng
e
m
erg
ency
veh
i
cl
e
syst
e
m
in
Ma
la
ysi
a
is
by
us
in
g
the
ra
dio
syst
em
and
then
c
onnect
e
d
with
a
cal
l
cen
te
r.
T
he
em
erg
ency
ve
hicle
s
just
gi
ve
a
flas
hing
li
ght
an
d
loud
sire
n
to
warn
the
r
oad’
s
use
r
that
the
em
erg
ency
ve
hicle
s
need
t
he
rig
ht
of
way.
S
om
eti
m
es,
flashin
g
li
gh
t
an
d
lo
ud
siren
do
not
giv
e
a
n
aff
ect
to
r
oa
d
us
ers
due
to
a
n
issue
t
hat
is
s
om
e
ro
ad
us
e
r
s
are
hea
rin
g
t
he
rad
i
o
with
high
vo
l
um
e,
no
s
pace
to
gi
ve
way
an
d
oth
e
r
inter
fe
ren
ces
.
T
her
e
f
or
e
,
this
kind
of
iss
ue
m
ay
con
t
rib
ute
fact
ors
f
or
the
em
erg
ency
veh
ic
le
s t
o
r
ea
ch
the
d
e
sti
nation sm
oo
thly
.
3.
METHO
DOL
OGY
This
pa
per
use
s
a
nar
rati
ve
li
te
ratur
e
re
vie
w
ap
proach
to
com
par
e
and
su
m
m
arize
on
the
existi
ng
te
chn
iq
ues
of
traf
fic
con
tr
ol
s
yst
e
m
in
the
li
t
eratur
e
.
The
na
rr
at
ive
li
te
rature
rev
ie
w
a
pproach
aim
s
to
discuss
the
sta
te
of
a
s
pecific
to
pic
or
them
e
fr
om
a
theo
reti
cal
and
co
ntextual
poi
nt
of
view
.
T
hi
s
pa
per
analy
s
ed
th
e
sel
ect
ed
stu
die
s b
ase
d o
n
the
fo
ll
owin
g
c
rite
ria:
a)
Tech
niques
use
d
to
contr
ol tr
aff
ic
routin
g d
eci
sion
s
.
b)
Traffic
d
at
a
col
le
ct
ion
m
et
ho
ds
t
o
m
anag
e t
he ro
utin
g decisi
on
s
.
c)
Nu
m
ber
a
nd ty
pes of va
riable
s u
se
to
s
up
por
t t
he
r
outi
ng and si
gn
a
l
decisi
on
s
.
4.
TE
CHN
I
QUE
S FO
R
T
RAF
FIC CO
NTR
OL SYST
EM
In
recent
ye
ar
s,
there
has
be
en
an
i
ncr
easi
ng
am
ount
of
li
te
ratur
e
on
s
olv
in
g
the
pro
blem
of
the
traff
ic
c
ongesti
on.
T
his
pa
per
rev
ie
wed
relev
ant
pu
blica
ti
ons
that
disc
us
se
d
the
c
omm
on
te
chn
iq
ues
us
e
d
f
or
traff
ic
co
ngest
ion
w
hich
are
RFID
,
wi
reless
netw
ork
sensor
an
d
im
a
ge
processi
ng.
The
detai
l
of
each
te
chn
iq
ue
is
explai
ned in t
he f
ollow
i
ng s
ub
se
ct
ion
.
4.1.
RFI
D
Gen
e
rall
y,
RFI
D
is
a
su
it
able
ap
proac
h
that
can
be
us
e
d
to
co
ntr
ol
the
tra
ff
ic
c
ongestio
n.
RFI
D
a
r
e
div
ide
d
int
o
th
ree
ty
pes
wh
ic
h
are
lo
w
fr
e
quency
(L
F),
hi
gh
fr
e
qu
e
ncy
(
HF
)
a
nd
ultra
-
high
fr
e
quency
(U
H
F)
bands
[
4].
T
he
va
rio
us
ty
pes
of
bands
can
pro
du
ce
di
ff
e
r
ent
re
su
lt
s
i
n
t
erm
s
of
acc
uracy
an
d
pr
eci
s
ion
t
o
detect
.
Hash
im
et
al
.
[
5]
pro
pose
a
R
FI
D
te
ch
nique
to
c
on
tr
ol
the
traff
ic
c
onge
s
ti
on
veh
ic
le
(
VTCE)
.
T
he
pro
po
se
d
te
ch
nique
us
e
d
the
RFID
Re
ade
r
in
the
veh
ic
le
to
read
the
ve
hicle
ta
g
and
transf
e
r
the
r
equ
i
red
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Revi
ew
o
f t
ra
ff
ic
co
ntr
ol tech
niques f
or
e
me
rg
e
ncy ve
hicle
s (Wan M
ohd Ha
fi
z
bin Wa
n Hu
s
sin)
1245
inf
or
m
at
ion
to
the
database
i
n
the
Ce
ntral
Com
pu
te
r
Syst
e
m
.
The
Ce
ntr
al
Co
m
pu
te
r
S
yst
e
m
wil
l
det
erm
ine
the
tra
ff
ic
c
on
gestio
n
sta
tus
of
the
r
oad
net
work
by
f
ollo
wing
ce
rtai
n
proce
dures
bas
e
d
on
the
data
obta
ined
from
the
Ce
ntral
Com
pu
te
r
S
yst
e
m
(CCS).
The
resu
lt
s
of
the
stu
dy
in
dicat
e
that
the
VT
CE
syst
e
m
had
be
e
n
su
ccess
fu
l
by
introd
u
ci
ng
R
FI
D
rea
de
rs
at
each
of
the
intersect
io
n
points
a
nd
ad
ding
RF
ID
la
bels
to
al
l
veh
ic
le
s.
Howe
ver,
unli
ke
S
ur
es
h
et
al
.
[6
]
w
hich
e
xp
l
ai
ns
that
by
us
i
ng
RF
ID
it
is
possible
to
a
vo
i
d
pro
blem
s
arisi
ng
f
ro
m
norm
al
li
gh
t
con
t
ro
l
syst
e
m
s
associat
ed
with
beam
i
nterf
e
re
nce
te
chn
i
qu
e
s
an
d
i
m
age
processi
ng.
Suresh
et
al
pr
op
os
e
d
a
te
chn
iq
ue
that
us
e
a
RF
read
er
on
t
he
ro
a
d
interse
ct
ion
to
co
ns
id
er
the
pr
i
or
it
y
for
the
em
erg
ency
ve
hicle
s
an
d
the
densi
ty
of
the
traff
ic
on
the
r
oads.
T
he
resul
ts
sh
ow
that
it
can
red
uce tim
e eff
ic
ie
ntly
an
d gi
ve dynam
ic
tim
e in r
eal
ti
m
e
to
a
vo
i
d
tra
ff
i
c co
ng
e
sti
on.
Ra
j
u
et
al
.
[
7]
m
ade
fu
rt
her
s
upport
by
integrati
ng
RFID
a
nd
Glob
al
Syst
em
for
Mo
bile
com
m
un
ic
at
ion
(
GS
M
)
to
c
ontr
ol
the
tra
ff
ic
congesti
on.
H
ow
e
ve
r,
it
only
fo
c
us
es
on
am
bu
la
nce
to
pro
ve
this
m
et
ho
ds. As
a
n
exam
ple, onc
e an
am
bu
la
nc
e reach
t
he
traf
fic li
gh
t j
unct
ion, it
co
r
respo
nd
i
ng
la
ne
traf
fic li
gh
t
beco
m
es
gr
ee
n
and
t
he
oth
er
side
bec
om
e
red
the
n
the
am
bu
la
nce
ca
n
re
a
ch
the
hosp
it
al
sm
oo
thly
.
The
way
to
update
th
e
syst
e
m
dynam
ic
al
ly
by
us
in
g
SM
S
th
r
ough
t
he
GS
M
m
odule.
The
m
os
t
i
m
po
rta
nt
th
ing
by
us
in
g
RFI
D
is
cost
eff
ect
i
ve
and
t
hen
will
pr
ovi
de
unin
te
rr
upte
d
c
omm
un
ic
at
ion
ev
en
in
bad
we
at
her
conditi
ons.
