Prompting method and device, vehicle, medium and program product

Abstract

The invention relates to a prompting method and device, a vehicle, a medium and a program product. The prompting method comprises the steps that tire pressure information of a tire is obtained; analyzing the tire sound signal acquired by the sound acquisition device, and determining tire noise information; and executing tire information prompt according to the tire noise information and the tire pressure information. Tire detection is performed in combination with the tire sound signal and the tire pressure information, so that the accuracy and reliability of tire detection are improved, and the accuracy of tire information prompt is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of automobile safety monitoring, and in particular to a prompting method, device, vehicle, medium, and program product. Background Art

[0002] Tires are key components that directly contact the road. Their condition not only affects the vehicle's driving performance and safety, but also directly impacts driving comfort and maintenance costs. Therefore, real-time monitoring and accurate assessment of tire condition are crucial. Summary of the Invention

[0003] To overcome the problems existing in the related art, the present disclosure provides a prompting method, device, vehicle, medium and program product.

[0004] According to a first aspect of an embodiment of the present disclosure, a prompting method is provided, comprising: Get tire pressure information; Analyze the tire sound signal collected by the sound collection device to determine tire noise information; A tire information prompt is performed according to the tire noise information and the tire pressure information.

[0005] This technical solution combines tire sound signals and tire pressure information for tire detection, improving the accuracy and reliability of tire detection and, consequently, the accuracy of tire information displayed. Dual verification of information collected by the tire pressure sensor and the sound collection device enables more precise tire anomaly detection, reducing missed and false alarms.

[0006] In some possible implementations, before analyzing the tire sound signal collected by the sound collection device to determine the tire noise information, the following steps are included: According to the tire pressure information corresponding to the tire, it is determined that there is no tire pressure drop in the tire.

[0007] The above technical solution directly determines whether there is any tire pressure drop through the tire pressure information, and then analyzes the tire sound signal to determine the tire noise information as a further judgment on whether there is any tire pressure drop. It can achieve more accurate tire abnormality detection and reduce missed reports.

[0008] In some possible implementations, performing tire information prompting based on the tire noise information and the tire pressure information includes: determining initial tire noise information of the tire according to the tire noise information; When the initial tire noise information indicates that an abnormality exists in the tire, the initial tire noise information is used as target prompt information to perform tire information prompting.

[0009] This technical solution determines initial tire noise information based on tire noise data. It leverages audio analysis technology to deeply analyze complex tire noise signals, accurately extracting characteristic parameters from the noise that reflect the tire's actual operating status. This technology then integrates real-time data from the tire pressure sensor to provide tire information notifications. This collaborative analysis effectively avoids the risk of misjudgment by a single sensor, improving the accuracy and reliability of tire detection and, consequently, the accuracy of tire information notifications.

[0010] In some possible implementations, when the initial tire noise information indicates that there is no abnormality in the tire, the tire pressure information and / or the tire pressure information are used as target prompt information to perform tire information prompting.

[0011] The above technical solution uses tire pressure information and / or tire pressure information as target prompt information, executes tire information prompts, and collaborative analysis effectively avoids the risk of misjudgment by a single sensor. In the absence of abnormalities and reduced tire pressure, the tire can be continuously monitored and prompts can be executed through tire pressure, allowing users to maintain understanding of tire information, improving the accuracy and reliability of tire detection, and thus improving the accuracy of tire information prompts.

[0012] In some possible implementations, the method further includes: When it is determined based on the tire pressure information corresponding to the tire that the tire pressure has dropped, the tire information prompt is performed using the tire pressure information as target prompt information.

[0013] The above technical solution can directly indicate that there are problems such as tire leakage when it is determined that the tire pressure is low based on the tire pressure information. The tire pressure information can be directly used as the target prompt information to execute the tire information prompt, avoiding more logical judgments and improving timeliness and prompt efficiency.

[0014] In some possible implementations, the sound collection device includes an external sound collection device disposed outside the vehicle and / or an internal sound collection device disposed inside the vehicle.

[0015] The above technical solution collects tire sound signals through sound collection devices inside and outside the vehicle, and combines them with tire pressure sensors for multi-sensor fusion analysis, which can more accurately identify potential tire problems, making up for the deficiency of only using tire pressure sensors to detect tire pressure to determine whether there is a tire abnormality, and improving the accuracy and reliability of tire monitoring and prompts.

[0016] In some possible implementations, the external vehicle collection device and / or the internal vehicle collection device is a microphone built into the vehicle body.

[0017] The above technical solution can reuse the built-in microphones outside and inside the vehicle to collect sound signals, reducing the manufacturing cost of the vehicle.

[0018] In some possible implementations, analyzing the tire sound signal collected by the sound collection device to determine tire noise information includes: Analyzing the tire sound signal collected by the external vehicle collection device to determine the external vehicle tire noise information corresponding to the external vehicle collection device; Analyzing the tire sound signal collected by the in-vehicle collection device to determine the in-vehicle tire noise information corresponding to the in-vehicle collection device; The tire noise information is determined according to the external tire noise information and / or the internal tire noise information.

[0019] The above-mentioned technical solution's off-board data collection device can more directly capture the noise generated by tire-ground friction. Therefore, by comparing on-board and off-board data, the source of abnormal tire noise can be detected. By integrating on-board and off-board tire noise information, multi-dimensional fault diagnosis can be achieved. By comparing the spectrum differences between the two, the noise source can be located. Combined with tire pressure data, tire information prompts are provided, improving the detection rate of tire anomalies and providing drivers with accurate prompts including fault location, severity, and repair recommendations, effectively improving driving safety and maintenance efficiency. This reduces false alarms, provides accurate prompts and warnings, and enhances vehicle driving safety.

[0020] In some possible implementations, analyzing the tire sound signal collected by the sound collection device to determine tire noise information includes: Performing time domain analysis on the tire sound signal to obtain tire noise amplitude information; Performing frequency domain analysis on the tire sound signal to obtain tire noise frequency distribution information; The tire noise information is determined according to the tire noise amplitude information and the tire noise frequency distribution information.

[0021] Abnormal frequency or amplitude changes of tire noise in the above technical solution (such as enhanced signals in certain frequency bands) may indicate potential cracks or puncture problems in the tire.

[0022] In some possible implementations, the method further includes: When the tire information indicates that an abnormality exists in the tire, a tire abnormality response control is executed on the vehicle.

[0023] The above technical solution triggers and executes tire abnormality response control when there is an abnormality in the tire, thereby improving driving safety.

[0024] In some possible implementations, the tire abnormality response control includes vehicle speed control; and executing the tire abnormality response control on the vehicle includes: determining a target speed of the vehicle according to the abnormality type of the tire abnormality; The vehicle speed is controlled according to the target vehicle speed.

[0025] The above technical solution triggers the execution of vehicle speed reduction control due to tire abnormality when there is an abnormality in the tire, thereby improving driving safety.

[0026] In some possible implementations, the tire abnormality response control includes suspension adjustment control; and the tire abnormality response control on the vehicle includes: Identify the target tire with abnormality; determining suspension adjustment information of the vehicle according to an installation position of the tire on the vehicle; The suspension of the vehicle is adjusted according to the suspension adjustment information.

