Development of a Freight Database for Use in Allocating Freight Traffic to Sub-state Traffic Zones
G. Harris, N Schoening, M Anderson, J Thompson, University of Alabama, US; R Jilla, E Oranika, Alabama Department of Transportation, US
The use of national freight data at the local level is challenging due to the high level of aggregation and it is proprietary. This research presents a framework for data development and integration into transportation models.
The basis of any reasonable predictor of freight activity in an area is the availability of accurate and verifiable data. Freight planning in the United States has traditionally been performed by applying backward-looking data analysis and forward-projecting trend line forecasting. This method of data development and analysis is wholly inadequate for the economic environment of today. At best, trend line forecasting assumes that whatever has happened in the past will be replicated in the future. If the underlying principles of freight demand generation can be discovered for a particular industry an alternative to trend line analysis can be developed to accurately predict freight demand on the transportation system. Most all methods of utilizing freight data depend on applying proxy factors to allocate the freight on the system. The planning factors used in freight system analysis must be capable of describing the freight generation and attraction characteristics of the region.
It is difficult to incorporate freight information into transportation models and plans because freight data is proprietary and the release of that data is considered to be detrimental to the company?s competitive position. In the United States, many national freight databases aggregate information to the individual states, or major communities in the states. An example is the Freight Analysis Framework, Version 2 Database (FAF2), developed and distributed by the Federal Highway Administration (FHWA).
The use of national freight data at the local level is challenging due to the high level of aggregation. In most instances the disaggregation of freight data from national levels for use in local areas has been based on the factor ?employment? by prorating the employment in the local area to the to the total employment in the study region. The use of employment as a planning factor has come under scrutiny due to the inability of the factor to accurately estimate the effect of productivity improvements to increase production without increasing employment.
Under the FAF2 Commodity Origin-Destination (O-D) Database, the US is divided into 131 separate traffic zones, 17 of which are the major freight entry points into the country. The remaining 114 regions are either those defined to include one or more major Metropolitan Statistical Areas (MSA) or Consolidated Statistical Areas (CSA) or those that lie outside of these MSA?s and CSA?s. Alabama is divided into two such zones ? the Birmingham CSA and the remainder of the state. This geographical division does not give enough detail to forecast future freight movements within the state, so a way had to be found to allocate to substate freight analysis zones (FAZ?s) incoming and outgoing traffic assigned to Alabama in the FAF2 Commodity O-D Database.
This research presents the idea that local economic data from many different sources can successfully be used to allocate freight volume into smaller FAZ?s from the future freight traffic volumes provided by highly aggregated national databases such as FAF2. The output of this effort is used as input to the modeling of freight, and the integration of that freight into existing transportation planning and modeling activities at the state and local level. This has been accomplished in Alabama at the statewide and metropolitan planning organization level, resulting in validated transportation models that integrate freight into the planning activity. The methodology described in this paper can easily be replicated.
Association for European Transport