This document provides an overview of transportation network modeling and terminology. It discusses the four-step modeling process of trip generation, trip distribution, modal split, and trip assignment. It also covers topics like network coding, multimodal representation, capacity constraints, calibration and validation of models. Transportation modeling is presented as an interaction between land use and transportation systems, with zoning of areas and socioeconomic data factored in.
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Case for smart transportation, detailing the catalysts for change and outlining the strategic imperatives required for success. Case studies reflect how a new approach makes transportation smarter.
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In today’s world with the ever increasing traffic it is inherent that we immediately find an optimum solution for it so that we can move on from being a developing nation to a super power.
There is a great need to resolve our transportation issues at the earliest as connectivity is of grave importance. Finding a systematic and organized way around the current situation is only going to benefit us in the long run. Better connectivity reduces transportation costs immensely and saves time in traveling.
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Professor Amal Kumarage, Endeavour Executive Fellow, presented his research on Transport Planning as part of the SMART Seminar Series on Tuesday, 25th November 2014.
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1. Harun
al-‐Rasyid
LUBIS
h4p://personal.;sl.itb.ac.id/halubis/
Fakultas
Teknik
Sipil
dan
Lingkungan
ITB
SJ-‐5245
Pemodelan
Sistem
Transportasi
Review
Transporta/on
Network
Modeling
1
2. 2
Review
:
Model
Transport
4
Tahap
Trip Generation
Trip Distribution
Modal Split
Trip Assignment
Volume Lalu Lintas
Jaringan
Transportasi
Sistem
Zona
Tata Guna Lahan dan
Karakteristik Sosio
Ekonomi
5. 5
Asal
/Origin (O)
Tujuan
/Destination (D)
Perjalanan
/Trip (t)
Perjalanan/Trip
D5
D1
O
D2
D3
D4
30
%
20
%
10
%
25
%
15
%
Bangkitan seluruh perjalanan
dari zona asal (O)
Distribusi seluruh
perjalanan dari zona
asal (O) ke semua zona
tujuan (D)
!
Mobil Pribadi 25%
Kendaraan Umum
20%
Motor 30%
Tak Bermotor 15%
Jalan Kaki 10%
Tujuan
/Destination
(D1)
Asal
/Origin (O)
Asal
/Origin (O)
Tujuan
/Destination
(D1)
Σ t
Pemilihan/pemisahan
perjalanan menurut
jenis moda dari zona
asal (O) ke zona tujuan
(D1)
Pembebanan perjalanan
menurut jenis moda
kepada rute-rute
(jaringan) diantara
pasangan zona asal (O)
dan zona tujuan (D) utk
public dan private
transport
9. 9
Asumsi
Dasar
Model
Transport
• Pola
interaksi
dan
perilaku
• Memaksimalkan
uVlitas
• KeseVmbangan
(equilibrium)
• Agregasi
10. 10
Interaksi
Transport
–
Tata
Guna
Lahan
Pemilihan
Rute
Pemilihan
Moda
Pemilihan
Tujuan
Keputusan Melakukan Perjalanan
Kepemilikan
Kendaraan
Aktifitas
Penempatan Lahan
Pembangunan
Pemilihan Lahan
oleh Investor
Pemilihan Lahan
oleh Pengguna
Daya Tarik Lahan
Aksesibilitas