[0027] The above technical solution adjusts the vehicle suspension system to balance the wheel load, reduce the pressure of the damaged tire, and improve driving safety when there is an abnormality in the tire.

[0028] In some possible implementations, the step of providing tire information prompts includes: The tire information prompt is performed through at least one of the following: a dashboard, a vehicle-mounted central control screen, a speaker, and a mobile terminal.

[0029] The above technical solution can execute tire information prompts on at least one of the dashboard, the vehicle's central control screen, the speaker, and the mobile terminal, thereby improving the flexibility of tire information prompts. At the same time, it is convenient for users to understand tire information in a timely manner, thereby improving vehicle driving safety.

[0030] According to a second aspect of an embodiment of the present disclosure, there is provided a prompting device, comprising: An acquisition module, configured to acquire tire pressure information of a tire; an analysis module configured to analyze the tire sound signal collected by the sound collection device to determine tire noise information; The prompt module is configured to perform tire information prompting according to the tire noise information and the tire pressure information.

[0031] In some possible implementations, the apparatus further includes: a determining module configured to: Before analyzing the tire sound signal collected by the sound collection device to determine the tire noise information, it is determined that there is no tire pressure drop in the tire based on the tire pressure information corresponding to the tire.

[0032] In some possible implementations, the prompt module is configured to: determining initial tire noise information of the tire according to the tire noise information; When the initial tire noise information indicates that an abnormality exists in the tire, the initial tire noise information is used as target prompt information to perform tire information prompting.

[0033] In some possible implementations, the prompt module is configured to: When the initial tire noise information indicates that there is no abnormality in the tire, the tire pressure information and / or the tire pressure information are used as target prompt information to perform tire information prompting.

[0034] In some possible implementations, the prompt module is configured to: When it is determined based on the tire pressure information corresponding to the tire that the tire pressure has dropped, the tire information prompt is executed using the tire pressure information as target prompt information.

[0035] In some possible implementations, the sound collection device includes an external sound collection device disposed outside the vehicle and / or an internal sound collection device disposed inside the vehicle.

[0036] In some possible implementations, the apparatus further includes: The response control module is configured to perform tire abnormality response control on the vehicle when the tire information indicates that the tire has an abnormality.

[0037] In some possible implementations, the tire abnormality response control includes vehicle speed control; and the response control module includes: a vehicle speed determination submodule, configured to determine a target vehicle speed of the vehicle according to the abnormality type of the tire abnormality; The vehicle speed control submodule is configured to control the vehicle speed according to the target vehicle speed.

[0038] In some possible implementations, the tire abnormality response control includes suspension adjustment control; the response control module includes: a tire determination submodule, configured to determine a target tire with an abnormality; an adjustment determination submodule, configured as a tire determination submodule, configured to determine suspension adjustment information of the vehicle according to an installation position of the tire on the vehicle; The suspension adjustment submodule is configured to adjust the suspension of the vehicle according to the suspension adjustment information.

[0039] According to a third aspect of an embodiment of the present disclosure, there is provided a vehicle, comprising: processor; a memory for storing processor-executable instructions; The processor is configured to execute the executable instructions stored in the memory to implement the method according to any one of the first aspects.

[0040] According to a fourth aspect of an embodiment of the present disclosure, there is provided a computer-readable storage medium having a computer program stored thereon, which implements the steps of any one of the methods described in the first aspect when executed by a processor.

[0041] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, comprising a computer program, which implements the steps of any one of the methods in the first aspect when executed by a processor.

[0042] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0044] Figure 1 The figure is a flowchart of a prompting method according to an exemplary embodiment.

[0045] Figure 2 An implementation according to an exemplary embodiment is shown Figure 1 Flowchart of step S13 in FIG.

[0046] Figure 3 An implementation according to an exemplary embodiment is shown Figure 1 Flowchart of step S11 in FIG.

[0047] Figure 4 The figure is a flowchart of another prompting method according to an exemplary embodiment.

[0048] Figure 5 The figure is a block diagram showing a prompting device according to an exemplary embodiment.

[0049] Figure 6 is a block diagram of a vehicle according to an exemplary embodiment. DETAILED DESCRIPTION

[0050] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0051] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the corresponding data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0052] Before introducing a prompting method provided by an embodiment of the present disclosure, we first introduce the technical solutions in related scenarios. TPMS (Tire Pressure Monitoring System) is divided into two types: direct and indirect systems. Direct tire pressure monitoring systems monitor tire pressure in real time through tire pressure sensors. Indirect tire pressure monitoring systems infer tire pressure changes based on data such as wheel speed, and then determine tire pressure based on tire pressure changes. However, if a tire is leaking slowly due to small cracks or punctures, and no obvious leak occurs, the tire pressure change rate is lower than the system threshold. For example, if a nail punctures the tire and becomes stuck in the tread without falling off, the leak rate is lower than the system threshold, and the tire pressure change cannot be identified. Therefore, the presence of cracks, punctures, etc. in the tire cannot be identified by tire pressure changes. At the same time, due to the lack of effective monitoring of tire wear, non-tire pressure-related defects that may cause a blowout cannot be identified in advance, resulting in delayed tire blowout warnings and affecting driving safety.

[0053] In view of this, the warning method provided in the embodiment of the present disclosure is intended to avoid tire blowout warning lag, and to improve the accuracy of identifying potential tire blowouts, thereby improving the accuracy and reliability of tire warnings, thereby improving vehicle driving safety.

[0054] Figure 1 is a flowchart of a prompting method according to an exemplary embodiment. Figure 1 As shown, the method can be applied to a vehicle, for example, the method provided by the embodiment of the present disclosure is executed by the vehicle's body domain controller (BDC) or intelligent cockpit domain controller (IDC), including the following steps.

[0055] In step S11 , tire pressure information of the tire is acquired.

[0056] Tire pressure information can be obtained through tire pressure sensors installed on the tire hub. Tire pressure sensors are used to monitor changes in tire internal pressure in real time and convert pressure information into electrical signals for output. Tire pressure sensors can monitor changes in tire pressure in real time for each tire, ensuring timely detection of abnormal tire pressure.

[0057] Among them, it is also possible to collect images of the tires and then perform tire image recognition to determine the tire pressure changes of each tire. By monitoring the tire pressure changes of each tire through images, it is also possible to ensure that tire pressure abnormalities are discovered in time.

[0058] In the disclosed embodiments, the tire pressure sensor continuously monitors the pressure inside the tire, converts the pressure value into an electrical signal, and transmits it to the vehicle control system. The control system determines the tire pressure information by comparing the current tire pressure with a preset normal range threshold.

[0059] In step S12, the tire sound signal collected by the sound collection device is analyzed to determine tire noise information.

[0060] The sound collection device may be a device for collecting tire sound signals, such as a microphone installed on a vehicle. In the embodiment of the present disclosure, the tire sound signals collected by the sound collection device can be processed and used to identify whether there is abnormal tire noise.

[0061] In the disclosed embodiment, the sound collection device and tire pressure sensor are automatically initialized after the vehicle is started. After initialization, the sound collection device and tire pressure sensor can be used to collect real-time tire [A31] sound signals and tire pressure information, respectively. Initialization is essential for ensuring real-time monitoring of tire status. This can reduce costs and improve monitoring capabilities based on existing hardware, especially when the tire pressure sensor and sound collection device are reused.

