Vehicle noise reduction method, device, equipment, medium, program product and vehicle

Abstract

The application relates to a vehicle noise reduction method, device, equipment, medium, program product and vehicle, wherein a target noise reduction parameter is determined according to driving environment information of the vehicle; and noise reduction processing is performed according to the target noise reduction parameter. The application can effectively improve the noise reduction effect of the vehicle and improve the user experience.

Description

Technical Field

[0001] This application relates to the field of vehicle noise reduction, and more particularly to a vehicle noise reduction method, device, equipment, medium, program product, and vehicle. Background Technology

[0002] With the rapid popularization of new energy vehicles and the rapid development of digitalization and intelligence, the NVH (Noise, Vibration, and Harshness) performance of automobiles has become one of the important indicators for measuring the ride comfort of automobiles. In order to improve the NVH performance of automobiles, active noise cancellation is currently carried out by collecting noise. However, complex road conditions ahead can affect vehicle noise cancellation, and using relatively fixed noise cancellation solutions can lead to less than ideal noise cancellation effects. Summary of the Invention

[0003] This application provides a vehicle noise reduction method, apparatus, device, medium, program product, and vehicle, which improves the vehicle noise reduction effect and at least partially solves the above-mentioned technical problems.

[0004] To achieve the above objectives, according to a first aspect of this application, a vehicle noise reduction method is provided for use in a vehicle, the vehicle noise reduction method comprising:

[0005] Determine the target noise reduction parameters based on the vehicle's driving environment information;

[0006] Noise reduction processing is performed based on the target noise reduction parameters.

[0007] According to a second aspect of this application, an electronic device is provided for use in a vehicle, the electronic device comprising:

[0008] The determination unit is used to determine the target noise reduction parameters based on the vehicle's driving environment information;

[0009] The noise reduction unit is used to perform noise reduction processing based on the target noise reduction parameters.

[0010] According to a third aspect of this application, an electronic device is also provided, which includes at least two different noise measurement devices, a processor, and a memory, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of any of the above methods.

[0011] According to a fourth aspect of this application, a computer-readable storage medium is also provided, comprising a computer program that, when run on an electronic device, causes the electronic device to perform the steps of any of the methods described above.

[0012] According to a fifth aspect of this application, a computer program product is also provided, comprising a computer program stored in a computer-readable storage medium; when a processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, causing the electronic device to perform the steps of any of the methods described above.

[0013] The vehicle noise reduction method provided in this application is applied to vehicles. It determines target noise reduction parameters based on the vehicle's driving environment information and performs noise reduction processing based on these parameters. By selecting appropriate target noise reduction parameters based on the vehicle's driving environment information, the vehicle noise reduction effect can be improved, thus enhancing the user experience.

[0014] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] To gain a more complete understanding of this application and its beneficial effects, the following description will be provided in conjunction with the accompanying drawings, wherein the same reference numerals in the following description denote the same parts.

[0017] Figure 1 This is a flowchart illustrating one embodiment of the vehicle noise reduction method provided in this invention.

[0018] Figure 2 This is a schematic diagram of the structure of the vehicle noise reduction system provided in an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of the arrangement of the noise measurement device for a vehicle provided in an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of various driving environment information provided in the embodiments of the present invention;

[0021] Figure 5 This is a framework diagram of the vehicle noise reduction system provided in the embodiments of the present invention;

[0022] Figure 6 This is a flowchart of vehicle noise reduction processing provided in an embodiment of the present invention;

[0023] Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of the present invention;

[0024] Figure 8 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the protection scope of this application.

[0026] With the rapid popularization of new energy vehicles and the rapid development of digitalization and intelligence, the NVH (Noise, Vibration, and Harshness) performance of automobiles has become one of the important indicators for measuring vehicle ride comfort. To improve the NVH performance of automobiles, the mainstream noise reduction methods include passive noise reduction through measures such as increasing the stiffness and mass of sheet metal components and laying sound-absorbing, sound-insulating, and damping materials. However, these solutions still have relatively poor noise suppression effects on vehicles.

[0027] Therefore, an active noise control technology (Road Noise Cancellation, RNC) that can effectively suppress low-frequency road noise has been proposed. RNC uses an accelerometer mounted on the vehicle chassis to collect road noise vibration as a reference signal, and a microphone mounted inside the vehicle to collect real-time road noise inside the vehicle as an error signal. The reverse noise is emitted through the vehicle's speakers to reduce road noise at the microphone.

[0028] However, the inventors discovered that in the face of complex vehicle driving environments, road conditions can affect vehicle noise reduction, and using a relatively fixed noise reduction scheme can lead to less than ideal noise reduction results.