The
works
by
Asw
a
ni
[
8]
al
so
use
s
RFI
D
a
nd
GS
M
t
o
pro
ve
that
this
de
vi
ces
can
be
us
e
d
to
c
ontro
l
the traff
ic
c
onge
sti
on
. Ho
we
ve
r,
it
h
as a b
it
d
iffe
re
nt w
it
h R
aju
et al
. [7] b
ecau
se it
ap
pl
ie
d
LPC2
148 wh
ic
h
is
syst
e
m
-
on
-
c
hi
p
to
rea
d
the
RFID
ta
gs
at
ta
c
hed
to
t
he
ve
hi
cl
e
and
the
m
ai
n
goal
of
t
his
researc
h
is
t
o
c
on
t
ro
l
t
he
tra
ff
ic
li
ght
syst
em
fo
r
t
he
em
erg
ency
ve
hicle
.
He
e
xp
la
ined
that
t
his
s
yst
e
m
can
re
duce
the
m
anu
al
effor
t
on
par
t o
f
traf
f
ic
p
olice
to
co
ntr
ol traf
fic co
ng
e
sti
on
a
nd
it
also r
eq
uires v
ery le
ss h
um
an
interve
ntion.
Th
us
, it
al
so
can
im
pr
ovise
his
resea
r
c
h
by
us
i
ng
I
nt
ern
et
of
T
hing
(
I
OT)
t
o
m
on
it
or
t
he
tra
ff
i
c
sign
al
s
de
ns
i
ty
and
con
t
ro
l t
he
tra
f
fic sig
nals.
Chit
ta
et
al
.
[9
]
pr
esent
a
sm
art
traff
ic
li
gh
t
con
tr
ol
syst
em
fo
r
em
erg
en
cy
veh
ic
le
s
especial
ly
fo
r
a
m
bu
la
nce
to
pass
thr
ou
gh
t
raffic
li
gh
t
j
un
ct
ion
sm
oo
thly
by
us
ing
RF
I
D
an
d
IOT
ap
plica
ti
on
s.
T
he
RFID
read
e
r
will
be
instal
le
d
at
the
traff
ic
li
gh
t
ju
nc
ti
on
m
eanw
hi
le
RFID
ta
gs
fi
xed
to
the
veh
i
cl
es.
Then,
the
total
of
the
syst
em
can
be
m
on
it
ored
th
r
ough
I
O
T.
As
a
res
ult,
his
w
orks
m
igh
t
be
sa
ved
the
m
anu
al
effor
t
on
the
par
t
of
the
poli
ce
traf
fic
to
c
ontr
ol
the
c
onge
sti
on
by
us
in
g
IO
T
ap
plica
ti
ons.
Ot
her
t
han
that,
the
integ
r
at
ion
betwee
n
RFI
D
and
IOT
ap
pl
ic
at
ion
can
c
re
at
e
a
new
re
voluti
on
to
c
on
t
ro
l
the
tra
ff
ic
congesti
on.
Ta
ble
1
sh
ows
t
he
s
um
m
ary
f
or
th
e
RFID
te
ch
niq
ue
s
base
d
t
he
ref
e
ren
ce
s,
pro
po
se
d
a
ppr
oach,
a
dv
a
nta
ges
a
nd
disad
va
ntages.
Table
1
.
S
umm
ary f
or RFI
D
t
echn
i
qu
e
s
Ref
erences
Prop
o
sed
App
roach
Ad
v
an
tag
es
Disad
v
an
tag
es
Hash
i
m
et
al.
[
5
]
RFID
Techn
iq
u
e
-
Econ
o
m
i
cal
-
Low co
st
-
Do
es n
o
t
d
istu
rb traff
ic
On
ly
sen
ses
eq
u
ip
p
ed
v
eh
icles
at
a
p
o
in
t on
the road
.
Su
resh
et
al.
[
6
]
RFID
Techn
iq
u
e
-
Deliv
er
ti
m
e
ef
f
icien
cy
an
d
g
iv
e
d
y
n
a
m
ic
ti
m
e
in
r
eal
ti
m
e
to
av
o
id
traff
ic con
g
estio
n
.
-
Ef
f
ectiv
ely
con
trol traf
f
ic f
lo
w.
On
ly
sen
ses
eq
u
ip
p
ed
v
eh
icles
at
a
p
o
in
t on
the road
.
Raju
et
al.
[
7
]
RFID and
GS
M
-
Co
st ef
f
ectiv
e.
-
W
ill
p
rov
id
e
u
n
in
terr
u
p
ted
co
m
m
u
n
icatio
n
ev
en
in
b
ad
weather con
d
itio
n
s.
On
ly
sen
ses
eq
u
ip
p
ed
v
eh
icles
at
a
p
o
in
t on
the road
.
Aswan
i [
8
]
RFID and
GS
M
-
Red
u
ce
m
an
u
al
e
f
fort
o
n
p
art
o
f
p
o
lice tr
af
f
ic.
-
Un
resp
o
n
siv
e to b
ad
weather.
On
ly
sen
ses
eq
u
ip
p
ed
v
eh
icles
at
a
p
o
in
t on
the road
.
Ch
itta et
al.
[
9
]
RFID
an
d
IOT
Ap
p
licatio
n
s
-
Sav
e
m
an
u
al
ef
f
o
rt
o
n
p
art
o
f
p
o
lice tr
af
f
ic.
-
Ef
f
ectiv
ely
con
trol traf
f
ic f
lo
w.
-
Low p
o
wer
co
n
su
m
p
tio
n
s.
-
Un
resp
o
n
siv
e to b
ad
weather.
-
Flex
ib
le
d
esig
n
to
f
u
l
f
ill
g
reat
v
ariety
of
app
licati
o
n
s.
On
ly
sen
ses
eq
u
ip
p
ed
v
eh
icles
at
a
p
o
in
t on
the road
.
4.2.
Wir
el
ess N
e
twork Sens
or (
WSN)
On
t
he
oth
er
ha
nd, W
SN
can also
be
us
e
d
to
con
t
ro
l
tra
ff
ic
co
ngest
io
n
on
the
r
oa
d.
T
he
re ar
e
se
ver
a
l
functi
on
of
W
SN
t
hat
can
be
us
e
d
s
uc
h
as
t
o
c
ollec
t
traff
i
c
data,
act
i
vely
co
ntr
olli
ng
tr
a
ff
ic
a
nd
bei
ng
placed
on
net
work
co
ntr
ollers.
T
hus
,
W
S
N
a
re
ve
ry
easy
f
or
i
nst
al
la
ti
on
,
le
ss
of
m
ai
ntenance
,
faster
tran
s
fer
of
inf
or
m
at
ion
and less
e
xpen
siv
e com
par
ed
to othe
r netw
ork op
ti
ons
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
1
3
, N
o.
3
,
Ma
rc
h
201
9
:
1
2
4
3
–
1
2
5
1
1246
Ther
e
a
re
sev
eral
i
m
po
rtant
researc
h
on
traf
fic
li
gh
t
co
ntr
ol
for
em
er
gen
cy
ve
hicle
s
us
ing
WSN
te
chn
iq
ues
to
preve
nt
tra
ff
ic
c
ongestio
n
on
t
he
ro
a
d
[10
]
-
[
14]
.
F
or
exam
ple,
S
hruthi
et
al
.
[
10]
pro
pose
WSN
te
chn
iq
ues
to
con
t
ro
l
bo
t
h
si
ng
le
a
nd
m
ultip
le
intersect
io
n.
T
his
researc
h
is
al
so
de
sig
ned
to
c
ontrol
traff
i
c
ov
e
r
m
ulti
ple
intersect
io
ns
a
nd
fo
ll
ows
i
nter
national
sta
nda
rd
f
or
traf
fic
li
gh
t
operati
ons.
The
sen
sor
will
be
instal
le
d
on
th
e
traff
ic
li
ght
an
d
t
hen
the
FR
sign
al
s
will
be
em
i
tt
ed
by
sensor
locat
ed
in
t
he
em
e
rg
e
ncy
veh
ic
le
.
A
fter
bein
g
detect
ed
,
the
traff
ic
li
gh
t
con
tr
oller
w
il
l
chan
ge
the
li
gh
t
dep
e
nd
on
it
s
pr
iority
that
is
assigne
d
t
o
e
m
erg
ency
ve
hicle
s.
