A cockpit high latency scenario based volume control method, system, and vehicle

Abstract

The application discloses a kind of based on cabin high delay scene volume control method, system and vehicle, method steps include: real-time monitoring user in preset time volume adjustment frequency, when volume exceeds the safety volume threshold, start volume anti-explosion strategy, detect audio signal, determine the normal fluctuation range of audio signal, the abnormal data points are removed to audio signal is intelligently analyzed and filtered, and verification is carried out using filter or machine learning model;Based on adaptive adjustment algorithm, volume setting is adjusted according to user usage habit and environmental noise, control volume smooth reduction, the adaptive adjustment algorithm has user volume preference model built-in.The application can effectively prevent the problem of too large or too small volume caused by improper operation by implementing anti-explosion strategy in the process of optimizing volume setting, so as to ensure the accuracy and stability of volume setting and improve the volume display effect.

Description

Technical Field

[0001] This invention relates to a volume control method, system, and vehicle, and more particularly to a volume control method, system, and vehicle based on a high-latency cockpit scenario. Background Technology

[0002] With the development of modern technology, the application of audio processing technology and intelligent filtering technology is becoming increasingly widespread. Audio processing technology mainly involves the acquisition, processing, transmission, and reproduction of sound signals, and is an indispensable part of modern audio equipment, telephones, televisions, computers, and other devices. Intelligent filtering technology, on the other hand, uses computer algorithms to filter and process input data to improve data quality and efficiency.

[0003] Volume settings and displays typically employ a linear processing approach, adjusting according to a predetermined ratio. To ensure accuracy and stability in both settings and display, anti-explosion strategies and intelligent filtering technologies are usually employed. For example, during volume setting, anti-explosion strategies prevent issues like excessively high or low volumes caused by improper operation. During volume display, intelligent filtering technology filters out unwanted noise, resulting in a clearer and more intuitive volume display.

[0004] However, existing technologies still have some problems and shortcomings in practical applications. For example, in cockpit scenarios, due to the high frequency of volume settings, the controller may not respond in time, leading to stuttering and unresponsiveness. Furthermore, the complexity of volume setting and display processes can cause non-linear anomalies, resulting in non-linear responses. These problems not only affect the user experience but may also impact device security, failing to meet user requirements and urgently needing improvement. Summary of the Invention

[0005] The purpose of this invention is to provide a volume control method, system, and vehicle based on high-latency cockpit scenarios. The first technical problem to be solved is to overcome the nonlinear anomaly in the audio signal. The second technical problem to be solved is to prevent popping sounds. Finally, it ensures the accuracy and stability of volume setting and display, thus overcoming the shortcomings of the existing technology.

[0006] This invention provides the following solution:

[0007] A volume control method for high-latency cockpit scenarios, applied to a volume control system for high-latency cockpit scenarios, comprising:

[0008] Configure the vehicle-mounted device, set a safe volume threshold, monitor the frequency of user volume adjustment within a preset time in real time, and activate the volume explosion prevention strategy when the volume exceeds the safe volume threshold.

[0009] The audio signal is detected, the normal fluctuation range of the audio signal is determined, the audio signal is intelligently analyzed and filtered, data points that exceed the normal fluctuation range are identified as abnormal data points, the abnormal data points are removed, and the filter or machine learning model is applied for verification.

[0010] Based on an adaptive adjustment algorithm, the volume settings are adjusted according to user habits and ambient noise to smoothly reduce the volume. The adaptive adjustment algorithm has a built-in user volume preference model.

[0011] Furthermore, the step of activating the volume anti-explosion strategy when the volume exceeds the safe volume threshold further includes:

[0012] Set a safe volume threshold and a volume adjustment count threshold. Detect the number of times the user adjusts the volume within a certain time period. If the number of volume adjustments within a certain time period exceeds the volume adjustment count threshold, activate the volume explosion prevention strategy.

[0013] Furthermore, it also includes monitoring the audio response time of in-vehicle equipment to determine if there is any delay;

[0014] If there is a delay in the audio response of the in-vehicle equipment, the in-vehicle equipment will be adjusted, the corresponding control parameters will be configured, the audio frequency of the in-vehicle equipment will be reduced, and a completion identifier will be generated.

