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Main Authors: Mean, Chan Chea, Alam, Sameer, Fennedy, Katherine, Hsieh, Meng-Hsueh, Xin, Shiwei, Hilburn, Brian
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2505.01679
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author Mean, Chan Chea
Alam, Sameer
Fennedy, Katherine
Hsieh, Meng-Hsueh
Xin, Shiwei
Hilburn, Brian
author_facet Mean, Chan Chea
Alam, Sameer
Fennedy, Katherine
Hsieh, Meng-Hsueh
Xin, Shiwei
Hilburn, Brian
contents Runway and taxiway incursions continue to challenge aviation safety, as pilots often experience disorientation from poor visibility in adverse conditions and cognitive workload in complex airport layouts. Current tools, such as airport moving maps on portable tablets, allow manual route planning but do not dynamically adapt to air traffic controllers' (ATCOs) clearances, limiting their effectiveness in high-stress scenarios. This study investigates the impact of different input modalities - paper-based, keyboard touch, map touch, and speech-to-text - on taxiway navigation performance, using a medium-fidelity flight simulator and a Wizard-of-Oz methodology to simulate ideal automation conditions. Contrary to common assumptions, recent studies indicate that paper-based methods outperform digital counterparts in accuracy and efficiency under certain conditions, highlighting critical limitations in current automation strategies. In response, our study investigates why manual methods may excel and how future automation can be optimized for pilot-centered operations. Employing a Wizard-of-Oz approach, we replicated the full taxiing process - from receiving ATCO clearances to executing maneuvers - and differentiated between readback and execution accuracy. Findings reveal that speech-based systems suffer from low pilot trust, necessitating hybrid solutions that integrate error correction and confidence indicators. These insights contribute to the development of future pilot-centered taxiway assistance that enhance situational awareness, minimize workload, and improve overall operational safety.
format Preprint
id arxiv_https___arxiv_org_abs_2505_01679
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Evaluating Input Modalities for Pilot-Centered Taxiway Navigation: Insights from a Wizard-of-Oz Simulation
Mean, Chan Chea
Alam, Sameer
Fennedy, Katherine
Hsieh, Meng-Hsueh
Xin, Shiwei
Hilburn, Brian
Human-Computer Interaction
Runway and taxiway incursions continue to challenge aviation safety, as pilots often experience disorientation from poor visibility in adverse conditions and cognitive workload in complex airport layouts. Current tools, such as airport moving maps on portable tablets, allow manual route planning but do not dynamically adapt to air traffic controllers' (ATCOs) clearances, limiting their effectiveness in high-stress scenarios. This study investigates the impact of different input modalities - paper-based, keyboard touch, map touch, and speech-to-text - on taxiway navigation performance, using a medium-fidelity flight simulator and a Wizard-of-Oz methodology to simulate ideal automation conditions. Contrary to common assumptions, recent studies indicate that paper-based methods outperform digital counterparts in accuracy and efficiency under certain conditions, highlighting critical limitations in current automation strategies. In response, our study investigates why manual methods may excel and how future automation can be optimized for pilot-centered operations. Employing a Wizard-of-Oz approach, we replicated the full taxiing process - from receiving ATCO clearances to executing maneuvers - and differentiated between readback and execution accuracy. Findings reveal that speech-based systems suffer from low pilot trust, necessitating hybrid solutions that integrate error correction and confidence indicators. These insights contribute to the development of future pilot-centered taxiway assistance that enhance situational awareness, minimize workload, and improve overall operational safety.
title Evaluating Input Modalities for Pilot-Centered Taxiway Navigation: Insights from a Wizard-of-Oz Simulation
topic Human-Computer Interaction
url https://arxiv.org/abs/2505.01679