FiLM - a Model of Freight and LGV Movements in London
G Deane, I Williams, Y Zhu, J Pharoah, D Kabeizi, WSP, UK; B Khan, Transport for London, UK
WSP have developed for Transport for London a multi-modal freight model.
An innovative feature is its representation of all movements in light goods vehicles (LGVs):
1) Commuter travel
2) Service related trips
3) Goods collection & delivery
WSP?s Policy & Research Unit in Cambridge, UK have developed for Transport for London (TfL) a multi-modal freight model focussed on London. It forecasts future freight traffic in London to inform TfL?s transport planning decisions up to 2031.
The model outputs are freight flows and tonnages by origin and destination, commodity type, logistic stage and transport mode. The model has: 700 zones (400 within the M25 motorway); 6 road freight vehicle types in addition to rail and shipping; and uses 16 commodities split into 3 distribution stages. It uses a spatial input-output model to determine the pattern of demand for freight travel based on the economic structure of the regions of the UK. It includes the stages of freight generation, distribution, mode choice and assignment to detailed road and rail networks.
The model will be used to examine policy measures that impact within London on freight and logistics services. Its output matrices will also be used as an input to TfL?s multi-modal model: LTS. This model replaces the current simpler freight forecasting tool used by TfL which was developed by WSP in 2008.
An innovative feature of this model is its representation of all movements in light goods vehicles (LGVs). LGV traffic has been the major source of growth in traffic (+33%) in Great Britain over the last decade, contrasting with +5% in cars, -7% in HGVs. Within London, LGV traffic has continued to grow, whereas car and HGV traffic have declined in recent years, despite its rapid growth in population and jobs. The three main components of LGV movements are forecast separately within the model:
1) Commuter travel (37% of trips in company owned vans in Great Britain)
2) Service related trips (27% of trips)
3) Goods collection and delivery (32% of trips)
Trips for personal purposes within LGVs mainly occur outside working hours and are limited in number and so are of less relevance.
The pattern of freight movements within a major conurbation such as London is rather different to the national traffic pattern and so it introduces special modelling requirements. London has a large dynamic service sector and much of the employment within the manufacturing sector is engaged in administrative rather than production of goods activities. We have made innovative use of a variety of data sources to provide the foundations to determine the pattern of production and of consumption of goods within London.
The model explicitly distinguishes primary, secondary and tertiary distribution stages for a wide range of individual commodities. For tertiary distribution it represents the multi-drop pattern of collection and delivery that is carried out mainly in LGVs and smaller HGVs. These are quite different in their trip lengths, vehicle types and time of day patterns to the long haul primary movements to distribution centres in and around London that are carried by rail, water or large fully loaded artics.
Association for European Transport