To comply with AB 32 and SB 375, California local and regional governments are working to reduce vehicle miles traveled (VMT). To develop targeted policies with scarce resources, policymakers need guidance as to which policies will be most effective in their jurisdictions. This research uses empirical analysis of travel survey data to quantify how much Californians will change the amount that they drive in response to changes in land use and transport system variables. The study improves upon past research in three key ways. First, the researchers assembled and used a dataset that consists of merged information from five California-based household travel surveys that were conducted between 2000 and 2009. Second, they developed and employed a novel approach to control for residential self-selection, categorizing neighborhoods into land use types and using these as the alternatives in a predictive model of neighborhood type choice. Third, the team focused on understanding heterogeneity in effects of variables on VMT across two important dimensions – neighborhood land use type and trip type. They found considerable differences in the VMT effect of policy-sensitive variables across land use types, and found some variation across trip types. Results of this research will be embedded in the VMT Impact spreadsheet tool, which allows users to easily see the implications of this work for any census tract, city, or region in California.