Abstract
Anthropomorphic robots need to maintain effective and emotive communication with humans as automotive agents to establish and maintain effective human–robot performances and positive human experiences. Previous research has shown that the characteristics of robot communication positively affect human–robot interaction outcomes such as usability, trust, workload, and performance. In this study, we investigated the characteristics of transparency and anthropomorphism in robotic dual-channel communication, encompassing the voice channel (low or high, increasing the amount of information provided by textual information) and the visual channel (low or high, increasing the amount of information provided by expressive information). The results showed the benefits and limitations of increasing the transparency and anthropomorphism, demonstrating the significance of the careful implementation of transparency methods. The limitations and future directions are discussed.
Highlights
The emergence of on-board intelligent robots has enriched the practical application scenarios for robots, enhanced the human–vehicle interaction experience, and improved the overall intelligence level of the intelligent cockpit
We investigated the differences between two transparency levels for two tasks in the driving state and three transparency levels for one task in the nondriving state, sent by the on-board robot to humans via voice and vision (Figure 1)
Participants in Group 2 and Group 3 had much longer sweep duration means of the robot, which implies that the participants were more interested in the robot performances in
Summary
The emergence of on-board intelligent robots has enriched the practical application scenarios for robots, enhanced the human–vehicle interaction experience, and improved the overall intelligence level of the intelligent cockpit. It belongs to the field of Human–Robot. Stimulating interactive robots with human–robot communication capabilities has effectively become an area of active research in the last two decades [1]. Voice communication is one of the main interaction methods to convey information between human and robots, so robots with human-like voice communication capabilities can provide better services. Natural voice commands do not fully convey precise information, and human sometimes prefer uncertain terms, symbols, and concepts [2]
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