A navigation voice broadcast control method and related device

Abstract

This application discloses a control method and related equipment for navigation voice broadcasting, relating to the field of voice navigation technology. The method includes: acquiring multiple in-vehicle environmental parameters at the current moment during the driving of a target vehicle, wherein the in-vehicle environmental parameters are parameters affecting the navigation voice broadcasting effect; performing a weighted summation of the various in-vehicle environmental parameters to determine the in-vehicle environmental noise value of the target vehicle at the current moment, wherein the in-vehicle environmental noise value characterizes the degree of interference of the target vehicle's in-vehicle environment on the navigation voice broadcasting; determining the broadcasting control parameters for navigation voice broadcasting based on the in-vehicle environmental noise value at the current moment; and controlling the target vehicle's in-vehicle voice system to broadcast navigation voice according to the broadcasting control parameters. This application adaptively adjusts the navigation voice broadcasting according to changes in the in-vehicle environment, ensuring that the driver clearly receives navigation instructions under different driving conditions.

Description

Technical Field

[0001] This application relates to the field of voice navigation technology, and in particular to a control method and related equipment for navigation voice broadcasting. Background Technology

[0002] With the development of smart cockpit technology, in-vehicle navigation has become an essential tool for driving. As the carrier of navigation information, the quality of navigation voice broadcasting affects the driver's efficiency in receiving navigation instructions and driving safety. Currently, most in-vehicle navigation voice broadcasts use fixed broadcast parameters or only allow for simple adjustments to a single parameter, making it difficult to adapt to complex and changing driving environments. In actual driving, changes in the in-vehicle environment affect the driver's ability to hear navigation voice commands: in noisy environments, drivers may not be able to hear key navigation instructions clearly; in quiet environments, excessively high volume or redundant broadcast content can cause auditory interference and distract the driver. Therefore, a control method for navigation voice broadcasting is urgently needed to solve the aforementioned technical problems. Summary of the Invention

[0003] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key features and essential technical features of the claimed technical solutions, nor is it intended to determine the scope of protection of the claimed technical solutions.

[0004] Firstly, this application proposes a control method for navigation voice broadcasting, the method comprising: During the driving process of the target vehicle, various in-vehicle environmental parameters are acquired at the current moment, wherein the in-vehicle environmental parameters are parameters that affect the navigation voice broadcast effect; The in-vehicle environment parameters are weighted and summed to determine the in-vehicle noise value of the target vehicle at the current time, wherein the in-vehicle noise value is used to characterize the degree of interference of the in-vehicle environment of the target vehicle with the navigation voice broadcast. Based on the current in-vehicle noise level, determine the navigation voice broadcast control parameters; According to the broadcast control parameters, the vehicle's in-vehicle voice system is controlled to broadcast navigation voice messages.

[0005] In some implementations, the vehicle environment parameters include vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters. The step of weighted summing of these vehicle environment parameters to determine the in-vehicle noise value of the target vehicle at the current time includes: Obtain the weighting coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively; The vehicle speed parameter, window status parameter, air conditioning operation parameter, and in-vehicle noise parameter are weighted and summed based on the weighting coefficients to obtain the in-vehicle noise value of the target vehicle at the current time.

[0006] In some implementations, the weighting coefficients corresponding to the vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters respectively include: The current driving scenario of the target vehicle is determined based on vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters. Based on the current driving scenario, determine the weighting coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively.

[0007] In some implementations, determining the current driving scenario of the target vehicle based on vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters includes: Determine whether the vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters meet their respective preset scene triggering conditions, and determine the preset scenes that meet the preset scene triggering conditions as candidate scenes; When only one of the candidate scenarios exists, the candidate scenario is taken as the current driving scenario; When at least two candidate scenarios exist, the current driving scenario is determined from the at least two candidate scenarios according to a preset priority; When no candidate scenario exists, the preset default scenario will be used as the current driving scenario.

[0008] In some implementations, determining the weighting coefficients for vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters based on the current driving scenario includes: Determine the target weight allocation scheme corresponding to the current driving scenario from multiple preset weight allocation schemes; Based on the target weight allocation scheme, determine the weight coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively.

[0009] In some implementations, determining the navigation voice broadcast control parameters based on the in-vehicle ambient noise level at the current moment includes: From at least two candidate value intervals, determine the target value interval to which the in-vehicle noise value at the current moment belongs; Based on the preset adaptation rules corresponding to the target value range, the broadcast control parameters of the navigation voice broadcast are determined. The preset adaptation rules include multiple preset value ranges and the broadcast control parameters. The broadcast control parameters include broadcast volume control parameters, broadcast timing control parameters, and broadcast content detail control parameters.

[0010] In some implementations, determining the navigation voice broadcast control parameters based on the in-vehicle ambient noise level at the current moment includes: Determine the noise difference between the in-vehicle noise level at the previous moment and the in-vehicle noise level at the current moment; If the noise difference is less than a preset threshold, the navigation voice broadcasting control parameters are determined based on the in-vehicle noise value of the previous moment. If the noise difference is not less than the preset threshold, then the navigation voice broadcast control parameters are determined based on the in-vehicle environment noise value at the current moment.

[0011] Secondly, this application proposes a control device for navigation voice broadcasting, the device comprising: The vehicle environment parameter acquisition module is used to acquire various vehicle environment parameters at the current time during the driving process of the target vehicle, wherein the vehicle environment parameters are parameters that affect the navigation voice broadcast effect; The in-vehicle environmental noise calculation module is used to perform weighted summation on each of the vehicle environmental parameters to determine the in-vehicle environmental noise value of the target vehicle at the current time, wherein the in-vehicle environmental noise value is used to characterize the degree of interference of the in-vehicle environment of the target vehicle on the navigation voice broadcast. The broadcast control parameter determination module is used to determine the broadcast control parameters for navigation voice broadcast based on the in-vehicle noise level at the current moment. The in-vehicle navigation voice broadcast module is used to control the in-vehicle voice system of the target vehicle to broadcast navigation voice messages according to the broadcast control parameters.

[0012] Thirdly, this application proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program stored in the memory to implement the steps of the control method for navigation voice broadcasting described in any of the first aspects.

[0013] Fourthly, this application also proposes a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the control method for navigation voice broadcasting according to any one of the first aspects.

[0014] In summary, the navigation voice broadcast control method provided in this application acquires various in-vehicle environmental parameters that affect the navigation voice broadcast effect during vehicle operation, enabling broadcast adjustments to be based on actual environmental conditions rather than fixed preset values. It performs a weighted summation of various in-vehicle environmental parameters, and differentiates the contribution of each parameter to the evaluation result through weight allocation based on the varying degrees of influence of different environmental parameters on the broadcast listening effect. This quantifies multi-dimensional environmental information into an in-vehicle environmental noise value reflecting the degree of interference of the in-vehicle environment on the navigation voice broadcast. Based on the in-vehicle environmental noise value, it determines the navigation voice broadcast control parameters, ensuring that the broadcast volume, timing, and detail of the broadcast content match the current actual in-vehicle environment, avoiding unclear broadcast content or redundant information interfering with the driver's attention due to environmental changes. By controlling the in-vehicle voice system to broadcast navigation voice according to these broadcast control parameters, the navigation voice output adjusts with changes in the in-vehicle environment, allowing the driver to obtain navigation instructions in different environmental conditions. This improves the clarity and rationality of the navigation voice broadcast, enhancing driving safety and user experience. Attached Figure Description

[0015] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit this specification. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A schematic flowchart of a control method for navigation voice broadcasting provided in an embodiment of this application; Figure 2 A schematic diagram of a control device for navigation voice broadcasting provided in an embodiment of this application; Figure 3 This is a schematic diagram of a control electronic device for navigation voice broadcasting provided in an embodiment of this application. Detailed Implementation

[0016] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. 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.

