Automobile cabin user experience evaluation method and system based on digital interconnection

Abstract

The invention discloses an automobile cabin user experience evaluation method and system based on digital interconnection, and relates to the field of information processing, and the method comprises the steps: constructing an automobile cabin comfort evaluation index system; designing an automobile cabin user comfort single-factor test under typical working conditions of static, constant speed and acceleration of an automobile, wherein noise, illumination, temperature and intelligent degree are typical; carrying out dimensionless operation; performing calculation through an analytic hierarchy process to obtain subjective weights of the evaluation indexes; using an entropy weight method to calculate an objective weight of the automobile cabin comfort; synthesizing subjective and objective weights by using a game theory method; and obtaining an automobile cabin comfort comprehensive evaluation model by using a multiplication synthesis method. By arranging an evaluation system construction module, a user experience evaluation module, a secondary index calculation module, a primary index calculation module and an evaluation model construction module, the comfort of the intelligent cabin is researched from the aspects of a cabin sound environment, a light environment, a thermal environment and a man-machine interaction environment.

Description

Technical Field

[0001] The present invention relates to the field of information processing, and in particular to a method and system for evaluating user experience in a car cockpit based on digital interconnection. Background Art

[0002] Entering the 21st century, modern cars are no longer a single mechanical product, but a multi-disciplinary and multi-category product collection. Computers, new materials, software and control technologies are intensively applied to cars, and cars are becoming more and more intelligent. The original purpose of car intelligence was to reduce traffic accidents and ensure vehicle safety. In recent years, people have higher and higher requirements for car comfort. With the advancement of automobile technology, the direction of automobile performance evaluation is also changing. From the early days of mainly conducting evaluations of automobile power, economy, vibration and noise, to the use of simulation technology for engine thermal management, automobile collision and safety evaluation, and then entering the current stage of people-oriented automobile comfort evaluation.

[0003] Automobile comfort has become a standard for evaluating the quality of smart vehicles, and directly affects people's acceptance, trust and willingness to buy smart cars. Improving comfort can help popularize smart vehicles. The research results of evaluation methods are an important means to guide the progress of automobile design. The development of automobile technology is inseparable from the progress and improvement of evaluation and analysis methods. Therefore, it is of great significance to carry out automobile cockpit comfort evaluation. At present, the research on automobile comfort mainly focuses on objective physical parameters such as vibration, space, temperature, etc., while there are few special comfort studies on cockpits. With the development of smart cockpits in recent years, it is increasingly important to carry out occupant comfort research for smart cockpits. Summary of the invention

[0004] In order to solve the above technical problems, a method and system for evaluating the user experience of a car cockpit based on digital interconnection are provided. This technical solution solves the problems raised in the above background technology.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for evaluating the user experience of a car cockpit based on digital interconnection, comprising:

[0007] Using the principle of hierarchical analysis method, a vehicle cabin comfort evaluation index system is constructed from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment;

[0008] Combined with the evaluation index system of automobile cabin comfort, a single factor test of automobile cabin user comfort is designed under typical working conditions of stationary, constant speed and acceleration of automobiles, with noise, illumination, temperature and intelligence level as typical factors.

[0009] Based on the experimental research results based on single factors, the value level and comfort relationship of each evaluation factor in the comprehensive comfort evaluation index system are dimensionless by using the efficacy coefficient method, and a single factor evaluation model of automobile cabin comfort is obtained by synthesis.

[0010] The subjective weights of evaluation indicators were calculated by questionnaire survey and analytic hierarchy process.

[0011] Combined with expert evaluation, based on the impact of the boundary value of the evaluation index, the entropy weight method is used to calculate the objective weight of the car cabin comfort;

[0012] The subjective and objective weights are synthesized using the game theory method to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of the vehicle cabin comfort.

[0013] Combined with the weights of the vehicle cabin comfort evaluation indexes, the comprehensive evaluation model of vehicle cabin comfort is obtained using the multiplication synthesis method.