[0062] In the disclosed embodiments, the amplitude changes of the collected tire sound signals are observed along the time axis. Amplitude statistical parameters (such as mean, variance, and peak value) are calculated to describe the overall strength and fluctuation of the signal. For example, when tires are severely worn, the roughness of the contact surface increases, and the impact vibration generated by the tire hitting the road intensifies. This increases the mean amplitude of the tire noise signal, and may also increase the variance, reflecting more intense signal fluctuations.

[0063] In the disclosed embodiment, a Fourier transform is used to convert tire sound signals in the time domain into frequency domain signals, revealing the energy distribution of the signal at different frequencies. Different tire conditions correspond to different spectral characteristics. For example, tread wear can increase the energy of specific frequency components. By analyzing parameters such as the spectral center of gravity and dominant frequency offset, the extent of tire wear and possible abnormalities can be determined.

[0064] By combining amplitude information obtained from time-domain analysis (such as mean and peak amplitude values) with frequency distribution information from frequency-domain analysis (such as dominant frequency and harmonic distribution), a multidimensional feature vector is constructed to characterize tire noise. For example, as tire wear progresses, the amplitude in the time domain may increase, and the energy of certain frequency components in the frequency domain may also increase. Combining this information allows for more accurate determination of tire noise.

[0065] Furthermore, the tire sound signals corresponding to the sound collection device and the tire pressure information corresponding to the tire pressure sensor are collected and processed by the vehicle's intelligent cockpit domain controller (or other domain controller) to ensure continuous monitoring of tire pressure information and tire sound signals while the vehicle is driving.

[0066] In step S13 , tire information prompting is performed based on the tire noise information and the tire pressure information.

[0067] In the disclosed embodiment, the tire pressure information collected by the tire pressure sensor in real time for each tire is analyzed. After analysis, if the tire pressure of a tire is lower than a set safety threshold, or the tire pressure changes at a rate exceeding the safety limit, the tire can be marked as a potentially dangerous tire.

[0068] Furthermore, if a potentially hazardous tire is identified, tire noise information can be combined to verify tire abnormalities. For example, if the tire noise information indicates abnormal frequency or amplitude changes (such as increased signal strength in certain frequency bands), this could indicate a potential crack or puncture in the potentially hazardous tire, leading to low tire pressure or rapid changes in tire pressure.

[0069] In this way, if the tire pressure sensor detects a downward trend in tire pressure and the tire noise frequency analysis shows an abnormality, it will be determined that the tire may be at risk of cracks or punctures. Multi-sensor fusion can effectively reduce the false alarm rate and provide a more accurate fault identification mechanism. Tire abnormalities represented by tire noise information (such as frequency enhancement or irregular waveform) occur simultaneously with abnormal tire pressure and can trigger early warning prompts. For example, an early warning can be issued through the instrument panel, voice prompts, or the in-vehicle screen, suggesting slowing down or stopping to check the tires. For another example, tire abnormality information can be sent to a connected smart device (such as a smartphone, smartwatch / bracelet, etc.) via the in-vehicle network, reminding you to go to a nearby repair station for tire inspection or replacement.

[0070] In the disclosed embodiment, if both the tire noise information and the tire pressure information indicate that the tire is normal, a prompt message indicating that the tire is normal may be generated, and a tire information prompt may be provided. For example, the current tire pressure may be determined using the tire pressure information [A32] and displayed on the instrument panel.

[0071] This technical solution combines tire sound signals and tire pressure information for tire detection, improving the accuracy and reliability of tire detection and, consequently, the accuracy of tire information displayed. Dual verification of information collected by the tire pressure sensor and the sound collection device enables more precise tire anomaly detection, reducing missed and false alarms.

[0072] In some possible implementations, before analyzing the tire sound signal collected by the sound collection device to determine the tire noise information, the following steps are included: According to the tire pressure information corresponding to the tire, it is determined that there is no tire pressure drop in the tire.

[0073] In the disclosed embodiment, the tire pressure information obtained by the tire pressure sensor or image sensor can first be used to determine whether the tire pressure drops. If it is determined that there is no tire pressure drop, the sound signal analysis can be performed to further determine the tire information prompt, so as to avoid determining whether there is a tire pressure drop solely through the tire pressure information, which may cause inaccurate tire information determination.

[0074] Among them, the tire pressure information can be compared with the normal tire pressure threshold to determine whether it is within the normal range, and the first information obtained can also be the rate of change of the tire pressure over a period of time, and whether the rate of change exceeds a preset threshold to obtain the second information.

[0075] In the disclosed embodiment, normal tire pressure range thresholds are pre-set for different vehicle models and tire specifications. These thresholds are based on vehicle manufacturer recommendations and extensive experimental data, ensuring that tires maintain good performance and safety under normal driving conditions. Upon obtaining real-time tire pressure information from the corresponding tire pressure sensor, the system compares this real-time tire pressure value with the pre-set normal tire pressure range threshold. If the real-time tire pressure value is lower than the lower limit of the normal tire pressure range, the tire is determined to have low tire pressure.

[0076] In the disclosed embodiment, tire pressure data is continuously collected at multiple time points to calculate the rate of change of tire pressure. If tire pressure drops rapidly over a short period of time, even if the current pressure value is not below the lower limit of the normal tire pressure range, it may indicate an abnormal condition such as a tire leak. In this case, it is also determined to be a low tire pressure. For example, a pressure drop of more than 0.2 bar within 10 minutes is considered an abnormal rate of change.

[0077] Among them, the tire pressure information determines that there is no tire pressure drop. Through the analysis of sound signals, potential problems with tire pressure can be discovered in time, such as slow air leakage although the tire pressure has not dropped.

[0078] The above technical solution directly determines whether there is any tire pressure drop through the tire pressure information, and then analyzes the tire sound signal to determine the tire noise information as a further judgment on whether there is any tire pressure drop. It can achieve more accurate tire abnormality detection and reduce missed reports.

[0079] In one possible implementation, see Figure 2 As shown, in step S13, the tire information prompt is executed according to the tire noise information and the tire pressure information, including: In step S131 , initial tire noise information of the tire is determined according to the tire noise information.

[0080] In the disclosed embodiment, normal tire noise data can be pre-stored. This data covers tire noise characteristics under different vehicle models and driving conditions (e.g., different road surfaces and different speeds). Once real-time tire noise information is acquired, it is compared with the pre-stored normal tire noise characteristic model to determine whether any tire anomalies exist.

[0081] The comparison model, which can be trained based on a machine learning algorithm (such as a neural network or support vector machine), can classify and evaluate the input tire noise information. By calculating the similarity or difference between the real-time tire noise characteristics and the normal model, it can determine whether the initial tire noise information is within the normal range.

[0082] In the disclosed embodiments, a series of thresholds based on tire noise characteristic parameters can be set. For example, upper and lower thresholds can be set for parameters such as the mean amplitude of the tire noise, the dominant frequency of the frequency distribution, and the energy content of specific frequency bands. When the real-time tire noise characteristic parameters exceed these thresholds, initial abnormal tire noise information is obtained. When the real-time tire noise characteristic parameters do not exceed these thresholds, initial normal tire noise information is obtained.

