A car evaluation method and system based on a multi-dimensional combined sound scene

Abstract

The application relates to the field of automobile evaluation technology and discloses an automobile evaluation method and system based on a multi-dimensional combined sound scene, which comprises the following steps: classifying and processing vehicle external sound environment data according to preset influence factors; establishing a vehicle external sound scene library according to the classified and processed vehicle external sound environment data and according to sound characteristic parameters corresponding to each multi-dimensional combined vehicle external sound scene; determining a target sound scene from the vehicle external sound scene library according to a target evaluation requirement and reconstructing a vehicle external sound environment based on sound characteristic parameters corresponding to the target sound scene; placing a vehicle to be tested in a simulated vehicle external sound environment to obtain functional response data of the vehicle to be tested under the target sound scene; establishing a correlation between the vehicle external sound scene and the functional performance of the vehicle; and evaluating the acoustic performance of the vehicle to be tested based on the correlation. The application can improve the authenticity, repeatability and comparability of automobile acoustic testing.

Description

Technical Field

[0001] This invention relates to the field of automotive testing technology, and more specifically, to an automotive testing method and system based on multi-dimensional combined sound scenarios. Background Technology

[0002] With the rapid development of automotive intelligence, connectivity, and smart cockpit technologies, vehicle acoustic systems have evolved from traditional noise control to a multi-functional integration of voice interaction, in-vehicle communication, and audio-visual entertainment. In actual use, the acoustic function of a vehicle is affected not only by its own structural noise but also by external environmental noise, such as rain and wind noise under different weather conditions, road noise from changing road conditions, and complex noise sources from surrounding vehicles, pedestrians, construction sites, and others. Therefore, how to comprehensively evaluate vehicle acoustic systems under conditions close to real-world usage has become an important research direction in the field of automotive acoustic testing.

[0003] Existing automotive acoustic testing methods mainly rely on real-vehicle road testing or fixed-environment testing methods such as semi-anechoic chambers and acoustic laboratories. Among them, real-vehicle road testing can reflect the actual operating state of the vehicle, but the testing process is easily affected by weather changes, road conditions, traffic flow, and surrounding environmental factors, making it difficult to maintain a consistent testing scenario and resulting in poor repeatability of test results. While laboratory testing can provide more stable testing conditions, it is usually used to evaluate a single noise source or a fixed acoustic environment, making it difficult to simulate the complex external sound environment formed by the coupling of multiple factors during actual vehicle use.

[0004] Therefore, it is necessary to provide a vehicle evaluation method and system based on multi-dimensional combined sound scenarios to solve the problems of difficulty in standardizing the construction of complex external sound environments, poor repeatability of test scenarios, and inability to establish the correlation evaluation relationship between external sound environment and vehicle functional performance in the existing vehicle acoustic testing process. Summary of the Invention

[0005] In view of this, the present invention proposes a vehicle evaluation method and system based on multi-dimensional combined sound scenarios, aiming to solve the problems of difficulty in standardizing the construction of complex external sound environments, poor repeatability of test scenarios, and inability to establish the correlation evaluation relationship between external sound environment and vehicle functional performance in the existing vehicle acoustic testing process.

[0006] On the one hand, this invention proposes a vehicle evaluation method based on multi-dimensional combined sound scenarios, including: Acquire external sound environment data during actual vehicle use, and classify the external sound environment data according to preset influencing factors; Based on the classified and processed vehicle exterior sound environment data, preset influencing factors are combined and matched to generate multiple multi-dimensional combined vehicle exterior sound scenes, and a vehicle exterior sound scene library is established based on the acoustic feature parameters corresponding to each multi-dimensional combined vehicle exterior sound scene. According to the target evaluation requirements, the target sound scene is determined from the vehicle exterior sound scene library, and the vehicle exterior sound environment is reconstructed based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated vehicle exterior sound field environment that matches the target sound scene. The vehicle under test is placed in the simulated external sound field environment, and the functional response data of the vehicle under test under the target sound scene is obtained; wherein, the functional response data includes at least one of voice interaction response data, communication response data and audio playback response data; Based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, a correlation between the external sound scene and the vehicle's functional performance is established, and the acoustic performance of the vehicle under test is evaluated based on the correlation to generate automotive acoustic evaluation results.

[0007] Furthermore, the preset influencing factors include weather conditions, road conditions, and human environmental conditions; The external acoustic environment data includes sound pressure information, spectrum information, sound source location information, and sound field change information.

[0008] Furthermore, the process of acquiring external sound environment data during actual vehicle use and classifying the external sound environment data according to preset influencing factors includes: Collect external sound environment data during actual vehicle use, and obtain weather conditions, road conditions, and human factors environmental conditions information corresponding to the external sound environment data; Based on the weather conditions information, the external sound environment data is classified and coded according to the weather dimension to generate corresponding weather category identifiers; Based on the road condition information, the external sound environment data is classified and coded according to the road dimension to generate corresponding road category identifiers; Based on the human-factor environmental condition information, the vehicle exterior sound environment data is classified and coded according to the human-factor environmental dimension to generate a corresponding human-factor environmental category identifier. The weather category identifier, road category identifier, and human-caused environment category identifier are associated and stored with the corresponding vehicle exterior sound environment data to form a multi-dimensional sound environment data set.

[0009] Furthermore, the step of combining and matching preset influencing factors based on the classified vehicle exterior sound environment data to generate multiple multi-dimensional combined vehicle exterior sound scenes, and establishing a vehicle exterior sound scene library based on the acoustic feature parameters corresponding to each of the multi-dimensional combined vehicle exterior sound scenes, includes: Based on the weather category identifier, road category identifier, and human factor environment category identifier, the vehicle exterior sound environment data in the multidimensional sound environment data set are combined and matched to determine the combination relationship corresponding to different weather conditions, road conditions, and human factor environment conditions. Based on the combination relationship, the corresponding vehicle exterior sound environment data is selected from the multidimensional sound environment data set, and a multidimensional combined vehicle exterior sound scene including weather dimension, road dimension and human factor environment dimension is generated. Feature extraction is performed on the external sound environment data corresponding to each of the multi-dimensional combined external sound scenarios to obtain the corresponding acoustic feature parameters; wherein, the acoustic feature parameters include sound pressure level parameters, spectral feature parameters, sound source spatial location information, and sound field change feature parameters; Establish a mapping relationship between the multi-dimensional combined vehicle exterior sound scenes and the corresponding acoustic feature parameters, and store each multi-dimensional combined vehicle exterior sound scene according to the mapping relationship to form a vehicle exterior sound scene library.