[0014] Preferably, the use of the principle of hierarchical analysis method to construct an automobile cabin comfort evaluation index system from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment specifically includes:

[0015] The first-level indicators of the automobile cabin comfort evaluation index system are noise and vibration environment, light environment, thermal environment, and human-computer interaction environment indicators;

[0016] Under the noise and vibration environment index, there are three secondary indicators: noise loudness level, noise frequency level, and cabin vibration frequency;

[0017] Under the light environment index, there are three secondary indicators: color temperature of the light in the cabin, illumination in the cabin, and brightness;

[0018] Under the thermal environment index, there are four secondary indicators: temperature, humidity, pressure and wind speed in the cabin;

[0019] Under the human-computer interaction environment index, there are seven secondary indicators: the influence of cabin space and instrument interior, entertainment technology, equipment output response and reliability, seat system comfort, driving operation ergonomics, cabin personalization and emotional care application.

[0020] Preferably, the single-factor based experimental research results are used as a basis, and the value level and comfort relationship of each evaluation index in the comprehensive comfort evaluation index system are dimensionless by using the efficacy coefficient method, and the single-factor evaluation model of automobile cabin comfort obtained by synthesis specifically includes:

[0021] Obtain the results of single-factor test on the comfort of the vehicle cabin users under typical working conditions of the vehicle at rest, at a constant speed and at acceleration, with noise, illumination, temperature and intelligence as typical examples;

[0022] The test results were dimensionless processed using the efficacy coefficient formula, and the evaluation values ​​of each secondary evaluation index were calculated;

[0023] Based on the principle of segmented synthesis, the evaluation values ​​of each secondary evaluation index are synthesized into the evaluation value of the corresponding primary evaluation index;

[0024] Determine whether there is an indicator greater than the first preset threshold value among the individual indicators. If so, output the maximum evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator. If not, no output is made.

[0025] Determine whether there is an indicator less than the second preset threshold value among the individual indicators. If so, output the minimum evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator. If not, output the average evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator.

[0026] The efficacy coefficient formula is:

[0027]

[0028] In the formula, k i is the evaluation value of the i-th secondary evaluation index, x i is the test value of the i-th secondary evaluation index, x imax is the theoretical maximum value of the i-th secondary evaluation index, x imin is the theoretical minimum value of the i-th secondary evaluation index.

[0029] Preferably, the method of using a questionnaire survey to calculate the subjective weights of the evaluation indicators by means of a hierarchical analysis method specifically includes:

[0030] A questionnaire survey was conducted to obtain the average values ​​of the impact of each first-level evaluation index on the comfort of the vehicle cabin user;

[0031] Construct a judgment matrix through analytic hierarchy process;

[0032] The judgment matrix is ​​normalized by using the normalization formula to obtain a normalized judgment matrix;

[0033] Add the columns of the same row of the normalized judgment matrix and divide it by the total number of first-level evaluation indicators to obtain the subjective weight of each first-level evaluation indicator;

[0034] The judgment matrix is:

[0035]

[0036] In the formula, A1 is the judgment matrix, b ijis the ratio of the average value of the influence of the i-th first-level evaluation index on the comfort of the automobile cabin user to the average value of the influence of the j-th first-level evaluation index on the comfort of the automobile cabin user;

[0037] The normalization formula is:

[0038]

[0039] In the formula, c ij is the data in the i-th row and j-th column of the normalized judgment matrix, b ij is the data in the i-th row and j-th column of the judgment matrix, and n is the total number of primary evaluation indicators.

[0040] Preferably, the method of calculating the objective weight of the comfort of the automobile cabin by using the entropy weight method in combination with the expert evaluation based on the influence of the boundary value of the evaluation index specifically includes:

[0041] Obtain expert evaluations and enter the expert evaluations into an expert evaluation matrix;

[0042] Based on the expert evaluation matrix, calculate the evaluation proportion of each first-level evaluation indicator in the evaluation value of each expert;

[0043] The entropy value formula is used to calculate the evaluation entropy value of each first-level evaluation index;

[0044] Input the evaluation entropy value into the entropy weight method formula to obtain the objective weight of each primary evaluation index;

[0045] The expert evaluation matrix is:

[0046]

[0047] Where A2 is the expert evaluation matrix, d ij is the score of the jth expert on the i-th first-level evaluation index, and m is the total number of experts;

[0048] The evaluation weights are:

[0049]

[0050] In the formula, p ij is the evaluation proportion of the i-th first-level evaluation index in the j-th expert score, k0 is the correction coefficient, which is generally 10 -6 ;

[0051] The entropy value formula is:

[0052]

[0053] In the formula, H i is the entropy value of the i-th first-level evaluation index;

[0054] The entropy weight method formula is:

[0055]

[0056] In the formula, ω i is the objective weight of the i-th first-level evaluation index.

