Objective quantification method for subjective evaluation of warning property of automobile warning tone

Abstract

The invention belongs to the technical field of finished automobile information and entertainment systems, and relates to an objective quantification method for subjective evaluation of a warning property of an automobile warning tone. The method includes the steps that a multiple linear regression model is established, a subjective evaluation performance value is taken as a dependent variable, an acoustic parameter value is taken as an independent variable, the model is alpha = a * L + b * Sh + c * F + d, and in the formula, alpha is the subjective evaluation performance value; l is the loudness, Sh is the sharpness, and F is the frequency of the sounding interval, and a, b, c and d are undetermined coefficients; regression analysis is performed by adopting a step-by-step method; independent variable selection is performed according to a rule that a variable with a P value of less than or equal to 0.050 enters and a variable with a P value of more than or equal to 0.100 is shifted out according to an F test; acoustic parameter values are input into a formula for subjective evaluation performance value calculation, and when the prediction error of the subjective evaluation performance value is within 10%, it is considered that the multiple linear regression model has the effect of predicting a subjective evaluation result through automobile prompt tone objective test data. The influence of human factors on the evaluation result is reduced, the discreteness of the evaluation result is reduced, the evaluation efficiency is improved, and the authority of evaluation is increased.

Description

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AI Technical Summary

Benefits of technology

In this patented technology, there are two ways we use objectively evaluate how well these sounds were made during car accidents: one way was done manually or through trial runs with different levels of difficulty (like trying out loudspeakers). Another approach involves creating models based upon both subjective evaluations obtained from previous tests and objective values like speed limit signs. These methods help predict when they will occur more effectively than just relying solely on their own performance level.

Problems solved by technology

The technical problem addressed by these inventors relates to improving the assessments made during electronic cars without compromise being overlooked. Current methods involve subjectively measuring the impact caused by airborne noises while ignoring other sources like background music. However, current methods have limitations including requiring subjects to train themselves accurately beforehand accounting for environmental effects, making them difficult to interpret responses even if they were correctly identified. Additionally, previous methods require subjectivity judges who may lack confidence in judgment standards leading to imprecision in estimative calculations.

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