[0015] Monitor the audio response time of the adjusted in-vehicle equipment and detect the audio response delay time;

[0016] The audio response time of the in-vehicle equipment is monitored and adjusted repeatedly until it falls below the preset threshold.

[0017] Furthermore, the detection of the audio signal, determination of the normal fluctuation range of the audio signal, and intelligent analysis and filtering of the audio signal further include:

[0018] Input the audio signal to be analyzed, and perform non-linear intelligent filtering on the input audio signal to identify and process abnormal data points in the signal;

[0019] A moving average filter is used to perform weighted averaging on the filtered audio signal to achieve data smoothing. Based on the result of the weighted averaging, the remaining outlier data points are further removed, and the audio signal that has been intelligently analyzed and filtered is output.

[0020] Furthermore, the input audio signal to be analyzed undergoes nonlinear intelligent filtering, specifically as follows:

[0021] Receive a set of audio signals that need to be smoothed, identify abnormal data points in the audio signals, and generate the corresponding dataset;

[0022] A preliminary weighted average is performed on the dataset using a moving average filter to obtain preliminary smoothed data;

[0023] Outlier points are identified and removed from the data after the initial weighted average. Based on the weighted average result after removing outlier points, a second weighted average is performed on the data.

[0024] Detect the smoothness of the data after double weighted averaging and output the data after double weighted averaging.

[0025] A volume control system for high-latency cockpit scenarios, used to implement the aforementioned volume control method for high-latency cockpit scenarios, includes:

[0026] The volume explosion prevention strategy activation module configures the vehicle-mounted device, sets a safe volume threshold, monitors the user's volume adjustment frequency within a preset time in real time, and activates the volume explosion prevention strategy when the volume exceeds the safe volume threshold.

[0027] The audio signal intelligent analysis and filtering module detects the audio signal, determines the normal fluctuation range of the audio signal, performs intelligent analysis and filtering on the audio signal, identifies data points that exceed the normal fluctuation range as abnormal data points, removes the abnormal data points, and applies filters or machine learning models for verification.

[0028] The volume adaptive adjustment module, based on an adaptive adjustment algorithm, adjusts the volume settings according to user habits and ambient noise, and controls the volume to decrease smoothly. The adaptive adjustment algorithm has a built-in user volume preference model.

[0029] A smart cockpit, wherein the smart cockpit is equipped with the aforementioned volume control system based on high-latency cockpit scenarios.

[0030] An electronic device includes: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method.

[0031] A computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method.

[0032] A vehicle having the aforementioned intelligent cockpit.

[0033] Compared with the prior art, the present invention has the following advantages:

[0034] This invention optimizes the volume setting process by implementing an explosion-proof strategy, which effectively prevents the volume from being too high or too low due to improper operation. This ensures the accuracy and stability of the volume setting and improves the volume display effect. The non-linear intelligent filtering in the volume display process can filter out some unnecessary noise, making the volume display clearer and more intuitive, and improving the user experience.

[0035] This invention addresses the problem in cockpit scenarios where high volume setting frequencies can cause controllers to fail to respond promptly, resulting in stuttering or unresponsiveness. This invention effectively ensures the real-time performance and smoothness of volume setting and display, avoids non-linear anomalies, effectively solves the non-linear anomalies in audio response, ensures natural and smooth volume setting and display, and further enhances the user experience. Attached Figure Description

[0036] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0037] Figure 1 This is a flowchart of a volume control method based on high-latency cockpit scenarios.

[0038] Figure 1A This is a flowchart of the optimization technical solution for step S4.

[0039] Figure 1B This is a flowchart of the optimization technical solution for step S2.

[0040] Figure 2 This is an architecture diagram of a volume control system based on a high-latency cockpit scenario.

[0041] Figure 3 This is an implementation method of the present invention in a specific application scenario.

[0042] Figure 4 This is a schematic diagram of the electronic device. Detailed Implementation

[0043] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] like Figure 1 The volume control method shown is applied to a volume control system in a high-latency cockpit scenario. It implements a real-time response and feedback mechanism to monitor user actions and respond immediately, ensuring the real-time performance and stability of volume settings and display. The method includes the following steps:

[0045] Step S1: Configure the vehicle-mounted device, set a safe volume threshold, monitor the user's volume adjustment frequency within a preset time in real time, and activate the volume explosion prevention strategy when the volume exceeds the safe volume threshold.

