A vehicle control method, apparatus, device, and storage medium

Abstract

This invention discloses a vehicle control method, apparatus, device, and storage medium to facilitate ensuring safety during driving. The method involves obtaining the driver's driving state; when the driver's driving state is abnormal, obtaining vehicle reference information; the reference information is vehicle-related information obtained during vehicle operation; the reference information includes at least: the vehicle's window status; determining abnormal state recovery items based on the reference information and driving state; and controlling the vehicle to execute the abnormal state recovery items. In this embodiment, when the driver is in an abnormal state, the abnormal state recovery items are jointly determined based on the vehicle's reference information and the driver's abnormal state, making the determined abnormal state recovery items more consistent with the driver's situation, thereby improving the execution effect of the abnormal state recovery items.

Description

Technical Field

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

[0002] With technological advancements, the demand for vehicles is increasing. Prolonged driving can lead to driver fatigue. Fatigue driving refers to a decline in driving skills resulting from physiological and psychological dysfunction caused by prolonged continuous driving. Fatigue driving significantly increases the risk of traffic accidents; therefore, appropriate measures are needed to alleviate driver fatigue and ensure driving safety.

[0003] Related technologies include in-vehicle fragrance systems and wearable hardware to alleviate driving fatigue, but the relief effect is not ideal. Summary of the Invention

[0004] The purpose of this invention is to provide a vehicle control method, apparatus, device, and storage medium to solve the technical problems in the prior art.

[0005] In a first aspect, embodiments of this application provide a vehicle control method, the method comprising:

[0006] Obtain the driver's driving status; when the driver's driving status is abnormal, obtain vehicle reference information; the reference information is information associated with the vehicle obtained during the vehicle's operation; the reference information includes at least: the vehicle's window status; based on the reference information and the driving status, determine abnormal status recovery items; control the vehicle to execute the abnormal status recovery items.

[0007] In this embodiment of the application, when the driver is in an abnormal state, the abnormal state recovery items are jointly determined based on the vehicle's reference information and the driver's abnormal state, so that the determined abnormal state recovery items are more in line with the driver's situation, thereby making the execution effect of the abnormal state recovery items better.

[0008] In some possible embodiments, obtaining the driver's driving state includes: determining the current road conditions corresponding to the vehicle; obtaining the driver's driving state based on the current road conditions and the image information set corresponding to the driver; the image information set includes images of the driver taken within a first preset time period.

[0009] In this embodiment of the application, the driver's driving state refers to the state that the driver experiences during driving that may affect driving safety. Different road conditions require different driving abilities from the driver. Therefore, determining the driver's driving state based on the current road conditions can better ensure driving safety.

[0010] In some possible embodiments, obtaining the driver's driving state based on the current road conditions and the image information set corresponding to the driver includes: acquiring driving state judgment conditions corresponding to the current road conditions; the same driving state has different driving state judgment conditions under different road conditions; and determining the driver's driving state based on the driving state judgment conditions and the image information set.

[0011] In this embodiment of the application, different road conditions place different demands on the driver. The worse the road conditions (i.e., the higher the degree of danger), the higher the demands on the driver. The driver needs to maintain a good driving state. Therefore, setting different driving state judgment conditions for different road conditions can better ensure driving safety.

[0012] In some possible embodiments, obtaining the driver's driving state based on the current road conditions and the image information set corresponding to the driver includes: determining the sensitivity level corresponding to the current road conditions; obtaining driving state judgment conditions corresponding to the current road conditions based on the sensitivity level; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions; and determining the driver's driving state based on the driving state judgment conditions and the image information set.

[0013] In this embodiment, multiple sensitivity levels are preset, with higher sensitivity levels corresponding to more dangerous road conditions. The sensitivity level of the current road condition can be obtained based on the range of road condition parameters corresponding to each sensitivity level. Different driving state judgment conditions are set for different sensitivity levels. More stringent driving state judgment conditions make it easier to trigger abnormal state recovery items, which helps users stay alert and ensures that users can pass through the current road conditions in a better driving state.

[0014] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's eye-closing duration percentage, continuous eye-closing duration, and number of first postures based on the image information set; determining a first eye-closing percentage threshold, a first eye-closing duration threshold, a first posture threshold, and a first driving time threshold based on the driving state judgment conditions; determining the driver's driving state as a moderate fatigue state in an abnormal state when the eye-closing duration percentage is greater than or equal to the first eye-closing duration threshold, and / or the continuous eye-closing duration is greater than or equal to the first eye-closing duration threshold, and / or the number of first postures is greater than or equal to the first posture threshold, and / or the vehicle's driving time is greater than or equal to the first driving time threshold; wherein, the vehicle's driving time is obtained from the vehicle's reference information.

[0015] In this embodiment of the application, by simultaneously judging the percentage of time the eyes are closed, the duration of continuous eye closure, the first posture, and the driving time, the accuracy of identifying abnormal driver states is improved. By judging only any one of the percentage of time the eyes are closed, the duration of continuous eye closure, the first posture, and the driving time, driving safety is further improved.

[0016] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's eye-closing duration percentage, continuous eye-closing duration, and number of first postures based on the image information set; determining a second eye-closing percentage threshold, a second eye-closing duration threshold, a second posture threshold, and a second driving time threshold based on the driving state judgment conditions; determining the driver's driving state as a severely fatigued state within an abnormal state when the eye-closing duration percentage is greater than or equal to the second eye-closing duration threshold, and / or the continuous eye-closing duration is greater than or equal to the second eye-closing duration threshold, and / or the number of first postures is greater than or equal to the second posture threshold, and / or the vehicle's driving time is greater than or equal to the second driving time threshold; wherein, the vehicle's driving time is obtained from the vehicle's reference information.

[0017] In this embodiment of the application, by setting different judgment conditions than those for moderate fatigue state, it is easier to trigger the abnormal state recovery project when the driver's driving state is worse, thereby ensuring the safety of the driver during driving.

[0018] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's line of sight angle and head angle according to the image information set; determining a line of sight deviation threshold and a head deviation angle threshold according to the driving state judgment conditions; and determining the driver's driving state as a distracted state in an abnormal state when the line of sight angle is greater than or equal to the line of sight deviation threshold and / or the head angle is greater than or equal to the head deviation angle threshold.

[0019] In this embodiment of the application, by judging both the line of sight angle and the head angle simultaneously, the accuracy of identifying abnormal driver states is improved. By judging only either the line of sight angle or the head angle, the driving safety of the driver is further guaranteed.

[0020] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's target driving posture according to the image information set; determining an abnormal behavior posture set according to the driving state judgment conditions; and determining the driver's driving state as an abnormal driving state among abnormal states when the target driving posture is in the abnormal behavior posture set.

[0021] In this embodiment of the application, by setting a set of abnormal behavior postures, postures that are dangerous to driving safety can be filtered out, thereby ensuring driving safety.

[0022] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's continuous eye-closing duration according to the image information set; determining a third eye-closing duration threshold according to the driving state judgment conditions; and determining the driver's driving state as an abnormal state of incapacity when the continuous eye-closing duration is greater than or equal to the third eye-closing duration threshold.

[0023] In this embodiment of the application, when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold, it indicates that the driver has been in a state of eye closure for a relatively long time, and therefore it can be determined that the driver may have lost the ability to drive.

[0024] In some possible embodiments, controlling the vehicle to execute the abnormal state recovery project includes: when there are multiple abnormal state recovery projects, determining the recommended weight of each abnormal state recovery project; and controlling the vehicle to execute the abnormal state recovery project with the highest recommended weight.

[0025] In this embodiment of the application, by setting recommendation weights, the abnormal state recovery items that need to be manually executed can be determined, thus avoiding the problem of poor user experience caused by executing multiple abnormal state recovery items.

[0026] In some possible embodiments, determining the recommendation weight of each abnormal state recovery project includes: obtaining the associated account corresponding to the vehicle; and obtaining the recommendation weight corresponding to each abnormal state recovery project based on the associated account.

[0027] In this embodiment of the application, different users have different preferences. Therefore, personalized customization for different users can be achieved by obtaining associated accounts, ensuring that the recommendation weight determined for each user is based on that user's preferences.

[0028] In some possible embodiments, determining the recommended weight for each abnormal state recovery item includes: for each abnormal state recovery item, performing the following steps: obtaining the number of times the abnormal state recovery item was used within a preset historical time period; determining the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery item; and using the ratio of the number of uses to the average recovery time as the recommended weight for the abnormal state recovery item.

[0029] In this embodiment, the number of times an abnormal state recovery item is used can reflect the user's preference for different abnormal state recovery items, and the average recovery time of an abnormal state recovery item can reflect the effectiveness of the execution of the abnormal state recovery item. Therefore, by comprehensively determining the recommendation weight by the average recovery time and the number of times an abnormal state recovery item is used, the determined recommendation weight can be more in line with the user's actual situation.

[0030] In some possible embodiments, determining the recommended weight for each abnormal state recovery item includes: for each abnormal state recovery item, performing the following steps: obtaining the number of times the abnormal state recovery item was used within a preset historical time period; and using the number of times it was used as the recommended weight for the abnormal state recovery item.

[0031] In this embodiment, the number of times an abnormal state recovery item is used can reflect the user's preference for different abnormal state recovery items. The recommendation weight is determined by the number of times the item is used, so that the identified abnormal state recovery items are more in line with the user's preferences.

[0032] In some possible embodiments, determining the recommended weight for each abnormal state recovery item includes: for each abnormal state recovery item, performing: determining the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery item; and obtaining the recommended weight for the abnormal state recovery item based on the average recovery time.

[0033] In this embodiment of the application, the average recovery time of the abnormal state recovery project can reflect the effectiveness of the execution of the abnormal state recovery project. By executing the abnormal state recovery project with the shortest average recovery time, the user's alertness is better, thereby ensuring a safer driving process.

[0034] In some possible embodiments, controlling the vehicle to execute the abnormal state recovery project includes: when there are multiple abnormal state recovery projects, broadcasting the name corresponding to each abnormal state recovery project and displaying the option corresponding to each abnormal state recovery project on the vehicle's display screen; and controlling the vehicle to execute the target abnormal state recovery project when receiving the name corresponding to the target abnormal state recovery project via user voice input, and / or when receiving the user's selection operation for the target abnormal state recovery project based on the display screen.

[0035] In this embodiment, the user is interacted with via voice and display, allowing the user to determine the abnormal state recovery items to be performed, thus making the determined abnormal state recovery items more in line with the user's preferences.

[0036] In some possible embodiments, determining the abnormal state recovery item based on the reference information and the driving state includes: when the driving state is a severe fatigue state in an abnormal state, and the reference information determines that the vehicle meets a first condition, determining that the abnormal state recovery item is to activate intelligent driving; wherein, the first condition includes at least one or a combination of the following: determining that the driving time of the vehicle from the end of the driving route is greater than a first preset driving time, determining that the driving time of the vehicle from the preset parking location is less than or equal to a second preset driving time, and determining that the driving segment of the vehicle is a highway segment.

[0037] In this embodiment of the application, intelligent driving is used to assist the driver in controlling the vehicle, which can ensure driving safety.

[0038] In some possible embodiments, activating intelligent driving includes: determining a target parking area based on the vehicle's navigation route; wherein the target parking area is the service area or parking area on the navigation route that is closest to the vehicle's current location; and adding the target parking area as a waypoint to the navigation route.

[0039] In this embodiment of the application, by adding the target parking area to the waypoint, the purpose of allowing the driver to rest in the target parking area can be achieved, which facilitates the driver's safety during subsequent driving.

[0040] In some possible embodiments, determining the abnormal state recovery item based on the reference information and the driving state includes: when the driving state is abnormal and a second condition is met according to the reference information, determining the abnormal state recovery item as opening the window for ventilation; wherein, the second condition includes determining that the window is closed and at least one or a combination of the following: determining that the estimated driving time is greater than or equal to a second preset driving time, the driving speed is less than or equal to a preset driving speed, determining that the vehicle's interior temperature is greater than or equal to the exterior temperature, determining that the exterior temperature is greater than or equal to a preset temperature, and determining that the exterior weather parameter is a sunny weather parameter.

[0041] In this embodiment of the application, when the driver is in an abnormal state and the vehicle windows are closed, the vehicle windows can be opened by performing window ventilation, thereby facilitating the driver's recovery from the abnormal state to the normal state.

[0042] In some possible embodiments, determining the abnormal state recovery item based on the reference information and the driving state includes: when the driving state is abnormal and a third condition is met according to the reference information, determining the abnormal state recovery item to be a refreshing music; wherein the third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a third preset driving time, and determining that the vehicle's audio status is off.

[0043] In this embodiment of the application, when the driver is in an abnormal state and the vehicle's audio is off, the driver can be restored to a normal state by turning on the audio.

[0044] In some possible embodiments, the window ventilation includes: opening the vehicle window, playing a voice message corresponding to opening the window, and displaying a prompt corresponding to window ventilation on the vehicle's display screen.

[0045] In this embodiment of the application, the user is interacted with through a combination of voice and display, which enhances the user experience.

[0046] In some possible embodiments, opening the vehicle window includes: acquiring the historical opening status of the vehicle window; determining the opening extent of the vehicle window based on the historical opening status; and opening the vehicle window based on the opening extent.

[0047] In this embodiment of the application, the vehicle windows are opened to the user's preferred opening degree according to the user's window opening preference, ensuring the user's experience and comfort.

[0048] In some possible embodiments, the stimulating music includes: playing a voice message corresponding to the music, controlling the vehicle to play the music, and displaying a prompt corresponding to the stimulating music on the vehicle's display screen.

[0049] In this embodiment of the application, while playing music, the system interacts with the user through voice and display to inform the user of the audio playback status, thereby enhancing the user experience.

[0050] In some possible embodiments, controlling the vehicle to execute the abnormal state recovery project includes: controlling the vehicle to execute the abnormal state recovery project when no abnormal state recovery project has been executed within a second preset time period before the current time is determined.

[0051] In this embodiment of the application, the abnormal state recovery project is executed only once within the second preset time period, which reduces the degree of disturbance to the user and ensures the user's experience.

[0052] In some possible embodiments, the method further includes: detecting road conditions to obtain current road conditions; determining the voice to be played based on the driving state and the current road conditions; and controlling the vehicle to play the voice to be played.

[0053] In this embodiment of the application, after determining that a voice message is to be played, the vehicle is controlled to play the voice message to remind the user, thereby ensuring the driver's driving safety.

[0054] In some possible embodiments, the method further includes: stopping the execution of the abnormal state recovery program when it is determined that the driver's driving state has returned to normal.