[0057] Preferably, the method of using game theory to synthesize the subjective and objective weights to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of automobile cabin comfort specifically includes:

[0058] Obtain the weights of the evaluation indicators of the intelligent cockpit noise and vibration environment, light environment, thermal environment and human-computer interaction environment calculated by the subjective weight and objective weight methods, and combine them to obtain the weight vectors;

[0059] According to the optimal derivative condition linear equation system obtained by matrix differential properties, the linear combination coefficients of each weight vector are calculated;

[0060] The final weight of each primary evaluation index is calculated using the game theory combined weight formula;

[0061] The weight vector is:

[0062] W i =(ω i ,ω i ′),

[0063] Where W i is the weight vector of the i-th first-level evaluation index, ω i ′ is the subjective weight of the i-th first-level evaluation index;

[0064] The optimal derivative condition linear equation system is:

[0065]

[0066] In the formula, is the transpose of the weight vector of the nth primary evaluation index, α n is the linear combination coefficient of each weight vector;

[0067] The game theory combined weight formula is:

[0068]

[0069] Where W i ′ is the final weight of the i-th primary evaluation index.

[0070] Furthermore, a digitally interconnected automobile cockpit user experience evaluation system is proposed, which is used to implement the digitally interconnected automobile cockpit user experience evaluation method as described above, including:

[0071] An evaluation system construction module, wherein the evaluation system construction module is used to construct an automobile cabin comfort evaluation index system from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment by using the principle of hierarchical analysis method;

[0072] A user experience evaluation module, which is used to design a single factor test of user comfort in the automobile cabin under typical working conditions of a stationary, uniform speed and accelerated automobile, with noise, illumination, temperature and intelligence level as typical factors, in combination with the automobile cabin comfort evaluation index system;

[0073] A secondary index calculation module, which is used to non-dimensionalize the value level and comfort relationship of each evaluation factor in the comprehensive comfort evaluation index system based on the experimental research results based on a single factor, and synthesize a single factor evaluation model of automobile cabin comfort;

[0074] A primary indicator calculation module, wherein the primary indicator calculation module is used to calculate the subjective weights of the evaluation indicators by means of a questionnaire survey through a hierarchical analysis method, calculate the objective weights of the vehicle cabin comfort by using an entropy weight method based on the influence of the boundary value of the evaluation indicators in combination with expert evaluation, and synthesize the subjective and objective weights by using a game theory method to obtain the final weights of each primary evaluation indicator of the comprehensive evaluation index of the vehicle cabin comfort;

[0075] The evaluation model building module is used to combine the weights of the automobile cabin comfort evaluation index and use the multiplication synthesis method to obtain a comprehensive evaluation model of the automobile cabin comfort.

[0076] Optionally, the first-level indicator calculation module specifically includes:

[0077] A subjective weight calculation unit, wherein the subjective weight calculation unit is used to calculate the subjective weight of the evaluation index by using a questionnaire survey and a hierarchical analysis method;

[0078] An objective weight calculation unit, the objective weight calculation unit is used to calculate the objective weight of the vehicle cabin comfort by using an entropy weight method based on the influence of the boundary value of the evaluation index in combination with the expert evaluation;

[0079] The final weight calculation unit is used to synthesize the subjective and objective weights by using the game theory method to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of the automobile cabin comfort.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] By setting up an evaluation system construction module and a user experience evaluation module, the intelligent cockpit of the car is taken as the research object and the car occupant experience is used as the basis. The comfort of the intelligent cockpit is studied from the perspectives of the cockpit sound environment, light environment, thermal environment and human-computer interaction environment. Based on the test data and the subjective and objective comprehensive weighting method, a comprehensive evaluation model for cabin comfort is obtained, which provides suggestions for improving and optimizing the comprehensive comfort of the intelligent cockpit of the car. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 This is a flow chart of the method for evaluating the user experience of a digitally interconnected automobile cockpit according to the present invention;

[0083] Figure 2 A flow chart of a method for constructing an automobile cabin comfort evaluation index system according to the present invention;

[0084] Figure 3 is a flow chart of the dimensionless method of the present invention;

[0085] Figure 4 A flow chart of a method for calculating subjective weights of evaluation indicators using the analytic hierarchy process of the present invention;

