Freight Demand Modeling and Data Improvement
Keith M. Chase, Patrick Anater, Thomas Phelan, University of Washington
Abstract
Keith M. Chase, Patrick Anater, Thomas Phelan, University of Washington
Abstract
Understanding freight flows and forecasting them is critical to determining the need for future transportation capacity on the nation’s highways or other modal infrastructure. However, current freight demand forecasting models and data sources are based on methods and tools developed for passenger transportation, and are inadequate for forecasting freight movements or volumes. The overall objective of SHRP2 C-20 is to “foster fresh ideas and new approaches to designing and implementing freight demand modeling,” instead of addressing freight movement planning through short-term measures that represent improvements to the current state of practice but still contain many inherent weaknesses. This research report documents the current state of the practice for freight demand modeling and the data required for effective freight modeling, data collection, and decision-making. The information presented is derived from outreach to practitioners and decision-makers at all levels, in both the public and private sectors. The report also provides a strategic plan to advance a broad new direction for improving freight planning; promoting continuous innovation for breakthrough solutions to freight analytical and data needs; and fostering a collaborative approach for private, public, and academic stakeholders.
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Understanding freight flows and forecasting them is critical to determining the need for future transportation capacity on the nation’s highways or other modal infrastructure. However, current freight demand forecasting models and data sources are based on methods and tools developed for passenger transportation, and are inadequate for forecasting freight movements or volumes. The overall objective of SHRP2 C-20 is to “foster fresh ideas and new approaches to designing and implementing freight demand modeling,” instead of addressing freight movement planning through short-term measures that represent improvements to the current state of practice but still contain many inherent weaknesses. This research report documents the current state of the practice for freight demand modeling and the data required for effective freight modeling, data collection, and decision-making. The information presented is derived from outreach to practitioners and decision-makers at all levels, in both the public and private sectors. The report also provides a strategic plan to advance a broad new direction for improving freight planning; promoting continuous innovation for breakthrough solutions to freight analytical and data needs; and fostering a collaborative approach for private, public, and academic stakeholders.
Key concepts: Computer science