[0055] In this embodiment of the application, the user experience is improved by actively stopping the abnormal state recovery project.

[0056] Secondly, embodiments of this application also provide a vehicle control method, the method comprising:

[0057] The system determines the sensitivity level corresponding to the current road conditions of the vehicle; wherein, the higher the sensitivity level, the more stringent the driving state judgment conditions; the system determines the driver's driving state based on the sensitivity level; when the driver's driving state is abnormal, the system obtains reference information about the vehicle; the reference information is information associated with the vehicle obtained during the vehicle's operation; the reference information includes at least: the vehicle's window status; based on the reference information and the driving state, the system determines abnormal state recovery items; and the system controls the vehicle to execute the abnormal state recovery items.

[0058] In this embodiment of the application, when the driver is in an abnormal state, the abnormal state recovery items are jointly determined based on the vehicle's reference information and the driver's abnormal state, so that the determined abnormal state recovery items are more in line with the driver's situation, thereby making the execution effect of the abnormal state recovery items better.

[0059] In some possible embodiments, determining the driver's driving state based on the sensitivity level includes: obtaining driving state judgment conditions corresponding to the current road conditions based on the sensitivity level; obtaining the driver's driving state based on the driving state judgment conditions and the image information set corresponding to the driver; the image information set includes images of the driver taken within a first preset time period.

[0060] In this embodiment, multiple sensitivity levels are preset, with higher sensitivity levels corresponding to more dangerous road conditions. The sensitivity level of the current road condition can be obtained based on the range of road condition parameters corresponding to each sensitivity level. Different driving state judgment conditions are set for different sensitivity levels. More stringent driving state judgment conditions make it easier to trigger abnormal state recovery items, which helps users stay alert and ensures that users can pass through the current road conditions in a better driving state.

[0061] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's eye-closing duration percentage, continuous eye-closing duration, and number of first postures based on the image information set; determining a first eye-closing percentage threshold, a first eye-closing duration threshold, a first posture threshold, and a first driving time threshold based on the driving state judgment conditions; determining the driver's driving state as a moderate fatigue state in an abnormal state when the eye-closing duration percentage is greater than or equal to the first eye-closing duration threshold, and / or the continuous eye-closing duration is greater than or equal to the first eye-closing duration threshold, and / or the number of first postures is greater than or equal to the first posture threshold, and / or the vehicle's driving time is greater than or equal to the first driving time threshold; wherein, the vehicle's driving time is obtained from the vehicle's reference information.

[0062] In this embodiment of the application, by simultaneously judging the percentage of time the eyes are closed, the duration of continuous eye closure, the first posture, and the driving time, the accuracy of identifying abnormal driver states is improved. By judging only any one of the percentage of time the eyes are closed, the duration of continuous eye closure, the first posture, and the driving time, driving safety is further improved.

[0063] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's eye-closing duration percentage, continuous eye-closing duration, and number of first postures based on the image information set; determining a second eye-closing percentage threshold, a second eye-closing duration threshold, a second posture threshold, and a second driving time threshold based on the driving state judgment conditions; determining the driver's driving state as a severely fatigued state within an abnormal state when the eye-closing duration percentage is greater than or equal to the second eye-closing duration threshold, and / or the continuous eye-closing duration is greater than or equal to the second eye-closing duration threshold, and / or the number of first postures is greater than or equal to the second posture threshold, and / or the vehicle's driving time is greater than or equal to the second driving time threshold; wherein, the vehicle's driving time is obtained from the vehicle's reference information.

[0064] In this embodiment of the application, by setting different judgment conditions than those for moderate fatigue state, it is easier to trigger the abnormal state recovery project when the driver's driving state is worse, thereby ensuring the safety of the driver during driving.

[0065] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's line of sight angle and head angle according to the image information set; determining a line of sight deviation threshold and a head deviation angle threshold according to the driving state judgment conditions; and determining the driver's driving state as a distracted state in an abnormal state when the line of sight angle is greater than or equal to the line of sight deviation threshold and / or the head angle is greater than or equal to the head deviation angle threshold.

[0066] In this embodiment of the application, by judging both the line of sight angle and the head angle simultaneously, the accuracy of identifying abnormal driver states is improved. By judging only either the line of sight angle or the head angle, the driving safety of the driver is further guaranteed.

[0067] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's target driving posture according to the image information set; determining an abnormal behavior posture set according to the driving state judgment conditions; and determining the driver's driving state as an abnormal driving state among abnormal states when the target driving posture is in the abnormal behavior posture set.

[0068] In this embodiment of the application, by setting a set of abnormal behavior postures, postures that are dangerous to driving safety can be filtered out, thereby ensuring driving safety.

[0069] In some possible embodiments, determining the driver's driving state based on the driving state judgment conditions and the image information set includes: determining the driver's continuous eye-closing duration according to the image information set; determining a third eye-closing duration threshold according to the driving state judgment conditions; and determining the driver's driving state as an abnormal state of incapacity when the continuous eye-closing duration is greater than or equal to the third eye-closing duration threshold.

[0070] In this embodiment of the application, when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold, it indicates that the driver has been in a state of eye closure for a relatively long time, and therefore it can be determined that the driver may have lost the ability to drive.

[0071] In some possible embodiments, controlling the vehicle to execute the abnormal state recovery project includes: when there are multiple abnormal state recovery projects, determining the recommended weight of each abnormal state recovery project; and controlling the vehicle to execute the abnormal state recovery project with the highest recommended weight.

[0072] In this embodiment of the application, by setting recommendation weights, the abnormal state recovery items that need to be manually executed can be determined, thus avoiding the problem of poor user experience caused by executing multiple abnormal state recovery items.

[0073] In some possible embodiments, determining the recommendation weight of each abnormal state recovery project includes: obtaining the associated account corresponding to the vehicle; and obtaining the recommendation weight corresponding to each abnormal state recovery project based on the associated account.

[0074] In this embodiment of the application, different users have different preferences. Therefore, personalized customization for different users can be achieved by obtaining associated accounts, ensuring that the recommendation weight determined for each user is based on that user's preferences.

[0075] In some possible embodiments, determining the recommended weight for each abnormal state recovery item includes: for each abnormal state recovery item, performing the following steps: obtaining the number of times the abnormal state recovery item was used within a preset historical time period; determining the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery item; and using the ratio of the number of uses to the average recovery time as the recommended weight for the abnormal state recovery item.

[0076] In this embodiment, the number of times an abnormal state recovery item is used can reflect the user's preference for different abnormal state recovery items, and the average recovery time of an abnormal state recovery item can reflect the effectiveness of the execution of the abnormal state recovery item. Therefore, by comprehensively determining the recommendation weight by the average recovery time and the number of times an abnormal state recovery item is used, the determined recommendation weight can be more in line with the user's actual situation.

[0077] In some possible embodiments, determining the recommended weight for each abnormal state recovery item includes: for each abnormal state recovery item, performing the following steps: obtaining the number of times the abnormal state recovery item was used within a preset historical time period; and using the number of times it was used as the recommended weight for the abnormal state recovery item.

[0078] In this embodiment, the number of times an abnormal state recovery item is used can reflect the user's preference for different abnormal state recovery items. The recommendation weight is determined by the number of times the item is used, so that the identified abnormal state recovery items are more in line with the user's preferences.

[0079] In some possible embodiments, determining the recommended weight for each abnormal state recovery item includes: for each abnormal state recovery item, performing: determining the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery item; and obtaining the recommended weight for the abnormal state recovery item based on the average recovery time.

[0080] In this embodiment of the application, the average recovery time of the abnormal state recovery project can reflect the effectiveness of the execution of the abnormal state recovery project. By executing the abnormal state recovery project with the shortest average recovery time, the user's alertness is better, thereby ensuring a safer driving process.

[0081] In some possible embodiments, controlling the vehicle to execute the abnormal state recovery project includes: when there are multiple abnormal state recovery projects, broadcasting the name corresponding to each abnormal state recovery project and displaying the option corresponding to each abnormal state recovery project on the vehicle's display screen; and controlling the vehicle to execute the target abnormal state recovery project when receiving the name corresponding to the target abnormal state recovery project via user voice input, and / or when receiving the user's selection operation for the target abnormal state recovery project based on the display screen.

[0082] In this embodiment, the user is interacted with via voice and display, allowing the user to determine the abnormal state recovery items to be performed, thus making the determined abnormal state recovery items more in line with the user's preferences.

[0083] In some possible embodiments, determining the abnormal state recovery item based on the reference information and the driving state includes: when the driving state is a severe fatigue state in an abnormal state, and the reference information determines that the vehicle meets a first condition, determining that the abnormal state recovery item is to activate intelligent driving; wherein, the first condition includes at least one or a combination of the following: determining that the driving time of the vehicle from the end of the driving route is greater than a first preset driving time, determining that the driving time of the vehicle from the preset parking location is less than or equal to a second preset driving time, and determining that the driving segment of the vehicle is a highway segment.

[0084] In this embodiment of the application, intelligent driving is used to assist the driver in controlling the vehicle, which can ensure driving safety.

[0085] In some possible embodiments, activating intelligent driving includes: determining a target parking area based on the vehicle's navigation route; wherein the target parking area is the service area or parking area on the navigation route that is closest to the vehicle's current location; and adding the target parking area as a waypoint to the navigation route.

[0086] In this embodiment of the application, by adding the target parking area to the waypoint, the purpose of allowing the driver to rest in the target parking area can be achieved, which facilitates the driver's safety during subsequent driving.

[0087] In some possible embodiments, determining the abnormal state recovery item based on the reference information and the driving state includes: when the driving state is abnormal and a second condition is met according to the reference information, determining the abnormal state recovery item as opening the window for ventilation; wherein the second condition includes at least one or a combination of the following: determining that the estimated driving time is greater than or equal to a third preset driving time, the driving speed is less than or equal to a preset driving speed, determining that the vehicle's interior temperature is less than the vehicle's exterior temperature, determining that the vehicle's exterior temperature is greater than or equal to a preset temperature, determining that the window status is closed, and determining that the exterior weather parameter is a sunny weather parameter.

[0088] In this embodiment of the application, when the driver is in an abnormal state and the vehicle windows are closed, the vehicle windows can be opened by performing window ventilation, thereby facilitating the driver's recovery from the abnormal state to the normal state.

[0089] In some possible embodiments, determining the abnormal state recovery item based on the reference information and the driving state includes: when the driving state is abnormal and a third condition is met according to the reference information, determining the abnormal state recovery item to be a refreshing music; wherein the third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a first preset driving time, and determining that the vehicle's audio is off.

[0090] In this embodiment of the application, when the driver is in an abnormal state and the vehicle's audio is off, the driver can be restored to a normal state by turning on the audio.

[0091] In some possible embodiments, the window ventilation includes: opening the vehicle window, playing a voice message corresponding to opening the window, and displaying a prompt corresponding to window ventilation on the vehicle's display screen.

[0092] In this embodiment of the application, the user is interacted with through a combination of voice and display, which enhances the user experience.

[0093] In some possible embodiments, opening the vehicle window includes: acquiring the historical opening status of the vehicle window; determining the opening extent of the vehicle window based on the historical opening status; and opening the vehicle window based on the opening extent.

[0094] In this embodiment of the application, the vehicle windows are opened to the user's preferred opening degree according to the user's window opening preference, ensuring the user's experience and comfort.

[0095] In some possible embodiments, the stimulating music includes: controlling the vehicle to play music and displaying a prompt corresponding to the stimulating music on the vehicle's display screen.

[0096] In this embodiment of the application, while playing music, the system interacts with the user through voice and display to inform the user of the audio playback status, thereby enhancing the user experience.

[0097] In some possible embodiments, controlling the vehicle to execute the abnormal state recovery project includes: controlling the vehicle to execute the abnormal state recovery project when no abnormal state recovery project has been executed within a second preset time period before the current time is determined.

[0098] In this embodiment of the application, the abnormal state recovery project is executed only once within the second preset time period, which reduces the degree of disturbance to the user and ensures the user's experience.

[0099] In some possible embodiments, the method further includes: detecting road conditions to obtain current road conditions; determining the voice to be played based on the driving state and the current road conditions; and controlling the vehicle to play the voice to be played.

[0100] In this embodiment of the application, after determining that a voice message is to be played, the vehicle is controlled to play the voice message to remind the user, thereby ensuring the driver's driving safety.

[0101] In some possible embodiments, the method further includes: stopping the execution of the abnormal state recovery program when it is determined that the driver's driving state has returned to normal.

[0102] In this embodiment of the application, the user experience is improved by actively stopping the abnormal state recovery project.

[0103] Thirdly, embodiments of this application provide a vehicle control device, the device comprising:

[0104] The status acquisition module is used to obtain the driver's driving status;

[0105] The first information acquisition module is used to acquire reference information about the vehicle when the driver's driving state is abnormal; the reference information is information associated with the vehicle acquired during the vehicle's operation; the reference information includes at least the vehicle's window status.

[0106] The first project determination module is used to determine the abnormal state recovery project based on the reference information and the driving state.

[0107] The first project execution module is used to control the vehicle to execute the abnormal state recovery project.

[0108] In some possible embodiments, the state acquisition module is specifically used to: determine the current road conditions corresponding to the vehicle; obtain the driving state of the driver based on the current road conditions and the image information set corresponding to the driver; the image information set includes images of the driver taken within a first preset time period.

[0109] In some possible embodiments, the state acquisition module is specifically used to: acquire the driving state judgment conditions corresponding to the current road conditions; the driving state judgment conditions corresponding to the same driving state are different under different road conditions; and determine the driving state of the driver based on the driving state judgment conditions and the image information set.

[0110] In some possible embodiments, the state acquisition module is specifically used to: determine the sensitivity level corresponding to the current road condition; acquire the driving state judgment conditions corresponding to the current road condition based on the sensitivity level; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions; and determine the driver's driving state based on the driving state judgment conditions and the image information set.