[0029] Specifically, the vibration point that best reflects road noise may change, while the installation position of the acceleration sensor, which is used as a noise measurement device, is generally fixed, which may result in inaccurate noise measurement and poor vehicle noise reduction effect.

[0030] To address the aforementioned issues, this application proposes a vehicle noise reduction method, apparatus, device, medium, program product, and vehicle. This application proposes selecting appropriate target noise reduction parameters based on vehicle driving environment information to improve vehicle noise reduction performance and enhance user experience.

[0031] Specifically, the vehicle noise reduction method in this application can be applied to vehicles, and the subject performing the vehicle noise reduction method can be a vehicle, such as a car, an electric vehicle, or a hybrid vehicle.

[0032] The following sections will use the vehicle as an example to illustrate the implementation of the vehicle noise reduction method, and will provide a detailed description of each embodiment.

[0033] Correspondingly, such as Figure 1 As shown, vehicle noise reduction methods may include the following steps:

[0034] S10. Determine the target noise reduction parameters based on the vehicle's driving environment information;

[0035] S20. Perform noise reduction processing according to the target noise reduction parameters.

[0036] In this embodiment, the vehicle's driving environment information refers to the information about the environment in which the vehicle is driving, including road surface information or road slope information, such as road surface smoothness, road surface type, slope value, or slope type. Different driving environments cause changes in the vehicle's vibration level and driving posture, leading to changes in the vehicle's noise reduction effect. Therefore, appropriate target noise reduction parameters are selected based on the driving environment information for noise reduction processing.

[0037] By selecting appropriate target noise reduction parameters based on vehicle driving environment information, the noise reduction effect of the vehicle can be improved, thus enhancing the user experience.

[0038] In some embodiments, the driving environment information includes road information, which includes road surface information and / or slope information.

[0039] In this embodiment, the driving environment information includes road information, which is information related to the road ahead of the vehicle. Road information includes pavement information and / or slope information. Pavement information characterizes the smoothness of the road ahead, and slope information characterizes the gradient of the road ahead. In this embodiment, the driving environment information may include pavement information and / or slope information of the road ahead. Pavement information may refer to the type of road surface ahead, and slope information may refer to the type of road surface ahead, or pavement information and slope information may be specific data values, etc. Road information, and the pavement information and / or slope information included in it, are the main factors affecting vehicle noise reduction. Therefore, determining the target noise reduction parameters based on the road information and its included pavement information and / or slope information can further improve the noise reduction effect.

[0040] In some embodiments, determining the target noise reduction parameters based on the vehicle's driving environment information further includes:

[0041] Visual data of the road ahead of the vehicle is collected using at least two types of sensors.

[0042] Based on the visual data collected by the at least two sensing devices, determine the road information of the road ahead.

[0043] In this embodiment, the vehicle is equipped with at least two types of sensors, which allow the vehicle to acquire information about the driving environment ahead. These sensors may include binocular cameras and / or lidar, enabling the collection of visual data from the front of the vehicle. At least two types of visual data are available, and based on the visual data collected by these sensors, accurate road information can be obtained.

[0044] Optionally, in this embodiment, the vehicle includes two sensing devices: a binocular camera and a lidar. The visual data includes image data and / or point cloud data. The vehicle can acquire image data of the road ahead through the binocular camera and point cloud data of the road ahead through the lidar. The image data and / or point cloud data collected by the vehicle's sensing devices include image data and / or point cloud data of the road ahead. By processing and analyzing the two types of visual data, image data and point cloud data, road information can be obtained. Furthermore, based on the image data and / or point cloud data of the road ahead, the road surface information and / or slope information of the road ahead can be determined.

[0045] In one embodiment, determining road information of the road ahead based on visual data collected by the at least two sensing devices includes:

[0046] The visual data collected by the at least two sensing devices are fused from multiple sources and feature extracted to obtain road features;

[0047] The road features are input into a pre-trained neural network model to determine the road information of the road ahead.

[0048] In this embodiment, during the pre-training phase, a neural network model capable of predicting road information ahead can be trained. After acquiring at least two types of visual data through at least two types of sensing devices, the at least two types of visual data are fused from multiple sources and feature extracted to obtain road features of the road ahead. These road features are then input into the pre-trained neural network model to predict road information ahead, including road surface information and / or slope information.

[0049] In one embodiment, noise reduction processing is performed based on the target noise reduction parameters, including:

[0050] Based on the driving environment information and the preset mapping relationship, the target noise reduction parameters are determined. The preset mapping relationship includes the mapping relationship between various driving environment information and various noise reduction parameters.

