This report reviews the existing state of the art and also the state of the practice of freight performance measurement. Most performance measures at the state level have aimed at evaluating highway or transit infrastructure performance with an emphasis on passenger transportation. Freight performance measurement ultimately requires evaluation of performance of the entire freight transportation system, which includes highways, waterways, rail, air, and modal connections. This requires considerable expansion of thinking beyond the traditional focus of state Departments of Transportation (DOTs) on highway performance. This project builds upon past and current work in the area of freight performance measurement and incorporates recent literature on the development of these measures. A thorough review of state practices is conducted by surveying state DOT web sites and reporting on the measures most frequently recommended and used by individual states for planning purposes. The emphasis is on the application of performance measures to freight transportation, and the usefulness and limitations of these measures, is discussed. Recommendations are made for potential freight performance measures for each freight mode (air, rail, trucking, and water/marine), including initial information on data availability, validity, and feasibility given existing data for Oregon. Future research needs discussed include additional data collection and development required to support performance measures, what is needed to track system performance changes over time, and testing of measures for their sensitivity and usefulness for policy and decision-making.
Freight Performance Measures: Approach Analysis
2010
135 pages
Report
Keine Angabe
Englisch
Road Transportation , Railroad Transportation , Marine & Waterway Transportation , Transportation , Public Administration & Government , Freight transportation system , Freight performance measures , State practices , Recommendations , Transit infrastructure , Highway performance , Data availability , Data collection , Decision-making
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