CHAPTER 3 PROJECT OUTLINES
3.3 REVIEW OF TRAFFIC DEMAND FORECAST
3.3.1 REVIEW OF EXISTING TRAFFIC DEMAND FORECAST (1) Methodology Overview
Figure 3.2.5 Typical Cross Section (Ramp Section)
The validity of the calibrated O-D matrix depends upon the availability of data sources. In order to support the process, traffic surveys were conducted, including Traffic Count (TC) and Road Side Interview (RSI) surveys, which covered most of the study area.
Demand forecasting were developed based on socio-economic development scenarios where forecasted socio-economic parameters such as population, GRDP, employment, etc. are important factors influencing the estimated number of trips in the future. In order to control the growth of future travel demand more realistic, a future trend of the number of registered vehicles was also forecast as the control growth factors.
Finally, the traffic assignment model forecast the daily traffic volume on the road network, in which further analysis of highway network performance resulted in the need for highway improvement, especially for the Bandung Metropolitan Area Network. This future traffic assignment involved road network development plans.
Figure 3.3.1 Methodology for Forecasting Future Traffic Demand Review Previous Studies and Secondary Data Sources
Traffic and O-D Movement Characteristics
Traffic Surveys:
RSI, TC, Speed Model Development and Calibration
For Base Year O-D Matrices (2009) Feasibility and Environmental Impact Assesment (AMDAL) Studies (2006),
Bandung O-D 2002, etc
Highway Network and Transport Conditions Socio-Economic Data:
GDP, Economic Growth Population, etc
Calibrated Base Year OD
Road Network Model Node and Link based on
IRMS/URMS , Function, Class etc.
Future Transport Scenarios Transport Policy Framework
Highway Network Other Transport Modes Forecast Future Parameters
GRDP, Population, Economic Growth, Land-use and Structure Plan
etc.
Travel Demand Forecast Production-Attraction
O-D Movement Modal Split
Future Highway Network
Traffic Assignment Forecast Traffic Flow on
Highway Network Toll Road Network
Performance
(2) Future Socio Economic Framework 1) Model Parameters
Travel demand forecasting follows the rule that travel demand is derived mainly from social and economic activities in a specific area. With this assumption, zonal parameters were considered as variables influencing the number of trip generation. The trip generation model was developed based on regression models that involve a set of zonal parameters. The selected zonal parameters were mainly socio-economic parameters such as population, population density, GRDP, per capita GRDP, etc. BPS is the main reliable data source for these parameters. For the purpose of demand forecasting, these parameters were aggregated to the traffic zoning system.
The main constraint in forecasting the socio-economic parameters was the emergence of new districts wherein Official Guidelines /Master Plan /Spatial Development Plan are not yet available. Therefore, these new districts were considered to remain as part of their former districts, where most data are available. Moreover, the parameter forecast for these districts were mainly based on trend analysis.
2) Future Socio-Economic Framework
The first step in forecasting model parameters is to establish an appropriate future socio-economic scenario. The main concern on the economic scenario is the future economic growth. In 1997, Indonesia faced an economic crisis. In 2008-2009, again Indonesia is affected by the global economic crisis. Some manufacturing industries closed, such as textile segments and secondary products. It is assumed that Indonesia will recover in 2010.
a. National GDP and economic growth
The average GDP growth (at 2000 constant prices) during 2005 to 2007 is about 6.2% p.a.
while per capita GDP growth is at 4.2% p.a. The real GDP and per capita income growth in 2005 slowed down to 5.5% and 5.0%, respectively. The 2009 financial crisis resulted in a full blown recession in 2008 with GDP (with oil and gas) contracting by -18.5% (GDP without oil and gas by -19.3%) and real per capita income contracting by -14.5%.
Under the current socio-economic condition and in the light of recent political events, current financial crisis and recent terrorists attack in the US, as the impact of the global economy, the economy of Indonesia might slow down its recovery during the next few years same as other countries in the world.
