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Another curious RFP tender document advertised today from NZTA.
It says given the scale and scope of transport investments, it is prudent when making planning, investment, asset management and accessibility/use decisions, to quantify demands that might be placed on the land transport system.
Calling for “research that is practical and able to be applied,” the RFP is to develop a model that predicts demand for transport by mode and by region.
Modes to be covered are private vehicle travel by road, public transport by road and rail and freight movement by road and rail. Active modes, such as walking and cycling, are not to be considered.
The documentation explains that the NZTA currently operates a scanning system that anticipates changes in the macro-environment in order to identify what the implications might be for the transport demand. This is primarily a qualitative exercise.
“What is needed is a quantitative assessment to test/confirm these qualitatively derived implications for transport demand with a view to informing investment in land transport solutions.
“It is expected that the outputs of the model will inform the National Land Transport Fund Revenue Forecast Model and the Vehicle Fleet Emissions Model that is currently “run” by the Ministry of Transport.
“Model outputs will also be used to test/confirm the outputs of scenarios that are/or will be developed by both regional and local government.”
The successful researcher will:
- Provide a solid understanding of the concepts, definitions, measurements and an assessment of competing methodologies associated with estimating demand for transport by mode. When reviewing existing work, special attention should be made to competing methodologies, model specifications, data sources and empirical contexts. This will also include an investigation into whether it is feasible to disaggregate a national land transport model into separate regional models.
- Develop a set of specifications for the structural characteristics of a model based on a recommended methodology. Structural characteristics include specification of function form, model limitations and areas for further development.
- Apply the recommended methodology and model specifications to build a suitable model that predicts transport demand. Inputs to the model will include the outputs from an internal scenario development process. These outputs refer to key drivers that will shape transport demand in the future and include changes in demographics, changes in economic structure, advances in technology, sustainability of the natural environment and energy price patterns. Forecasts or predictions from the model will relate to vehicle kilometres travelled, tonnages transport and public transport patronage, among others.
- Run the model, compare outputs against historic actuals and make adjustments where necessary.
NZTA developing funding models for transport projects
Earlier in the week AKT reported other RFP tenders advertised by NZTA which gave an insight into the agency’s continuing desire to come up with new models of ways to justify funding for public transport – and say that “there will be major changes in the way public transport services are appraised in future funding decisions.”
One called for the development of “the new outcomes based funding framework for public transport services, which is under development.”
2 Comments
What on earth are our government agencies for, if they can’t do this work? Weird. Looks like the govt wants an “independent report” that justifies their conclusions.
Me, I don’t trust models. Any that have variables based on human behaviour are extremely assumption dependent. Far better to do comparative studies and see what actually happens in real situations.
Not hard to be suspicious of any moves by these organisations, that they make highly suspect projections is obvious enough, but the fact that they do no post use analysis to check their methodology is totally damning.
They always under predict PT use while making unsupportable claims for roading projects, especially ignoring externalities and over promising congestion outcomes.