[0083] For example, when a certain vehicle model is driving normally on a flat asphalt road, the dominant frequency of tire noise is typically concentrated in the 500-800Hz range, with an average amplitude of 0.5-0.8V (assuming the voltage value of the processed signal is correlated with the amplitude). While the vehicle is driving, the collected tire noise information shows that the dominant frequency has shifted to 1200Hz, with an average amplitude of 1.2V. The system compares this real-time tire noise signature with a normal model and finds that both the dominant frequency and average amplitude are outside the normal range. The average amplitude also exceeds the preset 1.0V threshold, thus determining that the initial tire noise information is abnormal, possibly indicating wear or other problems.

[0084] In step S132 , when the initial tire noise information indicates that the tire is abnormal, the initial tire noise information is used as target prompt information to perform tire information prompting.

[0085] In the disclosed embodiments, after determining the initial tire noise information, if the initial tire noise information indicates a tire abnormality, the abnormal tire noise information can be analyzed. Tire pressure information reflects the internal pressure state of the tire and is potentially correlated with the tire noise information. For example, low tire pressure may increase the tire-ground contact area, thereby changing the frequency distribution and amplitude of the tire noise. By establishing a multi-parameter correlation model that comprehensively considers tire noise characteristic parameters (such as amplitude and frequency) and tire pressure parameters (such as pressure value and pressure change rate), the specific type and severity of the tire abnormality can be determined.

[0086] In the disclosed embodiments, rules based on multi-parameter fusion can be preset. These rules can be derived from a large amount of experimental data and actual case studies, and are used to map the fused parameter information to specific tire problem types and corresponding prompt strategies. For example, when the tire noise amplitude increases abnormally and the tire pressure is a certain percentage below the normal range, it is determined that the tire may have a leak or severe wear. When the high-frequency component energy of the tire noise increases and the tire pressure is normal, it may indicate that the tire has local structural damage. Based on the matched rules, it is determined which tire information prompt method to execute.

[0087] In the disclosed embodiments, after determining the prompt strategy, tire information can be communicated to the driver through various means. For example, it can be displayed via a pop-up window on the vehicle's display screen, an audible alarm, or a push notification via a mobile app. The prompt will clearly indicate the tire problem (e.g., low tire pressure, severe tire wear), the severity of the problem (e.g., mild, moderate, severe), and the recommended action (e.g., prompt inspection, immediate stop for repair, etc.).

[0088] For example, suppose the initial tire noise information for a particular tire indicates an abnormality, such as a 40% increase in average tire noise amplitude and a 30% increase in high-frequency component energy. At the same time, the tire pressure sensor for that tire indicates a pressure of 1.8 bar, while the normal pressure range is 2.2-2.5 bar, representing a decrease of approximately 20%. Multi-parameter fusion analysis can be performed to match a pre-set rule: an abnormally increased tire noise amplitude and a pressure drop exceeding 15% indicate a possible tire leak, leading to insufficient pressure and increased tire wear. A red warning box can then pop up on the vehicle's display, stating, "Tire pressure is too low (currently 1.8 bar) and abnormal tire noise. This may indicate a leak or wear issue. Please stop and check immediately and refill tire pressure." A sharp warning tone can also be emitted to alert the driver. The same notification can also be sent to the driver via a mobile app, allowing them to stay informed of the vehicle's condition.

[0089] This technical solution determines initial tire noise information based on tire noise data. It leverages audio analysis technology to deeply analyze complex tire noise signals, accurately extracting characteristic parameters from the noise that reflect the tire's actual operating status. This technology then integrates real-time data from the tire pressure sensor to provide tire information notifications. This collaborative analysis effectively avoids the risk of misjudgment by a single sensor, improving the accuracy and reliability of tire detection and, consequently, the accuracy of tire information notifications.

[0090] In some possible implementations, the method further includes: When the initial tire noise information indicates that there is no abnormality in the tire, the tire pressure information and / or the tire pressure information are used as target prompt information to perform tire information prompting.

[0091] In the disclosed embodiments, if both tire pressure information and tire pressure information can confirm that the tire has not underinflated, either tire pressure information or tire pressure information can be used as the target prompt information. Tire pressure information can intuitively reflect the current inflation status of the tire. Based on the preset prompt strategy, an appropriate method is selected to convey the low tire pressure information to the driver. Common prompt methods include pop-up displays on the vehicle display, sound alarms, and mobile phone app push notifications.

[0092] In some possible implementations, the method further includes: When it is determined based on the tire pressure information corresponding to the tire that the tire pressure has dropped, the tire information prompt is executed using the tire pressure information as target prompt information.

[0093] The prompt will indicate which tire has experienced a drop in pressure, along with the current pressure value. It will also provide recommendations based on the severity of the drop. For example, if the drop is only minor, the driver may be prompted to check and refill the tires as soon as possible. A significant drop in pressure may prompt the driver to stop and check immediately to avoid potential safety hazards.

[0094] The above technical solution uses tire pressure information as target prompt information to perform early warning after confirming that the tire pressure has dropped, and realizes that the tire pressure sensor detects the tire pressure. In the implementation of the present disclosure, after determining that the tire pressure has dropped based on the tire pressure, it can be directly determined that there is a tire abnormality.

[0095] In this disclosure, tire pressure information is communicated to the driver using a pre-set notification strategy. This notification typically includes an on-board display screen or a push notification on a mobile app. The notification clearly identifies the tire and the current pressure, and informs the driver that the pressure is outside the normal range.

[0096] The above technical solution can continuously monitor the tire through tire pressure and issue prompts when there is an abnormality in the tire, so that the user can keep aware of the tire information.

[0097] In some possible implementations, the method further includes: When the initial tire noise information indicates that there is no abnormality in the tire, the tire pressure information is used as target prompt information to perform tire information prompting.

[0098] In the present disclosure, the initial tire noise information indicates that there is no abnormality in the tire (i.e., the tire is normal), but tire pressure information is equally important for safe driving of the vehicle. Therefore, the tire pressure information of the tire is used as the target prompt information.

[0099] Similarly, the prompt method can include on-board display screen display, voice broadcast, etc. In the prompt content, it will clearly indicate which tire and the current tire pressure value, and inform the driver that the tire pressure is within the normal range.

[0100] The above technical solution continuously monitors the tire through tire pressure and issues prompts when the initial tire noise information indicates that there is no abnormality in the tire, so that the user can keep informed of the tire information.

[0101] In some possible implementations, the sound collection device includes an external sound collection device disposed outside the vehicle and / or an internal sound collection device disposed inside the vehicle.

[0102] In some possible implementations, the external vehicle collection device and / or the internal vehicle collection device is a microphone built into the vehicle body.

[0103] In the disclosed embodiments, the in-vehicle sound collection device installed inside the vehicle can be an in-vehicle microphone. The tire sound signals collected by the in-vehicle microphone are subjected to time domain analysis (e.g., detecting sudden amplitude changes) and frequency domain analysis (e.g., Fourier transform analysis of frequency distribution). Abnormal frequency or amplitude changes in tire noise (e.g., signal enhancement in certain frequency bands) can indicate potential tire cracks or punctures.