[0017] This application relates to the field of voice navigation technology, and more particularly to a control method and related equipment for navigation voice broadcasting. With the rapid development of smart cockpit technology, in-vehicle navigation systems have become an auxiliary tool during vehicle operation. As the carrier for transmitting navigation information to the driver, the effectiveness of navigation voice broadcasting directly affects the driver's efficiency in receiving navigation instructions and driving safety. Currently, most in-vehicle navigation voice broadcasting uses fixed broadcast parameters, that is, fixed volume, broadcast timing, and level of detail in the broadcast content are set at the factory or during system initialization. Regardless of the driving environment, the same parameters are used for navigation voice broadcasting. Alternatively, some solutions may adjust the broadcast parameters to some extent, but only to a simple adjustment of the single parameter of volume, such as increasing the volume according to vehicle speed.

[0018] However, in actual driving, the in-vehicle environment is dynamically changing. Factors such as vehicle speed, window opening or closing, air conditioning system operation (especially fan speed), and in-vehicle noise all affect the in-vehicle sound environment. When the vehicle is traveling at high speed, windows are open, or the air conditioning is running at high fan speed, the in-vehicle noise increases. If navigation instructions are still broadcast at a fixed volume, the driver may not be able to hear key instructions clearly. When the vehicle is traveling at low speed, windows are closed, and the air conditioning is running at low fan speed, the in-vehicle environment is relatively quiet. If the broadcast volume is too loud or the content is too lengthy, it will cause auditory interference to the driver and distract their attention. Therefore, there is an urgent need for a control scheme that adaptively adjusts the navigation voice broadcast according to changes in the in-vehicle environment to improve the clarity of navigation voice broadcasts and driving safety.

[0019] The technical solution provided in this application can be widely applied to various vehicles with in-vehicle navigation functions, including but not limited to gasoline vehicles, electric vehicles, and hybrid vehicles. It is particularly suitable for intelligent cockpit systems with high requirements for intelligent, personalized, and safe navigation broadcasts. The technical solution of this application does not require additional hardware equipment and can utilize existing vehicle sensors and control systems, such as vehicle speed sensors, window status sensors, air conditioning control modules, in-vehicle microphones, and in-vehicle voice systems. It features low cost, easy deployment, and wide applicability.

[0020] To facilitate understanding of the technical solution of this application, several terms used in this application will be explained below.

[0021] The in-vehicle environmental parameters in this application refer to various environmental parameters acquired by the target vehicle during operation that affect the listening effect of navigation voice broadcasts. These parameters reflect the current physical and acoustic environment of the vehicle. Specifically, the in-vehicle environmental parameters include vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters. Vehicle speed parameters can be acquired through an in-vehicle speed sensor or positioning module, reflecting the vehicle's current speed; changes in vehicle speed directly affect the levels of wind and road noise inside the vehicle. Window status parameters can be acquired through a window control sensor, reflecting the open, closed, or partially open state of the windows; changes in window status determine the degree of sound isolation between the interior and the external environment. Air conditioning operation parameters can be acquired through the air conditioning control module, specifically including the air conditioning fan speed level; the air conditioning fan speed directly affects the intensity of airflow noise inside the vehicle. In-vehicle noise parameters can be acquired through an in-vehicle microphone, reflecting the decibel value of the in-vehicle ambient noise.

[0022] The weighted summation method in this application refers to a mathematical operation that multiplies each in-vehicle environmental parameter according to its corresponding weight coefficient and then sums the products. Since different types of in-vehicle environmental parameters have different physical dimensions and numerical ranges—for example, vehicle speed is measured in kilometers per hour, and in-vehicle noise is measured in decibels—these parameters cannot be directly fused in their raw values. Therefore, before performing weighted summation on each in-vehicle environmental parameter, each parameter is first standardized, converting it into a standard value within a uniform numerical range to ensure comparability between different parameters. Based on this, a corresponding weight coefficient is assigned to each in-vehicle environmental parameter, reflecting its contribution to the level of in-vehicle noise. The specific calculation method for weighted summation is to multiply the standard value of each in-vehicle environmental parameter by its corresponding weight coefficient to obtain the weighted value of that parameter, and then sum the weighted values ​​of all parameters to obtain the in-vehicle noise value.

[0023] The in-vehicle environmental noise value in this application refers to a quantitative index obtained through the aforementioned weighted summation calculation. This quantitative index is used to characterize the degree of interference between the in-vehicle environment and navigation voice broadcasting. The in-vehicle environmental noise value is not an expression of a single environmental parameter, but rather an evaluation result obtained by fusing multi-dimensional environmental information such as vehicle speed, window status, air conditioning operation status, and in-vehicle noise. The magnitude of this value is positively correlated with the degree of in-vehicle environmental noise: the higher the in-vehicle environmental noise value, the greater the interference of the current in-vehicle environment with navigation voice broadcasting, and the greater the difficulty for the driver to hear navigation instructions clearly; conversely, the lower the in-vehicle environmental noise value, the quieter the current in-vehicle environment, and the lower the degree of interference with navigation voice broadcasting.

[0024] The broadcast control parameters in this application refer to the collective term for various parameters used to control the in-vehicle voice system of the target vehicle to broadcast navigation voice messages. Specifically, the broadcast control parameters include broadcast volume control parameters, broadcast timing control parameters, and broadcast content detail control parameters. The broadcast volume control parameter controls the volume of the navigation voice broadcast, determining the sound intensity when the driver hears the navigation instructions; the broadcast timing control parameter controls the advance time of the navigation voice broadcast relative to the navigation node, determining how much time before the driver receives the navigation instructions before reaching the navigation node; the broadcast content detail control parameter controls the amount of information included in the navigation voice broadcast, determining whether the broadcast content includes complete road names, operation prompts and precautions, or only steering action instructions.

[0025] The preset adaptation rules in this application refer to a set of pre-defined rules used to establish a mapping relationship between in-vehicle environmental noise values ​​and broadcast control parameters. The preset adaptation rules include multiple preset numerical ranges and their correspondences with the broadcast control parameters. The range of in-vehicle environmental noise values ​​is divided into multiple preset numerical ranges, each corresponding to a set of broadcast control parameters. Once the in-vehicle environmental noise value at the current moment is determined, the target numerical range to which the noise value belongs is first determined. Then, based on the preset adaptation rules corresponding to the target numerical range, the broadcast control parameters matching that range are determined.

[0026] The preset scenario triggering conditions and preset scenarios in this application are interconnected to identify driving scenarios. A preset scenario refers to a predefined class of driving situations with specific environmental characteristics. In the embodiments of this application, this may include high-speed scenarios, window-open scenarios, high-airflow air conditioning scenarios, and high-noise scenarios. Preset scenario triggering conditions refer to the judgment conditions corresponding to each preset scenario, used to determine whether the scenario is valid. Specifically, each in-vehicle environmental parameter corresponds to its own preset scenario triggering condition—for example, the vehicle speed parameter corresponds to the triggering condition for the high-speed scenario (vehicle speed greater than a preset speed threshold), the window status parameter corresponds to the triggering condition for the window-open scenario (window is open), the air conditioning operation parameter corresponds to the triggering condition for the high-airflow air conditioning scenario (airflow level greater than or equal to a preset flow level), and the in-vehicle noise parameter corresponds to the triggering condition for the high-noise scenario (in-vehicle noise greater than a preset noise threshold). When a certain in-vehicle environmental parameter meets its corresponding preset scenario triggering condition, the preset scenario corresponding to that triggering condition is determined as a candidate scenario. By judging multiple in-vehicle environmental parameters one by one, all triggered candidate scenarios at the current moment can be identified, thereby determining the driving scenario.

