Vehicle control method, device and equipment and storage medium

Abstract

The invention discloses a vehicle control method and device, equipment and a storage medium, and belongs to the technical field of vehicle control. The control method of the vehicle comprises the steps that a plurality of physiological and characteristic signals are collected; determining a stress characteristic signal in the plurality of physiological and characteristic signals according to a first specified condition; if the stress characteristic signal meets a second specified condition, determining that the driver is in a stress state; under the condition that the driver is in the stress state, determining a target stress level corresponding to the stress state in a plurality of preset stress levels; and adjusting the cabin environment of the vehicle according to the target stress level. The current stress state is graded and classified on the basis of the multiple preset stress levels, the cabin environment is adjusted on the basis of the target stress level, targeted active intervention is conducted on the stress state, the stress response of a driver can be quickly relieved, and the driving experience is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to a vehicle control method, device, equipment and storage medium. Background Technology

[0002] During vehicle operation, the driver's physiological and psychological state directly affects driving safety and comfort. Against this backdrop, user demands for the cabin environment are shifting from passive adjustment to personalized customization, making intelligent cockpit technology a core area for enhancing user experience and vehicle competitiveness.

[0003] In related technologies, the implementation of intelligent cockpit technology typically involves the autonomous recognition of the driver's physiological and psychological state when experiencing stress responses, as well as the issuance of alarms for abnormal conditions. For example, specific alarm signals can be used to alert the driver when they experience stress responses such as tension, anxiety, or fatigue.

[0004] However, because drivers have different physiological characteristics and psychological needs under different stress responses, and alarm signals may interfere with or re-stimulate, the above methods have problems such as limited intervention, poor targeting, poor effect on alleviating stress responses, and may even aggravate the driver's stress response. Summary of the Invention

[0005] This application provides a vehicle control method, apparatus, device, and storage medium to solve the technical problems existing in the related art. Specifically, it includes the following technical solutions.

[0006] In a first aspect, this application provides a vehicle control method, the method comprising: collecting multiple physiological and characteristic signals, the multiple physiological and characteristic signals indicating the physiological and psychological state of a driver during driving; determining a stress characteristic signal among the multiple physiological and characteristic signals according to a first specified condition; determining that the driver is in a stress state if the stress characteristic signal meets a second specified condition; determining a target stress level corresponding to the stress state among multiple preset stress levels when the driver is in the stress state; and adjusting the vehicle's cabin environment according to the target stress level.

[0007] In some possible implementations, the first designation condition includes the target first designation condition corresponding to the driver and the non-target first designation condition corresponding to other drivers. The step of determining the stress feature signal among the plurality of physiological and feature signals according to the first designation condition includes: if any physiological and feature signal among the plurality of physiological and feature signals satisfies the target first designation condition, determining the any physiological and feature signal as the stress feature signal.

[0008] In some possible implementations, the second specified condition is that the number of stress characteristic signals reaches a first quantity threshold within a specified time interval.

[0009] In some possible implementations, determining the target stress level corresponding to the stress state among a plurality of preset stress levels includes: determining the target stress level among the plurality of preset stress levels based on the number of stress feature signals.

[0010] In some possible implementations, the cabin environment adjustment strategy includes multiple environmental modes corresponding to the plurality of preset stress levels. Each of the multiple environmental modes includes a target environmental mode corresponding to the driver and a non-target environmental mode corresponding to other drivers. Adjusting the vehicle's cabin environment according to the target stress level includes: obtaining the target environmental mode corresponding to the target stress level; and adjusting the cabin environment according to the target environmental mode.

[0011] In some possible implementations, the method further includes: acquiring first scene feature information of the vehicle in a first driving scenario, wherein the first driving scenario is the driving scenario corresponding to the sampling time at which the plurality of physiological and feature information is collected; and adjusting the first specified condition according to the first scene feature information.

[0012] In some possible implementations, the method further includes: if the stress level reaches a level threshold and the duration of the stress state reaches a duration threshold, generating a first warning message, the first warning message being used to alert the driver to an abnormal stress response.

[0013] Secondly, this application provides a vehicle control device, the device comprising a data acquisition module, a determination module, and an adjustment module; the data acquisition module is configured to acquire multiple physiological and characteristic signals, the multiple physiological and characteristic signals indicating the driver's physiological and psychological state during driving; the determination module is configured to determine a stress characteristic signal among the multiple physiological and characteristic signals according to a first specified condition; the determination module is further configured to determine that the driver is in a stress state if the stress characteristic signal meets a second specified condition; and, when the driver is in the stress state, determine a target stress level corresponding to the stress state among multiple preset stress levels; the adjustment module is configured to adjust the vehicle's cabin environment according to the target stress level.

