AR-HUD fuzzy comprehensive evaluation method based on subjective and objective combination weighting method and computer equipment

By using subjective and objective combination empowerment method and fuzzy algorithm in the AR-HUD system, the problem of lack of objective weight analysis in the existing technology is solved, and a more intuitive and accurate AR-HUD system evaluation is achieved.

CN119648017APending Publication Date: 2025-03-18GUANGZHOU AUTOMIBILE GRP MOTOR
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Patent Information

Application Number
CN202411477989.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-22
Publication Date
2025-03-18

AI Technical Summary

Technical Problem

The lack of objective weight analysis of the AR-HUD system in the prior art has led to the inability to intuitively reflect the advantages and disadvantages of the system.

Method used

The AR-HUD fuzzy comprehensive evaluation method based on subjective and objective combination empowerment method is used to calculate the comprehensive weight of each index through hierarchical analysis method and entropy weight method, and the fuzzy algorithm is used to perform weighted average to determine the final evaluation result.

Benefits of technology

This method can comprehensively consider subjective weights and objective weights, and the results are intuitive, and can more accurately reflect the advantages and disadvantages of the AR-HUD system, overcoming the problems of improving accuracy and unintuitive evaluation results in the prior art.

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Abstract

The invention relates to the technical field of automobile intelligent cabin function evaluation, in particular to an AR-HUD fuzzy comprehensive evaluation method based on a subjective and objective combination weighting method and computer equipment, and the method comprises the steps: S100, building an AR-HUD index evaluation system, and formulating a grading standard for each index; s200, designing an AR-HUD road evaluation scheme, performing an AR-HUD road evaluation test, and obtaining an index result of the AR-HUD index evaluation system in the step S100 according to an AR-HUD road evaluation test result and the optical parameters; s300, determining a subjective weight of each index in the step S200 based on an analytic hierarchy process, determining an objective weight of each index in the step S200 based on an entropy weight method, and obtaining a combined weight of the indexes by adopting a geometric averaging method; and S400, determining a final evaluation result of the evaluation object by adopting a weighted average principle based on a fuzzy algorithm according to the combined weight of the indexes in the step S300. The subjective weight and the objective weight in the evaluation system are comprehensively considered, and the evaluation result can visually reflect the advantages and disadvantages of the AR-HUD system.
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