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C
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Data
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1.
I
NT
RO
D
UCT
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O
N
I
n
ter
n
et
-
of
-
v
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h
icles
(
I
o
V)
p
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m
its
a
lar
g
e
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etwo
r
k
o
f
v
eh
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s
in
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s
atellites,
W
i
-
F
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an
d
ce
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lar
n
etwo
r
k
s
,
alo
n
g
with
t
h
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s
a
g
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o
f
ar
tific
ial
in
tellig
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ce
(
AI
)
an
d
b
ig
d
ata
to
o
f
f
er
p
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d
ictiv
e
m
ain
ten
an
c
e,
s
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ar
t
tr
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g
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en
t,
a
n
d
au
to
n
o
m
o
u
s
d
r
iv
in
g
[
1
]
.
Ho
wev
er
,
I
o
V
d
if
f
er
s
f
r
o
m
v
eh
ic
u
lar
ad
h
o
c
n
etwo
r
k
(
VANE
T
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in
v
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s
p
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Her
e,
th
e
f
o
r
m
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ased
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m
ak
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r
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s
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b
i
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ata
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o
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n
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to
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s
e
r
ea
l
-
tim
e
co
o
r
d
in
atio
n
p
r
im
a
r
ily
[
2
]
.
Fu
r
th
er
,
th
e
r
an
g
e
o
f
co
n
n
ec
tio
n
s
an
d
d
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v
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clu
s
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in
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is
f
ar
h
ig
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d
m
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co
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p
lex
th
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n
in
c
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tr
ast
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f
VANE
T
.
At
p
r
esen
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th
er
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a
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e
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s
tu
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claim
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f
o
r
e
v
o
lv
e
d
r
o
u
tin
g
s
tr
ateg
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in
I
o
V
[
3
]
–
[
5
]
;
h
o
wev
er
,
th
er
e
ar
e
wid
e
-
o
p
en
s
et
o
f
ch
allen
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es in
cu
r
r
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t tim
es.
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h
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ty
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s
h
o
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tco
m
in
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s
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es
to
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m
in
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ata
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s
m
is
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in
th
e
v
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lar
n
etwo
r
k
o
f
I
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V,
wh
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ar
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f
r
eq
u
en
t
alter
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s
in
to
p
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ter
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iv
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s
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ca
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m
ax
im
a
in
g
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g
r
ap
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ic
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tin
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,
[
6
]
.
Scalin
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th
e
d
ata
tr
an
s
m
is
s
io
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s
ch
em
e
to
m
illi
o
n
s
o
f
v
eh
icles
in
I
o
V
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th
er
p
r
ac
tical
ch
allen
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wh
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to
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s
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t
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ates
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tes
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r
s
ely
af
f
ec
t
r
o
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tin
g
p
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r
f
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r
m
an
ce
[
7
]
.
Ap
a
r
t
f
r
o
m
th
is
,
th
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e
is
also
a
f
r
eq
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en
t
ex
ch
a
n
g
e
o
f
co
n
tr
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l m
ess
ag
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wh
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is
m
a
in
ly
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s
ed
eith
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o
r
r
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u
te
m
ain
ten
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ce
o
r
f
o
r
r
o
u
te
d
is
co
v
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y
o
p
er
atio
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s
.
Su
ch
a
task
n
o
t
o
n
ly
u
s
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ex
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s
s
iv
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c
h
an
n
el
ca
p
ac
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u
t
also
co
n
s
u
m
es
p
r
o
ce
s
s
in
g
o
v
er
h
ea
d
.
Fr
o
m
th
e
p
er
s
p
ec
tiv
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o
f
d
elay
-
s
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s
itiv
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licatio
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lar
n
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k
s
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it
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ted
th
at
th
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m
ajo
r
ity
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f
th
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a
p
p
licatio
n
s
to
war
d
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
2
5
2
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I
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t J Ar
tif
I
n
tell
,
Vo
l.
1
5
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
6
:
229
-
2
3
6
230
co
llis
io
n
av
o
id
a
n
ce
d
em
a
n
d
a
m
in
im
al
s
co
r
e
o
f
en
d
-
to
-
e
n
d
d
ela
y
,
wh
ile
c
o
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v
e
n
tio
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al
d
ata
tr
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s
m
is
s
io
n
s
ch
em
es
m
ay
n
o
t
ac
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u
ally
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ter
to
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d
e
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an
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ain
ts
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f
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ea
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-
tim
e
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p
p
licatio
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s
in
I
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V
[
8
]
,
[
9
]
.
B
ec
au
s
e
o
f
all
th
e
ab
o
v
e
-
m
en
t
io
n
ed
is
s
u
es,
it is
v
er
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ch
allen
g
in
g
to
p
r
ac
tically
m
ain
tain
s
t
ab
le
r
o
u
tes y
ield
in
g
to
u
n
r
eliab
le
c
o
m
m
u
n
icatio
n
.
I
n
a
l
l
t
h
e
s
e
c
o
n
t
e
x
t
s
,
AI
h
as
a
p
o
t
e
n
t
ia
l
s
c
o
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n
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d
r
es
s
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n
g
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h
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s
e
i
s
s
u
e
s
[
1
0
]
.
B
a
s
i
c
a
l
l
y
,
AI
m
o
d
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s
ar
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c
a
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ab
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s
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s
s
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ev
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n
i
n
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co
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p
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n
v
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m
en
t
.