[0014] In some possible implementations, the first designation condition includes the target first designation condition corresponding to the driver and the non-target first designation condition corresponding to other drivers. When the determining module determines the stress feature signal among the plurality of physiological and feature signals according to the first designation condition, it is configured to: if any physiological and feature signal among the plurality of physiological and feature signals satisfies the target first designation condition, determine the any physiological and feature signal as the stress feature signal.

[0015] In some possible implementations, the second specified condition is that the number of stress characteristic signals reaches a first quantity threshold within a specified time interval.

[0016] In some possible implementations, when determining the target stress level corresponding to the stress state among a plurality of preset stress levels, the determining module is configured to: determine the target stress level among the plurality of preset stress levels based on the number of stress feature signals.

[0017] In some possible implementations, the cabin environment adjustment strategy includes multiple environmental modes corresponding to the plurality of preset stress levels. Any one of the multiple environmental modes includes a target environmental mode corresponding to the driver and a non-target environmental mode corresponding to other drivers. When adjusting the vehicle's cabin environment according to the target stress level, the adjustment module is configured to: acquire the target environmental mode corresponding to the target stress level; and adjust the cabin environment according to the target environmental mode.

[0018] In some possible implementations, the adjustment module is further configured to: acquire first scene feature information of the vehicle in a first driving scenario, wherein the first driving scenario is the driving scenario corresponding to the sampling time at which the plurality of physiological and feature information is collected; and adjust the first specified condition according to the first scene feature information.

[0019] In some possible implementations, the device further includes a warning module; the warning module is configured to generate a first warning message if the stress level reaches a level threshold and the duration of the stress state reaches a duration threshold, the first warning message being used to alert the driver to an abnormal stress response.

[0020] Thirdly, this application provides an electronic device for controlling a vehicle, comprising: a memory storing at least one program instruction for controlling the vehicle; and a processor, wherein when the program instruction is executed by the processor, the vehicle implements the method of the first aspect of this application or any possible embodiment of the first aspect.

[0021] Fourthly, this application provides a computer program (product) including computer program / instructions, which are executed by a processor to cause a vehicle to implement the method of the first aspect of this application or any possible implementation of the first aspect.

[0022] Fifthly, this application provides a computer-readable storage medium having stored thereon program instructions for controlling a vehicle, which, when executed by one or more processors, cause the vehicle to implement the method of the first aspect of this application or any possible implementation thereof.

[0023] In a sixth aspect, this application provides a vehicle that includes the apparatus described in the second aspect of this application or any possible embodiment of the second aspect.

[0024] The beneficial effects of the technical solution provided in this application include at least the following: The technical solution provided in this application, on the one hand, monitors the driver's physiological and psychological state during driving from multiple data dimensions through multiple physiological and characteristic signals. It determines stress characteristic signals among these signals based on a first specified condition and determines whether the driver is in a stressful state based on a second specified condition. This improves the accuracy and reliability of identifying the driver's physiological and psychological state, avoiding misjudgments caused by a single data dimension. On the other hand, when the driver is in a stressful state, this application embodiment can also classify and process the current stress state based on multiple preset stress levels, and adjust the cabin environment based on the target stress level. This provides targeted proactive intervention to quickly alleviate the driver's stress response, improve the driving experience, reduce the risk of operational errors caused by stress, and enhance driving safety. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of an implementation scenario provided in the embodiments of this application; Figure 2 This is a flowchart of a vehicle control method provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of the vehicle control device provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of an electronic device for controlling a vehicle provided in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0029] Figure 1 This is a schematic diagram of an implementation scenario provided in an embodiment of this application. (Reference) Figure 1 The implementation scenarios provided in this application include vehicle-mounted sensor 11, data processing unit 12, and cockpit domain control unit 13.

[0030] The vehicle-mounted sensor 11 is used, but is not limited to, to collect data related to the physiological or psychological state of the driver in the vehicle, and to upload the collected data to the data processing unit 12. Exemplarily, the vehicle-mounted sensor may be any type of sensor, including but not limited to contact electrodes, steering wheel capacitors, near-infrared cameras in a DMS (driver monitoring system).

