Benefits of modelling freight transport


Policymakers need to forecast freight for the uncertain future to:
• Allow policymakers to plan for the future
• Provide evidence to support business cases for, and appraisal of, interventions
• Reduce risk by considering the potential impact of future scenarios.

The Great Britain Freight Model (GBFM) is the UK’s state-of the art freight transport model.

The Great Britain Freight Model (GB Freight Model) is a comprehensive freight transport demand simulation model that has been developed continuously by MDS Transmodal over the last 20 years to become the UK’s state of the art freight transport model. The GB Freight Model comprises the following components:
• Multi-dimensional base O-D matrix with 7,000 O-D Zones
• Freight transport cost models, validated against industry data
• Mode-choice assignment tool, to assign future O-D flows to road or rail modes
• Road assignment tool, assigning HGVs to the national highway network
• Rail assignment model, based upon current operating behaviour.

Existing freight transport flows between the 7,000 O-D zones are calibrated against current freight industry costs, thereby explaining choice of mode and by port for international flows.

The GB Freight Model allows traffic flow forecasts to be developed for a future year and scenarios to be ‘tested’ to examine their potential impacts. These scenarios can reflect the impact of changes to freight transport costs (such as driver wage increases) or new infrastructure, or policy interventions (such as road charging) or new freight services.

The starting point for producing freight forecasts using the GB Freight Model is establishing a detailed baseline position which explains current freight flows by mode, origin-destination and commodity, calibrated to freight transport costs, so that the costs employed by the model reflect market rates.

Forecasting freight flows is then undertaken using the GB Freight Model by:
• Developing an understanding of demand drivers for freight in the area
• Horizon-scanning for future changes in demand drivers
• Developing forecasts of total freight demand to the horizon year
• Defining the scenarios
• Translating changes in demand drivers into quantified changes in freight transport costs for each scenario
• Changing input parameters for scenarios and running the model to obtain outputs
• Analysing outputs, comparing scenarios with the baseline.