[0010] Furthermore, when determining the target sound scene from the vehicle exterior sound scene library according to the target evaluation requirements, the process includes: Obtain the target evaluation requirements corresponding to the vehicle under test, and parse the target evaluation requirements to determine the corresponding evaluation function type and target usage environment conditions; Based on the evaluation function type and the target usage environment conditions, a matching process is performed in the vehicle exterior sound scene library to determine the candidate vehicle exterior sound scene corresponding to the target evaluation requirement in the vehicle exterior sound scene library. Based on the weather category identifier, road category identifier, human factor environment category identifier, and acoustic characteristic parameters corresponding to each candidate vehicle exterior sound scene, the candidate vehicle exterior sound scenes are screened to determine the target sound scene that meets the target evaluation requirements. Acquire the acoustic feature parameters corresponding to the target sound scene, and use the acoustic feature parameters as input parameters for reconstructing the external sound environment.

[0011] Furthermore, when reconstructing the external sound environment based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated external sound field environment that matches the target sound scene, the process includes: Based on the acoustic feature parameters corresponding to the target sound scene, determine the sound source feature information, sound field spatial distribution information, and sound field dynamic change information corresponding to the target sound scene; Based on the sound source characteristic information, sound field spatial distribution information, and sound field dynamic change information, the sound source devices in the simulated test environment are configured to determine the sound source location, output sound pressure, and playback parameters corresponding to each sound source device. The sound source device is controlled to output the corresponding analog sound signal according to the playback parameters, and the spatial distribution of the analog sound signal is adjusted according to the sound source location to generate a simulated vehicle exterior sound field environment corresponding to the target sound scene; Real-time acoustic parameters in the simulated external sound field environment are collected, and the real-time acoustic parameters are compared with the acoustic feature parameters corresponding to the target sound scene. The simulated external sound field environment is adjusted according to the comparison results to match the simulated external sound field environment with the target sound scene.

[0012] Furthermore, when placing the vehicle under test in the simulated external sound field environment and acquiring the functional response data of the vehicle under test in the target sound scene, the process includes: The vehicle under test is placed at the test position corresponding to the simulated external sound field environment, and the vehicle test status is configured according to the evaluation function type corresponding to the target sound scene. During the operation of the simulated vehicle external sound field environment, the operation response data of the target functional module in the vehicle under test are collected, wherein the target functional module includes at least one of a voice interaction module, a communication module, and an audio playback module; When the target functional module is a voice interaction module, the voice recognition result, response time and command execution result of the vehicle under test after receiving a preset voice command are obtained, and voice interaction response data is generated. When the target functional module is a communication module, the call signal quality, speech clarity and noise suppression effect of the vehicle under test in a simulated external sound environment are obtained, and communication response data is generated. When the target functional module is an audio playback module, the audio output parameters and acoustic evaluation parameters when the vehicle under test plays the target audio are obtained, and audio playback response data is generated. The voice interaction response data, communication response data, and audio playback response data are associated and stored to form the functional response data of the vehicle under test in the target sound scenario.

[0013] Furthermore, when establishing the correlation between the external sound scene and the vehicle's functional performance based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, it includes: Acquire the acoustic feature parameters corresponding to the target sound scene, and perform feature association processing on the acoustic feature parameters to determine the acoustic environment features corresponding to the target sound scene; The functional response data is parsed to extract the functional performance parameters corresponding to each target functional module of the vehicle under test; wherein, the functional performance parameters include at least one of the following: speech recognition accuracy, response time, communication quality parameters, and audio output quality parameters. The acoustic environment features are correlated and matched with the corresponding functional performance parameters to determine the performance variation relationship of each target functional module under different vehicle exterior sound scenarios; Based on the correspondence between acoustic environment characteristics and functional performance parameters corresponding to multiple target sound scenes, establish the correlation mapping relationship between external sound scenes and vehicle functional performance; The impact of different external sound scenarios on vehicle functional performance is determined based on the aforementioned correlation mapping relationship, and scenario-function correlation data for evaluating vehicle acoustic performance is generated.

[0014] Furthermore, when evaluating the acoustic performance of the vehicle under test based on the aforementioned correlation and generating automotive acoustic evaluation results, the process includes: Based on the scenario-function association data, determine the vehicle function performance evaluation index corresponding to the target sound scenario; The functional response data of the vehicle under test in each target sound scenario are compared and analyzed with preset evaluation indicators to determine the functional performance evaluation parameters of the vehicle under test in different external sound scenarios. Based on the functional performance evaluation parameters corresponding to different target sound scenarios, the acoustic performance of the vehicle under test is comprehensively evaluated to determine the acoustic adaptability of the vehicle under test in multi-dimensional combined sound scenarios. Based on the acoustic adaptability and the functional performance evaluation parameters corresponding to each target acoustic scenario, the automotive acoustic evaluation results are generated. The automotive acoustic evaluation results include at least one of the following: functional performance evaluation results under different vehicle exterior sound scenarios, acoustic environment adaptability evaluation results, and acoustic function information to be optimized.

[0015] Compared with existing technologies, the beneficial effects of this invention are as follows: Firstly, this invention acquires external acoustic environment data during vehicle operation and classifies it according to influencing factors such as weather conditions, road conditions, and human-induced environmental conditions, providing a data foundation for constructing multi-dimensional combined sound scenarios. Secondly, it combines and matches different influencing factors to generate multi-dimensional combined external acoustic scenarios and extracts corresponding acoustic feature parameters to establish an external acoustic scenario library, achieving standardized storage of actual complex acoustic environments. Thirdly, it determines the target sound scenario from the sound scenario library according to evaluation requirements and reconstructs the simulated external acoustic environment based on corresponding acoustic feature parameters, enabling the test environment to reproduce actual usage scenarios. Finally, it places the vehicle under test in the simulated sound environment, acquires functional response data such as voice interaction, communication, and audio playback, and establishes the correlation between sound scenarios and vehicle functional performance, achieving a comprehensive evaluation of vehicle acoustic performance. In summary, this invention can improve the authenticity, repeatability, and comparability of automotive acoustic testing, providing technical support for vehicle acoustic system optimization and scenario-based testing.