[0111] In some possible embodiments, the state acquisition module is specifically used to: determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a first eye closure percentage threshold, a first eye closure duration threshold, a first posture threshold, and a first driving time threshold based on the driving state judgment conditions; determine that the driver's driving state is a moderate fatigue state in an abnormal state when the percentage of time the driver's eyes are closed is greater than or equal to the first eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the first eye closure duration threshold, and / or the number of first postures is greater than or equal to the first posture threshold, and / or the driving time of the vehicle is greater than or equal to the first driving time threshold; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0112] In some possible embodiments, the state acquisition module is specifically used to: determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a second eye closure percentage threshold, a second eye closure duration threshold, a second posture threshold, and a second driving time threshold based on the driving state judgment conditions; determine that the driver's driving state is a severely fatigued state in an abnormal state when the percentage of time the driver's eyes are closed is greater than or equal to the second eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the second eye closure duration threshold, and / or the number of first postures is greater than or equal to the second posture threshold, and / or the driving time of the vehicle is greater than or equal to the second driving time threshold; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0113] In some possible embodiments, the state acquisition module is specifically used to: determine the driver's gaze angle and head angle based on the image information set; determine a gaze offset threshold and a head offset angle threshold based on the driving state judgment conditions; and determine that the driver's driving state is a distracted state in an abnormal state when the gaze angle is greater than or equal to the gaze offset threshold and / or the head angle is greater than or equal to the head offset angle threshold.

[0114] In some possible embodiments, the state acquisition module is specifically used to: determine the driver's target driving posture based on the image information set; determine the abnormal behavior posture set based on the driving state judgment conditions; and determine the driver's driving state as an abnormal driving state among abnormal states when the target driving posture is in the abnormal behavior posture set.

[0115] In some possible embodiments, the state acquisition module is specifically used to: determine the duration of continuous eye closure of the driver based on the image information set; determine a third eye closure duration threshold based on the driving state judgment condition; and determine that the driver's driving state is an abnormal state of incapacity when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold.

[0116] In some possible embodiments, the first project execution module is specifically used to: determine the recommended weight of each abnormal state recovery project when there are multiple abnormal state recovery projects; and control the vehicle to execute the abnormal state recovery project with the highest recommended weight.

[0117] In some possible embodiments, the first project execution module is specifically used to: obtain the associated account corresponding to the vehicle; and obtain the recommendation weight corresponding to each abnormal state recovery project based on the associated account.

[0118] In some possible embodiments, the first project execution module is specifically used to: for each abnormal state recovery project, perform: obtaining the number of times the abnormal state recovery project is used within a preset historical time period; determining the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and using the ratio of the number of uses to the average recovery time as the recommended weight of the abnormal state recovery project.

[0119] In some possible embodiments, the first project execution module is specifically used to: for each abnormal state recovery project, perform the following: obtain the number of times the abnormal state recovery project has been used within a preset historical time period; and use the number of times it has been used as the recommendation weight of the abnormal state recovery project.

[0120] In some possible embodiments, the first project execution module is specifically used to: for each abnormal state recovery project, determine the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and obtain the recommended weight of the abnormal state recovery project based on the average recovery time.

[0121] In some possible embodiments, the first project execution module is specifically used to: when there are multiple abnormal state recovery projects, announce the name corresponding to each abnormal state recovery project and display the option corresponding to each abnormal state recovery project on the display screen of the vehicle; when the name corresponding to the target abnormal state recovery project is received by the user's voice input, and / or, based on the user's selection operation for the target abnormal state recovery project received by the display screen, control the vehicle to execute the target abnormal state recovery project.

[0122] In some possible embodiments, the first item determination module is specifically used to: determine the abnormal state recovery item as activating intelligent driving when the driving state is a severe fatigue state in an abnormal state and the reference information determines that the vehicle meets a first condition; wherein, the first condition includes at least one or a combination of the following: determining that the driving time of the vehicle from the end of the driving route is greater than a first preset driving time, determining that the driving time of the vehicle from the preset parking location is less than or equal to a second preset driving time, and determining that the driving segment of the vehicle is a highway segment.

[0123] In some possible embodiments, the first project execution module is specifically used to: determine a target parking area based on the vehicle's navigation route; wherein the target parking area is the service area or parking area in the navigation route that is closest to the vehicle's current location; and add the target parking area as a waypoint to the navigation route.

[0124] In some possible embodiments, the first item determination module is specifically used to: determine the abnormal state recovery item as opening the window for ventilation when the driving state is abnormal and the second condition is met according to the reference information; wherein, the second condition includes determining that the window state is closed and at least one or a combination of the following: determining that the estimated driving time is greater than or equal to a second preset driving time, the driving speed is less than or equal to a preset driving speed, determining that the vehicle interior temperature is greater than or equal to the vehicle exterior temperature, determining that the vehicle exterior temperature is greater than or equal to a preset temperature, and determining that the vehicle exterior weather parameter is a sunny weather parameter.

[0125] In some possible embodiments, the first item determination module is specifically used to: determine the abnormal state recovery item as a refreshing music when the driving state is abnormal and a third condition is met according to the reference information; wherein the third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a third preset driving time, and determining that the vehicle's audio status is off.

[0126] In some possible embodiments, the first project execution module is specifically used to: open the vehicle window, play the voice corresponding to opening the window, and display the prompt corresponding to opening the window for ventilation on the vehicle's display screen.

[0127] In some possible embodiments, the first project execution module is specifically used to: acquire the historical opening status of the vehicle's windows; determine the opening range of the vehicle's windows based on the historical opening status; and open the vehicle according to the opening range.

[0128] In some possible embodiments, the first project execution module is specifically used to: play the voice corresponding to the music being played, control the vehicle to play music, and display a prompt corresponding to the stimulating music on the vehicle's display screen.

[0129] In some possible embodiments, the first project execution module is specifically used to: control the vehicle to execute the abnormal state recovery project when no abnormal state recovery project has been executed within a second preset time period before the current time is determined.

[0130] In some possible embodiments, the first project execution module is further configured to: detect road conditions to obtain the current road conditions; determine the voice to be played based on the driving state and the current road conditions; and control the vehicle to play the voice to be played.

[0131] In some possible embodiments, the state acquisition module is further configured to: stop executing the abnormal state recovery project when it is determined that the driver's driving state has returned to normal.

[0132] Fourthly, embodiments of this application also provide a vehicle control device, the device comprising:

[0133] The sensitivity level determination module is used to determine the sensitivity level corresponding to the current road conditions of the vehicle; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions are.

[0134] A status determination module is used to determine the driver's driving status based on the sensitivity level;

[0135] The second information acquisition module is used to acquire reference information about the vehicle when the driver's driving state is abnormal; the reference information is information associated with the vehicle acquired during the vehicle's operation; the reference information includes at least the vehicle's window status.

[0136] The second project determination module is used to determine the abnormal state recovery project based on the reference information and the driving state.

[0137] The second project execution module is used to control the vehicle to execute the abnormal state recovery project.

[0138] In some possible embodiments, the state determination module is specifically used to: obtain driving state judgment conditions corresponding to the current road conditions based on the sensitivity level; obtain the driving state of the driver based on the driving state judgment conditions and the image information set corresponding to the driver; the image information set includes images of the driver taken within a first preset time period.

[0139] In some possible embodiments, the state determination module is specifically used to: determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a first eye closure percentage threshold, a first eye closure duration threshold, a first posture threshold, and a first driving time threshold based on the driving state judgment conditions; determine that the driver's driving state is a moderate fatigue state in an abnormal state when the percentage of time the driver's eyes are closed is greater than or equal to the first eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the first eye closure duration threshold, and / or the number of first postures is greater than or equal to the first posture threshold, and / or the driving time of the vehicle is greater than or equal to the first driving time threshold; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0140] In some possible embodiments, the state determination module is specifically used to: determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a second eye closure percentage threshold, a second eye closure duration threshold, a second posture threshold, and a second driving time threshold based on the driving state judgment conditions; determine that the driver's driving state is a severely fatigued state in an abnormal state when the percentage of time the driver's eyes are closed is greater than or equal to the second eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the second eye closure duration threshold, and / or the number of first postures is greater than or equal to the second posture threshold, and / or the driving time of the vehicle is greater than or equal to the second driving time threshold; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0141] In some possible embodiments, the state determination module is specifically used to: determine the driver's gaze angle and head angle based on the image information set; determine a gaze offset threshold and a head offset angle threshold based on the driving state judgment conditions; and determine that the driver's driving state is an abnormal state of distraction when the gaze angle is greater than or equal to the gaze offset threshold and / or the head angle is greater than or equal to the head offset angle threshold.

[0142] In some possible embodiments, the state determination module is specifically used to: determine the driver's target driving posture based on the image information set; determine an abnormal behavior posture set based on the driving state judgment conditions; and determine the driver's driving state as an abnormal driving state among abnormal states when the target driving posture is in the abnormal behavior posture set.

[0143] In some possible embodiments, the state determination module is specifically used to: determine the duration of continuous eye closure of the driver based on the image information set; determine a third eye closure duration threshold based on the driving state judgment condition; and determine that the driver's driving state is an abnormal state of incapacity when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold.

[0144] In some possible embodiments, the second project execution module is specifically used to: determine the recommended weight of each abnormal state recovery project when there are multiple abnormal state recovery projects; and control the vehicle to execute the abnormal state recovery project with the highest recommended weight.

[0145] In some possible embodiments, the second project execution module is specifically used to: obtain the associated account corresponding to the vehicle; and obtain the recommendation weight corresponding to each abnormal state recovery project based on the associated account.

[0146] In some possible embodiments, the second project execution module is specifically used to: for each abnormal state recovery project, perform: taking the number of times the abnormal state recovery project is used within a preset historical time period; determining the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and using the ratio of the number of uses to the average recovery time as the recommended weight of the abnormal state recovery project.

[0147] In some possible embodiments, the second project execution module is specifically used to: for each abnormal state recovery project, perform the following: obtain the number of times the abnormal state recovery project has been used within a preset historical time period; and use the number of times the project has been used as the recommendation weight of the abnormal state recovery project.

[0148] In some possible embodiments, the second project execution module is specifically configured to: for each abnormal state recovery project, perform: determine the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and obtain the recommended weight of the abnormal state recovery project based on the average recovery time.

[0149] In some possible embodiments, the second project execution module is specifically used to: when there are multiple abnormal state recovery projects, announce the name corresponding to each abnormal state recovery project and display the option corresponding to each abnormal state recovery project on the display screen of the vehicle; when the name corresponding to the target abnormal state recovery project is received by the user's voice input, and / or when the user's selection operation for the target abnormal state recovery project is received based on the display screen, control the vehicle to execute the target abnormal state recovery project.

[0150] In some possible embodiments, the second item determination module is specifically used to: determine the abnormal state recovery item as activating intelligent driving when the driving state is a severe fatigue state in an abnormal state and the vehicle meets a first condition based on the reference information; wherein, the first condition includes at least one or a combination of the following: determining that the driving time of the vehicle from the end of the driving route is greater than a first preset driving time, determining that the driving time of the vehicle from the preset parking location is less than or equal to a second preset driving time, and determining that the driving segment of the vehicle is a highway segment.

[0151] In some possible embodiments, the second project execution module is specifically used to: determine a target parking area based on the vehicle's navigation route; wherein the target parking area is the service area or parking area in the navigation route that is closest to the vehicle's current location; and add the target parking area as a waypoint to the navigation route.

[0152] In some possible embodiments, the second item determination module is specifically used to: determine the abnormal state recovery item as opening the window for ventilation when the driving state is abnormal and the second condition is met according to the reference information; wherein, the second condition includes at least one or a combination of the following: determining that the estimated driving time is greater than or equal to a third preset driving time, the driving speed is less than or equal to a preset driving speed, determining that the vehicle's interior temperature is less than the vehicle's exterior temperature, determining that the vehicle's exterior temperature is greater than or equal to a preset temperature, determining that the window status is closed, and determining that the exterior weather parameter is a sunny day parameter.

[0153] In some possible embodiments, the second item determination module is specifically used to: determine the abnormal state recovery item as a refreshing music when the driving state is abnormal and a third condition is met according to the reference information; wherein the third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a first preset driving time, and determining that the vehicle's audio status is off.

[0154] In some possible embodiments, the second project execution module is specifically used to: open the vehicle window, play the voice corresponding to opening the window, and display the prompt corresponding to opening the window for ventilation on the vehicle's display screen.

[0155] In some possible embodiments, the second project execution module is specifically used to: obtain the historical opening status of the vehicle's windows; determine the opening range of the vehicle's windows based on the historical opening status; and open the vehicle according to the opening range.

[0156] In some possible embodiments, the second project execution module is specifically used to: control the vehicle to play music and display a prompt corresponding to the stimulating music on the vehicle's display screen.

[0157] In some possible embodiments, the second project execution module is specifically used to: control the vehicle to execute the abnormal state recovery project when no abnormal state recovery project has been executed within a second preset time period before the current time is determined.

[0158] In some possible embodiments, the second project execution module is further configured to: detect road conditions to obtain the current road conditions; determine the voice to be played based on the driving state and the current road conditions; and control the vehicle to play the voice to be played.

[0159] In some possible embodiments, the state determination module is further configured to: stop executing the abnormal state recovery project when it is determined that the driver's driving state has returned to normal.

[0160] Fifthly, embodiments of this application also provide a vehicle dynamic control system, the system comprising: the vehicle control device described in the third and fourth aspects above.

[0161] Sixthly, embodiments of this application also provide a vehicle, including: a processor and a memory, the memory being used to store a program; the processor being used to run the program to implement the vehicle control method described in either the first or second aspect above.

[0162] In a seventh aspect, another embodiment of this application also provides an electronic device, including at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform any of the methods provided in the first or second aspect embodiments of this application.

[0163] Eighthly, another embodiment of this application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for causing a computer to perform any of the methods provided in the first or second aspect of the embodiments of this application.

[0164] Ninthly, another embodiment of this application also provides a computer program product, the computer program product comprising: computer program code, which, when run on a computer, causes the computer to perform any of the methods provided in the first or second aspect embodiments described above.

[0165] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0166] Figure 1 This is a schematic diagram of the overall process of a vehicle control method provided in an embodiment of this application;

[0167] Figure 2 A schematic diagram illustrating the process of obtaining the driver's driving state in a vehicle control method provided in this application embodiment;

[0168] Figure 3 This is a schematic diagram illustrating a vehicle control method based on map information to determine current road conditions, as provided in an embodiment of this application.

[0169] Figure 4 This is a schematic diagram illustrating the process of determining the driver's driving state based on driving state judgment conditions and image information set, as provided in an embodiment of this application.

[0170] Figure 5 This is another flowchart illustrating a vehicle control method provided in this application, which determines the driver's driving state based on driving state judgment conditions and image information set.

[0171] Figure 6 This is another flowchart illustrating a vehicle control method provided in this application, which determines the driver's driving state based on driving state judgment conditions and image information set.

[0172] Figure 7 This is another flowchart illustrating a vehicle control method provided in this application, which determines the driver's driving state based on driving state judgment conditions and image information set.