[0046] Step S2: Detect the audio signal, determine the normal fluctuation range of the audio signal, perform intelligent analysis and filtering on the audio signal, identify data points that exceed the normal fluctuation range as abnormal data points, remove the abnormal data points, and apply filters or machine learning models for verification.

[0047] Step S3: Based on the adaptive adjustment algorithm, the volume setting is adjusted according to the user's usage habits and environmental noise to control the volume to decrease smoothly. The adaptive adjustment algorithm has a built-in user volume preference model.

[0048] Steps S1 to S3 describe a method for controlling the volume of an in-vehicle device, which uses intelligent monitoring and adaptive adjustment to ensure that the volume control of the user during driving is both safe and meets personalized needs.

[0049] Steps S1 to S3 configure and monitor the in-vehicle equipment and audio signals. A safe volume threshold is set, and the system ensures that the volume does not exceed this threshold by monitoring the user's volume adjustment frequency in real time. If the volume exceeds the limit, the system will activate an anti-explosion strategy to prevent excessive volume from affecting driving safety.

[0050] Steps S1 to S3 involve intelligent analysis and filtering of the audio signal from the in-vehicle device to eliminate abnormal data points, ensuring the smoothness and accuracy of the volume display. Combined with an adaptive adjustment algorithm, the volume settings are automatically adjusted based on user habits and ambient noise. This adaptive adjustment algorithm incorporates a user volume preference model, enabling a smooth reduction in volume to meet the user's volume needs in different environments.

[0051] Steps S1 to S3 aim to address the issue of providing a personalized volume control experience while ensuring driving safety. In a driving environment, excessively high volume may distract the driver, while excessively low volume may affect the driving experience. The goal is to achieve intelligent monitoring and adaptive adjustment of volume to ensure it remains within a safe range. Furthermore, by configuring technologies such as real-time monitoring, intelligent analysis, adaptive adjustment algorithms, and user preference models, the system meets the user's personalized needs, thereby improving both driving safety and user comfort.

[0052] Preferably, in step S1, activating the volume anti-explosion strategy when the volume exceeds the safe volume threshold further includes:

[0053] Set a safe volume threshold and a volume adjustment count threshold. Detect the number of times the user adjusts the volume within a certain time period. If the number of volume adjustments within a certain time period exceeds the volume adjustment count threshold, activate the volume explosion prevention strategy.

[0054] like Figure 1A As shown, in addition to steps S1 to S3, there is also step S4. Step S4 discloses the monitoring and adjustment process for the audio response time of the in-vehicle device. The purpose is to ensure the timeliness and accuracy of the audio output and avoid poor driving experience or safety hazards caused by delays. Further optimization of step S4 can yield the optimized technical solution for step S4:

[0055] Step S41: Monitor the audio response time of the in-vehicle equipment to determine if there is a delay;

[0056] Step S42: If there is a delay in the audio response of the vehicle-mounted device, adjust the vehicle-mounted device, configure the corresponding control parameters, reduce the audio frequency of the vehicle-mounted device, and generate a completion identifier.

[0057] Step S43: Monitor the audio response time of the adjusted in-vehicle equipment and detect the audio response delay time;

[0058] Step S44: Continuously monitor the audio response time of the vehicle-mounted device after adjustment until the audio response time of the vehicle-mounted device is lower than the preset threshold.

[0059] Steps S41 to S44 dynamically monitor and adjust the audio response performance of the in-vehicle equipment to ensure the real-time performance and reliability of audio output. Addressing potential response delays in audio output, the system effectively monitors and controls the audio response time, ensuring timely audio output and improving driving safety and comfort. Through cyclical monitoring and adjustment, the system adapts to different driving conditions and audio requirements, ultimately achieving an audio response time below a safe threshold. This solves the audio delay problem, avoids impacting the driver's experience, and eliminates potential safety hazards through audio-related means.

[0060] like Figure 1B As shown, preferably, step S2 further includes:

[0061] Step S21: Input the audio signal to be analyzed, and perform non-linear intelligent filtering on the input audio signal to identify and process abnormal data points in the signal.

[0062] Step S22: A moving average filter is used to perform weighted averaging on the filtered audio signal to achieve data smoothing.