[0051] In this implementation, during the pre-training phase, a preset mapping relationship between different driving environment information, i.e., road surface information and / or slope information, and noise reduction parameters can be determined. This preset mapping relationship includes mapping relationships between various driving environment information and various noise reduction parameters. For example, different road surface types and different slope information can be preset to set different driving environment information, referring to... Figure 4 Road surface types can be categorized as follows: I: cobblestone road, II: type B twisted road, III: pothole road, IV: bumpy road, and V: stone road. Slope types are categorized as: A: gentle slope, B: medium slope, C: steep slope, D: sharp slope, and E: reverse slope. Combinations of different road surface and slope types yield various driving environment information. During the pre-training phase, each driving environment information is tested under specific driving conditions. For each driving environment information, the coherence between different noise reduction parameters and the driving environment information is obtained. One or more noise reduction parameters with the highest coherence are identified and correlated with the driving environment information to obtain a preset mapping relationship. This preset mapping relationship is then queried to determine the noise reduction parameter corresponding to the currently identified driving environment information as the target noise reduction parameter.

[0052] In one embodiment, the vehicle includes at least two different noise measurement devices, and the target noise reduction parameters include target noise measurement device information;

[0053] The noise reduction process based on the target noise reduction parameters includes:

[0054] Based on the target noise measurement device information, a target noise measurement device is determined from at least two noise measurement devices;

[0055] Noise reduction processing is performed based on the noise information collected by the target noise measurement device.

[0056] In the face of complex vehicle driving environments, the vibration points, noise sources, and noise types that best reflect road noise may change. However, the accelerometer, which is used as a noise measurement device, is generally fixed, especially its position. This may result in the inability to accurately measure noise information that reflects vehicle noise, and the vehicle noise reduction effect is still poor.

[0057] Therefore, in this embodiment, at least two different noise measurement devices are installed on the vehicle. The at least two different noise measurement devices include at least one difference in installation location and equipment type. The driving environment information can characterize the changes in the vibration point, noise source, and noise type of the current road noise. Based on the vehicle's driving environment information, a suitable target noise measurement device needs to be determined from the at least two different noise measurement devices to collect the vehicle's noise. Noise reduction processing is performed based on the noise information collected by the target noise measurement device, thereby enabling more accurate noise reduction and improving the noise reduction effect.

[0058] Based on the above design, the target noise reduction parameters determined according to the driving environment information include target noise measurement device information. The target noise measurement device information can point to at least one of the at least two different noise measurement devices installed on the vehicle. The target noise measurement device information can include at least one of the installation location, device type, and device identification. The device type includes at least one of the acceleration sensor, vibration sensor, and microphone sensor.

[0059] It should be noted that all noise measurement devices can collect noise information, which can include vibration signals, sound signals, noise levels, and noise types. Different noise measurement devices can reflect vehicle noise to varying degrees. The target noise measurement device, however, is the one among the vehicle's multiple noise measurement devices that best reflects vehicle noise under the current driving environment. That is, the noise information it collects is more accurate than the noise parameters collected by other devices. Therefore, using the noise information collected by the target noise measurement device as a noise reduction reference allows for more accurate and targeted noise reduction, achieving a better noise reduction effect. For example, the noise information can be used to obtain a reference signal for vehicle noise, forming and playing an inverse signal opposite to the noise to cancel it out, achieving a better noise reduction effect.

[0060] In the technical solution disclosed in this embodiment, based on the discovery that the vibration point that best reflects road noise changes, at least two different noise measurement devices are installed on the vehicle. When noise reduction of the vehicle is required, a suitable target noise measurement device is selected according to the vehicle driving environment information to collect noise information that better reflects vehicle noise for noise reduction, so as to ensure a better noise reduction effect. Therefore, the vehicle noise reduction effect can be improved and the user experience can be enhanced.

[0061] In some specific embodiments, considering that the vibration point that best reflects road noise changes more significantly under different driving environments, and that this change leads to a change in the optimal noise measurement location, at least two different noise measurement devices in this embodiment differ in their installation positions. (Refer to...) Figure 2 Multiple acceleration sensors are installed in different locations. Driving environment information reflects changes in the optimal noise measurement location; therefore, the target noise measurement device determined based on this information is the closest noise reduction location to the optimal measurement position. Understandably, because the installation location of the noise measurement devices is relatively fixed, the target noise measurement device may not be at the actual optimal measurement position, but it is closer to that optimal position than other noise measurement devices. The noise information collected by the target noise measurement device can more accurately reflect the current vehicle noise level.

[0062] In one embodiment, the vehicle includes at least two noise measurement zones, each including the at least two different noise measurement devices.