[0104] Tire noise monitoring is performed using only the in-car microphone and tire pressure sensor. It is suitable for vehicles without external microphones. By reusing the in-car microphone, low-cost tire noise monitoring can be achieved.

[0105] The external collection device installed outside the vehicle can be an external microphone. If the vehicle is equipped with an external microphone, both the external microphone and the internal microphone can collect sound signals. These signals can then be combined with the tire sound signals from the external microphone for more precise frequency analysis. The external microphone can more directly capture the noise generated by tire-ground friction. Therefore, by comparing internal and external data, the source of abnormal tire noise can be verified. For vehicles equipped with an external microphone, combining the data from the internal and external microphones allows for more accurate tire noise analysis and judgment. This system is suitable for vehicles requiring higher safety and real-time performance.

[0106] The above technical solution collects tire sound signals through sound collection devices inside and outside the vehicle, and combines them with tire pressure sensors for multi-sensor fusion analysis, which can more accurately identify potential tire problems, making up for the deficiency of only using tire pressure sensors to detect tire pressure to determine whether there is a tire abnormality, and improving the accuracy and reliability of tire monitoring and prompts.

[0107] For some possible implementations, see Figure 3 As shown, in step S11, analyzing the tire sound signal collected by the sound collection device to determine tire noise information includes: In step S111, the tire sound signal collected by the external vehicle collection device is analyzed to determine the external vehicle tire noise information corresponding to the external vehicle collection device.

[0108] In the disclosed embodiments, the tire sound signals collected by the off-board collection device often contain various noise interferences, such as ambient wind noise and the sounds of other vehicles. Therefore, the signal must first be preprocessed to enhance the characteristics of the tire noise signal. Common preprocessing methods include filtering, such as using a bandpass filter. The filter's upper and lower cutoff frequencies are set based on the frequency range of the tire noise (typically between tens of hertz and several kilohertz). This allows only signals within this frequency range to pass, thereby filtering out both low- and high-frequency noise interferences.

[0109] After preprocessing, the signal needs to be feature extracted to obtain key information representative of external tire noise. Commonly used features include time domain features and frequency domain features. Time domain features, such as the signal's mean, variance, and peak value, can reflect the overall amplitude and fluctuation of the signal. For example, calculating the signal's mean within a certain time window can reveal the average strength of the tire noise signal; the variance measures the signal's dispersion, reflecting the instability of the tire noise. Frequency domain features, using methods such as Fourier transform, convert the time domain signal into a frequency domain signal to extract parameters such as the dominant frequency and frequency band energy. The dominant frequency is the frequency with the highest energy concentration in the tire noise signal. Different tire wear levels and tire pressure conditions may cause the dominant frequency to vary. The frequency band energy reflects the energy distribution of the signal within different frequency ranges. For example, increased energy in certain frequency bands may indicate a tire abnormality. The extracted time and frequency domain features are integrated to form external tire noise information. This feature information can be a multidimensional vector, with each dimension representing a specific characteristic parameter, which comprehensively describes the characteristics of external tire noise.

[0110] In step S112, the tire sound signal collected by the in-vehicle collection device is analyzed to determine the in-vehicle tire noise information corresponding to the in-vehicle collection device.

[0111] In the disclosed embodiments, the tire sound signals collected by the in-vehicle collection device are also subject to various in-vehicle noise influences, such as the sounds generated by the operation of electronic devices and the conversations of passengers. Preprocessing methods are similar to those for external signals. First, filtering is employed. Based on the approximate frequency range of the in-vehicle tire noise (which may differ from that outside the vehicle, as the frequency components typically change after propagation through the vehicle body structure), appropriate filter parameters are set to remove frequency components unrelated to the tire noise. Furthermore, noise reduction algorithms, such as adaptive filtering, may be employed to eliminate noise components from the tire noise signal by using reference noise signals (e.g., signals from other known noise sources within the vehicle).

[0112] Feature extraction for tire noise inside a vehicle also involves both time and frequency domain features. For time domain features, in addition to basic parameters such as mean, variance, and peak, other parameters such as the signal's rise and fall times can also be considered. These parameters can reflect the temporal variation of the tire noise signal. For frequency domain features, a Fourier transform is also performed to obtain information such as the main frequency and frequency band energy. However, because tire noise inside a vehicle is attenuated and reflected by the vehicle body structure, its frequency domain characteristics may differ from those of tire noise outside the vehicle. For example, some high-frequency components may be significantly attenuated.

[0113] The extracted time-domain and frequency-domain features of the tire noise are integrated to form the tire noise information. This can also be represented as a multi-dimensional vector to accurately describe the characteristics of the tire noise.

[0114] In step S113 , the tire noise information is determined according to the external tire noise information and the internal tire noise information.

[0115] In the disclosed embodiment, the tire noise information outside the vehicle and the tire noise information inside the vehicle are fused to comprehensively reflect the overall characteristics of the tire noise. The fusion method can adopt a simple splicing method to directly connect the feature vectors outside the vehicle and inside the vehicle to form a longer feature vector. A weighted fusion method can also be adopted to assign different weights to different feature parameters according to the importance of the tire noise outside the vehicle and inside the vehicle to the tire state assessment, and then perform a weighted sum. For example, if it is believed that the main frequency information of the tire noise outside the vehicle can better reflect the friction state between the tire and the road surface, and the frequency band energy information of the tire noise inside the vehicle can better reflect the transmission characteristics of the vehicle body to the tire noise, then higher weights can be assigned to the main frequency outside the vehicle and the frequency band energy inside the vehicle, respectively.

[0116] For example, abnormal tire noise (such as increased frequency or abnormal waveform) detected by external and internal acquisition devices is compared with normal tire noise frequencies to determine whether the noise source is related to tire cracks or punctures. Through big data collection and machine learning, tire noise characteristic values ​​can be extracted for different vehicle speeds, road surfaces, and tire conditions (normal, cracked, or punctured), further improving monitoring quality.

[0117] The above-mentioned technical solution's off-board data collection device can more directly capture the noise generated by tire-ground friction. Therefore, by comparing on-board and off-board data, the source of abnormal tire noise can be detected. By integrating on-board and off-board tire noise information, multi-dimensional fault diagnosis can be achieved. By comparing the spectrum differences between the two, the noise source can be located. Combined with tire pressure data, tire information prompts are provided, improving the detection rate of tire anomalies and providing drivers with accurate prompts including fault location, severity, and repair recommendations, effectively improving driving safety and maintenance efficiency. This reduces false alarms, provides accurate prompts and warnings, and enhances vehicle driving safety.

[0118] In some possible implementations, in step S11, analyzing the tire sound signal collected by the sound collection device to determine tire noise information includes: The tire sound signal is analyzed in the time domain to obtain tire noise amplitude information.

[0119] In the disclosed embodiments, a sound collection device (such as a microphone) converts the continuous tire sound signal into an electrical signal, which is then sampled and quantized by an analog-to-digital converter (ADC). Sampling discretizes the continuous analog signal in time, capturing the instantaneous value of the signal at fixed intervals (the sampling frequency). Quantization converts the sampled continuous amplitude signal into discrete digital values ​​for computer processing. For example, if the sampling frequency is set to 44.1kHz, 44,100 signal samples are collected per second.

