Investigating the critical building layout features on the wayfinding process by integrating graph theory and virtual reality

Indoor wayfinding is a critical aspect of fire evacuations and is significantly affected by the building layout features. Existing research has focused on the topological parametric evaluation of building layouts and investigated the impact of layout features on route choice and exit selection. However, these studies overlooked the impact of critical layout features on wayfinding process in terms of human cognitive and behavioural responses. Therefore, this paper proposed a method to identify the critical building layout features and evaluate their impact on the wayfinding efficiency by integrating Graph Theory (GT) and Virtual Reality (VR) technology. GT enables a parametric evaluation of evacuation routes, and a VR-based platform provides human-environment interaction, and collects behaviour data to assess the impact of building layout on fire evacuation. This study introduced two cognitive load-related metrics, Cognitive Load of Area ( CLA ) and Cognitive Load of AOI ( CLA_eye ), which integrated behaviour data and GT-based parameters, enabling the calculation of cognitive load distribution across various areas and identifying critical layout features that significantly affect cognitive load during wayfinding. The results highlighted that accessibility, connectivity, fragmentation level, travel distance, average path length, and central hub area serve as the critical layout features that significantly impact wayfinding performance. Following that, recommendations are provided to building designers for improving fire safety design. This study provides a novel cognitive load measurement considering human behavioural data and parameters and offers a comprehensive evaluation of building layout design, contributing to supporting designers in building design assessment in terms of fire evacuation efficiency.