[0027] The preset priority in this application refers to the selection rule used to determine a unique current driving scenario from multiple candidate scenarios when they exist simultaneously. In some embodiments of this application, when multiple vehicle environmental parameters simultaneously meet their respective preset scenario triggering conditions, i.e., when multiple candidate scenarios exist simultaneously, one is selected as the current driving scenario according to the preset priority. The preset priority setting rule is as follows: high-speed scenarios have higher priority than window-opening scenarios, window-opening scenarios have higher priority than air conditioning high-airflow scenarios, and air conditioning high-airflow scenarios have higher priority than high-noise scenarios. By using preset priorities, it is ensured that the current driving scenario can still be uniquely determined even when multiple scenario conditions are met simultaneously.

[0028] The preset weight allocation scheme in this application refers to a set of weight coefficient allocation schemes pre-configured for each preset scenario. This scheme specifies the specific values ​​of the weight coefficients corresponding to various in-vehicle environmental parameters under that scenario. Different preset scenarios correspond to different preset weight allocation schemes—for example, in a high-speed scenario, the weight coefficient of the vehicle speed parameter is configured as the maximum value among all weight coefficients to characterize the main influence of vehicle speed on the noise level of the in-vehicle environment; in a window-open scenario, the weight coefficient of the window status parameter is configured as the maximum value among all weight coefficients; in a high-airflow scenario, the weight coefficient of the air conditioning operation parameter is configured as the maximum value among all weight coefficients; and in a high-noise scenario, the weight coefficient of the in-vehicle noise parameter is configured as the maximum value among all weight coefficients. Regardless of the preset weight allocation scheme, the sum of the weight coefficients corresponding to various in-vehicle environmental parameters is equal to 1. Through the preset weight allocation scheme, the differentiated configuration of the influence of various environmental parameters under different driving scenarios is achieved, making the weighted summation result more accurately reflect the actual noise level of the in-vehicle environment under the current driving scenario.

[0029] Please see Figure 1 This is a flowchart illustrating a control method for navigation voice broadcasting provided in an embodiment of this application, which may specifically include: S110. During the driving process of the target vehicle, acquire various in-vehicle environmental parameters at the current moment, among which the in-vehicle environmental parameters are parameters that affect the navigation voice broadcast effect; For example, the in-vehicle environment changes during vehicle operation. Vehicle speed, window opening / closing, air conditioning fan speed, and in-vehicle noise levels all affect the reception of navigation voice prompts. To achieve adaptive control of navigation voice prompts, various parameters reflecting the current in-vehicle environment are acquired. Acquiring multiple in-vehicle environmental parameters allows the navigation system to perceive interference from the current in-vehicle environment on voice prompts, avoiding mismatches between the prompts and actual conditions caused by relying on a single parameter or fixed preset value.

[0030] S120. The in-vehicle environmental parameters are weighted and summed to determine the in-vehicle noise value of the target vehicle at the current moment. The in-vehicle noise value is used to characterize the degree of interference of the in-vehicle environment of the target vehicle with the navigation voice broadcast. For example, after acquiring various in-vehicle environmental parameters, these parameters are fused into a quantitative indicator reflecting the degree of interference between the in-vehicle environment and navigation voice broadcasting. Since different types of in-vehicle environmental parameters have different physical meanings and units of measurement, and their respective impacts on broadcast reception vary, a weighted summation method is required for the fusion calculation. Weighted summation involves assigning a weight coefficient to each in-vehicle environmental parameter, reflecting the parameter's contribution to the level of in-vehicle noise. Then, each parameter is multiplied by its corresponding weight coefficient, and the results are summed to obtain the in-vehicle noise value.

[0031] S130. Determine the navigation voice broadcast control parameters based on the current in-vehicle noise level. For example, after determining the current in-vehicle noise level, specific control parameters for navigation voice broadcasting are determined based on this noise level. The magnitude of the in-vehicle noise level reflects the degree of interference between the current in-vehicle environment and the navigation voice broadcasting; different noise levels require different broadcasting control strategies. When the noise level is low, the in-vehicle environment is relatively quiet, so the broadcasting volume should not be too loud to avoid disturbing the driver, the broadcasting timing should not be too early, and the broadcasting content should be complete and detailed enough to provide sufficient navigation guidance information. When the noise level is high, the in-vehicle environment is quite noisy, so the broadcasting volume needs to be increased to ensure the driver can clearly hear the navigation instructions, and the broadcasting should be done earlier to allow the driver more reaction time. At the same time, the broadcasting content should be simplified, retaining only the most essential steering action instructions to avoid redundant information distracting the driver's attention. By determining the broadcasting control parameters based on the noise level, the broadcasting strategy is matched to the current in-vehicle environment, ensuring that the driver clearly receives navigation instructions while avoiding unnecessary auditory interference.

[0032] S140. Control the vehicle's in-vehicle voice system to broadcast navigation voice messages according to the broadcast control parameters.

[0033] For example, after determining the broadcast control parameters for navigation voice prompts, the in-vehicle voice system is controlled to actually execute the navigation voice prompts according to these parameters. The broadcast control parameters include specific settings for broadcast volume, broadcast timing, and the level of detail in the broadcast content. The in-vehicle voice system adjusts the volume of the voice output, selects the trigger time for broadcasting, and organizes the amount of information to be broadcast according to these settings. By executing the broadcast according to the broadcast control parameters, the actual output effect of the navigation voice is adapted to the current in-vehicle environment. In noisy environments, the driver can clearly hear the navigation instructions; in quiet environments, the driver will not be disturbed by excessively high volume or redundant information, thus achieving adaptive output of the navigation voice prompts under different environmental conditions.

[0034] In summary, the navigation voice broadcast control method provided in this application acquires various in-vehicle environmental parameters that affect the navigation voice broadcast effect during vehicle operation, enabling broadcast adjustments to be based on actual environmental conditions rather than fixed preset values. It performs a weighted summation of various in-vehicle environmental parameters, and differentiates the contribution of each parameter to the evaluation result through weight allocation based on the varying degrees of influence of different environmental parameters on the broadcast listening effect. This quantifies multi-dimensional environmental information into an in-vehicle environmental noise value reflecting the degree of interference of the in-vehicle environment on the navigation voice broadcast. Based on the in-vehicle environmental noise value, it determines the navigation voice broadcast control parameters, ensuring that the broadcast volume, timing, and detail of the broadcast content match the current actual in-vehicle environment, avoiding unclear broadcast content or redundant information interfering with the driver's attention due to environmental changes. The method controls the in-vehicle voice system to broadcast navigation voice according to these parameters, adjusting the navigation voice output according to changes in the in-vehicle environment. This allows the driver to obtain navigation instructions in different environmental conditions, improving the clarity and rationality of the navigation voice broadcast, and enhancing driving safety and user experience.

[0035] In some embodiments, the vehicle environmental parameters include vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters. A weighted summation of these parameters is performed to determine the in-vehicle noise level of the target vehicle at the current moment, including: Obtain the weighting coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively; The vehicle speed parameter, window status parameter, air conditioning operation parameter, and in-vehicle noise parameter are weighted and summed based on the weighting coefficients to obtain the in-vehicle noise value of the target vehicle at the current moment.

