Alternative Approaches to Modeling the Travel-Demand Impacts of Smart Growth

Abstract

Four-step travel demand forecasting models were never meant to estimate the travel impacts of neighborhood-level smart growth initiatives like transit villages, but rather to guide regional highway and transit investments. While progress has been made in enhancing large-scale models, some analysts have turned to post-processing and direct models to reduce modeling time and cost, and to better capture the travel impacts of neighborhood-scale land use strategies. This paper presents examples of direct or off-line modeling of rail and transit-oriented land use proposals for greater Charlotte, the San Francisco Bay Area exurbs, and south St. Louis County. These alternative approaches provided a useful platform for scenario testing, and their results revealed that concentrating development near rail stations produced an appreciable ridership bonus. These alternative models are appropriate as sketch-planning supplements to, not substitutes for, traditional four-step models.