Vehicle control method, system and vehicle

Abstract

A vehicle control method, system and vehicle, comprising: controlling a vehicle execution module to work according to control information of the execution module; wherein the control information is determined according to an ear pressure risk level of a user, and the ear pressure risk level is determined according to physiological information of the user. The vehicle control method provided by the embodiment of the present disclosure can determine the ear pressure risk level according to the physiological information of the user, determine the control information of the execution module according to the ear pressure risk level to control the execution module to work, so that a more matched control strategy can be executed according to different users to improve the relief effect of ear pressure discomfort of different users. The method can determine the control information according to the physiological information of the user to relieve ear pressure discomfort, can be integrated with intelligent driving, and improve the control effect and intelligent level of the scheme.

Description

Technical Field

[0001] This disclosure relates to a vehicle control method, system, and vehicle. Background Technology

[0002] In related technologies, a target ear pressure level inside the vehicle is determined based on environmental perception information (this level is positively correlated with the ear pressure of passengers inside the vehicle); the vehicle is then controlled to perform ear pressure equalization operations based on the target ear pressure level. However, this approach cannot distinguish between the sensitivity differences of different passengers. Summary of the Invention

[0003] This disclosure provides a vehicle control method, system, and vehicle to at least partially solve the above-mentioned problems.

[0004] This disclosure provides a vehicle control method, including:

[0005] The operation of the execution module is controlled based on the control information from the vehicle execution module.

[0006] The control information is determined based on the user's ear pressure risk level, which is determined based on the user's physiological information.

[0007] In some embodiments, the ear pressure risk level is determined based on the user's physiological information, including: the ear pressure risk level is determined based on the deviation from the physiological baseline, and the deviation from the physiological baseline is determined based on the user's physiological information.

[0008] In some embodiments, the ear pressure risk level is determined based on the deviation from the physiological baseline, including: the ear pressure risk level is determined based on the deviation from the physiological baseline and the standard deviation of the physiological index baseline.

[0009] In some embodiments, the ear pressure risk level is determined based on the deviation from the physiological baseline and the standard deviation of the physiological index baseline, including at least one of the following:

[0010] When the deviation from the physiological baseline is the first multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be low risk;

[0011] When the deviation from the physiological baseline is the second multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be medium risk;

[0012] When the deviation from the physiological baseline is the third multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be high risk.

[0013] In some embodiments, the physiological baseline deviation is the sum of the products of the offset of each physiological indicator and its corresponding weight, where the offset is the difference between the current value of each physiological indicator and the physiological baseline data.

[0014] In some embodiments, the ear pressure risk level is determined based on the user's physiological information, including: the ear pressure risk level is determined based on the user's physiological information and the vehicle's environmental information.

[0015] In some embodiments, the ear pressure risk level is determined based on the user's physiological information and the vehicle's environmental information, including: the ear pressure risk level is determined based on physiological baseline deviation and environmental coupling, wherein the physiological baseline deviation is determined based on the user's physiological information and the environmental coupling is determined based on the vehicle's environmental information.

[0016] In some embodiments, the ear pressure risk level is determined based on physiological baseline deviation and environmental coupling, including at least one of the following:

[0017] When the deviation from the physiological baseline is the first multiple of the standard deviation of the physiological index baseline and the environmental coupling degree is the first coupling degree, the ear pressure risk level is determined to be low risk.

[0018] When the deviation from the physiological baseline is the second multiple of the standard deviation of the physiological index baseline and the environmental coupling degree is the second coupling degree, the ear pressure risk level is determined to be medium risk.

[0019] When the deviation from the physiological baseline is the third multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be high risk.

[0020] In some embodiments, the physiological baseline deviation is the sum of the products of the offset of each physiological indicator of physiological information and its corresponding weight, where the offset is the difference between the current value of each physiological indicator and the physiological baseline data; the environmental coupling degree is the sum of the products of the matching degree between the current environmental information of the vehicle and the environmental warning data and their corresponding weights.

[0021] In some embodiments, the control information is determined based on the user's ear pressure risk level and includes at least one of the following:

[0022] When the ear pressure risk level is low, the control information is determined to be the first control information;

[0023] When the ear pressure risk level is medium risk, the control information is determined to be the second control information;

[0024] When the ear pressure risk level is high, the control information is determined to be the third control information.

[0025] In some embodiments, the first control information includes: control information for the air conditioning system and / or control information for the seat system.

[0026] In some embodiments, the control information of the air conditioning system includes: blower duty cycle and / or air outlet mode.

[0027] In some embodiments, the control information of the seat system includes: control information of the seat massage system.

[0028] In some embodiments, the second control information includes: control information for the speaker at the headrest and / or control information for the seat side wing adjustment device and / or control information for the headrest micro-airflow device.

[0029] In some embodiments, the third control information includes at least one of the following: control information for the suspension system, control information for the door speakers, control information for the windows, and control information for the speakers at the central control screen and / or the seat headrests.

[0030] In some embodiments, the control method further includes: after controlling the execution module to work according to the control information of the vehicle execution module, adjusting the control information according to the intervention effect.

[0031] In some embodiments, the control information includes: second control information and / or third control information.

[0032] In some embodiments, the intervention effect is determined based on the intervention response coefficient.

[0033] In some embodiments, the intervention response coefficient is determined based on the deviation of the physiological baseline before the execution module starts working and after working for a period of time.

[0034] In some embodiments, the intervention response coefficient is determined according to the following formula: (physiological baseline deviation before the execution module starts working - physiological baseline deviation after working for a period of time) / physiological baseline deviation before working.

[0035] In some embodiments, adjusting the control information based on the intervention effect includes at least one of the following:

[0036] When the intervention response coefficient is the first coefficient, the control information is maintained as the current level control information;

[0037] When the intervention response coefficient is the second coefficient, the control information is adjusted to be the sum of the current level control information and the lower level control information;

[0038] When the intervention response coefficient is the third coefficient, the control information is adjusted to a higher level of control information.

[0039] The vehicle control method provided in this disclosure can determine the ear pressure risk level based on the user's physiological information, and determine the control information of the execution module according to the ear pressure risk level to control the operation of the execution module. This allows for the implementation of more tailored control strategies for different users, thereby improving the relief of ear pressure discomfort for different users. This method, which determines control information based on the user's physiological information to alleviate ear pressure discomfort, can be integrated with intelligent driving to improve the control effect and intelligence level of the solution.