[0086] Figure 5 This is a flow chart of a method for calculating the objective weight of automobile cabin comfort using the entropy weight method of the present invention;

[0087] Figure 6 This is a flow chart of the method for synthesizing subjective and objective weights using the game theory method of the present invention. DETAILED DESCRIPTION

[0088] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0089] Reference Figure 1 As shown, a method for evaluating the user experience of a car cockpit based on digital interconnection includes:

[0090] Using the principle of hierarchical analysis method, a vehicle cabin comfort evaluation index system is constructed from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment;

[0091] Combined with the evaluation index system of automobile cabin comfort, a single factor test of automobile cabin user comfort is designed under typical working conditions of stationary, constant speed and acceleration of automobiles, with noise, illumination, temperature and intelligence level as typical factors.

[0092] Based on the experimental research results based on single factors, the value level and comfort relationship of each evaluation factor in the comprehensive comfort evaluation index system are dimensionless by using the efficacy coefficient method, and a single factor evaluation model of automobile cabin comfort is obtained by synthesis.

[0093] The subjective weights of evaluation indicators were calculated by questionnaire survey and analytic hierarchy process.

[0094] Combined with expert evaluation, based on the impact of the boundary value of the evaluation index, the entropy weight method is used to calculate the objective weight of the car cabin comfort;

[0095] The subjective and objective weights are synthesized using the game theory method to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of the vehicle cabin comfort.

[0096] Combined with the weights of the vehicle cabin comfort evaluation indexes, the comprehensive evaluation model of vehicle cabin comfort is obtained using the multiplication synthesis method.

[0097] Reference Figure 2 As shown in the figure, using the principle of hierarchical analysis method, from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment, the automobile cabin comfort evaluation index system is constructed, which specifically includes:

[0098] The first-level indicators of the automobile cabin comfort evaluation index system are noise and vibration environment, light environment, thermal environment, and human-computer interaction environment indicators;

[0099] Under the noise and vibration environment index, there are three secondary indicators: noise loudness level, noise frequency level, and cabin vibration frequency;

[0100] Under the light environment index, there are three secondary indicators: color temperature of the light in the cabin, illumination in the cabin, and brightness;

[0101] Under the thermal environment index, there are four secondary indicators: temperature, humidity, pressure and wind speed in the cabin;

[0102] Under the human-computer interaction environment index, there are seven secondary indicators: the influence of cabin space and instrument interior, entertainment technology, equipment output response and reliability, seat system comfort, driving operation ergonomics, cabin personalization and emotional care application.

[0103] The comfort evaluation index system of automobile intelligent cockpit is a top-down, internally logically related and indivisible system. The index selection is based on the principle of integrity and simplicity, and pays special attention to maintaining the consistency of the overall scope. The measurement and comparative calculation methods of index selection must be unified. On the basis of the hierarchical principle, the index layer is constructed in a top-down manner, and the related indicators that are closely related to the evaluation of comfort are classified into one category to construct the corresponding indicator group.

[0104] Reference Figure 3As shown in the figure, based on the experimental research results based on single factors, the value level and comfort relationship of each evaluation index in the comprehensive comfort evaluation index system are dimensionless by using the efficacy coefficient method, and the single factor evaluation model of automobile cabin comfort is synthesized, which specifically includes:

[0105] Obtain the results of single-factor test on the comfort of the vehicle cabin users under typical working conditions of the vehicle at rest, at a constant speed and at acceleration, with noise, illumination, temperature and intelligence as typical examples;

[0106] The test results were dimensionless processed using the efficacy coefficient formula, and the evaluation values ​​of each secondary evaluation index were calculated;

[0107] Based on the principle of segmented synthesis, the evaluation values ​​of each secondary evaluation index are synthesized into the evaluation value of the corresponding primary evaluation index;

[0108] Determine whether there is an indicator greater than the first preset threshold value among the individual indicators. If so, output the maximum evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator. If not, no output is made.

[0109] Determine whether there is an indicator less than the second preset threshold value among the individual indicators. If so, output the minimum evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator. If not, output the average evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator.

[0110] The efficacy coefficient formula is:

[0111]

[0112] In the formula, k i is the evaluation value of the i-th secondary evaluation index, x i is the test value of the i-th secondary evaluation index, x imax is the theoretical maximum value of the i-th secondary evaluation index, x imin is the theoretical minimum value of the i-th secondary evaluation index.

