From Awareness to Intent: Mitigating Silent Driving System Failures through Prospective Situation Awareness Enhancing Interfaces

Wang, Jiyao; Yan, Song; Yang, Xiao; He, Qihang; Wang, Ange; Liu, Chenglin; Chen, Chenglin; Wang, Zhenyu; He, Dengbo · 2026 · arXiv

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Summary

This study addresses the critical safety challenge of "silent failures" in partially automated vehicles (SAE Level 2), where the automated driving system (ADS) fails to detect hazards or plans conflicting trajectories without issuing a takeover request (TOR). While existing research focuses on TOR-initiated scenarios, silent failures leave drivers with minimal time to react, particularly when hazards are invisible or obscured. The authors investigate whether Prospective Situation Awareness Enhancement (PSAE) interfaces, delivered via augmented reality head-up displays (AR-HUD), can mitigate these risks by providing forward-looking information about the system’s perception and planned maneuvers. The researchers conducted a multi-modal driving simulator study with 48 participants using a mixed 4×2×2 factorial design. The between-subject factors were PSAE type (Baseline, Environment Perception [EP], Planned Maneuver [PM], and Combined [EP+PM]) and lighting condition (day vs. night). The within-subject factor was hazard visibility (visible vs. invisible). Participants encountered six silent-failure scenarios while physiological data, including electroencephalography (EEG) and electromyography (EMG), were recorded to measure cognitive processing and motor preparation. The study analyzed behavioral metrics (takeover lead time and success), subjective psychological states (situation awareness, trust, perceived safety), and neuro-physiological indicators to determine how PSAE interfaces influence driver performance. The results indicate that situational awareness (SA) serves as a significant moderating factor through which PSAE interfaces improve takeover performance. Specifically, providing perceptual cues (EP) was most effective in enhancing drivers’ SA, allowing them to better detect system misalignments with the environment. In contrast, communicating system intent (PM) was superior for building driver trust. The study also identified correlations between SA and neuro-physiological activity, noting that the interface’s effect on performance was indirectly mediated by the driver’s SA. Statistical analyses revealed significant effects of PSAE type and lighting conditions on SA, perceived safety, and physiological markers such as frontal theta activation time and parietal alpha power ratios. The significance of this work lies in its contribution to understanding how transparency-oriented interfaces support drivers during safety-critical silent failures. By demonstrating that different PSAE components serve distinct psychological functions—perception cues for awareness and maneuver cues for trust—the study provides empirically grounded design insights for human-machine interaction in automated driving. It suggests that effective HMI design for silent failures should prioritize enhancing prospective situation awareness to bridge the gap between system limitations and driver response capabilities, thereby improving overall safety in shared-control driving paradigms.

Key finding

PSAE interfaces improved takeover performance via situational awareness as a mediator; perceptual cues were most effective at enhancing SA, while intent cues better supported trust calibration; an EEG ERSP correlate of SA was identified, supporting transparency-oriented HMI design for silent failures.

Methodology

simulator

Sample size: N=48 participants

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via discover_arxiv_cs.HC on 2026-05-04 (4 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• situational awareness
• automation
• mode awareness
• automation surprise
• anticipation
• hazard perception

Information type

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• Methodological Resource: tool software
• Theoretical Contribution: theory or model, conceptual framework