The
wea
kn
e
ss
of
t
his
r
esearch
is
that
it
is
necessa
r
y
to
proce
ss
a
la
rge
a
m
ou
nt
of r
eal
-
tim
e traff
ic
da
ta
an
d t
im
e
-
con
su
m
ing
c
ontr
ol syst
em
s n
eed to be
f
ast
.
A
stu
dy
co
nd
ucted
by
Nell
or
eet
et
al
.
[
11]
us
e
WSN
t
o
pr
ov
i
de
a
ta
xonom
y
of
dif
fer
e
nt
traf
fic
con
t
ro
l
syst
em
schem
es
that
wer
e
us
ed
to
a
vo
i
d
traf
fic
co
ng
e
sti
on
on
th
e
ro
a
d
especial
ly
fo
r
the
em
er
gen
cy
veh
ic
le
s.
H
owever,
[
11
]
on
l
y
fo
c
us
on
t
he
traff
ic
c
on
t
ro
l
syst
e
m
fo
r
pri
or
it
y
base
d
on
sig
nalin
g,
re
du
ci
ng
congesti
on
an
d
the
aver
a
ge
w
ai
ti
ng
tim
e
(A
WT)
of
veh
ic
l
es
at
intersect
i
on.
The
se
nso
r
networ
k
co
ns
ist
s
of
two
el
em
ent
w
hich
a
re
t
he
se
ns
or nod
es
an
d
the g
at
eway n
od
e
s.
T
he
f
un
c
ti
on
o
f
t
he
se
nsor
node
is
to
m
on
it
or
traff
ic
co
ngest
ion
at
certai
n
area
by
m
easur
e
seve
ral
ph
y
sic
al
traff
ic
suc
h
as
de
ns
it
y,
vo
l
um
e
and
w
ai
ti
ng
tim
e. Th
e g
at
eway n
ote w
il
l coll
ect
all
the t
raffic
infor
m
at
i
on
from
all
the n
odes a
nd d
ire
ct
to
the b
ase
s
ta
ti
on.
As
a
res
ult
of
the
st
ud
y,
W
SN
ca
n
pro
vi
de
t
he
m
ob
il
ity
of
se
ns
ors
node
,
t
he
a
bili
t
y
to
withstan
d
ha
rs
h
env
i
ronm
ental
conditi
ons
an
d
lo
w
po
wer
consum
ption
.
The
d
isa
dvant
age
of
this
re
search
is
us
in
g
m
any
nodes
to
pr
oduce
m
or
e
eff
ic
ie
nt
cov
e
rag
e
and
c
oor
din
at
ion
betwee
n
no
des
with
ce
ntr
al
syst
e
m
s
is
a
m
ajo
r
pro
blem
.
Howe
ver,
unli
ke
Y
ousef
et
al
.
[12]
wh
ic
h
exp
la
in
s
that
WSN
can
be
us
e
d
for
an
a
da
ptive
traf
fic
li
gh
t
c
on
tr
ol
s
yst
e
m
especial
ly
for
si
ng
le
a
nd
m
ulti
ple
intersect
ion.
T
he
pur
po
se
of
us
i
ng
WSN
is
t
o
route
traff
ic
ba
sed
on
traf
fic
de
ns
it
y
and
wait
in
g
tim
e.
The
sens
ors
are
fitt
ed
on
each
r
oad
to
de
te
ct
the
pr
ese
nce
of
veh
ic
le
s
a
nd
to
store
t
he
wait
ing
tim
e
in
the
m
e
m
or
y.
The
n,
al
l
the
data
w
il
l
pr
ocess
by
t
he
intel
li
gen
t
t
raffic
con
t
ro
ll
er
bas
e
d
on
tw
o
al
go
rithm
s
Traf
fic
Syst
em
Co
m
m
un
ic
at
ion
Al
gorithm
(TSC
A)
w
hich
are
Traffic
Sign
al
Tim
e
M
anip
ulati
on
Al
gorithm
(TST
MA)
t
o
route
t
he
tra
ff
ic
va
riat
ion
s
of
al
l
la
n
es
of
inte
rsecti
on
s
at
a
par
ti
cula
r
ti
m
e
an
d
T
raffic
Con
tr
ol
Algor
it
h
m
on
Mult
iple
I
ntersecti
ons
(TCAM
I).
TSTMA
us
e
s
thre
e
te
chn
iq
ues
w
hi
ch
are
dy
nam
ic
sel
ect
ion
of
traf
fic
base
d
on
the
num
ber
of
la
nes
al
lo
wed
in
t
he
j
unct
io
n,
dynam
ic
adap
ta
ti
on
to
the
ch
a
ng
e
s
in
the
a
r
rival
an
d
dep
a
rtur
e
rates
an
d
la
stl
y
by
us
ing
dy
nam
ic
con
trol
of
traff
ic
cy
cl
e
ti
m
ing
the
tra
ff
i
c
li
gh
t
pe
rio
ds
.
TCAMI
us
es
to
co
ordinate
a
nd
set
ti
ng
s
of
traf
fic
pa
ram
et
e
rs
on
the
m
ult
iple
j
un
ct
io
ns.
The
resu
lt
s
of
the
stud
y
s
how
n
that
this
s
yst
em
had
a
bette
r
pe
rfor
m
ance
rate
i
n
m
anag
in
g
tra
ffi
c
com
par
ed
w
it
h
the
tradit
io
nal
traf
fic
li
gh
t
con
t
ro
l
syst
em
.
The
disad
va
nt
age
of
this
sys
tem
is
that
it
cann
ot
adjust
to
the
changin
g
tra
ff
i
c
sit
uation.
T
hen,
f
or
a
dap
t
ive
tim
e
con
trol,
the
du
rati
on
an
d
seq
uen
ce
of all
traf
fic phases
are
dynam
ic
.
Go
el
et
al
.
[13
]
furthe
r
s
upports
t
he
st
udy
cond
ucted
by
Youse
f
et
al
.
[
12
]
by
devel
opin
g
a
sm
art
traff
ic
li
ghti
ng
syst
e
m
to
pr
ioriti
ze
em
erg
ency
ve
hicle
ba
sed
on
WSN.
This
syst
em
w
orks
is
w
her
e
traff
ic
li
gh
ts
from
one
intersect
io
n
c
an
c
omm
un
ic
at
e
with
t
he
nea
rest
inter
sect
io
n
or
ne
xt
by
usi
ng
sens
ors
a
nd
t
hen
giv
in
g
pri
ori
ty
to
sp
eci
al
veh
i
cl
es
by
m
aking
traff
ic
cl
earan
ce.
W
S
N
can
be
us
ed
to
get
th
e
inform
ation
about
the
inc
om
ing
f
low
of
tra
ff
ic
,
traf
fic
loa
d
o
n
a
pa
rtic
ular
ro
a
d
a
nd
in
ve
hicle
pri
or
it
iz
at
ion.
T
hen,
WSN
c
an
be
instal
le
d
al
ong
a
r
oad
t
o
c
ontrol
the
tr
af
fic
load
on
the
r
oads
an
d
at
tr
aff
ic
inte
rsecti
on
s
.
T
hus,
t
he
sens
or
nodes
t
hat
are
fitt
ed
al
ong
t
he
ro
a
d
a
re
have
low
e
ne
rg
y
c
on
s
um
ption
a
nd
sm
al
l
in
siz
e
.
The
wea
knes
ses
of
this
te
chn
i
qu
e
is
the
routin
g
pro
blem
wh
ic
h
is
the
ta
sk
of
fin
ding
m
ulti
hop
path
f
r
om
a
sensor
node
to
th
e
base s
ta
ti
on.
Bhuva
nesw
a
ri
et
al
.
[1
4]
presents
the
tra
f
fic
co
ntro
l
sys
tem
Ad
aptive
Sign
al
T
raffic
us
in
g
the
W
i
reless
Se
nsors
Netw
ork
(
ATSWS
N).
H
ow
e
ve
r,
it
is
di
ff
e
ren
t from
[1
2]
base
d
on
t
he
tim
e
slot
al
loc
at
ed
f
or
each
r
ou
te
no
t
fo
c
us
in
g
on
tr
aff
ic
de
ns
it
y
but
al
so
on
em
e
rg
e
ncy
sit
uatio
ns
an
d
s
peed
pa
tt
ern
s.