The current issues of the national economy are high debt, high inflation and limited budget for development, whilst the global economy is likely under recession. Under these uncertain conditions, it is assumed that the period of 2009-2011 is the economic recovery period with economic growth not to exceed 5%. It is also assumed that in this context, alternative predictions of economic growth are made towards the target year of 2028 as well as other socio-economic frameworks such as population and employment population.
b. Economic Development Scheme
In order to predict the macro-economic framework over the planned time horizon, GDP was selected as the essential economic indicator for the Study. The projection process was made from the regional down to the local levels. The regional GDP without oil/gas was first predicted and then, the GRDP for West Java province as a whole, considering the local growth potential, comparative advantages, and constraints in the whole context of the national settings. Afterwards, the GRDP for the West Java province (without oil/gas) was broken down into the related district/municipality levels.
As for the economic forecast, there exist very few long-run projections because of high uncertainty in the international and domestic economies. The government of Indonesia has no long term development plan for economic development yet and it is still under process and unavailable so far.
c. Forecasted GRDP by Zone in Study Area Zoning System
The GRDP by Sub-District was projected using the 2005 database. The average forecasted growth rate of GRDP in Bandung and Cimahi Municipalities are in the range of 4.5-5.9% per annum in the period of 2009-2015, while the average projected growth rate of GRDP in Bandung and Sumedang districts are in the range of 5.6% per annum.
Table 3.3.1 GRDP/Capita in Bandung Metropolitan Area
(Unit : Rupiah/month) No. District / Municipality 2009 2015 2020 2025 2028
1 Bandung City 21,331,789 28,601,159 38,375,577 51,528,328 69,240,764 2 Cimahi City 9,594,134 11,967,482 14,927,937 18,620,735 23,227,037 3 Bandung District 6,779,827 8,903,218 11,691,640 15,353,375 20,161,939 4 West Bandung District 6,779,827 8,903,218 11,691,640 15,353,375 20,161,939 5 Sumedang District 9,534,287 12,520,355 16,441,637 21,591,036 28,353,189 Source: JICA Survey Team
Table 3.3.2 shows past trend of the Gross Domestic Product in Bandung Metropolitan Area at current price.
Tabel 3.3.2 Gross Domestic Product in Bandung Metropolitan Area at Current Price
(Unit : Million Rupiah) Regency/Cities 2002 2003 2004 2005 2006 2007 Bandung City 20,690,502.0 23,420,126.0 27,422,419.0 34,792,185.0 43,491,380.0 52,066,112.0 Bandung District 21,301,942.7 23,833,127.4 27,069,312.6 32,161,720.7 40,147,744.9 n.a Cimahi City 4,648,150.5 5,182,892.8 7,132,099.9 7,227,777.5 8,399,784.4 9,356,230.5 Sumedang District 4,863,811.4 5,338,800.0 5,943,300.0 7,048,210.0 8,066,640.0 9,034,570.0
Source: Bandung in Figures 2008, BAPPEDA Bandung City (3) Population Forecast
Initially, the provincial population was projected as the basis of the entire population framework in the planning period of the Study. The projection on SUPAS 2005 made by the consultants and BPS were reviewed because there was a discrepancy between the 2000 population projection and 2000 population census data. Population figures given in 2000 Population Census were set as the base population for future projection.
Projection process was made from the provincial down to district/municipality levels based on the trend of growth rates in the past census during 2000 to 2005 taking into account local share of population, regional development policy specified in the national and provincial development plans, and the regional advantages and constraints. The population projected by district/municipality was used as control totals for projection of the related study area. Further, the projected provincial population was used as the control total of the relevant Kabupatens/Kotamadyas population projection.
Table 3.3.3 Forecast Number of Population 2015 – 2028
(Unit : In thousands) No. District /
Municipality
Population Growth
(%)
2009 2015 2020 2025 2028
1 Bandung City 1.4% 2,691 2,932 3,149 3,383 3,634
2 Cimahi City 2.7% 580 680 776 886 1,011
3 Bandung District 2.1% 3,314 3,745 4,147 4,593 5,086
4 West Bandung District 2.1% 2,231 2,521 2,792 3,092 3,424
5 Sumedang District 2.0% 229 258 285 314 347
Total 9,045 10,137 11,150 12,267 13,501
Source: Statistic Regional Office, 2008
3.3.2 STUDY ON THE GENERATED TRAFFIC DEMAND BY NEW DEVELOPMENT