United States Department of Transportation
i
Vertical Equity Statewide Pilot, Data Inventory, and Guidelines for Performance Based Planning (VESPI)
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2018-01-06
[PDF-3.76 MB]
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Abstract:In this project with tile “Vertical Equity Statewide Pilot, Data Inventory, and Guidelines for Performance Based Planning” (dubbed VESPI) the authors develop a method for vertical equity analysis. Vertical equity is the analysis of disadvantages groups of different incomes and other sociodemographic characteristics experience from the land use-transportation system. They first create a data inventory for the indicators needed to satisfy performance based planning in California. In parallel, using detailed in space and time databases in the GeoTrans laboratory they create a first pilot geo-computation of equity indicators covering the entire State at fine spatial detail. They compare data available and this pilot to the literature on gentrification, equity analysis, and access to opportunities. The authors also review the latest travel behavior advances to identify research gaps in this research. This is done through informal discussion with experts, a presentation at an international travel behavior conference (in Santa Barbara, July 2018) together with research gap identification from workshops in the same conference (IATBR2018.org). Input from the different expert sources is then used to finalize the geo-computation of equity. The project ends with findings and next steps. In terms of substantive policy findings, they show that timing of activity participation and travel times to work are very different among jobs of different industries and these are heavily influenced by the type of centers surrounding them. This in turn shows they need to introduce a fine grade definition of jobs and their distribution in space to gain insights about the impact of policies that are at the intersection of land use and transportation. For example, employer-based demand management strategies (e.g., staggered work hours, telecommuting) will have different impacts on different job types depending on the opportunities offered around home and job sites. This in turn also implies the mix of job types at a location will determine the impact of these policies in space. Recording the number and type of jobs in different locations will then allow them to assess the impact of policies with higher precision and accuracy
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