ENHANCHING PUBLIC TRANSPORT SYSTEM IN BOGOR TOWARD MULTIMODAL PUBLIC TRANSPORT SYSTEM
Presented in International Conference, The Seventh Asia Pasific Conference on Transportation and The Environment, APTE7, 3-5 June 2010
Semarang, Indonesia
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Erika BUCHARI Associate Professor Department of Civil Engineering Fakultas Teknik Sipil Universitas Sriwijaya Jalan Raya Palembang-Prabumulih Km.32 Indralaya. 30662 eribas17@gmail.com |
Gandhi Indra PERMANA Alumni Department of Civil Engineering Fakultas Teknik Sipil Universitas Sriwijaya Jalan Raya Palembang-Prabumulih Km.32 Indralaya. 30662 gandhi_88@yahoo.co.id |
ABSTRACT
Multimodal Public Transport (MMPT) is a series of trips that use two or more modes, which are integrated, connected by transfer points, and have the rules so that the travel using public transport can be shortened in terms of time and money. This research is connected to the previous studies and findings of Ness (2002), Krygsman (2004), and Buchari (2008). The steps of the research is firstly to find the problems on the field, secondl, to set up the goals, and study the literature. Then, the nest step is to collect, process and analyze the data. Data were collected by the counting surveys, public transport movement surveys, and interview surveys. Data were analyzed by description method and matrix methods. The description method is outlining the eight variables, which includes family status, gender, age, employment, and number of vehicles in the family car. The number of motor vehicles in the family, private vehicle user priorities in the family, and the salaries (plus allowances) per month. While the matrix method is revealing the analysis of multimodal components; namely connecting modes, main modes, multimodal networks, facilities for intermodal transition, and regulations. Modal split for all trips with a distinction between unimodal and multimodal trips are obtained. The share of multimodal trips is 48.10% of all trips, which is higher than Palembang, which is 32.9% and Netherlands 2.9%.
Keywords: Multimodal Public Transport . Unimoda. Multimodality. Transfer Points
1. INTRODUCTION
Travel arises because someone has to move from one place to another to get the needs and activities. Therefore. for each trip there must be the origin and destination. In the process of achieving origin and destination. Sometimes people only use one vehicle (unimoda), which is usually used as personal vehicles. But there are also many people that use more than one mode (multimoda) for travel in public transport system. The travels that use several modes usually need longer journey time and more money, so many of them switch to personal vehicles.
Multimodal Public Transport (MMPT) is a transportation system that offers public transportation systems which are connected and integrated one another so that the trip using public transportation from origin to destination will be more effective and efficient. both in time and cost. MMPTcan have an integrated system. such as one means of payment (cards. smart cards). In addition, MMPT also has integrated schedules of many routes. Therefore. MMPT can be one solution to attract private vehicle users to use public transport so that it can reduce the volume of vehicles on the highway.
Bogor has acute urban transportation problem. It is known as the ‘Kota Sejuta Angkot’, which describes the level of current stage of public transports operated in Bogor. Angkutan Kota (Angkot). informal public transports have been suspected as the causes of congestion in Bogor. Researches on multimodality of Public Transport have been done by Nes in the Netherlands. and Buchari in Palembang (Nes. 2002. Buchari. 2008). In Netherlands. the share of multimodality only 2.9% while in Palembang reached 32.9%. This means the Netherland dominated by single or unimoda public transport (bicycle and cars) whereas Palembang is dominated by public transports.
As it has been done in the Netherlands and Palembang, the study of multimodal public transport in Bogor will be conducted. The purpose of this research is; (1) to obtain data regarding the share of multimodality in Bogor and to solve the problem of its public transport. What are the causes of the heavy congestion in the central city of Bogor? Is it because of the high mobility of the internal movement of population Bogor itself. or it is caused by internal-external and external-internal trip. or it may well be caused by external-external movement crossing Bogor city; (2) to fulfil the real need of public transportation in Bogor.
