Abstract

The U.S. population is expected to increase to 389 million by 2045 compared to 321 million in 2015, with economic growth doubling in size. Consequently, freight movements are expected to increase by approximately 42 percent by 2040. Among all freight modes, trucks show the largest expected increase in flows by 2040. However, the ability for transportation agencies to understand and adequately plan for increased truck movement and related impacts is extremely limited due to a lack of data on truck travel patterns.The main sources of truck data are truck surveys and truck counts collected by infrastructure-based detectors. Surveys provide detailed information (i.e., truck type, Origin-Destination, weight, and vehicle miles traveled) useful for understanding truck activity pattern by industry or associating freight commodities with specific truck types, but because of low response rates, surveys cannot be utilized to provide the actual quantification of truck activity at the geographical level. In-pavement sensor technologies, such as Weigh-in-Motion (WIM) or Automated Vehicle Classifiers (AVCs), provide point observations, such as truck volumes. These existing data sources are used to model and generate truck path flows (i.e., travel routes) and/or travel time estimations.