Estimating freight flows for metropolitan area highway networks using secondary data sources

We present a method for estimating intra-metropolitan freight flows on a highway network. The work is part of a larger project aimed at developing an automated, integrated system for freight flow analysis and planning. To overcome the limitations of current estimation methods for commodity flows, we use reliable secondary sources, including small-area employment data, and derive estimates in a plausible way by means of a computational workflow. When available, we extract the data automatically from online sources, so that estimations can be continuously updated. Using widely available data sources allows for transferability. In this paper we provide an overview of our modeling approach and the major data sources used. We apply the model using data from the Los Angeles region, and compare our traffic assignment results with available screenline counts. Results are encouraging. Our approach should be easily applied to other metropolitan areas, allowing planners and policymakers to make more informed decisions by utilizing the most recent data from many sources and enhancing the ability to explore different scenarios.