Effect of riding experience and HMI on users' trust and riding comfort in fully driverless autonomous motorcycles
DOI: 10.1016/j.apergo.2025.104580
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Summary
This study addresses the critical barriers to the widespread adoption of fully driverless autonomous vehicles (AVs): low user trust and high incidence of motion sickness (MS). While previous research suggested that Human-Machine Interfaces (HMIs) displaying vehicle trajectories could enhance trust and alleviate MS, these findings were largely derived from simulations or "Wizard of Oz" studies lacking realistic risk and vehicle dynamics. This research investigates, for the first time in a commercially operating robotaxi, whether displaying real-time dynamic trajectory plans affects passengers' perceived system transparency, trust, and MS symptoms. It also examines the role of riding experience in shaping trust. The methodology involved an on-road experiment with 16 participants who had no prior AV riding experience and scored above the 50th percentile for MS susceptibility. Participants completed two 15-km rides in a fully driverless MPV, engaging in a visual non-driving-related task (watching videos) throughout. The study employed a within-subject design where the availability of the dynamic trajectory HMI was counterbalanced: in one condition, the screen displayed the AV’s planned path and perceived environment; in the other, this information was concealed. Vehicle dynamics were recorded via an Inertial Measurement Unit, and subjective measures included pre- and post-ride questionnaires for trust and system transparency, as well as minute-by-minute oral reports of MS using the Misery Scale and post-ride Motion Sickness Assessment Questionnaires. Linear mixed-effects models were used to analyze the data. The results indicated that displaying the dynamic trajectory HMI had limited effects on perceived system transparency and trust, failing to support the hypothesis that such information boosts trust. However, the initial riding experience significantly enhanced trust, with the first ride producing a substantial increase in trust scores that stabilized by the second ride. Regarding motion sickness, while the HMI did not produce a statistically significant reduction in overall MS scores, there was a discernible trend toward alleviation. Specifically, the increase in gastrointestinal and peripheral MS symptoms was non-significant when the HMI was present, whereas these symptoms increased significantly without the HMI. The study also confirmed that motion stimuli and task engagement were consistent across conditions, ensuring valid comparisons. The findings suggest that while real-time trajectory visualization may offer marginal benefits for MS mitigation, it is insufficient for enhancing trust in AVs, particularly among tech-savvy users who already possess high initial transparency perceptions. The study concludes that the first ride experience is the most critical factor for trust enhancement, implying that service providers should prioritize optimizing the initial user experience. Furthermore, the authors recommend future HMI designs incorporate explanations for vehicle actions and integrate non-visual cues, such as auditory or tactile feedback, to more effectively mitigate motion sickness and build user trust.
Key finding
The initial riding experience significantly enhances user trust in autonomous vehicles, while displaying real-time dynamic trajectory plans has limited impact on trust and only a non-significant trend toward alleviating motion sickness.
Methodology
on_road
Sample size: 16
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | — | — | — | 1 | 2026-05-28 |
| archive | success | canonical_url | — | — | 1 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-07 |
| chunk | success | chunk | — | — | 1 | 2026-06-07 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-07 |
| enrich | success | semantic_scholar | — | — | 4 | 2026-06-15 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 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.
- trust calibration
- passenger motion sickness comfort
- automation
- acceptance adoption
- automation surprise
- trust in automation foundations
Information type
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- Empirical Findings: self report data