Ma
c
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a
lg
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m
s
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o
f
v
e
h
i
cu
l
a
r
n
o
d
e
s
,
w
h
i
ch
ca
n
d
e
f
i
n
i
t
e
ly
co
n
tr
i
b
u
t
e
t
o
w
a
r
d
s
r
o
u
t
e
s
t
ab
i
l
i
t
y
.
A
p
a
r
t
f
r
o
m
th
i
s
,
A
I
i
n
co
r
p
o
r
a
t
i
o
n
c
a
n
a
l
s
o
co
n
tr
i
b
u
t
e
to
w
a
r
d
s
r
o
u
te
o
p
t
i
m
i
za
t
i
o
n
f
o
r
m
in
i
m
i
z
in
g
en
e
r
g
y
co
n
s
u
m
p
t
io
n
,
wh
i
ch
i
s
h
ig
h
ly
h
e
l
p
f
u
l
wh
e
n
d
e
a
l
in
g
w
i
t
h
r
es
o
u
r
c
e
-
co
n
s
t
r
a
in
ed
d
e
v
i
ce
s
i
n
I
o
V.
T
h
er
e
is
n
o
d
en
y
in
g
th
e
f
ac
t
th
at
AI
is
a
b
etter
s
o
lu
tio
n
;
h
o
wev
er
,
th
e
r
e
is
n
o
t
m
u
ch
attem
p
t
to
cr
ea
te
a
s
u
itab
le
b
aselin
e
ar
ch
itectu
r
e
f
o
r
s
u
p
p
o
r
ti
n
g
ad
v
an
ce
d
AI
f
o
r
ef
f
ec
tiv
e
d
ata
tr
a
n
s
m
is
s
io
n
in
I
o
V.
I
n
th
e
m
ajo
r
ity
o
f
e
x
is
tin
g
s
tu
d
ies
[
1
1
]
,
th
e
m
o
d
el
ac
q
u
ir
es
a
d
ataset
f
r
o
m
a
p
u
b
licly
av
ailab
le
r
eso
u
r
ce
,
s
u
b
jects
it
to
s
tan
d
ar
d
n
o
r
m
aliza
tio
n
,
a
n
d
d
ir
ec
tly
f
ee
d
s
it
to
d
if
f
er
en
t
v
ar
ian
ts
o
f
AI
.
B
y
ad
o
p
tin
g
s
u
ch
a
s
tr
ateg
y
,
th
e
ex
ten
t
o
f
in
n
o
v
atio
n
is
s
o
lely
d
ep
e
n
d
en
t
o
n
th
e
AI
m
o
d
el,
wh
er
ea
s
th
er
e
ar
e
g
o
o
d
c
h
an
ce
s
to
r
ef
r
am
e
th
e
b
aselin
e
m
o
d
el
a
n
d
in
c
o
r
p
o
r
at
e
m
u
ch
o
f
lo
g
ical
o
p
e
r
atio
n
s
,
wh
ich
co
u
ld
f
u
r
th
er
m
i
n
im
ize
th
e
o
p
er
atio
n
al
an
d
co
m
p
u
tatio
n
al
l
o
ad
o
n
th
e
AI
m
o
d
u
le
an
d
y
ield
b
etter
o
p
tim
ized
r
esu
lts
at
th
e
s
am
e
tim
e.
Un
f
o
r
tu
n
atel
y
,
th
er
e
ar
e
f
ew
s
u
ch
id
e
o
lo
g
ies b
ein
g
in
co
r
p
o
r
ated
in
t
h
e
ex
is
tin
g
s
y
s
tem
,
wo
r
k
in
g
to
wa
r
d
s
th
is
d
ir
ec
tio
n
.
T
h
e
r
elate
d
wo
r
k
ass
o
ciate
d
with
v
ar
io
u
s
d
ata
t
r
an
s
m
is
s
io
n
s
ch
em
es
f
o
r
ad
v
an
ce
d
v
eh
icu
lar
n
etwo
r
k
s
h
as
b
ee
n
s
tu
d
ied
.
I
t
is
n
o
ted
th
at
th
er
e
is
f
r
eq
u
en
t
wo
r
k
ca
r
r
ied
o
u
t
u
s
in
g
a
ty
p
e
o
f
s
ch
em
e
wh
ich
u
s
es
d
ata
tr
an
s
m
is
s
io
n
b
ased
o
n
p
o
s
itio
n
,
wh
er
e
th
e
n
o
d
e
r
esid
in
g
n
ea
r
to
d
esti
n
atio
n
n
o
d
e
r
ec
eiv
es
th
e
d
ata
p
ac
k
et.
I
n
th
e
ab
s
en
ce
o
f
s
u
ch
a
g
r
ee
d
y
f
o
r
war
d
i
n
g
s
ch
em
e,
s
u
ch
m
eth
o
d
s
u
s
e
p
er
im
eter
f
o
r
war
d
i
n
g
.
C
o
n
s
id
er
in
g
n
am
in
g
th
is
m
e
th
o
d
as
C
Me
t1
,
th
er
e
ar
e
v
ar
io
u
s
wo
r
k
s
ca
r
r
ie
d
o
u
t
in
[
1
2
]
‒
[
1
5
]
.
A
n
o
th
er
f
r
eq
u
e
n
tly
u
s
ed
d
ata
-
tr
a
n
s
m
is
s
io
n
m
eth
o
d
is
f
o
u
n
d
to
j
o
in
tly
u
s
e
to
p
o
l
o
g
y
-
b
ased
d
ata
in
teg
r
ated
with
p
o
s
itio
n
-
b
ased
r
o
u
tin
g
.