2. LITERATURE STUDY
Multimodal Public Transport system has been well known in recent years. Some model approaches have been developed by many researchers, such as developing intermodal transport building, and developing the travel behaviour demand models for multimodal travel chain. Among researchers that have multimodal public transport research (MMPT). Nes analyzed the level of multimodal public transport needs in the Netherlands (Nes. 2002). Krygsman found the main modes, access and aggress modes on multimoda network (Krygsman. 2004). Buchari found six main components contained in multimodal public transport system as it is presented in the following figure (Buchari . 2008). It includes (1) Connecting Modes or before (access) and after (egress) modes, (2) Main Modes, (3) Multimodal Network (Main route. Feeder Route), (4) Transfer Point, (5) Intermodal Transfer Points and (6) Counter Measures.
Figure 1: Component of multimodal public transportation
3. METHODOLOGY
Overall plan of this research can be seen in the following flow chart.
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Literature Study |
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Goal: Enhancing PT system toward MMPT system |
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Problem on the field: Congestion, execcive no of Oplet, low occupancy of oplet
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Problem Formulation: · How is the characteristics of passenger of PT in Bogor · How is Level of multimodality di Bogor · How is components of MMPTin Bogor |
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Data Collection:
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Data Processing: Tabulation, matrices product
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Analysis: · Descriptive Analysis · Matrices Analysis for elements of MMPT
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Conclusion
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Primary Data: Counting survey, public transport movement survey, interview survey)
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Secondary data: Central Statistics Beurou (Badan Pusat Statistik)
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Figure 2: Flow Chart of Research
4. ANALYSIS AND DISCUSSION
4.1. Counting Survey
The survey location is shown in Figure 2. After processing the data of counting survey which is conducted in 6 of the city borders in Bogor. The results can be presented as in the following table 1, 2, and 3. As a whole, it can be concluded that trips in and out of Bogor (External-Internal and Internal-External trip) are dominated by motorcycle. The average use of motorcycles reached above 50% on every street in every postal survey, except in Tajur and Ciheuleut. In Ciheuleut, only a little number of motorcycles that pass through the road because it is a TOLL road access so that it was dominated by private cars.