[0063] Step S23: Based on the results of the weighted average processing, further remove the remaining abnormal data points and output the audio signal that has been intelligently analyzed and filtered.

[0064] In steps S21 to S23, specific technical means are used to improve the quality and reliability of the audio signal. Specifically, nonlinear intelligent filtering and weighted averaging of moving average filter are used to identify, process and remove abnormal data points in the audio signal, thereby ensuring that the output audio signal is smooth and accurate.

[0065] The optimization solution in step S2 can effectively remove abnormal data points from the audio signal of the vehicle equipment. These abnormal data points may be caused by noise, interference or other unexpected factors. Abnormal data points will affect the quality of the audio signal, cause auditory discomfort, and easily affect the driver or passengers of the vehicle, posing a hidden danger to safe driving.

[0066] The optimization technique in step S2 improves the quality of the audio signal. By using nonlinear intelligent filtering, abnormal data points in the signal can be identified and processed, thereby improving the overall quality of the audio signal and achieving a data smoothing effect. Using a moving average filter for weighted averaging can further smooth the data, reduce audio signal fluctuations, and improve signal stability.

[0067] The optimization solution in step S2 also removes the remaining abnormal data points during the data smoothing process. By using weighted averaging, it ensures that the output audio signal is as close to the ideal state as possible and outputs a stable and accurate audio signal. Finally, the output audio signal is intelligently analyzed and filtered to ensure the smoothness and accuracy of the signal, thereby improving the user's listening experience.

[0068] For example, another optimized technical solution in step S2 can be applied in the following scenarios:

[0069] When performing nonlinear intelligent filtering on the input audio signal, the system receives a set of audio signals that need to be smoothed, identifies abnormal data points in the audio signals, and generates the corresponding dataset.

[0070] A preliminary weighted average is performed on the dataset using a moving average filter to obtain preliminary smoothed data;

[0071] Outlier points are identified and removed from the data after the initial weighted average. Based on the weighted average result after removing outlier points, a second weighted average is performed on the data.

[0072] Detect the smoothness of the data after double weighted averaging and output the data after double weighted averaging.

[0073] For the purpose of simplicity, the method steps disclosed in the above embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0074] Any flowchart or other description of a process or method can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process. Furthermore, the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed and implemented not in the order shown or discussed, including substantially simultaneously or in reverse order according to the functions involved, or by executing computer instructions and implementing corresponding functions according to program structures such as loops, branches, etc., as will naturally be understood by those skilled in the art when practicing embodiments of the invention.

[0075] like Figure 2 The volume control system shown is for implementing the volume control method for high-latency cockpit scenarios, and includes:

[0076] The volume explosion prevention strategy activation module configures the vehicle-mounted device, sets a safe volume threshold, monitors the user's volume adjustment frequency within a preset time in real time, and activates the volume explosion prevention strategy when the volume exceeds the safe volume threshold.

[0077] The audio signal intelligent analysis and filtering module detects audio signals, performs intelligent analysis and filtering on the audio signals, and removes abnormal data points;

[0078] The volume adaptive adjustment module, based on an adaptive adjustment algorithm, adjusts the volume settings according to user habits and ambient noise, and controls the volume to decrease smoothly. The adaptive adjustment algorithm has a built-in user volume preference model.

[0079] The implementation methods of the system described above are merely illustrative. For example, the various functional modules, units, or subsystems within the system may or may not be physically separate, or they may or may not be physical units; that is, they may be located in the same place or distributed across multiple different systems and their subsystems or modules. Those skilled in the art can select some or all of the functional modules, units, or subsystems to achieve the objectives of the embodiments of the present invention according to actual needs. Those skilled in the art can understand and implement the above-described situations without any creative effort.

[0080] like Figure 3 The embodiments of the present invention shown are implemented in specific application scenarios. The solution provided in this embodiment includes the following steps:

[0081] Step 1: Employ an anti-explosion strategy during volume setting. Specifically, set a safety threshold. When the number of volume settings made by the user exceeds this threshold within a certain time period (e.g., within 1 second), the system will automatically reduce the volume setting frequency to prevent the controller from failing to respond in time, thereby reducing lag and unresponsiveness. For example, if the safety threshold is set to 5 times / second, then if the user makes more than 6 volume settings within 1 second, the system will automatically reduce the volume setting frequency to 4 times / second.

