A11.9 - Applying variable trip matrix techniques
- A11.1 - Congested networks and induced traffic
- A11.2 - Applying growth constraint techniques
- A11.3 - Applying peak spreading
- A11.4 - Applying the matrix scaling method
- A11.5 - Applying the incremental matrix capping method
- A11.6 - Applying the shadow network method
- A11.7 - Applying elasticity methods (FTM)
- A11.8 - Applying demand models (FTM)
- A11.9 - Applying variable trip matrix techniques
- A11.10 - Applying elasticity methods (VTM)
- A11.11 - Applying project demand models (VTM)
- A11.12 - Conducting cost benefit analyses using variable matrix
- A11.13 - Checking growth constraint or variable matrix methods
A11.9 - Applying variable trip matrix techniques
When to use
Variable trip matrix (VTM) techniques should be used to model the effects of induced traffic where high levels of congestion are expected in both or either the do minimum or project option networks. Variable matrix methods differ from conventional fixed trip matrix techniques in that demand in the project option matrix is generally higher than that in the do minimum matrix for a given forecast year. VTM methods also require more complex procedures to evaluate net project benefits than fixed matrix methods.
VTM methods may not be necessary if induced traffic is expected to have similar effects on the economic performance of each project option being compared. If this exceptional case is considered to apply, advice should be sought from Land Transport NZ or Transit NZ as to whether VTM methods should be used.
General guidance
The purpose of variable matrix methods is to provide estimates of the effects of a project on travel patterns (that is, the difference between the do minimum and project option matrices) and on the benefits of the scheme. Because these effects may be small and the estimates should be unbiased, methods relying heavily on professional judgement (such as many of the growth constraint techniques) are inappropriate. Two variable matrix methods based on analytical techniques are recommended: elasticity methods and demand models.
The options are:
- using these methods consistently for both the do minimum and project option matrices or
- using growth constraint methods to establish the do minimum matrix and variable matrix methods for estimating the effect of the project option on the trip matrix (as an adjustment to the do minimum).
For demand modelling approaches, where the source of data is a strategic city model, it may be considered unlikely that the strategic model will have sufficient sensitivity to measure the impact on the trip matrix of a single scheme, and the use of such models will therefore generally not be feasible. Elasticity methods are therefore likely to be needed to supplement the strategic model.
For project demand models, it is likely that these would generally be applied consistently for the do minimum and project option matrices.
Whatever method is applied, its results should be verified by comparison with an FTM evaluation based on the do minimum trip matrix.
Procedure
Having decided that congestion will be significant in both the do minimum and project option for a forecast year, follow the steps below to apply variable matrix methods.
| Step | Action | ||
|---|---|---|---|
| 1 | Select an appropriate method to adjust the do minimum and project option matrices: | ||
| Method | Description | Go to | |
| A | Use elasticity methods for both the do minimum and project option matrices. | Appendix A11.10 | |
| B | Use other growth constraint techniques (appendix A11.2) for the do minimum matrix and elasticity techniques to estimate the effects of the project option on the trip matrix. | Appendix A11.10 | |
| C | Use the project demand model for both the do minimum and project option matrices. | Appendix A11.11 | |
| Alternatively, use a fixed matrix approach, then apply a predetermined correction factor to adjust benefits for variable matrix effects. Note that project benefits will need to be calculated using a consumer surplus evaluation and reported in worksheet 3. |
|||
| 2 | Conduct a fixed matrix analysis (see appendix A11.2) and compare the results with those obtained from the variable matrix analysis. | ||
