  In recent years, the rapid development of large-scale models has made new
possibilities for interdisciplinary fields such as architecture. In this paper,
we present a novel daylight-driven AI-aided architectural design method.
Firstly, we formulate a method for generating massing models, producing
architectural massing models using random parameters quickly. Subsequently, we
integrate a daylight-driven facade design strategy, accurately determining
window layouts and applying them to the massing models. Finally, we seamlessly
combine a large-scale language model with a text-to-image model, enhancing the
efficiency of generating visual architectural design renderings. Experimental
results demonstrate that our approach supports architects' creative
inspirations and pioneers novel avenues for architectural design development.
Project page: https://zrealli.github.io/DDADesign/.