[0016] On the other hand, this application also provides a vehicle evaluation system based on a multi-dimensional combined sound scene, including: The vehicle exterior sound environment acquisition and classification module is configured to acquire vehicle exterior sound environment data during actual vehicle use and classify the vehicle exterior sound environment data according to preset influencing factors. The multi-dimensional sound scene construction module is configured to combine and match preset influencing factors based on the classified and processed vehicle exterior sound environment data to generate multiple multi-dimensional combined vehicle exterior sound scenes, and to establish a vehicle exterior sound scene library based on the acoustic feature parameters corresponding to each multi-dimensional combined vehicle exterior sound scene. The sound field reconstruction module is configured to determine the target sound scene from the vehicle exterior sound scene library according to the target evaluation requirements, and reconstruct the vehicle exterior sound environment based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated vehicle exterior sound field environment that matches the target sound scene. The vehicle function response acquisition module is configured to place the vehicle under test in the simulated external sound field environment and acquire the function response data of the vehicle under test in the target sound scene; wherein, the function response data includes at least one of voice interaction response data, communication response data and audio playback response data; The correlation evaluation module is configured to establish a correlation between the external sound scene and the vehicle's functional performance based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, and to evaluate the acoustic performance of the vehicle under test based on the correlation to generate automotive acoustic evaluation results.

[0017] It is understood that the vehicle evaluation method and system based on multi-dimensional combined sound scenes provided in this application have the same beneficial effects, and will not be elaborated here. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 A flowchart illustrating the vehicle evaluation method based on a multi-dimensional combined sound scene provided in an embodiment of the present invention; Figure 2 This is a functional block diagram of a car evaluation system based on a multi-dimensional combined sound scene provided in an embodiment of the present invention. Detailed Implementation

[0019] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] In some embodiments of this application, see Figure 1 As shown, this embodiment provides a vehicle evaluation method based on a multi-dimensional combined sound scene, including the following steps: S100. Acquire external sound environment data during actual vehicle use, and classify the external sound environment data according to preset influencing factors. S200. Based on the classified and processed vehicle exterior sound environment data, the preset influencing factors are combined and matched to generate multiple multi-dimensional combined vehicle exterior sound scenes, and a vehicle exterior sound scene library is established based on the acoustic feature parameters corresponding to each multi-dimensional combined vehicle exterior sound scene. S300. Determine the target sound scene from the vehicle exterior sound scene library according to the target evaluation requirements, and reconstruct the vehicle exterior sound environment based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated vehicle exterior sound field environment that matches the target sound scene. S400. Place the vehicle under test in the simulated external sound field environment and acquire the functional response data of the vehicle under test in the target sound scene; wherein, the functional response data includes at least one of voice interaction response data, communication response data and audio playback response data; S500. Based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, establish the correlation between the external sound scene and the vehicle's functional performance, and evaluate the acoustic performance of the vehicle under test based on the correlation to generate automotive acoustic evaluation results.

[0021] Understandably, this invention first acquires external acoustic environment data during vehicle operation and classifies it according to influencing factors such as weather conditions, road conditions, and human-induced environmental conditions, providing a data foundation for constructing multi-dimensional combined sound scenarios. Further, it combines and matches different influencing factors to generate multi-dimensional combined external sound scenarios and extracts corresponding acoustic feature parameters to establish an external sound scenario library, achieving standardized storage of real-world complex sound environments. Based on evaluation requirements, it determines the target sound scenario from the sound scenario library and reconstructs the simulated external sound environment based on corresponding acoustic feature parameters, enabling the test environment to reproduce actual usage scenarios. The vehicle under test is placed in the simulated sound environment to acquire functional response data such as voice interaction, communication, and audio playback, and establishes the correlation between sound scenarios and vehicle functional performance, achieving a comprehensive evaluation of vehicle acoustic performance. In summary, this invention can improve the authenticity, repeatability, and comparability of automotive acoustic testing, providing technical support for vehicle acoustic system optimization and scenario-based testing.

[0022] In some specific embodiments of this application, the preset influencing factors include weather conditions, road conditions, and human-related environmental conditions; The external acoustic environment data includes sound pressure information, spectrum information, sound source location information, and sound field change information.

[0023] It is understood that, in this embodiment, by setting weather conditions, road conditions, and human environmental conditions as preset influencing factors, the external sound environment data can be divided into multiple dimensions.

[0024] Among them, weather conditions are used to characterize the impact of different meteorological environments on the external sound propagation characteristics of vehicles, such as the different acoustic characteristics formed under sunny, rainy, and windy weather conditions; road conditions are used to reflect the impact of different road types and road surface conditions on vehicle driving noise, such as urban roads, highways, and tunnel sections; human factors environmental conditions are used to describe the changes in environmental sound caused by factors such as the activities of people around the vehicle and traffic participation status.

[0025] Furthermore, the external sound environment data includes sound pressure information, spectrum information, sound source location information, and sound field change information. Among them, sound pressure information is used to characterize the intensity of the sound environment, spectrum information is used to reflect the distribution characteristics of different sound components, sound source location information is used to determine the sound source and spatial distribution, and sound field change information is used to describe the dynamic changes of sound over time or vehicle operating status.

[0026] In summary, by combining the above-mentioned multidimensional influencing factors and acoustic parameters, we can more comprehensively characterize the complex external acoustic environment during real vehicle use, providing an accurate data foundation for subsequent multidimensional combined sound scene construction and acoustic environment reconstruction, and improving the authenticity and reliability of automotive acoustic evaluation.

