Abstract

Planners require definitions of transportation accessibility that combine physical connectivity with the interlocking socio-spatial constraints that shape how potential travelers (especially lower income travelers) differentially access the benefits of the transportation system. We propose a framework that modifies physical accessibility - traditional impedance-based accessibility measures - with experienced accessibility reflective of individual constraints related to social, demographic, and economic variables. Our methodology begins with measuring key non-linear correlations between accessibility and constraints that ultimately drive a k-means cluster analysis to comprehensively group census tracts by constraint variables. We then juxtapose the clusters against empirical cumulative distribution functions (ECDFs) of their accessibility to develop an equity-driven planning framework that defines key areas for transport intervention. This approach provides greater insight into the constraints individuals face, their true ability to engage with the transportation system, and the effect that interventions would have on their access to the needs of daily life.

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