From Paper Charts to Augmented Reality: A Two-Phase Mixed-Methods Investigation of Taxiing Support Technologies and the Design Case for Pilot-Directed Sequential Information Architecture

Airport taxiing imposes substantial cognitive demands on flight crews, particularly at unfamiliar airports. This study employed a two-phase mixed-methods design to investigate taxiing-support technologies and associated operational needs. Phase 1 was a human-in-the-loop simulation experiment with 30 Korean pilots comparing Paper Chart, ForeFlight EFB, and Taxi Ribbon (AR chevrons) using subjective difficulty, positional situation awareness (SA), response initiation time, and taxi errors. Positional SA was assessed using a SAGAT-derived freeze-and-query procedure. Both digital conditions were rated as less difficult than Paper Chart. Taxi Ribbon produced significantly shorter response initiation latency than Paper Chart, whereas no statistically significant condition effect was detected in positional SA accuracy. Phase 2 surveyed 44 active Korean commercial pilots using episodic memory recall. ATC route visualization and ATC instruction text display showed the largest information gaps, highlighting spatial-information processing and clearance comprehension as key support needs. Integrating these findings, we propose the Pilot-Directed Sequential Information Architecture (PDSIA), comprising allocentric pre-taxi planning, egocentric AR execution support, and cross-modal threat alerting. PDSIA is presented as an evidence-informed conceptual framework requiring integrated empirical validation.