C
o
n
s
i
d
er
in
g
n
am
i
n
g
th
is
m
eth
o
d
as
C
Me
t2
,
s
u
ch
ap
p
r
o
ac
h
es
o
f
t
en
ev
alu
ate
an
ch
o
r
p
o
in
ts
u
s
in
g
s
tr
ee
t
g
r
ap
h
s
w
h
er
e
d
ata
p
ac
k
ets
ar
e
tr
an
s
m
itted
f
r
o
m
o
n
e
an
c
h
o
r
to
an
o
th
er
(
a
n
ch
o
r
s
ar
e
ty
p
ically
th
e
in
ter
s
ec
tio
n
p
o
in
ts
)
.
T
h
is
m
eth
o
d
is
witn
es
s
ed
in
wo
r
k
ca
r
r
ied
o
u
t
in
[
1
6
]
‒
[
1
9
]
.
T
h
e
r
e
ar
e
also
v
ar
io
u
s
ex
is
tin
g
s
tu
d
ies
em
p
h
asizin
g
to
war
d
s
f
o
r
m
u
latio
n
o
f
d
ata
tr
an
s
m
is
s
io
n
d
u
r
in
g
an
em
er
g
e
n
cy
.
C
o
n
s
id
er
in
g
th
e
n
am
e
o
f
s
u
ch
ap
p
r
o
ac
h
es
as
C
Me
t3
,
v
ar
i
o
u
s
au
th
o
r
s
i
n
[
2
0
]
‒
[
2
5
]
h
av
e
p
r
esen
ted
s
o
lu
tio
n
s
to
p
er
f
o
r
m
m
ess
ag
e
d
is
s
em
in
atio
n
d
u
r
i
n
g
d
is
tr
ess
co
n
d
itio
n
s
.
T
h
e
r
esear
ch
p
r
o
b
lem
s
id
e
n
tifie
d
ar
e
as
f
o
llo
ws.
First,
th
e
m
ajo
r
ity
o
f
t
h
e
ex
is
tin
g
C
Me
t1
s
ch
em
es
lack
co
n
s
id
er
atio
n
o
f
b
a
n
d
wi
d
th
,
r
eliab
ilit
y
,
an
d
d
elay
,
ev
en
if
th
ey
o
f
f
er
b
etter
s
ca
lab
ilit
y
an
d
m
in
im
al
o
v
er
h
ea
d
.
Seco
n
d
,
a
m
ax
im
u
m
o
f
C
Me
t2
m
eth
o
d
s
s
u
f
f
e
r
f
r
o
m
ca
r
r
y
in
g
o
u
td
ated
in
f
o
r
m
atio
n
o
f
th
e
p
ath
,
ev
en
if
th
e
y
h
a
v
e
b
etter
p
er
f
o
r
m
an
ce
o
n
u
r
b
an
s
ce
n
ar
io
s
with
en
h
an
ce
d
r
o
u
tin
g
d
ec
is
i
o
n
s
.
T
h
ir
d
,
C
Me
t3
m
eth
o
d
s
in
d
u
ce
c
o
m
p
u
tatio
n
a
l
ex
p
en
s
es,
esp
ec
ially
i
n
ter
m
s
o
f
h
i
g
h
er
b
an
d
wid
th
u
s
ag
e,
an
d
h
e
n
ce
t
h
ey
a
r
e
n
o
t
r
eso
u
r
ce
ef
f
icien
t,
esp
ec
ially
in
th
e
ca
s
e
o
f
d
y
n
am
ic
s
tr
ee
t
to
p
o
lo
g
y
.
All
th
ese
ar
e
ac
tu
ally
o
p
e
n
-
en
d
e
d
r
esear
ch
ch
allen
g
es th
at
n
ee
d
t
o
b
e
ad
d
r
ess
ed
im
m
ed
iately
.
T
h
e
aim
o
f
th
e
p
r
o
p
o
s
ed
s
tu
d
y
is
to
d
ev
elo
p
a
n
o
v
el
c
o
m
p
u
tatio
n
al
m
o
d
el
to
war
d
s
m
an
a
g
in
g
lar
g
e
r
s
tr
ea
m
s
o
f
tr
af
f
ic
d
ata,
alo
n
g
with
lev
er
ag
in
g
in
ter
ac
tiv
e
s
e
r
v
ices
am
o
n
g
v
e
h
icles
u
s
in
g
a
n
ewly
o
p
tim
ized
co
n
tr
o
ller
s
y
s
tem
f
o
r
m
ed
iatin
g
n
o
d
es.
T
h
e
p
r
o
p
o
s
ed
s
y
s
tem
in
tr
o
d
u
ce
s
a
b
aselin
e
m
o
d
e
l
th
at
co
u
ld
p
er
f
o
r
m
m
o
r
e
lo
g
ical,
co
s
t
-
ef
f
ec
tiv
e
co
m
p
u
tatio
n
al
o
p
er
ati
o
n
s
f
o
r
lev
er
ag
in
g
AI
o
p
er
atio
n
s
in
I
o
V.
T
h
e
ter
m
m
ed
iatin
g
n
o
d
es
r
ef
er
s
to
th
o
s
e
in
ter
m
ed
iate
v
eh
icu
lar
n
o
d
es
th
at
co
n
n
ec
t
two
v
eh
icl
es'
co
m
m
u
n
icatio
n
s
y
s
tem
s
wh
en
th
ey
ar
e
f
o
u
n
d
r
esid
in
g
at
co
m
m
o
n
s
en
s
in
g
-
tr
an
s
m
is
s
io
n
zo
n
es
o
f
b
o
th
v
eh
icu
lar
n
o
d
es.