From the Counting data, it can also be seen that the movement of vehicles in and out for micro-buses and buses are still very low (not more than 9%). People prefer to use their own motorcycle rather than buses. It is because they prefer to travel fast, to feel safe, comfortable. effective and efficient. The high use of motorcycle (and private car use) cause heavy traffic congestion and this is a big problem in transportation system. Therefore, it requires a system that can answer these demands so that private vehicle users can switch to public transport modes.
Table 1: Vehicle Movement Composition at 07.00-09.00 (in percent)
|
Direction Movement |
TWV |
PC |
O |
MB |
B |
MC |
LGV |
NMV |
Total |
|
Parung (Parung - Bogor) |
0 |
16.74 |
10.74 |
2.6 |
0.5 |
56.72 |
12.69 |
0 |
100 |
|
Parung (Bogor - Parung) |
0 |
22.84 |
15.64 |
3.32 |
1.23 |
46.91 |
10.07 |
0 |
100 |
|
Cibinong (Cibinong-Bogor) |
0.04 |
14.77 |
18.73 |
2.06 |
1.29 |
56.15 |
6.966 |
0 |
100 |
|
Cibinong (Bogor-Cibinong) |
0 |
23.35 |
15.46 |
0.77 |
0.84 |
52.09 |
7.489 |
0 |
100 |
|
Tajur (Sukabumi-Bogor) |
0 |
16.23 |
21.25 |
1.92 |
3.52 |
36.12 |
20.93 |
0.03 |
100 |
|
Tajur (Bogor-Sukabumi) |
0 |
16.74 |
12.8 |
8.19 |
7.46 |
25.06 |
29.76 |
0 |
100 |
|
Ciheuleut (Jakarta - Bogor) |
0 |
84.43 |
1.787 |
1.83 |
3.07 |
0 |
8.887 |
0 |
100 |
|
Ciheuleut (Bogor - Jakarta) |
0 |
86.98 |
1.83 |
0.88 |
2.58 |
0 |
7.734 |
0 |
100 |
|
Ciomas (Ciomas-Bogor) |
0 |
18.46 |
30.44 |
0.19 |
0 |
45.44 |
5.466 |
0 |
100 |
|
Ciomas (Bogor-Ciomas) |
0 |
10.11 |
21.86 |
0 |
0 |
47.35 |
20.68 |
0 |
100 |
|
Dramaga (Dramaga-Bogor) |
0 |
9.468 |
18.62 |
0.14 |
0.07 |
67.37 |
4.335 |
0 |
100 |
|
Dramaga (Bogor-Dramaga) |
0 |
10.73 |
21.12 |
0.2 |
0.32 |
62.01 |
5.613 |
0 |
100 |
Source: analysis
Table 2: Vehicle Movement Composition at 12.00-14.00 (in percent)
|
Direction Movement |
TWV |
PC |
O |
MB |
B |
MC |
LGV |
NMV |
Total |
|
Parung (Parung - Bogor) |
0 |
17.16 |
10.58 |
1.59 |
0.33 |
53.13 |
17.2 |
0 |
100 |
|
Parung (Bogor - Parung) |
0 |
21.25 |
8.63 |
1.32 |
0.12 |
52.44 |
16.3 |
0 |
100 |
|
Cibinong (Cibinong-Bogor) |
0 |
18.25 |
20.15 |
1.65 |
0.19 |
46.91 |
12.8 |
0 |
100 |
|
Cibinong (Bogor-Cibinong) |
0 |
13.67 |
15.13 |
0.76 |
2.28 |
56.67 |
11.5 |
0 |
100 |
|
Ciheuleut (Jakarta - Bogor) |
0 |
74.2 |
2.31 |
1.37 |
2.56 |
0 |
19.6 |
0 |
100 |
|
Ciheuleut (Bogor - Jakarta) |
0 |
80.63 |
1.135 |
0.71 |
2.77 |
0.213 |
14.5 |
0 |
100 |
|
Tajur (Sukabumi-Bogor) |
0 |
17.89 |
23.96 |
3.3 |
2.85 |
34.68 |
17.3 |
0 |
100 |
|
Tajur (Bogor-Sukabumi) |
0 |
17.87 |
27.73 |
1.61 |
2.44 |
38.3 |
12 |
0 |
100 |
|
Ciomas (Ciomas-Bogor) |
0 |
21.76 |
21.49 |
0.27 |
0 |
53.24 |
3.24 |
0 |
100 |
|
Ciomas (Bogor-Ciomas) |
0 |
9.968 |
26.27 |
0.04 |
0 |
61.05 |
2.67 |
0 |
100 |
|
Dramaga (Dramaga-Bogor) |
0 |
12.66 |
24.47 |
0.18 |
0.07 |
54.96 |
7.64 |
0 |
100 |
|
Dramaga (Bogor-Dramaga) |
0 |
14.08 |
21.79 |
0.19 |
0 |
54.91 |
9.03 |
0 |
100 |
Source: analysis
Table 3: Vehicle Movement Composition at 16.00-18.00 (in percent)
|
Direction Movement |
TWV |
PC |
O |
MB |
B |
MC |
LGV |
NMV |
Total |
|
(Parung - Bogor) |
0 |
15.65 |
7.743 |
1.15 |
0.11 |
63.26 |
12.1 |
0 |
100 |
|
Parung (Bogor - Parung) |
0 |
27.32 |
8.101 |
1.02 |
0.2 |
46.67 |
16.7 |
0 |
100 |
|
Cibinong (Cibinong-Bogor) |
0.02 |
13.43 |
16.56 |
2.04 |
0.55 |
62.19 |
5.22 |
0 |
100 |
|
Cibinong (Bogor-Cibinong) |
