Estimating Truck Trips with Product Specific Data: A Disruption Case Study in Washington potatoes

Currently, knowledge of actual freight flows in the US is insufficient at a level of geographic resolution that permits corridor-level freight transportation analysis and planning. Commodity specific origins, destinations, and routes are typically estimated from four-step models or commodity flow models. At a sub-regional level, both of these families of models are built on important assumptions driven by the limited availability of data. This study was motivated by a desire to determine whether efforts to gather corridor-level freight movement data will bring significant new insights over current approaches to freight transportation modeling. Through a case study of Washington State’s potato and value added potato products industry, we show that significant insight can be gained by collecting commodity-specific truck trip generation and destination data: the approach allows product specific truck trips to be estimated for each roadway link. When considering a network change, the number of affected trips can be identified, and their re-route distance quantified.