Waktu Tempuh/
Jarak/Biaya
Volume di Ruas
Jalan
TRANSPORTASI
GUNA LAHAN
11. Tata
ruang
dan
transportasi
RUANG
AKTIVITAS
POTENSI
PERGERAKAN
PERFORMANCE
INDICATORSISTEM
TRANSPORTASI
aksesibilitas
Ham
batan
ruang
Kapasitas
Direpresentasikan oleh:
1. Jaringan transportasi
a. Prasarana
b. Sarana
2. Pengaturan
RUANG
AKTIVITAS
POTENSI
PERGERAKAN
PERFORMANCE
INDICATORSISTEM
TRANSPORTASI
aksesibilitas
Ham
batan
ruang
Kapasitas
Direpresentasikan oleh:
1. Jaringan transportasi
a. Prasarana
b. Sarana
2. Pengaturan
11
12. 12
Proses
Pemodelan
Transport
“Best fit” model
Variabel model
Base year data
Spesifikasi Model
Struktur model
Kalibrasi Model
Validasi Model
Validation data
Predicted data
Implementasi Model Out put model
Analisis
14. Transit
Assignment
Results
2001
Base
Case
Observed vs Predicted Transit Line Boardings
0
2000
4000
6000
8000
10000
12000
14000
0 2000 4000 6000 8000 10000 12000
Observed
Predicted PRED
Total Boardings by Sub-Mode OBS PRED RMSE RMS%
Durham Bus 7499 7164 126.1891 1.68%
York Bus 7111 7280 143.0784 2.01%
Peel Bus 38497 40217 332.7368 0.86%
Halton Bus 4536 4990 81.51716 1.80%
HSR Bus 15982 16337 292.8422 1.83%
GO Bus 7172 7353 399.3889 5.57%
GO Rail 13659 13735 645.6756 4.73%
TTC Bus 282084 260041 1038.175 0.37%
TTC Prem Bus 672 101 176.9569 26.33%
TTC Subway 254060 235691 9103.319 3.58%
TTC Streetcar 47097 47097 1201.121 2.55%
Overall 678369 640006 1036.107 0.15%
Final
parameter
sedngs
with
embedded
transit
fares
seem
to
be
providing
good
assignment
of
transit
trips
to
lines
and
sub-‐modes.
14
16. The
Number
of
Boarding
and
AlighKng
in
Tehran
Transit
Stops
in
Morning
Peak
Hour,
2003
16
17. 17
Sistem
Zona
(kecamatan)
contoh
:
Jakarta
Mass
Rapid
Transit
System
Study
211
241
212
213
214
215
216
217
218
231
227
226
225
224
223
232
234
233
222
242
245
246
249
238
237
236
235
244
243
251
253
259
261
254
248
247
255
256
257
258
271
Zona Internal
Zona Eksternal
18. Greater
Bandung
Metropolitan
Public
Transport
Zoning
13
Zones
based
on
Density
5 6 7
2 3 41
North BMA (Cimahi +Bandung Barat)
1
=
Kota
Cimahi
2
=
Kota
Bandung
2
3
=
Kota
Bandung
3
4
=
Kota
Bandung
4
5
=
Kota
Bandung
5
6
=
Kota
Bandung
6
7
=
Kota
Bandung
7
South West
Bandung
South East
Bandung
South West BMA South East BMA
Sumedang
18
19. Greater
Bandung
Metropolitan
Public
Transport
Socio-‐economic
Analysis
PopulaVon
and
GDP
by
Zones
in
BMA
(2006)
No. D es cription
P opulation
in
1,000
G D P
per
capita
in
Mio
R s
Z one
1 K ota
B andung
1 375
Z one
2 K ota
B andung
2 475
Z one
3 K ota
B andung
3 263
Z one
4 K ota
B andung
4 234
Z one
5 K ota
B andung
6 525
Z one
6 K ota
B andung
5 307
Z one7 North
B MA 950 13
Z one
8 S outh
Wes t
B MA 1.105 15
Z one
9 S outh
E as t
B MA 545 13
Z one10 S outh
E as t
B andung 800 15
Z one
11 S outh
Wes t
B andung 710 15
Z one
12 C imahi
NW
B andung 520 16
Z one
13 S pecial
Z one
S umedang 235 9
18
19
20. Zone
x
Zone z
Zone y
Greater
Bandung
Metropolitan
Public
Transport
Methodology
of
the
Analysis
of
Traffic
Pa4ern
in
BMA
(1)
Commuter
Rail
Toll
Road
Bus
Line
Traffic
Volume
Each
Zone