T
h
e
id
ea
is
to
b
r
id
g
e
th
e
co
m
m
u
n
i
ca
tio
n
wh
en
two
s
en
s
in
g
r
eg
io
n
s
o
f
two
v
eh
icles
d
o
n
’
t
in
te
r
s
ec
t
ea
ch
o
th
er
,
b
u
t
h
av
e
a
co
m
m
o
n
n
o
d
e
ca
lled
a
m
ed
iatin
g
n
o
d
e
b
etwe
en
th
em
.
T
h
e
v
a
l
u
e
-
a
d
d
ed
c
o
n
t
r
ib
u
t
io
n
o
f
p
r
o
p
o
s
ed
s
t
u
d
y
ar
e
a
s
f
o
ll
o
w
s
:
i
)
t
h
e
p
r
o
p
o
s
e
d
s
tu
d
y
in
t
r
o
d
u
c
e
s
o
r
i
en
t
a
t
i
o
n
d
eg
r
e
e
f
o
r
o
p
t
i
m
iz
i
n
g
t
h
e
d
e
c
i
s
i
o
n
o
f
d
a
t
a
t
r
an
s
m
i
s
s
i
o
n
i
n
v
e
h
i
cu
l
a
r
n
e
t
w
o
r
k
s
th
a
t
c
a
n
a
s
s
e
s
s
s
i
g
n
a
l
q
u
a
l
i
ty
,
m
o
b
i
l
i
ty
,
an
d
r
e
l
a
t
i
v
e
p
o
s
i
t
io
n
b
e
t
w
e
en
t
wo
n
o
d
e
s
;
i
i
)
th
e
i
n
tr
o
d
u
c
e
d
s
ch
e
m
e
im
p
r
o
v
e
s
t
h
e
d
a
t
a
tr
a
n
s
m
i
s
s
i
o
n
e
f
f
ic
i
e
n
cy
b
y
i
n
c
o
r
p
o
r
a
t
in
g
a
s
e
l
e
c
t
io
n
m
ec
h
an
i
s
m
f
o
r
m
e
d
i
a
t
in
g
n
o
d
e
s
d
y
n
am
i
c
a
l
ly
b
a
s
e
d
o
n
co
m
m
u
n
i
c
a
t
i
o
n
c
a
p
a
b
i
l
i
t
i
e
s
,
m
o
b
i
l
i
t
y
,
an
d
p
r
o
x
im
i
t
y
;
i
i
i)
th
e
p
r
o
p
o
s
ed
s
c
h
em
e
s
u
p
p
o
r
t
s
v
eh
i
c
l
e
t
o
ev
er
y
th
i
n
g
(
V
2
X
)
wh
e
r
e
s
t
a
n
d
a
lo
n
e
co
m
m
u
n
i
c
a
t
i
o
n
c
ap
a
b
i
l
i
t
i
e
s
o
f
a
v
eh
i
c
l
e
i
s
en
co
u
r
a
g
ed
a
s
w
e
l
l
a
s
v
e
h
i
c
le
c
an
t
a
k
e
a
s
s
i
s
t
a
n
c
e
o
f
i
n
f
r
a
s
t
r
u
c
t
u
r
e
-
b
a
s
e
d
co
m
m
u
n
i
c
a
t
i
o
n
to
o
;
an
d
i
v
)
th
e
p
r
e
s
e
n
t
e
d
f
r
a
m
e
wo
r
k
i
s
f
o
u
n
d
to
o
f
f
e
r
an
im
p
r
o
v
e
d
s
c
a
l
a
b
i
li
t
y
p
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i
t
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
E
fficien
t d
a
ta
s
tr
ea
min
g
in
d
y
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a
mic
ve
h
icu
la
r
n
etw
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ks:
a
h
yb
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n
tr
o
ller
fo
r
…
(
P
r
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ib
h
a
Th
imma
p
p
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)
231
2.
M
E
T
H
O
D
T
h
e
p
r
im
e
aim
o
f
th
e
p
r
o
p
o
s
ed
s
tu
d
y
m
o
d
el
is
to
co
n
s
tr
u
ct
a
n
o
v
el
s
o
f
twar
e
m
o
d
ellin
g
to
war
d
s
s
tr
ea
m
lin
in
g
th
e
tr
af
f
ic
f
lo
w
,
alo
n
g
with
a
n
in
tr
o
d
u
ctio
n
to
an
o
p
tim
ized
tr
af
f
ic
c
o
n
tr
o
ller
s
y
s
tem
f
o
r
m
ed
iatin
g
co
m
m
u
n
icatio
n
s
er
v
ices
f
o
r
th
e
I
o
V
s
y
s
tem
.
T
h
e
co
m
p
lete
f
r
am
ewo
r
k
is
d
esig
n
ed
co
n
s
id
er
in
g
ce
r
tain
ess
en
tial
o
p
er
atio
n
al
m
o
d
u
les,
v
iz.
,
s
m
ar
t
p
r
o
ce
s
s
in
g
o
f
on
-
b
o
a
r
d
u
n
it
(
OB
U)
,
f
o
r
m
atio
n
o
f
clu
s
ter
in
g
g
r
id
,
a
n
d
s
elec
tio
n
o
f
m
e
d
iatin
g
n
o
d
e.
