Transportation agencies often evaluate regional transportation network performance by measuring impacts on residents, such as automobile fatalities or ime spent in congested conditions. Few, however, evaluate the system based on social equity. Standardized, quantitative equity metrics will help planners and policymakers assess the ability of all residents to move throughout metropolitan regions safely, conveniently and within a reasonable amount of time. One dataset for constructing such equity metrics is the American Community Survey (ACS), which collects journey-to-work data including reported commute times. Commute times are a complex indicator, as they vary based on the spatial distribution and relative proximity of different types of residences and employment destinations as well as the transportation system’s options for connecting workers to jobs. Although strong scholarship exists that looks at commuting patterns by race and gender, racially-based differentials in travel time have not been addressed in the transportation research literature in recent years. To fill this gap, this paper introduces methods for the calculation of commute time differentials by race, travel mode and skill level using ACS data, designed to be replicable and comparable between regions. Applying these methods to a test region consisting of 153 communities around Boston, we present data detailing the extent and pattern of raciallybased commute time disparities, including descriptive statistics and results of OLS regression tests. We hope that the identification of significant racially-based commute time differentials and the inequity of the resulting travel time penalty will contribute to a larger conversation around transportation equity.
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