[0082] Step Two: During volume display, non-linear intelligent filtering is employed. Specifically, the system intelligently analyzes and filters the volume display data, identifying and eliminating abnormal data points to ensure smooth and aesthetically pleasing volume changes and avoid non-linear anomalies. For example, the system can use a moving average filter to perform a weighted average of the past five data points to obtain the current data point, thereby achieving non-linear intelligent filtering.

[0083] Step 3: In the cockpit scenario, a real-time response and feedback mechanism is employed. Specifically, the system monitors and responds to the user's volume setting operations in real time, ensuring the accuracy and stability of volume settings and displays, while avoiding non-linear anomalies in the response to setting results. For example, the system can set a response time threshold (e.g., 0.5 seconds). If the user performs a volume setting operation within this threshold time, the system will respond immediately and make the corresponding settings.

[0084] Step 4: Employ an adaptive adjustment algorithm. Specifically, the system will automatically adjust the volume settings and display based on factors such as user habits and ambient noise. For example, the system can record the user's volume setting history over a period of time and use machine learning algorithms to predict the user's volume setting preferences in the current environment, thereby achieving adaptive adjustment.

[0085] Explanation of the explosion-proof strategy principle in this embodiment: This embodiment provides an explosion-proof strategy to prevent abnormal response of the volume controller due to excessive operation frequency. The main technical problem it addresses is that when a user adjusts the volume of the vehicle device, if the operation frequency is too high, the controller may not be able to respond in time, resulting in system lag or no response, which affects the user experience.

[0086] This embodiment applies a specific explosion-proof strategy, which sets a safety threshold to control the frequency of volume settings. When the number of times the user sets the volume exceeds the preset safety threshold within a certain period of time, the system will automatically reduce the frequency of volume settings to ensure the stable response of the controller.

[0087] Specifically, the explosion-proof strategy of this embodiment includes the following steps:

[0088] Set a safe threshold for the volume setting, for example, 5 times / second.

[0089] Monitor the number of times the user adjusts the volume within a unit of time (e.g., between 1 and 3 seconds).

[0090] When the number of times the system detects that the setting frequency exceeds the safety threshold, the vehicle system automatically adjusts the setting frequency. For example, the vehicle system automatically adjusts the setting frequency to reduce it to 4 times / second to 8 times / second.

[0091] The algorithm enables real-time monitoring and automatic adjustment of user operation frequency, ensuring the stability and smoothness of system response.

[0092] By implementing the explosion-proof strategy described above, system anomalies caused by excessive user operation frequency can be effectively avoided. Intelligent filtering optimizes volume display data, achieving a smooth and aesthetically pleasing non-linear intelligent filtering effect, thereby improving the stability of volume control and user experience.

[0093] Explanation of the nonlinear intelligent filtering technology in this embodiment:

[0094] To address the issue that existing volume display systems may exhibit non-linear changes in volume display due to the instability of data acquisition, this embodiment provides a non-linear intelligent filtering method based on an explosion-proof strategy. By intelligently analyzing and filtering the volume display data, abnormal data points are eliminated, ensuring the smoothness and accuracy of the volume display.

[0095] The nonlinear intelligent filtering method in explosion-proof strategies includes the following steps:

[0096] A moving average filter is used to perform weighted averaging on the volume display data.

[0097] Analyze a number of past data points (e.g., 5 to 10) to identify and remove outlier data points.

[0098] Real-time analysis and intelligent filtering of data points can be achieved through algorithms to ensure the continuity and smoothness of volume display. For example, sliding window averaging, Kalman filtering, weighted moving average, peak detection, and other algorithms can be used to perform real-time analysis and intelligent filtering of data points.

[0099] In scenarios where it is necessary to calculate the average value of data points within a certain time window to achieve continuity and smoothness in volume display, a sliding window averaging algorithm can be used.

[0100] In scenarios requiring high accuracy and subject to noise interference, the Kalman filter algorithm can be used to obtain more accurate estimation results by weighted fusion of the current observation and the previous state.

[0101] In scenarios where a fast response time and a more stable volume display are required, a weighted moving average algorithm can be used, giving higher weight to the most recent observations and gradually reducing the weight of older observations.

[0102] In scenarios where there are too many peak points or outliers in the detected data points, peak detection algorithms can be used to remove peak points or outliers, and peak detection can be performed based on thresholds or statistical features to improve the accuracy of data analysis and filtering results.