T
h
e
s
o
le
p
u
r
p
o
s
e
o
f
th
is
a
d
o
p
ted
m
eth
o
d
o
l
o
g
y
is
to
war
d
s
e
n
s
u
r
e
s
ca
lab
le
f
ac
ilit
atio
n
o
f
d
ata
s
tr
ea
m
in
g
with
r
ea
l
-
tim
e
an
d
ad
a
p
tiv
e
p
er
f
o
r
m
an
ce
;
m
u
ch
n
ee
d
ed
f
o
r
t
h
e
d
y
n
am
ic
en
v
ir
o
n
m
en
t o
f
v
eh
ic
u
lar
n
et
wo
r
k
s
.
Fig
u
r
e
1
h
ig
h
lig
h
ts
th
e
ad
o
p
ted
la
y
o
u
t
o
f
th
e
p
r
o
p
o
s
ed
s
tu
d
y
m
o
d
el.
Fig
u
r
e
1
.
L
a
y
o
u
t
o
f
p
r
o
p
o
s
ed
m
o
d
el
Acc
o
r
d
in
g
to
Fig
u
r
e
1
,
it
ca
n
b
e
n
o
ted
th
at
th
er
e
a
r
e
v
a
r
io
u
s
o
p
er
atio
n
al
m
o
d
u
les
in
v
o
lv
ed
in
th
e
d
esig
n
s
tr
u
ctu
r
e
o
f
th
e
p
r
o
p
o
s
ed
lay
o
u
t.
E
ac
h
o
p
er
atio
n
a
l
b
lo
ck
s
ar
e
m
ea
n
t
to
ex
ec
u
te
a
s
p
ec
if
ic
task
an
d
is
also
in
ter
co
n
n
ec
ted
with
th
e
o
th
er
.
A
s
im
p
lifie
d
m
ath
em
atica
l
o
p
er
atio
n
is
ca
r
r
ied
o
u
t
to
ac
co
m
p
lis
h
th
is
task
.
T
h
e
f
o
llo
win
g
is
th
e
b
r
ief
in
g
o
f
m
ath
e
m
atica
l
m
o
d
ellin
g
with
in
ea
ch
o
p
er
atio
n
al
m
o
d
u
le
o
f
th
e
p
r
o
p
o
s
ed
s
tu
d
y
.
2
.
1
.
S
m
a
rt
pro
ce
s
s
ing
o
f
on
-
bo
a
rd
un
it
T
h
e
aim
o
f
th
is
f
ir
s
t
m
o
d
u
le
is
to
c
o
n
s
tr
u
ct
a
lo
ca
l
u
n
it
o
f
co
m
m
u
n
icatio
n
k
n
o
wn
as
OB
U
with
in
th
e
v
eh
icle
b
ef
o
r
e
f
o
r
m
u
latin
g
a
r
o
u
tin
g
d
ec
is
io
n
.
T
h
e
s
tu
d
y
c
o
n
s
id
er
s
th
at
a
s
m
ar
t
OB
U
is
m
o
u
n
te
d
o
n
ea
ch
v
eh
icle
th
at
p
e
r
f
o
r
m
s
m
u
ltip
le
task
s
ass
o
ciate
d
with
d
ata
p
ac
k
ets
b
ef
o
r
e
ac
tu
ally
s
en
s
in
g
th
em
,
v
iz.
,
b
u
f
f
er
in
g
th
e
s
tr
ea
m
,
f
ilter
in
g
th
e
f
lo
w,
an
d
ca
te
g
o
r
izin
g
th
e
p
ac
k
ets.
T
h
e
m
at
h
em
atica
l
ex
p
r
ess
io
n
to
war
d
s
th
e
d
ata
s
tr
ea
m
,
ac
tin
g
as in
p
u
t
f
ee
d
,
is
r
ep
r
esen
ted
as
(
1
)
.
(
)
=
∑
(
)
−
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1
)
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n
(
1
)
,
it
ca
n
b
e
n
o
ted
th
at
q
u
an
tific
atio
n
o
f
a
n
in
c
o
m
in
g
d
ata
s
tr
ea
m
D
in
(
t
)
is
d
ep
en
d
e
n
t
u
p
o
n
th
e
n
u
m
b
er
o
f
d
ata
p
ac
k
ets/
s
er
v
ices
N
an
d
th
e
i
th
d
ata
p
ac
k
et
o
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tain
ed
at
t
th
tim
e
i.e
.
,
P
i
(
t
)
.
T
h
e
p
r
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p
o
s
ed
s
y
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tem
also
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k
s
a
p
r
io
r
ity
v
alu
e
π
i,
c
o
n
s
id
er
in
g
a
r
an
g
e
o
f
[
0
,
1
]
wi
th
ea
ch
P
i
(
t
)
d
ata
p
ac
k
et.
Hen
c
e,
it
will
m
ea
n
th
at
if
π
i
=1
th
at
it
will
r
e
p
r
esen
t
s
er
v
ices
with
h
ig
h
er
p
r
i
o
r
ity
,
wh
ile
if
π
i
=0
will
r
e
p
r
esen
t
s
er
v
ices
with
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wer
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r
io
r
ity
(
e.
g
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en
ter
tain
m
en
t
-
b
ased
s
er
v
ices)
.
T
h
is
ca
n
b
e
f
u
r
th
er
s
im
p
lifie
d
in
th
e
f
o
r
m
o
f
a
m
ath
em
atica
l
ex
p
r
ess
io
n
as
(
2
)
.