[0036] For example, vehicle environmental parameters include vehicle speed, window status, air conditioning operation, and in-vehicle noise. These parameters have different physical dimensions and numerical ranges; for instance, vehicle speed is measured in kilometers per hour, and noise is measured in decibels, making direct fusion calculations impossible. Therefore, before obtaining the weighting coefficients for each of the vehicle speed, window status, air conditioning operation, and in-vehicle noise parameters, the obtained vehicle environmental parameters are first standardized, converting each parameter into a value within a uniform range (0-100) to obtain the standard environmental parameter value for each parameter.

[0037] When obtaining the weighting coefficients, the current driving scenario of the target vehicle is first determined based on the vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters. Then, based on the current driving scenario, the corresponding target weighting scheme is determined from multiple preset weighting schemes to obtain the weighting coefficients corresponding to the vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively.

[0038] After determining the standard values ​​and weighting coefficients for each environmental parameter, the product of the standard value and its corresponding weighting coefficient for each in-vehicle environmental parameter is calculated to obtain the weighted value of that parameter. The weighted values ​​of the four parameters are then summed to obtain the in-vehicle noise level of the target vehicle at the current moment. This weighted summation method integrates environmental information from different dimensions into a comprehensive index; a higher value indicates a greater degree of interference from the current in-vehicle environment with the navigation voice broadcast.

[0039] In some embodiments, obtaining the weighting coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters respectively includes: Based on vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters, determine the current driving scenario of the target vehicle; Based on the current driving scenario, determine the weighting coefficients for vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively.

[0040] For example, when obtaining the weight coefficients corresponding to each in-vehicle environmental parameter, the driving scenario of the target vehicle at the current moment is first determined. When determining the current driving scenario, it is determined whether the vehicle speed parameter, window status parameter, air conditioning operation parameter, and in-vehicle noise parameter meet their respective preset scenario triggering conditions. Preset scenarios that meet the preset scenario triggering conditions are identified as candidate scenarios. When only one candidate scenario exists, that candidate scenario is used as the current driving scenario; when at least two candidate scenarios exist, one is selected from multiple candidate scenarios according to a preset priority as the current driving scenario; when no candidate scenario exists, a preset default scenario is used as the current driving scenario.

[0041] After determining the current driving scenario, a target weight allocation scheme corresponding to the current driving scenario is selected from multiple pre-configured preset weight allocation schemes. This target weight allocation scheme specifies the weight coefficients for vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, and the sum of all weight coefficients is 1. Based on this target weight allocation scheme, the weight coefficients corresponding to each in-vehicle environmental parameter can be obtained.

[0042] In some embodiments, the current driving scenario of the target vehicle is determined based on vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters, including: Determine whether the vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters meet their respective preset scene triggering conditions, and determine the preset scenes that meet the preset scene triggering conditions as candidate scenes; When only one candidate scenario exists, the candidate scenario is taken as the current driving scenario; When there are at least two candidate scenarios, the current driving scenario is determined from the at least two candidate scenarios according to a preset priority. When no candidate scenario exists, the preset default scenario will be used as the current driving scenario.

[0043] For example, when determining the current driving scenario of the target vehicle, the system first checks whether the vehicle speed parameter, window status parameter, air conditioning operation parameter, and in-vehicle noise parameter meet their respective preset scenario trigger conditions. Each in-vehicle environmental parameter corresponds to its own preset scenario trigger condition. The vehicle speed parameter corresponds to the high-speed scenario trigger condition, specifically, the vehicle speed is greater than a preset speed threshold, which can be set to 80 km / h. The window status parameter corresponds to the window opening scenario trigger condition, specifically, the window is in an open or partially open state. The air conditioning operation parameter corresponds to the high airflow scenario trigger condition, specifically, the airflow level is greater than or equal to a preset airflow level, which can be set to level 4. The in-vehicle noise parameter corresponds to the high-noise scenario trigger condition, specifically, the in-vehicle noise is greater than a preset noise threshold, which can be set to 80 dB.

[0044] When a certain in-vehicle environmental parameter meets its corresponding preset scene trigger condition, the preset scene corresponding to that trigger condition is identified as a candidate scene. For example, if the vehicle speed reaches 110km / h and meets the high-speed scene trigger condition, then the high-speed scene is identified as a candidate scene; if the car window is also open at this time, then the open window scene is also identified as a candidate scene. By judging each of the four in-vehicle environmental parameters one by one, all triggered candidate scenes at the current moment can be identified.

[0045] After determining the candidate scenarios, the number of candidate scenarios is categorized. When only one candidate scenario exists, that scenario is taken as the current driving scenario. For example, with a vehicle speed of 60 km / h, windows open, air conditioning fan speed at level 2, and interior noise of 65 dB, only the window status parameters meet the triggering conditions for the window open scenario. The other parameters do not trigger the corresponding preset scenarios. Therefore, only the window open scenario is determined as the candidate scenario, and it is taken as the current driving scenario.

[0046] When at least two candidate scenarios exist—that is, when multiple in-vehicle environmental parameters simultaneously meet their respective preset scenario triggering conditions—one of the candidate scenarios is determined as the current driving scenario based on preset priorities. The preset priority rules are as follows: high-speed scenarios have higher priority than open window scenarios, open window scenarios have higher priority than high air conditioning fan speed scenarios, and high air conditioning fan speed scenarios have higher priority than high noise scenarios. For example, when the vehicle speed is 110 km / h, the window is open, the air conditioning fan speed is level 4, and the in-vehicle noise is 95 dB, the high-speed scenario, open window scenario, high air conditioning fan speed scenario, and high noise scenario are all identified as candidate scenarios. Based on the preset priority, the high-speed scenario is determined as the current driving scenario. This preset priority ensures that the current driving scenario can still be uniquely determined even when multiple scenario conditions are met simultaneously.

[0047] When no candidate scenario exists, meaning none of the four in-vehicle environmental parameters meet their respective preset scenario trigger conditions, it indicates that no preset scenario is triggered at the current moment, and the preset default scenario is used as the current driving scenario. For example, if the vehicle speed is 25 km / h, the windows are closed, the air conditioning fan speed is level 1, and the in-vehicle noise level is 45 dB, then the vehicle speed does not exceed 80 km / h, the windows are not open, the air conditioning fan speed is not at level 4, and the noise level does not exceed 80 dB. Since none of the four preset scenario trigger conditions are met, the preset default scenario is used as the current driving scenario. Through this judgment process, regardless of whether there are one, multiple, or zero candidate scenarios, a unique current driving scenario can be determined.

[0048] It should be noted that the default preset scenario is a pre-defined fallback scenario used to cover situations where no preset scenario is matched. This scenario corresponds to the basic environmental state where the target vehicle is traveling at low speed, windows are closed, air conditioning is running at low fan speed, and in-vehicle noise is low. That is, the vehicle speed has not reached the trigger threshold for the high-speed scenario, the windows are not open, the air conditioning fan speed has not reached the trigger level for the high fan speed scenario, and the in-vehicle noise has not exceeded the trigger threshold for the high-noise scenario. Under this state, none of the four in-vehicle environmental parameters trigger their corresponding preset scenarios, indicating that the current in-vehicle environment is relatively quiet and the interference with navigation voice broadcast is low.

[0049] In summary, this application embodiment achieves preliminary identification and screening of driving scenarios by determining whether each in-vehicle environmental parameter meets its corresponding preset scenario triggering conditions and filtering the preset scenarios that meet the conditions as candidate scenarios. When only one candidate scenario exists, it is directly used as the current driving scenario, omitting the selection step between multiple candidate scenarios and improving scenario determination efficiency. When at least two candidate scenarios exist, the current driving scenario is determined from them according to a preset priority. The preset priority ensures that the current driving scenario is uniquely determined when multiple scenario conditions are met simultaneously, avoiding decision uncertainty caused by scenario conflicts. When no candidate scenario exists, the preset default scenario is used as the current driving scenario, so that the scenario determination logic covers all possible environmental states, including the case where no preset scenario is triggered.