[0040] This disclosure also provides a vehicle control system, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0041] This disclosure also provides an electrical device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0042] This disclosure also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of any of the methods described above.

[0043] This disclosure also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of any of the methods described above.

[0044] This disclosure also provides a vehicle that includes the vehicle control system described in any of the preceding claims.

[0045] The above description is merely an overview of the technical solution disclosed herein. In order to better understand the technical means of this disclosure and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this disclosure more apparent and understandable, specific embodiments of this disclosure are described below. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of this disclosure. Those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0047] To gain a more complete understanding of this disclosure and its beneficial effects, the following description will be made in conjunction with the accompanying drawings, wherein the same reference numerals denote the same parts in the following description.

[0048] Figure 1 This is a flowchart illustrating a vehicle control method according to some embodiments;

[0049] Figure 2 This is a structural schematic diagram of a vehicle according to some embodiments;

[0050] Figure 3 A schematic diagram of the structure of a vehicle's intelligent decision-making module according to some embodiments;

[0051] Figure 4 This is a schematic diagram of the structure of a vehicle control method according to some other embodiments;

[0052] Figure 5 This is a schematic diagram of the structure of a vehicle control method according to some other embodiments;

[0053] Figure 6 This is a schematic diagram of the structure of a vehicle control method according to some other embodiments;

[0054] Figure 7 This is a schematic diagram of the structure of a vehicle control method according to some other embodiments;

[0055] Figure 8 This is a schematic diagram of the structure of a vehicle control method according to some other embodiments;

[0056] Figure 9 This is a structural schematic diagram of a vehicle control method according to some other embodiments. Detailed Implementation

[0057] The technical solutions of the embodiments of this disclosure 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 disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the protection scope of this disclosure.

[0058] In the description of this disclosure, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or relative positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this disclosure and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this disclosure. Unless otherwise specified, the above-mentioned orientational descriptions can be flexibly set in practical applications, provided that the relative positional relationships shown in the accompanying drawings are satisfied.

[0059] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this disclosure, unless otherwise stated, "a plurality of" means two or more.

[0060] Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0061] In the description of this disclosure, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "electrical connection," and "communication" should be interpreted broadly. For example, they can refer to fixed electrical connections, detachable electrical connections, or integral electrical connections. Connections can be direct or indirect through an intermediate medium, and can be internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure according to the specific circumstances.

[0062] In embodiments of this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in embodiments of this disclosure is not limited. Functions may be performed in the order shown or discussed, or may be performed substantially simultaneously or in reverse order depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0063] In this disclosure, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this disclosure should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0064] In the description of this specification, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0065] In related technologies, pure electric vehicles, lacking the "masking effect" of engine noise from gasoline vehicles, typically have low-frequency vibrations and noise transmitted through the chassis, tires, etc., concentrated in the 20-200Hz range, especially the 30-40Hz frequency band. These are easily perceived by occupants, causing strong discomfort such as oppression and roaring. This phenomenon (i.e., low-frequency ear pressure) is one of the core challenges in the field of NVH (Noise, Vibration, Harshness).

[0066] The aforementioned problems are usually caused by the coupling of multiple factors. For example, vibrations from the chassis and subframe are transmitted to the body through the structure, resonating with the body sheet metal parts, especially the tailgate, and thus amplifying within the cabin cavity to create a low-frequency booming sound. This involves a complex systemic problem from the excitation source and transmission path to the body response.

[0067] The solutions in related technologies are mostly "remedial measures after the fact." On the one hand, in the later stages of research and development, components such as "dynamic vibration absorbers" are added to suppress vibrations of specific frequencies. On the other hand, in the after-sales process, car owners are advised to replace rubber strips, add sound insulation materials, or adjust chassis components. However, these solutions are all "passive repairs" targeting single physical problems. They are not only costly and their effectiveness varies from person to person, but they also cannot dynamically adapt to different road conditions and passenger states. Even after trying various methods, the problem "still exists" or "cannot be solved."

[0068] In terms of technologies related to vehicle interior comfort, various solutions have been attempted to alleviate ear pressure discomfort for passengers during driving, but these solutions still have significant limitations in terms of adjustment mechanisms, target orientation, and personalized adaptation.

[0069] The first type: The most common method of ear pressure adjustment is passive adjustment technology based on physical parameters, which triggers the adjustment action by monitoring changes in the physical environment inside the vehicle. The common drawback of this type of technology is that it only starts from the physical state of the vehicle, completely ignoring individual differences and real-time physiological feelings of the occupants. It belongs to the "undifferentiated, passive response" mode based on fixed rules. It cannot identify the differences in ear pressure sensitivity among different occupants, nor can it actively intervene before the occupants experience actual discomfort. The adjustment effect has a large degree of randomness.

[0070] The second category: Current ear pressure regulation methods are singular and cannot cover the complex causes of ear pressure discomfort, and the regulation strategies are undifferentiated. Ear pressure discomfort is usually the result of multiple factors such as vibration excitation, noise interference, and air pressure fluctuations. However, a single actuator can only address a single cause and cannot cope with the complexity of ear pressure discomfort. In addition, related technologies all adopt a "threshold-triggered" binary decision-making approach, executing an action when parameters exceed the limit. This "one-size-fits-all" approach can lead to problems of over-intervention and under-intervention.

[0071] The third category is active regulation technology based on environmental prediction. This technology introduces a prediction mechanism to achieve early intervention, but the prediction model relies almost entirely on external environmental parameters and lacks closed-loop feedback on the actual physiological state of the occupants. Since no individual physiological signals are collected, the system cannot verify the accuracy of the prediction, judge the actual effect of the regulation measures, or establish personalized regulation models for different occupants' physiological characteristics. Essentially, it is still an "open-loop" intelligent attempt, with significant bottlenecks in regulation accuracy, reliability, and individual adaptability.

[0072] In summary, the relevant technologies either neglect the human factor in the adjustment mechanism, deviate from the core requirements of ear pressure adjustment in terms of functional goals, or lack physiological feedback and personalized closed loop in the implementation path, making it difficult to achieve accurate, proactive, and personalized vehicle ear pressure adjustment effects.

