Art and Design, Vol. 6, Issue 1, Mar  2023, Pages 30-38; DOI: https://doi.org/10.31058/j.ad.2023.61004 https://doi.org/10.31058/j.ad.2023.61004

Design of Automatic Parking Interactive Interface Based on Human-machine Trust

Art and Design, Vol. 6, Issue 1, Mar  2023, Pages 30-38.

DOI: https://doi.org/10.31058/j.ad.2023.61004

Jinjun Xia 1 , Jinna Men 1* , Zixuan Wang 1 , Yanfan Zheng 1

1 Chongqing University, Chongqing, China

Received: 3 December 2022; Accepted: 24 December 2022; Published: 7 January 2023

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Abstract

As technologies marked by big data, artificial intelligence and cloud computing drive autonomous driving in the direction of intelligence, autonomy and collaboration, the trust issue has become one of the biggest challenges for the promotion and application of autonomous driving. from the perspective of interactive interface design, we explore the design strategy of automotive human-machine interactive interface for automatic driving trust problem. Through the analysis of automated trust theory and the theoretical study of system transparency principle, the interactive interface design strategy based on SAT model is proposed, and it is verified by design practice.

Keywords

Autonomous Driving System, Trust, Design Strategy, SAT Model, Interface Design

Copyright

© 2017 by the authors. Licensee International Technology and Science Press Limited. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

References

[1] Chiou, E.K.; Lee, J.D. Trusting automation: Designing for responsivity and resilience. Hum Factors, 2021: 00187208211009995.

[2] Lee, J.D.; See, K.A. Trust in automation: Designing for appropriate reliance. Hum Factors, 2004, 46(1), 50-80.

[3] Zhuo, Z.N. HMI design method for the trust problem of autonmous vehicles . Design, 2020, 33(03), 50-3.

[4] Bobko, P.; Hirshfield, L.; Eloy, L. et al. Human-agent teaming and trust calibration: a theoretical framework, configurable testbed, empirical illustration, and implications for the development of adaptive systems. Theor Iss Ergon Sci, 2022; pp. 1-25.

[5] Sanneman, L.; Shah, J.A. The Situation Awareness Framework for Explainable AI (SAFE-AI) and Human Factors Considerations for XAI Systems. Int J Hum Comput Interact, 2022; pp. 1-17.

[6] Chen, J.Y.C.; Lakhmani, S.G.; Stowers, K.et al. Situation awareness-based agent transparency and human-autonomy teaming effectiveness. Theor Iss Ergon Sci, 2018, 19(3), 259-82.

[7] Selkowitz, A.R.; Lakhmani, S.G.; Chen, J.Y.C. Using agent transparency to support situation awareness of the Autonomous Squad Member. Cogn Syst Res, 2017, 46, 13-25.

[8] You, F.; Deng, H.J.; Hansen, P.et al. Research on Transparency Design Based on Shared Situation Awareness in Semi-Automatic Driving. Appl Sci, 2022, 12(14).

[9] Roth Gunar, Schulte Axel, Schmitt Fabian, et al. Transparency for a Workload-Adaptive Cognitive Agent in a Manned–Unmanned Teaming Application. IEEE T Hum-Mach Syst, 2020, 50(3), 225-33.

[10] Schmitt, F.; Roth, G.; Barber, D. et al. Experimental Validation of Pilot Situation Awareness Enhancement Through Transparency Design of a Scalable Mixed-Initiative Mission Planner; proceedings of the Intelligent Human Systems Integration, F, 2018.

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