Design of Proactive Interaction for In-Vehicle Robots Based on Transparency
Jianmin Wang, Tianyang Yue, Yujia Liu, Yuxi Wang, Chengji Wang, Fei Yan, Fang You
Tongji University Nanchang University Universität Ulm
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摘要与影响
Based on the transparency theory, this study investigates the appropriate amount of transparency information expressed by the in-vehicle robot under two channels of voice and visual in a proactive interaction scenario. The experiments are to test and evaluate different transparency levels and combinations of information in different channels of the in-vehicle robot, based on a driving simulator to collect subjective and objective data, which focuses on users' safety, usability, trust, and emotion dimensions under driving conditions. The results show that appropriate transparency expression is able to improve drivers' driving control and subjective evaluation and that drivers need a different amount of transparency information in different types of tasks.
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学科主题
社会科学Human-Automation Interaction and Safety
Autonomous Vehicle Technology and Safety · Traffic and Road Safety
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