[0031] The cabin domain controller 13 is used, but is not limited to, to regulate the cabin environment of a vehicle, such as, but not limited to, an on-board oxygen controller for regulating the oxygen concentration in the cabin environment, a thermal management controller for regulating the temperature in the cabin environment, and an on-board fragrance controller for regulating the fragrance in the cabin environment. This application makes no limitation in this regard.

[0032] The data processing unit 12 is connected to the vehicle sensor 11 and the cockpit domain controller 13 via wired or wireless means. It is used, but not limited to, to monitor the physiological or psychological state of the driver in the vehicle based on the data collected by the vehicle sensor 11, and to control the cockpit domain controller 13 based on the physiological or psychological state of the driver in the vehicle to adjust the cockpit environment.

[0033] In some embodiments, the vehicle-mounted sensor 11 may include, for example, sensors such as millimeter-wave radar, lidar, camera, and ultrasonic radar for collecting data related to the vehicle's surrounding environment; sensors such as gyroscope, accelerometer, GPS (global positioning system) module, and vehicle speed sensor for collecting data related to the vehicle's motion characteristics; sensors such as voltage sensor, current sensor, temperature sensor, and oil pressure sensor for collecting data related to the vehicle's operating status; or sensors for collecting any other type of data related to the vehicle. This application does not impose any limitations in this regard.

[0034] The data processing unit 12 may be a vehicle-mounted terminal capable of data processing and control functions, or a server, or a server cluster composed of multiple servers. This application makes no restrictions in this regard.

[0035] Those skilled in the art should understand that the above-described vehicle sensor 11, data processing unit 12, and cockpit and control unit 13 are merely examples. Other existing or future vehicle sensors, data processing units, cockpit and control units that are applicable to this application should also be included within the scope of protection of this application, and are hereby incorporated by reference.

[0036] Figure 2 This is a flowchart of a vehicle control method provided in an embodiment of this application. This method can, for example, be... Figure 1 The data processing unit shown performs the operation, and this application makes no limitations in this regard. See also Figure 2 The vehicle control method provided in this application embodiment may include steps S210-S250.

[0037] Step S210: Collect multiple physiological and characteristic signals, which indicate the driver's physiological and psychological state during the driving process.

[0038] For example, multiple physiological and characteristic signals may be collected, such as the driver's skin impedance signal collected by the steering wheel capacitor installed in the vehicle, or the driver's electrocardiogram signal collected by the contact electrode, or the driver's pupil diameter change rate and pupil nystagmus rate and other eye signals collected by the near-infrared camera, as well as any other type of signal used to indicate the driver's physiological and psychological state during driving. This application does not impose any limitations in this regard.

[0039] During driving, when a driver is in a state of fatigue or tension due to sudden road conditions, emergency braking, high-speed overtaking, or traffic congestion, their physiological and psychological state may undergo abnormal changes, leading to abnormal fluctuations in physiological and characteristic signals. For example, when a driver is in a state of stress due to tension, they may exhibit phenomena such as gripping the steering wheel tightly, increased heart rate, rapid breathing, dilated pupils, panicked gaze, or facial muscle tension, resulting in characteristic changes in one or more of the driver's skin impedance signals, electrocardiogram signals, and ocular signals. Based on this, embodiments of this application can monitor the driver's physiological and psychological state during driving by collecting multiple physiological and characteristic signals.

[0040] Step S220: Determine the stress characteristic signal among multiple physiological and characteristic signals according to the first specified condition.

[0041] For example, the first specified condition may be a preset threshold and / or a preset mathematical model used to determine whether any of the multiple physiological and characteristic signals exhibits abnormal fluctuations, used, but not limited to, to indicate abnormal changes in the driver's physiological or psychological state during driving. Stress characteristic signals may be, for example, filtered and labeled physiological and characteristic signals corresponding to abnormal fluctuations in the driver's physiological or psychological state, used to characterize whether the driver may be in a stressful state such as tension, anxiety, or fatigue.

[0042] Since the signal types, physiological meanings and fluctuation characteristics of multiple physiological and characteristic signals are different, in view of this, in the method provided in the embodiments of this application, there are multiple first specified conditions, and each of the multiple first specified conditions corresponds one-to-one with multiple physiological and characteristic signals. Any one of the multiple first specified conditions is used to determine whether the corresponding physiological and characteristic signal has abnormal fluctuations, so as to improve the accuracy of stress characteristic signal identification.

