Abstract:
Freight transportation is often not explicitly modeled, but is included implicitly as a percentage of non-home-based trips, which has nothing to do with the actual behavior of freight. This incorporation has the potential to develop future traffic forecasts that are unreasonable and potentially will lead to poor roadway infrastructure investment decisions. The federal freight flow data contained in the Freight Analysis Framework Version 2.2 (FAF2) Database has the potential to improve the forecast year accuracy, however, use of the database itself is often suspect and the large aggregation level of the database usually makes it impractical. This paper examines a process to systematically improve the forecasted volumes from the FAF2 using local industry sector knowledge to a potential level that is acceptable for urban transportation modeling. A case study is shown using Mobile, AL to demonstrate the process of adjusting the FAF2 data to account for industries located in the community. The paper concludes that with appropriate adjustment and application, the FAF2 database can be used for in forecasting future travel demand in a smaller urban area.