[0027] In some specific embodiments of this application, the step of acquiring external sound environment data during actual vehicle use and classifying the external sound environment data according to preset influencing factors includes: Collect external sound environment data during actual vehicle use, and obtain weather conditions, road conditions, and human factors environmental conditions information corresponding to the external sound environment data; Based on the weather conditions information, the external sound environment data is classified and coded according to the weather dimension to generate corresponding weather category identifiers; Based on the road condition information, the external sound environment data is classified and coded according to the road dimension to generate corresponding road category identifiers; Based on the human-factor environmental condition information, the vehicle exterior sound environment data is classified and coded according to the human-factor environmental dimension to generate a corresponding human-factor environmental category identifier. The weather category identifier, road category identifier, and human-caused environment category identifier are associated and stored with the corresponding vehicle exterior sound environment data to form a multi-dimensional sound environment data set.

[0028] It is understandable that by collecting external sound environment data during actual vehicle use and classifying and coding the external sound environment data in combination with multi-dimensional influencing factors such as weather conditions, road conditions, and human factors, the acoustic data corresponding to different environmental factors can be distinguished and correlated.

[0029] Specifically, firstly, external sound environment data generated by the vehicle under different usage scenarios is collected, and weather condition information, road condition information, and human-related environmental condition information corresponding to the sound environment data are acquired simultaneously. Further, the external sound environment data is classified and coded according to the aforementioned influencing factors to generate corresponding weather category identifiers, road category identifiers, and human-related environmental category identifiers, so that each set of sound environment data has a corresponding environmental attribute label. Then, each category identifier is associated with and stored with the corresponding external sound environment data to form a sound environment data set containing multi-dimensional environmental information.

[0030] Through the above classification and coding, structured management of complex vehicle external sound environments is realized, enabling the rapid retrieval and combination of acoustic data under different weather, road, and human factors conditions. This provides an accurate data foundation for the subsequent generation of multi-dimensional combined vehicle external sound scenarios, the establishment of a vehicle external sound scenario library, and the conduct of scenario-based automotive acoustic evaluation, thereby improving the flexibility of sound scenario construction and the repeatability of the testing process.

[0031] In some specific embodiments of this application, the step of combining and matching preset influencing factors based on the classified vehicle exterior sound environment data to generate multiple multi-dimensional combined vehicle exterior sound scenes, and establishing a vehicle exterior sound scene library based on the acoustic feature parameters corresponding to each of the multi-dimensional combined vehicle exterior sound scenes, includes: Based on the weather category identifier, road category identifier, and human factor environment category identifier, the vehicle exterior sound environment data in the multidimensional sound environment data set are combined and matched to determine the combination relationship corresponding to different weather conditions, road conditions, and human factor environment conditions. Based on the combination relationship, the corresponding vehicle exterior sound environment data is selected from the multidimensional sound environment data set, and a multidimensional combined vehicle exterior sound scene including weather dimension, road dimension and human factor environment dimension is generated. Feature extraction is performed on the external sound environment data corresponding to each of the multi-dimensional combined external sound scenarios to obtain the corresponding acoustic feature parameters; wherein, the acoustic feature parameters include sound pressure level parameters, spectral feature parameters, sound source spatial location information, and sound field change feature parameters; Establish a mapping relationship between the multi-dimensional combined vehicle exterior sound scenes and the corresponding acoustic feature parameters, and store each multi-dimensional combined vehicle exterior sound scene according to the mapping relationship to form a vehicle exterior sound scene library.

[0032] Understandably, based on weather category identifiers, road category identifiers, and human factor environment category identifiers, the sound environment data in the multidimensional sound environment dataset is correlated and matched to determine the combination relationship between different weather conditions, road conditions, and human factor environment conditions. For example, the sound environment combination corresponding to different road environments and human activity states under different weather conditions. Furthermore, based on the determined combination relationship, corresponding sound environment data is selected from the multidimensional sound environment data set to generate a multidimensional combined vehicle exterior sound scene that simultaneously includes weather, road, and human factors environmental dimensions, so that a single sound environment data can be expanded into a complex sound environment scene that is closer to the actual vehicle use process. Subsequently, feature extraction was performed on the external sound environment data corresponding to each multi-dimensional combined external sound scene to obtain acoustic feature parameters for characterizing the sound field characteristics, including sound pressure level parameters, spectral feature parameters, sound source spatial location information, and sound field change feature parameters, so as to achieve accurate description of different sound scenes. Finally, a mapping relationship is established between multi-dimensional combined vehicle exterior sound scenes and corresponding acoustic feature parameters, and the scenes are stored according to the mapping relationship to form a vehicle exterior sound scene library.

[0033] Through the above, the present invention can standardize the management of complex and changing acoustic conditions in actual road environments, realize the rapid recall and reproduction of multi-dimensional sound scenes, improve the coverage and repeatability of automotive acoustic test scenarios, and provide a reliable data foundation for subsequent reconstruction of the vehicle's external sound environment and evaluation of vehicle acoustic performance.

[0034] In some specific embodiments of this application, determining the target sound scene from the vehicle exterior sound scene library according to the target evaluation requirements includes: Obtain the target evaluation requirements corresponding to the vehicle under test, and parse the target evaluation requirements to determine the corresponding evaluation function type and target usage environment conditions; Based on the evaluation function type and the target usage environment conditions, a matching process is performed in the vehicle exterior sound scene library to determine the candidate vehicle exterior sound scene corresponding to the target evaluation requirement in the vehicle exterior sound scene library. Based on the weather category identifier, road category identifier, human factor environment category identifier, and acoustic characteristic parameters corresponding to each candidate vehicle exterior sound scene, the candidate vehicle exterior sound scenes are screened to determine the target sound scene that meets the target evaluation requirements. Acquire the acoustic feature parameters corresponding to the target sound scene, and use the acoustic feature parameters as input parameters for reconstructing the external sound environment.

[0035] Understandably, by selecting target sound scenarios from the external sound scenario library that match the target test conditions based on vehicle evaluation requirements, automotive acoustic testing can be scenario-based for different functions and usage environments.