[0043] For example, if multiple physiological and characteristic signals include the driver's skin impedance signal, electrocardiogram (ECG) signal, a first eye signal indicating the rate of change of the driver's pupil diameter, and a second eye signal indicating the rate of pupillary nystagmus, and multiple first specified conditions include, for example, a grip state detection condition corresponding to the skin impedance signal, a heart rate fluctuation detection condition corresponding to the ECG signal, a pupil dilation detection condition corresponding to the first eye signal, and a pupillary nystagmus detection condition corresponding to the second eye signal. The skin impedance signal is collected by a steering wheel capacitor mounted in the vehicle and is used, but not limited to, to indicate the driver's grip state on the steering wheel.

[0044] Based on this, the skin impedance signal includes, for example, the frequency response characteristics of the impedance detection circuit under a specified swept AC signal, and the phase angle of the impedance detection circuit at a specified fixed frequency. The gripping state detection conditions are, for example, that the frequency response characteristics satisfy the characteristic valley frequency of human skin impedance, the phase angle is within a specific range, and the instantaneous rate of change of the phase angle of the impedance detection circuit at the specified fixed frequency reaches a phase angle change rate threshold. If the skin impedance signal meets the gripping state detection conditions, then the skin impedance signal is determined as a stress characteristic signal.

[0045] The characteristic valley frequency of human skin impedance represents the inherent impedance characteristics of human skin, and the specific range corresponds to the normal contact phase angle interval of human skin. When the frequency response characteristics of the impedance detection circuit under a specified swept AC signal meet the characteristic valley frequency of human skin impedance, and the phase angle of the impedance detection circuit at a specified fixed frequency is within a specific range, it indicates that the driver is gripping the steering wheel. If the instantaneous rate of change of the phase angle reaches the phase angle change rate threshold, it indicates a drastic change in the driver's grip strength. Therefore, the skin impedance signal is identified as a stress characteristic signal. The impedance detection circuit for the skin impedance signal is, for example, the circuit formed by the driver gripping the steering wheel and the steering wheel capacitor. The value of the phase angle change rate threshold can be adjusted according to the actual application scenario, and this application does not impose any restrictions in this regard.

[0046] The electrocardiogram signal may include, for example, a heart rate fluctuation signal that indicates the instantaneous heart rate fluctuation of the driver. The heart rate fluctuation detection condition may be, for example, that the instantaneous heart rate fluctuation indicated by the heart rate fluctuation signal reaches a heart rate fluctuation threshold. If the heart rate fluctuation signal meets the heart rate fluctuation detection condition, then the heart rate fluctuation signal is identified as a stress characteristic signal.

[0047] Eye signals include, for example, a first eye signal indicating the rate of change of the driver's pupil diameter. The pupil dilation detection condition is, for example, that the rate of change of the pupil diameter indicated by the first eye signal reaches a pupil diameter change rate threshold. If the first eye signal satisfies the pupil dilation detection condition, then the first eye signal is identified as a stress characteristic signal.

[0048] The eye signals may also include, for example, a second eye signal indicating the driver's pupillary tremor rate. The pupillary tremor detection condition is, for example, that the pupillary tremor rate indicated by the second eye signal reaches a pupillary tremor rate threshold. If the second eye signal meets the pupillary tremor detection condition, then the second eye signal is identified as a stress characteristic signal.

[0049] Considering that in practical applications, stress states include various types of stress states, such as a driver experiencing a first type of stress state due to tension and a driver experiencing a second type of stress state due to fatigue, the abnormal fluctuations of the same physiological and characteristic signals may differ under different types of stress states. Therefore, in some embodiments, if there are multiple stress states, any one of the multiple first specified conditions includes multiple first specified conditions corresponding one-to-one with the multiple stress states. Any one of the multiple first specified conditions is used, but is not limited to, to set a differentiated judgment threshold or mathematical model for the same physiological and characteristic signals based on the physiological characteristics of the corresponding type of stress state.

[0050] For example, the grip state detection conditions corresponding to skin impedance signals include grip state detection condition A corresponding to the first type of stress state and grip state detection condition B corresponding to the second type of stress state; the heart rate fluctuation detection conditions corresponding to electrocardiogram signals include heart rate fluctuation detection condition A corresponding to the first type of stress state and heart rate fluctuation detection condition B corresponding to the second type of stress state; the pupil dilation detection conditions corresponding to the first eyeball signal include pupil dilation detection condition A corresponding to the first type of stress state and pupil dilation detection condition B corresponding to the second type of stress state; and the pupil nystagmus detection conditions corresponding to the second eyeball signal include pupil nystagmus detection condition A corresponding to the first type of stress state and pupil nystagmus detection condition B corresponding to the second type of stress state.

