Situational Awareness, Drivers Trust in Automated Driving Systems and Secondary Task Performance
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Summary
This study investigates how situational awareness (SA) influences driver trust in automated driving systems and subsequent performance on secondary tasks. The authors address the problem that drivers often lack trust in automation, causing them to monitor the vehicle rather than engage fully in non-driving activities, which hinders task performance. The central hypothesis is that enhancing a driver’s situational awareness—by providing information about the driving environment—will increase trust in the automated system, allowing drivers to focus more effectively on secondary tasks. The researchers conducted a human-in-the-loop experiment with 30 participants using a driving simulator. Participants performed a semi-autonomous driving task while completing a visual secondary task (identifying target letters among distractors). The study employed a within-subjects design with three conditions manipulating the level of situational awareness support via auditory messages: a control condition with no information, a low SA condition providing a status update (“Stopped vehicle ahead”), and a high SA condition providing a status update plus a suggested course of action (e.g., “No action needed” or “Take control now”). Data were collected through surveys measuring self-reported trust and situational awareness, eye-tracking to monitor gaze behavior, heart rate monitors for physiological stress indicators, and driving logs to assess takeover behavior and secondary task accuracy. Results indicated that increased situational awareness significantly promoted trust and improved secondary task performance. Specifically, the high SA condition led to significantly higher self-reported trust and better situational awareness scores compared to the control condition. Behaviorally, drivers in the high SA condition waited longer before taking control of the vehicle and stayed in their lane closer to obstacles, indicating greater reliance on the automation. Eye-tracking data showed that drivers in both SA conditions spent less time monitoring the road than those in the control condition, suggesting they felt more comfortable disengaging from the driving task. Physiological measures, including heart rate and heart rate variability, did not show significant differences across conditions. Crucially, statistical modeling revealed that situational awareness moderated the relationship between trust and secondary task performance; higher situational awareness amplified the positive impact of trust on task completion rates. The findings demonstrate that providing drivers with clear situational awareness information enhances their trust in automated systems, enabling them to perform secondary tasks more effectively. This suggests that driver assistance systems should not only automate driving functions but also actively communicate the vehicle’s understanding of the environment and intended actions. By reducing uncertainty and cognitive load, such systems can facilitate safer and more efficient human-automation interaction, allowing drivers to leverage the benefits of automation without compromising performance on concurrent tasks.
Key finding
High-SA audio (status + recommended action) raised composite SART scores and self-reported trust over control, reduced on-road monitoring ratio (0.125 vs 0.180), and let drivers wait longer (9,900 ms vs 8,000 ms in low-SA) and stay in-lane closer (85 m vs 130 m in low-SA) before taking control. The moderation model indicated SA both promoted and amplified the effect of trust on secondary-task performance.
Methodology
simulator
Sample size: 30 (33 recruited, 3 excluded for simulation errors); 22 male, 8 female; mean age 25.7 (SD 5.5)
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 on 2026-05-04 (3 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | arxiv | — | — | 3 | 2026-05-04 |
| archive | success | — | — | — | 1 | 2026-05-04 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-04 |
| promote | success | — | — | — | 1 | 2026-05-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 16 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
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
- trust calibration
- automation
- automation surprise
- mode awareness
- trust in automation foundations
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: behavioral performance data, self report data
- Theoretical Contribution: theory or model