[0120] In the time domain, amplitude represents the signal's intensity at a specific moment. For discretized tire noise signals, amplitude information can be obtained by calculating the voltage value (or normalized value) at each sampling point. A common approach is to directly read the value at each sampling point. Alternatively, statistics such as the average, maximum, and minimum amplitudes of the sampling points over a period of time can be calculated to more comprehensively describe the amplitude characteristics of the tire noise. For example, calculating the average amplitude of all sampling points within a one-second period can reflect the average intensity of the tire noise during that period.

[0121] Extracting time-domain characteristic parameters further describes tire noise amplitude information, such as amplitude variance and standard deviation. Variance and standard deviation measure the dispersion of the amplitude and reflect the fluctuation of tire noise amplitude. A large variance indicates significant variations in tire noise amplitude at different times, potentially indicating unstable tire-road friction.

[0122] Perform frequency domain analysis on the tire sound signal to obtain tire noise frequency distribution information.

[0123] In the disclosed embodiments, the Fourier transform decomposes a time-domain signal into a linear combination of sine and cosine functions at different frequencies, thereby determining the signal's energy distribution at each frequency. For discrete tire sound signals, a discrete Fourier transform (DFT) or fast Fourier transform (FFT) algorithm is used for calculation. The FFT is a highly efficient implementation of the DFT, significantly reducing computational complexity. For example, for a discrete signal of length N, the FFT algorithm can complete the transformation within logarithmic time complexity.

[0124] After a Fourier transform, the signal's spectrum is obtained, namely the amplitude spectrum or power spectrum of the signal at different frequencies. The amplitude spectrum indicates the amplitude of each frequency component, while the power spectrum indicates the energy of each frequency component. By analyzing the spectrum, the primary frequency components of the tire noise signal and their relative intensities can be determined. For example, the tire noise spectrum may have one or more distinct peaks. The frequencies corresponding to these peaks are the primary frequency components of the tire noise, which may be related to the tire's rotational frequency, the friction frequency between the tire and the road, and other factors.

[0125] Extract other frequency domain characteristic parameters, such as analyzing the total energy of the signal within the frequency range to obtain the band energy, center frequency, etc. The center frequency can be the weighted average frequency of the band energy, which is used to reflect the concentration location of the band energy.

[0126] The tire noise information is determined according to the tire noise amplitude information and the tire noise frequency distribution information.

[0127] In this disclosed embodiment, the tire noise amplitude information obtained from time-domain analysis and the tire noise frequency distribution information obtained from frequency-domain analysis are integrated. This information can be combined into a multi-dimensional feature vector, with each dimension representing a specific characteristic parameter. For example, the feature vector can be represented by (average amplitude, variance, primary frequency components, frequency band energy, etc.).

[0128] In the aforementioned technical solution, abnormal frequency or amplitude changes in tire noise (such as signal enhancement in certain frequency bands) may indicate potential tire cracks or punctures. By fusing tire sound signals with tire pressure information, more accurate multi-sensor analysis can be performed. Therefore, if the tire pressure sensor detects a decreasing tire pressure trend and the tire noise frequency analysis shows an abnormality, it can be determined that the tire may be at risk of cracks or punctures, and a warning can be issued. Multi-sensor fusion can effectively reduce false alarm rates and provide a more accurate fault identification mechanism. Abnormal results identified by the tire sound signal (such as frequency enhancement or irregular waveform) occur simultaneously with the tire pressure abnormality indicated by the tire pressure information, improving the accuracy of the warning.

[0129] For some possible implementations, see Figure 4 As shown, the method further includes: In step S14 , when the tire information indicates that the tire has an abnormality, a tire abnormality response control is executed on the vehicle.

[0130] In the disclosed embodiments, responding to tire anomalies on the vehicle may include actively reducing vehicle speed to prevent accidents caused by tire blowouts. For vehicles equipped with electronic suspension control, in the event of severe underinflation, the vehicle's suspension system can be adjusted to balance wheel loads, reduce pressure on damaged tires, and enhance driving safety. Speed ​​reduction and suspension adjustments can be implemented, thereby synergizing the vehicle's suspension and braking systems to improve driving safety in the event of tire anomalies.

[0131] The disclosed embodiments can implement response control through the following process: system startup, activation of sensors (such as tire pressure sensors and in-vehicle / out-vehicle microphones), and signal acquisition through the sensors (i.e., tire pressure information is collected through the tire pressure sensors, and tire sound signals are collected through in-vehicle / out-vehicle microphones). The tire pressure information and tire sound signals are then analyzed, and the analysis results from multiple sensors are fused to determine whether there are any tire abnormalities. If the tire information indicates a tire abnormality, a real-time warning is issued by the vehicle itself, a warning is executed by the smart device, and response control (deceleration / suspension adjustment) is triggered. If the tire information indicates no tire abnormality, the tire pressure information can be displayed in real time.

[0132] In the disclosed embodiments, a mapping relationship between tire anomaly types and corresponding response control strategies is pre-established. Different tire anomaly types, such as low tire pressure or severe localized tire wear, have varying degrees of impact on vehicle safety and require different response measures. For example, low tire pressure can increase tire-ground contact area, increasing fuel consumption and tire wear, and in severe cases, can even cause a tire blowout. For low tire pressure, the response strategy might be to remind the driver to inflate the tire promptly.

[0133] The above technical solution triggers and executes tire abnormality response control when there is an abnormality in the tire, thereby improving driving safety.

[0134] In some possible implementations, in step S14, the tire abnormality response control includes vehicle speed control. The tire abnormality response control on the vehicle includes: A target vehicle speed of the vehicle is determined according to the abnormality type of the tire abnormality.

[0135] In the disclosed embodiment, the target speed of the vehicle may be determined based on the type of tire abnormality and road information of the current road (eg, road type, minimum speed limit).

[0136] The vehicle speed is controlled according to the target vehicle speed.

[0137] In the disclosed embodiment, if the current vehicle speed is greater than the target speed, the vehicle can be controlled to reduce the speed to the target speed. If the current vehicle speed is less than the target speed, the vehicle can be controlled to maintain the current speed.

[0138] The above technical solution triggers the execution of vehicle speed reduction control due to tire abnormality when there is an abnormality in the tire, thereby improving driving safety.

[0139] In some possible implementations, in step S14, the tire abnormality response control includes suspension adjustment control. The tire abnormality response control on the vehicle includes: Identify the target tire with the abnormality.

[0140] In the disclosed embodiment, when a tire anomaly is detected, the system needs to determine the specific tire experiencing the anomaly based on the sensor's installation location and the vehicle's layout. Vehicle sensors are typically associated with specific tires. By reading the sensor's identification information and the predefined tire location codes on the vehicle, the target tire with the anomaly can be accurately located. For example, if a tire pressure sensor is installed on the vehicle's front left tire, when that sensor detects abnormal data, the system can determine that the front left tire is the target tire with the anomaly.

[0141] Suspension adjustment information of the vehicle is determined according to the installation position of the tire on the vehicle.

