Fusing Freight Analysis Framework and Transearch Data: Econometric Data Fusion Approach with Application to Florida

Abstract

A major hurdle in freight demand modeling has always been the lack of adequate data on freight movements for different industry sectors for planning applications. Both Freight Analysis Framework (FAF) and Transearch (TS) databases contain annualized commodity flow data. However, the representations of commodity flows in the two databases are inherently different. FAF flows represent estimated transportation network flows, whereas TS flows represent production–consumption commodity flows. This study aims to develop a fused database from FAF and TS to determine transportation network flows at a fine spatial resolution (county level) while accommodating production and consumption behavioral trends (provided by TS). To this end, a joint econometric model framework embedded within a network flow approach and grounded in a maximum-likelihood technique is formulated to estimate county-level commodity flows. The algorithm is implemented for the commodity flow information from 2012 FAF data and 2011 TS databases to generate transportation network flows for 67 counties in Florida. The proposed approach may be able to circumvent the need to purchase expensive TS databases in the future.