Bidirectional Adaptation of Shared Autonomous Vehicles(SAVs) and Old Town’s Urban Spaces: The Views of Residents on the Present and the Future

The integration of shared autonomous vehicles into historic urban areas presents both opportunities and challenges. In heritage-rich environments like very old Asian (such as Suzhou old town, which serves as a use case example) or European (especially Mediter ranean coastal cities) areas—characterized by narrow alleys, dense development, and sen sitive cultural landscapes—shared autonomous vehicle adoption raises critical spatial and social questions. This study employs a qualitative, user-centered approach based on the ripple model to examine residents’ perceptions across four dimensions: residential pat terns, parking land use, regional accessibility, and street-level infrastructure. Semi-struc tured interviews with 27 participants reveal five key findings: (1) public trust depends on transparent decision-making and safety guarantees; (2) shared autonomous vehicles may reshape generational residential clustering; (3) the short-term parking demand remains stable, but the long-term reuse of space is feasible; (4) shared autonomous vehicles could enhance accessibility in historic cores; (5) transport systems may evolve toward intelli gent, human-centered designs. Based on these insights, the study proposes three strate gies: (1) transparent risk assessment using explainable artificial intelligence and digital twins; (2) polycentric development to diversify land use; (3) hierarchical street retrofitting to balance mobility and preservation. While this study is limited by its qualitative scope and absence of simulation, it offers a framework for culturally sensitive, small-scale inter ventions supporting sustainable mobility transitions in historic urban contexts.