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Not all racial/ethnic groups in the US have access to the health benefits of active transportation (AT) (i.e., walking and biking). While the physical drivers of racial/ethnic inequities in AT use, such as inaccessibility to safe infrastructure, are well-established in the literature, quantitative evidence for the contextual socio-cultural drivers that influence access to AT is sparse. Our goal is to use a neighborhood peer effects framework to investigate the question, “Are people more likely to engage in AT use in neighborhoods where more people of their same race/ethnicity engage in AT use?” We approach this question by estimating multilevel logistic regression models to measure the likelihood of an individual to engage in AT (i.e., walk or bike), based on the proportion of AT commuters of their same race/ethnicity within their neighborhoods. We define neighborhoods at the Public Use Microdata Area (PUMA) level and include all PUMAs (n = 265) in the state of California. We construct a PUMA same group AT use measure, which describes the proportions of AT commuters of each race/ethnicity for each PUMA, using commuting data from the 5-Year American Community Survey (2017). We merge neighborhood-level characteristics with our individual-level sample (n = 32,510) from the US National Household Travel Survey (2017) in order to analyze the variation in peer influence on AT use among racial/ethnic groups. In both observed and adjusted models, we find a positive and significant association between individual-level AT use and PUMA same group AT rate for White, Asian, and Hispanic people. We do not find a significant association for the Black population. We find that PUMA same group AT rate has the strongest association with individual-level AT use for the White group, with Asians being the only group with an association significantly weaker than that of Whites. Our study provides key quantitative evidence of the systemic socio-cultural forces that could prevent racial/ethnic minorities from fully accessing AT systems, and broadly informs AT interventions that aim to create more equitable neighborhoods for any and all people.