[0073] In some embodiments, such as Figure 1 As shown, this disclosure provides a vehicle control method, including:

[0074] The system controls the operation of the execution module based on the control information from the vehicle execution module.

[0075] The control information is determined based on the user's ear pressure risk level, which is determined based on the user's physiological information.

[0076] The vehicle control method provided in this disclosure can determine the ear pressure risk level based on the user's physiological information, and determine the control information of the execution module according to the ear pressure risk level to control the operation of the execution module. This allows for the implementation of more tailored control strategies for different users, thereby improving the relief of ear pressure discomfort for different users. This method, which determines control information based on the user's physiological information to alleviate ear pressure discomfort, can be integrated with intelligent driving to improve the control effect and intelligence level of the solution.

[0077] In some embodiments, the physiological information includes at least one of the following: the average temperature, temperature change rate, and temperature distribution entropy of the periauricular ROI (Region of Interest).

[0078] The periauricular ROI can be one or more specific sub-regions predefined in the field of view of an infrared thermal imager (such as an infrared thermal imaging camera) for analyzing the ear and its surrounding area.

[0079] The periauricular region may include the skin area behind the auricle, the surface of the mastoid bone, the earlobe and its junction with the cheek, the area in front of the tragus, and the skin near the temporomandibular joint.

[0080] In some embodiments, physiological information includes at least one of the following: average temperature, temperature change rate, temperature distribution entropy, respiratory rate, respiratory depth coefficient, heart rate, heart rate variability, pressure center trajectory, posture adjustment frequency, pressure distribution entropy, facial motion unit intensity, blinking frequency, and head posture angle.

[0081] In some embodiments, the ear pressure risk level is determined based on the user's physiological information, including: the ear pressure risk level is determined based on the deviation from the physiological baseline, which is determined based on the user's physiological information.

[0082] Ear pressure risk level can be determined based on the user's physiological information in various appropriate ways. For example, the deviation from the physiological baseline can be determined based on the user's physiological information, and the ear pressure risk level can be determined based on the deviation from the physiological baseline. The solution is simple and accurate.

[0083] In some embodiments, the ear pressure risk level is determined based on the deviation from the physiological baseline, including: the ear pressure risk level is determined based on the deviation from the physiological baseline and the standard deviation of the physiological index baseline.

[0084] Ear pressure risk level can be determined in various appropriate ways based on the deviation from the physiological baseline, such as by the deviation from the physiological baseline and the standard deviation of the physiological index baseline. The method is simple and accurate.

[0085] In some embodiments, the ear pressure risk level is determined based on the deviation from the physiological baseline and the standard deviation of the physiological index baseline, including at least one of the following:

[0086] When the deviation from the physiological baseline is the first multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be low risk;

[0087] When the deviation from the physiological baseline is the second multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be medium risk;

[0088] When the deviation from the physiological baseline is the third multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be high risk.

[0089] Ear pressure risk level can be determined in various appropriate ways based on the deviation from the physiological baseline and the standard deviation of the physiological index baseline. For example, the method described above is simple and direct.

[0090] The first, second, and third multiples can be any suitable multiples. For example, the first multiple can be (1.5, 2.0), the second multiple can be [2.0, 2.5], and the third multiple can be a value greater than 2.5.

[0091] In some embodiments, the physiological baseline deviation is the sum of the product of the offset of each physiological indicator and its corresponding weight, where the offset is the difference between the current value of each physiological indicator and the physiological baseline data.

[0092] The deviation of the physiological baseline can be determined in various appropriate ways, such as by summing the products of the deviation of each physiological indicator and its corresponding weight. The weights of each physiological indicator can be the same or different. Those skilled in the art can reasonably determine the corresponding weights of different physiological indicators, thereby facilitating a more accurate determination of the deviation of the physiological baseline.

[0093] Physiological baseline data can be determined by various suitable methods, such as by detecting the user's physiological information before the implementation of the scheme in the embodiments of this disclosure.

[0094] Physiological baseline data can be the physiological information data of a user when driving a vehicle at rest for 5-10 minutes on a smooth road, with the air conditioning off or at low airflow, and without external interference.

[0095] The baseline standard deviation of physiological indicators can be determined based on physiological baseline data (physiological baseline data at multiple time points). For example, the mean of physiological baseline data at different time points can be taken first, and then the mean can be subtracted from the physiological baseline data at each time point and squared. The mean of the sum of squares can then be taken as the square root to determine the baseline standard deviation of physiological indicators.

[0096] In some embodiments, the ear pressure risk level is determined based on the user's physiological information, including: the ear pressure risk level is determined based on the user's physiological information and the vehicle's environmental information.

[0097] Ear pressure risk level can be determined using various appropriate methods based on the user's physiological information, such as the user's physiological information and the vehicle's environmental information, thus allowing for a more accurate determination of ear pressure risk level.

[0098] In some embodiments, the vehicle's environmental information may include at least one of the following: static air pressure, air pressure fluctuation spectrum, and sound pressure level.

[0099] In some embodiments, the vehicle's environmental information may include at least one of the following: static air pressure, air pressure fluctuation spectrum, sound pressure level, 1 / 3 octave band spectrum, beamforming sound source localization, wheel speed, wheel acceleration, slip ratio, vertical displacement, vertical velocity, and vertical acceleration.

[0100] Determining the ear pressure risk level by using the user's physiological information and the vehicle's environmental information (which can be supplemented by physiological information) can make the determination of the ear pressure risk level more accurate, thereby improving the relief of ear pressure discomfort.

[0101] In some embodiments, the ear pressure risk level is determined based on the user's physiological information and the vehicle's environmental information, including: the ear pressure risk level is determined based on physiological baseline deviation and environmental coupling, wherein the physiological baseline deviation is determined based on the user's physiological information and the environmental coupling is determined based on the vehicle's environmental information.

[0102] Ear pressure risk level can be determined in various appropriate ways based on the user's physiological information and the vehicle's environmental information, such as by determining it based on the deviation from the physiological baseline and the degree of environmental coupling. The solution is simple and accurate.

[0103] In some embodiments, the ear pressure risk level is determined based on deviation from physiological baseline and environmental coupling, including at least one of the following:

[0104] When the deviation from the physiological baseline is the first multiple of the standard deviation of the physiological index baseline and the environmental coupling degree is the first coupling degree, the ear pressure risk level is determined to be low risk.