[0113] The efficacy coefficient method converts the original value of the evaluation factor into a dimensionless evaluation value between 40 and 100, where 40 represents dissatisfaction and 100 represents complete satisfaction.

[0114] Reference Figure 4 As shown in the figure, the subjective weights of the evaluation indicators are calculated by questionnaire survey and analytic hierarchy process, including:

[0115] A questionnaire survey was conducted to obtain the average values ​​of the impact of each first-level evaluation index on the comfort of the vehicle cabin user;

[0116] Construct a judgment matrix through analytic hierarchy process;

[0117] The judgment matrix is ​​normalized by using the normalization formula to obtain a normalized judgment matrix;

[0118] Add the columns of the same row of the normalized judgment matrix and divide it by the total number of first-level evaluation indicators to obtain the subjective weight of each first-level evaluation indicator;

[0119] The judgment matrix is:

[0120]

[0121] In the formula, A1 is the judgment matrix, b ij is the ratio of the average value of the influence of the i-th first-level evaluation index on the comfort of the automobile cabin user to the average value of the influence of the j-th first-level evaluation index on the comfort of the automobile cabin user;

[0122] The normalization formula is:

[0123]

[0124] In the formula, c ij is the data in the i-th row and j-th column of the normalized judgment matrix, b ij is the data in the i-th row and j-th column of the judgment matrix, and n is the total number of primary evaluation indicators.

[0125] In the hierarchical analysis method, when an upper-level element is affected by multiple lower-level elements, it is generally difficult to define the degree of influence of the lower-level elements on the upper-level elements. The more commonly used method is to take two lower-level elements at a time and compare them with each other. By comparing the relative importance or priority between two elements, it is easy to get the relative importance of each element.

[0126] Reference Figure 5 As shown in the figure, combined with expert evaluation, based on the impact of the boundary value of the evaluation index, the entropy weight method is used to calculate the objective weight of the car cabin comfort, which includes:

[0127] Obtain expert evaluations and enter the expert evaluations into an expert evaluation matrix;

[0128] Based on the expert evaluation matrix, calculate the evaluation proportion of each first-level evaluation indicator in the evaluation value of each expert;

[0129] The entropy value formula is used to calculate the evaluation entropy value of each first-level evaluation index;

[0130] Input the evaluation entropy value into the entropy weight method formula to obtain the objective weight of each primary evaluation index;

[0131] The expert evaluation matrix is:

[0132]

[0133] Where A2 is the expert evaluation matrix, d ij is the score of the jth expert on the i-th first-level evaluation index, and m is the total number of experts;

[0134] The evaluation weights are:

[0135]

[0136] In the formula, p ij is the evaluation proportion of the i-th first-level evaluation index in the j-th expert score, k0 is the correction coefficient, which is generally 10 -6 ;

[0137] The entropy value formula is:

[0138]

[0139] In the formula, H i is the entropy value of the i-th first-level evaluation index;

[0140] The entropy weight method formula is:

[0141]

[0142] In the formula, ω i is the objective weight of the i-th first-level evaluation index.

[0143] When applying the entropy weight method to conduct a comprehensive evaluation of the comfort of an intelligent cockpit, if there are too many evaluation indicators or evaluation angles to choose from, the evaluation experts may believe that a certain indicator has little or no effect on the comprehensive comfort, which will cause the calculation formula to lose its practical significance. If the entropy values ​​of the intelligent cockpit comfort evaluation indicators tend to 1, the slight difference between the entropy values ​​may cause a huge change in the final result of the entropy value, resulting in inaccurate evaluation results. Therefore, a correction factor is introduced.

[0144] Reference Figure 6 As shown in the figure, the subjective and objective weights are synthesized by using the game theory method, and the final weights of each primary evaluation index of the comprehensive evaluation index of automobile cabin comfort are obtained, which specifically include:

[0145] Obtain the weights of the evaluation indicators of the intelligent cockpit noise and vibration environment, light environment, thermal environment and human-computer interaction environment calculated by the subjective weight and objective weight methods, and combine them to obtain the weight vectors;

[0146] According to the optimal derivative condition linear equation system obtained by matrix differential properties, the linear combination coefficients of each weight vector are calculated;

[0147] The final weight of each primary evaluation index is calculated using the game theory combined weight formula;

[0148] The weight vector is:

[0149] W i =(ω i ,ω i ′),

[0150] Where W i is the weight vector of the i-th first-level evaluation index, ω i ′ is the subjective weight of the i-th first-level evaluation index;

[0151] The optimal derivative condition linear equation system is:

[0152]

[0153] Where W n T is the transpose of the weight vector of the nth primary evaluation index, α n is the linear combination coefficient of each weight vector;

[0154] The game theory combined weight formula is:

[0155]

[0156] Where W i ' is the final weight of the i-th first-level evaluation index.