is
trips
Generator
and
a4ractor
20
23. MULTIMODAL NETWORK REPRESENTATION
A
C
B
Jl,Rl
Jl
Jl,Kl
A
C
B
:Jalan
:Rel
:Kapal
(a)
(b)
Penyederhanaan
tampilan
jaringan
TiVk
simpul
(TERMINAL)
tempat
perpindahan
moda
23
24. MODELLING
OF
SEA
NODE
Dermag
a
Waktu Merapat
Waktu Tunggu
Source:
Diolah
dari
PELINDO
• Berthing time, approaching and waiting time is time to represent sea node capacity
• Sea node capacity depend on loading and unloading facilities and type of commodity
– Container, bulk and liquid cargo have fast loading and unloading
– General cargo has slow loading and unloading
• Berthing time, approaching and waiting time also represent process of loading and unloading
Berth
Berthing
Vme
WaiVng
and
Approaching
Time
24
25. 25
Rail
StaVon
Micro-‐coding
Streets
Bus
plalorm
node
Rail
plalorm
node
MetroRail
PNR
KNR
Time=
~1
min
Time=
~0.5
min
Time=
~2
min
Time=
~2
min
Access
Connectors
Escalator
Link
Time=
~1
min
Source:
AECOM
Consult
29. Trip
Assignment
ObjecKves:
• Explain
the
concept
of
an
all-‐or-‐nothing
assignment
• Explain
the
concept
of
an
equilibrium
assignment
• MathemaVcal
formulaVon
&
finding
soluVon
+
algorithm
• IdenVfy
the
cost-‐flow
or
delay-‐flow
funcVon
29
30. Inputs
and
Outputs
Inputs
•
O&D
trip
table
•
Coded
network
Outputs
•
Link
flows
as
per
coded
network
•
Link
travel
Vmes/speeds
•
VMT
•
Vehicle
hours
of
travel
30
31. Step 3:
Continue until
trips between all
TAZ pairs have
been assigned
Step 2:
Assign all trips to
links
compromising
shortest route
Step 1:
Find Shortest
route between
the TAZs
All-‐or-‐Nothing
Assignment
Advantages
• Simple
• Inexpensive
• Results
easy
to
understand
Disadvantages
• Assumes
all
traffic
will
travel
on
shortest
path
• Creates
unrealisVc
flow
pa4erns
31
32. Logit
model
Can
set
Ui
=
1/4i,
but
if
you
do,
will
need
a
calibraVon
coefficient
Can
set
Ui
=
-‐4i
(7)
(8)
(9)
67
24
9
These
results
From
this
specificaVon
32
33. Capacity
Restraint
• Volume-‐delay
relaVonship
• Average
travel
speed
decreases
with
increased
flow
(volume)
• Average
travel
Vme
increases
as
the
volume-‐to-‐capacity
raVo
on
a
link
increases
• The
Bureau
of
Public
Roads
(BPR)
formula,
used
as
default
in
most
model
packages
shows
this
relaVonship:
Travel
Vme
depends
on
the
loading,
but
the
loading
depends
on
the
travel
Vme
–
it’s
an
iteraVve
process
33
35. 4/5/16
35
One attempt to re
the relationships a
urban activities an
transportation mo
PTV Americ
36. Jenis Pergerakan
a. Eksternal – Eksternal
b. Eksternal – Internal
c. Internal –internal
Sumatera
c
a
b
b
Prov. Banten
D K I
JABAR
37. Pola
Pergerakan
Angkutan
KAB.PANDEGLANG
KOTA.SERANG
KAB.TANGGERANG
KAB.LEBAK
KOTA.CILEGON
KAB.SERANG
KOTA
TANGGERANG
KOTA
TANGGERANG
SELATAN
38. Basis Pemodelan Transportasi
Data
Jaringan
dan
Data
Zona
(18
x
18)
• Analisa
Kebutuhan
•
Penanganan
Jaringan
OD
/
MAT
Dasar
(2012)
Model
SATURN
(Buffer
network)
Prediksi
Arus
Lalu
Lintas
y.a.d
Model
Distribusi
(
Gravitasi
&
Furness
)
Proyeksi
MAT
y.a.d
O-‐D
2011
39. 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Sistem
Zona
Prov.