[0051] Furthermore, considering that in practical applications, individual differences can lead to varying baseline levels and amplitudes of abnormal fluctuations in physiological and characteristic signals when drivers are under stress. Therefore, the method provided in this application supports personalized configuration and adjustment of the first specified condition based on the physiological characteristics of different drivers. In some embodiments, the first specified condition includes a target first specified condition corresponding to the driver and non-target first specified conditions corresponding to other drivers. Determining stress characteristic signals among multiple physiological and characteristic signals based on the first specified condition includes: if any physiological and characteristic signal satisfies the target first specified condition, determining that physiological and characteristic signal as a stress characteristic signal.

[0052] Different drivers are used to indicate the exclusively authorized users of a vehicle, such as multiple users of a family-owned vehicle. Different drivers include, for example, the current authorized user of the vehicle, and other drivers who are not currently authorized users. In this case, there are multiple first designations, and there is a one-to-one correspondence between these multiple first designations and different drivers. The target first designation is the first designation corresponding to the current driver of the vehicle, and the non-target first designations are the first designations other than the target first designation among the multiple first designations.

[0053] For example, the driver and other drivers can be identified through biometric information such as facial features collected by a facial recognition module installed in the vehicle, fingerprint information collected by a fingerprint recognition device, and voice features collected by a voiceprint recognition system. Alternatively, they can be identified through feedback information received by the vehicle from human-machine interaction terminals such as the in-vehicle central control screen, smart key, and mobile phone interconnection APP that are connected to the vehicle. The feedback information from human-machine interaction terminals connected to the vehicle includes, but is not limited to, account login commands, identity verification confirmation signals, and exclusive permission activation requests.

[0054] Step S230: If the stress characteristic signal meets the second specified condition, determine that the driver is in a stress state.

[0055] For example, the second specified condition is a preset rule used to perform quantitative statistics or logical relationship analysis on stress characteristic signals to determine whether the driver is in a stress state. As mentioned above, stress characteristic signals are, for example, filtered and labeled physiological and characteristic signals, including multiple stress characteristic signals that correspond one-to-one with multiple physiological and characteristic signals, used to characterize whether the driver may be in a stress state such as tension, anxiety, or fatigue. In other words, if the driver's psychological or physiological state changes abnormally during driving, causing abnormal fluctuations in the corresponding physiological and characteristic signals, these physiological and characteristic signals can be labeled to indicate that the driver may be in a stress state. In this case, the labeled physiological and characteristic signals, i.e., the stress characteristic signals, are comprehensively analyzed and judged according to the second specified condition to determine whether the driver is in a stress state. For example, the number of stress characteristic signals can be used to determine whether the stress characteristic signals meet the second specified condition, or the logical relationship between multiple stress characteristic signals corresponding to electrocardiogram signals, skin impedance signals, and eye signals can be used to determine whether the stress characteristic signals meet the second specified condition.

[0056] In some embodiments, the second specified condition is that the number of stress feature signals reaches a first quantity threshold within a specified time interval. A method for determining whether a stress feature signal meets the second specified condition based on the number of stress feature signals is as follows: if the number of stress feature signals reaches the first quantity threshold within the specified time interval, then the stress feature signal meets the second specified condition, and the driver is determined to be in a stress state; otherwise, the stress feature signal does not meet the second specified condition, and the driver is not in a stress state. This allows the system to perform cross-validation based on multi-dimensional physiological and behavioral characteristics, avoiding misjudgment or omission errors caused by single-dimensional data. The values ​​of the specified time interval and the first quantity threshold can be adjusted according to the actual application scenario, and this application does not impose any restrictions in this regard.

[0057] For example, in the case of multiple physiological and characteristic signals including the driver's skin impedance signal, electrocardiogram signal, first ocular signal indicating the rate of change of the driver's pupil diameter, and second ocular signal indicating the rate of pupillary nystagmus of the driver, if any two of the multiple physiological and characteristic signals are identified as stress characteristic signals within a specified time interval, that is, the number of stress characteristic signals is two, then the driver is determined to be in a state of stress.

[0058] Step S240: When the driver is in a state of stress, determine the target stress level corresponding to the stress state among multiple preset stress levels.

