Annex 4 Modelling Approach in CMP Process

Estimation of Transport Demand for the Target Year

Step 1: Trip Generation/Attraction: A function that estimates future person-trip generation and attraction should be prepared through a regression analysis from the number of base-year person-trips and explanatory variables, such as population, number of employees and number of non-employees. The function should be estimated by trip purpose.

Next, future trip generation/attraction in each zone are estimated through the function described above, using socio-economic data such as forecast population and employment, which are to be clarified for the future land use scenario described in the previous section.

Required data and outputs are as follows:

  • Required Data
    • Socio-economic data for each zone
    • Trip generation/attraction function
  • Output
    • Number of trip generations/attractions in each zone

Step 2: Trip Distribution: The number of trips between zonal pairs is estimated from the volume of trip generation/attraction in each zone. Among several methods of estimating trip distribution, the gravity method is most widely used. Required data and output are as shown below.

  • Required Data
    • Number of trip generations/attractions in each zone
    • Trip distribution function
    • Distance matrices between each two zones
  • Output
    • Person-trip O-D matrices for target year

Step 3: Modal Split: Using the modal split scenario and the average number of passengers carried by each vehicle type, the O-D matrix for each vehicle type is estimated from the person-trip O-D.

Required data and output are as follows:

  • Required Data
    • Modal split
    • Trip distribution function
    • Distance matrices between each two zones
  • Output
    • Person-trip O-D matrices for target year

Box 1 summarizes the modal split models.

Box 1 Modal Split Models

There are two major types of model to calculate the modal split rate: aggregate and disaggregate:

  • Aggregate Model: An aggregate model uses aggregated data, such as modal choice rate by trip distance based on the O-D survey. An aggregate model can be developed relatively easily, but is not suitable for evaluating specific public transport projects, such as MRT projects, since it does not forecast modal shift from private vehicles to public transport. The future modal share can be provided from policy targets, although there is no certainty that it will be achieved.
  • Disaggregate Model: The disaggregate model is based on individual preferences in modal choice. The disaggregate model requires additional data and specialized knowledge to develop and use the model. In particular, it is relatively complicated to develop a model for more than two modes. The advantage of a disaggregate model is that it can assess both modal shift from private vehicles to public transport and the benefits of a public transport project, such as an MRT.

An aggregate model is recommended for the CMP. However, a disaggregate model for a limited corridor should be developed for the Detailed Project Report of a major public transport project, such as an MRT project.

Step 4 Assignment: Using the same methodology as applied in the base-year model, the traffic volume on each road section should be calculated. Future vehicle-trips, person-trip ODs, and the road network will be required as input data.

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