[0157] After calculating the subjective and objective weights of the sound environment, light environment, thermal environment and human-computer interaction environment, the subjective and objective weights need to be allocated. Since the subjective and objective factors are symbiotic and relative to each other in the cockpit comfort indicators, we cannot only consider one aspect of the subjective and objective weights and lose sight of the other, nor can we simply allocate them equally. Therefore, the allocation based on subjective and objective weights can be optimized according to the idea of ​​game theory.

[0158] Furthermore, based on the same inventive concept as the above-mentioned digitally interconnected automobile cockpit user experience evaluation method, the present solution also proposes a digitally interconnected automobile cockpit user experience evaluation system, comprising:

[0159] An evaluation system construction module, wherein the evaluation system construction module is used to construct an automobile cabin comfort evaluation index system from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment by using the principle of hierarchical analysis method;

[0160] A user experience evaluation module, which is used to design a single factor test of user comfort in the automobile cabin under typical working conditions of a stationary, uniform speed and accelerated automobile, with noise, illumination, temperature and intelligence level as typical factors, in combination with the automobile cabin comfort evaluation index system;

[0161] A secondary index calculation module, which is used to non-dimensionalize the value level and comfort relationship of each evaluation factor in the comprehensive comfort evaluation index system based on the experimental research results based on a single factor, and synthesize a single factor evaluation model of automobile cabin comfort;

[0162] A primary indicator calculation module, wherein the primary indicator calculation module is used to calculate the subjective weights of the evaluation indicators by means of a questionnaire survey through a hierarchical analysis method, calculate the objective weights of the vehicle cabin comfort by using an entropy weight method based on the influence of the boundary value of the evaluation indicators in combination with expert evaluation, and synthesize the subjective and objective weights by using a game theory method to obtain the final weights of each primary evaluation indicator of the comprehensive evaluation index of the vehicle cabin comfort;

[0163] The evaluation model construction module is used to combine the weights of the automobile cabin comfort evaluation index and use the multiplication synthesis method to obtain a comprehensive evaluation model of the automobile cabin comfort.

[0164] The first-level indicator calculation module specifically includes:

[0165] A subjective weight calculation unit, wherein the subjective weight calculation unit is used to calculate the subjective weight of the evaluation index by using a questionnaire survey and a hierarchical analysis method;

[0166] An objective weight calculation unit, the objective weight calculation unit is used to calculate the objective weight of the vehicle cabin comfort by using an entropy weight method based on the influence of the boundary value of the evaluation index in combination with the expert evaluation;

[0167] The final weight calculation unit is used to synthesize the subjective and objective weights by using the game theory method to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of the automobile cabin comfort.

[0168] Furthermore, the present solution also proposes a computer-readable storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned digital interconnection-based automobile cockpit user experience evaluation method is executed.

[0169] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0170] To sum up, the advantages of the present invention are: by setting up an evaluation system construction module and a user experience evaluation module, the automobile intelligent cockpit is taken as the research object, and the automobile occupant experience is used as the basis, and the intelligent cockpit comfort is studied from the perspectives of the cockpit sound environment, light environment, thermal environment and human-computer interaction environment, and a comprehensive evaluation model for cabin comfort is obtained based on test data and the subjective and objective comprehensive weighting method, so as to provide suggestions for improving and optimizing the comprehensive comfort of the automobile intelligent cockpit.