[0059] For example, multiple preset stress levels are used to indicate pre-configured classification criteria for stress states, and are used, but not limited to, to provide differentiated cabin environment intervention strategies based on the stress level of the stress state. Each of the multiple preset stress levels corresponds to a stress level determination index, used, but not limited to, to determine the current stress state of the driver to identify the target stress level of the current driver's stress state. For example, the multiple preset stress levels include a first preset stress level and a second preset stress level. The stress level determination index corresponding to the first preset stress level is that the number of stress feature signals reaches a second threshold. If the number of stress feature signals reaches the second threshold, the target stress level is determined to be the first preset stress level. The stress level determination index corresponding to the second preset stress level is that the number of stress feature signals reaches a third threshold. If the number of stress feature signals reaches the third threshold, the target stress level is determined to be the second preset stress level. The values ​​of the first and second thresholds can be adjusted according to the actual application scenario, and this application does not impose any restrictions in this regard.

[0060] In this case, a method for determining the target stress level corresponding to the stress state among multiple preset stress levels may include, for example, determining the target stress level among multiple preset stress levels based on the number of stress characteristic signals.

[0061] Step S250: Adjust the vehicle's cabin environment according to the target stress level.

[0062] Optionally, the cabin environment is used to indicate the physical environmental parameters and atmosphere of the vehicle's interior space. The cabin environment can be adjusted in ways including, but not limited to, adjusting one or more of the following: oxygen concentration, temperature, lighting, music, and / or fragrance. This application does not impose any limitations in this regard.

[0063] In some embodiments, the cabin environment adjustment strategy includes multiple environmental modes corresponding to multiple preset stress levels. Each of these environmental modes includes a target environmental mode corresponding to the driver and a non-target environmental mode corresponding to other drivers. Adjusting the vehicle's cabin environment according to the target stress level includes: obtaining the target environmental mode corresponding to the target stress level; and adjusting the cabin environment according to the target environmental mode so that the cabin environment can adapt to the driver's cabin environment setting preferences, providing personalized adjustment strategies for different drivers. The target environmental mode is a cabin environment adjustment scheme set according to the driver's relief needs and personalized cabin environment preferences under stress conditions corresponding to the preset stress levels. The non-target environmental mode is a cabin environment adjustment scheme set according to the relief needs and personalized cabin environment preferences of other drivers under stress conditions corresponding to the preset stress levels. The cabin environment adjustment scheme may include, for example, adjustments to air conditioning temperature, air vent airflow, fragrance type, background music style, and seat massage mode; this application does not impose any limitations in this regard.

[0064] Optionally, the driver and other drivers can be identified by biometric information such as facial features collected by the facial recognition module installed in the vehicle, fingerprint information collected by the fingerprint recognition device, and voice features collected by the voiceprint recognition system, or by feedback information received by the vehicle from human-machine interaction terminals such as the in-vehicle central control screen, smart key, and mobile phone interconnection APP that are connected to the vehicle. This application does not impose any restrictions in this regard.

[0065] Considering the uncertainty of vehicle driving scenarios in practical applications, and how changes in these scenarios can cause abnormal fluctuations in the driver's physiological and characteristic signals—for example, during high-speed driving or emergency maneuvers, the driver's electrocardiogram and skin impedance signals may experience brief abnormal fluctuations, or changes in lighting conditions in the driving environment may cause abnormal fluctuations in the driver's eye signals—in some embodiments, the vehicle control method provided in this application further includes: acquiring first scene feature information of the vehicle in a first driving scenario, where the first driving scenario corresponds to the sampling time at which multiple physiological and characteristic information are collected; and adjusting first specified conditions based on the first scene feature information.

[0066] The first scene feature information includes, but is not limited to, any type of information related to the vehicle's driving scenario, such as vehicle speed, acceleration / deceleration status, steering wheel angle, surrounding traffic conditions, road type, and whether the vehicle is actively avoiding obstacles or undergoing emergency braking. This first scene feature information may be acquired through sensors such as millimeter-wave radar, lidar, cameras, and ultrasonic radar installed in the vehicle to collect data related to the vehicle's surrounding environment; or through sensors such as gyroscopes, accelerometers, GPS modules, and vehicle speed sensors to collect data related to the vehicle's motion characteristics; or through sensors such as voltage sensors, current sensors, temperature sensors, and oil pressure sensors to collect data related to the vehicle's operating status. This application makes no limitations in this regard. Adjusting the first specified condition based on the first scene feature information may involve increasing the detection threshold of the first specified condition or temporarily skipping the labeling and filtering of physiological and feature signals corresponding to a certain first specified condition.

