Effect of Explanatory Interfaces on Safety and Trust in L3 Automated Driving: Pre-Task, During-Task, and Post-Task Comparisons

Empirical insights into how explanatory HMIs (X-HMIs) shape driver trust, perceived safety, and takeover performance across pre-task, during-task, and post-task phases in Level 3 automated driving remain scarce. This driving simulator study (n = 64) employed a 2 (HMI type) × 3 (task phase) mixed design to compare objective takeover metrics (time, lateral stability) and subjective evaluations across planned and unplanned takeover scenarios. X-HMI did not significantly reduce takeover time for planned or unplanned takeovers (p = 0.295 and p = 0.340, respectively), but markedly improved takeover quality: y-axis velocity deviation decreased by 46% (p < 0.001) and steering angle deviation by 58% (p < 0.001), indicating enhanced lateral stability and smoother control. Subjectively, X-HMI significantly elevated trust and perceived safety across all phases (all p < 0.001) with large effect sizes (Cohen’s d > 1.4). These findings suggest that X-HMIs enhance safety and user experience not by expediting driver responses, but potentially by calibrating appropriate trust and contributing to stable control transitions. Phase-specific transparency emerges as a core HMI design principle, providing a validated framework for user-centered automated driving systems.

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Publication Details

Journal
International Journal of Human-Computer Interaction
Published
2026-08-27
DOI
https://doi.org/10.1080/10447318.2026.2721894
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Effect of Explanatory Interfaces on Safety and Trust in L3 Automated Driving: Pre-Task, During-Task, and Post-Task Comparisons

Banben He, Yu Wu, Xiaofang Yuan
International Journal of Human-Computer Interaction
Human-Automation Interaction and Safety
article

Effect of Explanatory Interfaces on Safety and Trust in L3 Automated Driving: Pre-Task, During-Task, and Post-Task Comparisons

Banben He, Yu Wu, Xiaofang Yuan
article en

Abstract

Empirical insights into how explanatory HMIs (X-HMIs) shape driver trust, perceived safety, and takeover performance across pre-task, during-task, and post-task phases in Level 3 automated driving remain scarce. This driving simulator study (n = 64) employed a 2 (HMI type) × 3 (task phase) mixed design to compare objective takeover metrics (time, lateral stability) and subjective evaluations across planned and unplanned takeover scenarios. X-HMI did not significantly reduce takeover time for planned or unplanned takeovers (p = 0.295 and p = 0.340, respectively), but markedly improved takeover quality: y-axis velocity deviation decreased by 46% (p < 0.001) and steering angle deviation by 58% (p < 0.001), indicating enhanced lateral stability and smoother control. Subjectively, X-HMI significantly elevated trust and perceived safety across all phases (all p < 0.001) with large effect sizes (Cohen’s d > 1.4). These findings suggest that X-HMIs enhance safety and user experience not by expediting driver responses, but potentially by calibrating appropriate trust and contributing to stable control transitions. Phase-specific transparency emerges as a core HMI design principle, providing a validated framework for user-centered automated driving systems.

International Journal of Human-Computer Interaction
Tongji University (CN), Wuhan University of Technology (CN)
Openalex Percentile: Top 6%
Human-Automation Interaction and Safety
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