0 |
10.97 |
12.36 |
0.92 |
0.41 |
69.54 |
5.81 |
0 |
100 |
|
Ciheuleut (Jakarta - Bogor) |
0 |
85.81 |
0.965 |
1.07 |
1.86 |
0.034 |
10.3 |
0 |
100 |
|
Ciheuleut (Bogor - Jakarta) |
0 |
80.14 |
3.05 |
1.23 |
1.82 |
0.036 |
13.7 |
0 |
100 |
|
Tajur (Sukabumi-Bogor) |
0 |
21 |
24.84 |
2.56 |
3.19 |
32.92 |
15.5 |
0 |
100 |
|
Tajur (Bogor-Sukabumi) |
0 |
19.3 |
29.65 |
4 |
1.84 |
32.83 |
12.4 |
0 |
100 |
|
Ciomas (Ciomas-Bogor) |
0 |
25.88 |
20.21 |
0.29 |
0.57 |
49.86 |
3.19 |
0 |
100 |
|
Ciomas (Bogor-Ciomas) |
0 |
10.62 |
28.4 |
0.04 |
0.11 |
59.05 |
1.79 |
0 |
100 |
|
Dramaga (Dramaga-Bogor) |
0 |
11.48 |
17.25 |
0.16 |
0.23 |
63.32 |
7.56 |
0 |
100 |
|
Dramaga (Bogor-Dramaga) |
0 |
9.73 |
18.75 |
0.32 |
0.06 |
66.25 |
4.88 |
0 |
100 |
Source: analysis
Note:
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TWV |
= |
Three Wheel Vehicle (Bemo dan Bajaj) |
|
PC |
= |
Private Car (sedan. st wagon. jeep) |
|
O |
= |
Opelet (public transport). Pick Up. Combi. Sub Urban |
|
MB |
= |
Micro Bus |
|
B |
= |
Bus |
|
MC |
= |
Motor cycle |
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LGV |
= |
Light Good Vehicle (pick up. truck) |
|
NMV |
= |
Non Motorized Vehicle (bicycle. pedicap. pulled by animal) |
|
|
|
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Figure 3: Map of Counting Survey Locations
4.2. Public Transport Movement Survey
Public Transport Movement Survey was conducted in 4 public transportation routes in Bogor. The results can be seen in Figure 4, 5, 6 and 7 as in the following sub sections.
4.2.1. Public Transport 01 (Baranangsiang-Ciawi) Route
From the Figure 3, it can be seen that the public transport route 01 (Baranangsiang-Ciawi) has quite high load factor, which is 0.74, but it is only at 16.00-18.00 hours. While at 07.00-09.00 hours and 12.00-14.00 the load factors are still low, namely 0.59 and 0.52. It means that the number of public transport Baranangsiang-Ciawi is excessive so that occupancies are low. Therefore, oplets needs to be reduced because it is considered less efficient.
Figure 4: The Graph of Loading Factor in Baranangsiang-Ciawi Route
4.2.2. Public Transport 03 (Baranangsiang-Bubulak) Route
Figure 4 shows that the public transport route 03 (Baranangsiang-Bubulak) has an extremely high load factor (1.2). It seems that number of oplets are less then they were required. But after it is confirmed with the number of oplets during the day. It shows that the route has high load factor only in short time during congestion time (12.00-14.00). Meanwhile. in the morning hours (07.00-09.00) and afternoon (16.00-18.00) load factors are still low, which is 0.49. This shows that there has been a very bad traffic at the time. This makes the spread of passengers is not smooth at that hours.
Figure 5: The Graph of Loading Factor in Baranangsiang-Bubulak Route
4.2.3. Public Transport 05 (Cimahpar-Ramayana) Route
From the Figure 5, it reveals that the route 05 (Cimahpar-Ramayana) has very low load factors in the morning (07.00-09.00). which is only 0.23 on the average. But there are enough passengers jump drastically in the afternoon and evening time. respectively 0.64 and 0.69.
