Incorporating Job Competition and Matching to an Indicator-Based Transportation Equity Analysis for Auto and Transit in Dallas-Fort Worth Area

Abstract

Transportation equity is a vital but vague issue for planners and engineers in the United States, where mobility-based transportation planning has triggered the disproportionate distribution of benefits and burdens in the transportation system. Previously, transportation equity studies have evaluated equity using different transportation service metrics and socio-demographic factors. Job accessibility is one principal metric for transportation quality as it directly relates to a community’s economic prosperity. While most equity studies analyze aggregate accessibility for a single mode, our study measures blue-collar and white-collar job accessibilities for automobile and transit by incorporating job proximity, competition, and matching, using the Dallas-Fort Worth area as a case study. Using Lorenz curve, Gini coefficient, and Atkinson measure, we performed horizontal and vertical equity (within and between groups) studies and compared various population groups by disaggregating the population based on the two most cited environmental justice indicators, namely, income and race. Our findings suggest that (a) job accessibility by transit mode has higher inequalities compared with automobile, (b) white-collar and blue-collar jobs have similar inequality levels, (c) low- and high-income populations experience somewhat the same inequality levels, and (d) inequality is highest among African American communities, (e) blue-collar job accessibility has higher inequality for Hispanic and Asian communities for both transportation modes and (f) the disparities in job accessibility are greater between racial groups than income groups in the Dallas-Fort Worth area. To address such disparities, planners must enhance transit availability through subsidizing transit costs and transit feeder services like on-demand shared services.