[0050] In some embodiments, based on the current driving scenario, weighting coefficients are determined for vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters, including: Determine the target weight allocation scheme corresponding to the current driving scenario from multiple preset weight allocation schemes; Based on the target weight allocation scheme, determine the weight coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively.

[0051] For example, in different driving scenarios, the contributions of vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters to the level of in-vehicle noise vary. In high-speed scenarios, increased vehicle speed directly leads to a significant increase in wind noise and road noise, making vehicle speed parameters the most significant contributor to the level of in-vehicle noise. In scenarios with open windows, the reduced sound isolation between the vehicle and the outside world allows external noise to directly enter the vehicle, making window status parameters the most significant contributor to the level of in-vehicle noise. In scenarios with high air conditioning fan speed, the airflow noise generated by the air conditioning system operating at high fan speed becomes the main source of in-vehicle noise, making air conditioning operating parameters the most significant contributor to the level of in-vehicle noise. In high-noise scenarios, the in-vehicle noise parameters themselves reflect the intensity of interference that the broadcast needs to overcome, making in-vehicle noise parameters the most significant contributor to the level of in-vehicle noise. Therefore, each preset scenario is pre-configured with a corresponding weighting scheme, which specifies the specific values ​​of the weighting coefficients for each of the various in-vehicle environmental parameters in that scenario. Once the current driving scenario is determined, a target weight allocation scheme corresponding to the scenario is selected from multiple preset weight allocation schemes to match the weight coefficients of each parameter with the actual contribution of each parameter in the current scenario.

[0052] Based on the target weight allocation scheme, the weight coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters are determined. The target weight allocation scheme specifies the weight coefficient values ​​for each of the four in-vehicle environmental parameters, and the weight coefficient corresponding to each parameter can be obtained by following this scheme.

[0053] Taking a high-speed scenario as an example, in the target weight allocation scheme for this scenario, the vehicle speed parameter has the highest weight value, which can be 0.4; the window status parameter has a weight value of 0.35; the air conditioning operation parameter has a weight value of 0.15; and the in-vehicle noise parameter has a weight value of 0.1. The sum of the four weight values ​​is 1. Taking a window-open scenario as an example, in the target weight allocation scheme for this scenario, the window status parameter has the highest weight value, which can be 0.35; the vehicle speed parameter has a weight value of 0.3; the air conditioning operation parameter has a weight value of 0.2; and the in-vehicle noise parameter has a weight value of 0.15. Taking a high-airflow air conditioning scenario as an example, in the target weight allocation scheme for this scenario, the air conditioning operation parameter has the highest weight value, which can be 0.35. Taking a high-noise scenario as an example, in the target weight allocation scheme for this scenario, the in-vehicle noise parameter has the highest weight value, which can be 0.4. Regardless of the preset weight allocation scheme, the sum of the weight values ​​for each in-vehicle environmental parameter is equal to 1.

[0054] For the preset default scenario, a corresponding weight allocation scheme is also pre-configured. Since all in-vehicle environmental parameters are in a normal state before the preset scenario is triggered, i.e., the vehicle speed is in the low to medium speed range, the windows are closed, the air conditioning is at a low fan speed, and the in-vehicle noise is at a low level, the contribution of each parameter to the noise level of the in-vehicle environment is relatively balanced. However, the in-vehicle noise parameter reflects the quietness of the current in-vehicle acoustic environment, so its weight coefficient can be set to the highest value among the four parameters.

[0055] In summary, this application embodiment determines the target weight allocation scheme corresponding to the current driving scenario from multiple preset weight allocation schemes, thereby achieving the matching of the weight coefficients of each parameter with the current driving scenario, and making the configuration of the weight coefficients reflect the differences in the contribution of each parameter to the noise level of the in-vehicle environment under different scenarios.

[0056] In some embodiments, the navigation voice broadcast control parameters are determined based on the current in-vehicle noise level, including: From at least two candidate value intervals, determine the target value interval to which the in-vehicle noise level belongs at the current moment; Based on the preset adaptation rules corresponding to the target numerical range, the broadcast control parameters for navigation voice broadcast are determined. The preset adaptation rules include the mapping relationship between multiple preset numerical ranges and broadcast control parameters. The broadcast control parameters include broadcast volume control parameters, broadcast timing control parameters, and broadcast content detail control parameters.

[0057] For example, the range of in-vehicle ambient noise values ​​is divided into multiple candidate value intervals, each corresponding to a set of broadcast control parameters. After calculating the in-vehicle ambient noise value at the current moment, the noise value is compared with the value range of each candidate value interval to determine which candidate value interval the noise value falls into, and that candidate value interval is taken as the target value interval.

[0058] For example, the in-vehicle noise level ranges from 0 to 100, and can be pre-divided into three candidate value ranges: a first range of 0 to 30, a second range of 31 to 60, and a third range of 61 to 100. If the calculated in-vehicle noise level is 85, this value is compared with the value ranges of the three ranges, and it is determined that it falls within the third range of 61 to 100, which is then used as the target value range. If the calculated in-vehicle noise level is 25, it is determined that it falls within the first range of 0 to 30, which is then used as the target value range.

[0059] Based on the preset adaptation rules corresponding to the target numerical range, the broadcast control parameters for navigation voice broadcast are determined. The preset adaptation rules pre-configure the mapping relationship between multiple preset numerical ranges and broadcast control parameters. Each preset numerical range corresponds to a set of broadcast control parameters, which include broadcast volume control parameters, broadcast timing control parameters, and broadcast content detail control parameters.

[0060] After determining the target numerical range, based on the mapping relationship between numerical ranges and broadcast control parameters in the preset adaptation rules, the broadcast control parameter corresponding to the target numerical range is found, and this broadcast control parameter is used as the control parameter for the navigation voice broadcast at the current moment. For example, given the preset adaptation rules configured as follows: the first range (0 to 30) corresponds to a broadcast volume of 0.5 times the base volume, a broadcast timing of 4 seconds before the navigation node, and a full guide; the second range (31 to 60) corresponds to a broadcast volume of 1.2 times the base volume, a broadcast timing of 5 seconds before the navigation node, and a concise guide; and the third range (61 to 100) corresponds to a broadcast volume of 1.5 times the base volume, a broadcast timing of 7 seconds before the navigation node, and a very concise guide, if the target numerical range is the third range (61 to 100), then the broadcast volume control parameter is determined to be 1.5 times the base volume, the broadcast timing control parameter is 7 seconds before the navigation node, and the detail control parameter for the broadcast content is very concise. If the target value range is the first range of 0 to 30, then the broadcast volume control parameter is set to 0.5 times the base volume, the broadcast timing control parameter is 4 seconds before the navigation node, and the broadcast content detail control parameter is complete guidance. Through the mapping relationship between multiple preset value ranges and broadcast control parameters in the preset adaptation rules, the mapping from the in-vehicle environmental noise value to the specific broadcast control parameters is realized.

[0061] In some embodiments, the navigation voice broadcast control parameters are determined based on the current in-vehicle noise level, including: Determine the noise difference between the in-vehicle noise level at the previous moment and the in-vehicle noise level at the current moment; If the noise difference is less than the preset threshold, the navigation voice broadcast control parameters are determined based on the noise level of the in-vehicle environment at the previous moment. If the noise difference is not less than the preset threshold, the navigation voice broadcast control parameters are determined based on the noise level of the in-vehicle environment at the current moment.