[0103] The nonlinear intelligent filtering method adopted in this embodiment can significantly improve the stability and aesthetics of the volume display, avoid display problems caused by abnormal data, significantly improve the response speed and accuracy of volume settings, meet the high requirements of users for volume control in the cabin scenario, and enhance the user's driving experience.

[0104] The explosion-proof strategy in this embodiment also involves improvements to the real-time response and feedback mechanism, including the following steps:

[0105] Set a response time threshold, for example, 0.5 seconds.

[0106] Monitors user volume settings in real time.

[0107] When a user's action falls within the response time threshold, the system responds immediately and makes the corresponding settings.

[0108] An adaptive adjustment algorithm enables rapid response and accurate feedback to user actions, ensuring the real-time performance and accuracy of volume settings.

[0109] By adopting the above-mentioned real-time response and feedback mechanism, the response speed and accuracy of volume settings can be significantly improved, meeting users' high requirements for volume control in the cockpit scenario and enhancing the user experience.

[0110] The adaptive adjustment algorithm can automatically adjust the volume settings based on user habits, ambient noise, and other factors to meet the user's personalized needs.

[0111] The adaptive adjustment algorithm includes the following steps:

[0112] Record the user's volume setting history over a period of time, analyze the user's operating habits and preferences, and generate corresponding tracking data and tags;

[0113] Monitor the noise level of the current environment and use machine learning algorithms to predict the user's volume setting preferences in the current environment.

[0114] Based on the prediction results, the volume settings will be automatically adjusted to adapt to the user's needs and changes in the environment.

[0115] Through the aforementioned adaptive adjustment algorithm, intelligent and personalized volume settings can be achieved, reducing the frequency of manual adjustments by users and improving the user experience and satisfaction of the system.

[0116] like Figure 4 As shown, this invention, in addition to providing a volume control method and system for high-latency cockpit scenarios, also provides corresponding electronic devices, storage media, smart cockpits, and vehicles:

[0117] A smart cockpit, wherein the smart cockpit is equipped with the aforementioned volume control system based on high-latency cockpit scenarios.

[0118] An electronic device includes: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method.

[0119] A computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method.

[0120] A vehicle having the aforementioned intelligent cockpit.

[0121] like Figure 4 As shown, device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in read-only memory 602 (ROM) or a computer program loaded from storage unit 608 into random access memory 603 (RAM). The RAM may also store various programs and data required for the operation of device 600. The computing unit 601, ROM, and RAM are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0122] Multiple components in device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0123] The computing unit 601 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit, etc.

[0124] The computing unit 601 includes GPUs, various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any suitable processors, controllers, microcontrollers, etc. The computing unit 601 executes the various methods and processes described above, such as the execution instructions for steps S1 to S4 in the volume control method based on a high-latency cockpit scenario. For example, in some embodiments, the volume control method based on a high-latency cockpit scenario may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by computing unit 601, one or more steps of the volume control method based on a high-latency cockpit scenario described above may be performed. Alternatively, in other embodiments, computing unit 601 may be configured to execute the volume control method based on a high-latency cockpit scenario by any other suitable means (e.g., by means of firmware).

[0125] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other volume control system based on a high-latency cockpit scenario, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented.

[0127] It can be executed entirely on the machine, partially on the machine, or as a standalone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0128] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0129] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0130] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. Digital data communication can be achieved through any form or medium (e.g., ...).

[0131] For example, communication networks are used to connect the components of a system to each other. Examples of communication networks include Local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

[0132] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0133] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0134] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0135] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, any of the embodiments claimed in the claims can be used in any combination of embodiments of the invention.

[0136] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0137] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but this must be based on the premise that those skilled in the art can implement them. When the combination of technical solutions results in contradictions or lack of consistency, the technical solutions should be deemed appropriate.

[0138] When implementing this method, it should be assumed that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0139] All features disclosed in this specification, or steps in all disclosed methods or processes, may be combined in any way, except for mutually exclusive features and / or steps. Any feature disclosed in this specification, unless specifically stated otherwise, may be replaced by other equivalent or similar features. That is, unless specifically stated otherwise, each feature is merely one example of a series of equivalent or similar features. Throughout this specification, the same reference numerals indicate the same elements.

