Underground Parking Layout Generation Based on the WaveFunctionCollapse Algorithm

Abstract

During the design process, architectural layout configuration is subject to complex constraints such as site conditions and design requirements, resulting in limited design efficiency. This research aims to provide architects with an effective design tool that can generate reference-worthy underground parking layout solutions based on the given site information. In this research, we extract spatial modules from underground parking layouts, and transform the design constraints into adjacency rules based on the analysis of the configuration process for underground parking layout, then develop a generation and optimization model of the underground parking layout based on the WaveFunctionCollapse algorithm (WFC) and Multi-objective Optimization (MOO), and verify the effectiveness of the model through experiments. The results show that with given plan contour and entrance/exit locations as inputs, the model can efficiently generate architectural layout solutions that meet the design objectives.

Keywords

• underground parking layout configuration
• generative design
• WaveFunctionCollapse algorithm (WFC)
• multi-objective optimization (MOO)