Design of Proactive Interaction for In-Vehicle Robots Based on Transparency.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

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.

Authors

  • Jianmin Wang
  • Tianyang Yue
    Car Interaction Design Lab, College of Arts and Media, Tongji University, Shanghai 201804, China.
  • Yujia Liu
    The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
  • Yuxi Wang
    Department of Pulmonary and Critical Care Medicine, Targeted Tracer Research and Development Laboratory, Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China; Frontiers Medical Center, Tianfu Jincheng Laboratory, Chengdu, 610093, Sichuan, China. Electronic address: yuxiwang@scu.edu.cn.
  • Chengji Wang
    Car Interaction Design Lab, College of Arts and Media, Tongji University, Shanghai 201804, China.
  • Fei Yan
    Department of Infectious Diseases, Affiliated Taizhou Hospital of Wenzhou Medical University, No.50 Ximeng Road, Taizhou, 317000, China.
  • Fang You
    Car Interaction Design Lab, College of Arts and Media, Tongji University, Shanghai 201804, China.