Abstract

An alternate approach for truck transportation planning at the state level is presented using a case study application in the State of Iowa. The method was based on some freight modeling concepts and available freight data sets. However, the model takes advantage of two concepts: unconstrained highway capacities and the decomposition of commodities, resulting in manageable data and modeling requirements. Identification of significant economic sectors, selection of appropriate productivity measures, estimation of truck freight volumes for each sector individually, and estimation of routing of truck traffic on major highway routes are major elements of the planning method. The case study used two industrial sectors—food and kindred products, and machinery products—which accounted for the largest portion of state employment in nonservice sectors and the largest truck traffic generated in the state. A simplistic transportation network was used to demonstrate the modeling procedure. The analysis uses county-level employment and population to estimate zonal freight tonnage. The truck share of generated freight was estimated as the total freight generated less the freight tonnage shipped by rail. A gravity model was used to distribute the truck tonnage among origin-destination pairs, using travel time as the impedance on highway links. Estimated truck flows were converted to vehicle trips on least time highway routes using typical vehicle equivalent weights.

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