Transport and urban decision-making are often guided by aggregate performance indicators and economic appraisal, even as it is increasingly recognized that transport systems distribute benefits and burdens unevenly across space and social groups. Transport justice research highlights these distributional concerns, yet many equity assessments embed implicit assumptions about what constitutes fair distribution and rarely compare alternative distributive principles. This paper asks how justice-theory choice alters intra-urban transport equity assessments and how distributive theories can be translated into quantitative metrics using spatial data. Rather than privileging a single perspective, we translate four prominent justice theories — utilitarianism, egalitarianism, prioritarianism, and sufficientarianism — into quantitative metrics and apply them to Berlin. We compute four transport currencies on 100 m × 100 m census grids and aggregate results to neighborhoods and districts using weighted and unweighted specifications. Currencies include 15-min walking accessibility to essential services, traffic noise, severe-injury and fatal road traffic crash density, and the proportion of car-dedicated street space. Egalitarian inequality metrics systematically diverge from other logics, sometimes reversing area rankings. Utilitarian, prioritarian, and sufficientarian metrics often converge because high mean burdens coincide with local hotspots and large shares exceeding minimum standards. Socioeconomic index ranking adds a social-ordering dimension and mainly reshapes interpretation at fine scales, distinguishing spatial hotspots from socially structured disadvantage. Overall, the study shows that equity metrics encode contestable normative claims and suggests that different transport outcomes may require different justice perspectives. For practice, we recommend either justifying the adopted principle or developing currency-specific evaluation logics alongside comparative reporting.
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Sierts et al. (2026) studied this question.
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