[0062] For example, since the collection of in-vehicle environmental parameters is performed periodically according to a preset collection frequency, the in-vehicle environmental noise values ​​corresponding to two adjacent collection times are temporally adjacent. Calculating the difference between the two can reflect the change in the level of in-vehicle environmental noise between adjacent collection times. The noise difference is calculated by subtracting the in-vehicle environmental noise value of the previous time from the current time and taking the absolute value, so that the noise difference is always a non-negative value, used to characterize the amount of change in noise level.

[0063] After calculating the noise difference, it is compared with a preset threshold. Based on the comparison result, the noise value at which moment is used to determine the broadcast control parameters. If the noise difference is less than the preset threshold, it indicates that the change in the noise level of the in-vehicle environment between adjacent collection moments is small, and the environmental state at the current moment has not changed significantly compared to the previous moment. In this case, the broadcast control parameters for navigation voice broadcasting are determined based on the in-vehicle environment noise value at the previous moment. For example, if the preset threshold is set to 10, the in-vehicle environment noise value at the previous moment is 45, and the in-vehicle environment noise value at the current moment is 48, the noise difference is 3, which is less than the preset threshold of 10. In this case, the change in the in-vehicle environment noise level is not significant, and there is no need to update the broadcast control parameters. The broadcast control parameters corresponding to the noise value at the previous moment are continued to be used for broadcasting.

[0064] If the noise difference is not less than a preset threshold, it indicates that the noise level in the vehicle's interior has changed significantly between adjacent data collection times, and the current environmental state differs greatly from the previous time. In this case, the navigation voice broadcast control parameters are determined based on the current in-vehicle noise value. For example, if the in-vehicle noise value was 45 in the previous time and 60 in the current time, the noise difference is 15, which is greater than or equal to the preset threshold of 10. In this case, the in-vehicle noise level has increased significantly, and the broadcast control parameters need to be updated. The corresponding broadcast control parameters are determined using the noise value at the current time for broadcasting.

[0065] In summary, this embodiment of the application assesses the magnitude of changes in the in-vehicle environment by determining the noise difference between the previous and current in-vehicle noise levels and comparing this difference with a preset threshold. When the noise difference is less than the preset threshold, it indicates a small change in the environment, and the broadcast control parameters from the previous moment are continued to be used. This avoids frequent adjustments to the broadcast parameters due to minor fluctuations in environmental parameters, preventing repeated changes in navigation voice broadcasts that could cause auditory discomfort and reduce the continuity of the broadcast experience for the driver. When the noise difference is not less than the preset threshold, it indicates that the environmental change has reached a level requiring a response. In this case, the broadcast control parameters are updated based on the noise value at the current moment, ensuring that the adjustment of the broadcast parameters follows significant changes in the in-vehicle environment and guarantees the timeliness and effectiveness of the broadcast adaptation.

[0066] The technical solution of this application will be further described in detail below through specific embodiments.

[0067] Example 1: High-speed scenario In this embodiment, the target vehicle is traveling at 110 km / h on a highway with the windows open, the air conditioning fan speed at level 4, and the interior noise level at 95 dB. The system determines whether the four in-vehicle environmental parameters meet their respective preset scenario trigger conditions. A vehicle speed of 110 km / h is greater than the preset speed threshold of 80 km / h, meeting the high-speed scenario trigger condition; the windows being open meets the window-open scenario trigger condition; the air conditioning fan speed at level 4 is greater than or equal to the preset fan speed level of 4, meeting the high-air conditioning fan speed scenario trigger condition; and the interior noise level of 95 dB is greater than the preset noise threshold of 80 dB, meeting the high-noise scenario trigger condition. Since all four in-vehicle environmental parameters meet their respective preset scenario trigger conditions, the high-speed scenario, the window-open scenario, the high-air conditioning fan speed scenario, and the high-noise scenario are all identified as candidate scenarios. At this point, there are at least two candidate scenarios. The current driving scenario is determined from these four candidate scenarios based on a preset priority. In the preset priority, the high-speed scenario has a higher priority than the window-opening scenario, the window-opening scenario has a higher priority than the air conditioning high-airflow scenario, and the air conditioning high-airflow scenario has a higher priority than the high-noise scenario. Therefore, the high-speed scenario is determined as the current driving scenario.

[0068] Once the current driving scenario is determined to be a highway scenario, a target weight allocation scheme corresponding to the highway scenario is selected from multiple preset weight allocation schemes. Based on this target weight allocation scheme, the weight coefficients corresponding to each in-vehicle environmental parameter are obtained. In the target weight allocation scheme corresponding to the highway scenario, the weight coefficient for the vehicle speed parameter is 0.4, the weight coefficient for the window status parameter is 0.35, the weight coefficient for the air conditioning operation parameter is 0.15, and the weight coefficient for the in-vehicle noise parameter is 0.1. The sum of all weight coefficients is 1.

[0069] After obtaining the weighting coefficients for each in-vehicle environmental parameter, the parameters are standardized to convert their original values ​​into standard values ​​within a unified range. For example, vehicle speed (110 km / h) is standardized to a standard value of 55; window open status is standardized to a standard value of 100; air conditioning fan speed level (level 4) is standardized to a standard value of 80; and in-vehicle noise (95 dB) is standardized to a standard value of 95. The product of the standard value and its corresponding weighting coefficient for each in-vehicle environmental parameter is calculated: vehicle speed weighted at 55 × 0.4 = 22; window weighted at 100 × 0.35 = 35; air conditioning weighted at 80 × 15% = 12; and noise weighted at 95 × 10% = 9.5. Summing these weighted values ​​yields an in-vehicle noise level of 22 + 35 + 12 + 9.5 = 78.5.

[0070] After determining the in-vehicle noise level to be 78.5, the target noise range to which 78.5 belongs is determined from at least two candidate noise ranges. The in-vehicle noise level ranges from 0 to 100 and is pre-divided into three intervals: 0 to 30 (first interval), 31 to 60 (second interval), and 61 to 100 (third interval). 85 falls within the third interval (61 to 100), therefore, the third interval is determined as the target noise range. Based on the preset adaptation rules corresponding to the target noise range, the broadcast control parameters are determined: the broadcast volume control parameter for the third interval is 1.5 times the base volume (assuming the base volume is 50%, the adjusted broadcast volume is 75%); the broadcast timing control parameter is 7 seconds before the navigation node; and the broadcast content detail control parameter is minimalist guidance, meaning the broadcast content only includes turning instructions, such as "turn left 1 kilometer ahead." Based on the above broadcast control parameters, the in-vehicle voice system is controlled to broadcast navigation voice messages, with the minimalist guidance content broadcast at 75% volume 7 seconds before the navigation node.

[0071] Example 2: Urban Low-Speed ​​Scenario In this embodiment, the target vehicle is traveling at 25 km / h on a low-speed urban road with the windows closed, the air conditioning fan speed at level 1, and the interior noise level at 45 dB. The system determines whether the four in-vehicle environmental parameters meet their respective preset scenario trigger conditions. The vehicle speed of 25 km / h is less than the preset speed threshold of 80 km / h, thus not meeting the high-speed scenario trigger condition; the windows are closed, thus not meeting the window-open scenario trigger condition; the air conditioning fan speed level of 1 is less than the preset fan speed level of 4, thus not meeting the high-fan speed scenario trigger condition; and the interior noise level of 45 dB is less than the preset noise threshold of 80 dB, thus not meeting the high-noise scenario trigger condition. Since none of the four in-vehicle environmental parameters meet their respective preset scenario trigger conditions, there are no candidate scenarios, and the preset default scenario is used as the current driving scenario.