[0142] In the disclosed embodiment, if the target tire pressure is too low, the tire's contact area with the ground increases, potentially causing the vehicle to roll or experience increased turbulence during driving. The stiffness of the suspension corresponding to the tire can be appropriately increased to improve vehicle support and reduce roll. Therefore, based on the installation location, the suspension adjustment information can be determined to adjust the stiffness and height of the suspension corresponding to the installation location.

[0143] In the disclosed embodiment, specific suspension adjustment information is generated based on the relationship between the vehicle's suspension system and tire position, as well as the established suspension adjustment strategy. This suspension adjustment information typically includes the suspension component to be adjusted, the direction of adjustment (increase or decrease), and the magnitude of the adjustment. For example, it is determined that the suspension stiffness corresponding to the right rear tire needs to be adjusted in the direction of increase and by 10%.

[0144] The suspension of the vehicle is adjusted according to the suspension adjustment information.

[0145] In the disclosed embodiment, the suspension control system controls the corresponding actuators based on the analyzed suspension adjustment information. The actuators of the suspension system typically include electric control valves, motors, etc. For example, if the suspension stiffness needs to be adjusted, the suspension control system will control the electric control valves to change the preload of the springs in the suspension or adjust the internal structure of the shock absorbers to achieve stiffness adjustment. If the suspension height needs to be adjusted, the control system will control the motor to drive the suspension lifting mechanism to change the vehicle body height.

[0146] The above technical solution adjusts the vehicle suspension system to balance the wheel load, reduce the pressure of the damaged tire, and improve driving safety when there is an abnormality in the tire.

[0147] In some possible implementations, the step of providing tire information prompts includes: The tire information prompt is performed through at least one of the following: a dashboard, a vehicle-mounted central control screen, a speaker, and a mobile terminal.

[0148] In the disclosed embodiments, tire pressure information can be displayed via text or icons, for example, on an instrument panel, head-up display, or on a mobile device such as a cell phone or smartwatch. Alternatively, tire information can be provided via voice or other more intuitive and convenient means.

[0149] The above technical solution can execute tire information prompts on at least one of the dashboard, the vehicle's central control screen, the speaker, and the mobile terminal, thereby improving the flexibility of tire information prompts. At the same time, it is convenient for users to understand tire information in a timely manner, thereby improving vehicle driving safety.

[0150] The present disclosure provides a prompting device, see Figure 5 Shown, including: An acquisition module 510 is configured to acquire tire pressure information of a tire; The analysis module 520 is configured to analyze the tire sound signal collected by the sound collection device to determine tire noise information; The prompt module 530 is configured to perform tire information prompting according to the tire noise information and the tire pressure information.

[0151] In some possible implementations, the apparatus further includes: a determining module configured to: Before analyzing the tire sound signal collected by the sound collection device to determine the tire noise information, it is determined that there is no tire pressure drop in the tire based on the tire pressure information corresponding to the tire.

[0152] In some possible implementations, the prompt module 530 is configured to: determining initial tire noise information of the tire according to the tire noise information; When the initial tire noise information indicates that an abnormality exists in the tire, the initial tire noise information is used as target prompt information to perform tire information prompting.

[0153] In some possible implementations, the prompt module 530 is configured to: When the initial tire noise information indicates that there is no abnormality in the tire, the tire pressure information and / or the tire pressure information are used as target prompt information to perform tire information prompting.

[0154] In some possible implementations, the prompt module 530 is configured to: When it is determined based on the tire pressure information corresponding to the tire that the tire pressure has dropped, the tire information prompt is executed using the tire pressure information as target prompt information.

[0155] In some possible implementations, the sound collection device includes an external sound collection device disposed outside the vehicle and / or an internal sound collection device disposed inside the vehicle.

[0156] In some possible implementations, the external vehicle collection device and / or the internal vehicle collection device is a microphone built into the vehicle body.

[0157] In some possible implementations, the analysis module 520 includes: an external vehicle signal analysis submodule, configured to analyze the tire sound signal collected by the external vehicle acquisition device to determine the external vehicle tire noise information corresponding to the external vehicle acquisition device; an in-vehicle signal analysis submodule, configured to analyze the tire sound signal collected by the in-vehicle collection device to determine in-vehicle tire noise information corresponding to the in-vehicle collection device; The fusion analysis submodule is configured to determine the tire noise information based on the external tire noise information and the internal tire noise information.

[0158] In some possible implementations, the analysis module 520 includes: a time domain analysis submodule, configured to perform time domain analysis on the tire sound signal to obtain tire noise amplitude information; a frequency domain analysis submodule, configured to perform frequency domain analysis on the tire sound signal to obtain tire noise frequency distribution information; The determination and analysis submodule is configured to determine the tire noise information according to the tire noise amplitude information and the tire noise frequency distribution information.

[0159] In some possible implementations, the apparatus further includes: The response control module is configured to perform tire abnormality response control on the vehicle when the tire information indicates that the tire has an abnormality.

[0160] In some possible implementations, the tire abnormality response control includes vehicle speed control; and the response control module includes: a vehicle speed determination submodule, configured to determine a target vehicle speed of the vehicle according to the abnormality type of the tire abnormality; The vehicle speed control submodule is configured to control the vehicle speed according to the target vehicle speed.

[0161] In some possible implementations, the tire abnormality response control includes suspension adjustment control; the response control module includes: a tire determination submodule, configured to determine a target tire with an abnormality; an adjustment determination submodule, configured as a tire determination submodule, configured to determine suspension adjustment information of the vehicle according to an installation position of the tire on the vehicle; The suspension adjustment submodule is configured to adjust the suspension of the vehicle according to the suspension adjustment information.

[0162] In some possible implementations, the prompt module 530 is configured to execute the tire information prompt through at least one of the following: a dashboard, a vehicle-mounted central control screen, a speaker, and a mobile terminal.

[0163] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0164] The present disclosure also provides a vehicle, including: processor; a memory for storing processor-executable instructions; The processor is configured to execute the executable instructions stored in the memory to implement the method described in any one of the aforementioned embodiments.

[0165] An embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method described in any one of the aforementioned embodiments are implemented.

[0166] An embodiment of the present disclosure provides a computer program product, including a computer program, which implements the steps of any one of the methods in the aforementioned embodiments when executed by a processor.

[0167] Figure 6 FIG6 is a block diagram illustrating a vehicle 600 according to an exemplary embodiment. For example, vehicle 600 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or another type of vehicle. Vehicle 600 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0168] Reference Figure 6 Vehicle 600 may include various subsystems, such as an infotainment system 610, a perception system 620, a decision control system 630, a drive system 640, and a computing platform 650. Vehicle 600 may also include more or fewer subsystems, and each subsystem may include multiple components. Furthermore, each subsystem and each component of vehicle 600 may be interconnected via wired or wireless means.

[0169] In some embodiments, the infotainment system 610 may include a communication system, an entertainment system, a navigation system, and the like.

[0170] The perception system 620 may include several sensors for sensing information about the environment surrounding the vehicle 600. For example, the perception system 620 may include a global positioning system (which may be a GPS system, a BeiDou system, or another positioning system), an inertial measurement unit (IMU), a laser radar, a millimeter-wave radar, an ultrasonic radar, and a camera.