T
his
s
yst
e
m
us
es
a
n
I
nfra
-
r
ed
(
IR)
se
ns
or
to
colle
ct
real
-
tim
e
data
and
m
ic
ro
co
ntro
ll
e
r
al
gorithm
s
to
process
data
and
t
hen
decide
w
hic
h
directi
on
to
ge
t
gr
een
li
ght
prefere
nces.
T
he
resu
lt
s
of
t
he
stud
y
sho
w
tha
t
ATSWSN
re
gister
s
the
highe
r
traf
f
ic
flow
rate
an
d
pr
oduce
the
l
ow
e
r
a
ver
a
ge
wait
ing
ti
m
e.
So
m
et
i
m
es,
th
e
sens
or
nodes
are
i
n
sle
ep
m
od
e
or
switc
hed
off
wh
e
n
not
in
operati
on
is
a
weakness
of
this
te
chn
i
qu
e
.
Table
2
sh
ows
the
su
m
m
ary fo
r
t
he WS
N
te
ch
ni
qu
e
s
based the
ref
e
ren
ces
, pr
opose
d ap
proac
h,
a
dvanta
ges
a
nd d
isa
dvanta
ge
s.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Revi
ew
o
f t
ra
ff
ic
co
ntr
ol tech
niques f
or
e
me
rg
e
ncy ve
hicle
s (Wan M
ohd Ha
fi
z
bin Wa
n Hu
s
sin)
1247
Table
2
.
Su
m
m
ary f
or
WSN T
echn
i
qu
e
s
Ref
erences
Prop
o
sed
App
roach
Ad
v
an
tag
es
Disad
v
an
tag
es
S
h
r
u
t
h
i
e
t
a
l
.
[1
0
]
W
SN
T
ec
h
n
i
q
u
e
C
o
n
t
r
o
l
s
i
n
g
l
e
a
n
d
m
u
lt
i
p
le
i
n
t
e
r
se
c
t
i
o
n
.
-
P
r
o
c
e
ss
a
l
a
r
g
e
am
o
u
n
t
o
f
r
e
a
l
-
t
im
e
tr
a
ff
i
c
d
a
ta
a
n
d
t
i
m
e
-
c
o
n
s
u
m
i
n
g
c
o
n
tr
o
l
s
y
s
te
m
s
n
ee
d
t
o
b
e
fa
s
t.
N
e
l
l
o
r
e
et
et
al
.
[1
1
]
W
SN
T
ec
h
n
i
q
u
e
P
r
o
v
i
d
e
t
h
e
m
o
b
i
li
ty
o
f
s
e
n
s
o
r
s
n
o
d
e
a
n
d
l
o
w
p
o
w
er
c
o
n
s
u
m
p
t
i
o
n
.
-
U
s
i
n
g
m
an
y
n
o
d
e
s
t
o
p
r
o
d
u
c
e
m
o
re
e
ff
i
c
i
e
n
t
c
o
v
e
r
a
g
e
a
n
d
c
o
o
r
d
i
n
a
t
i
o
n
b
e
t
we
e
n
n
o
d
e
s
w
i
t
h
c
e
n
t
ra
l
s
y
st
e
m
s
i
s
a
m
a
j
o
r
p
r
o
b
l
em
.
Y
o
u
s
e
f
e
t
a
l.
[1
2
]
W
SN
T
ec
h
n
i
q
u
e
C
o
n
t
r
o
l
s
i
n
g
l
e
a
n
d
m
u
lt
i
p
le
i
n
t
e
r
se
c
t
i
o
n
.
-
C
a
n
n
o
t
a
d
j
u
s
t
t
o
t
h
e
c
h
a
n
g
i
n
g
t
r
a
ff
i
c
si
t
u
a
t
i
o
n
.
G
o
e
l
e
t
a
l
.
[1
3
]
W
SN
T
ec
h
n
i
q
u
e
C
a
n
b
e
u
s
e
d
t
o
g
et
t
h
e
i
n
fo
r
m
at
i
o
n
a
b
o
u
t
t
h
e
i
n
c
o
m
i
n
g
fl
o
w
o
f
t
ra
ff
i
c
a
n
d
t
ra
ff
i
c
l
o
a
d
o
n
a
p
ar
t
i
c
u
la
r
r
o
a
d
.
-
R
o
u
t
i
n
g
p
r
o
b
l
em
w
h
i
c
h
i
s
t
h
e
t
a
s
k
o
f
fi
n
d
i
n
g
m
u
l
t
i
h
o
p
p
a
t
h
fr
o
m
a
se
n
s
o
r
n
o
d
e
t
o
t
h
e
b
a
s
e
s
t
a
t
i
o
n
.
B
h
u
v
a
n
e
s
w
ar
i
et
a
l
.
[1
4
]
W
SN
T
ec
h
n
i
q
u
e
C
o
n
t
r
o
l
s
i
n
g
l
e
a
n
d
m
u
lt
i
p
le
i
n
t
e
r
se
c
t
i
o
n
.
-
S
o
m
et
i
m
e
s,
t
h
e
s
en
s
o
r
n
o
d
e
s
a
r
e
i
n
s
l
e
e
p
m
o
d
e
o
r
s
w
i
t
c
h
e
d
o
ff
w
h
e
n
n
o
t
i
n
o
p
e
ra
t
io
n
4.3.
Ima
ge
Pr
ocess
ing
Anothe
r
te
ch
ni
qu
e
t
hat
can
be
us
e
d
to
c
on
t
ro
l
tra
ff
ic
c
ongestio
ns
is
to
us
e
a
n
im
age
processi
ng
appr
oach.
Ba
sic
al
ly
,
i
m
age
processin
g
is
a
te
chn
i
qu
e
t
o
en
han
ce
a
raw
i
m
age
that
rece
ived
f
r
om
senso
rs
or
ca
m
era.
A
dd
it
ion
al
ly
,
it
is
al
so
reli
able
to
es
tim
a
te
the
pr
es
ence
of
ve
hicle
s
for
us
i
ng
ac
tual
traff
ic
im
a
ges
.
So
,
im
age
pro
cessi
ng
can
be
cl
assifi
ed
as
a
good
te
c
hn
i
qu
e
f
or
co
ntr
ol
li
ng
the
cha
nge
of
the
sta
te
of
the
traff
ic
li
ght.
Chan
dr
a
sek
har
et
al
.
[1
5]
pro
pose
a
syst
e
m
to
con
tr
ol
traff
ic
co
ng
e
sti
on
us
i
ng
dig
it
al
i
m
age
processi
ng.
Th
e
veh
ic
le
is
detect
ed
by
the
syst
e
m
thro
ugh
the
use
of
el
ect
ro
nic
sen
s
or
s
em
bed
de
d
in
the
pav
em
ent.
T
he
cam
era
will
be
fitt
ed
with
a
traf
fic
li
gh
t
t
o
ca
pture
the
im
age
seq
ue
nc
e.
T
hen,
the
im
ages
captu
red
i
n
suc
cessi
on
a
re
m
at
ched
us
i
ng
i
m
age
m
at
chi
ng
with
a
re
fe
ren
ce
im
age
t
hat
is
an
em
pt
y
ro
a
d
i
m
age.
Traffic
is
con
tr
olled
a
ccordin
g
to
the
cor
re
spo
nd
i
ng
per
ce
ntage.
F
or
em
erg
ency
veh
ic
le
s,
the
a
naly
sis
is
cal
culat
ed
ba
sed
on
a
flas
hing
red
li
ght.
The
di
sa
dvant
ages
of
this
te
chn
i
qu
e
are
to
pe
rfor
m
m
or
e
im
age
processi
ng proc
esses to
prod
uc
e good im
age
qu
al
it
y f
or
t
he dete
ct
ion o
f
e
m
erg
ency
ve
hicle
s.
Jad
hav
et
al
.
[1
6]
dem
on
stra
te
d
a
s
m
art
tra
ff
ic
co
ntr
ol
syst
e
m
us
ing
i
m
age
proces
sin
g.
The
stu
dy
was
co
nduct
e
d
us
in
g
Ma
tl
ab
so
ftwa
re
an
d
the
m
ai
n
pu
r
pose
was
to
pr
e
ven
t
he
avy
tra
ff
ic
on
the
r
oa
d.
I
n
add
it
io
n,
this
s
tud
y
us
e
s
im
ag
e
processin
g
te
chn
i
qu
e
s.