[0036] Specifically, the first step is to obtain the target evaluation requirements for the vehicle under test, and then analyze the target evaluation requirements to determine the types of functions to be tested and the corresponding target usage environment conditions, such as the testing requirements for voice interaction functions in a highway environment, or the testing requirements for communication functions in a complex urban environment. Furthermore, based on the determined evaluation function type and target usage environment conditions, a pre-established external sound scene library is used for matching to select candidate external sound scenes related to the target evaluation requirements, enabling the testing process to select the corresponding sound environment based on actual usage conditions. Subsequently, based on the weather category identifier, road category identifier, human factor environment category identifier, and acoustic characteristic parameters corresponding to the candidate external sound scenes, the candidate sound scenes are further filtered to determine the target sound scene that meets the testing requirements, thereby improving the accuracy of sound scene selection. Finally, the acoustic characteristic parameters corresponding to the target sound scene are obtained and used as input parameters for the subsequent external sound environment reconstruction process, so that the reconstructed simulated sound environment can accurately correspond to the target test scene.

[0037] In summary, this invention enables precise retrieval of the sound scene library according to different evaluation needs, avoiding the problem of high randomness in sound environment selection in traditional testing, and improving the relevance, accuracy and repeatability of automotive acoustic testing.

[0038] In some specific embodiments of this application, when reconstructing the external sound environment based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated external sound field environment that matches the target sound scene, the process includes: Based on the acoustic feature parameters corresponding to the target sound scene, determine the sound source feature information, sound field spatial distribution information, and sound field dynamic change information corresponding to the target sound scene; Based on the sound source characteristic information, sound field spatial distribution information, and sound field dynamic change information, the sound source devices in the simulated test environment are configured to determine the sound source location, output sound pressure, and playback parameters corresponding to each sound source device. The sound source device is controlled to output the corresponding analog sound signal according to the playback parameters, and the spatial distribution of the analog sound signal is adjusted according to the sound source location to generate a simulated vehicle exterior sound field environment corresponding to the target sound scene; Real-time acoustic parameters in the simulated external sound field environment are collected, and the real-time acoustic parameters are compared with the acoustic feature parameters corresponding to the target sound scene. The simulated external sound field environment is adjusted according to the comparison results to match the simulated external sound field environment with the target sound scene.

[0039] It is understandable that by reconstructing the actual external sound environment based on the acoustic feature parameters corresponding to the target sound scene, the complex and difficult-to-reproduce road sound environment can be accurately reproduced in the simulated test environment.

[0040] Specifically, firstly, based on acoustic characteristic parameters such as sound pressure level parameters, spectral characteristic parameters, sound source spatial location information, and sound field change characteristic parameters corresponding to the target sound scene, the sound source characteristic information, sound field spatial distribution information, and sound field dynamic change information corresponding to the target sound scene are determined to obtain the sound composition, spatial distribution, and time-varying characteristics of the target sound environment; then, based on the determined sound source characteristic information, sound field spatial distribution information, and sound field dynamic change information, multiple sound source devices in the simulated test environment are configured to determine the installation position, output sound pressure, and playback parameters of each sound source device, so that different sound source devices can simulate sound sources with different locations, intensities, and changing patterns in the actual environment; The system further controls each sound source device to output simulated sound signals according to the corresponding playback parameters, and adjusts the spatial distribution of the simulated sound signals based on the sound source location, so that the sounds generated by multiple sound sources form a simulated external sound field environment that matches the target sound scene within the test area. Furthermore, the system collects real-time acoustic parameters in the simulated external sound field environment and compares them with the acoustic characteristic parameters corresponding to the target sound scene. Based on the comparison results, the system adjusts the sound source output parameters, spatial distribution parameters, etc., so that the simulated sound environment continuously approaches the target sound scene.

[0041] Through the above, the present invention can achieve high-precision and repeatable reconstruction of complex vehicle external acoustic environments, reduce the impact of weather, road and traffic environment changes on test results in actual road tests, and improve the stability and reliability of the vehicle acoustic evaluation process.

[0042] In some specific embodiments of this application, the step of placing the vehicle under test in the simulated external sound field environment and acquiring the functional response data of the vehicle under test in the target sound scene includes: The vehicle under test is placed at the test position corresponding to the simulated external sound field environment, and the vehicle test status is configured according to the evaluation function type corresponding to the target sound scene. During the operation of the simulated vehicle external sound field environment, the operation response data of the target functional module in the vehicle under test are collected, wherein the target functional module includes at least one of a voice interaction module, a communication module, and an audio playback module; When the target functional module is a voice interaction module, the voice recognition result, response time and command execution result of the vehicle under test after receiving a preset voice command are obtained, and voice interaction response data is generated. When the target functional module is a communication module, the call signal quality, speech clarity and noise suppression effect of the vehicle under test in a simulated external sound environment are obtained, and communication response data is generated. When the target functional module is an audio playback module, the audio output parameters and acoustic evaluation parameters when the vehicle under test plays the target audio are obtained, and audio playback response data is generated. The voice interaction response data, communication response data, and audio playback response data are associated and stored to form the functional response data of the vehicle under test in the target sound scenario.

[0043] Understandably, by placing the vehicle under test in a simulated external sound field environment corresponding to the target sound scene, and by detecting the operating status of different functional modules of the vehicle in a complex sound environment, a quantitative evaluation of the vehicle's acoustic performance can be achieved.

[0044] Specifically, firstly, based on the evaluation function type corresponding to the target sound scene, the vehicle under test is set in a preset test position in a simulated external sound field environment, and the vehicle's operating status is configured to make the vehicle work in a state that matches the actual application scenario; furthermore, during the operation in the simulated external sound field environment, the target functional modules in the vehicle under test are monitored in real time, and the operating response data generated by each functional module under different sound environment conditions are collected, wherein the target functional modules include at least one of a voice interaction module, a communication module, and an audio playback module.

[0045] Specifically, when testing the voice interaction module, preset voice commands are input into the vehicle, and the vehicle's recognition results, response time, and command execution results are obtained to form voice interaction response data, which is used to evaluate the impact of the external sound environment on the vehicle's voice control capabilities. When testing the communication module, the vehicle's call signal quality, speech clarity, and noise suppression effect in a simulated external sound environment are collected to form communication response data, which reflects the vehicle's communication performance in complex sound environments. When testing the audio playback module, audio output parameters and acoustic evaluation parameters are obtained during the playback of target audio to form audio playback response data, which is used to evaluate the impact of different external sound scenarios on the in-vehicle audio experience. Finally, the response data corresponding to each functional module is associated and stored with the target sound scenario to form the functional response data of the vehicle under test in the target sound scenario.