[0173] Figure 8 This is another flowchart illustrating a vehicle control method provided in this application, which determines the driver's driving state based on driving state judgment conditions and image information set.

[0174] Figure 9 A schematic diagram illustrating the interaction between a voice-plus-display method for vehicle control provided in this application embodiment and the user;

[0175] Figure 10 This is a schematic diagram illustrating a vehicle control method provided in this application that interacts with the user solely through display.

[0176] Figure 11 This is a schematic diagram corresponding to the window ventilation of a vehicle control method provided in an embodiment of this application;

[0177] Figure 12 A schematic diagram showing the stimulating music corresponding to a vehicle control method provided in an embodiment of this application;

[0178] Figure 13 A schematic diagram illustrating the addition of a target parking area to a waypoint in a vehicle control method provided in this application embodiment;

[0179] Figure 14 A schematic diagram illustrating the process of determining the voice to be played based on road conditions in a vehicle control method provided in this application embodiment;

[0180] Figure 15 A schematic diagram illustrating the correspondence between current road conditions and the voice to be played in a vehicle control method provided in an embodiment of this application;

[0181] Figure 16 A schematic diagram illustrating the process of determining and executing abnormal state recovery items based on sensitivity levels in a vehicle control method provided in this application embodiment;

[0182] Figure 17 A schematic diagram of an apparatus for a vehicle control method provided in an embodiment of this application;

[0183] Figure 18 This is a schematic diagram of another device for a vehicle control method provided in an embodiment of this application;

[0184] Figure 19 This is a schematic diagram of an electronic device for a vehicle control method provided in an embodiment of this application. Detailed Implementation

[0185] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0186] To better understand the technical solution of this application, the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0187] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0188] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0189] It should be understood that the term "and / or" used in this article 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, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0190] With technological advancements, the demand for vehicles is increasing. Prolonged driving can lead to driver fatigue. Fatigue driving refers to a decline in driving skills resulting from physiological and psychological dysfunction caused by prolonged continuous driving. Fatigue driving significantly increases the risk of traffic accidents; therefore, appropriate measures are needed to alleviate driver fatigue and ensure driving safety.

[0191] Related technologies include in-vehicle fragrance systems and wearable hardware to alleviate driving fatigue, but the relief effect is not ideal.

[0192] To address the aforementioned problems, embodiments of this application provide a vehicle control method, apparatus, device, and storage medium to solve these problems. The inventive concept of this application can be summarized as follows: obtaining the driver's driving state; when the driver's driving state is abnormal, obtaining reference information about the vehicle; the reference information is vehicle-related information obtained during the vehicle's operation; the reference information includes at least: the vehicle's window status; determining abnormal state recovery items based on the reference information and the driving state; and controlling the vehicle to execute the abnormal state recovery items.

[0193] In this embodiment of the application, when the driver is in an abnormal state, the abnormal state recovery items are jointly determined based on the vehicle's reference information and the driver's abnormal state, so that the determined abnormal state recovery items are more in line with the driver's situation, thereby making the execution effect of the abnormal state recovery items better.

[0194] For ease of understanding, the vehicle control method provided in this application embodiment will be described in detail below with reference to the accompanying drawings:

[0195] like Figure 1 The diagram shown is a schematic overall flow chart of a vehicle control method provided in an embodiment of this application, wherein:

[0196] In step 101: Obtain the driver's driving status.

[0197] In this embodiment, the driver's driving state refers to a state that affects driving safety during driving; it includes normal and abnormal states. In a normal state, the driver's physiological and psychological functions are normal, objectively ensuring driving skills. In an abnormal state, the driver's physiological and / or psychological functions become disordered, leading to an objective decline in driving skills and an inability to guarantee driving safety. Abnormal states include, but are not limited to: moderate fatigue, severe fatigue, distraction, abnormal driving, and disability.

[0198] Among them, moderate fatigue refers to a driver's relatively mild level of fatigue and a smaller decline in driving skills;

[0199] Severe fatigue refers to a state where the driver is highly fatigued, has significantly reduced driving skills, and is unable to guarantee driving safety.

[0200] Distracted state refers to a driver's inattentiveness while driving, where their gaze or head is not directed in the direction of travel, which can affect driving safety.

[0201] Abnormal driving state refers to abnormal behavior of the driver during driving, including but not limited to: smoking, drinking water, and eating.

[0202] Disability refers to a state in which a driver loses the ability to drive and can no longer control the vehicle.

[0203] In some possible embodiments, the demands on the driver vary depending on road conditions, with higher demands placed on the driver in more dangerous or complex road conditions, thus requiring the driver to maintain a better state of mind; therefore, step 101 above, obtaining the driver's driving state, can be specifically implemented as follows: Figure 2 The steps shown are as follows:

[0204] In step 201: Determine the current road conditions corresponding to the vehicle.

[0205] In this embodiment, current road conditions refer to the road conditions at the vehicle's current location. These conditions can be determined by information obtained from the vehicle's control system, map information, automated driving system (ADS), and other controls.

[0206] For example: Figure 3 As shown, the map information in the vehicle can determine the road condition and guidance information. Based on the road condition, information such as road type, congestion, speed limit, and traffic violation cameras can be obtained. Based on the guidance information, information such as continuous curves, highway entrances and exits, ramps, and lane change guidance can be obtained. Based on the vehicle control information, information such as vehicle speed and sunlight / rain conditions can be obtained. Based on the ADS (Adaptive Digital Sensor) system, information such as perception data, road structure, and vehicle status can be obtained. Based on the perception data, information such as the number of obstacles, distance to obstacles, and obstacle movement status can be obtained. Based on the road structure, information such as traffic lights, speed limits, intersection distance, and intersection type can be obtained. Based on the vehicle status, information such as sudden braking by the vehicle in front, distance to the vehicle in front, and lane departure can be obtained.

[0207] In step 202: Based on the current road conditions and the image information set corresponding to the driver, the driver's driving state is obtained; the image information set includes images of the driver taken within a first preset time period.

[0208] In this embodiment, different road conditions place different demands on the driver. The worse the road conditions (i.e., the higher the degree of danger), the higher the demands on the driver, requiring the driver to maintain a good driving state. Therefore, different driving state judgment conditions are set for different road conditions. The first preset duration can be set based on the experience of technicians, and this application does not limit it.

[0209] In some possible embodiments, step 202 above may specifically be implemented as follows: obtaining the driving state judgment conditions corresponding to the current road conditions; the driving state judgment conditions corresponding to the same driving state are different under different road conditions; and determining the driver's driving state based on the driving state judgment conditions and the image information set.

[0210] In this embodiment of the application, different driving state judgment conditions are set for different driving states. This method makes it easier to trigger abnormal state recovery items, which helps users stay alert and ensures that users can pass through the current road conditions in a better driving state.

[0211] In some other possible embodiments, step 202 above may also be implemented as: determining the sensitivity level corresponding to the current road condition; obtaining the driving state judgment conditions corresponding to the current road condition based on the sensitivity level; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions; and determining the driver's driving state based on the driving state judgment conditions and the image information set.

[0212] In this embodiment of the application, multiple sensitivity levels can be preset. The more dangerous the road condition, the higher the sensitivity level. The sensitivity level of the current road condition can be obtained according to the range of road condition parameters corresponding to each sensitivity level.

[0213] A higher sensitivity level indicates a higher level of danger in the current road condition. Stricter driving condition judgment conditions should be set for road conditions with higher levels of danger. Stricter driving condition judgment conditions make it easier to trigger abnormal state recovery items, making it easier for users to stay alert and ensuring that users can pass through the current road condition in a better driving state.

[0214] In this application embodiment, the parameters in the image information set used to identify different abnormal states are different. Therefore, in order to ensure accurate identification of each abnormal state, it is necessary to obtain the corresponding driving state judgment conditions for different abnormal states. The following describes the different abnormal states respectively:

[0215] In some possible embodiments, the driver's driving state is determined based on driving state judgment conditions and a set of image information. Specifically, this can be implemented as follows: Figure 4 The steps shown are as follows:

[0216] In step 401: Based on the image information set, determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures.

[0217] In this embodiment, images of the driver with their eyes closed and images of the driver in a first posture can be filtered from the image information set. The duration of continuous eye closure can be determined by the timestamp corresponding to the driver's closed-eye image. When multiple durations of continuous eye closure are determined based on the image information set, the mean, mode, or median of the multiple durations of continuous eye closure can be used as the duration of continuous eye closure determined based on the image information set. The first posture includes, but is not limited to, yawning.

[0218] In step 402: the first closed-eye percentage threshold, the first closed-eye duration threshold, the first posture threshold, and the first driving duration threshold are determined based on the driving state judgment conditions.

[0219] In this embodiment, the driving state judgment conditions are different for different road conditions. For example, under normal road conditions: the first eye-closing percentage threshold is 32.5%, the first eye-closing duration threshold is 3 seconds, the first posture threshold is 4, and the first driving time threshold is 3 hours; under highway conditions, the first eye-closing percentage threshold is 25%, the first eye-closing duration threshold is 2 seconds, the first posture threshold is 2, and the first driving time threshold is 2 hours. It can be understood that in order to make it easier to trigger the abnormal state recovery project under more dangerous road conditions, the more dangerous the road conditions, the smaller the first eye-closing percentage threshold, the first eye-closing duration threshold, the first posture threshold, and the first driving time threshold.

[0220] In step 403: when the proportion of time spent with eyes closed is greater than or equal to the first threshold for the proportion of time spent with eyes closed, and / or the duration of continuous time spent with eyes closed is greater than or equal to the first threshold for the duration of time spent with eyes closed, and / or the number of first postures is greater than or equal to the first threshold for the first posture, and / or the driving time of the vehicle is greater than or equal to the first threshold for the first driving time, the driver's driving state is determined to be a moderate fatigue state in the abnormal state; wherein, the driving time of the vehicle is obtained from the vehicle's reference information.

[0221] In this embodiment of the application, in order to improve the accuracy of identifying abnormal driver status, the percentage of time with eyes closed, the duration of continuous eye closure, the first posture, and the driving time can be judged simultaneously. If the driving safety of the driver is to be ensured, only one of the percentage of time with eyes closed, the duration of continuous eye closure, the first posture, and the driving time can be judged. If any one of the conditions is met, the subsequent steps will continue to be executed.

[0222] For example: if the current road condition is determined to be normal, the driving state judgment conditions corresponding to normal road conditions are: the first eye-closing percentage threshold is 32.5%, the first eye-closing duration threshold is 3 seconds, the first posture threshold is 4, and the first driving time threshold is 3 hours; if the driver's eye-closing duration percentage is determined to be 35%, the continuous eye-closing duration is 5 seconds, the number of first postures is 4, and the first driving time is 4 hours based on the image information set, then the driver's current driving state can be determined to be a moderate fatigue state.

[0223] In other possible embodiments, the driver's driving state is determined based on driving state judgment conditions and image information sets, and can also be implemented as follows: Figure 5 The steps shown are as follows:

[0224] In step 501: Based on the image information set, determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures.

[0225] The specific implementation method of this step is the same as that of step 401 above, and will not be repeated here.

[0226] In step 502: the second closed-eye percentage threshold, the second closed-eye duration threshold, the second posture threshold, and the second driving duration threshold are determined based on the driving state judgment conditions.

[0227] In this embodiment, under the same road conditions, the driving state judgment conditions corresponding to different abnormal states are not the same. For example, under normal road conditions, the driving state judgment conditions corresponding to moderate fatigue are: a first eye-closing percentage threshold of 32.5%, a first eye-closing duration threshold of 3 seconds, a first posture threshold of 4 seconds, and a first driving time threshold of 3 hours. Under normal road conditions, the driving state judgment conditions corresponding to severe fatigue are: a second eye-closing percentage threshold of 35%, a second eye-closing duration threshold of 6 seconds, a second posture threshold of 5 seconds, and a second driving time threshold of 4 hours. It can be understood that in order to make it easier to trigger the abnormal state recovery project when the driver's driving state is worse, the driving state judgment conditions corresponding to the driving state with greater impact on driving safety are more stringent. That is, under the same road conditions, the second eye-closing percentage threshold is greater than the first eye-closing percentage threshold, the second eye-closing duration threshold is greater than the first eye-closing duration threshold, the second posture threshold is greater than the first posture threshold, and the second driving time threshold is greater than the first driving time threshold.

[0228] In step 503: when the proportion of time spent with eyes closed is greater than or equal to the second threshold for the proportion of time spent with eyes closed, and / or the duration of continuous time spent with eyes closed is greater than or equal to the second threshold for the duration of time spent with eyes closed, and / or the number of first postures is greater than or equal to the second threshold for the second posture, and / or the driving time of the vehicle is greater than or equal to the second threshold for the second driving time, the driver's driving state is determined to be a severe fatigue state in an abnormal state; wherein, the driving time of the vehicle is obtained from the vehicle's reference information.

[0229] In this embodiment of the application, in order to improve the accuracy of identifying abnormal driver status, the percentage of time with eyes closed, the duration of continuous eye closure, the first posture, and the driving time can be judged simultaneously. If the driving safety of the driver is to be ensured, only one of the percentage of time with eyes closed, the duration of continuous eye closure, the first posture, and the driving time can be judged. If any one of the conditions is met, the subsequent steps will continue to be executed.

[0230] For example: if the current road condition is determined to be normal, the driving state judgment conditions corresponding to normal road conditions are: the second eye-closing percentage threshold is 35%, the second eye-closing duration threshold is 6 seconds, the second posture threshold is 5, and the second driving time threshold is 4 hours; if the driver's eye-closing duration percentage is determined to be 37%, the continuous eye-closing duration is 8 seconds, the number of first postures is 6, and the first driving time is 4 hours based on the image information set, then the driver's current driving state can be determined to be a state of severe fatigue.

[0231] It is understandable that when the percentage of time the driver closes their eyes, the duration of continuous eye closure, and the number of first postures determined based on the image information set meet the driving state judgment conditions corresponding to severe fatigue, they must also meet the driving state judgment conditions corresponding to moderate fatigue under the same road conditions. In this case, the driving state that has a greater impact on driving safety will be determined as the driver's driving state, that is, the driver's driving state will be determined as severe fatigue.

[0232] In some possible embodiments, the driver's driving state is determined based on driving state judgment conditions and a set of image information. Specifically, this can be implemented as follows: Figure 6 The steps shown are as follows:

[0233] In step 601: Based on the image information set, determine the driver's line of sight angle and head angle.