[0072] After the current driving scenario is determined to be the preset default scenario, a target weight allocation scheme corresponding to the preset default scenario is selected from multiple preset weight allocation schemes. Based on this target weight allocation scheme, the weight coefficients corresponding to each in-vehicle environmental parameter are obtained. In the target weight allocation scheme corresponding to the preset default scenario, the weight coefficient for the vehicle speed parameter is 0.2, the weight coefficient for the window status parameter is 0.2, the weight coefficient for the air conditioning operation parameter is 0.2, the weight coefficient for the in-vehicle noise parameter is 0.4, and the sum of all weight coefficients is 1.

[0073] After obtaining the weighting coefficients for each in-vehicle environmental parameter, the parameters are standardized to convert their original values ​​into standard values ​​within a unified range. For example, a vehicle speed of 25 km / h is standardized to a standard value of 12.5; a closed window is standardized to a standard value of 0; an air conditioning fan speed of level 1 is standardized to a standard value of 20; and in-vehicle noise of 45 dB is standardized to a standard value of 45. The product of the standard value and its corresponding weighting coefficient for each in-vehicle environmental parameter is calculated: vehicle speed weighted value is 12.5 × 0.2 = 2.5; window weighted value is 0 × 0.2 = 0; air conditioning weighted value is 20 × 0.2 = 4; and noise weighted value is 45 × 0.4 = 18. Summing these weighted values ​​yields an in-vehicle noise level of 2.5 + 0 + 4 + 18 = 24.5.

[0074] After determining the in-vehicle noise level to be 24.5, the target value range to which 24.5 belongs is determined from at least two candidate value ranges. The in-vehicle noise level ranges from 0 to 100 and is pre-divided into three intervals: 0 to 30 (first interval), 31 to 60 (second interval), and 61 to 100 (third interval). 24.5 falls within the first interval (0 to 30), therefore, the first interval is determined as the target value range. Based on the preset adaptation rules corresponding to the target value range, the broadcast control parameters are determined: the broadcast volume control parameter for the first interval is 50% of the base volume, the broadcast timing control parameter is 4 seconds before the navigation node, and the broadcast content detail control parameter is complete guidance, meaning the broadcast content includes turning actions, distance information, road names, and operation prompts, such as "Turn right 300 meters ahead to enter XX Road. Please change lanes in advance and be aware of pedestrians." Based on the above broadcast control parameters, the in-vehicle voice system is controlled to broadcast navigation voice messages, broadcasting the complete guidance content at 50% of the base volume 4 seconds before the navigation node.

[0075] Example 3: Congestion Scenario In this embodiment, the target vehicle is traveling at 15 km / h in a congested urban area with the windows partially open, the air conditioning fan speed at level 2, and the interior noise level at 70 dB. The system determines whether the four in-vehicle environmental parameters meet their respective preset scenario trigger conditions. A speed of 15 km / h is less than the preset speed threshold of 80 km / h, thus not meeting the high-speed scenario trigger condition; the partially open window meets the window-open scenario trigger condition; the air conditioning fan speed at level 2 is less than the preset fan speed level of 4, thus not meeting the high-fan speed scenario trigger condition; and the interior noise level of 70 dB is less than the preset noise threshold of 80 dB, thus not meeting the high-noise scenario trigger condition. Only the window status parameter meets its corresponding preset scenario trigger condition; therefore, only the window-open scenario is determined as the current driving scenario.

[0076] Once the current driving scenario is determined to be a window-opening scenario, a target weight allocation scheme corresponding to the window-opening scenario is selected from multiple preset weight allocation schemes. Based on this target weight allocation scheme, the weight coefficients corresponding to each in-vehicle environmental parameter are obtained. In the target weight allocation scheme corresponding to the window-opening scenario, the weight coefficient for the vehicle speed parameter is 0.25, the weight coefficient for the window status parameter is 0.3, the weight coefficient for the air conditioning operation parameter is 0.2, and the weight coefficient for the in-vehicle noise parameter is 0.25. The sum of all weight coefficients is 1.

[0077] After obtaining the weighting coefficients for each in-vehicle environmental parameter, the parameters are standardized to convert their original values ​​into standard values ​​within a unified range. For example, a vehicle speed of 15 km / h is standardized to a standard value of 7.5; a window half-open state is standardized to a standard value of 50; an air conditioning fan speed level of 2 is standardized to a standard value of 40; and in-vehicle noise of 70 dB is standardized to a standard value of 70. The product of the standard value and its corresponding weighting coefficient for each in-vehicle environmental parameter is calculated: vehicle speed weighted value is 7.5 × 0.25 = 1.875; window weighted value is 50 × 0.3 = 15; air conditioning weighted value is 40 × 0.2 = 8; and noise weighted value is 70 × 0.25 = 17.5. Summing these weighted values ​​yields the in-vehicle noise level: 1.875 + 15 + 8 + 17.5 = 42.375.

[0078] After determining the in-vehicle noise level to be 42.375, the target value range to which 42.375 belongs is determined from at least two candidate value ranges. The in-vehicle noise level ranges from 0 to 100 and is pre-divided into three ranges: a first range of 0 to 30, a second range of 31 to 60, and a third range of 61 to 100. 42.375 falls within the second range of 31 to 60, therefore the second range is determined as the target value range. Based on the preset adaptation rules corresponding to the target value range, the broadcast control parameters are determined: among the broadcast control parameters corresponding to the second range, the broadcast volume control parameter is 1.2 times the base volume; assuming the base volume is 50%, the adjusted broadcast volume is 60%; the broadcast timing control parameter is 5 seconds before the navigation node; and the broadcast content detail control parameter is simplified guidance, that is, the broadcast content includes turning actions and distance information, omitting operation prompts, such as "turn right in 200 meters ahead". The vehicle voice system is controlled to broadcast navigation voice messages according to the above broadcast control parameters, and a concise guide message is broadcast at 60% volume 5 seconds before the navigation node.

[0079] Please see Figure 2 This is a schematic diagram of the structure of a navigation voice broadcast control device 20 provided in an embodiment of this application. The device specifically includes: The vehicle environment parameter acquisition module 21 is used to acquire various vehicle environment parameters at the current time during the driving process of the target vehicle. Among them, the vehicle environment parameters are parameters that affect the navigation voice broadcast effect. The in-vehicle environmental noise calculation module 22 is used to perform weighted summation of various in-vehicle environmental parameters to determine the in-vehicle environmental noise value of the target vehicle at the current moment. The in-vehicle environmental noise value is used to characterize the degree of interference of the in-vehicle environment of the target vehicle with the navigation voice broadcast. The broadcast control parameter determination module 23 is used to determine the broadcast control parameters of the navigation voice broadcast based on the noise level of the in-vehicle environment at the current time. The in-vehicle navigation voice broadcast module 24 is used to control the in-vehicle voice system of the target vehicle to broadcast navigation voice according to the broadcast control parameters.

[0080] In some embodiments, the vehicle environment parameters include vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters. The in-vehicle environmental noise calculation module 22 includes: The weight coefficient acquisition submodule is used to acquire the weight coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively. The parameter weighted summation submodule is used to perform weighted summation of vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters based on weight coefficients to obtain the in-vehicle noise value of the target vehicle at the current moment.

[0081] In some embodiments, the weight coefficient acquisition submodule includes: The driving scenario determination unit is used to determine the current driving scenario of the target vehicle based on vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters. The weighting coefficient determination unit is used to determine the weighting coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters based on the current driving scenario.