Figure 6: The Graph of Loading Factor in Cimahpar-Ramayana Route
4.2.4. Public Transport 08 (Pasar Anyar-Citeureup) Route
From the Figure 6, it shows that route 08 (Pasar Anyar-Citeureup) has a low load factor. This means that the number of public transport (Pasar Anyar-Citeureup) in Bogor is excessive. Therefore, the reduction of number of oplets is necessary for this direction because it is not efficient.
Figure 7: The Graph of Loading Factor in Pasar Anyar-Citeureup Route
4.3. Interview Survey
Surveys was conducted between 2-5 October 2009, in residence of 6 Zones (kecamatan), terminal, and train station. Population is represented by population of households which has members in age of trip makers (Assumed as Senior high school students to elderly). Number of Bogor Population, according to statistical data in 2006 is 750,250. Sampling taken for interview survey is 3025. After processing the data from interview surveys. obtained information on population characteristics of Bogor travel patterns can be seen in Table 4.
Table 4: Characteristics of travel patterns of residents Bogor
|
Variable |
Characteristics |
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Family Status |
Father (47.93%); Children (37.72%); Mother (12.93%); Brothers/sisters (1.32%); Grandmother/Grandfather (0.10%) |
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Gender |
Men (73.19%); Women (26.81%) |
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Age |
Age 25-40 (46.48%); Age 41-60 (23.97%); Age 18-24 (18.81%); Age 12-17 (9.65%); Age >60 (1.09%) |
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Employment |
Private Sector (33.52%); Students (17.55%); Trader/Private (17.39%); Civil Servant (8.40%); labour (7.85%); Security (4.76%); Housewives (3.7%); Professionals (0.79%); Managers (0.69%); Retirement (0.83%); Farmers (0.83%); Unemployment (1.16%) |
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Number Of Car In The Family |
No Car (94.21%); One Car (5.06%); Two Cars (0.60%); More than two Cars (0.13%) |
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The Number Of Motorcycle In The Family. |
No motorcycles (48.73%); One motorcycles (46.94%); two motorcycles (3.90%); More than two motorcycles (0.43%) |
|
Private Vehicle User Priorities In The Family |
No Private Cars (46.18%); Father (36%); Children (14.38%); Mother (2.28%); Brothers/sisters (1.12%); Grandmother/Grandfather (0.03%) |
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The Salaries And Allowances Per Month |
Rp500.000.00-Rp1.500.000.00 (44.76%); Rp1.500.001.00-Rp2.500.000.00 (24.99%); less than Rp500.000.00 (22.71%); Rp2.500.000.00-Rp3.500.000.00 (5.36%); Rp3.500.000.00-Rp5.000.000.00 (1.52%); more than Rp5.000.000.00 (0.66%) |
Source: analysis
4.4. Multimodality in Bogor
Table 5 shows the modal split for all trips with a distinction between unimodal and multimodal trips. It can be seen from the table that the share of multimodal trips is 48.10% of all trips. If it is compared to Palembang study case (Buchari. 2008) which is 32.9% of all trips are multimodal. the need for multimodal trip in Bogor is quite high.
