# Intelligent Automobile Bionic Cockpit Selection Considering Personalization Requirements: Multiple-Criterion Model and Decision-Making Method

## TL;DR

This paper introduces a new decision-making method to help select personalized smart car cockpits based on comfort, safety, and entertainment needs.

## Contribution

A novel decision-making approach combining entropy measure and ELECTRE with Spherical Fuzzy Sets for intelligent cockpit selection.

## Key findings

- The proposed method effectively addresses cockpit selection challenges with multiple personalization criteria.
- Sensitivity analysis confirmed the robustness of the decision-making model.
- The approach provides practical insights for designers of intelligent automobile cockpits.

## Abstract

The extensive integration of intelligent and bionic technologies in the automotive industry has significantly heightened interest in the advancement of smart vehicle cockpits. The growing demand for automobile cockpit functions makes the personalization of intelligent automobile bionic cockpits more challenging. In addition, the evaluation and selection for cockpits considering multiple attributes remains incomplete, which hinders the development of intelligent automobile bionic cockpits. Thus, this paper constructed a multiple criterion model considering the personalization needs of drivers and passengers, which include comfort, security, and spiritual entertainment needs. A novel decision-making approach that merges the entropy measure and the Elimination and Choice Expressing Reality (ELECTRE) method is introduced to address the selection challenges of smart vehicle cockpits. This methodology incorporates the Spherical Fuzzy Set (SFS) to accurately gather and interpret the data within the decision matrix. This study employs a practical application by examining three types of intelligent automobile cockpits to validate the effectiveness of the proposed decision-making method. Through sensitivity analysis and comprehensive validation, the findings substantiate that the research offers a potent instrument for addressing the selection challenges associated with intelligent automobile cockpits, providing valuable insights for designers.