[0234] In this embodiment, images containing the driver's head can be filtered from the image information set. Based on these images, the gaze angle and head angle corresponding to each image can be determined. The driver's gaze angle is determined based on the mean, mode, or median of the gaze angles corresponding to multiple images, and similarly, the driver's head angle can be determined.

[0235] It is understandable that the line-of-sight angle is the angle between the driver's eyes and the direction of the vehicle's travel, while the head angle is the angle between the driver's head and the direction of the vehicle's travel.

[0236] In step 602: Determine the line of sight deviation threshold and head deviation angle threshold based on the driving status judgment conditions.

[0237] In this embodiment, the driving state judgment conditions differ for different road conditions. For example, under normal road conditions, the line-of-sight deviation threshold is 15 degrees and the head deviation threshold is 17 degrees; under highway conditions, the line-of-sight deviation threshold is 12 degrees and the head deviation threshold is 15 degrees. It is understood that, in order to more easily trigger the abnormal state recovery project under more dangerous road conditions, the more dangerous the road condition, the smaller the line-of-sight deviation threshold and the head deviation threshold.

[0238] In step 603: when the line of sight angle is greater than or equal to the line of sight deviation threshold, and / or the head angle is greater than or equal to the head deviation angle threshold, the driver's driving state is determined to be a distracted state in an abnormal state.

[0239] In this embodiment of the application, in order to improve the accuracy of identifying abnormal driver status, both the line of sight angle and the head angle can be judged simultaneously; if the driver's driving safety is to be ensured, only either the line of sight angle or the head angle can be judged, and the subsequent steps can be continued when either condition is met.

[0240] For example: if the current road conditions are determined to be normal, the driving state judgment conditions corresponding to normal road conditions are: the line of sight deviation threshold is 15 degrees and the head deviation threshold is 17 degrees; if the driver's line of sight angle is determined to be 17 degrees and the head angle is determined to be 18 degrees based on the image information set, then the driver's current driving state can be determined to be a distracted state.

[0241] In other possible embodiments, the driver's driving state is determined based on driving state judgment conditions and image information sets, and can also be implemented as follows: Figure 7 The steps shown are as follows:

[0242] In step 701: Determine the driver's target driving posture based on the image information set.

[0243] In this embodiment of the application, images of the driver’s posture as the target driving posture are selected from the image information set, wherein the target driving posture includes, but is not limited to: smoking, drinking water, eating, making a phone call, etc.

[0244] In step 702: Determine the set of abnormal behavior postures based on the driving status judgment conditions.

[0245] In this embodiment, the driving state judgment conditions are different for different road conditions, that is, the set of abnormal behaviors and postures can be different under different road conditions. For example: under normal road conditions, the set of abnormal behaviors and postures includes: eating and making a phone call; under highway conditions, the set of abnormal behaviors and postures includes: smoking, drinking water, eating, and making a phone call.

[0246] In step 703: when the target driving posture is in the abnormal behavior posture set, the driver's driving state is determined to be an abnormal driving state among abnormal states.

[0247] In this embodiment of the application, once the driver's target driving posture is determined to be in the abnormal behavior posture set, the driver's driving state can be determined to be an abnormal driving state.

[0248] For example: if the current road condition is determined to be normal, and the set of abnormal behaviors and postures corresponding to normal road conditions includes: eating, making a phone call; if the target driving posture is determined to be making a phone call, then the driver's current driving state can be determined to be an abnormal driving state.

[0249] In some possible embodiments, the driver's driving state is determined based on driving state judgment conditions and a set of image information. Specifically, this can be implemented as follows: Figure 8 The steps shown are as follows:

[0250] In step 801: Determine the duration of the driver's continuous eye closure based on the image information set.

[0251] In this embodiment of the application, images of the driver with closed eyes can be filtered out from the image information set. The duration of the driver's continuous eye closure can be determined by the timestamp corresponding to the image of the driver with closed eyes. When multiple durations of continuous eye closure are determined based on the image information set, the mean, mode, or median of the multiple durations of continuous eye closure can be used as the duration of continuous eye closure determined based on the image information set.

[0252] In step 802: Determine the third eye-closing duration threshold based on the driving status judgment conditions.

[0253] In this embodiment, the driving state judgment conditions differ for different road conditions. For example, under normal road conditions, the third eye-closing duration threshold is 8 seconds, while under highway conditions, the third eye-closing duration threshold is 6 seconds. It is understandable that, in order to more easily trigger the abnormal state recovery project under more dangerous road conditions, the third eye-closing duration threshold is smaller for more dangerous road conditions.

[0254] In step 803: when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold, the driver's driving state is determined to be an abnormal state of incapacity.

[0255] In this embodiment of the application, when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold, it indicates that the driver has been in a state of eye closure for a relatively long time, and therefore it can be determined that the driver may have lost the ability to drive.

[0256] For example: if the current road condition is determined to be normal, and the driving state judgment condition corresponding to normal road condition is: the third eye-closing duration threshold is 8 seconds, and the driver's continuous eye-closing duration is determined to be 10 seconds based on the image information set, then the driver's current driving state can be determined to be a disabled state.

[0257] In other possible embodiments, in addition to using the duration of continuous eye closure to determine whether the driver is in a disabled state, it is also possible to determine from the image information set whether there are images containing bloodstains and / or images containing foam. If it is determined that there are images containing bloodstains and / or images containing foam, it can be determined that the driver is injured or foaming at the mouth, and thus the driver's driving state can also be determined to be a disabled state.

[0258] It is understandable that the above-mentioned methods for determining the driver's driving status are executed in parallel, that is, the driver is simultaneously judged to be in a state of moderate fatigue, severe fatigue, distraction, abnormal driving, and incapacity. When the driver meets multiple conditions, the driver's final driving status can be selected according to the priority of the degree of danger corresponding to each condition.

[0259] For example, the order of priority from highest to lowest danger level is: incapacitated state, severely fatigued state, distracted state, abnormal driving state, and moderate fatigued state. If the driver is determined to be in both severely fatigued and moderate fatigued states according to the above method, then the driver's final driving state is determined to be severely fatigued.

[0260] In step 102: when the driver's driving state is abnormal, obtain the vehicle's reference information; the reference information is information related to the vehicle obtained during the vehicle's operation; the reference information includes at least the vehicle's window status.

[0261] In this embodiment, when the driver's driving state is abnormal, the abnormal state recovery project is determined by obtaining the vehicle's reference information and considering the vehicle's real-time situation and the driver's driving state. This ensures that the determined abnormal state recovery project is more in line with the actual situation of the vehicle and the user, resulting in better execution of the abnormal state recovery project.

[0262] In some possible embodiments, the reference information includes, in addition to the vehicle's window status, any one or a combination of the following: the estimated travel time from the destination, the vehicle's speed, the corresponding outside and inside temperatures, the vehicle's window status, the vehicle's audio status, the vehicle's travel distance, the vehicle's outside weather parameters, and the vehicle's route. The vehicle's window status includes both closed and open states; the vehicle's audio status includes both closed and open states; and the vehicle's outside weather parameters are used to determine the weather at the vehicle's location.

[0263] In step 103: Based on the reference information and driving status, determine the abnormal state recovery items.

[0264] In this embodiment, the abnormal state recovery items are determined jointly based on the real-time status of the vehicle and the driver's driving status, ensuring that the determined abnormal state recovery items are more in line with the actual situation of the vehicle and the user.

[0265] In some possible embodiments, based on reference information and driving status, an abnormal state recovery item is determined. Specifically, when the driving status is a severe fatigue state in an abnormal state, and the reference information determines that the vehicle meets a first condition, the abnormal state recovery item is determined to be to activate intelligent driving. The first condition includes at least one or a combination of the following: determining that the driving time from the end of the driving route is greater than a first preset driving time, determining that the driving time from the target parking area is less than or equal to a second preset driving time, and determining that the driving segment of the vehicle is a highway segment.

[0266] In this embodiment of the application, when the driver is in a state of severe fatigue, if the driving time from the end of the journey is short, it means that the driver is about to reach the end, so there is no need to perform the abnormal state recovery project. If the driving time from the end of the journey is longer than the first preset driving time, it means that the driver is far from the end. If the driver continues to drive the vehicle in a state of severe fatigue, driving safety cannot be guaranteed, so the abnormal state recovery project needs to be performed.

[0267] Similarly, if a driver is severely fatigued and the travel time to the target parking area is less than or equal to the second preset travel time, it indicates that the driver can rest at the target parking area. Therefore, the abnormal state recovery program needs to be executed to enable the driver to rest at the target parking area. If a driver is severely fatigued and the vehicle is traveling on a highway, it indicates that the current driving situation is relatively dangerous. Therefore, the abnormal state recovery program needs to be executed to ensure the driver's safety during driving.

[0268] In some other possible embodiments, the abnormal state recovery item is determined based on reference information and driving status. It can also be implemented as follows: when the driving status is abnormal and the second condition is met according to the reference information, the abnormal state recovery item is determined to be opening the window for ventilation. The second condition includes determining that the window status is closed and at least one or a combination of the following: determining that the expected driving time is greater than or equal to a second preset driving time, the driving speed is less than or equal to a preset driving speed, determining that the vehicle interior temperature is greater than or equal to the vehicle exterior temperature, determining that the vehicle exterior temperature is greater than or equal to a preset temperature, and determining that the vehicle exterior weather parameter is a sunny weather parameter.

[0269] In this embodiment, when the driver is in an abnormal state and the vehicle windows are closed, the windows can be opened for ventilation, thus facilitating the driver's recovery from the abnormal state to a normal state. When the estimated driving time is greater than or equal to a second preset driving time, it indicates that the driver is far from the destination. Continuing to drive in an abnormal state would compromise driving safety. Therefore, an abnormal state recovery program (window ventilation) is required to help the driver return to a normal state.

[0270] Similarly, opening windows for ventilation at excessive vehicle speeds can negatively impact driving safety; therefore, the abnormal state recovery program (window ventilation) should be executed when the vehicle speed is less than or equal to the preset speed. When the vehicle's interior temperature is lower than the exterior temperature, opening windows for ventilation is insufficient to alleviate the user's abnormal state; therefore, the abnormal state recovery program (window ventilation) should be executed when the interior temperature is equal to or equal to the exterior temperature. When the exterior temperature is below zero degrees Celsius, opening windows for ventilation will negatively impact the driver's experience; therefore, the abnormal state recovery program (window ventilation) should be executed when the exterior temperature is equal to or equal to the preset temperature. Similarly, when it is raining or snowing outside, opening windows for ventilation will negatively impact the driver's experience; therefore, the abnormal state recovery program (window ventilation) should be executed when the exterior weather parameters are sunny.

[0271] The preset temperature can be 0 degrees Celsius.

[0272] In some other possible embodiments, based on reference information and driving status, an abnormal state recovery item is determined. Specifically, when the driving status is abnormal and a third condition is met according to the reference information, the abnormal state recovery item is determined to be a refreshing music. The third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a third preset driving time, and determining that the vehicle's audio status is off.

[0273] In this embodiment, when the driver is in an abnormal state and the vehicle's audio is off, the driver can be brought back to a normal state by turning on the audio. When the estimated driving time of the vehicle is greater than or equal to a third preset driving time, it indicates that the driver is far from the destination. If the driver continues to drive in an abnormal state, driving safety cannot be guaranteed. Therefore, it is necessary to execute the abnormal state recovery program (refreshing music) to help the driver return to a normal state.

[0274] It is understood that the first preset driving time, the second preset driving time, and the third preset driving time can be the same or different.

[0275] In step 104: Control the vehicle to perform the abnormal state recovery project.

[0276] In the embodiments of this application, the execution methods for different abnormal state recovery projects are different, and they will be described separately below.

[0277] In some possible embodiments, multiple abnormal state recovery items may be determined simultaneously based on reference information and the driver's driving status. If multiple abnormal state recovery items are executed at the same time, it will lead to a poor user experience. Therefore, it is necessary to select one to execute. Thus, controlling the vehicle to execute the abnormal state recovery item can be implemented as follows: when there are multiple abnormal state recovery items, determine the recommended weight of each abnormal state recovery item; control the vehicle to execute the abnormal state recovery item with the highest recommended weight.

[0278] In this embodiment of the application, a corresponding recommendation weight is set for each abnormal state recovery project. When executing an abnormal state recovery project, only the one with the highest recommendation weight is selected for execution.

[0279] In some possible embodiments, in order to further ensure that the abnormal state recovery item with the highest recommended weight is the item that the driver prefers, the associated account corresponding to the vehicle can be obtained; and the recommended weight corresponding to each abnormal state recovery item can be obtained based on the associated account.

[0280] In this embodiment of the application, different users have different preferences. Therefore, personalized customization for different users can be achieved by obtaining associated accounts, ensuring that the recommendation weight determined for each user is based on that user's preferences.

[0281] In some other possible embodiments, when determining the recommended weight of each abnormal state recovery item, for each abnormal state recovery item, it can also be implemented as follows: obtaining the number of times the abnormal state recovery item is used within a preset historical time period; determining the average recovery time for the driver's driving state to recover from the abnormal state to the normal state after each execution of the abnormal state recovery item; and using the ratio of the number of uses to the average recovery time as the recommended weight of the abnormal state recovery item.

[0282] In this embodiment, the number of times an abnormal state recovery item is used can reflect the user's preference for different abnormal state recovery items, and the average recovery time of an abnormal state recovery item can reflect the effectiveness of the execution of the abnormal state recovery item. Therefore, by comprehensively determining the recommendation weight by the average recovery time and the number of times an abnormal state recovery item is used, the determined recommendation weight can be more in line with the user's actual situation.

[0283] For example, if the preset historical time period is one month, and the number of times the window was opened for ventilation within that month is 3, with an average recovery time of 8 minutes; and the number of times the wake-up music was used is 2, with an average recovery time of 15 minutes, then the recommended weight for opening the window for ventilation is determined to be 3 / 8 = 0.375, and the recommended weight for wake-up music is determined to be 2 / 15 = 0.133. Therefore, the recommended weight for opening the window for ventilation is greater.

[0284] In other possible embodiments, either the average recovery time corresponding to the abnormal state recovery item or the number of times it is used can be used to determine the recommendation weight; wherein, when the number of times it is used to determine the recommendation weight, the number of times it is used can be directly used as the recommendation weight corresponding to the abnormal state recovery item; when the average recovery time is used to determine the recommendation weight, the ratio of the preset value to the average recovery time can be used as the recommendation weight.