Table 5: The level of multimoda public transport needed in Bogor
|
Main modes |
all trips (%) |
unimodal (%) |
multimodal (%) |
% multimoda |
|
Walking |
13.68595 |
13.55371901 |
0.132231405 |
0.966183575 |
|
Bicycle |
0.2644628 |
0.26446281 |
0 |
0 |
|
Pedicap |
1.1570248 |
0.132231405 |
1.024793388 |
88.57142857 |
|
(Take) Motorcycle |
32.92562 |
32.66115702 |
0.26446281 |
0.803212851 |
|
(Passenger) Motorcycle |
2.9752066 |
0.925619835 |
2.049586777 |
68.88888889 |
|
(Take) Car |
2.9421488 |
2.776859504 |
0.165289256 |
5.617977528 |
|
(Passenger) Car |
0.7933884 |
0.396694215 |
0.396694215 |
50 |
|
Bus |
6.1487603 |
0.132231405 |
6.016528926 |
97.84946237 |
|
Public Transport |
33.652893 |
0.991735537 |
32.66115702 |
97.05304519 |
|
Train |
5.0578512 |
0 |
5.05785124 |
100 |
|
Taxi |
0.0330579 |
0 |
0.033057851 |
100 |
|
Passenger (Truck) |
0 |
0 |
0 |
0 |
|
Others |
0.3636364 |
0.066115702 |
0.297520661 |
81.81818182 |
|
|
100 |
51.90082645 |
48.09917355 |
|
Source: analysis
It can be seen that the passengers of train and taxi modes have a percentage reaches 100%. For train. it is reasonable that the user requires another mode. But for the taxi. this 100% multimodality reveals that people use taxis only for connection, not for door to door service as usual.
For users of cars and motorcycle, the percentage of multimodality or dependency on other modes are low , which are 0.80 and 5.62. This shows that almost all private vehicle users do not change the modes to reach their destination. But passengers of Cars and Motorcycles which have options in choosing private and public vehicles, their demands are parking facilities at terminals and stations to facilitate them to change their modes to buses and trains. This demands account for 68.89% and 50%.
Captive passengers of bus and oplet, their multimodality or dependencies on other modes is ultimate and extremely high which are 97.85 and 97.05. This indicates that bus and oplet need to combine with other mode and it should be facilitated.
4.5. Analysis Results of Multimodal Public Transport Components
The results of analysis of 6 components of multinodality will be described in subsequent sub headings.
4.5.1. Connecting Modes
From the matrix Origin1-Moda. it can be seen that the most chosen mode for the first mode in the tripchain is walking (54.12%). See Figure 7. This means that there is the need for sidewalk facilities, such as zebra cross, and bridge crossing on the highway or road, good pedestrian without mud, and street lights for pedestrian at night. The second highest mode choice for acces modes are motorcycles, which is 24.71%. Many Bogor residents who do not use public transport will choose motorcycle to reach their destination. The third rank of access modes is oplet (3.83%). Next access choices are cars (2.98%), passenger motorcycle (2.28%), passenger cars (0.73%, becak (0.3 %). and bicycles (0.3%).
4.5.2. Main Mode
From the matrix Mode1- Mode2, it is revealed that the most mode used in the second mode is the main mode of public transport, which is oplet 72.68%, followed by Bus (6.85%), Train (7.14%). But all those main modes are obviously dependent on the population with modes public transport in Bogor. It was the government who should give special attention to the existence of the public transport. especially infrastructure facilities and regulations. It aims to create a comfortable atmosphere. and safety in Bogor.
4.5.3. Multimoda Public Transport Network
Public Transport Network can be analyzed from matrices origin-mode1, orgin-mode2 etc. It can be recognized that the primary network and feeder networks are overlapped. Oplets are operated in the network in the city, in pramary and secondary road. However, oplets are also are operated in small streets in kampong and residential areas as access roads.
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Figure 8: Multimodal Public Transport Network in Bogor
4.5.4. Transfer Point (TP) and Intermodal Transfer Point (ITP)
TP and ITP analysis using matrices program M1-M2, M2-M3, M3. M4, and M4-M5.
1) Analysis of Matrix M1-M2:
Based on Matrix M1-M2, the largest access modes to the train is walking 52 trip ( 49.06%). motorcycle 26 trips (24.53%).,public transport 19 trip (17.92%). The second largest mode before using the train mode is motorcycle (24.53%). This shows the need for parking facilities to accommodate the motorcycle before continueing the journey by train. Before using the train, many respondents use oplet (17.92%). This needs Intermodal Transfer Points between Oplet and Train mode.
