How can design help enhance trust calibration in public autonomous vehicles?
DOI: 10.48550/arxiv.2106.16106
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Summary
This paper addresses the challenge of calibrating passenger trust in public autonomous vehicles (AVs), specifically focusing on the psychological and functional void created by the absence of a human driver. The authors argue that trust is a critical, multilayered concept for the successful adoption of AVs, and that design interventions can help establish an adequate level of trust for safe and positive user experiences. The research was motivated by the need to replace the traditional roles of the driver—such as providing safety cues, confirming routes, and offering reassurance—with effective human-machine interfaces (HMI) that foster familiarity, authority, and control among passengers. The study was conducted by an international, multidisciplinary team from the University of Tokyo and Bezalel Academy of Art and Design. Utilizing design-led methodologies including ideation, design thinking, and “treasure hunting,” the team developed “Project Ripple,” an experimental HMI prototype. The core hypothesis posits that using the vehicle floor as an interactive interface can streamline trust calibration. The team identified three key scenarios impacted by the driver’s absence: boarding/alighting, detailed ride information, and ambient environmental information. To address these, they designed an interactive floor interface that provides physical and visual feedback. For instance, the floor acknowledges a passenger’s presence upon boarding, signals vehicle movements like braking, and displays personalized ride details such as stops and fares. This approach aims to replace anthropomorphic or high-tech screens with natural, nature-inspired interactions that reduce estrangement. The paper outlines the current prototyping phase and future experimental design rather than presenting final empirical results. The team has constructed a “prototype booth” mimicking a bus interior, equipped with interactive flooring, LIDAR sensors, and pressure sensors to test the three defined scenarios. In this lab setting, participants interact with the prototype while their behaviors are observed and evaluated via questionnaires and interviews. The research aims to determine whether the timing, nature, and adequacy of information contribute to building trust or if redundant information harms it. Future steps involve deploying the refined interface on a Navia autonomous shuttle for real-world testing in Tokyo and Jerusalem. These trials will assess the system’s effectiveness across different cultural contexts and investigate whether trust can be regained after being lost, addressing the dynamic nature of trust in automated systems. The significance of this work lies in its shift from driver-centric to passenger-centric trust calibration in public transportation. By proposing the vehicle floor as a mediator for communication, the study offers a novel design solution to counter the fear of the unknown associated with driverless vehicles. The research highlights the importance of replacing traditional human cues with coherent, ambient digital feedback to maintain a sense of safety and control. Ultimately, the project seeks to provide a framework for designing HMI systems that not only inform passengers but also actively build and maintain trust, thereby facilitating the societal acceptance of autonomous public transport.
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 author_sweep_intake on 2026-05-28.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | canonical_url | — | — | 1 | 2026-06-04 |
| extract | success | cached | — | — | 3 | 2026-06-15 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-15 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-06-15 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-15; verification: verified.
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- Applied Guidance: design guidelines
- Empirical Findings: self report data