T
he
web
cam
era
is
locat
ed
in
the
t
raffic
la
ne
that
will
captu
re
the
str
eet
i
m
age.
The
n,
t
hese
im
ages
are
proce
s
se
d
e
ff
ic
ie
ntly
to
determ
ine
traf
fic
de
ns
it
y.
Ba
sed
on
data
process
ed
from
Matla
b,
the
co
ntr
oller
w
il
l
send
instr
uc
ti
on
s
to
LE
D
tr
aff
ic
to
in
dicat
e
a
sp
eci
fic
ti
m
e
on
the
sig
nal
to
m
anag
e
traf
fic.
This
re
searc
h
i
s
giv
e
n
t
o
a
ce
rtai
n
r
oa
dw
ay
li
gh
t
acco
r
din
g
to
tra
ff
ic
dens
it
y
on
the
ro
a
d
with
pri
or
it
y
giv
e
n
to
the
a
m
bu
la
nce
based
on
flash
ing
re
d
li
ght.
T
he
disa
dv
a
ntag
e
of
this
te
ch
ni
que
is
to
us
e
im
age
processi
ng
an
d
Ma
tl
ab
s
of
t
w
are
to
process
im
ages
that
wil
l
cause
m
uch
work
to
be
done
an
d
cost inc
reases.
Kaur
et
al
.
[17
]
al
so
pr
ese
nt
a
traff
ic
m
anag
em
ent
app
li
cat
ion
us
i
ng
digi
ta
l
i
m
age
pro
cessi
ng.
Th
e
m
et
ho
dolo
gy
ha
s
bee
n
us
e
d
a
re
al
m
os
t
the
s
a
m
e
with
[
15
]
,
[
16]
by
us
i
ng
ca
m
era.
T
he
c
a
m
era
is
fitt
ed
on
a
long
pill
ar
fro
m
wh
ere
the
la
ne
view
can
be
ta
ken
ver
y
cl
early
.
The
funct
ion
of
the
cam
era
is
to
ta
ke
i
m
ages
or
vid
e
os
of
t
he
la
ne
to
c
hec
k
out
the
t
raffic
at
any
instan
t
on
t
he
la
ne.
The
im
ages
that
captur
e
d
by
ca
m
era
will
be
process
ed
us
i
ng
im
age
processin
g
te
c
hn
i
qu
e
s
an
d
th
e
nu
m
ber
of
th
e
veh
ic
le
s
on
e
ach
la
ne
is
co
unte
d.
Howe
ver,
the
tim
e
is
assigned
to
traf
fic
li
ght
on
eac
h
la
ne
accor
ding
to
th
e
count
or
the
densi
ty
of
ve
hi
cl
e
on
that
ro
a
d
with
pr
i
or
it
y
giv
e
n
t
o
em
erg
enc
y
veh
ic
le
s.
E
m
erg
ency
vehi
cl
es
is
detect
ed
by
den
sit
y
of
th
e
flashin
g
re
d
li
gh
t.
A
s
a
res
ul
t,
by
us
in
g
m
ulti
ple
seq
ue
ntial
ca
m
eras
wi
ll
help
t
o
inc
r
ease
the
a
naly
sis
of
traff
ic
c
onge
sti
on
on
the
r
oad.
T
he
disad
va
nt
age
of
t
his
te
c
hn
i
qu
e
is
to
use
a
m
ulti
ple
of
seq
ue
ntial
cam
eras
that wil
l cause
high
pr
ic
es a
nd
h
ig
h
m
ai
ntena
nce.
Syawal
udin
e
t
al
.
[18]
m
ade
fu
rt
her
s
uppo
rt
by
us
in
g
co
m
bin
at
ion
of
HSV
colo
r
s
pa
ce
and
R
GB
colo
r
sp
ace
te
chn
i
qu
e
f
or
intel
li
gen
t
traff
ic
li
gh
t
syst
e
m
to
detect
e
merg
e
ncy
veh
ic
l
es.
The
ai
m
s
of
thi
s
researc
h
is
to
de
velo
p
a
syst
e
m
that
can
co
nt
ro
l
the
tra
ff
ic
li
gh
t
f
or
a
ny
e
m
erg
ency
veh
i
cl
es
to
pass
thr
ough
a
ro
a
d
intersect
i
on
sm
oo
thly
and
in
directl
y
that
will
m
ake
the
e
m
erg
ency
veh
ic
le
s
reac
h
the
em
erg
en
cy
sit
e
faster,
he
nce
m
any
li
ves
ca
n
be
safe.
T
hi
s
research
al
so
us
es
im
age
pr
oce
ssin
g
te
chn
i
qu
e
s
to
detect
e
m
erg
ency
ve
hicle
s.
The
re
aso
n
w
hy
us
i
ng
H
SV
c
olor
sp
ace
a
nd
R
G
B
color
is
to
analy
ze
the
li
gh
t
of
e
m
erg
ency
ve
hi
cl
es
and
pro
duce
m
or
e
acc
urat
e
detect
io
n
of
em
erg
e
ncy
veh
ic
le
s.
The
ca
m
era
is
fitt
ed
at
the
intersect
io
n
an
d
the
n
the
im
a
ge
will
co
nvert
to
f
ram
e
by
fra
m
e
of
im
ages.
The
im
ages
pr
oces
sin
g
te
ch
niques
can
be
a
ppli
ed
to
detect
the
e
m
erg
ency
ve
hicle
s
from
al
l
t
he
ve
hicle
s
on
the
r
oa
d
from
t
he
fr
am
e
of
im
ages
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
1
3
, N
o.
3
,
Ma
rc
h
201
9
:
1
2
4
3
–
1
2
5
1
1248
The
dif
fer
e
nce
of
em
erg
ency
veh
ic
le
s
with
oth
er
ve
hicle
s
is
the
e
m
erg
ency
li
gh
t
on
tho
se
ve
hicle
s.
The
disad
va
ntage
of
this
te
chn
i
que
is
to
us
e
a
lot
of
cam
eras
to
process
photo
s
to
get
cl
ear
i
m
ages
an
d
cau
se
cost
increases
.
The
st
ud
y
c
ondu
ct
e
d
by
Gai
kw
a
d
et
al
.
[
19]
on
im
age
pro
cessi
ng
base
d
t
raffic
li
gh
t
c
ontrol
is
ai
m
s
to prev
e
nt h
ea
vy traf
fic
co
ngest
ion
on
t
he
r
oad. T
his stu
dy
also u
se Mat
la
b
s
of
twa
re to
i
m
ple
m
ent the system
.
It
does
no
t
act
ually
m
easur
e
the
num
ber
of
veh
ic
le
s
that
present
on
the
r
oad
but
it
m
ea
su
res
the
a
rea
cov
e
re
d
by
ve
hicle
s
on
the
ro
a
d.
Om
kar
Ra
m
das
Gaikw
a
d
et
al
appl
ie
d
t
hr
ee
ste
ps
to
i
m
ple
m
ent
this
stud
y
w
hic
h
ar
e
i
m
age
acq
uisit
ion
,
RGB
to
gray
scal
e
tran
sf
or
m
at
ion
an
d
la
stl
y
i
m
age
e
nh
a
ncem
ent.
T
he
key
po
i
nt
of
the
stud
y
is
it
us
e
d
web
cam
era
wh
ic
h
fitt
ed
in
a
tra
ff
ic
la
ne
that
will
capt
ure
the
im
age.
The
n,
t
he
im
a
ges
a
r
e
eff
ic
ie
ntly
p
r
oc
essed
to kn
ow
the traff
ic
d
e
nsi
ty
. Th
e Ma
tl
a
b
will
p
r
ocess
the d
at
a an
d
the
co
ntr
oller w
il
l sen
d
the
com
m
and
to
the
tim
er
t
o
sho
w
pa
rtic
ular
tim
e
on
the
sig
nal
to
m
anag
e
traf
fic
.
For
the
em
e
rg
e
ncy
veh
ic
le
s,
it
al
so
giv
e
pri
or
it
y
base
d
on
fl
as
hin
g
re
d
li
ght.
T
he
disad
va
ntag
es
of
this
te
ch
ni
qu
e
a
re
necess
ary
to
get
a
cl
ear
i
m
age
from
the
best
qual
it
y
c
a
m
eras
befor
e
processin
g
th
e
i
m
age
and
pro
du
ce
good
resu
lt
s
.