[0063] In this embodiment, since the interior space of the vehicle is relatively large and the noise heard at different locations varies, multiple noise measurement zones can be set up within the vehicle settings according to the needs of the vehicle users. For each noise measurement zone, at least two different noise measurement devices are set up within each noise measurement zone. Based on the driving environment information, at least one target noise measurement device can be determined from each noise measurement zone.

[0064] Understandably, target noise measurement devices within each noise measurement area can be grouped into a target noise measurement device group. During noise reduction, the noise information collected by each target noise measurement device within this group can be fused, and then noise reduction processing can be performed based on the fused noise information. Alternatively, for each noise measurement area, noise information collected by the target noise measurement devices within that area can be used to characterize the vehicle noise within that area, and then noise reduction processing can be performed on that area.

[0065] Reference Figure 2 The vehicle includes at least two noise measurement zones, corresponding to the driver's side, the passenger side, and both sides of the rear seats. Each noise measurement zone is equipped with multiple accelerometers to collect vibration signals as noise information, error sensors to collect residual noise as error signals, and secondary speakers to emit secondary noise. For each noise measurement zone, based on the vibration signals collected by the accelerometers within that zone, an active noise reduction algorithm controls the secondary speakers to emit sound, thereby reducing noise in the secondary channel between the secondary speakers and the error sensors within the noise measurement zone. Furthermore, the active noise reduction algorithm used in that noise measurement zone can be adjusted based on the error signals collected by the error sensors to achieve better noise reduction results.

[0066] In this way, multiple different noise measurement devices are set up in various noise measurement areas on the vehicle that require noise reduction. By using driving environment information to determine the target noise measurement device in each noise measurement area, the vehicle noise in each noise measurement area can be more accurately characterized through noise information, so as to carry out noise reduction more meticulously and improve the noise reduction effect.

[0067] Optionally, the target noise reduction information includes at least one of installation location, equipment type, and equipment identification. Based on the target noise reduction information, a noise measurement device that meets the target noise measurement device information can be selected from each noise measurement area as the target noise measurement device for that noise measurement area.

[0068] Furthermore, the noise measurement devices within different noise measurement areas are symmetrically arranged relative to the vehicle's center, and the noise measurement areas themselves are also symmetrically arranged relative to the vehicle's center. This ensures that the installation locations and equipment types of the noise measurement devices within each noise measurement area are common. Consequently, under the same driving environment information, the positions of the target noise measurement devices within each noise measurement area are also symmetrically arranged relative to the vehicle's center. This allows the target noise measurement device to be determined from all noise measurement areas at once based on a single target noise measurement information corresponding to the driving environment information.

[0069] Alternatively, after identifying the target noise measurement device within at least one noise measurement region, this symmetrical relationship can be used to identify the target noise measurement device within other noise measurement regions. This can reduce the cost of determining the preset mapping relationship during the pre-training phase and improve algorithm efficiency.

[0070] To better understand, a specific application scenario is provided below for reference. Figure 3 Optionally, based on the vehicle's noise reduction requirements and the user's seating position, multiple noise measurement zones are pre-set, corresponding to the driver's side, passenger's side, and both sides of the rear seats. Within each noise measurement zone, three accelerometers at different locations are installed as noise measurement devices. These symmetrical accelerometers can form accelerometer group 1, accelerometer group 2, and accelerometer group 3. During driving, if the installation location of the target noise measurement device is determined to be near the outer edge of the vehicle based on the acquired driving environment information, then accelerometer group 3 can be uniformly selected to collect noise information for noise reduction processing.

[0071] In one embodiment, the noise reduction processing based on the noise information collected by the target noise measurement device includes:

[0072] The noise information is input into the active noise reduction algorithm to obtain inverse noise information;

[0073] The vehicle's speakers are controlled to emit sound based on the inverse noise information for noise reduction processing.

[0074] In this embodiment, the noise reduction system employs an active noise reduction algorithm. The reference signal for active noise reduction is the noise information. Specifically, the active noise reduction process is as follows: After determining the target noise measurement device, this device is effective for a certain period of time. In this embodiment, the target noise measurement device is the optimal noise measurement device for the vehicle within a preset time. Therefore, within the preset time, the target noise measurement device can collect noise information at the vehicle's location. This noise information can be used as a reference signal. After processing by the active noise reduction algorithm, inverse noise information can be obtained. Based on this inverse noise information, the speaker is controlled to emit sound. It can be understood that the sound signal emitted based on the inverse noise information is essentially the opposite of the vehicle noise and can cancel out the vehicle noise, thereby achieving active noise reduction and improving the noise reduction effect.

