Applications of Integrated Transport and Gravity-Based Land Use Models for Policy Analysis

Abstract

Forecasting urban futures is of great importance to ensure the adequate provision of public and private services and to implement policies that guide demand while mitigating negative impacts. This study produces year 2030 predictions of land use and travel conditions across the Austin–Round Rock statistical metropolitan area of Texas by integrating a gravity-based land use model (modeled on Putman's Integrated Transportation–Land Use Package specification) with a standard travel demand model. The land use model cycles through job, household, and land consumption estimates across traffic analysis zones before feeding forward into a contemporaneous model of travel patterns. To understand the implications of different policies better, three scenarios were generated: a business-as-usual scenario, a congestion pricing plus carbon tax scenario, and an urban growth boundary (UGB) scenario. Results reveal how these transportation and land use policies may shape our land and travel futures, and they illuminate challenges and pitfalls of the gravity-based approach to land use (including the accompanying land consumption model). Of particular interest is that the imposition of road pricing (roughly 5¢/mi) had almost no discernable effect on land use predictions, yet resulted in the same predicted reduction in regional vehicle miles traveled as the UGB policy (roughly 15%).