How transport systems create opportunities for social interaction

Social mixing in cities emerges from encounters between individuals of different backgrounds in shared spaces. These opportunities for inter-group contact are not randomly distributed but shaped by urban transport systems that channel millions of daily trajectories. As cities face rising segregation, understanding and quantifying these opportunity structures has become critical for designing evidence-based policies that foster social inclusion. Yet existing approaches face significant limitations in capturing the probabilistic nature of these opportunities within complex, multimodal cities. This study addresses this gap by developing a computational framework that treats encounters as likelihoods shaped by behavioral uncertainty. Encounter probabilities among individuals are calculated within mode-specific encounter spaces—from individual roads, city blocks to rail and bus service segments—by aggregating potential trajectories across socioeconomic groups. Using city-scale mobility data, the outcomes reveal how infrastructure, daily rhythms, and travel choices interweave to create spatially and temporally varying opportunity structures across multimodal transport systems. We then extend these findings through agent-based simulations, demonstrating how transport policies designed to promote sustainable mobility may produce unintended social consequences. The study underscores that effective policymaking for social inclusion must account for how transport interventions reshape encounter opportunities in citizens' daily mobility.