[0075] More specifically, refer to Figure 2 The noise measurement devices installed on the vehicle are all acceleration sensors. Each noise measurement device can be an acceleration sensor, and the target noise measurement device can be a target acceleration sensor. These acceleration sensors can be installed on the vehicle chassis, specifically near the suspension or wheels. They can directly sense the vibrations that generate vehicle noise, which is mainly caused by the vibration process corresponding to this vibration signal. Using this vibration signal as noise information provides a more direct and complete characterization of vehicle noise. These acceleration sensors are installed on the vehicle chassis in different locations.

[0076] Reference Figure 5 By acquiring at least two types of visual data through at least two types of vehicle sensors (such as binocular cameras and LiDAR), and performing multi-source fusion and feature extraction on the at least two types of visual data, a neural network model can predict the road surface and slope information ahead. Based on a preset mapping relationship, a target noise measurement device is selected. There can be multiple target noise measurement devices, and these devices can be, for example, […]. Figure 3 The noise information collected by one of the acceleration sensor groups shown is the vibration signal at the chassis location. This vibration signal is the main source of vehicle noise and can characterize vehicle noise. The vibration signal collected by each acceleration sensor in the acceleration sensor group is used as a reference signal input to the active noise reduction algorithm to achieve better noise reduction effect.

[0077] In one embodiment, the method may further include:

[0078] The step of determining the target noise reduction parameters based on the vehicle's driving environment information is performed at preset time intervals.

[0079] In this embodiment, since the driving environment of the vehicle is constantly changing during operation, the step of determining the target noise reduction parameters based on the vehicle's driving environment information can be performed at preset time intervals. Specifically, driving environment information can be acquired at preset time intervals, and the target noise reduction parameters can be determined based on the latest acquired driving environment information for noise reduction processing. Compared to real-time acquisition of driving environment information and real-time adjustment of target noise reduction parameters, this embodiment only acquires driving environment information and adjusts target noise reduction parameters at preset time intervals. This reduces the computational power requirement while ensuring better target noise reduction parameters, improving the robustness of the noise reduction system, and further enhancing the vehicle noise reduction effect.

[0080] In one embodiment, the method further includes:

[0081] If the vehicle's speed exceeds a preset speed, then the step of determining the target noise reduction parameters based on the vehicle's driving environment information is executed.

[0082] In this embodiment, vehicle noise has minimal impact when the vehicle speed is below a certain threshold. Therefore, the vehicle speed is acquired during operation. When the vehicle speed exceeds a preset speed, the vehicle's driving environment information needs to be reacquired to adjust the noise reduction parameters accordingly, ensuring better noise reduction performance. If the vehicle speed is below the preset speed, the target noise reduction parameters are not updated, or noise reduction may not be necessary until the vehicle speed exceeds the preset speed. This further reduces computational requirements, improves the robustness of the noise reduction system, and enhances the vehicle noise reduction effect.

[0083] Optionally, it is determined whether the vehicle speed exceeds a preset speed. If the vehicle speed exceeds the preset speed, the step of determining the target noise reduction parameters based on the vehicle's driving environment information is executed. After a preset time interval, the step of determining whether the vehicle speed exceeds the preset speed is executed again to determine whether noise reduction needs to continue.

[0084] To better understand, another specific application scenario is provided below, for reference. Figure 6 :

[0085] After the vehicle starts or during operation, the vehicle's speed is acquired to determine if it exceeds a preset speed V. The preset speed V can be 30 km / h. For most vehicle models, road noise has a relatively small impact when the speed is below 30 km / h, so noise reduction is unnecessary. If the speed is below 30 km / h, the binocular camera and LiDAR are not used to acquire driving environment information to determine the target noise reduction parameters. If the speed exceeds 30 km / h, the binocular camera and LiDAR are activated to collect image data and point cloud data of the road ahead. After multi-source fusion and feature extraction, the data is input into a neural network model to predict the road surface and slope information ahead. Combined with the preset mapping relationship stored in the database during the pre-training stage, the target noise reduction parameters are determined to be the target acceleration sensor group in each noise measurement area. Then, the active noise reduction algorithm is activated, a time threshold τ is set, and the timer is T=0. The vibration signal collected by the activated target acceleration sensor group is used as a reference signal for active noise reduction. When the time T reaches the threshold τ, the vehicle speed V can be re-evaluated to see if it exceeds 30 km / h, and the above operation is repeated.

[0086] In some other embodiments, if the vehicle's speed does not exceed a preset speed, the noise measurement device information corresponding to the preset noise measurement device is set as the target noise reduction parameter, and the step of performing noise reduction processing according to the target noise reduction parameter is executed.