[0105] When the deviation from the physiological baseline is the second multiple of the standard deviation of the physiological index baseline and the environmental coupling degree is the second coupling degree, the ear pressure risk level is determined to be medium risk.

[0106] When the deviation from the physiological baseline is the third multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be high risk.

[0107] Ear pressure risk level can be determined by various appropriate methods based on deviation from physiological baseline and environmental coupling. For example, it can be determined using the above-mentioned scheme, which is simple and accurate.

[0108] The first, second, and third multiples can be any suitable multiples. For example, the first multiple can be (1.5, 2.0), the second multiple can be [2.0, 2.5], and the third multiple can be a value greater than 2.5.

[0109] The first coupling degree and the second coupling degree can be various suitable coupling degree values, such as the first coupling degree being (0.5, 0.7) and the second coupling degree being [0.7, 1.0].

[0110] In some embodiments, the physiological baseline deviation is the sum of the products of the offset of each physiological indicator of physiological information and its corresponding weight, where the offset is the difference between the current value of each physiological indicator and the physiological baseline data; the environmental coupling degree is the sum of the products of the matching degree between the current environmental information of the vehicle and the environmental warning data and their corresponding weights.

[0111] The deviation of the physiological baseline can be determined in various appropriate ways, such as by summing the products of the deviation of each physiological indicator and its corresponding weight. The weights of each physiological indicator can be the same or different. Those skilled in the art can reasonably determine the corresponding weights of different physiological indicators, thereby facilitating a more accurate determination of the deviation of the physiological baseline.

[0112] The degree of environmental coupling can be determined in various appropriate ways, such as by summing the product of the degree of matching between the vehicle's current environmental information and the environmental warning data and their corresponding weights. The corresponding weights for the degree of matching of each environmental information can be the same or different. Those skilled in the art can reasonably determine the corresponding weights based on different environmental information, thereby facilitating a more accurate determination of the degree of environmental coupling.

[0113] In some embodiments, the control information is determined based on the user's ear pressure risk level and includes at least one of the following:

[0114] When the ear pressure risk level is low, the control information is determined as the first control information;

[0115] When the ear pressure risk level is medium risk, the control information is determined as the second control information;

[0116] When the ear pressure risk level is high, the control information is determined to be the third control information.

[0117] Control information can be determined based on the user's ear pressure risk level in various appropriate ways, such as according to the above scheme, so as to facilitate the adoption of corresponding control strategies according to different ear pressure risk levels, thereby improving the relief effect at different ear pressure risk levels.

[0118] In some embodiments, the first control information includes: control information for the air conditioning system and / or control information for the seat system.

[0119] The first control information can be any suitable control information, such as control information for the air conditioning system and / or the seat system. That is, in low-risk situations, ear pressure discomfort can be relieved by controlling the air conditioning system and / or the seat system.

[0120] In some embodiments, the control information of the air conditioning system includes: blower duty cycle and / or air outlet mode.

[0121] The control information for the air conditioning system can be various suitable information, such as the blower duty cycle and / or air outlet mode.

[0122] In some embodiments, the control information corresponding to the blower duty cycle can be adjusting or increasing the blower duty cycle (e.g., increasing the duty cycle by 3%). The control information corresponding to the air outlet mode can be switching the air outlet mode to a "face blowing + foot blowing" mixed mode.

[0123] In some embodiments, the control information of the seat system includes: control information of the seat massage system.

[0124] The control information for the seat system can be various suitable information, such as the control information for the seat massage system.

[0125] In some embodiments, the control information of the seat massage system can activate two broadband exciters at the front edge of the seat cushion to output white noise vibration with a frequency of 80Hz and an amplitude of 0.1g.

[0126] In some embodiments, the second control information includes: control information for the speaker at the headrest and / or control information for the seat side wing adjustment device and / or control information for the headrest micro-airflow device.

[0127] The second control information can be various suitable information, such as control information for the speaker at the headrest and / or the seat side wing adjustment device and / or the seat headrest micro-airflow device. That is, in the case of medium risk, ear pressure discomfort can be relieved by controlling the speaker at the headrest and / or the seat side wing adjustment device and / or the seat headrest micro-airflow device.

[0128] In some embodiments, the control information for the speakers at the headrest can be used to control the near-field active noise-canceling speakers (such as four speakers) in the headrest area to send sound wave signals that are out of phase with the real-time identified main frequency noise, with a gain of -3dB.

[0129] The control information for the seat side wing adjustment device can be that the seat side wing airbag inflation valve opens for 150ms and the side wing retracts by 8°.

[0130] The control information of the micro-airflow device in the headrest can control the micro-fan inside the headrest to deliver a gentle airflow to the area behind the ears at a wind speed of 1.5m / s.

[0131] In some embodiments, the third control information includes at least one of the following: control information for the suspension system, control information for the door speakers, control information for the windows, and control information for the speakers at the central control screen and / or the seat headrests.

[0132] The third control information can be various suitable information, such as control information for one or more of the suspension system, door speakers, window center console screen, and / or seat headrest speakers. That is, in high-risk situations, one or more of the suspension system, door speakers, windows, center console screen, and / or seat headrest speakers can be controlled to alleviate ear pressure discomfort.

[0133] In some embodiments, the control information for the suspension system can be the damping enhancement of the suspension system (such as a CDC (Continuous Damping Control) shock absorber) (e.g., damping enhancement level 3).

[0134] The control information for the door speakers can be used to control the entire vehicle's ANC (Active Noise Cancellation) to activate active noise cancellation for all door speakers, covering a wide frequency band of 20-500Hz, with a target noise reduction of 8-10dB.

[0135] The window control information can cause all four windows to drop 5mm simultaneously (if the vehicle speed is less than 80km / h), creating a continuous exhaust gap.

[0136] The control information from the central control screen and / or the speakers at the headrests can display visual animations on the central control screen to guide occupants to perform slow-rhythmic abdominal breathing of "inhaling for 4 seconds - holding their breath for 2 seconds - exhaling for 6 seconds", and / or play low-frequency pulse sounds from the speakers at the headrests to guide the breathing rhythm.

[0137] In some embodiments, the control method further includes: after controlling the execution module to work according to the control information of the vehicle execution module, adjusting the control information according to the intervention effect.