(
)
=
{
1
,
>
0
,
ℎ
(
2
)
In
(
2
)
s
h
o
wca
s
es
th
e
v
ar
iab
l
e
δ
to
r
e
p
r
esen
t
th
e
p
r
io
r
ity
cu
t
-
o
f
f
s
co
r
e
d
e
f
in
ed
b
y
a
s
y
s
tem
to
war
d
s
th
e
co
m
p
u
tatio
n
o
f
th
e
f
ilter
in
g
f
u
n
ctio
n
F
i
(
t
)
with
p
r
io
r
ity
aw
ar
en
ess
.
Hen
ce
,
th
e
f
in
al
m
ath
em
atica
l
ex
p
r
ess
io
n
o
f
th
e
ef
f
ec
tiv
e
d
ata
s
tr
ea
m
wi
ll b
e
as
(
3
)
.
(
)
=
∑
(
)
.
(
)
−
1
(
3
)
In
(
3
)
r
e
p
r
esen
ts
th
at
all
th
e
OB
Us
in
ter
co
n
n
ec
t
th
em
s
elv
es
to
f
o
r
m
a
p
o
s
s
ib
le
n
etwo
r
k
with
th
e
v
eh
icu
lar
in
te
r
f
ac
e,
w
h
ile
a
p
r
io
r
ity
cu
t
-
o
f
f
s
co
r
e
is
u
s
ed
f
o
r
f
ilter
in
g
th
e
in
co
m
in
g
d
ata
p
a
ck
ets
f
o
r
ass
ess
in
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
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t J Ar
tif
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tell
,
Vo
l.
1
5
,
No
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1
,
Feb
r
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ar
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-
2
3
6
232
th
eir
ty
p
e
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d
u
r
g
en
cy
.
All
t
h
e
b
u
f
f
er
ed
d
ata
p
ac
k
ets
ar
e
ar
r
an
g
e
d
in
th
e
f
o
r
m
o
f
a
q
u
eu
e
wh
ile
th
e
y
ar
e
f
u
r
th
er
f
o
r
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d
ed
s
elec
tiv
ely
d
ep
en
d
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g
o
n
th
eir
av
aila
b
le
s
ig
n
al
q
u
ality
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v
eh
icle
d
ir
e
ctio
n
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an
d
ch
a
n
n
el
ca
p
ac
ity
.
T
h
e
p
r
o
p
o
s
ed
s
y
s
tem
d
if
f
er
e
n
tiates
f
r
o
m
th
e
ex
is
tin
g
s
y
s
tem
b
y
in
c
o
r
p
o
r
atin
g
s
m
ar
t
an
d
ca
lcu
late
d
d
ec
is
io
n
-
m
ak
in
g
,
wh
ile
co
n
v
en
tio
n
al
s
tu
d
y
m
o
d
els
o
n
v
eh
icu
lar
n
etwo
r
k
s
u
s
u
ally
co
n
s
id
er
OB
U
as
tr
an
s
ce
iv
er
s
with
u
s
u
al
f
u
n
ctio
n
ality
to
war
d
s
co
m
m
u
n
icatio
n
.
T
h
ey
ar
e
also
d
ev
o
id
o
f
a
d
ap
tiv
e
ca
p
ab
ilit
ies o
f
s
to
r
in
g
in
tellig
en
t
f
ilter
in
g
.
O
n
th
e
co
n
tr
ar
y
,
th
e
s
m
ar
t
OB
U
in
th
e
p
r
o
p
o
s
ed
s
tu
d
y
m
o
d
el
p
lay
s
th
e
r
o
le
o
f
a
p
r
ep
r
o
ce
s
s
in
g
co
m
p
u
tatio
n
al
m
o
d
u
le
th
at
f
u
s
es
d
y
n
am
ic
b
u
f
f
er
m
a
n
ag
em
e
n
t
with
d
ata
f
il
ter
in
g
with
p
r
io
r
ity
awa
r
en
ess
.
T
h
is
ca
u
s
es
d
r
asti
c
m
in
im
izatio
n
o
f
n
etwo
r
k
o
v
er
h
ea
d
a
n
d
h
en
ce
co
n
tr
i
b
u
tes
to
im
p
r
o
v
ed
p
ac
k
et
q
u
ality
d
u
r
in
g
d
ata
f
o
r
wa
r
d
in
g
o
p
er
atio
n
s
.
2
.
2
.
F
o
rma
t
io
n o
f
clus
t
er
ing
g
rid
T
h
e
p
r
im
e
aim
o
f
th
is
m
o
d
u
le
is
to
p
er
f
o
r
m
a
lo
g
ical
p
ar
titi
o
n
in
g
o
f
th
e
I
o
V
en
v
ir
o
n
m
en
t
in
to
m
u
ltip
le
co
n
tr
o
lled
co
m
m
u
n
icatio
n
zo
n
es
f
o
r
f
ac
ilit
atin
g
lo
ca
l
d
ec
is
io
n
-
m
a
k
in
g
a
n
d
m
in
im
izin
g
d
ata
tr
an
s
m
is
s
io
n
co
m
p
lex
ities
.
T
h
e
p
r
o
p
o
s
ed
s
tu
d
y
u
s
es
a
clu
s
ter
in
g
g
r
id
f
o
r
p
ar
titi
o
n
i
n
g
th
e
g
eo
g
r
ap
h
ic
s
im
u
latio
n
ar
ea
d
ep
en
d
in
g
o
n
th
e
d
ep
lo
y
m
en
t
o
f
th
e
r
o
ad
s
id
e
u
n
it
(
R
SU
)
.
