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Current transit suffers from an evident inequity: the level of service oftransit in suburbs is much less satisfying than in city centers. As aconsequence, private cars are still the dominant transportation mode forsuburban people, which results in congestion and pollution. To achievesustainability goals and reduce car-dependency, transit should be (re)designedaround equity. To this aim, it is necessary to (i) quantify the "level ofequity" of the transit system and (ii) provide an indicator that scores thetransit lines that contribute the most to keep transit equitable. Thisindicator could suggest on which lines the transit operator must invest toincrease the service level (frequency or coverage) in order to reduce inequityin the system.  To the best of our knowledge, this paper is the first to tackle (ii). To thisaim, we propose efficient scoring methods that rely solely on open data, whichallows us to perform the analysis on multiple cities (7 in this paper). Ourmethod can be used to guide large-scale iterative optimization algorithms toimprove accessibility equity.

Equity Scores for Public Transit Lines from Open-Data and Accessibility Measures