[0138] After controlling the execution module to work based on the control information from the vehicle execution module, the control information can be adjusted according to the intervention effect, thereby facilitating the adoption of more appropriate control strategies to improve the relief of ear pressure discomfort.

[0139] In some embodiments, the control information includes: second control information and / or third control information.

[0140] The control information may include second and / or third control information, which can be used to verify the intervention effect of control information taken for medium and high risks and adjust the control information in a timely manner, thereby improving the relief effect of ear pressure discomfort in medium and high risks.

[0141] The effectiveness of interventions targeting low-risk control information (first control information) does not require verification or adjustment.

[0142] In some embodiments, the intervention effect is determined based on the intervention response coefficient.

[0143] The effectiveness of an intervention can be determined using various appropriate information, such as the intervention response coefficient, making the approach simple and direct.

[0144] In some embodiments, the intervention response coefficient is determined based on the deviation from the physiological baseline before and after the execution module has been in operation for a period of time.

[0145] The intervention response coefficient can be determined in various appropriate ways, such as by the deviation of the physiological baseline before the execution module starts working and after working for a period of time (e.g., 5 seconds). The method is simple and accurate.

[0146] In some embodiments, the intervention response coefficient is determined according to the following formula: (physiological baseline deviation before the execution module starts working - physiological baseline deviation after working for a period of time) / physiological baseline deviation before working.

[0147] The intervention response coefficient can be determined in various appropriate ways, such as by the formula mentioned above, which is simple and accurate.

[0148] In some embodiments, adjusting the control information based on the intervention effect includes at least one of the following:

[0149] When the intervention response coefficient is the first coefficient, the control information is maintained as the current level control information;

[0150] When the intervention response coefficient is the second coefficient, the adjusted control information is the sum of the current level control information and the next lower level control information;

[0151] When the intervention response coefficient is the third coefficient, the control information is adjusted to a higher level of control information.

[0152] Adjusting control information based on the intervention effect can be achieved in various suitable ways, such as by determining the above scheme, which is simple and direct.

[0153] The first coefficient, the second coefficient, and the third coefficient can be any suitable value. For example, the first coefficient can be a value greater than 0.7; the second coefficient can be a value greater than or equal to 0.3 and less than or equal to 0.7; and the third coefficient can be a value less than 0.3.

[0154] When the intervention response coefficient is the first coefficient, the control information is maintained as the current level control information. If the intervention response coefficient is the first coefficient when the current level control information is the second control information, then the control information is maintained as the second control information. That is, the control information intervention is significant at this time (i.e., the mitigation effect is significant), and there is no need to adjust the control strategy.

[0155] When the intervention response coefficient is the second coefficient, the adjusted control information is the sum of the current-level control information and the next lower level control information. If the current-level control information is the second control information, the adjusted control information is the sum of the second control information and the first control information, that is, the first control information is superimposed on the second control information. In this case, the intervention portion of the control information is effective, and the control effect can be improved by adding more control information.

[0156] When the intervention response coefficient is the third coefficient, the control information is adjusted to a higher level; if the current level control information is the second level, the adjusted control information is the third level. This means that the intervention is ineffective at this point, and the control strategy can be adjusted promptly to alleviate discomfort.

[0157] In some embodiments, such as Figure 2 As shown, a vehicle includes: an occupant physiological detection module, a multi-source environmental perception module, an intelligent decision control module, and a multi-mode execution module.

[0158] Occupant Physiological Detection Module: Responsible for acquiring multi-dimensional physiological and behavioral signals characterizing occupant ear pressure and overall comfort in real time in a completely non-contact and non-invasive manner. The occupant physiological detection module includes: an infrared thermal imaging camera, millimeter-wave radar, a high-resolution pressure sensor array, and a binocular camera. The module's output data includes: average temperature, temperature change rate, temperature distribution entropy, respiratory rate (breaths / min), respiratory depth coefficient, heart rate (breaths / min), heart rate variability, pressure center trajectory (x, y), posture adjustment frequency (breaths / min), pressure distribution entropy, facial motor unit intensity, blink frequency, and head posture angle.

[0159] The average temperature, temperature change rate, and temperature distribution entropy of the periauricular ROI region can be determined based on information such as the temperature detected by the infrared thermal imaging camera.

[0160] The respiratory depth coefficient, heart rate, and heart rate variability can be determined based on information detected by millimeter-wave radar.

[0161] The pressure center trajectory, posture adjustment frequency, and pressure distribution entropy can be determined based on information detected by a high-resolution pressure sensor array (located at the seat).

[0162] The intensity of facial motion units, blink frequency, and head posture angle can be determined based on information detected by binocular cameras.

[0163] Multi-source environmental perception module: Responsible for real-time monitoring of various physical environmental factors inside and outside the vehicle that may induce ear pressure discomfort. The external environment perception module includes: a front-facing camera, wheel speed sensors, suspension displacement sensors, air pressure sensors, and a microphone array. The module's output data includes: wheel speed (km / h), wheel acceleration (m / s²), slip ratio (%), vertical displacement (mm), vertical velocity (mm / s), vertical acceleration (m / s²), static air pressure (hPa), air pressure fluctuation spectrum (0.1-10Hz), sound pressure level (dB), 1 / 3 octave band spectrum, and beamforming sound source localization.

[0164] Wheel speed, wheel acceleration, and slip ratio can be determined based on information detected by the wheel speed sensor.

[0165] Vertical displacement, vertical velocity, and vertical acceleration can be determined based on information detected by the suspension displacement sensor.

[0166] Static air pressure and air pressure fluctuation spectrum can be determined based on information detected by air pressure sensors.

[0167] Sound pressure level, 1 / 3 octave band spectrum, and beamforming sound source localization can be determined based on information detected by the microphone array.

[0168] The intelligent decision-making and control module is responsible for integrating multi-source heterogeneous data, dynamically assessing the risk level of ear pressure discomfort through a built-in predictive model and personalized database, and generating corresponding collaborative control commands. The intelligent decision-making and control module consists of an edge computing unit, a storage unit, and a security encryption chip.

