Guidance on Freight Modelling



Guidance on Freight Modelling

Authors

I Williams, Y Jin, J Pharoah, WSP, UK; , John Bates, John Bates Services, UK; M Shahkarami, Department for Transport, UK

Description

This present the key findings from a study to update the published UK guidance to those appraising schemes, on the methods to be used for forecasting road freight movements.

Abstract

This summarises the findings from a six month study commissioned by the UK Department for Transport (DfT). The study is to update DfT's published guidance to those appraising schemes, on the methods to be used for forecasting road freight movements. It will present the key findings from the following components of this study.

Creating forecasts of expected future road freight traffic growth for light (LGV) and heavy goods vehicles (HGV) by vehicle type. The forecasts will use outputs from DfT's National Transport Model: HGVs will be based on the GBFM model, whereas those for LGVs will be based on time series analyses. Consideration will be given to whether there now appear to be a fundamental change in the long term trends of close linkage between GDP and HGV traffic growth (decoupling) and of ever increasing lengths of haul.

Disaggregating these growth forecasts by road type and area type. It has been observed in recent years that whereas light goods vehicle traffic has grown rapidly on most types of road, the growth rate of heavy goods vehicles has differed significantly by type of road and between rigid and articulated vehicles within the same type of road. The implications of these trends for future traffic forecasts will be explored.

Review existing freight modelling approaches. This will identify their strengths and weaknesses and make recommendations on how to improve general practice in freight modelling for road scheme assessment. Issues to be examined include: time of day of travel; differential speeds by vehicle type and associated speed-flow curves, methods for updating base year vehicle matrices, etc.

Review emerging data sources. There has been an increase in the range of GIS databases of properties and of economic activity that could potentially be used to provide improvements in the zonal estimates of freight generation and attraction. The growth in the volume of data from automated traffic counts and GPS systems and the reduction in availability of roadside interview surveys may change the way in which transport demand should be measured in future.

Publisher

Association for European Transport