Table
3
sho
ws
the
su
m
m
ary
for
the
i
m
age
processi
ng
te
c
hn
i
qu
e
s
base
d
the
ref
e
ren
ce
s,
propose
d
ap
proac
h,
adv
a
ntage
s a
nd d
isa
dv
a
ntages
.
Table
3
.
Su
m
m
ary
f
or I
m
age P
rocessi
ng Tec
hn
i
qu
e
s
Ref
erences
Prop
o
sed
App
roach
Ad
v
an
tag
es
Disad
v
an
tag
es
Ch
an
d
rasekh
ar
et
al.
[
1
5
]
Dig
ital I
m
ag
e P
rocess
in
g
Si
m
p
le
to
ad
d
an
d
ch
an
g
e
d
etectio
n
ar
eas.
Perf
o
r
m
m
o
r
e
i
m
ag
e
p
rocess
in
g
p
rocess
es
to
p
rod
u
ce
g
o
o
d
i
m
ag
e
q
u
ality
f
o
r
th
e
d
etectio
n
o
f
e
m
ergen
c
y
veh
icle
s.
Jad
h
av
et
al.
[
1
6
]
Dig
ital I
m
ag
e P
rocess
in
g
Mon
ito
rs
m
u
ltip
le
lan
es.
Proces
s
i
m
ag
es
t
h
at
will
caus
ed
m
u
ch
wo
rk
to
b
e
d
o
n
e
an
d
co
st
in
crea
ses
.
Kau
r
et
al.
[
1
7
]
Dig
ital I
m
ag
e P
rocess
in
g
Of
f
ers broad
ar
ea
d
etectio
n
.
Use
a
m
u
ltip
le
o
f
seq
u
en
tial
ca
m
e
ras
th
at
wi
ll
caus
e
h
ig
h
p
rices a
n
d
hig
h
m
a
in
ten
an
ce.
Sy
awalud
in
et
al.
[
1
8
]
Dig
ital
I
m
ag
e
Proces
sin
g
(Co
m
b
in
atio
n
o
f
HSV
co
lo
r
sp
ace
an
d
RGB
c
o
lo
r
sp
ace
tech
n
iq
u
e)
To
an
aly
ze
th
e
lig
h
t
o
f
e
m
e
rgen
cy
v
eh
icles
an
d
p
rod
u
ce
m
o
re
accurate
d
ete
ctio
n
o
f
e
m
ergen
cy
v
eh
icles.
Use
a
lo
t
o
f
ca
m
eras
to
p
rocess
p
h
o
to
s
to
g
et
clear
i
m
ag
es
an
d
co
st in
crea
ses
.
Gaik
wad
et
al
.
[
1
9
]
Dig
ital I
m
ag
e P
rocess
in
g
Si
m
p
le
to
ad
d
an
d
ch
an
g
e
d
etectio
n
ar
eas.
Perf
o
r
m
an
ce
is
s
en
sitiv
e
to
b
a
d
weather,
v
eh
icles
sh
ad
o
ws
an
d
d
u
sts
on
the ca
m
er
a lens
.
5.
PROP
OSE
D MET
HO
D
Ba
sed
on
the
r
eviewe
d
li
te
ratur
es
,
it
can
be
con
cl
ud
e
d
that
RFID
te
ch
nique
is
the
best
te
chn
i
qu
e
to
i
m
ple
m
ent
a
sm
art
traff
ic
li
gh
t
co
ntr
ol
syst
e
m
especial
ly
fo
r
em
erg
ency
ve
hicle
s
beca
us
e
of
lo
w
m
ai
ntenan
ce,
l
ow
pr
ic
e
an
d
c
an
be
use
d
in
var
i
ou
s
a
reas
of
ap
plica
ti
on
s.
Ba
sed
on
RFI
D'
s
li
te
ratur
e
rev
ie
ws
ind
ic
at
e
po
sit
iv
e res
ults w
he
n app
li
ed
it
on t
he
syst
e
m
.
In
Ma
la
ysi
a,
w
her
e
the
ec
onom
ic
sit
uation
i
s
in
t
he
sta
ge
of
dev
el
op
m
ent
and
co
ntr
ol
of
the
existi
ng
traff
ic
li
ght
is
not
en
ough
t
o
c
on
tr
ol
the
increasi
ng
of
ve
hicle
.
T
her
e
f
or
e
,
this
pro
posed
m
et
ho
d
ta
kes
al
l
consi
der
at
io
n
base
d
on
the
pro
blem
s
that
occu
r
to
im
pr
ove
the
exis
ti
ng
tra
ff
ic
li
ght
con
trol
syst
em
fo
r
e
m
erg
ency
ve
hi
cl
es.
The
m
ai
n
pur
po
s
e
of
this
pa
per
is
t
o
pr
ovide
cl
ear
pat
hs
to
em
erg
e
nc
y
veh
ic
le
s
a
nd
the
n
tra
ff
ic
sign
al
s
sho
uld
switc
h
aut
oma
ti
cal
ly
to
give
way
t
o
the
e
m
erg
ency
ve
hicle
s.
In
the
pro
po
se
d
m
et
ho
d,
th
e
desig
n
f
or
this
syst
e
m
is
div
id
ed
in
three
sys
tem
s.
Firstl
y,
i
s
fitt
ed
in
an
em
erg
ency
ve
hi
cl
e
and
kn
own
as
an
Em
erg
ency
Ve
hicle
s
Syst
em
(
EVS).
Sec
ondl
y,
is
fitt
ed
at
traff
ic
li
ght
jun
c
ti
on
a
nd
know
n
as
T
raffic
Junct
i
on
Syst
e
m
(TJS
).
Last
ly
,
known
as
Ba
se
Stat
i
on
Syst
em
(BSS)
.
T
hese
t
hree
syst
e
m
s
need
to
com
m
un
ic
at
e
to
each
oth
e
r.
Th
e f
ur
the
r deta
il
s to
e
xpla
in a
bout t
hese t
hr
ee
syst
e
m
s as b
el
ow
:
5.1.
Eme
rgenc
y V
ehic
le
s Sy
s
tem
(
EV
S)
The
el
em
ents
that
sh
ould
hav
e
f
or
th
e
e
m
erg
ency
veh
ic
le
s
syst
e
m
is
RFID
ta
g,
G
P
S,
m
ic
ro
co
ntro
ll
e
r,
Zi
gb
ee
,
po
w
er
sup
ply,
G
S
M
and
LCD
di
sp
la
y.
T
his
el
em
ent
play
an
i
m
po
rtant
r
ole
to
E
VS
.
The
f
unct
ion
of
RFI
D
ta
g
is
to
sto
re
al
l
the
inf
or
m
at
ion
ab
ou
t
veh
ic
le
s
s
uc
h
as
ve
hicle
’s
reg
ist
rati
on
num
ber
and
ty
pe
of
ve
hicle
s.
The
G
PS
will
be
give
n
an
inf
orm
ation
the
locat
io
n
of
the
em
erg
ency
ve
hicle
s
.
The
m
ic
ro
co
ntro
ll
e
r
cal
culat
es
the
directi
on
of
th
e
e
m
erg
ency
ve
hicle
s
by
us
i
ng
G
PS
a
nd
t
he
n
se
nd
t
he
sig
na
l
to
traff
ic
jun
ct
i
on
syst
e
m
to
cha
ng
e
the
sig
nal
from
red
to
green.
The
m
ic
r
ocontr
oller
is
play
s
m
ajo
r
rol
e.
It
i
s
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Revi
ew
o
f t
ra
ff
ic
co
ntr
ol tech
niques f
or
e
me
rg
e
ncy ve
hicle
s (Wan M
ohd Ha
fi
z
bin Wa
n Hu
s
sin)
12
49
us
e
d
as
a
com
pone
nt
in
com
plica
te
d
proce
ss
con
t
ro
l
syst
e
m
.
The
funct
ion
of
LCD
is
us
ed
to
disp
l
ay
the
inf
or
m
at
ion
abou
t t
he
c
urren
t
process
. T
o
il
lustrate
this
, c
onside
r
Fi
gure
1
show
s the
com
po
nen
t
for
E
VS
.
Figure
1.
Com
pone
nt for E
V
S
5.2.
