Article

Predict or prophesy? Issues and trade-offs in modelling long-term transport infrastructure demand and capacity

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Abstract

Effective planning and investment for transport infrastructure systems is seen as key for economic development in both advanced and developing economies. However, planning for such strategic transport investments is fraught with difficulties, due to their high costs and public profile, long asset life, and uncertainty over future transport demand patterns and technologies. Given that only a finite quantity of funding is available for transport investment, it is important that this funding is spent in the right places and on the right schemes in order to ensure that the best return is obtained from limited public resources. There is therefore a need for a model which is capable of assessing network demand and performance in a wide range of possible futures, in order that robust decisions can be taken with regard to which schemes are given the go ahead. This paper discusses a range of issues associated with the development of a strategic national transport model for Great Britain as part of a wider interdependent infrastructure systems modelling framework (NISMOD). It considers the compromises which have to be made in order to develop a model which can examine a wide range of potential futures in a reasonable timescale, outlines how such futures can be captured in the model, and finally assesses the continued role of planners and policy-makers in determining both how the model is applied and how the future of transport systems might play out in reality. While the paper is based on a case study example from Great Britain, most of the general issues discussed are of relevance to transport and infrastructure policy making in almost any national or international context.

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... Pag. 4 Detailed agent-based models have not been used to develop adaptive plans, and more generally to study future uncertainty in transport systems. The computational cost is usually stated as one of the main challenges when using transport models for long-term planning (Blainey & Preston, 2019;Wu & Levinson, 2021). Therefore, simpler models such as system dynamics models (Legêne et al., 2020) and aggregated "four-step" models (Blainey & Preston, 2019;Milkovits et al., 2019) are typically used. ...
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