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The paper introduces CoDesignAI, a multi-agent, multi-user system leveraging LLMs to enhance collaborative urban design by integrating residents and domain expert AI agents. CoDesignAI combines generative AI with spatial mapping to visualize design proposals at street level, while AI agents summarize discussions, extract design intentions, and generate prompts for design interventions. The system facilitates iterative design refinement and documents the process, demonstrating a shift towards more open and participatory urban design.
Democratizing urban design, CoDesignAI lets residents collaborate with AI expert agents to visualize and refine street-level proposals, potentially reshaping public participation in city planning.
Public participation has become increasingly important in collaborative urban design; yet, existing processes often face challenges in achieving efficient and scalable citizen engagement. To address this gap, this study explores how large language models (LLMs) can support cooperation among community members in participatory design. We introduce CoDesignAI, a collaborative urban design tool that combines multiple users, representing residents or stakeholders, with multiple AI agents, representing domain experts who provide facilitation and professional knowledge during the conceptual stage of urban design. This paper presents the system architecture and main components of the tool, illustrating how users interact with AI agents within a collaborative and iterative design workflow. Specifically, the system integrates generative AI with spatial mapping services to support street-level visualization of design proposals. AI agents assist users by summarizing discussion content, extracting shared design intentions, and generating prompts for presenting design interventions. The system also enables users to revise and refine their ideas over multiple rounds while documenting the design process. By combining conversational AI, multi-user interaction, and image-based design grounded in real-world urban contexts, this study argues that AI-enabled design systems can help shift urban design from an expert-centered practice to a more open and participatory process. The paper contributes a new web-based platform for AI-assisted collaborative design and offers an early exploration of how AI agents may expand the capacity for public participation in urban design.
