While most current freight research has focused on the state or regional level, this paper is based on the premise that planning models are necessary on continental scale. In the United States, for example, the 1997 Commodity Flow Survey (CFS) (US Census Bureau, 1997) found that the average freight trip length for all modes is 472 miles, and that the average trip length for rail, water, air, and multimodal trips is longer than truck-only trips. The long freight trip length leads to a significant proportion of the freight traffic having an out-of-state origin/destination. The existing freight data sources cannot satisfy freight analysis requirements due to deficiencies in coverage of commodity types, transportation modes, or lack of geographic details; and it is hard to merge different sources together to a common unit or to compare different data sources across regions or categories. Furthermore, international shipments are often well documented but difficult to aggregate. This paper considers the feasibility of continental freight planning models through development of trip generation models for the continental USA using commodity flow data. Specifically, we consider the appropriate predictor variables, zonal structure and modeling methodology for such large analysis zones. Even given the differences of zone size and characteristics, the relationship between employment and freight generation was solid. A key objective of this study was to generate spatial explanatory variables for zones using GIS. Six single zone spatial variables were generated to measure highway and railway connectivity and density. The premise for this development was to attempt to produce explanatory variables relevant to transportation planning and transportation infrastructure. These variables were significantly correlated with freight generation and could be considered for nation-wide freight planning models. Satisfactory freight generation models for the large scale freight generation models in North America are possible based on the existing structure and detail of the CFS database. However, the aggregate zonal structure might be sufficient for freight generation but would be inadequate when applying flows to the network in a traffic assignment model. Therefore the next stages of this work are examining techniques to estimate the optimal zone size and layout for the long haul transportation network. For the covering abstract see ITRD E126595.
Samenvatting