[0285] In other possible embodiments, when multiple abnormal state recovery items exist, the abnormal state recovery item to be executed can be determined by interacting with the driver. Specifically, this can be implemented as follows: when multiple abnormal state recovery items exist, the name corresponding to each abnormal state recovery item is announced, and the option corresponding to each abnormal state recovery item is displayed on the vehicle's display screen; when the name corresponding to the target abnormal state recovery item is received from the user's voice input, and / or when the user's selection operation for the target abnormal state recovery item is received based on the display screen, the vehicle is controlled to execute the target abnormal state recovery item.

[0286] Interaction with users can be achieved through a combination of voice and display, for example: Figure 9 As shown, the abnormal state recovery items include: opening windows for ventilation and playing refreshing music. The voice assistant on the display screen shows the icon and name corresponding to opening windows for ventilation in the voice interaction interface, and also shows the icon and name corresponding to refreshing music. At the same time, it says in voice, "Driving must be tiring. Would you like some refreshing music or to open the windows for ventilation?" In order to facilitate users to input the correct voice commands, the voice input prompts "Play refreshing music" and "Open the windows" are also displayed in the voice interface.

[0287] You can also interact with the user solely through display, for example: Figure 10 As shown, the abnormal state recovery items include: window ventilation and refreshing music. The corresponding icons and names for window ventilation and refreshing music are displayed on the screen. The driver can select window ventilation by clicking the corresponding selection icon.

[0288] It can also interact with users solely through voice. For example, existing abnormal state recovery items include: opening windows for ventilation and playing refreshing music. The system can use voice prompts such as "You must be tired from driving. Would you like some refreshing music or to open the windows for ventilation?" to determine the abnormal state recovery item selected by the user based on their voice input.

[0289] After identifying the abnormal state recovery items, the following details the execution methods for different abnormal state recovery items:

[0290] In some possible embodiments, when the abnormal state recovery item is window ventilation, it can be implemented as follows: opening the vehicle window, playing the corresponding voice message for opening the window, and displaying the corresponding prompt for window ventilation on the vehicle's display screen.

[0291] In this embodiment of the application, while opening the car window, the system interacts with the user through voice and display to inform the user that the car window is open, thereby enhancing the user's experience.

[0292] For example: Figure 11 As shown, the voice assistant on the display screen says, "You must be tired from driving. We've opened the window for you to let in some fresh air," while the display screen shows the corresponding prompts for opening the window for ventilation.

[0293] In some possible embodiments, in order to improve the user experience, the opening of the vehicle windows can be done according to the user's preferences. Specifically, this is implemented by: obtaining the historical opening status of the vehicle windows; determining the opening range of the vehicle windows based on the historical opening status; and opening the vehicle windows according to the opening range.

[0294] In this embodiment of the application, the vehicle windows are opened to the user's preferred opening degree according to the user's window opening preference, thus ensuring the user's experience and comfort.

[0295] In some other possible embodiments, when the abnormal state recovery item is a refreshing music, it can be implemented by: playing a voice command to control the vehicle to play music and displaying a prompt corresponding to the refreshing music on the vehicle's display screen.

[0296] In this embodiment of the application, while playing music, the system interacts with the user through voice and display to inform the user of the audio playback status, thereby enhancing the user experience.

[0297] For example: Figure 12 As shown, the voice assistant on the display screen says, "Driving must be tiring. Let me play some music for you to refresh yourself," and at the same time, the display screen shows the corresponding prompts for playing music.

[0298] In some possible embodiments, to enhance the energizing effect of the music playback, music that the user likes to sing along to can be identified from the historical music playback list and played. Specifically, each time music is played, it can be determined whether the user sings along by recognizing the user's lip movements and acquiring the user's voice; if the user sings along, the music is marked.

[0299] In this embodiment of the application, by playing music that the user sings along to, the performance of playing music is improved, and the refreshing effect is enhanced.

[0300] In some possible embodiments, when it is determined that the abnormal state recovery project is to enable intelligent driving, it can be specifically implemented as follows: determine the target parking area according to the vehicle's navigation route; wherein, the target parking area is the service area or parking area closest to the vehicle's current location in the navigation route; add the target parking area as a waypoint to the navigation route.

[0301] In this embodiment of the application, by adding the target parking area to the waypoint, the purpose of allowing the driver to rest in the target parking area can be achieved, which facilitates the driver's safety during subsequent driving.

[0302] For example: Figure 13 As shown, the voice assistant on the display screen will announce, "You look a bit tired. We'll be passing through the XX service area in 5 minutes. Why don't you stop there to rest?" If the user responds with a voice indicating agreement (including but not limited to: Okay, Sure, Alright, Go there to rest, Okay, OK), then the XX service area will be added as the target parking area to the navigation route.

[0303] In some possible embodiments, in order to avoid a poor user experience due to frequent execution of abnormal state recovery items, it can be implemented that: if no abnormal state recovery item has been executed within a second preset time period before the current time is determined, the vehicle is controlled to execute the abnormal state recovery item.

[0304] In this embodiment of the application, the abnormal state recovery project is executed only once within the second preset time period, which reduces the degree of disturbance to the user and ensures the user's experience.

[0305] In some other possible embodiments, the abnormal state recovery program can be stopped when it is determined that the driver's driving state has returned to normal.

[0306] For example: If the ongoing abnormal state recovery project is to open the windows for ventilation, once it is determined that the driver's driving status has returned to normal, then the window ventilation will be stopped and the windows will be closed.

[0307] In other possible embodiments, to ensure driving safety, the following can be implemented: Figure 14 The steps shown are as follows:

[0308] In step 1401: the road conditions are detected to obtain the current road conditions.

[0309] The specific implementation method of this step is the same as that of step 201 above, and will not be repeated here.

[0310] In step 1402: Determine the voice message to be played based on the driving status and current road conditions.

[0311] In this embodiment, a correspondence is established between driving status, current road conditions, and the audio to be played. For example, the correspondence between driving status, current road conditions, and the audio to be played is as follows: Figure 15 As shown (taking making or receiving a phone call as an example of abnormal behavior), if the current driving state is one of distraction and the current road condition is that the vehicle in front is too close, then the voice message to be played will be "The vehicle in front is too close, please do not drive while distracted".

[0312] In step 1403: Control the vehicle to play the voice message to be played.

[0313] In this embodiment of the application, after determining that a voice message is to be played, the vehicle is controlled to play the voice message to remind the user, thereby ensuring the driver's driving safety.

[0314] This application also provides a vehicle control method, such as... Figure 16 The diagram shown is a schematic overall flow chart of a vehicle control method provided in an embodiment of this application, wherein:

[0315] In step 1601: Determine the sensitivity level corresponding to the current road conditions of the vehicle; where the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions.

[0316] In this embodiment, multiple sensitivity levels can be preset, with higher sensitivity levels corresponding to more dangerous road conditions. The sensitivity level of the current road condition can be obtained based on the range of road condition parameters corresponding to each sensitivity level. A higher sensitivity level indicates a higher degree of danger for the current road condition.

[0317] In step 1602: Determine the driver's driving status based on the sensitivity level.

[0318] The specific implementation of this step is the same as the process in step 202 above, which determines the driving state judgment conditions based on the sensitivity level and obtains the driver's driving state based on the driving state judgment conditions, and will not be repeated here.

[0319] In step 1603: when the driver's driving state is abnormal, obtain the vehicle's reference information; the reference information is information related to the vehicle obtained during the vehicle's operation; the reference information includes at least the vehicle's window status.

[0320] The specific implementation method of this step is the same as that of step 102 above, and will not be repeated here.

[0321] In step 1604: Based on the reference information and driving status, determine the abnormal state recovery items.

[0322] The specific implementation method of this step is the same as that of step 103 above, and will not be repeated here.

[0323] In step 1605: Control the vehicle to perform the abnormal state recovery project.

[0324] The specific implementation method of this step is the same as that of step 104 above, and will not be repeated here.

[0325] Based on the same inventive concept, embodiments of this application also provide a vehicle control device, such as... Figure 17 As shown, the device includes:

[0326] The status acquisition module 17001 is used to obtain the driver's driving status;

[0327] The first information acquisition module 17002 is used to acquire reference information of the vehicle when the driver's driving state is abnormal; the reference information is information associated with the vehicle acquired during the vehicle's driving process; the reference information includes at least: the vehicle's window status.

[0328] The first project determination module 17003 is used to determine the abnormal state recovery project based on the reference information and the driving state.

[0329] The first project execution module 17004 is used to control the vehicle to execute the abnormal state recovery project.

[0330] In some possible embodiments, the state acquisition module 17001 is specifically used to: determine the current road conditions corresponding to the vehicle; obtain the driving state of the driver based on the current road conditions and the image information set corresponding to the driver; the image information set includes images of the driver taken within a first preset time period.

[0331] In some possible embodiments, the state acquisition module 17001 is specifically used to: acquire the driving state judgment conditions corresponding to the current road conditions; the driving state judgment conditions corresponding to the same driving state are different under different road conditions; and determine the driving state of the driver based on the driving state judgment conditions and the image information set.

[0332] In some possible embodiments, the state acquisition module 17001 is specifically used to: determine the sensitivity level corresponding to the current road condition; acquire the driving state judgment conditions corresponding to the current road condition based on the sensitivity level; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions; and determine the driver's driving state based on the driving state judgment conditions and the image information set.

[0333] In some possible embodiments, the state acquisition module 17001 is specifically used to: determine the percentage of time the driver closes their eyes, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a first eye closure percentage threshold, a first eye closure duration threshold, a first posture threshold, and a first driving time threshold based on the driving state judgment conditions; determine that the driver's driving state is a moderate fatigue state in an abnormal state when the percentage of time the driver closes their eyes is greater than or equal to the first eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the first eye closure duration threshold, and / or the number of first postures is greater than or equal to the first posture threshold, and / or the driving time of the vehicle is greater than or equal to the first driving time threshold; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0334] In some possible embodiments, the state acquisition module 17001 is specifically used to: determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a second eye closure percentage threshold, a second eye closure duration threshold, a second posture threshold, and a second driving time threshold based on the driving state judgment conditions; determine that the driver's driving state is a severely fatigued state in an abnormal state when the percentage of time the driver's eyes are closed is greater than or equal to the second eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the second eye closure duration threshold, and / or the number of first postures is greater than or equal to the second posture threshold, and / or the driving time of the vehicle is greater than or equal to the second driving time threshold; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0335] In some possible embodiments, the state acquisition module 17001 is specifically used to: determine the driver's gaze angle and head angle based on the image information set; determine the gaze offset threshold and head offset angle threshold based on the driving state judgment conditions; and determine that the driver's driving state is a distracted state in an abnormal state when the gaze angle is greater than or equal to the gaze offset threshold and / or the head angle is greater than or equal to the head offset angle threshold.

[0336] In some possible embodiments, the state acquisition module 17001 is specifically used to: determine the driver's target driving posture based on the image information set; determine the abnormal behavior posture set based on the driving state judgment conditions; and determine the driver's driving state as an abnormal driving state among abnormal states when the target driving posture is in the abnormal behavior posture set.

[0337] In some possible embodiments, the state acquisition module 17001 is specifically used to: determine the duration of continuous eye closure of the driver based on the image information set; determine a third eye closure duration threshold based on the driving state judgment condition; and determine that the driver's driving state is an abnormal state of incapacity when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold.

[0338] In some possible embodiments, the first project execution module 17004 is specifically used to: determine the recommended weight of each abnormal state recovery project when there are multiple abnormal state recovery projects; and control the vehicle to execute the abnormal state recovery project with the highest recommended weight.

[0339] In some possible embodiments, the first project execution module 17004 is specifically used to: obtain the associated account corresponding to the vehicle; and obtain the recommendation weight corresponding to each abnormal state recovery project based on the associated account.

[0340] In some possible embodiments, the first project execution module 17004 is specifically used to: for each abnormal state recovery project, perform: obtaining the number of times the abnormal state recovery project is used within a preset historical time period; determining the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and using the ratio of the number of uses to the average recovery time as the recommended weight of the abnormal state recovery project.

[0341] In some possible embodiments, the first project execution module 17004 is specifically used to: for each abnormal state recovery project, perform: obtain the number of times the abnormal state recovery project is used within a preset historical time period; and use the number of times it is used as the recommendation weight of the abnormal state recovery project.

[0342] In some possible embodiments, the first project execution module 17004 is specifically configured to: for each abnormal state recovery project, perform: determine the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and obtain the recommended weight of the abnormal state recovery project based on the average recovery time.

[0343] In some possible embodiments, the first project execution module 17004 is specifically used to: when there are multiple abnormal state recovery projects, announce the name corresponding to each abnormal state recovery project and display the option corresponding to each abnormal state recovery project on the display screen of the vehicle; when the name corresponding to the target abnormal state recovery project is received by the user's voice input, and / or when the user selects the target abnormal state recovery project based on the display screen, control the vehicle to execute the target abnormal state recovery project.

[0344] In some possible embodiments, the first item determination module 17003 is specifically used to: determine the abnormal state recovery item as activating intelligent driving when the driving state is a severe fatigue state in an abnormal state and the reference information determines that the vehicle meets a first condition; wherein, the first condition includes at least one or a combination of the following: determining that the driving time of the vehicle from the end of the driving route is greater than a first preset driving time, determining that the driving time of the vehicle from the preset parking location is less than or equal to a second preset driving time, and determining that the driving segment of the vehicle is a highway segment.

[0345] In some possible embodiments, the first project execution module 17004 is specifically used to: determine a target parking area based on the vehicle's navigation route; wherein the target parking area is the service area or parking area in the navigation route that is closest to the vehicle's current location; and add the target parking area as a waypoint to the navigation route.

[0346] In some possible embodiments, the first item determination module 17003 is specifically used to: determine the abnormal state recovery item as opening the window for ventilation when the driving state is abnormal and the second condition is met according to the reference information; wherein, the second condition includes determining that the window state is closed and at least one or a combination of the following: determining that the estimated driving time is greater than or equal to a second preset driving time, the driving speed is less than or equal to a preset driving speed, determining that the vehicle interior temperature is greater than or equal to the vehicle exterior temperature, determining that the vehicle exterior temperature is greater than or equal to a preset temperature, and determining that the vehicle exterior weather parameter is a sunny weather parameter.

[0347] In some possible embodiments, the first item determination module 17003 is specifically used to: determine the abnormal state recovery item as a refreshing music when the driving state is abnormal and the third condition is met according to the reference information; wherein the third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a third preset driving time, and determining that the vehicle's audio status is off.

[0348] In some possible embodiments, the first project execution module 17004 is specifically used to: open the vehicle window, play the voice corresponding to opening the window, and display the prompt corresponding to opening the window for ventilation on the vehicle's display screen.