[0087] The inventors also discovered that when the vehicle speed is below a certain threshold, the impact of vehicle noise is minimal, and the optimal noise measurement position does not change significantly. Therefore, during vehicle operation, the vehicle speed is acquired. When the vehicle speed exceeds a preset speed, it is necessary to acquire the vehicle's driving environment information to adjust the target noise measurement device for noise reduction in a timely manner, ensuring better noise reduction performance. If the vehicle speed does not exceed the preset speed, a fixed noise measurement device can be used for noise reduction. This involves setting a pre-determined noise measurement device for noise reduction as the target noise measurement device, and using the noise parameters collected by this device as noise information for noise reduction processing. It should be noted that there can be multiple preset noise measurement devices, including at least one preset noise measurement device in each noise measurement area, for example, selecting... Figure 3 The image shows a group of acceleration sensors. This ensures the stability of noise reduction, further reduces the computational requirements, improves the robustness of the noise reduction system, and further enhances the vehicle's noise reduction effect.

[0088] This embodiment also provides an electronic device, which can be specifically integrated into a vehicle, such as... Figure 7 As shown, the electronic device may include:

[0089] The determining unit 1001 is used to determine the target noise reduction parameters based on the vehicle's driving environment information;

[0090] The noise reduction unit 1002 is used to perform noise reduction processing according to the target noise reduction parameters.

[0091] Optionally, the driving environment information includes road information, which includes road surface information and / or slope information.

[0092] Optionally, the determining unit 1001 is further configured to:

[0093] Visual data of the road ahead of the vehicle is collected using at least two types of sensors.

[0094] Based on the visual data collected by the at least two sensing devices, determine the road information of the road ahead.

[0095] Optionally, the determining unit 1001 is further configured to:

[0096] The visual data collected by the at least two sensing devices are fused from multiple sources and feature extracted to obtain road features;

[0097] The road features are input into a pre-trained neural network model to determine the road information of the road ahead.

[0098] Optionally, the sensing device includes a binocular camera and / or a lidar.

[0099] Optionally, the noise reduction unit 1002 is also used for:

[0100] Based on the driving environment information and the preset mapping relationship, the target noise reduction parameters are determined. The preset mapping relationship includes the mapping relationship between various driving environment information and various noise reduction parameters.

[0101] Optionally, the vehicle includes at least two different noise measurement devices, the target noise reduction parameters include target noise measurement device information, and the noise reduction unit 1002 is further used for:

[0102] Based on the target noise measurement device information, a target noise measurement device is determined from at least two noise measurement devices;

[0103] Noise reduction processing is performed based on the noise information collected by the target noise measurement device.

[0104] Optionally, the noise reduction unit 1002 is also used for:

[0105] The noise information is input into the active noise reduction algorithm to obtain inverse noise information;

[0106] The vehicle's speakers are controlled to emit sound based on the inverse noise information for noise reduction processing.

[0107] Optionally, the vehicle includes at least two noise measurement zones, and each noise measurement zone includes the at least two different noise measurement devices.

[0108] Optionally, the target noise measurement device information includes at least one of the following: installation location, device type, and device identifier.

[0109] Optionally, the at least two different noise measurement devices may differ in at least one of installation location and device type.

[0110] Optionally, the device type includes at least one of an accelerometer, a vibration sensor, and a microphone sensor.

[0111] Optionally, the determining unit 1001 is further configured to:

[0112] The step of determining the target noise reduction parameters based on the vehicle's driving environment information is performed at preset time intervals.

[0113] Optionally, the determining unit 1001 is further configured to:

[0114] If the vehicle's speed exceeds a preset speed, then the step of determining the target noise reduction parameters based on the vehicle's driving environment information is executed.

[0115] This embodiment determines the target noise reduction parameters based on the vehicle's driving environment information; noise reduction processing is then performed based on these parameters. By selecting appropriate target noise reduction parameters based on the vehicle's driving environment information, the noise reduction effect can be improved, thus enhancing the user experience.

[0116] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0117] Accordingly, embodiments of this application also provide an electronic device, such as... Figure 8 As shown, Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 1100 further includes a processor 1101 with one or more processing cores, a memory 1102 with one or more computer-readable storage media, and a computer program stored on the memory 1102 and executable on the processor. The processor 1101 and the memory 1102 are electrically connected. Those skilled in the art will understand that the electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0118] The processor 1101 is the control center of the electronic device 1100. It connects various parts of the electronic device 1100 via various interfaces and lines. By running or loading software programs and / or units stored in the memory 1102, and by calling data stored in the memory 1102, it executes various functions and processes data of the electronic device 1100, thereby providing overall monitoring of the electronic device 1100. The processor 1101 can be a CPU, GPU, network processor (NP), etc., and can implement or execute the methods, steps, and logic diagrams disclosed in the embodiments of this application.

