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Intelligent Automobile Bionic Cockpit Selection Considering Personalization Requirements: Multiple-Criterion Model

Liangliang Shi1, Shaolin Zhang2,3, Tao Han2,3

  • 1State Key Laboratory of Intelligent Vehicle Safety Technology, China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China.

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Summary

This study introduces a new decision-making model for selecting smart vehicle cockpits, considering driver comfort, security, and entertainment needs. The method effectively addresses complex multi-attribute selection challenges in automotive cockpit design.

Keywords:
decision-makingentropy measureintelligent automobile bionic cockpits selectionspherical fuzzy set

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Area of Science:

  • Automotive Engineering
  • Decision Science
  • Human-Computer Interaction

Background:

  • The automotive industry is rapidly integrating intelligent and bionic technologies, increasing demand for advanced smart vehicle cockpits.
  • Personalization of intelligent cockpits presents challenges due to diverse user needs and incomplete multi-attribute evaluation methods.
  • Existing selection processes hinder the development of sophisticated and user-centric intelligent automobile bionic cockpits.

Purpose of the Study:

  • To develop a multi-criterion decision-making model for intelligent automobile bionic cockpits.
  • To address the personalization needs of drivers and passengers, including comfort, security, and spiritual entertainment.
  • To introduce a novel decision-making approach for selecting smart vehicle cockpits.

Main Methods:

  • Construction of a multi-criterion model incorporating driver and passenger personalization needs.
  • Integration of the entropy measure with the Elimination and Choice Expressing Reality (ELECTRE) method for decision-making.
  • Utilization of Spherical Fuzzy Sets (SFS) for accurate data interpretation in the decision matrix.

Main Results:

  • A novel decision-making approach combining entropy and ELECTRE methods within a Spherical Fuzzy Set framework was developed.
  • The proposed methodology was validated through a practical application involving the evaluation of three intelligent automobile cockpit types.
  • Sensitivity analysis confirmed the robustness and effectiveness of the decision-making approach.

Conclusions:

  • The developed decision-making method provides a potent tool for selecting intelligent automobile cockpits.
  • The research offers valuable insights for designers aiming to enhance smart vehicle cockpit development.
  • The study successfully addresses the complexities of multi-attribute selection for personalized intelligent automotive cockpits.