[0169] In some embodiments, such as Figure 3 As shown, the core algorithms of the intelligent decision-making and control module include: a data spatiotemporal alignment and fusion algorithm, an ear pressure discomfort prediction model, and a personalized baseline update algorithm. The database of the intelligent decision-making and control module includes: a personalized physiological baseline database for occupants, an environmental early warning database, and a personalized information weight database. The functional units of the intelligent decision-making and control module include: a data preprocessing unit, a spatiotemporal alignment and fusion unit, a prediction model inference unit, a risk level determination unit, and a strategy mapping unit. The input to the intelligent decision-making and control module is the signal data output from the occupant physiological detection module and the multi-source environmental perception module; the output of the intelligent decision-making and control module is the execution instruction strategy package.

[0170] Multi-mode execution module: Based on the instructions from the decision-making module, it hierarchically and collaboratively invokes various actuators distributed throughout the vehicle, forming a comprehensive intervention network from source suppression and path blocking to perception compensation. The execution module includes: the air conditioning system, seat massage system, seat side wing adjustment device, active noise cancellation speaker, headrest micro-airflow device, active suspension system, window system, and central control display. The input of the multi-mode execution module is the execution instruction strategy package; the output is actuator status detection data.

[0171] The solution in this embodiment can perform the task of collecting the occupant's physiological baseline data, so as to accurately distinguish between normal physiological fluctuations and stress responses caused by ear pressure discomfort, thereby avoiding accidental activation of the adjustment device. Figure 4 As shown, the specific process for collecting occupant physiological baseline data is as follows.

[0172] Step S01: The central control screen asks the occupant whether to activate the travel ear pressure adjustment function. When the occupant allows activation, the central control screen asks whether to allow the collection of the occupant's physiological baseline data. When the occupant allows activation, the central control screen prompts the occupant to control the vehicle to drive quietly for 5-10 minutes in an environment with a smooth road, air conditioning off or at low fan speed, and no external interference.

[0173] Step S02: The occupant physiological detection module continuously collects physiological characteristics such as the temperature distribution of periauricular infrared thermal imaging, the variability of respiratory rate and heart rate calculated by millimeter-wave radar, the symmetry of seat pressure distribution, and the baseline of facial micro-expressions.

[0174] Step S03: The intelligent decision control module performs mean and standard deviation statistics on the collected data to generate a unique "resting-state physiological feature vector" for the occupant, which is then encrypted and stored in the vehicle's secure storage area. This baseline data serves as a reference for all subsequent judgments regarding the occupant's physiological deviations.

[0175] The pressure adjustment system enters a continuous monitoring state after the vehicle is started. Its core workflow is a continuous closed loop of "perception-decision-execution-verification," such as... Figure 5 As shown, the basic execution flow is as follows.

[0176] Step S04: The occupant physiological detection module continuously collects the occupant's physiological characteristic data, and the environmental detection module continuously collects the environmental characteristic data.

[0177] Step S05: The intelligent decision control module compares the current physiological characteristics with the stored personal baseline in real time, executes dual triggering logic, and determines whether to trigger a risk warning action.

[0178] Step S06: After the triggering conditions are met, the intelligent decision control module performs multi-source data fusion of occupant physiological characteristics and environmental characteristics and calculates the ear pressure risk level.

[0179] Step S07: The intelligent decision control module dynamically adjusts the strategy set based on the current risk level, the physiological deviation of the members, and the current environmental coupling, and mobilizes the multi-mode execution module to execute the instructions.

[0180] Step S08: After the multi-mode execution module has executed all instructions in the strategy set, the intelligent decision control module immediately enters the closed-loop verification stage to perform physiological data feedback closed loop and strategy iteration.

[0181] In step S05, the dual trigger logic is as follows: when the physiological baseline deviation exceeds 1.5 for three consecutive sampling periods or the environmental coupling degree exceeds 0.5 for three consecutive sampling periods, ear pressure risk prediction and calculation are performed. The physiological baseline deviation refers to the sum of the products of the current value of each physiological indicator and the physiological baseline data (or the baseline mean), continuously calculated by the intelligent decision control module, and their corresponding weights. Mild, moderate, and severe deviation thresholds are defined as 1.5, 2.0, and 2.5 times the baseline standard deviation of each physiological indicator. The environmental coupling degree refers to the sum of the products of the matching degree between the current environment and the warning data in the environmental warning database and their corresponding weights.

[0182] In step S06, the intelligent decision control module preprocesses multi-source data on occupant physiological and environmental characteristics, weights and fuses them, and uses a neural network model for predictive reasoning to complete risk level determination and strategy output, such as... Figure 6 As shown, the specific steps include:

[0183] Step S061: The intelligent decision control module processes the received physiological and environmental characteristic signal data by removing outliers, imputing missing values, filtering and denoising, normalizing and standardizing, and outputs a structured dataset.

[0184] Step S062: Timestamp-align the signal data in the structured dataset, complete the coordinate system of the original sensor coordinate data, and construct a sliding window from the aligned data to generate time-series window data.

[0185] Step S063: Input the temporal window data into the attention fusion model for feature fusion. This model includes an input layer, a temporal attention layer, a spatial feature encoding layer, a modal attention layer, and an output layer. The model output is the fused deep features, temporal attention weights, and physiological and environmental modal weight data.

[0186] Step S064: Input the fused feature data into the ear pressure risk prediction model for prediction. This model consists of an input layer, multiple LSTM (Long Short-Term Memory) layers, a fully connected layer, and an output layer. This model can be trained on a large amount of real-vehicle road test data in the laboratory stage before being deployed in a vehicle. The model outputs three levels of risk probabilities (low, medium, and high) and model confidence scores.

[0187] In step S07, the intelligent decision control module assembles and executes instructions based on multiple factors, including the discrete risk level results output by the ear pressure risk prediction model, physiological deviation data, and environmental coupling degree, to generate a customized strategy adjustment package.

[0188] In some embodiments, such as Figure 8As shown, the intelligent decision-making and control module uses an ear pressure risk prediction model to classify ear pressure situations into low-risk, medium-risk, and high-risk scenarios. In a low-risk scenario, the physiological deviation is less than 2.0 times the standard deviation of the physiological indicator baseline and the environmental coupling degree is less than 0.7. In this scenario, a first-level prevention strategy (first control information) is adopted. In a medium-risk scenario, the physiological deviation is between 2.0 and 2.5 times the standard deviation of the physiological indicator baseline and the environmental coupling degree exceeds 0.7. In this scenario, a second-level prevention strategy (second control information) is adopted. In a high-risk scenario, the physiological deviation exceeds 2.5 times the standard deviation of the physiological indicator baseline. In this scenario, the highest-level prevention strategy (third control information) is adopted.