2) Analyze of Matrix M2-M3
The matrix M2-M3 gives data 715 trips (56.22%) that terminated. It can be seen from the connection by walking. and continued trip by (passenger) motorcycle are 10 trips (1.20%). Respondents that continue the trips is 297 (41.54%) consists of 87 trips travel (12.17%) by the bus. 168 trips (23.50%) by public transport. 42 trips (5.87%) by public transport that in the third modes of travel (people who use up to 3 modes ).
3) Analyze of Matrix M3-M4
By viewing the M3-M4 matrix. the remaining trip that seems continue from the third mode to the fourth mode by public transport are 46 trips ( 24.60%), continued with bus and train as much as 9 ( 4.81%). The travellers that terminate at their destinatioan by using mode 3 and 4 were 117 respondents (62.57%) consisted of 1 respondent by walking (0.33%). 1 respondent by becak (0.33%). 28 respondents by the bus (9.33%).100 respondents by oplet (33.33%), and 44 respondent by train (14.67%). Taxi passengers are as much as 2 (0.67%). and others as much as 6 trips (2%).
4.5.5. Regulation. Policies and Organizations
Regulations, policies. and organizations should be prepared for MMPT. The preparation regulation includes institutional reform, Route network planning policy, Intermodal Transfer Point, Time Schedule, new mass transit, the service organization, payment system, partnership system, public transport service tender, Organizations required (Urban transport authority; and Organization of public transport operators).
5. CONCLUSION
From the previous chapters. it can be conclude that:
(1) The share of multimodality in Bogor is 48.10% (Palembang, 32.9% and Netherlands, 2.9%). Dependency of oplets on other modes should be taken account. From Origin Destination Matrices, the internal zone trips are high, but if we see from matrices Origin-Modes, it can be seen that mostly first trip done by walking ( %). If government provided public transport services based on Origin Destination data only, without considering Origin-mode matrices, the provision of service will be misleading. As a result, the real problem of oplets is low load factors of oplets in central area. The city gives the service for local urban people, such as more angkots (oplets), but actually the real cause is the commuters. The internal-external and external-internal trips are quite high and external-external movement crossing Bogor city is also considerably high.
(2) Since the most chosen mode for the access mode is walking (54.12%), then demands for sidewalk facilities, (such as zebra cross, and bridge crossing on the highway or road, good pedestrian without mud, and street lights for pedestrian at night) should be provided. Overlapping network bentween main network and feeder should be corrected. Many Bogor residents who do not use public transport will choose motorcycle to reach their destination. Infrastructure for Transfer Points and Intermodal Transfer Points to facilitate motorcyclist, should be made, as well as for oplet passengers (3.83%), car users (2.98%), ojek passengers (2.28%), car passengers (0.73%), becak passengers (0.3 %). and bicyclist (0.3%).
LITERATURES
Bovy. H.L.P. 2002. Progress Report Seamless Multimodal Mobility 1997-2001. TRAIL Research School. Delft.
Buchari Erika, (2009), A multimodal public transport planning guidance for sustainable transport in developing countries, International Journal of Environment and Sustainable Development (IJESD), - Vol. 8, No.3/4 pp. 263 - 285
Krygsman. Stephen. (2004). Activity and Travel Choice(s) in Multimodal Public Transport System. PhD Dissertation. the urban and Regional research centre Utrecht (URU). Utrecht.
Nes. Van Roberts. (2002). Design of multimodal transport networks. a hierarchical Approach. PhD Dissertation-TRAIL-Thesis Series T2002/5. The Netherlands TRAIL Research School. DUP Science. Delft.
Tamin. Ofyar. Z. (2003) Perencanaan dan Pemodelan Transportasi. Penerbit ITB. Bandung.
Posted: July 14th, 2010 under multimodal public transport.
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