[0349] In some possible embodiments, the first project execution module 17004 is specifically used for: acquiring the historical opening status of the vehicle's windows; determining the opening range of the vehicle's windows based on the historical opening status; and opening the vehicle based on the opening range.

[0350] In some possible embodiments, the first project execution module 17004 is specifically used to: play the voice corresponding to the music being played, control the vehicle to play music, and display a prompt corresponding to the stimulating music on the vehicle's display screen.

[0351] In some possible embodiments, the first project execution module 17004 is specifically used to: control the vehicle to execute the abnormal state recovery project when no abnormal state recovery project has been executed within a second preset time period before the current time is determined.

[0352] In some possible embodiments, the first project execution module 17004 is further configured to: detect road conditions to obtain the current road conditions; determine the voice to be played based on the driving state and the current road conditions; and control the vehicle to play the voice to be played.

[0353] In some possible embodiments, the state acquisition module 17001 is further configured to: stop executing the abnormal state recovery project when it is determined that the driver's driving state has returned to normal.

[0354] Based on the same inventive concept, embodiments of this application also provide a vehicle control device, such as... Figure 18 As shown, the device includes:

[0355] The level determination module 18001 is used to determine the sensitivity level corresponding to the current road conditions of the vehicle; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions are.

[0356] The status determination module 18002 is used to determine the driver's driving status based on the sensitivity level;

[0357] The second information acquisition module 18003 is used to acquire reference information of the vehicle when the driver's driving state is abnormal; the reference information is information associated with the vehicle acquired during the vehicle's driving process; the reference information includes at least: the vehicle's window status.

[0358] The second project determination module 18004 is used to determine the abnormal state recovery project based on the reference information and the driving state.

[0359] The second project execution module 18005 is used to control the vehicle to execute the abnormal state recovery project.

[0360] In some possible embodiments, the state determination module 18002 is specifically used to: obtain the driving state judgment conditions corresponding to the current road conditions based on the sensitivity level; obtain the driving state of the driver based on the driving state judgment conditions and the image information set corresponding to the driver; the image information set includes images of the driver taken within a first preset time period.

[0361] In some possible embodiments, the state determination module 18002 is specifically used to: determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a first eye closure percentage threshold, a first eye closure duration threshold, a first posture threshold, and a first driving time threshold based on the driving state judgment conditions; when the percentage of time the driver's eyes are closed is greater than or equal to the first eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the first eye closure duration threshold, and / or the number of first postures is greater than or equal to the first posture threshold, and / or the driving time of the vehicle is greater than or equal to the first driving time threshold, determine that the driver's driving state is a moderate fatigue state in an abnormal state; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0362] In some possible embodiments, the state determination module 18002 is specifically used to: determine the percentage of time the driver's eyes are closed, the duration of continuous eye closure, and the number of first postures based on the image information set; determine a second eye closure percentage threshold, a second eye closure duration threshold, a second posture threshold, and a second driving time threshold based on the driving state judgment conditions; when the percentage of time the driver's eyes are closed is greater than or equal to the second eye closure percentage threshold, and / or the duration of continuous eye closure is greater than or equal to the second eye closure duration threshold, and / or the number of first postures is greater than or equal to the second posture threshold, and / or the driving time of the vehicle is greater than or equal to the second driving time threshold, determine that the driver's driving state is a severely fatigued state in an abnormal state; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

[0363] In some possible embodiments, the state determination module 18002 is specifically used to: determine the driver's gaze angle and head angle based on the image information set; determine a gaze offset threshold and a head offset angle threshold based on the driving state judgment conditions; and determine that the driver's driving state is a distracted state in an abnormal state when the gaze angle is greater than or equal to the gaze offset threshold and / or the head angle is greater than or equal to the head offset angle threshold.

[0364] In some possible embodiments, the state determination module 18002 is specifically used to: determine the driver's target driving posture based on the image information set; determine the abnormal behavior posture set based on the driving state judgment conditions; and determine the driver's driving state as an abnormal driving state among abnormal states when the target driving posture is in the abnormal behavior posture set.

[0365] In some possible embodiments, the state determination module 18002 is specifically used to: determine the duration of continuous eye closure of the driver based on the image information set; determine a third eye closure duration threshold based on the driving state judgment condition; and determine that the driver's driving state is an abnormal state of incapacity when the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold.

[0366] In some possible embodiments, the second project execution module 18005 is specifically used to: determine the recommended weight of each abnormal state recovery project when there are multiple abnormal state recovery projects; and control the vehicle to execute the abnormal state recovery project with the highest recommended weight.

[0367] In some possible embodiments, the second project execution module 18005 is specifically used to: obtain the associated account corresponding to the vehicle; and obtain the recommendation weight corresponding to each abnormal state recovery project based on the associated account.

[0368] In some possible embodiments, the second project execution module 18005 is specifically used to: for each abnormal state recovery project, perform the following: take the number of times the abnormal state recovery project is used within a preset historical time period; determine the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and use the ratio of the number of uses to the average recovery time as the recommended weight of the abnormal state recovery project.

[0369] In some possible embodiments, the second project execution module 18005 is specifically used to: for each abnormal state recovery project, perform the following: obtain the number of times the abnormal state recovery project is used within a preset historical time period; and use the number of times it is used as the recommendation weight of the abnormal state recovery project.

[0370] In some possible embodiments, the second project execution module 18005 is specifically used to: for each abnormal state recovery project, perform: determine the average recovery time for the driver's driving state to recover from an abnormal state to a normal state after each execution of the abnormal state recovery project; and obtain the recommended weight of the abnormal state recovery project based on the average recovery time.

[0371] In some possible embodiments, the second project execution module 18005 is specifically used to: when there are multiple abnormal state recovery projects, announce the name corresponding to each abnormal state recovery project and display the option corresponding to each abnormal state recovery project on the display screen of the vehicle; when the name corresponding to the target abnormal state recovery project is received by the user's voice input, and / or, based on the user's selection operation for the target abnormal state recovery project received by the display screen, control the vehicle to execute the target abnormal state recovery project.

[0372] In some possible embodiments, the second item determination module 18004 is specifically used to: determine the abnormal state recovery item as activating intelligent driving when the driving state is a severe fatigue state in an abnormal state and the reference information determines that the vehicle meets a first condition; wherein, the first condition includes at least one or a combination of the following: determining that the driving time of the vehicle from the end of the driving route is greater than a first preset driving time, determining that the driving time of the vehicle from the preset parking location is less than or equal to a second preset driving time, and determining that the driving segment of the vehicle is a highway segment.

[0373] In some possible embodiments, the second project execution module 18005 is specifically used to: determine a target parking area based on the vehicle's navigation route; wherein the target parking area is the service area or parking area in the navigation route that is closest to the vehicle's current location; and add the target parking area as a waypoint to the navigation route.

[0374] In some possible embodiments, the second item determination module 18004 is specifically used to: determine the abnormal state recovery item as opening the window for ventilation when the driving state is abnormal and the second condition is met according to the reference information; wherein, the second condition includes at least one or a combination of the following: determining that the estimated driving time is greater than or equal to a third preset driving time, the driving speed is less than or equal to a preset driving speed, determining that the vehicle's interior temperature is less than the vehicle's exterior temperature, determining that the vehicle's exterior temperature is greater than or equal to a preset temperature, determining that the window status is closed, and determining that the exterior weather parameter is a sunny weather parameter.

[0375] In some possible embodiments, the second item determination module 18004 is specifically used to: determine the abnormal state recovery item as a refreshing music when the driving state is abnormal and a third condition is met according to the reference information; wherein the third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a first preset driving time, and determining that the vehicle's audio status is off.

[0376] In some possible embodiments, the second project execution module 18005 is specifically used to: open the vehicle window, play the voice corresponding to opening the window, and display the prompt corresponding to opening the window for ventilation on the vehicle's display screen.

[0377] In some possible embodiments, the second project execution module 18005 is specifically used for: acquiring the historical opening status of the vehicle's windows; determining the opening range of the vehicle's windows based on the historical opening status; and opening the vehicle based on the opening range.

[0378] In some possible embodiments, the second project execution module 18005 is specifically used to: control the vehicle to play music and display a prompt corresponding to the stimulating music on the vehicle's display screen.

[0379] In some possible embodiments, the second project execution module 18005 is specifically used to: control the vehicle to execute the abnormal state recovery project when no abnormal state recovery project has been executed within a second preset time period before the current time is determined.

[0380] In some possible embodiments, the second project execution module 18005 is further configured to: detect road conditions to obtain the current road conditions; determine the voice to be played based on the driving state and the current road conditions; and control the vehicle to play the voice to be played.

[0381] In some possible embodiments, the state determination module 18002 is further configured to: stop executing the abnormal state recovery item when it is determined that the driver's driving state has returned to normal.

[0382] Based on the same inventive concept, this application also provides a vehicle dynamic control system, the system comprising: the above-described... Figure 17 , Figure 18 The aforementioned vehicle control device.

[0383] Based on the same inventive concept, this application also provides a vehicle, including: a processor and a memory, wherein the memory is used to store a program; and the processor is used to run the program to implement the above. Figures 1-16 The vehicle control method described in any one of the above.

[0384] Corresponding to the above embodiments, this application also provides an electronic device. Figure 19 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device 1900 may include a processor 1901, a memory 1902, and a communication unit 1903. These components communicate through one or more buses. Those skilled in the art will understand that the structure of the electronic device shown in the figure does not constitute a limitation on the embodiment of the present invention. It may be a bus topology or a star topology, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0385] The communication unit 1903 is used to establish a communication channel, enabling the electronic device to communicate with other devices. It receives user data from other devices or sends user data to other devices.

[0386] The processor 1901 serves as the control center of the electronic device, connecting various parts of the device via interfaces and lines. It executes software programs and / or modules stored in the memory 1902 and retrieves data stored in the memory to perform various functions and / or process data. The processor can be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, the processor 1901 may consist only of a central processing unit (CPU). In this embodiment, the CPU may have a single processing core or include multiple processing cores.

[0387] The memory 1902 is used to store the execution instructions of the processor 1901. The memory 1902 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0388] When the execution instructions in memory 1902 are executed by processor 1901, the electronic device 1900 is able to perform its functions. Figure 1 Some or all of the steps in the illustrated embodiments.

[0389] In a specific implementation, the present invention also provides a computer storage medium, wherein the computer storage medium may store a program, which, when executed, may include some or all of the steps of the various embodiments of the vehicle control method provided by the present invention. The storage medium may be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0390] In some possible implementations, various aspects of the terminal device control method provided in this application can also be implemented in the form of a program product, which includes program code. When the program product is run on a computer device, the program code is used to cause the computer device to perform the steps in a vehicle control method according to various exemplary embodiments of this application as described above.

[0391] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0392] The program product for controlling a terminal device according to embodiments of this application may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on an electronic device. However, the program product of this application is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0393] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.

[0394] The same or similar parts between the various embodiments in this specification can be referred to mutually. In particular, the device embodiments and terminal embodiments are basically similar to the method embodiments, so the description is relatively simple, and the relevant parts can be referred to the description in the method embodiments.

Claims

1. A vehicle control method, characterized in that, The method includes: Obtain the driver's driving status; When the driver's driving state is abnormal, reference information of the vehicle is obtained; the reference information is information associated with the vehicle obtained during the vehicle's operation; the reference information includes at least: the status of the vehicle's windows; Based on the reference information and the driving state, determine the abnormal state recovery items; Control the vehicle to perform the abnormal state recovery project.

2. The method according to claim 1, characterized in that, The process of obtaining the driver's driving status includes: Determine the current road conditions corresponding to the vehicle; Based on the current road conditions and the image information set corresponding to the driver, the driver's driving state is obtained; the image information set includes images of the driver taken within a first preset time period.

3. The method according to claim 2, characterized in that, The process of obtaining the driver's driving state based on the current road conditions and the corresponding image information set includes: Obtain the driving state judgment conditions corresponding to the current road conditions; the driving state judgment conditions for the same driving state are different under different road conditions. Based on the driving state judgment conditions and the image information set, the driver's driving state is determined.

4. The method according to claim 3, characterized in that, The process of obtaining the driver's driving state based on the current road conditions and the corresponding image information set includes: Determine the sensitivity level corresponding to the current road conditions; The driving state judgment conditions corresponding to the current road conditions are obtained based on the sensitivity level; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions. Based on the driving state judgment conditions and the image information set, the driver's driving state is determined.

5. The method according to any one of claims 3-4, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, determine the percentage of time the driver closed their eyes, the duration of continuous eye closure, and the number of first postures; The first eye-closing percentage threshold, the first eye-closing duration threshold, the first posture threshold, and the first driving duration threshold are determined based on the driving state judgment conditions. When the percentage of time spent with eyes closed is greater than or equal to the first threshold for percentage of time spent with eyes closed, and / or the duration of continuous time spent with eyes closed is greater than or equal to the first threshold for duration of time spent with eyes closed, and / or the number of the first postures is greater than or equal to the first threshold for the first posture, and / or the driving time of the vehicle is greater than or equal to the first threshold for the first driving time, the driver's driving state is determined to be a moderate fatigue state in an abnormal state; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

6. The method according to any one of claims 3-5, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, determine the percentage of time the driver closed their eyes, the duration of continuous eye closure, and the number of first postures; The second eye-closing percentage threshold, the second eye-closing duration threshold, the second posture threshold, and the second driving duration threshold are determined based on the driving state judgment conditions. When the percentage of time spent with eyes closed is greater than or equal to the second threshold for percentage of time spent with eyes closed, and / or the duration of continuous eye closure is greater than or equal to the second threshold for duration of time spent with eyes closed, and / or the number of the first postures is greater than or equal to the second threshold for the second posture, and / or the driving time of the vehicle is greater than or equal to the second threshold for the second driving time, the driver's driving state is determined to be a severely fatigued state in an abnormal state; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

7. The method according to any one of claims 3-6, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, the driver's line of sight angle and head angle are determined; Determine the line of sight deviation threshold and head deviation angle threshold based on the driving state judgment conditions; When the line of sight angle is greater than or equal to the line of sight offset threshold, and / or the head angle is greater than or equal to the head offset angle threshold, the driver's driving state is determined to be a distracted state in an abnormal state.

8. The method according to any one of claims 3-7, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, the driver's target driving posture is determined; Determine the set of abnormal behavior postures based on the driving state judgment conditions; When the target driving posture is within the set of abnormal behavior postures, the driver's driving state is determined to be an abnormal driving state within an abnormal state.