[0171] The decision control system 630 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0172] The drive system 640 may include components that provide power to the vehicle 600. In one embodiment, the drive system 640 may include an engine, an energy source, a transmission system, and wheels. The engine may be an internal combustion engine, an electric motor, an air compression engine, or a combination thereof. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0173] Some or all functions of the vehicle 600 are controlled by a computing platform 650. The computing platform 650 may include at least one processor 651 and a memory 652. The processor 651 may execute instructions 653 stored in the memory 652.

[0174] The processor 651 can be any conventional processor, such as a commercially available CPU. The processor can also include a graphics processor (GPU), a field programmable gate array (FPGA), a system on chip (SOC), an application specific integrated circuit (ASIC), or a combination thereof.

[0175] The memory 652 may be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0176] In addition to instructions 653 , memory 652 may also store data, such as road maps, route information, and vehicle location, direction, speed, etc. The data stored in memory 652 may be used by computing platform 650 .

[0177] In the embodiment of the present disclosure, the processor 651 may execute the instruction 653 to complete all or part of the steps of the above-mentioned prompting method.

[0178] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the appended claims.

[0179] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A prompting method, characterized in that: include: Get tire pressure information; Analyze the tire sound signal collected by the sound collection device to determine tire noise information; A tire information prompt is performed according to the tire noise information and the tire pressure information.

2. The method [A1] according to claim 1, characterized in that Before analyzing the tire sound signal collected by the sound collection device to determine the tire noise information, the method includes: According to the tire pressure information corresponding to the tire, it is determined that there is no tire pressure drop in the tire.

3. The method [A2] according to claim 2, characterized in that The performing tire information prompt according to the tire noise information and the tire pressure information includes: determining initial tire noise information of the tire according to the tire noise information; When the initial tire noise information indicates that an abnormality exists in the tire, the initial tire noise information is used as [A3] as target prompt information to perform tire information prompting.

4. The method [A4] according to claim 3, characterized in that The method further comprises: When the initial tire noise information indicates that there is no abnormality in the tire, the tire pressure information and / or the tire pressure information is used as [A5] target prompt information to perform tire information prompting.

5. The method according to claim 2 [A6], characterized in that The method further comprises: When it is determined based on the tire pressure information corresponding to the tire that the tire pressure has dropped, the tire pressure information is used as [A7] as target prompt information to execute the tire information prompt.

6. The method according to claim 1 [A8], characterized in that The sound collecting device includes an external sound collecting device arranged outside the vehicle and / or an internal sound collecting device arranged inside the vehicle.

7. The method according to claim 6 [A9], characterized in that The external vehicle collection device and / or the internal vehicle collection device is a microphone built into the vehicle body.

8. The method [A10] according to claim 7, characterized in that The analyzing the tire sound signal collected by the sound collection device to determine the tire noise information includes: Analyzing the tire sound signal collected by the external vehicle collection device to determine the external vehicle tire noise information corresponding to the external vehicle collection device; Analyzing the tire sound signal collected by the in-vehicle collection device to determine the in-vehicle tire noise information corresponding to the in-vehicle collection device; The tire noise information is determined according to the external tire noise information and / or the internal tire noise information.

9. The method according to claim 1 [A11], characterized in that The analyzing the tire sound signal collected by the sound collection device to determine the tire noise information includes: Performing time domain analysis on the tire sound signal to obtain tire noise amplitude information; Performing frequency domain analysis on the tire sound signal to obtain tire noise frequency distribution information; The tire noise information is determined according to the tire noise amplitude information and the tire noise frequency distribution information.

10. The method according to any one of claims 1 to 9, wherein The method further comprises: When the tire information indicates that an abnormality exists in the tire, a tire abnormality response control is executed on the vehicle.

11. The method according to claim 10 [A13], characterized in that The tire abnormality response control includes vehicle speed control; the tire abnormality response control performed on the vehicle includes: determining a target speed of the vehicle according to the abnormality type of the tire abnormality; The vehicle speed is controlled according to the target vehicle speed.

12. The method according to claim 10 [A14], characterized in that The tire abnormality response control includes suspension adjustment control; the tire abnormality response control performed on the vehicle includes: Identify the target tire with abnormality; determining suspension adjustment information of the vehicle according to an installation position of the tire on the vehicle; The suspension of the vehicle is adjusted according to the suspension adjustment information.

13. The method according to any one of claims 1 to 9 [A15], characterized in that The tire information prompting step includes: The tire information prompt is performed through at least one of the following: a dashboard, a vehicle-mounted central control screen, a speaker, and a mobile terminal.

14. A prompting device, characterized in that: include: An acquisition module, configured to acquire tire pressure information of a tire; an analysis module configured to analyze the tire sound signal collected by the sound collection device to determine tire noise information; The prompt module is configured to perform tire information prompting according to the tire noise information and the tire pressure information.

15. The device according to claim 14 [A16], characterized in that The apparatus further includes a determining module configured to: Before analyzing the tire sound signal collected by the sound collection device to determine the tire noise information, it is determined that there is no tire pressure drop in the tire based on the tire pressure information corresponding to the tire.

16. The device according to claim 15 [A17], characterized in that The prompt module is configured to: determining initial tire noise information of the tire according to the tire noise information; When the initial tire noise information indicates that the tire is abnormal, the initial tire noise information is used as [A18] target prompt information to perform tire information prompting.

17. The device according to claim 16 [A19], characterized in that The prompt module is configured to: When the initial tire noise information indicates that there is no abnormality in the tire, the tire pressure information and / or the tire pressure information is used as [A20] target prompt information to perform tire information prompting.

18. The device according to claim 15 [A21], characterized in that The prompt module is configured to: When it is determined based on the tire pressure information corresponding to the tire that the tire pressure has dropped, the tire pressure information is used as [A22] as target prompt information and the tire information prompt is executed.

19. The device according to claim 14 [A23], characterized in that The sound collecting device includes an external sound collecting device arranged outside the vehicle and / or an internal sound collecting device arranged inside the vehicle.

20. The device [A24] according to any one of claims 14 to 19, characterized in that The device further comprises: The response control module is configured to perform tire abnormality response control on the vehicle when the tire information indicates that the tire has an abnormality.

21. The device according to claim 20 [A25], characterized in that The tire abnormality response control includes vehicle speed control; the response control module includes: a vehicle speed determination submodule, configured to determine a target vehicle speed of the vehicle according to the abnormality type of the tire abnormality; The vehicle speed control submodule is configured to control the vehicle speed according to the target vehicle speed.

22. The device according to claim 20 [A26] [A27] [A28], characterized in that The tire abnormality response control includes suspension adjustment control; the response control module includes: a tire determination submodule, configured to determine a target tire with an abnormality; an adjustment determination submodule, configured as a tire determination submodule, configured to determine suspension adjustment information of the vehicle according to an installation position of the tire on the vehicle; The suspension adjustment submodule is configured to adjust the suspension of the vehicle according to the suspension adjustment information.

23. A vehicle, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute the executable instructions stored in the memory to implement the method according to any one of claims 1 to 13.

24. A computer-readable storage medium [A29] having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 13 are implemented.

25. A computer program product [A30], characterized in that The invention comprises a computer program, which implements the steps of the method according to any one of claims 1 to 13 when the computer program is executed by a processor.

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