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Multi-party Conversation of Driving Agents: The Effects of Overhearing Information on Lifelikeness and Distraction

Recently, the applications of conversational robots have been gaining popularity due to their potential in providing information while engaging the user in a conversation. However, when a user's attention is already focused on a task, engaging them in conversation may be difficult or even risky. The Human-Robot Interaction (HRI) field should consider interaction methods where a conversational robot can keep the user informed but without the obligation of engagement in the conversation. In this study, we discuss such an approach within a driving scenario by utilizing a multi-party social robot platform that comprises three minimalistic conversational robots, which possesses the feature of being able to decrease the number of directed utterances toward a driver through a turn-taking process among the robots. The results of this study revealed that overhearing information from the multi-party conversation of driving agents is perceived as possessing more life-like characteristics compared to a conventional, one-to-one communication-based approach that directly addresses the driver. Moreover, the proposed approach reduced the distraction level and increased the enjoyment of the drivers.