How to improve pedestrians' trust in automated vehicles: new road infrastructure, external human–machine interface with anthropomorphism, or conventional road signaling?
DOI: 10.3389/fpsyg.2023.1129341
archive: archived pipeline: cataloged verified
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Summary
This study addresses the critical challenge of establishing pedestrian trust in automated vehicles (AVs), a prerequisite for their societal acceptance. The core problem is the lack of effective communication channels between AVs and pedestrians, which can lead to uncertainty and unsafe interactions. The research investigates whether trust and willingness to cross streets can be improved through three distinct communication methods: new road infrastructure, an external human–machine interface (eHMI) with anthropomorphic features, or conventional road signaling via eHMI. The methodology involved an online survey with 731 participants who were mentally projected into standard and non-standard street crossing scenarios. The study compared three user-centered interfaces: "BOLD," an LED eHMI displaying conventional signals; "Alfy," an anthropomorphic eHMI featuring a virtual driver avatar; and "Sirocco," a smart road infrastructure system using poles with lights and projectors. Participants evaluated their feelings (trust, distrust, safety, uncertainty) and behaviors (willingness to cross, normed vs. non-normed crossing) after viewing video simulations of these interfaces in both safe and dangerous contexts. Data were analyzed using multivariate ANOVA and Pearson’s correlations. The results demonstrated that all three human–machine interfaces significantly improved pedestrian trust and willingness to cross compared to AVs without such interfaces. Specifically, the anthropomorphic eHMI (Alfy) showed significant advantages over the conventional LED eHMI (BOLD) in inducing trust and promoting safer crossing behaviors. However, the most impactful finding was the superior efficiency of the trust-based road infrastructure (Sirocco). This infrastructure-based approach yielded the best global street crossing experience, enhancing perceived safety, trust, and anticipation while reducing distrust and uncertainty more effectively than vehicle-mounted interfaces. The infrastructure also performed well in non-standard, riskier situations. The significance of these findings lies in supporting a trust-centered design approach for automated mobility. The study concludes that while anthropomorphic features on vehicles are beneficial, integrating communication into the road infrastructure offers the most robust solution for ensuring safe and satisfying human–machine interactions. This implies that future AV deployment should prioritize smart infrastructure upgrades alongside vehicle technology to effectively manage pedestrian expectations and safety.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | pdftotext | — | — | 4 | 2026-08-10 |
| clean | success | clean | — | — | 2 | 2026-08-10 |
| chunk | success | chunk | — | — | 2 | 2026-08-10 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 2 | 2026-08-10 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 17 | 2026-08-11 |
| verify | partial | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified_with_issues.
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