Research on the Subjective and Objective Evaluation Strategy of the Intelligent Vehicle Cockpit Based on the User Experience

Xue Zheng; Li Yang; Jingchun Gao

doi:10.62051/ijgem.v4n1.74

Authors

Xue Zheng
Li Yang
Jingchun Gao

DOI:

https://doi.org/10.62051/ijgem.v4n1.74

Keywords:

Visual cognition, Brain cognition, Subjective and objective evaluation, Intelligent cockpit

Abstract

The trend of intelligent networking in automobile industry is developing in full swing, with more and more functions. But feature richness does not necessarily reflect user needs. In order to perfect the evaluation system in the field of automobile intelligent cockpit, this paper constructs the subjective and objective evaluation strategy and tests the function of automobile intelligent cockpit. By building evaluation strategy, standardizing the tester, testing process pole test dimension, combining with subjective evaluation and eye movement, EEG device objective data, clear model and algorithm. Finally, the feasibility of the modified strategy is verified by a practical case.

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References

[1] Production and sales of the automobile industry in 2022 [EB / OL]. http://www.caam.org.cn/chn/4/cate_30/con_5236639.html

[2] Li Yong, Hao Ruimin, Lin Xiaopeng. Research on human-vehicle interaction design from the perspective of user experience [J]. Journal of Fine Arts, 2022 (06): 132-138.

[3] Zhaohui Huang, Xiemin Huang. A study on the application of voice interaction in automotive human machine interface experience design. AIP Conference Proceedings 18 April 2018; 1955 (1): 040074.

[4] Pfannmüller L, Kramer M, Senner B, et al. A comparison of display concepts for a navigation system in an automotive contact analog head-up display [J]. Procedia Manufacturing, 2015, 3: 2722-2729.

[5] Sc Human-computer Interaction dt G J, Rittger L. Guiding driver visual attention with LEDs[C]//Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 2017: 279-286.

[6] Tan Hao, Zhao Jianghong, Wang Wei. Automotive human-computer interaction interface design study [J]. Journal of Automotive Engineering, 2012, 2 (05): 315-321.

[7] Valli, Alessandro. The design of natural interaction [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2008, 38(3):295-305.

[8] Wang Rui, Dong Shiyu, and Xiao Jianghao. Human-computer Natural Interaction Study for Intelligent Vehicle Interface Design [J]. Mechanical design, 2019, 36 (02): 132-136.

[9] Xie Wei, Xin Xiangyang, Hu Weifeng. Current status of implicit measurement methods in product design [J]. Mechanical design, 2015, 32 (02): 105-110.

[10] Wang Yahui. Study on the cognitive mechanism and evaluation method of human-computer interaction in intelligent vehicle cockpit [D]. Northwestern Polytechnical University, 2019.

[11] Norman, D.A. (2002). Emotion and design: Attractive things work better. Interactions, 9(4), 36-42.

[12] Sutton, S., Braren, M., Zubin, J., & John, E.R. (1965). Evoked-potential correlates of stimulus uncertainty. Science, 150(3693), 1187-11.