Decoding human-space interaction: how point-line-area structures shape wayfinding performance in multi-granular space

Wayfinding in large public buildings remains difficult to predict from overall layout alone. We decomposed an airport terminal into point-like, line-like, and area-like primitives, quantified visibility and accessibility with Space Syntax, and derived local wayfinding load from eye-tracking, think-aloud protocols, and behavioral observations. Local wayfinding load peaked where low visibility coincided with high accessibility. Point-like primitives carried decision demands and line-like primitives monitoring demands. Cumulative load exposure along routes was associated with reduced wayfinding efficiency. The framework offers a meso-level account linking spatial granularity, local structure, and continuous human-space interaction.