Investigating the Ability to Assess VMT Impacts of Rural Capacity-Enhancing Projects

Recent changes in California transportation policy have increased the importance of evaluating the impacts of highway capacity expansion on travel demand by shifting environmental review practices away from level-of-service toward assessing impacts on vehicle miles traveled (VMT) and travel demand. While established analytical tools exist for evaluating induced travel in urban regions, limited research and modeling resources have made it difficult to apply similar methods in rural areas. This research investigates whether capacity-enhancing projects on rural elements of the California State Highway System (SHS) are associated with measurable increases in VMT. The study evaluates county-level statistical relationships using historical data from 1990 to 2024, describing roadway supply, travel demand, and socioeconomic conditions across California counties. Regression analyses were conducted using Highway Performance Monitoring System (HPMS) data, populationestimates, employment statistics, and other supporting variables to examine relationships between VMT, SHS roadway capacity, population, and employment. Analyses included comparisons across counties, changes over 5-year, 10-year, and 20-year intervals, and separate evaluations of rural, partly rural, and urban county groupings. The findings indicate that relationships between roadway capacity and VMT in rural areas can be substantially variable and less consistent than expected. While some statistical relationships between SHS capacity and VMT were identified, the analyses did not consistently support strong or stable induced travel effects across rural counties. Population and employment changes were generally found to be important explanatory variables. However, data limitations associated with roadway supply measures and traffic estimation methods have affected analytical reliability. The results suggest caution in directly applying urban-based induced travel elasticity assumptions and tools to rural areas and point to the need for additional research with improved rural datasets to better understand the long-term impacts of rural capacity-enhancing projects.