[0189] In some embodiments, such as Figure 8 As shown, the first-level prevention strategy adopts the principle of "non-intrusiveness." Command 1 is that the air conditioning system increases the blower's PWM duty cycle by 3%, switches the airflow mode to a mixed "face + foot" mode, and returns to normal after 5 seconds. Command 2 is that the seat system activates two wideband exciters at the front edge of the seat cushion, outputting white noise vibration at a frequency of 80Hz and an amplitude of 0.1g for 3 seconds. When the low-risk adjustment strategy is triggered again, the intelligent decision control module randomly selects one of the two commands or executes them alternately to avoid occupant adaptation. After execution, the system does not verify the occupant's physiological feedback but marks the intervention as complete.

[0190] In some embodiments, such as Figure 8 As shown, the second-level prevention strategy adopts the principle of "precise compensation." Command 1 involves the four near-field active noise-canceling speakers in the headrest area sending sound wave signals with a phase opposite to the real-time identified main frequency noise, with a gain of -3dB, continuing until the risk is eliminated or escalates. Command 2 involves the seat side wing airbag inflation valves opening for 150ms, with the side wings retracting 8°, maintaining this until the risk is eliminated. Command 3 involves the micro-fan inside the headrest delivering a gentle airflow to the area behind the ears at a speed of 1.5m / s for 10 seconds. The intelligent decision-making control module dynamically combines the above commands based on the degree of deviation of physiological indicators and the degree of environmental coupling. For example, if the in-vehicle microphone detects a clear 80Hz single-frequency roar, Command 1 is mandatory; if the seat pressure center trajectory shows obvious uneasy movement, Command 2 is mandatory. After all commands are executed, a mandatory 5-second physiological feedback verification period is initiated.

[0191] In some embodiments, such as Figure 8As shown, the highest-level prevention strategy adopts the principle of "system-level radical treatment." Command 1 sends a "damping enhancement level 3" command to the CDC damper controller, continuing until road surface characteristics change or the dominant vibration frequency shifts. Command 2 activates all door speakers for active noise cancellation, covering a wide frequency band of 20-500Hz, with a target noise reduction of 8-10dB. Command 3, if the vehicle speed is less than 80km / h, lowers all four door windows by 5mm simultaneously, creating a continuous exhaust gap. Command 4, a pop-up visual animation on the central control screen guides occupants to perform slow-rhythmic abdominal breathing: "inhale for 4 seconds - hold your breath for 2 seconds - exhale for 6 seconds," while low-frequency pulse sounds are played from the headrest speakers to guide the breathing rhythm. The intelligent decision control module adopts a parallel collaborative execution mode; the above commands are issued simultaneously, and each actuator acts according to its own response sequence. After all commands are executed, a mandatory 5-second physiological feedback verification period is initiated.

[0192] In step S08, after all intervention instructions are executed, the system immediately enters the closed-loop verification phase, such as... Figure 7 As shown, it mainly includes the following three steps.

[0193] Step S081: The occupant physiological detection module continuously detects the physiological characteristic signals of the occupants.

[0194] Step S082: The intelligent decision control module evaluates the intervention effect. Define the "intervention response coefficient" as: (Pre-intervention physiological deviation - Physiological deviation at 5 seconds after intervention) / Pre-intervention physiological deviation. If the intervention response coefficient is greater than 0.7, the intervention is considered significant, and the current strategy is maintained, with a reassessment every 10 seconds. If the intervention response coefficient is greater than or equal to 0.3 and less than or equal to 0.7, the intervention is considered partially effective, and a lower-level intervention strategy needs to be added to the current level of intervention strategy. If the intervention response coefficient is less than 0.3, the current intervention measure is considered ineffective, and an immediate upgrade to a higher-risk strategy is enforced. The failure of the current strategy in this scenario is recorded for personalized model learning.

[0195] Step S083: If the intelligent decision control module shows that the risk level has decreased to below the current level after three consecutive reassessments, the intervention strategy is downgraded. For example, it may revert from a high-risk strategy package to a strategy package that only maintains a medium-risk risk. When all physiological indicators return to within ±1.5 standard deviations of the baseline for 30 consecutive seconds, and the environmental coupling degree is less than 0.5, the system completely exits the intervention state and returns to monitoring mode.

[0196] In some embodiments, such as Figure 9As shown, this ear pressure adjustment system (vehicle control system) possesses lifelong learning capabilities. Each ear pressure intervention event is recorded as a training sample, which includes the fused feature vector before intervention and the strategy combination with the highest response coefficient during intervention. During daily parking, the onboard terminal uses accumulated local data for incremental learning, updating the parameters of the last two fully connected layers of the ear pressure risk prediction model and the personalized weight database corresponding to physiological environmental indicators, thereby continuously deepening the system's understanding of the response characteristics of specific occupants.

[0197] This disclosure presents an embodiment of a personalized ear pressure comfort system that is predictable and proactively intervenes based on a deep integration of physiological feedback and the vehicle environment. This system overturns the single, passive adjustment logic of related technologies that rely solely on vehicle physical signals. By introducing real-time physiological feedback from occupants, it forms a complete closed loop of "perception-decision-execution-verification," thereby achieving a fundamental shift from "vehicle function adjustment" to "occupant proactive comfort maintenance."

[0198] This disclosed embodiment focuses on detecting the physiological feedback signals of occupants and cross-validating them with multimodal data of the vehicle environment. It can directly and accurately identify whether a specific occupant actually feels ear pressure discomfort and the severity of the discomfort. It solves the problem of individual variability that related technologies cannot overcome, giving the system's perception the characteristics of "humanization" and "precision," laying a correct data foundation for subsequent personalized intervention, and avoiding false triggering or missed triggering from the source.

[0199] This disclosure deploys a hierarchical, collaborative multimodal actuator network. The system can intelligently combine and invoke actuators according to decision commands, providing systematic intervention from three levels: "vibration / noise source suppression," "transmission path blocking," and "occupant perception compensation." This solves the problem that related technologies often have limited effectiveness in addressing ear-piercing problems caused by complex acoustic-vibration coupling due to their singular and discrete execution methods, merely treating the symptoms rather than the root cause.