Tr
affic J
unct
i
on
Sy
s
tem
(TJS)
The
m
ai
n
el
em
ents
f
or
th
e
tra
ff
ic
jun
ct
io
n
syst
e
m
is
RFID
r
eader
,
m
ic
ro
co
ntr
oller, pow
e
r
sup
ply
an
d
Zigb
ee
.
T
he
f
un
ct
io
n
of
RF
ID
rea
der
is
t
o
rea
d
t
he
in
f
or
m
at
ion
from
RFID
ta
g
a
nd
the
R
FID
re
ader
is
instal
le
d
at
the
traf
fic
li
gh
t
ju
nction.
T
he
functi
on
of
pow
er
s
upply
is
to
pro
vid
e
the
c
urren
t
t
o
the
s
yst
e
m
.
Zigb
ee
is
a
wir
el
ess
te
chnolo
gy
that
was
gu
ided
by
IEE
E
802.1
5.4
pe
rs
onal
area
netw
ork
sta
nd
a
r
d
(
W
PAN).
It
is
us
ed
to
wide
ra
ng
i
ng
con
t
ro
ll
in
g
a
nd
rep
la
ce
the
existi
ng
no
n
-
st
and
a
r
d
te
ch
nolog
ie
s
.
On
ce
t
he
RFI
D
read
e
r
recei
ve
the
data
an
d
th
en
sen
d
in
t
o
the
m
ic
ro
con
tr
ol
le
r.
The
m
ic
ro
con
t
ro
ll
er
proc
ess
the
data
a
nd
gi
ve
the
inst
ru
ct
io
n
that
the
la
ne
on
w
hich
em
erg
ency
ve
hicle
s
is
com
ing
,
the
n
tu
r
n
the
gr
ee
n
c
olor
on
that
la
ne.
To
il
lustrate
t
hi
s,
co
ns
ide
r
Fig
ur
e
2
sho
ws
t
he
co
m
po
ne
nt
f
or TJS.
Figure
2.
Com
pone
nt for TJS
5.3.
Base S
tatio
n Syste
m (
BS
S)
The
f
un
ct
io
n
of
BSS
is
to
co
ntr
ol
and
sto
re
al
l
inform
at
io
n
ab
ou
t
ve
hicl
e’s
m
ov
e
m
ent.
The
GS
M
will
be
use
d
f
or
receive
a
nd
sen
d
m
essages.
To
il
lustrate
this,
c
on
si
de
r
Fig
ure
3
shows
the
c
om
po
ne
nt
for
BSS
.
Figure
3.
Com
pone
nt for B
S
S
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
1
3
, N
o.
3
,
Ma
rc
h
201
9
:
1
2
4
3
–
1
2
5
1
1250
6.
DISCU
SSI
ON
The
resear
ch
pro
blem
is
there
are
tra
ff
ic
co
ngest
io
n
occurr
ed
e
ver
y
day
on
the
r
oa
ds
.
So,
the
pe
opl
e
hav
e
to
wait
for
a
l
ong
tim
e
on
the
tra
ff
ic
c
onge
sti
on.
It
m
a
y
cause
dif
ficu
lt
y
fo
r
em
erg
ency
ve
hicle
s
t
o
pas
s
thr
ough
the
in
te
rsecti
on
with
traff
ic
li
ght.
So
m
e
interrupt
ion
s
a
re
po
s
sible
over
with
the
r
oad
us
e
rs.
It
is
because
the
ro
ad user
s
need to c
om
pr
om
ise
with this
sit
uat
ion
t
o protec
t s
om
eon
e’s
li
fe
.
The
ideal
way
to
pr
op
os
e
th
e
best
te
chn
iq
ue
is
to
rev
ie
w
the
li
te
rature
on
the
rele
va
nt
te
chn
iq
ues
us
e
d
to
c
on
t
rol
traff
ic
li
ghts
especial
ly
for
e
m
erg
ency
ve
hicle
s.
F
or
eac
h
te
ch
nique,
fi
ve
pre
vious
st
ud
ie
s
hav
e
b
ee
n revi
ewed. T
hen, th
e com
par
iso
ns
wer
e m
ade b
a
s
ed on
t
he result
s of eac
h
stu
dy
, th
e a
dvanta
ge
s and
the d
isa
dvanta
ges of ea
ch
tec
hn
i
qu
e
.
RFID
is
the b
e
st
te
chn
iq
ue
co
m
par
ed
to
oth
e
r
te
chn
i
ques
be
cause
of
lo
w
pri
ce,
low
m
ai
ntenan
ce a
nd
can
be
us
e
d
i
n
va
rio
us
a
rea
s
of
a
ppli
cat
ion
s
s
uch
a
s
m
i
l
it
ary,
m
edical
sci
ence,
c
ommerce,
el
ect
r
on
i
c
toll
colle
ct
ion
syst
e
m
s
and
so
on.
For
exam
ple,
RFI
D
te
chn
i
qu
e
c
a
n
be
con
side
re
d
as
a
low
pr
ic
e
for
com
m
un
ic
at
ion
beca
us
e
it
can
pro
vid
e
uninterr
upte
d
c
om
m
un
ic
at
ion
to
the
net
wor
k
even
in
ba
d
weathe
r
com
par
ed
t
o u
ns
ta
ble
WSN
duri
ng b
a
d weat
her [
20
]
.
A
stu
dy
c
ondu
ct
ed
by
C
hitt
a
et
al
.
[9
]
hav
e
pro
po
se
d
RF
I
D
te
ch
nique
as
the
be
st
te
ch
niq
ue
to
s
olv
e
traff
ic
li
ght
pr
ob
le
m
s
fo
r
em
erg
e
ncy
ve
hicle
s.
This
is
bec
ause
the
i
nteg
r
at
ion
be
twee
n
RFID
a
nd
G
S
M
and
In
te
r
net
te
ch
no
log
ie
s
ca
n
pro
du
ce
a
great
r
evo
l
ution
f
or
s
m
art
traff
ic
c
ontr
ol
syst
e
m
s.
The
syst
em
ca
n
al
so
store
da
ta
that
can
be
use
d
by
op
e
rato
rs
a
nd
plan
ners
to
i
m
pr
ov
e
t
he
syst
e
m
in
the
fu
t
ur
e.
Additi
onal
ly
,
syst
e
m
s
dev
el
op
e
d
by
Chit
ta
et
al
.
[9
]
pro
vid
e
go
od
resu
lt
s
w
hile
reducin
g
cos
ts
and
m
ini
m
iz
in
g
m
ai
ntenan
ce.
7.
CONCL
US
I
O
N
As
a
c
on
cl
us
io
n,
t
he
im
ple
m
e
ntati
on
of
sm
art
te
chnolo
gy
i
n
the
t
ran
s
portat
ion
syst
em
can
pro
duce
a
gr
eat
im
pact
on
traf
fic
le
vels
especial
ly
fo
r
the
em
erg
ency
veh
ic
le
s.
This
pap
e
r
rev
ie
ws
the
li
te
ratur
e
on
t
he
releva
nt
te
chn
i
qu
e
s
us
e
d
to
c
on
t
ro
l
traf
fic
li
gh
ts
to
pro
vide
a
cl
ear
path
to
the
em
erg
en
c
y
veh
ic
le
s
an
d
will
m
ake
the
em
erg
ency
ve
hicle
s
reach
the
em
erg
e
ncy
sit
e
fas
te
r.
T
his
pa
per
al
so
c
om
par
es
the
te
ch
niques
us
e
d
to contr
ol tra
ff
i
c li
gh
t s
uc
h
as
RFID, im
age pro
ces
sin
g
a
nd
WSN.
The
fin
ding
of
this
pa
pe
r
in
di
cat
es
that
RFI
D
is
the
best
t
echn
i
qu
e
to
c
ontr
ol
the
tra
ff
i
c
li
gh
t
f
or
e
m
erg
ency
ve
hicle
s.
As
a
f
ut
ur
e
work,
the
RFID
te
c
hn
i
qu
e
al
so
can
be
us
e
d
on
VVIP
veh
ic
le
s
a
nd
m
il
it
ary
conv
oys
to
av
oid
getti
ng
stu
ck
in
the
tra
ff
i
c
congesti
on.
