Hexagonal cellular automata and graph theory for procedural spatial layout generation

Spatial layout planning involves arranging spaces to meet functional and aesthetic requirements, a process increasingly automated to save time and explore diverse design alternatives. This study aims to automate the spatial layout planning process using a procedural approach chosen for its flexibility, control, and reduced reliance on large, high quality data sets. The proposed methodology introduces three core algorithms based on hexagonal cellular automata and graph theory, with its versatility showcased across mock examples of public spaces and a real-world case study. The generated layouts effectively satisfy the user-defined design objectives of area, adjacency, and design boundary. A post-processing step converts the hexagonal layouts into rectangular forms with orthogonal corners to align better with conventional architectural layouts while adhering to design constraints. This approach provides a potential foundation for developing automated, user-interactive tools, capable of addressing complex design objectives in architectural contexts. Future work includes the potential integration of visibility and circulation metrics through space syntax analysis and agent-based modelling to enhance wayfinding, traffic flow, and user experience of spatial layouts.