[0200] This disclosure introduces a "physiological detection closed-loop verification" mechanism, which uses the real-time physiological response of the occupants as an evaluation standard for the regulation effect and as the input basis for the next round of regulation.

[0201] This disclosure allows for full utilization of the sensor resources already installed in the vehicle. Smart cars are commonly equipped with facial cameras, millimeter-wave radar, seat pressure sensors, microphone arrays, wheel speed sensors, suspension displacement sensors, etc. This allows for greater utilization of vehicle hardware at a lower additional cost, addressing a widespread but long-neglected issue of ride comfort.

[0202] The vehicle control method provided in this disclosure can determine the ear pressure risk level based on the user's physiological information, and determine the control information of the execution module based on the ear pressure risk level to control the operation of the execution module. This allows for the execution of more suitable control strategies for different users, thereby improving the relief effect of ear pressure discomfort for different users.

[0203] This disclosure also provides a vehicle control system, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the above methods.

[0204] This disclosure also provides an electrical device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the above methods.

[0205] This disclosure also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of any of the above methods.

[0206] This disclosure also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of any of the above methods.

[0207] This disclosure also provides a vehicle that includes the vehicle control system described in any of the above claims.

[0208] It should be noted that the aforementioned electrical equipment can be any conventionally power-consuming equipment, such as, but not limited to, controllers, vehicles, skateboard chassis, ships, drones, mobile phones, computers, air conditioners, refrigerators, washing machines, microwave ovens, printers, fax machines, etc.

[0209] The embodiments of this disclosure have been described above with reference to the accompanying drawings. However, this disclosure is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this disclosure without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this disclosure.

Claims

1. A vehicle control method, characterized in that, include: The operation of the execution module is controlled based on the control information from the vehicle execution module. The control information is determined based on the user's ear pressure risk level, which is determined based on the user's physiological information.

2. The vehicle control method according to claim 1, characterized in that, The ear pressure risk level is determined based on the user's physiological information, including: the ear pressure risk level is determined based on the deviation from the physiological baseline, and the physiological baseline deviation is determined based on the user's physiological information; wherein, the ear pressure risk level is determined based on the deviation from the physiological baseline includes: the ear pressure risk level is determined based on the deviation from the physiological baseline and the standard deviation of the physiological indicator baseline.

3. The vehicle control method according to claim 2, characterized in that, The ear pressure risk level is determined based on the deviation from the physiological baseline and the standard deviation of the physiological index baseline, including at least one of the following: When the deviation from the physiological baseline is the first multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be low risk; When the deviation from the physiological baseline is the second multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be medium risk; When the deviation from the physiological baseline is the third multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be high risk; Wherein, the physiological baseline deviation is the sum of the product of the offset of each physiological indicator and its corresponding weight, and the offset is the difference between the current value of each physiological indicator and the physiological baseline data.

4. The vehicle control method according to claim 1, characterized in that, The ear pressure risk level is determined based on the user's physiological information, including: the ear pressure risk level is determined based on the user's physiological information and the vehicle's environmental information; wherein, the ear pressure risk level is determined based on the user's physiological information and the vehicle's environmental information, including: the ear pressure risk level is determined based on physiological baseline deviation and environmental coupling degree, the physiological baseline deviation is determined based on the user's physiological information, and the environmental coupling degree is determined based on the vehicle's environmental information.

5. The vehicle control method according to claim 4, characterized in that, The ear pressure risk level is determined based on deviation from physiological baseline and environmental coupling, including at least one of the following: When the deviation from the physiological baseline is the first multiple of the standard deviation of the physiological index baseline and the environmental coupling degree is the first coupling degree, the ear pressure risk level is determined to be low risk. When the deviation from the physiological baseline is the second multiple of the standard deviation of the physiological index baseline and the environmental coupling degree is the second coupling degree, the ear pressure risk level is determined to be medium risk. When the deviation from the physiological baseline is the third multiple of the standard deviation of the physiological index baseline, the ear pressure risk level is determined to be high risk; Wherein, the physiological baseline deviation is the sum of the products of the offset of each physiological indicator and its corresponding weight, and the offset is the difference between the current value of each physiological indicator and the physiological baseline data; the environmental coupling degree is the sum of the products of the matching degree between the current environmental information of the vehicle and the environmental warning data and their corresponding weights.

6. The vehicle control method according to claim 3 or 5, characterized in that, The control information is determined based on the user's ear pressure risk level and includes at least one of the following: When the ear pressure risk level is low, the control information is determined to be the first control information; wherein, the first control information includes: control information of the air conditioning system and / or control information of the seat system; wherein, the control information of the air conditioning system includes: blower duty cycle and / or air outlet mode, and / or the control information of the seat system includes: control information of the seat massage system; When the ear pressure risk level is medium risk, the control information is determined to be the second control information; wherein, the second control information includes: control information of the speaker at the seat headrest and / or control information of the seat side wing adjustment device and / or control information of the seat headrest micro airflow device; When the ear pressure risk level is high, the control information is determined to be third control information; wherein, the third control information includes at least one of the following: control information of the suspension system, control information of the door speakers, control information of the windows, control information of the speakers at the central control screen and / or the seat headrests.

7. The vehicle control method according to claim 6, characterized in that, The control method further includes: after controlling the execution module to work according to the control information of the vehicle execution module, adjusting the control information according to the intervention effect; wherein, the control information includes: second control information and / or third control information, and / or the intervention effect is determined according to the intervention response coefficient; wherein, the intervention response coefficient is determined according to the physiological baseline deviation before the execution module works and after working for a period of time; wherein, the intervention response coefficient is determined according to the following formula: (physiological baseline deviation before the execution module works - physiological baseline deviation after working for a period of time) / physiological baseline deviation before work.

8. The vehicle control method according to claim 7, characterized in that, The adjustment of the control information based on the intervention effect includes at least one of the following: When the intervention response coefficient is the first coefficient, the control information is maintained as the current level control information; When the intervention response coefficient is the second coefficient, the control information is adjusted to be the sum of the current level control information and the lower level control information; When the intervention response coefficient is the third coefficient, the control information is adjusted to a higher level of control information.

9. A vehicle control system, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-8.

10. A vehicle, characterized in that, include: The vehicle control system as described in claim 9.

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