[0171] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for evaluating the user experience of a car cockpit based on digital interconnection, characterized in that: include: Using the principle of hierarchical analysis method, a vehicle cabin comfort evaluation index system is constructed from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment; Combined with the evaluation index system of automobile cabin comfort, a single factor test of automobile cabin user comfort is designed under typical working conditions of stationary, constant speed and acceleration of automobiles, with noise, illumination, temperature and intelligence level as typical factors. Based on the experimental research results based on single factors, the value level and comfort relationship of each evaluation factor in the comprehensive comfort evaluation index system are dimensionless by using the efficacy coefficient method, and a single factor evaluation model of automobile cabin comfort is obtained by synthesis. The subjective weights of evaluation indicators were calculated by questionnaire survey and analytic hierarchy process. Combined with expert evaluation, based on the impact of the boundary value of the evaluation index, the entropy weight method is used to calculate the objective weight of the car cabin comfort; The subjective and objective weights are synthesized using the game theory method to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of the vehicle cabin comfort. Combined with the weights of the evaluation indexes of automobile cabin comfort, the comprehensive evaluation model of automobile cabin comfort is obtained by using the multiplication synthesis method.

2. The method for evaluating the user experience of a digitally interconnected automobile cockpit according to claim 1, characterized in that: The above-mentioned use of the principle of hierarchical analysis method to construct an automobile cabin comfort evaluation index system from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment specifically includes: The first-level indicators of the automobile cabin comfort evaluation index system are noise and vibration environment, light environment, thermal environment, and human-computer interaction environment indicators; Under the noise and vibration environment index, there are three secondary indicators: noise loudness level, noise frequency level, and cabin vibration frequency; Under the light environment index, there are three secondary indicators: color temperature of the light in the cabin, illumination in the cabin, and brightness; Under the thermal environment index, there are four secondary indicators: temperature, humidity, pressure and wind speed in the cabin; Under the human-computer interaction environment index, there are seven secondary indicators: the influence of cabin space and instrument interior, entertainment technology, equipment output response and reliability, seat system comfort, driving operation ergonomics, cabin personalization and emotional care application.

3. The method for evaluating the user experience of a digitally interconnected automobile cockpit according to claim 2, characterized in that: Based on the experimental research results based on a single factor, the value level and comfort relationship of each evaluation index in the comprehensive comfort evaluation index system are dimensionless by using the efficacy coefficient method, and the single factor evaluation model of automobile cabin comfort is synthesized, which specifically includes: Obtain the results of single-factor test on the comfort of the vehicle cabin users under typical working conditions of the vehicle at rest, at a constant speed and at acceleration, with noise, illumination, temperature and intelligence as typical examples; The test results were dimensionless processed using the efficacy coefficient formula, and the evaluation values ​​of each secondary evaluation index were calculated; Based on the principle of segmented synthesis, the evaluation values ​​of each secondary evaluation index are synthesized into the evaluation value of the corresponding primary evaluation index; Determine whether there is an indicator greater than the first preset threshold value among the individual indicators. If so, output the maximum evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator. If not, no output is made. Determine whether there is an indicator less than the second preset threshold value among the individual indicators. If so, output the minimum evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator. If not, output the average evaluation value of the secondary indicators under the primary evaluation indicator as the evaluation value of the primary evaluation indicator. The efficacy coefficient formula is: In the formula, k i is the evaluation value of the i-th secondary evaluation index, x i is the test value of the i-th secondary evaluation index, x imax is the theoretical maximum value of the i-th secondary evaluation index, x imin is the theoretical minimum value of the i-th secondary evaluation index.

4. The method for evaluating the user experience of a digitally interconnected automobile cockpit according to claim 3, characterized in that: The subjective weights of the evaluation indicators calculated by the analytic hierarchy process using the questionnaire survey specifically include: A questionnaire survey was conducted to obtain the average values ​​of the impact of each first-level evaluation index on the comfort of the vehicle cabin user; Construct a judgment matrix through analytic hierarchy process; The judgment matrix is ​​normalized by using the normalization formula to obtain a normalized judgment matrix; Add the columns of the same row of the normalized judgment matrix and divide it by the total number of first-level evaluation indicators to obtain the subjective weight of each first-level evaluation indicator; The judgment matrix is: In the formula, A1 is the judgment matrix, b ij is the ratio of the average value of the influence of the i-th first-level evaluation index on the comfort of the automobile cabin user to the average value of the influence of the j-th first-level evaluation index on the comfort of the automobile cabin user; The normalization formula is: In the formula, c ij is the data in the i-th row and j-th column of the normalized judgment matrix, b ij is the data in the i-th row and j-th column of the judgment matrix, and n is the total number of primary evaluation indicators.

