This paper advances a human-centered understanding of urban acceptance of autonomous vehicles (AVs) within ambient-intelligence mobility systems. Using survey data from 5,070 respondents across ten European pilot sites, we construct an AV Acceptance Index that combines perceived efficiency, economic acceptability, and commuting preference to capture individual readiness for autonomous mobility. The index reveals a population split between moderate and high acceptance, with a smaller but non-negligible low-acceptance minority, indicating that AVs are broadly plausible but far from universally embraced.A harmonized ordinary least squares model with 46 significant predictors explains about half of the variance in the index, showing that acceptance emerges from the joint influence of socio-demographics, mobility resources (access to and use of transport modes, perceived infrastructure quality, congestion and weather constraints), and contextualized perceptions of benefit, ease of use, and safety. Building on the strongest determinants, regression-guided k-means clustering identifies four archetypes: Low-resource skeptics, Assistance-seeking enthusiasts, Mainstream cautiously positive, and a Cautious under-served mainstream. Association rule mining further uncovers segment-specific patterns linking mobility resources, public transport use, and benefit perceptions to acceptance levels. Taken together, the results show that moving toward humanized autonomous mobility requires differentiated strategies: expanding concrete mobility opportunities and perceived benefits in resource-poor contexts, designing AV services as assistive infrastructure for users with functional limitations, and embedding AVs transparently within existing public transport ecosystems.