Banten
(
18
x
18)
1
Kota
Tangerang
101
2
Kab
Tangerang
102
3
Kota
Tangerang
Selatan
103
4
Kota
Serang
104
5
Kota
Cilegon
105
6
Kab
Serang
106
7
Kab
Pandeglang
107
8
Kab
Lebak
108
9
Kab
Pandeglang
2
207
10
Kab
Lebak
2
208
11
Local
A9rac/on
401
12
Local
A9rac/on
402
13
Local
A9rac/on
403
14
Local
A9rac/on
404
15
Local
A9rac/on
405
16
DKI
Jakarta
901
17
Jawa
Barat
902
18
Sumatera
903
40. Permasalahan transportasi Prov. banten
-TRANSPORTASI DARAT
• Kemacetan
Banyak faktor yang menjadi penyebab kemacetan di wilayah ini, namun peningkatan jumlah kendaraan
tanpa diiringi dengan pelebaran jalan yang memadai adalah penyebab utama kemacetan.
• Kerusakan Jalan
Berbagai macam hal dapat menyebabkan kerusakan jalan di Prov. Banten, di antaranya:
# Peningkatan beban / overloading
# Air tak terkendali
# Material konstruksi perkerasan
# Kondisi tanah dasar yang tidak stabil
# Iklim dan cuaca
# Proses pemadatan perkerasan di atas tanah dasar yang kurang baik.
• Rendahnya Kualitas pelayanan angkutan Umum ( lokal dan komuter)
• Tersendatnya penyebrangan Merak-Bakauhuni ( hambatan alam, kurang armada siap operasional)
• TRANSPORTASI LAUT
• * Tersendatnya rencana pembangunan Pelabuhan Internasional, SptPel. Bojonegara
- TRANSPORTASI UDARA
* Lalu Lintas yang padat, baik pesawat maupun penumpang yang diakibatkan pertumbuhan penumpang
yang sangat tinggi tidak diimbangi dengan penambahan luas area Bandara,
* Permasalahan SDM pengelola
* Rendahnya akses menuju ke Bandara, di mana akses menuju Bandara hanya di dominasi oleh
kendaraan pribadi, taxi, travel dan bus.
47. Penamaan Ruas dan Simpang
15
14
8
9
11 12
1
2
3
4
5
6
7
10
13
A
B
C
D
F
G
H
I
J
K
L
M
N
O
PQ
R
S
T
U
V W
X
Y
8 : Nomor Simpang
A : Kode Ruas
Keterangan:
Z
Z
E
47
48. Hasil Validasi 2015 pada Jam Puncak
Sore
15
14
8
9
11 12
13
1
2
3
4
6
7
10
A
B
F
G
K
L
N
O
PQ
R
S
T
U
V W
X
Y
8 : Nomor Simpang
A : Kode Ruas
Keterangan:Z1
H
5
16
E
D Z
M
GEH 4.25
GEH 3.05
GEH 3.44
GEH 4.17
GEH 3.16
GEH 2.85
GEH 0.85
GEH 3.41
GEH 4.95
GEH 4.27
GEH 6.1GEH 5.49
GEH 2.06
GEH 1.02
GEH 2.37
48
49. Kinerja Jaringan Jalan Tahun 2015
Pagi
: Panjang Antrian
TZ
H
Panjang antrian pada jam puncak
pagi
49
50. Kinerja Jaringan Jalan Tahun 2015
Sore
: Panjang Antrian
N
M
T
Y
Panjang antrian pada jam puncak
sore
50
51. Skenario Pemodelan
• Traffic
berkurang
20%
akibat
penerapan
skenario
penanganan
di
atas.
• Tambahan delay 15 detik per kendaraan
pada akses masuk ke STJ.
51
52. Panjang Antrian pada Jam Puncak Pagi
donothing dosomething
: Panjang Antrian
do-nothing setelah penanganan,
tanpa frontage road
52
53. Kecepatan Rata-rata pada Jam Puncak
Pagi
Ket:
15
6060
10
donothing dosomething
do-nothing setelah penanganan,
tanpa frontage road
53
54. Panjang Antrian pada Jam Puncak Sore
donothing dosomething
: Panjang Antrian
setelah penanganan,
tanpa frontage road
do-nothing
54
55. Panjang Antrian pada Jam Puncak Pagi
K
M
N
W
: Panjang Antrian
Setelah
penanganan, tanpa
frontage road
setelah
penanganan,
dengan frontage
road
55