5. The method for evaluating the user experience of a digitally interconnected automobile cockpit according to claim 4, characterized in that: The above-mentioned combination of expert evaluation and the use of entropy weight method to calculate the objective weight of automobile cabin comfort based on the impact of the boundary value of the evaluation index specifically includes: Obtain expert evaluations and enter the expert evaluations into an expert evaluation matrix; Based on the expert evaluation matrix, calculate the evaluation proportion of each first-level evaluation indicator in the evaluation value of each expert; The entropy value formula is used to calculate the evaluation entropy value of each first-level evaluation index; Input the evaluation entropy value into the entropy weight method formula to obtain the objective weight of each primary evaluation index; The expert evaluation matrix is: Where A2 is the expert evaluation matrix, d ij is the score of the jth expert on the i-th first-level evaluation index, and m is the total number of experts; The evaluation weights are: In the formula, p ij is the evaluation proportion of the i-th first-level evaluation index in the j-th expert score, k0 is the correction coefficient, which is generally 10 -6 ; The entropy value formula is: In the formula, H i is the entropy value of the i-th primary evaluation index; The entropy weight method formula is: In the formula, ω i is the objective weight of the i-th first-level evaluation index.

6. The method for evaluating the user experience of a digitally interconnected automobile cockpit according to claim 5, characterized in that: The method of using game theory to synthesize the subjective and objective weights to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of the automobile cabin comfort specifically includes: Obtain the weights of the evaluation indicators of the intelligent cockpit noise and vibration environment, light environment, thermal environment and human-computer interaction environment calculated by the subjective weight and objective weight methods, and combine them to obtain the weight vectors; According to the optimal derivative condition linear equation system obtained by matrix differential properties, the linear combination coefficients of each weight vector are calculated; The final weight of each primary evaluation index is calculated using the game theory combined weight formula; The weight vector is: W i =(ω i Oh, oh i ′), Where W i is the weight vector of the i-th first-level evaluation index, ω i ′ is the subjective weight of the i-th first-level evaluation index; The optimal derivative condition linear equation system is: In the formula, is the transpose of the weight vector of the nth primary evaluation index, α n is the linear combination coefficient of each weight vector; The game theory combined weight formula is: Where W i ' is the final weight of the i-th first-level evaluation index.

7. A digital interconnection-based automobile cockpit user experience evaluation system, used to implement the digital interconnection-based automobile cockpit user experience evaluation method according to any one of claims 1 to 6, characterized in that: include: An evaluation system construction module, wherein the evaluation system construction module is used to construct an automobile cabin comfort evaluation index system from the perspectives of noise and vibration environment, light environment, thermal environment and human-computer interaction environment by using the principle of hierarchical analysis method; A user experience evaluation module, which is used to design a single factor test of user comfort in the automobile cabin under typical working conditions of a stationary, uniform speed and accelerated automobile, with noise, illumination, temperature and intelligence level as typical factors, in combination with the automobile cabin comfort evaluation index system; A secondary index calculation module, which is used to non-dimensionalize the value level and comfort relationship of each evaluation factor in the comprehensive comfort evaluation index system based on the experimental research results based on a single factor, and synthesize a single factor evaluation model of automobile cabin comfort; A primary indicator calculation module, wherein the primary indicator calculation module is used to calculate the subjective weights of the evaluation indicators by means of a questionnaire survey through a hierarchical analysis method, calculate the objective weights of the vehicle cabin comfort by using an entropy weight method based on the influence of the boundary value of the evaluation indicators in combination with expert evaluation, and synthesize the subjective and objective weights by using a game theory method to obtain the final weights of each primary evaluation indicator of the comprehensive evaluation index of the vehicle cabin comfort; The evaluation model construction module is used to combine the weights of the automobile cabin comfort evaluation index and use the multiplication synthesis method to obtain a comprehensive evaluation model of the automobile cabin comfort.

8. The digital interconnection-based automobile cockpit user experience evaluation system according to claim 7, characterized in that: The first-level indicator calculation module specifically includes: A subjective weight calculation unit, wherein the subjective weight calculation unit is used to calculate the subjective weight of the evaluation index by using a questionnaire survey and a hierarchical analysis method; An objective weight calculation unit, the objective weight calculation unit is used to calculate the objective weight of the vehicle cabin comfort by using an entropy weight method based on the influence of the boundary value of the evaluation index in combination with the expert evaluation; The final weight calculation unit is used to synthesize the subjective and objective weights by using the game theory method to obtain the final weights of each primary evaluation index of the comprehensive evaluation index of the automobile cabin comfort.

Images