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DfT’s scenario-based forecasts pose challenges for modellers

Tom van Vuren, Divisional director, Mott MacDonald, Birmingham and Visiting professor, Institute for Transport Studies, the University of Leeds
02 April 2015
 

The Department for Transport ought to be congratulated for developing scenario forecasts for road traffic (‘DfT embraces scenario-based road traffic forecasts for uncertain world’ LTT 20 Mar). 

Strong opinions have been voiced about the lack of credibility of the previous forecast growth figures and the DfT has responded, sticking to well-founded economic relationships but acknowledging uncertainty. Some of us will remember the low and high National Road Traffic Forecasts of the early 1990s – scenarios of some kind. But the new forecasts are different – they are based on transparent, explicit reflections of the uncertainty in the main drivers of demand (oil prices and economic growth), and around the future development of recently observed changes in car ownership and usage, all else being equal.

This last caveat is important. All else is unlikely to be equal and there is as much uncertainty in other aspects of society and the transport system that will also affect future demand. This requires even more scenarios to be developed that reflect uncertainties such as technological change – emerging modes, their speed of introduction and their impact on the urban mobility offering. Think shared mobility or autonomous vehicles. We also need scenarios to reflect possible behavioural change, with a future population possibly valuing mobility quite differently from what can be observed today – challenging the underlying modelling concept of rational decision-making and utility maximisation. Scenarios reflecting these uncertainties will require a) fundamental research and b) potentially new modelling paradigms.

The 36% difference in 2040 vehicle miles between the highest and lowest DfT scenarios is also not a reduction in overall miles travelled: some of this difference will need to be absorbed by other modes (for example, because of higher fuel prices or lower car ownership). Accepting the range of potential future growth in the demand for car travel implies accepting a range of potential future growth in other modes, too! Modelling will be required to determine what that spread may look like. 

And decision-makers? They will now be presented with a range of impacts of a policy or a project: in terms of benefit:cost ratio, in terms of modal shares, in terms of economic and environmental impacts. An unanswered question is how they can use the increase in information to make better decisions. Will they still ask us as transport planners to give them that one, most likely outcome, however determined? Perhaps...  As American president Lyndon B Johnson is reputed to have once said: “Ranges are for cattle, give me a number!” But at least that will enable the debate to pay more attention to the assumptions that underlie the modelled outcomes. Discussion and if possible agreement of those may be more beneficial than more sophisticated modelling techniques.

 

 
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