Ohio’s unique geographic position makes it an important intermodal freight transportation and distribution location. ODOT and its partnering planning agencies such as the Mid-Ohio Regional Planning Agency (MORPC) have a history of freight planning designed to leverage and enhance this position. The recent completion of the Ohio Statewide Travel Demand Model (OSTDM) has allowed it use in these efforts and has led to improvements in the model revealed by these early applications.

The OSTDM long-distance freight component accepts dollar flows of activity from its higher level econometric and land-use models and then processes them using relationships derived from the commodity flow survey and other federal data sets. It contains an explicit network representation of freight rail and intermodal centers by treating them analogous to transit networks. Recently it was applied for the update to the MORPC freight plan. Despite the advanced commodity based approach and availability of rich data sets from the model, the application pointed out several challenges and shortcomings. The first of these was inconsistency between the model results and more recent freight trends available in FAF3. Given that the model was developed from pre-recession data sets, this was no surprise. Another major limitation was the fact that intermodal (i.e. freight using both truck and rail) freight was not being assigned to the highway networks. These and other challenges were overcome in the MORPC study with typical model techniques such as trip table factoring. However, for the following Ohio Statewide Freight Planning Study and subsequent efforts, modifications to the freight model were implemented to overcome these limitations.

First, the model is being more explicitly linked to (FAF3). A method has been developed to disaggregate freight flows from FAF zones to a finer zone level using employment data and input/output coefficients from the econometric models. This enhancement will ensure the model can easily be made compatible with the latest freight flow data. It is being enacted in concert with updates to the econometric models so that changes in economic conditions from the higher level models result in incremental changes from the known base freight flows. In addition, various enhancements to the intermodal freight representation including assigning the truck portion of intermodal trips to the highway networks are being made. Lastly, more explicit modeling of empty-trucks was added which balances the number of trucks entering and leaving every zone and matches empty-truck statistics.