C
o
n
s
id
er
in
g
A
as
a
s
im
u
latio
n
ar
ea
wh
er
e
a
s
q
u
ar
e
clu
s
ter
o
f
s
ize
l
x
l
is
m
a
n
ag
ed
b
y
R
SU.
Hen
ce
,
cu
m
u
lativ
e
C
clu
s
ter
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atica
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In
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way
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u
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p
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n
ter
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m
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wev
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ch
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m
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f
lo
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tellig
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clu
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h
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ax
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v
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itio
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o
f
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tr
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g
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y
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ce
n
ar
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I
o
V.
2
.
3
.
Select
io
n o
f
m
edia
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ing
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T
h
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aim
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th
is
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to
o
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(
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.
=
−
1
(
⃗
.
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|
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(
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8
9
3
8
E
fficien
t d
a
ta
s
tr
ea
min
g
in
d
y
n
a
mic
ve
h
icu
la
r
n
etw
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ks:
a
h
yb
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r
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(
P
r
a
th
ib
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a
Th
imma
p
p
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)
233
I
n
(
6
)
,
th
e
v
a
r
iab
les
an
d
r
ep
r
esen
ts
th
e
co
m
m
u
n
icatio
n
v
e
cto
r
f
r
o
m
th
e
s
o
u
r
ce
n
o
d
e
to
th
e
m
ed
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g
n
o
d
e
a
n
d
th
e
m
ed
i
atin
g
n
o
d
e
to
th
e
d
esti
n
atio
n
n
o
d
e,
r
esp
ec
tiv
ely
.
I
t
s
h
o
u
ld
b
e
n
o
ted
th
at
h
ig
h
e
r
alig
n
m
en
t
is
id
en
tifie
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in
t
h
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p
r
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f
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d
s
co
r
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o
f
th
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θ
o
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tatio
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an
g
le.
A
n
e
w
f
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m
o
f
em
p
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f
u
n
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k
n
o
wn
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t
h
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tili
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f
u
n
ctio
n
U
is
d
eter
m
in
ed
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o
r
ass
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in
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th
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u
itab
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o
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d
e,
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al
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.
Fu
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th
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p
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ep
lo
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tili
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with
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t to
m
e
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n
o
d
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v
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th
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is
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r
ep
r
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ted
as
(
7
)
.
(
)
=
.
(
1
−
)
+
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(
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(
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I
n
(
7
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,
th
e
co
m
p
u
tatio
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f
th
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tili
ty
f
u
n
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U
is
ca
r
r
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with
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a
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Ap
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m
th
is
,
th
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(
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also
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n
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titi
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α
,
β
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t
o
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tu
n
ed
.
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n
ce
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th
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ex
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r
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th
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tim
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e
d
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is
as
(
8
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.
∗
=
∈
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(
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(
8
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n
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,
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e
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n
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ed
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e.
Fu
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e
r
,
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y
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in
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tr
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s
with
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d
is
co
v
er
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g
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m
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lete
en
d
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to
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en
d
r
o
u
te.
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x
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g
d
ata
tr
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s
m
is
s
io
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s
ch
em
es
m
ain
ly
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ely
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n
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ased
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d
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s
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m
r
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is
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y
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u
lar
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ter
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B
o
th
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o
n
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ar
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d
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o
n
o
t
h
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f
d
y
n
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in
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o
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in
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Hen
ce
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d
if
f
er
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x
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s
ch
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th
e
p
r
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p
o
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s
y
s
tem
u
s
es
th
is
m
o
d
u
le
to
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tr
o
d
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ce
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s
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eth
o
d
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m
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atter
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er
e
b
y
e
n
s
u
r
in
g
r
o
b
u
s
t
r
o
u
tes
an
d
m
o
r
e
s
tab
ilit
y
.
I
t c
an
n
o
w
b
e
s
tated
th
at
th
e
p
r
o
p
o
s
ed
s
y
s
tem
o
f
f
er
s
r
eliab
le
p
ac
k
et
d
eliv
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y
an
d
lin
k
l
o
n
g
e
v
ity
b
y
its
in
h
er
en
t i
n
clu
s
io
n
o
f
m
o
tio
n
-
b
ased
f
ilter
in
g
an
d
o
r
ien
t
atio
n
attr
ib
u
tes.
3.
RE
SU
L
T
AND
DI
SCUS
SI
O
N
T
h
e
im
p
lem
en
tatio
n
o
f
th
e
p
r
o
p
o
s
ed
s
tu
d
y
is
ca
r
r
ied
o
u
t
co
n
s
id
er
in
g
5
0
0
v
eh
icu
lar
n
o
d
es
s
im
u
lated
o
n
a
1
,
0
0
0
×
1
,
1
0
0
m
2
ar
ea
with
2
-
10
m
/s
o
f
v
eh
ic
u
lar
s
p
ee
d
an
d
2
,
0
0
0
b
y
tes
o
f
p
ac
k
ets.
T
h
e
p
r
o
p
o
s
ed
lo
g
ic
was
s
cr
ip
ted
in
MA
T
L
A
B
an
d
h
as
b
ee
n
co
m
p
ar
ed
with
th
r
ee
s
tate
-
of
-
th
e
-
ar
t
m
eth
o
d
s
,
C
Me
t1
,
C
Me
t2
,
an
d
C
Me
t3
,
co
n
s
id
er
in
g
f
o
u
r
p
er
f
o
r
m
an
ce
m
etr
ics,
e.
g
.
s
ig
n
al
q
u
ality
,
r
esp
o
n
s
e
tim
e,
d
ela
y
,
an
d
t
h
r
o
u
g
h
p
u
t.