[0119] In this embodiment, the processor 1101 in the electronic device 1100 loads the instructions corresponding to the processes of one or more applications into the memory 1102 according to the following steps, and the processor 1101 runs the applications stored in the memory 1102 to realize various functions, such as:

[0120] Determine the target noise reduction parameters based on the vehicle's driving environment information;

[0121] Noise reduction processing is performed based on the target noise reduction parameters.

[0122] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0123] Optional, such as Figure 8 As shown, the electronic device 1100 also includes: a touch display screen 1103, a radio frequency circuit 1104, an audio circuit 1105, an input unit 1106, and a power supply 1107. The processor 1101 is electrically connected to the touch display screen 1103, the radio frequency circuit 1104, the audio circuit 1105, the input unit 1106, and the power supply 1107. Those skilled in the art will understand that... Figure 8 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0124] The touch display screen 1103 can be used to display a graphical user interface (GUI) and receive operation commands generated by the user interacting with the GUI. The touch display screen 1103 may include a display panel and a touch panel. The display panel can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of the electronic device. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. Optionally, the display panel can be configured using a liquid crystal display (LCD), an organic light-emitting diode (OLED), or other similar devices. The touch panel can be used to collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel), generate corresponding operation commands, and execute the corresponding program according to the operation commands. Optionally, the touch panel may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch location and the signal generated by the touch operation, transmitting the signal to the touch controller. The touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 1101. It can also receive and execute commands from the processor 1101. The touch panel can cover the display panel. When the touch panel detects a touch operation on or near it, it transmits the information to the processor 1101 to determine the type of touch event. Subsequently, the processor 1101 provides corresponding visual output on the display panel based on the type of touch event. In this embodiment, the touch panel and the display panel can be integrated into the touch display screen 1103 to achieve input and output functions. However, in some embodiments, the touch panel and the touch display screen 1103 can be used as two independent components to achieve input and output functions. That is, the touch display screen 1103 can also be used as part of the input unit 1106 to achieve input functions.

[0125] The radio frequency circuit 1104 can be used to transmit and receive radio frequency signals to establish wireless communication with networked medical devices or other electronic devices, and to transmit and receive signals with networked medical devices or other electronic devices.

[0126] Audio circuit 1105 can be used to provide an audio interface between a user and an electronic device via a speaker and a microphone. Audio circuit 1105 can convert received audio data into electrical signals and transmit them to the speaker, where the speaker converts them into sound signals for output. Conversely, the microphone converts the collected sound signals into electrical signals, which are then received by audio circuit 1105, converted back into audio data, and then processed by processor 1101 before being transmitted via radio frequency circuit 1104 to, for example, another electronic device, or output to memory 1102 for further processing. Audio circuit 1105 may also include an earphone jack to provide communication between peripheral headphones and electronic devices.

[0127] The input unit 1106 can be used to receive input numbers, characters, or user characteristic information (such as fingerprints, iris, facial information, etc.), and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control.

[0128] Power supply 1107 is used to supply power to various components of electronic device 1100. Optionally, power supply 1107 can be logically connected to processor 1101 through a power management device, thereby enabling functions such as charging, discharging, and power consumption management through the power management device. Power supply 1107 may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0129] although Figure 8 As not shown in the diagram, the electronic device 1100 may also include a camera, sensor, wireless fidelity module, Bluetooth module, etc., which will not be described in detail here.

[0130] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0131] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0132] Therefore, embodiments of this application provide a computer-readable storage medium storing multiple computer programs. These computer programs can be loaded by a processor to execute any of the vehicle noise reduction methods provided in this application. The computer program can execute the following steps of the vehicle noise reduction method:

[0133] Determine the target noise reduction parameters based on the vehicle's driving environment information;

[0134] Noise reduction processing is performed based on the target noise reduction parameters.

[0135] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0136] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0137] Since the computer-readable storage medium contains a computer program that can implement any of the vehicle noise reduction methods provided in the embodiments of this application, it can execute any of the vehicle noise reduction methods provided in the embodiments of this application. Therefore, the effects are detailed in the preceding embodiments and will not be repeated here.

[0138] In the above descriptions of vehicle noise reduction methods, electronic devices, electronic equipment, computer-readable storage media, computer program products, and vehicles, each embodiment has its own emphasis. Parts not detailed in a particular embodiment can be found in the relevant descriptions of other embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes and beneficial effects of the above-described electronic devices, vehicle noise measurement devices, computer-readable storage media, computer program products, vehicles, and their corresponding units can be referred to the description of the vehicle noise reduction method in the above embodiments, and will not be repeated here.

