The burgeoning resurgence of interest in artificial intelligence (AI) is transforming urban planning and design. While studies have leveraged AI for generative planning and design, the focus has been on augmenting the capabilities of planners and designers, often overlooking public participation. Addressing this gap, this study proposes a new AI-aided and data-driven (AIDD) framework that integrates design, science, and participation to support participatory generative planning and design. Demonstrated in a hypothetical design case, this framework allows users with limited expertise to generate designs that resemble favored urban forms, meet zoning requirements, and improve safety perception performance.
Steven Jige Quan (2026) studied this question.