[0067] In some other embodiments, the vehicle control method provided in this application further includes, for example, generating a first warning message if the stress level reaches a level threshold and the duration of the stress state reaches a duration threshold. The first warning message is used to alert the driver to an abnormal stress response, proactively reminding the driver to pay attention to the current state and take timely rest or adjustment measures to ensure driving safety. The level threshold is, for example, any preset stress level from a plurality of pre-specified preset stress levels, used, but not limited to, distinguishing between a general stress state and a severe stress state requiring intervention. The form of the first warning message includes, but is not limited to, one or more of visual, auditory, and tactile information; this application makes no limitations in this regard.

[0068] The technical solution provided in this application, on the one hand, monitors the driver's physiological and psychological state during driving from multiple data dimensions through multiple physiological and characteristic signals. It determines stress characteristic signals among these signals based on a first specified condition and determines whether the driver is in a stressful state based on a second specified condition. This improves the accuracy and reliability of identifying the driver's physiological and psychological state, avoiding misjudgments caused by a single data dimension. On the other hand, when the driver is in a stressful state, this application embodiment can also classify and process the current stress state based on multiple preset stress levels, and adjust the cabin environment based on the target stress level. This provides targeted proactive intervention to quickly alleviate the driver's stress response, improve the driving experience, reduce the risk of operational errors caused by stress, and enhance driving safety.

[0069] In some other possible implementations, this application also provides a vehicle control device. Figure 3 This is a schematic diagram of the structure of the vehicle control device provided in an embodiment of this application. (Reference) Figure 3 The vehicle control device provided in this application embodiment includes a data acquisition module 310, a determination module 320, and an adjustment module 330.

[0070] The acquisition module 310 is configured to acquire multiple physiological and characteristic signals, which indicate the driver's physiological and psychological state during driving.

[0071] The determination module 320 is configured to determine a stress characteristic signal among a plurality of physiological and characteristic signals based on a first specified condition. The determination module 320 is also configured to determine that the driver is in a stress state if the stress characteristic signal meets the second specified condition; and to determine the target stress level corresponding to the stress state among multiple preset stress levels when the driver is in a stress state.

[0072] The adjustment module 330 is configured to adjust the vehicle's cabin environment according to the target stress level.

[0073] In some possible implementations, the first designation condition includes the target first designation condition corresponding to the driver and the non-target first designation condition corresponding to other drivers. When determining the stress feature signal among the multiple physiological and feature signals according to the first designation condition, the determination module 320 is configured to: if any physiological and feature signal among the multiple physiological and feature signals satisfies the target first designation condition, determine any physiological and feature signal as a stress feature signal.

[0074] In some possible implementations, the second specified condition is that the number of stress characteristic signals reaches a first quantity threshold within a specified time interval.

[0075] In some possible implementations, when determining the target stress level corresponding to the stress state among multiple preset stress levels, the determining module 320 is configured to: determine the target stress level among multiple preset stress levels based on the number of stress feature signals.

[0076] In some possible implementations, the cabin environment adjustment strategy includes multiple environmental modes corresponding to multiple preset stress levels. Any of the multiple environmental modes includes a target environmental mode corresponding to the driver and a non-target environmental mode corresponding to other drivers. When adjusting the vehicle's cabin environment according to the target stress level, the adjustment module 330 is configured to: acquire the target environmental mode corresponding to the target stress level; and adjust the cabin environment according to the target environmental mode.

[0077] In some possible implementations, the adjustment module 330 is further configured to: acquire first scene feature information of the vehicle in a first driving scenario, wherein the first driving scenario is the driving scenario corresponding to the sampling time of collecting multiple physiological and feature information; and adjust a first specified condition according to the first scene feature information.

[0078] In some possible implementations, the device further includes a warning module; the warning module is configured to generate a first warning message if the stress level reaches a level threshold and the duration of the stress state reaches a duration threshold, the first warning message being used to alert the driver to an abnormal stress response.

[0079] It should be understood that the vehicle control device and the vehicle control method provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the vehicle control method embodiments.

[0080] In some other possible implementations, this application also provides an electronic device for controlling a vehicle. Figure 4 This is a schematic diagram of the structure of an electronic device for controlling a vehicle provided in an embodiment of this application. See also... Figure 4 The electronic device for controlling a vehicle provided in this application includes the following structure.

[0081] Memory 410 stores at least one program instruction for controlling the vehicle. Processor 420 executes the program instruction, causing the vehicle to achieve the above-mentioned combination. Figure 2The steps of the described method and its various embodiments are described below. Depending on the implementation, the processor 420 may be one or more types of processors, including but not limited to DSP (digital signal processor), ASIC (application-specific integrated circuit), FPGA (field-programmable gate array), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., and the number of such devices may be determined according to actual needs.