[0046] Through the above, the present invention can obtain the response of various acoustic functions of a vehicle in a repeatable simulated sound environment, avoiding the problem that traditional real vehicle road tests are greatly affected by environmental changes, and providing reliable data support for establishing the correlation between the external sound scene and the vehicle's functional performance and carrying out comprehensive acoustic performance evaluation.

[0047] In some specific embodiments of this application, establishing the correlation between the external sound scene and the vehicle's functional performance based on the acoustic feature parameters corresponding to the target sound scene and the functional response data includes: Acquire the acoustic feature parameters corresponding to the target sound scene, and perform feature association processing on the acoustic feature parameters to determine the acoustic environment features corresponding to the target sound scene; The functional response data is parsed to extract the functional performance parameters corresponding to each target functional module of the vehicle under test; wherein, the functional performance parameters include at least one of the following: speech recognition accuracy, response time, communication quality parameters, and audio output quality parameters. The acoustic environment features are correlated and matched with the corresponding functional performance parameters to determine the performance variation relationship of each target functional module under different vehicle exterior sound scenarios; Based on the correspondence between acoustic environment characteristics and functional performance parameters corresponding to multiple target sound scenes, establish the correlation mapping relationship between external sound scenes and vehicle functional performance; The impact of different external sound scenarios on vehicle functional performance is determined based on the aforementioned correlation mapping relationship, and scenario-function correlation data for evaluating vehicle acoustic performance is generated.

[0048] Understandably, by correlating and analyzing the acoustic characteristic parameters corresponding to the target sound scene with the functional response data of the vehicle under test, a mapping relationship between the external sound environment and the vehicle's functional performance is established, thereby realizing the evaluation of automotive acoustic performance based on actual usage scenarios.

[0049] Specifically, the acoustic feature parameters corresponding to the target sound scene are first obtained, and feature correlation processing is performed on the acoustic feature parameters. Information such as sound pressure level, spectrum characteristics, spatial distribution of sound sources, and sound field change characteristics are comprehensively analyzed to determine the acoustic environment characteristics that can characterize the target sound scene. Furthermore, the functional response data generated by the vehicle under test in the target sound scene are analyzed to extract the functional performance parameters corresponding to the target functional modules such as the voice interaction module, communication module, and audio playback module. Among them, the functional performance parameters include speech recognition accuracy, response time, communication quality parameters, and audio output quality parameters, so as to quantitatively reflect the operating status of vehicle functions under different sound environment conditions. Furthermore, the acoustic environment characteristics are correlated and matched with the corresponding functional performance parameters to analyze the impact of different external sound scenarios on the performance of various functional modules of the vehicle, and to determine the correspondence between different acoustic environment factors and changes in functional performance. By summarizing the correlation results between acoustic environment characteristics and functional performance parameters under multiple target sound scenarios, a correlation mapping relationship between external sound scenarios and vehicle functional performance is established. Finally, based on the correlation mapping relationship, the degree of influence of different external sound scenarios on vehicle functional performance is determined, and scenario-function correlation data for evaluating automotive acoustic performance is generated.

[0050] In summary, this invention realizes the transformation from simple acoustic parameter detection to evaluation of the correlation between acoustic environment and vehicle functional performance, which can more comprehensively reflect the acoustic adaptability of vehicles in complex real-world usage environments.

[0051] In some specific embodiments of this application, the step of evaluating the acoustic performance of the vehicle under test based on the correlation and generating automotive acoustic evaluation results includes: Based on the scenario-function association data, determine the vehicle function performance evaluation index corresponding to the target sound scenario; The functional response data of the vehicle under test in each target sound scenario are compared and analyzed with preset evaluation indicators to determine the functional performance evaluation parameters of the vehicle under test in different external sound scenarios. Based on the functional performance evaluation parameters corresponding to different target sound scenarios, the acoustic performance of the vehicle under test is comprehensively evaluated to determine the acoustic adaptability of the vehicle under test in multi-dimensional combined sound scenarios. Based on the acoustic adaptability and the functional performance evaluation parameters corresponding to each target acoustic scenario, the automotive acoustic evaluation results are generated. The automotive acoustic evaluation results include at least one of the following: functional performance evaluation results under different vehicle exterior sound scenarios, acoustic environment adaptability evaluation results, and acoustic function information to be optimized.

[0052] Understandably, by conducting a comprehensive acoustic performance evaluation of the vehicle under test based on scenario-function correlation data, a quantitative analysis of the vehicle's functional adaptability under different external acoustic environment conditions can be achieved.

[0053] First, based on the established scene-function association data, vehicle functional performance evaluation indicators corresponding to each target sound scene are determined, enabling different types of external sound environments to correspond to specific functional evaluation dimensions. Next, the functional response data collected from the vehicle under test in each target sound scene is compared and analyzed with preset evaluation indicators to determine the vehicle's functional performance evaluation parameters under different combinations of weather, road, and human environmental conditions, thereby obtaining the actual performance of each functional module in complex sound environments. Then, based on the functional performance evaluation parameters corresponding to multiple target sound scenes, the overall acoustic performance of the vehicle under test is comprehensively analyzed to determine the vehicle's acoustic adaptability in multi-dimensional combined sound scenes, reflecting the degree of adaptability of the vehicle's acoustic system to different external environments. Finally, based on the determined acoustic adaptability and the functional performance evaluation parameters corresponding to each target sound scene, automotive acoustic evaluation results are generated. These results include functional performance evaluation results under different external sound scenes, acoustic environment adaptability evaluation results, and information on acoustic functions to be optimized.

[0054] Through the above, the present invention can overcome the limitations of traditional automotive acoustic testing, which only evaluates a single noise index, and achieve a comprehensive evaluation of vehicle acoustic systems for real-world usage scenarios.