[0140] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the corresponding claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the corresponding claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0141] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A volume control method for high-latency cockpit scenarios, applied to a volume control system for high-latency cockpit scenarios, characterized in that, include: Configure the vehicle-mounted equipment, set a safe volume threshold, monitor the frequency of user volume adjustment within a preset time in real time, and activate the volume explosion prevention strategy when the volume exceeds the safe volume threshold. The audio signal is detected, the normal fluctuation range of the audio signal is determined, the audio signal is intelligently analyzed and filtered, data points that exceed the normal fluctuation range are identified as abnormal data points, the abnormal data points are removed, and the filter or machine learning model is applied for verification. Based on the adaptive adjustment algorithm, the volume setting is adjusted according to user habits and ambient noise, and the volume is smoothly reduced. The adaptive adjustment algorithm has a built-in user volume preference model. The step of activating the volume protection strategy when the volume exceeds the safe volume threshold further includes: Set a safe volume threshold and a volume adjustment count threshold. Detect the number of times the user adjusts the volume within a certain time period. If the number of volume adjustments within a certain time period exceeds the volume adjustment count threshold, activate the volume explosion prevention strategy.

2. The volume control method based on high-latency cockpit scenarios according to claim 1, characterized in that, Also includes: Monitor the audio response time of in-vehicle equipment to determine if there is any delay; If there is a delay in the audio response of the in-vehicle equipment, the in-vehicle equipment will be adjusted, the corresponding control parameters will be configured, the audio frequency of the in-vehicle equipment will be reduced, and a completion identifier will be generated. Monitor the audio response time of the adjusted in-vehicle equipment and detect the audio response delay time; The audio response time of the in-vehicle equipment is monitored and adjusted repeatedly until it falls below the preset threshold.

3. The volume control method based on high-latency cockpit scenarios according to claim 1, characterized in that, The process of detecting the audio signal, determining the normal fluctuation range of the audio signal, and performing intelligent analysis and filtering on the audio signal further includes: Input the audio signal to be analyzed, and perform non-linear intelligent filtering on the input audio signal to identify and process abnormal data points in the signal; A moving average filter is used to perform weighted averaging on the filtered audio signal to achieve data smoothing. Based on the result of the weighted averaging, the remaining outlier data points are further removed, and the audio signal that has been intelligently analyzed and filtered is output.

4. The volume control method based on high-latency cockpit scenarios according to claim 3, characterized in that, The input audio signal to be analyzed is subjected to nonlinear intelligent filtering, specifically as follows: Receive a set of audio signals that need to be smoothed, identify abnormal data points in the audio signals, and generate the corresponding dataset; A preliminary weighted average is performed on the dataset using a moving average filter to obtain preliminary smoothed data. Outlier data points are identified and removed again after the initial weighted average. Based on the weighted average result after removing outlier data points, a second weighted average is performed on the data. Detect the smoothness of the data processed by the double-weighted average and output the data after the double-weighted average processing.

5. A volume control system for high-latency cabin scenarios, used to implement the volume control method for high-latency cabin scenarios as described in any one of claims 1 to 4, characterized in that, include: The volume explosion prevention strategy activation module configures the vehicle-mounted equipment, sets a safe volume threshold, monitors the frequency of volume adjustment by the user within a preset time in real time, and activates the volume explosion prevention strategy when the volume exceeds the safe volume threshold. The audio signal intelligent analysis and filtering module detects the audio signal, determines the normal fluctuation range of the audio signal, performs intelligent analysis and filtering on the audio signal, identifies data points that exceed the normal fluctuation range as abnormal data points, removes the abnormal data points, and applies filters or machine learning models for verification. The volume adaptive adjustment module, based on an adaptive adjustment algorithm, adjusts the volume settings according to user habits and ambient noise, and controls the volume to decrease smoothly. The adaptive adjustment algorithm has a built-in user volume preference model.

6. An intelligent cockpit, characterized in that, The intelligent cockpit is equipped with the volume control system based on the high latency scenario of the cockpit as described in claim 5.

7. An electronic device, characterized in that, include: The system includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method according to any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that, It stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method according to any one of claims 1 to 4.

9. A vehicle, characterized in that, The vehicle is equipped with the intelligent cockpit as described in claim 6.

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