Othe
r
than
t
ha
t,
it
can
giv
e
r
esearche
rs
the
idea
o
f
dev
el
op
i
ng a s
m
art syst
e
m
to
con
t
ro
l
ro
a
d
t
r
aff
ic
in
the
futur
e
.
ACKN
OWLE
DGE
MENT
The
aut
hors
w
ou
l
d
li
ke
to
th
ank
t
he
U
niv
e
rsiti
Teknolo
gi
Ma
ra
for
thei
r
fina
ncial
sup
port
to
this
pro
j
ect
un
der
BESTAR
I Gra
nt No.
600
-
IR
MI/PER
D
ANA 5/3 BE
S
T
A
RI (1
05
/
2018)
.
REFERE
NCE
S
[1]
Malay
s
ia
Autom
at
iv
e
As
socia
t
io
n,
“
Summ
ar
y
of
Sale
s
&
Produc
ti
on
Dat
a
MA
A
News
le
tt
er
Augus
t
2017,
”
Ku
ala
Lumpur,
2017.
[2]
K.
Sangee
th
a,
e
t
al.
,
“
Autom
at
ic
Am
bula
nce
R
e
scue
w
it
h
In
te
l
li
gent
Tra
ff
ic
L
ight
S
y
st
em,”
I
OSR
Journal
of
Engi
ne
ering
,
vol
/i
ss
ue:
4
(
2
)
,
pp
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–
57,
2014
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[3]
htt
p://ww
w
-
05.
i
bm
.
com/za
/off
ice/pdf
/IBM
-
A V
ision
for a
Sm
arter
Ci
t
y
–
Nair
obi
.
pdf.
[4]
htt
p://ww
w.i
m
pinj
.
com/re
sour
ce
s
/a
bout
-
rf
id
-
ho
wdorfids
y
stems
work.
[5]
K.
Athava
n
,
et
al.
,
“
Autom
at
i
c
Am
bula
nce
Res
cue
S
y
st
em,”
20
12
Sec
ond
Int
e
rnational
Conf
ere
nce
on
Adv
an
c
ed
Computing
&
C
omm
unic
ati
on
T
ec
hnolog
ie
s
,
201
2.
[6]
S
.
Sharm
a,
et
a
l
.
,
“
Tra
ff
ic
Li
ght
Priority
Contro
l
f
or
Emerge
n
c
y
Vehic
l
e
Us
ing
RF
ID,”
Inte
rnat
ional
Journal
of
Innov
ati
on
in En
gine
ering
and
T
ec
hnolog
y
(
IJI
E
T)
,
v
ol
/i
ss
ue:
2
(
2
)
,
2013
.
[7]
T.
N
.
R
aj
u
,
e
t
al.
,
“
Sm
art
Traffic
L
ight
Con
t
rol
S
y
st
em
for
Emerge
nc
y
and
Detect
ion
of
Stole
n
Veh
ic
l
es,
”
Inte
rnational
Jo
urnal
of Adv
an
c
ed
R
ese
arch
in
S
ci
en
ce,
Eng
ineering
and
Te
chnology
,
v
ol
/i
ss
ue:
1
(
5
)
,
2014
.
[8]
D.
As
wani,
“
Sm
art
Tra
ff
ic
Con
tr
ol
S
y
st
em
for
E
m
erg
ency
Veh
icle
C
le
ar
ance,”
I
nte
rnational
Jou
rnal
&
Magazin
e
of
Eng
ine
ering
,
Technol
ogy
,
Ma
nageme
nt
and
R
ese
arch
,
v
ol
.
3,
2016.
[9]
A
.
S
.
Chit
ta
and
Dinesha
P
.
,
“
Pr
iori
t
y
Mana
g
ement
of
Emerge
nc
y
Vehicle
s
Us
ing
IOT
Approac
h,
”
Inte
rnat
ional
Journal
o
f
Ad
va
nce
d
Re
search
i
n
Computer
and
Comm
unic
ati
on
Engi
ne
ering
,
v
ol
/i
ss
ue:
5
(
9
)
,
201
6.
[10]
Shruthi
K
.
R
.
and
Vinodha
K
.
,
“
Priority
Base
d
Tra
ffic
L
ight
s
Control
le
r
Us
ing
W
ire
le
ss
Sensor
Networks,”
Inte
rnational
Jo
urnal
of El
e
ct
ro
nic
s Si
gna
ls and
Syste
ms
(
IJE
SS)
,
v
ol
/i
ss
ue:
1
(
4
)
,
2012.
[11]
K
.
Nell
or
e
and
G
.
P.
Han
cke
,
“
A
Surve
y
on
Ur
ban
Tr
aff
i
c
Man
age
m
ent
S
y
stem
Us
ing
W
ire
le
ss
Sensor
Networks,”
2016.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Revi
ew
o
f t
ra
ff
ic
co
ntr
ol tech
niques f
or
e
me
rg
e
ncy ve
hicle
s (Wan M
ohd Ha
fi
z
bin Wa
n Hu
s
sin)
1251
[12]
K.
M.
Yous
ef,
e
t
al.
,
“
Intelli
g
en
t
Tra
ff
ic
Li
ght
Flow
Control
Sy
stem
Us
ing
W
i
rel
ess
Sensor
Networks
(W
SN
),
”
Journal
of
Infor
mation
Sc
ie
nc
e and E
ngin
ering
,
vol.
26
,
pp
.
753
-
768,
2010
.
[13]
A
.
Goel,
e
t
al.
,
“
Inte
ll
ig
ent
Tr
af
fic
Li
gh
t
S
y
st
e
m
to
Priorit
iz
ed
Emerge
nc
y
Pur
pose
Vehic
l
es
base
d
on
W
ire
le
s
s
Sensor Net
work,
”
Int
ernati
onal
J
ournal
of
Comp
ute
r A
pp
li
ca
ti
on
s
,
v
ol
/
issue:
40
(
12
)
,
2012
.
[14]
P.
T.
V.
Bhuv
an
eswari
,
e
t
al
.
,
“
Adapti
ve
Tra
ff
ic
Signal
Flow
Control
usingW
ire
l
ess
Sensor
Networks,”
pp.
85
-
89
,
2012.
[15]
Chandra
sekha
r
M
.
,
et
a
l.
,
“
Tr
aff
ic
Con
trol
Us
ing
Digital
Im
ag
e
P
roc
essing,
”
v
ol
/is
sue:
2
(
5
)
,
2013.
[16]
P
.
Jadha
v,
e
t
al
.
,
“
Sm
art
Tr
aff
i
c
Control
S
y
st
e
m
Us
ing
Im
age
Proce
ss
ing,
”
In
te
rnational
R
ese
arch
Journal
o
f
Engi
ne
ering
and
Technol
og
y
(
IR
JE
T)
,
v
ol
/i
ss
ue:
03
(
03
)
,
2016
.
[17]
G
.
Kaur
and
S
.
S
har
m
a,
“
Tra
ffi
c
Mana
gement
Us
ing
Digit
a
l
Im
ag
e
Proce
ss
ing,
”
In
te
rnational
Journal
of
C
om
pute
r
Sci
en
ce
a
nd
Tec
hnology
,
IJCST
,
v
ol
/i
ss
ue:
8
(
2
)
,
2
017.
[18]
M
.
S
y
awa
ludi
n
and
M
.
R
.
Daud
,
“
Detect
ion
of
emerge
nc
y
vehicle
s
using
combinat
ion
of
HS
V
col
or
spa
ce
an
d
RGB c
olor
spa
c
e
t
ec
hniqu
e
for
i
nte
lligent tr
aff
i
c li
ght
s
y
stem,
”
20
15.
[19]
O
.
R
.
Gaikwa
d
,
et
a
l.
,
“
Im
age
Proce
ss
ing
B
ase
d
Tra
f
fic
Light
Control,”
I
nte
rnational
Jo
urnal
of
Scienc
e,
Engi
ne
ering
and
Technol
og
y Re
s
earc
h
(
IJS
ETR)
,
v
ol
/i
ss
ue:
3
(
4
)
,
2
014.
[20]
S
.
Djahel,
et
a
l.
,
“
Adapti
ve
Tr
a
ffic
Man
age
m
en
t
for
Secur
e
and
Eff
i
ci
en
t
Emer
gency
Serv
ic
es
i
n
Sm
art
Cit
i
es,
”
IEE
E
,
2013
.
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