[0139] The above provides a detailed description of a vehicle noise reduction method, apparatus, device, medium, program product, and vehicle provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A vehicle noise reduction method, characterized in that, Applied to vehicles, the vehicle noise reduction method includes: The target noise reduction parameters are determined based on the vehicle's driving environment information, which includes road information, road surface information and / or slope information, road surface information including road surface smoothness and road surface type, and slope information including slope value or slope type. The vehicle includes at least two different noise measurement devices, and the target noise reduction parameters include target noise measurement device information. Noise reduction processing is performed based on the target noise reduction parameters; The step of determining the target noise reduction parameters based on the vehicle's driving environment information includes: Visual data of the road ahead of the vehicle is collected using at least two types of sensors. Based on the visual data collected by the at least two sensing devices, determine the road information of the road ahead; The noise reduction process based on the target noise reduction parameters includes: Based on the target noise measurement device information, a target noise measurement device is determined from at least two noise measurement devices; Noise reduction processing is performed based on the noise information collected by the target noise measurement device.

2. The vehicle noise reduction method as described in claim 1, characterized in that, Determining road information ahead based on visual data collected by the at least two sensing devices includes: The visual data collected by the at least two sensing devices are fused from multiple sources and feature extracted to obtain road features; The road features are input into a pre-trained neural network model to determine the road information of the road ahead.

3. The vehicle noise reduction method as described in claim 1, characterized in that, The sensing device includes a binocular camera and / or lidar.

4. The vehicle noise reduction method as described in claim 1, characterized in that, The noise reduction process based on the target noise reduction parameters includes: Based on the driving environment information and the preset mapping relationship, the target noise reduction parameters are determined. The preset mapping relationship includes the mapping relationship between various driving environment information and various noise reduction parameters.

5. The vehicle noise reduction method as described in claim 1, characterized in that, The noise reduction process based on the noise information collected by the target noise measurement device includes: The noise information is input into the active noise reduction algorithm to obtain inverse noise information; The vehicle's speakers are controlled to emit sound based on the inverse noise information for noise reduction processing.

6. The vehicle noise reduction method as described in claim 1, characterized in that, The vehicle includes at least two noise measurement zones, and each noise measurement zone includes at least two different noise measurement devices.

7. The vehicle noise reduction method as described in claim 1, characterized in that, The target noise measurement device information includes at least one of the following: installation location, device type, and device identifier.

8. The vehicle noise reduction method as described in claim 1, characterized in that, The at least two different noise measurement devices differ in at least one of the following: installation location and device type.

9. The vehicle noise reduction method as described in claim 8, characterized in that, The device type includes at least one of an accelerometer, a vibration sensor, and a microphone sensor.

10. The vehicle noise reduction method according to any one of claims 1-9, characterized in that, The method further includes: The step of determining the target noise reduction parameters based on the vehicle's driving environment information is performed at preset time intervals.

11. The vehicle noise reduction method according to any one of claims 1-9, characterized in that, The method further includes: If the vehicle's speed exceeds a preset speed, then the step of determining the target noise reduction parameters based on the vehicle's driving environment information is executed.

12. An electronic device, characterized in that, The electronic device, used in vehicles, includes: The determining unit is used to determine target noise reduction parameters based on the vehicle's driving environment information. The driving environment information includes road information, which includes road surface information and / or slope information. The road surface information includes road surface smoothness and road surface type. The slope information includes slope value or slope type. The vehicle includes at least two different noise measurement devices. The target noise reduction parameters include target noise measurement device information. A noise reduction unit is used to perform noise reduction processing based on the target noise reduction parameters; The determining unit is used for: Visual data of the road ahead of the vehicle is collected using at least two types of sensors. Based on the visual data collected by the at least two sensing devices, determine the road information of the road ahead; The noise reduction unit is also used for: Based on the target noise measurement device information, a target noise measurement device is determined from at least two noise measurement devices; Noise reduction processing is performed based on the noise information collected by the target noise measurement device.

13. An electronic device, characterized in that, The device includes a processor connected to a memory storing a computer program, the processor being configured to run the computer program in the memory to perform the vehicle noise reduction method according to any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the vehicle noise reduction method according to any one of claims 1 to 11.

15. A computer program product, characterized in that, It includes a computer program, which is executed by a processor to implement the vehicle noise reduction method according to any one of claims 1 to 11.

16. A vehicle, characterized in that, This includes the electronic device as described in claim 12 or the electronic device as described in claim 13.

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