This paper describes a transport modelling framework which is being produced as part of the UK Infrastructure Transitions Research Consortium (ITRC). The aims of this consortium are to deliver research, models and decision support tools to enable analysis and planning of a robust national infrastructure system. ITRC research is structured around four major challenges: 1) How can infrastructure capacity and demand be balanced in an uncertain future; 2) what are the risks of infrastructure failure and how can we adapt national infrastructure to make it more resilient; 3) how do infrastructure systems evolve and interact with society and the economy; and 4) what should the UK strategy be for integrated provision of national infrastructure in the long term. A number of interdependencies exist between infrastructure systems, and ITRC aims to explicitly account for these interdependencies by developing an integrated framework of geographically explicit national-scale models of energy, transport, water, waste water and solid waste systems. The models will then be used to evaluate the impacts of a range of scenarios and strategies on the infrastructure systems in the period up to 2100.
The modelling framework will be based on Capacity-Demand Assessment Models (CDAMs) for each of the infrastructure systems, and this paper gives details of the Transport CDAM and presents some preliminary results. Initial work involved a review of relevant data sources and existing models and the development of a national level Fast Track Analysis. Subsequent work has involved the development of a more detailed CDAM that builds on existing UK modelling capabilities, explicitly considers interactions within and between passenger and freight transport and with other economic sectors, and considers a much longer time period than most other long-term models. The model forecasts transport demand and capacity within and between 142 zones based on local authorities, covering the whole of Great Britain. A ‘base year’ representation of the transport infrastructure system was produced, along with current usage levels for this system. The infrastructure system modelled comprises link-based trunk road and rail networks, along with nodes representing all major airports and major seaports. Although vehicles are not normally considered to form a part of ‘infrastructure’ they are nevertheless an important consideration in this study, in particular in terms of vehicle technology and alternative fuels. GIS-based methods are used to integrate the model infrastructure network with usage data, which for the model ‘base case’ came from a range of sources, including for example ‘Average Annual Daily Flow’ traffic counts, rail ticket sales, and Department for Transport bus statistics. Taken together, this provided base data for the model outputs, which include road passenger and freight vehicle km, rail passenger numbers and freight traffic volumes, within-zone bus passenger numbers, airport passenger numbers, freight tonnage handled at ports, infrastructure capacity utilisation levels, and transport energy consumption and emissions.
The CDAM can then be used to forecast future levels of these outputs based on a number of variables, including infrastructure capacity changes (both at a national average level or describing specific interventions), GDP, population, employment, energy prices, fuel mix, fuel efficiency, public transport fares, taxation levels, speed limits (and other legal interventions), and inputs from other ITRC sector models. These variables are adjusted to represent particular scenarios, such as the construction of new high speed rail lines, or a large and sustained increase in oil prices. It thus provides a virtual environment in which to test strategies for long term investment, and can help understand how these strategies perform with respect to policy constraints such as reliability and security of supply, cost, carbon emissions and adaptability to demographic and climate change. Overall, the ITRC project will inform analysis, planning and design of national infrastructure, through the development and demonstration of new decision support tools in partnership with government and industry.