T
ab
le
1
h
ig
h
lig
h
ts
th
e
n
u
m
er
ical
o
u
tco
m
e
o
f
th
e
s
tu
d
y
.
T
h
e
o
u
tco
m
e
s
h
o
ws
th
e
p
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p
o
s
ed
s
y
s
tem
Pro
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to
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in
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er
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r
m
a
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ce
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en
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e.
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n
u
m
e
r
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u
tco
m
e
in
T
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le
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its
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f
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llo
win
g
f
ac
ts
:
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p
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el,
Pr
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ex
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ed
iatin
g
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e
u
s
in
g
o
r
ien
tatio
n
d
eg
r
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h
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clu
s
io
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n
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t
o
n
l
y
m
in
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izes
lo
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o
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ata
p
ac
k
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b
u
t
also
en
h
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ce
s
lin
k
s
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ilit
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.
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g
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f
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er
f
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m
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n
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itio
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itio
n
s
,
th
e
Pr
o
p
s
u
cc
ess
f
u
ll
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f
ac
ilit
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m
in
im
al
r
esp
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n
s
e
tim
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m
ain
ly
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u
e
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ca
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m
ak
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g
with
s
m
ar
t O
B
U
u
n
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er
d
y
n
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ic
v
e
h
icu
lar
tr
af
f
ic
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n
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itio
n
s
.
T
ab
le
1
.
Nu
m
e
r
ical
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u
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m
e
o
f
s
tu
d
y
P
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r
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ma
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f
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tatio
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h
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tr
ib
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tes
to
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d
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th
e
p
o
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aly
s
is
f
o
r
m
ain
tain
in
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e
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n
.
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ce
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n
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t
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s
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g
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y
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n
v
en
tio
n
al
AI
m
eth
o
d
s
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th
e
lo
g
ical
o
p
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n
in
v
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lv
ed
in
Pro
p
s
er
v
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a
s
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r
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t
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tatio
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s
t
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d
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o
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eso
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r
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e
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en
d
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n
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o
f
r
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r
ce
s
.
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h
e
p
r
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p
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s
ed
s
y
s
tem
Pro
p
also
in
tr
o
d
u
ce
s
a
s
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n
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ec
h
an
is
m
o
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m
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o
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e,
wh
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atu
r
e.
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te
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ly
,
Pro
p
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p
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r
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es
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,
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lex
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ce
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g
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h
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h
ly
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co
m
m
u
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icatio
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s
o
lu
tio
n
.
(
a)
(
b
)
(
c)
(
d
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Fig
u
r
e
2
.
Acc
o
m
p
lis
h
ed
s
tu
d
y
o
u
tco
m
e
f
o
r
(
a)
s
ig
n
al
q
u
ality
,
(
b
)
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n
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e
tim
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,
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)
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d
-
to
-
en
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d
(
d
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r
o
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g
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p
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t
4.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
p
r
esen
ts
a
n
o
v
el
b
aselin
e
f
r
am
ewo
r
k
with
a
c
o
n
tr
o
ller
d
esig
n
th
at
is
m
ea
n
t
e
x
clu
s
iv
ely
to
war
d
s
en
r
ich
in
g
th
e
an
aly
tic
al
p
er
f
o
r
m
a
n
ce
o
f
an
AI
-
b
ased
I
o
V
co
m
m
u
n
icatio
n
s
y
s
tem
.
T
h
e
co
n
tr
ib
u
tio
n
o
f
p
r
o
p
o
s
ed
s
tu
d
y
m
o
d
el
ar
e
as
f
o
llo
ws:
i)
d
if
f
er
e
n
t
f
r
o
m
f
r
eq
u
en
tly
ad
o
p
ted
d
ata
tr
an
s
m
is
s
io
n
ap
p
r
o
ac
h
es,
p
r
o
p
o
s
ed
s
y
s
tem
is
f
o
u
n
d
t
o
o
f
f
er
e
n
h
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ce
d
s
ig
n
al
q
u
ality
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m
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ized
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e
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e
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d
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d
im
p
r
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e
d
th
r
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u
g
h
p
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t
;
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e
n
o
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el
in
tr
o
d
u
ctio
n
o
f
o
r
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n
tatio
n
d
e
g
r
ee
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th
e
f
o
r
m
o
f
a
r
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tin
g
attr
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te
co
n
tr
ib
u
tes to
war
d
s
o
p
tim
al
s
elec
tio
n
o
f
r
o
u
tes
;
iii)
th
e
jo
in
t
ef
f
o
r
t o
f
f
ix
e
d
ac
ce
s
s
p
o
in
t a
n
d
m
o
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ile
m
e
d
iatin
g
n
o
d
e
co
n
tr
ib
u
tes
to
war
d
s
s
ea
m
less
co
n
n
ec
tiv
ity
o
n
m
u
ltip
l
e
en
v
ir
o
n
m
en
ts
o
f
v
eh
icu
la
r
t
r
af
f
ic
in
I
o
V
;
an
d
iv
)
th
e
d
ep
en
d
en
cies
to
war
d
s
eith
er
f
ix
ed
-
p
ath
o
r
s
in
g
le
-
h
o
p
r
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tin
g
in
c
o
n
v
e
n
tio
n
al
d
ata
tr
an
s
m
is
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io
n
m
eth
o
d
s
is
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o
ten
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k
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m
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m
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c
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.
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