[0082] In some other possible implementations, this application also provides a computer program (product) comprising computer programs / instructions, which are executed by a processor to cause the vehicle to achieve the above-described combination. Figure 2 The steps of the described method and its various embodiments.

[0083] In some other possible embodiments, this application also provides a computer-readable storage medium storing program instructions for controlling a vehicle, which, when executed by one or more processors, cause the vehicle to perform the aforementioned actions. Figure 2 The steps of the described method and its various embodiments are described. The computer-readable storage medium can be a readable signal medium or a readable storage medium. A readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0084] In some other possible implementations, this application also provides a vehicle, the vehicle including Figure 3 The apparatus described in several embodiments thereof.

[0085] It should also be noted that the terms "first," "second," etc. (if applicable) in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0086] It should be noted that the information involved in this application, including but not limited to user device information, user personal information, etc., data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals, are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the physiological and characteristic signals involved in the application were obtained under full authorization. The term "and / or" in the embodiments of this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0087] The above description is only for the purpose of enabling those skilled in the art to understand the technical solution of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application shall be included within the scope of protection of this application.

Claims

1. A control method of a vehicle, characterized by, The method comprises: collecting a plurality of physiological and characteristic signals, the plurality of physiological and characteristic signals indicating physiological and psychological states of a driver during driving; determining a stress characteristic signal in the plurality of physiological and characteristic signals according to a first specified condition; if the stress characteristic signal meets a second specified condition, determining that the driver is in a stress state; if the driver is in the stress state, determining a target stress level corresponding to the stress state in a plurality of preset stress levels; adjusting a cabin environment of the vehicle according to the target stress level.

2. The method of claim 1, wherein, The first specified condition comprises a target first specified condition corresponding to the driver and a non-target first specified condition corresponding to other drivers, and the determination of the stress characteristic signal in the plurality of physiological and characteristic signals according to the first specified condition comprises: if any physiological and characteristic signal in the plurality of physiological and characteristic signals meets the target first specified condition, determining the any physiological and characteristic signal as the stress characteristic signal.

3. The method of claim 1, wherein, The second specified condition is that the number of stress characteristic signals reaches a first number threshold within a specified time interval.

4. The method of claim 1, wherein, The determination of the target stress level corresponding to the stress state in the plurality of preset stress levels comprises: determining the target stress level in the plurality of preset stress levels according to the number of stress characteristic signals.

5. The method of claim 1, wherein, The adjustment strategy of the cabin environment comprises a plurality of environment modes corresponding to the plurality of preset stress levels, any environment mode in the plurality of environment modes comprises a target environment mode corresponding to the driver and a non-target environment mode corresponding to other drivers, and the adjustment of the cabin environment of the vehicle according to the target stress level comprises: obtaining a target environment mode corresponding to the target stress level; adjusting the cabin environment according to the target environment mode.

6. The method according to any one of claims 1-5, characterized in that, The method further comprises: obtaining first scene characteristic information of the vehicle in a first driving scene, the first driving scene being a driving scene corresponding to a sampling time at which the plurality of physiological and characteristic information is collected; adjusting the first specified condition according to the first scene characteristic information.

7. The method according to any one of claims 1-5, characterized in that, The method further comprises: if the stress level reaches a level threshold and the duration of the stress state reaches a duration threshold, generating first warning information for prompting the driver to have an abnormal stress reaction.

8. A control device of a vehicle characterized by comprising: The device comprises a collection module, a determination module and an adjustment module; The collection module is configured to collect a plurality of physiological and characteristic signals, the plurality of physiological and characteristic signals indicating physiological and psychological states of a driver during driving; The determination module is configured to determine a stress characteristic signal in the plurality of physiological and characteristic signals according to a first specified condition; The determination module is further configured to, if the stress characteristic signal meets a second specified condition, determine that the driver is in a stress state, and if the driver is in the stress state, determine a target stress level corresponding to the stress state in a plurality of preset stress levels; The adjustment module is configured to adjust a cabin environment of the vehicle according to the target stress level.

9. An electronic device, comprising: comprises: a memory having stored thereon program instructions for controlling a vehicle; and, a processor, which when executing the program instructions, causes the vehicle to implement the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, a computer readable storage medium having stored thereon program instructions for controlling a vehicle, which when executed by one or more processors, causes the device to implement the method of any one of claims 1-7.

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