Information vs situation: balancing transparency and autonomy for trustworthy autonomous vehicles

Area of Science:

• Human-Robot Interaction
• Autonomous Systems
• Human-Computer Interaction

Background:

• Autonomous vehicles (AVs) are evolving into interactive agents with social features.
• This shift necessitates understanding human-robot interaction (HRI) dynamics.
• Key challenges include fostering trust, comfort, and agency between humans and AVs.

Purpose of the Study:

• To explore how information sharing and autonomy levels affect human perception of AVs.
• To investigate factors influencing user acceptance and trustworthiness of AVs.
• To understand the interplay between AV transparency, environment, and user-granted autonomy.

Main Methods:

• A between-subjects online study utilizing participatory design principles.
• Investigated the impact of different AV interfaces with varying information levels.
• Assessed participants' trust and comfort ratings regarding AV perception.

Main Results:

• AV transparency (information sharing) significantly influenced user trust and comfort.
• User acceptance of AV autonomy was complex, affected by transparency.
• Driving environment and specific AV events also played a role in perceived autonomy.

Conclusions:

• AV interface design, particularly information transparency, is crucial for user acceptance.
• Building trust and comfort in AVs requires a nuanced approach considering context.
• Future research should further explore the multifaceted relationship between users and autonomous systems.