[0055] On the other hand, see Figure 2 As shown, this application also provides a vehicle evaluation system based on a multi-dimensional combined sound scene, used to apply the above-mentioned vehicle evaluation method based on a multi-dimensional combined sound scene, including: The vehicle exterior sound environment acquisition and classification module is configured to acquire vehicle exterior sound environment data during actual vehicle use and classify the vehicle exterior sound environment data according to preset influencing factors. The multi-dimensional sound scene construction module is configured to combine and match preset influencing factors based on the classified and processed vehicle exterior sound environment data to generate multiple multi-dimensional combined vehicle exterior sound scenes, and to establish a vehicle exterior sound scene library based on the acoustic feature parameters corresponding to each multi-dimensional combined vehicle exterior sound scene. The sound field reconstruction module is configured to determine the target sound scene from the vehicle exterior sound scene library according to the target evaluation requirements, and reconstruct the vehicle exterior sound environment based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated vehicle exterior sound field environment that matches the target sound scene. The vehicle function response acquisition module is configured to place the vehicle under test in the simulated external sound field environment and acquire the function response data of the vehicle under test in the target sound scene; wherein, the function response data includes at least one of voice interaction response data, communication response data and audio playback response data; The correlation evaluation module is configured to establish a correlation between the external sound scene and the vehicle's functional performance based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, and to evaluate the acoustic performance of the vehicle under test based on the correlation to generate automotive acoustic evaluation results.

[0056] It is understood that this invention automates the construction of the vehicle's external acoustic environment, sound field reconstruction, and evaluation of vehicle functional performance. Specifically, the external acoustic environment acquisition and classification module acquires external acoustic environment data during actual vehicle use and classifies it according to influencing factors such as weather conditions, road conditions, and human-induced environmental conditions; the multi-dimensional sound scene construction module combines and matches the classified acoustic environment data to generate multi-dimensional combined external acoustic scenes and establishes an external acoustic scene library, achieving standardized management of complex acoustic environments; the sound field reconstruction module selects target sound scenes according to evaluation requirements and generates simulated external sound field environments based on corresponding acoustic feature parameters, enabling vehicles to be tested in a controlled environment; the vehicle functional response acquisition module collects functional response data such as voice interaction, communication, and audio playback of the vehicle under test in the target sound scene; and the correlation evaluation module establishes the correlation between sound scenes and vehicle functional performance and generates automotive acoustic evaluation results. Through the above, this invention enables the repeatable construction of complex external acoustic environments and comprehensive evaluation of vehicle acoustic performance, improving the authenticity, stability, and comparability of automotive acoustic testing.

[0057] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0059] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0060] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A vehicle evaluation method based on multi-dimensional combined sound scenes, characterized in that, include: Acquire external sound environment data during actual vehicle use, and classify the external sound environment data according to preset influencing factors; Based on the classified and processed vehicle exterior sound environment data, preset influencing factors are combined and matched to generate multiple multi-dimensional combined vehicle exterior sound scenes, and a vehicle exterior sound scene library is established based on the acoustic feature parameters corresponding to each multi-dimensional combined vehicle exterior sound scene. According to the target evaluation requirements, the target sound scene is determined from the vehicle exterior sound scene library, and the vehicle exterior sound environment is reconstructed based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated vehicle exterior sound field environment that matches the target sound scene. The vehicle under test is placed in the simulated external sound field environment, and the functional response data of the vehicle under test under the target sound scene is obtained; wherein, the functional response data includes at least one of voice interaction response data, communication response data and audio playback response data; Based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, a correlation between the external sound scene and the vehicle's functional performance is established, and the acoustic performance of the vehicle under test is evaluated based on the correlation to generate automotive acoustic evaluation results.

2. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 1, characterized in that, The preset influencing factors include weather conditions, road conditions, and human environmental conditions; The external acoustic environment data includes sound pressure information, spectrum information, sound source location information, and sound field change information.

3. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 2, characterized in that, The process of acquiring external sound environment data during actual vehicle use and classifying the external sound environment data according to preset influencing factors includes: Collect external sound environment data during actual vehicle use, and obtain weather conditions, road conditions, and human factors environmental conditions information corresponding to the external sound environment data; Based on the weather conditions information, the external sound environment data is classified and coded according to the weather dimension to generate corresponding weather category identifiers; Based on the road condition information, the external sound environment data is classified and coded according to the road dimension to generate corresponding road category identifiers; Based on the human-factor environmental condition information, the vehicle exterior sound environment data is classified and coded according to the human-factor environmental dimension to generate a corresponding human-factor environmental category identifier. The weather category identifier, road category identifier, and human-caused environment category identifier are associated and stored with the corresponding vehicle exterior sound environment data to form a multi-dimensional sound environment data set.

4. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 3, characterized in that, The step of combining and matching preset influencing factors based on the classified vehicle exterior sound environment data to generate multiple multi-dimensional combined vehicle exterior sound scenes, and establishing a vehicle exterior sound scene library based on the acoustic feature parameters corresponding to each of the multi-dimensional combined vehicle exterior sound scenes, includes: Based on the weather category identifier, road category identifier, and human factor environment category identifier, the vehicle exterior sound environment data in the multidimensional sound environment data set are combined and matched to determine the combination relationship corresponding to different weather conditions, road conditions, and human factor environment conditions. Based on the combination relationship, the corresponding vehicle exterior sound environment data is selected from the multidimensional sound environment data set, and a multidimensional combined vehicle exterior sound scene including weather dimension, road dimension and human factor environment dimension is generated. Feature extraction is performed on the external sound environment data corresponding to each of the multi-dimensional combined external sound scenarios to obtain the corresponding acoustic feature parameters; wherein, the acoustic feature parameters include sound pressure level parameters, spectral feature parameters, sound source spatial location information, and sound field change feature parameters; Establish a mapping relationship between the multi-dimensional combined vehicle exterior sound scenes and the corresponding acoustic feature parameters, and store each multi-dimensional combined vehicle exterior sound scene according to the mapping relationship to form a vehicle exterior sound scene library.

5. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 4, characterized in that, The step of determining the target sound scene from the vehicle exterior sound scene library according to the target evaluation requirements includes: Obtain the target evaluation requirements corresponding to the vehicle under test, and parse the target evaluation requirements to determine the corresponding evaluation function type and target usage environment conditions; Based on the evaluation function type and the target usage environment conditions, a matching process is performed in the vehicle exterior sound scene library to determine the candidate vehicle exterior sound scene corresponding to the target evaluation requirement in the vehicle exterior sound scene library. Based on the weather category identifier, road category identifier, human factor environment category identifier, and acoustic characteristic parameters corresponding to each candidate vehicle exterior sound scene, the candidate vehicle exterior sound scenes are screened to determine the target sound scene that meets the target evaluation requirements. Acquire the acoustic feature parameters corresponding to the target sound scene, and use the acoustic feature parameters as input parameters for reconstructing the external sound environment.

6. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 5, characterized in that, When reconstructing the external sound environment based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated external sound field environment that matches the target sound scene, the process includes: Based on the acoustic feature parameters corresponding to the target sound scene, determine the sound source feature information, sound field spatial distribution information, and sound field dynamic change information corresponding to the target sound scene; Based on the sound source characteristic information, sound field spatial distribution information, and sound field dynamic change information, the sound source devices in the simulated test environment are configured to determine the sound source location, output sound pressure, and playback parameters corresponding to each sound source device. The sound source device is controlled to output the corresponding analog sound signal according to the playback parameters, and the spatial distribution of the analog sound signal is adjusted according to the sound source location to generate a simulated vehicle exterior sound field environment corresponding to the target sound scene; Real-time acoustic parameters in the simulated external sound field environment are collected, and the real-time acoustic parameters are compared with the acoustic feature parameters corresponding to the target sound scene. The simulated external sound field environment is adjusted according to the comparison results to match the simulated external sound field environment with the target sound scene.

7. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 6, characterized in that, When placing the vehicle under test in the simulated external sound field environment and acquiring the functional response data of the vehicle under test in the target sound scene, the following steps are included: The vehicle under test is placed at the test position corresponding to the simulated external sound field environment, and the vehicle test status is configured according to the evaluation function type corresponding to the target sound scene. During the operation of the simulated vehicle external sound field environment, the operation response data of the target functional module in the vehicle under test are collected, wherein the target functional module includes at least one of a voice interaction module, a communication module, and an audio playback module; When the target functional module is a voice interaction module, the voice recognition result, response time and command execution result of the vehicle under test after receiving a preset voice command are obtained, and voice interaction response data is generated. When the target functional module is a communication module, the call signal quality, speech clarity and noise suppression effect of the vehicle under test in a simulated external sound environment are obtained, and communication response data is generated. When the target functional module is an audio playback module, the audio output parameters and acoustic evaluation parameters when the vehicle under test plays the target audio are obtained, and audio playback response data is generated. The voice interaction response data, communication response data, and audio playback response data are associated and stored to form the functional response data of the vehicle under test in the target sound scenario.

8. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 7, characterized in that, When establishing the correlation between the external sound scene and the vehicle's functional performance based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, the following steps are included: Acquire the acoustic feature parameters corresponding to the target sound scene, and perform feature association processing on the acoustic feature parameters to determine the acoustic environment features corresponding to the target sound scene; The functional response data is parsed to extract the functional performance parameters corresponding to each target functional module of the vehicle under test; wherein, the functional performance parameters include at least one of the following: speech recognition accuracy, response time, communication quality parameters, and audio output quality parameters. The acoustic environment features are correlated and matched with the corresponding functional performance parameters to determine the performance variation relationship of each target functional module under different vehicle exterior sound scenarios; Based on the correspondence between acoustic environment characteristics and functional performance parameters corresponding to multiple target sound scenes, establish the correlation mapping relationship between external sound scenes and vehicle functional performance; The impact of different external sound scenarios on vehicle functional performance is determined based on the aforementioned correlation mapping relationship, and scenario-function correlation data for evaluating vehicle acoustic performance is generated.

9. The vehicle evaluation method based on multi-dimensional combined sound scenes according to claim 8, characterized in that, When evaluating the acoustic performance of the vehicle under test based on the aforementioned correlation and generating automotive acoustic evaluation results, the process includes: Based on the scenario-function association data, determine the vehicle function performance evaluation index corresponding to the target sound scenario; The functional response data of the vehicle under test in each target sound scenario are compared and analyzed with preset evaluation indicators to determine the functional performance evaluation parameters of the vehicle under test in different external sound scenarios. Based on the functional performance evaluation parameters corresponding to different target sound scenarios, the acoustic performance of the vehicle under test is comprehensively evaluated to determine the acoustic adaptability of the vehicle under test in multi-dimensional combined sound scenarios. Based on the acoustic adaptability and the functional performance evaluation parameters corresponding to each target acoustic scenario, the automotive acoustic evaluation results are generated. The automotive acoustic evaluation results include at least one of the following: functional performance evaluation results under different vehicle exterior sound scenarios, acoustic environment adaptability evaluation results, and acoustic function information to be optimized.

10. A vehicle evaluation system based on multi-dimensional combined sound scenes, used to apply the vehicle evaluation method based on multi-dimensional combined sound scenes as described in any one of claims 1-9, characterized in that, include: The vehicle exterior sound environment acquisition and classification module is configured to acquire vehicle exterior sound environment data during actual vehicle use and classify the vehicle exterior sound environment data according to preset influencing factors. The multi-dimensional sound scene construction module is configured to combine and match preset influencing factors based on the classified and processed vehicle exterior sound environment data to generate multiple multi-dimensional combined vehicle exterior sound scenes, and to establish a vehicle exterior sound scene library based on the acoustic feature parameters corresponding to each multi-dimensional combined vehicle exterior sound scene. The sound field reconstruction module is configured to determine the target sound scene from the vehicle exterior sound scene library according to the target evaluation requirements, and reconstruct the vehicle exterior sound environment based on the acoustic feature parameters corresponding to the target sound scene to generate a simulated vehicle exterior sound field environment that matches the target sound scene. The vehicle function response acquisition module is configured to place the vehicle under test in the simulated external sound field environment and acquire the function response data of the vehicle under test in the target sound scene; wherein, the function response data includes at least one of voice interaction response data, communication response data and audio playback response data; The correlation evaluation module is configured to establish a correlation between the external sound scene and the vehicle's functional performance based on the acoustic feature parameters corresponding to the target sound scene and the functional response data, and to evaluate the acoustic performance of the vehicle under test based on the correlation to generate automotive acoustic evaluation results.

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