Dataset on passenger acceptance during autonomous ferry public trials: Questionnaires and interviews

Area of Science:

• Maritime Technology
• Human-Computer Interaction
• Transportation Science

Background:

• Public acceptance is crucial for autonomous vehicle (AV) adoption in urban transport.
• Assessing passenger perceptions of safety, trustworthiness, and reliability is key to understanding AV integration challenges.
• The maritime sector is exploring autonomous solutions for public transit.

Purpose of the Study:

• To present a comprehensive dataset from the inaugural public trial of an urban autonomous passenger ferry.
• To provide data for analyzing passenger acceptance of autonomous ferry technology.
• To facilitate research on technology acceptance indicators for autonomous vehicles.

Main Methods:

• Collected paired-sample questionnaire data (N=884) assessing perceived safety, trustworthiness, and reliability before and after ferry use.
• Gathered qualitative data through semi-structured interviews (N=25) on passenger perceptions.
• Conducted on-site data collection during a real-world public trial in Trondheim, Norway.

Main Results:

• The dataset captures pre- and post-interaction passenger responses regarding autonomous ferry experience.
• Qualitative interview transcripts provide in-depth insights into user perceptions.
• The data enables quantitative and qualitative analysis of technology acceptance factors.

Conclusions:

• The dataset is valuable for understanding public perception of autonomous maritime transport.
• Findings can inform the development of acceptance indicators for autonomous vehicles in public transportation.
• The data supports research applicable to both maritime and broader autonomous vehicle contexts.