[0082] In some embodiments, the driving scenario determination unit includes: The scene trigger judgment subunit is used to determine whether the vehicle speed parameters, window status parameters, air conditioning operation parameters and in-vehicle noise parameters meet their respective preset scene trigger conditions, and to determine the preset scenes that meet the preset scene trigger conditions as candidate scenes. The first candidate scenario subunit is used to select the candidate scenario as the current driving scenario when there is only one candidate scenario. The second candidate scenario subunit is used to determine the current driving scenario from at least two candidate scenarios according to a preset priority when there are at least two candidate scenarios. The third candidate scenario sub-unit is used to use the preset default scenario as the current driving scenario when no candidate scenario exists.

[0083] In some embodiments, the weighting coefficient determination unit includes: The weight allocation scheme subunit is used to determine the target weight allocation scheme corresponding to the current driving scenario from multiple preset weight allocation schemes; The weight coefficient determination subunit is used to determine the weight coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters according to the target weight allocation scheme.

[0084] In some embodiments, the broadcast control parameter determination module 23 includes: The numerical range determination submodule is used to determine the target numerical range to which the in-vehicle environmental noise value belongs at the current moment from at least two candidate numerical ranges. The broadcast parameter determination submodule is used to determine the broadcast control parameters of navigation voice broadcast based on the preset adaptation rules corresponding to the target value range. The preset adaptation rules include the mapping relationship between multiple preset value ranges and broadcast control parameters. The broadcast control parameters include broadcast volume control parameters, broadcast timing control parameters, and broadcast content detail control parameters.

[0085] In some embodiments, the broadcast control parameter determination module 23 includes: The environmental noise difference calculation submodule is used to determine the noise difference between the in-vehicle environmental noise value at the previous moment and the in-vehicle environmental noise value at the current moment. The ambient noise difference comparison submodule is used to determine the navigation voice broadcast control parameters based on the in-vehicle ambient noise value at the previous moment if the noise difference is less than a preset threshold; or, if the noise difference is not less than a preset threshold, to determine the navigation voice broadcast control parameters based on the in-vehicle ambient noise value at the current moment.

[0086] Please see Figure 3 This application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, it implements the steps of a control method for navigation voice broadcast.

[0087] Since the electronic device described in this embodiment is the device used by the control device for implementing the navigation voice broadcast in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiments of this application is within the scope of protection of this application.

[0088] In practice, when the computer program 311 is executed by the processor, it can implement any of the embodiments corresponding to the first aspect.

[0089] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium storing computer program instructions. When the computer program instructions are loaded and executed by a processor, they implement the steps of the control method for navigation voice broadcasting as described above.

[0090] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0091] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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 of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

[0092] Although preferred embodiments have been described in this specification, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications beyond the scope of this specification.

[0093] Obviously, those skilled in the art can make various modifications to this specification without departing from its spirit and scope. Therefore, this specification also intends to include any modifications that fall within the scope of the claims and their equivalents.

Claims

1. A control method for navigation voice broadcasting, characterized in that, The method includes: During the driving process of the target vehicle, various in-vehicle environmental parameters are acquired at the current moment, wherein the in-vehicle environmental parameters are parameters that affect the navigation voice broadcast effect; The in-vehicle environment parameters are weighted and summed to determine the in-vehicle noise value of the target vehicle at the current time, wherein the in-vehicle noise value is used to characterize the degree of interference of the in-vehicle environment of the target vehicle with the navigation voice broadcast. Based on the current in-vehicle noise level, determine the navigation voice broadcast control parameters; According to the broadcast control parameters, the vehicle's in-vehicle voice system is controlled to broadcast navigation voice messages.

2. The method according to claim 1, characterized in that, The vehicle environment parameters include vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters. The step of weighted summation of these vehicle environment parameters to determine the in-vehicle noise value of the target vehicle at the current time includes: Obtain the weighting coefficients corresponding to vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters, respectively; The vehicle speed parameter, the window status parameter, the air conditioning operation parameter, and the in-vehicle noise parameter are weighted and summed based on weighting coefficients to obtain the in-vehicle noise value of the target vehicle at the current time.

3. The method according to claim 2, characterized in that, The weighting coefficients corresponding to the acquired vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters include: The current driving scenario of the target vehicle is determined based on vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters. Based on the current driving scenario, determine the weighting coefficients corresponding to the vehicle speed parameter, the window status parameter, the air conditioning operation parameter, and the in-vehicle noise parameter, respectively.

4. The method according to claim 3, characterized in that, The process of determining the current driving scenario of the target vehicle based on vehicle speed parameters, window status parameters, air conditioning operating parameters, and in-vehicle noise parameters includes: Determine whether the vehicle speed parameters, window status parameters, air conditioning operation parameters, and in-vehicle noise parameters meet their respective preset scene triggering conditions, and determine the preset scenes that meet the preset scene triggering conditions as candidate scenes; When only one of the candidate scenarios exists, the candidate scenario is taken as the current driving scenario; When at least two candidate scenarios exist, the current driving scenario is determined from the at least two candidate scenarios according to a preset priority; When no candidate scenario exists, the preset default scenario will be used as the current driving scenario.

5. The method according to claim 3, characterized in that, The step of determining the weighting coefficients corresponding to the vehicle speed parameter, the window status parameter, the air conditioning operating parameter, and the in-vehicle noise parameter based on the current driving scenario includes: Determine the target weight allocation scheme corresponding to the current driving scenario from multiple preset weight allocation schemes; Based on the target weight allocation scheme, the weight coefficients corresponding to the vehicle speed parameter, the window status parameter, the air conditioning operation parameter, and the in-vehicle noise parameter are determined respectively.

6. The method according to claim 1, characterized in that, The step of determining the navigation voice broadcast control parameters based on the current in-vehicle noise level includes: From at least two candidate value intervals, determine the target value interval to which the in-vehicle noise value at the current moment belongs; Based on the preset adaptation rules corresponding to the target value range, the broadcast control parameters of the navigation voice broadcast are determined. The preset adaptation rules include multiple preset value ranges and the broadcast control parameters. The broadcast control parameters include broadcast volume control parameters, broadcast timing control parameters, and broadcast content detail control parameters.

7. The method according to claim 1, characterized in that, The step of determining the navigation voice broadcast control parameters based on the current in-vehicle noise level includes: Determine the noise difference between the in-vehicle noise level at the previous moment and the in-vehicle noise level at the current moment; If the noise difference is less than a preset threshold, the navigation voice broadcasting control parameters are determined based on the in-vehicle noise value of the previous moment. If the noise difference is not less than the preset threshold, then the navigation voice broadcast control parameters are determined based on the in-vehicle environment noise value at the current moment.

8. A control device for navigation voice broadcasting, characterized in that, The device includes: The vehicle environment parameter acquisition module is used to acquire various vehicle environment parameters at the current time during the driving process of the target vehicle, wherein the vehicle environment parameters are parameters that affect the navigation voice broadcast effect; The in-vehicle environmental noise calculation module is used to perform weighted summation on each of the vehicle environmental parameters to determine the in-vehicle environmental noise value of the target vehicle at the current time, wherein the in-vehicle environmental noise value is used to characterize the degree of interference of the in-vehicle environment of the target vehicle on the navigation voice broadcast. The broadcast control parameter determination module is used to determine the broadcast control parameters for navigation voice broadcast based on the in-vehicle noise level at the current moment. The in-vehicle navigation voice broadcast module is used to control the in-vehicle voice system of the target vehicle to broadcast navigation voice messages according to the broadcast control parameters.

9. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program stored in the memory, implements the steps of the control method for navigation voice broadcasting as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the control method for navigation voice broadcasting as described in any one of claims 1 to 7.

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