9. The method according to any one of claims 3-8, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, determine the duration of the driver's continuous eye closure; The third eye-closing duration threshold is determined based on the driving state judgment conditions. When the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold, the driver's driving state is determined to be an abnormal state of incapacity.

10. The method according to claim 1, characterized in that, The control of the vehicle to execute the abnormal state recovery project includes: When multiple abnormal state recovery projects exist, determine the recommended weight for each abnormal state recovery project; Control the vehicle to execute the abnormal state recovery project with the highest recommended weight.

11. The method according to claim 10, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: Obtain the associated account corresponding to the vehicle; The recommended weight for each abnormal status recovery project is obtained based on the associated account.

12. The method according to claim 10, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: Perform the following for each abnormal state recovery project: Obtain the number of times the abnormal state recovery project is used within a preset historical time period; Determine the average recovery time for the driver's driving state to return to normal after each execution of the abnormal state recovery project; The ratio of the number of uses to the average recovery time is used as the recommended weight for the abnormal state recovery project.

13. The method according to claim 10, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: Perform the following for each abnormal state recovery project: Obtain the number of times the abnormal state recovery project is used within a preset historical time period; The number of times it is used will be used as the recommended weight for the abnormal state recovery project.

14. The method according to claim 10, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: For each abnormal state recovery project, the following is performed: Determine the average recovery time for the driver's driving state to return to normal after each execution of the abnormal state recovery project; The recommended weight of the abnormal state recovery project is obtained based on the average recovery time.

15. The method according to claim 1, characterized in that, The control of the vehicle to execute the abnormal state recovery project includes: When there are multiple abnormal state recovery items, announce the name of each abnormal state recovery item and display the option corresponding to each abnormal state recovery item on the vehicle's display screen; Upon receiving the name of the target abnormal state recovery item corresponding to the user's voice input, and / or upon receiving the user's selection operation for the target abnormal state recovery item based on the display screen, the vehicle is controlled to execute the target abnormal state recovery item.

16. The method according to claim 1, characterized in that, The step of determining abnormal state recovery items based on the reference information and the driving state includes: When the driving state is an abnormal state of severe fatigue, and the vehicle meets the first condition based on the reference information, the abnormal state recovery item is determined to be to enable intelligent driving. The first condition includes at least one or a combination of the following: determining that the travel time of the vehicle from the end of the journey is greater than a first preset travel time, determining that the travel time of the vehicle from the preset parking location is less than or equal to a second preset travel time, and determining that the vehicle's travel route is a highway.

17. The method according to claim 16, characterized in that, Enabling intelligent driving includes: The target parking area is determined based on the vehicle's navigation route; wherein the target parking area is the service area or parking area on the navigation route that is closest to the vehicle's current location; Add the target parking area as a waypoint to the navigation route.

18. The method according to any one of claims 1-17, characterized in that, The step of determining abnormal state recovery items based on the reference information and the driving state includes: When the driving state is abnormal and the second condition is met according to the reference information, the abnormal state recovery item is determined to be opening the window for ventilation. The second condition includes determining that the window is closed and at least one or a combination of the following: determining that the estimated driving time is greater than or equal to a second preset driving time, that the driving speed is less than or equal to a preset driving speed, determining that the vehicle's interior temperature is greater than or equal to the exterior temperature, determining that the exterior temperature is greater than or equal to a preset temperature, and determining that the exterior weather parameter is a sunny weather parameter.

19. The method according to any one of claims 1-18, characterized in that, The step of determining abnormal state recovery items based on the reference information and the driving state includes: When the driving state is abnormal and the third condition is met according to the reference information, the abnormal state recovery item is determined to be a refreshing music. The third condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a third preset driving time, and determining that the vehicle's audio is off.

20. The method according to claim 18, characterized in that, The aforementioned window ventilation includes: The vehicle windows are opened, a voice prompt corresponding to opening the windows is played, and a prompt for opening the windows for ventilation is displayed on the vehicle's screen.

21. The method according to claim 20, characterized in that, Opening the vehicle's windows includes: Obtain the historical opening status of the vehicle's windows; The opening range of the vehicle's windows is determined based on the historical opening status. The vehicle is opened according to the opening range.

22. The method according to claim 19, characterized in that, The refreshing music includes: Play the voice prompt corresponding to the music to control the vehicle to play music, and display the prompt corresponding to the refreshing music on the vehicle's display screen.

23. The method according to any one of claims 1-22, characterized in that, The control of the vehicle to execute the abnormal state recovery project includes: If no abnormal state recovery project has been executed within a second preset time period prior to the current time, the vehicle is controlled to execute the abnormal state recovery project.

24. The method according to any one of claims 1-23, characterized in that, The method further includes: The road conditions are detected to obtain the current road conditions; The voice message to be played is determined based on the driving status and the current road conditions. Control the vehicle to play the audio to be played.

25. The method according to any one of claims 1-24, characterized in that, The method further includes: Once it is determined that the driver's driving status has returned to normal, the abnormal status recovery project is stopped.

26. A vehicle control method, characterized in that, The method includes: Determine the sensitivity level corresponding to the current road conditions of the vehicle; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions; The driver's driving status is determined based on the aforementioned sensitivity level; When the driver's driving state is abnormal, reference information of the vehicle is obtained; the reference information is information associated with the vehicle obtained during the vehicle's operation; the reference information includes at least: the status of the vehicle's windows; Based on the reference information and the driving state, determine the abnormal state recovery items; Control the vehicle to perform the abnormal state recovery project.

27. The method according to claim 26, characterized in that, Determining the driver's driving state based on the sensitivity level includes: Based on the sensitivity level, obtain the driving state judgment conditions corresponding to the current road conditions; Based on the driving state judgment conditions and the image information set corresponding to the driver, the driving state of the driver is obtained; the image information set includes images of the driver taken within a first preset time period.

28. The method according to claim 27, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, determine the percentage of time the driver closed their eyes, the duration of continuous eye closure, and the number of first postures; The first eye-closing percentage threshold, the first eye-closing duration threshold, the first posture threshold, and the first driving duration threshold are determined based on the driving state judgment conditions. When the percentage of time spent with eyes closed is greater than or equal to the first threshold for percentage of time spent with eyes closed, and / or the duration of continuous time spent with eyes closed is greater than or equal to the first threshold for duration of time spent with eyes closed, and / or the number of the first postures is greater than or equal to the first threshold for the first posture, and / or the driving time of the vehicle is greater than or equal to the first threshold for the first driving time, the driver's driving state is determined to be a moderate fatigue state in an abnormal state; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

29. The method according to any one of claims 27-28, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, determine the percentage of time the driver closed their eyes, the duration of continuous eye closure, and the number of first postures; The second eye-closing percentage threshold, the second eye-closing duration threshold, the second posture threshold, and the second driving duration threshold are determined based on the driving state judgment conditions. When the percentage of time spent with eyes closed is greater than or equal to the second threshold for percentage of time spent with eyes closed, and / or the duration of continuous eye closure is greater than or equal to the second threshold for duration of time spent with eyes closed, and / or the number of the first postures is greater than or equal to the second threshold for the second posture, and / or the driving time of the vehicle is greater than or equal to the second threshold for the second driving time, the driver's driving state is determined to be a severely fatigued state in an abnormal state; wherein, the driving time of the vehicle is obtained from the reference information of the vehicle.

30. The method according to any one of claims 27-29, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, the driver's line of sight angle and head angle are determined; Determine the line of sight deviation threshold and head deviation angle threshold based on the driving state judgment conditions; When the line of sight angle is greater than or equal to the line of sight offset threshold, and / or the head angle is greater than or equal to the head offset angle threshold, the driver's driving state is determined to be a distracted state in an abnormal state.

31. The method according to any one of claims 27-30, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, the driver's target driving posture is determined; Determine the set of abnormal behavior postures based on the driving state judgment conditions; When the target driving posture is within the set of abnormal behavior postures, the driver's driving state is determined to be an abnormal driving state within an abnormal state.

32. The method according to any one of claims 27-31, characterized in that, Determining the driver's driving state based on the driving state judgment conditions and the image information set includes: Based on the image information set, determine the duration of the driver's continuous eye closure; The third eye-closing duration threshold is determined based on the driving state judgment conditions. When the duration of continuous eye closure is greater than or equal to the third eye closure duration threshold, the driver's driving state is determined to be an abnormal state of incapacity.

33. The method according to claim 26, characterized in that, The control of the vehicle to execute the abnormal state recovery project includes: When multiple abnormal state recovery projects exist, determine the recommended weight for each abnormal state recovery project; Control the vehicle to execute the abnormal state recovery project with the highest recommended weight.

34. The method according to claim 33, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: Obtain the associated account corresponding to the vehicle; The recommended weight for each abnormal status recovery project is obtained based on the associated account.

35. The method according to claim 33, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: Perform the following for each abnormal state recovery project: Obtain the number of times the abnormal state recovery project is used within a preset historical time period; Determine the average recovery time for the driver's driving state to return to normal after each execution of the abnormal state recovery project; The ratio of the number of uses to the average recovery time is used as the recommended weight for the abnormal state recovery project.

36. The method according to claim 33, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: Perform the following for each abnormal state recovery project: Obtain the number of times the abnormal state recovery project is used within a preset historical time period; The number of times it is used will be used as the recommended weight for the abnormal state recovery project.

37. The method according to claim 33, characterized in that, The determination of the recommended weight for each abnormal state recovery project includes: For each abnormal state recovery project, the following is performed: Determine the average recovery time for the driver's driving state to return to normal after each execution of the abnormal state recovery project; The recommended weight of the abnormal state recovery project is obtained based on the average recovery time.

38. The method according to claim 26, characterized in that, The control of the vehicle to execute the abnormal state recovery project includes: When there are multiple abnormal state recovery items, announce the name of each abnormal state recovery item and display the option corresponding to each abnormal state recovery item on the vehicle's display screen; Upon receiving the name of the target abnormal state recovery item corresponding to the user's voice input, and / or upon receiving the user's selection operation for the target abnormal state recovery item based on the display screen, the vehicle is controlled to execute the target abnormal state recovery item.

39. The method according to claim 26, characterized in that, The step of determining abnormal state recovery items based on the reference information and the driving state includes: When the driving state is an abnormal state of severe fatigue, and the vehicle meets the first condition based on the reference information, the abnormal state recovery item is determined to be to enable intelligent driving. The first condition includes at least one or a combination of the following: determining that the travel time of the vehicle from the end of the travel route is greater than a first preset travel time, determining that the travel time of the vehicle from the preset parking location is less than or equal to a second preset travel time, and determining that the vehicle's travel route is a highway.

40. The method according to claim 39, characterized in that, Enabling intelligent driving includes: The target parking area is determined based on the vehicle's navigation route; wherein the target parking area is the service area or parking area on the navigation route that is closest to the vehicle's current location; Add the target parking area as a waypoint to the navigation route.

41. The method according to any one of claims 26-40, characterized in that, The step of determining abnormal state recovery items based on the reference information and the driving state includes: When the driving state is abnormal and the second condition is met according to the reference information, the abnormal state recovery item is determined to be opening the window for ventilation. The second condition includes at least one or a combination of the following: determining that the expected driving time is greater than or equal to a third preset driving time, that the driving speed is less than or equal to a preset driving speed, determining that the vehicle's interior temperature is less than the exterior temperature, determining that the exterior temperature is greater than or equal to a preset temperature, determining that the vehicle window is in a closed state, and determining that the exterior weather parameter is a sunny day parameter.

42. The method according to any one of claims 26-41, characterized in that, The step of determining abnormal state recovery items based on the reference information and the driving state includes: When the driving state is abnormal and the third condition is met according to the reference information, the abnormal state recovery item is determined to be a refreshing music. The third condition includes at least one or a combination of the following: determining that the estimated driving time is greater than or equal to the first preset driving time, and determining that the vehicle's audio is off.

43. The method according to claim 41, characterized in that, The aforementioned window ventilation includes: The vehicle windows are opened, a voice prompt corresponding to opening the windows is played, and a prompt for opening the windows for ventilation is displayed on the vehicle's screen.

44. The method according to claim 43, characterized in that, Opening the vehicle's windows includes: Obtain the historical opening status of the vehicle's windows; The opening range of the vehicle's windows is determined based on the historical opening status. The vehicle is opened according to the opening range.

45. The method according to claim 42, characterized in that, The refreshing music includes: Control the vehicle to play music and display a prompt corresponding to the refreshing music on the vehicle's display screen.

46. ​​The method according to any one of claims 26-45, characterized in that, The control of the vehicle to execute the abnormal state recovery project includes: If no abnormal state recovery project has been executed within a second preset time period prior to the current time, the vehicle is controlled to execute the abnormal state recovery project.

47. The method according to any one of claims 26-46, characterized in that, The method further includes: The road conditions are detected to obtain the current road conditions; The voice message to be played is determined based on the driving status and the current road conditions. Control the vehicle to play the audio to be played.

48. The method according to any one of claims 26-47, characterized in that, The method further includes: Once it is determined that the driver's driving status has returned to normal, the abnormal status recovery project is stopped.

49. A vehicle control device, characterized in that, The device includes: The status acquisition module is used to obtain the driver's driving status; The first information acquisition module is used to acquire reference information about the vehicle when the driver's driving state is abnormal; the reference information is information associated with the vehicle acquired during the vehicle's operation; the reference information includes at least the vehicle's window status. The first project determination module is used to determine the abnormal state recovery project based on the reference information and the driving state. The first project execution module is used to control the vehicle to execute the abnormal state recovery project.

50. A vehicle control device, characterized in that, The device includes: The sensitivity level determination module is used to determine the sensitivity level corresponding to the current road conditions of the vehicle; wherein, the higher the sensitivity level, the more stringent the corresponding driving state judgment conditions are. A status determination module is used to determine the driver's driving status based on the sensitivity level; The second information acquisition module is used to acquire reference information about the vehicle when the driver's driving state is abnormal; the reference information is information associated with the vehicle acquired during the vehicle's operation; the reference information includes at least the vehicle's window status. The second project determination module is used to determine the abnormal state recovery project based on the reference information and the driving state. The second project execution module is used to control the vehicle to execute the abnormal state recovery project.

51. A vehicle dynamic control system, characterized in that, The system includes the vehicle control device as described in claims 49 and 50.

52. A vehicle, characterized in that, include: A processor and a memory, the memory being used to store a program; the processor being used to run the program to implement the vehicle control method as described in any one of claims 1-49.

53. An electronic device, characterized in that, It includes a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to perform the method of any one of claims 1-48.

54. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method of any one of claims 1-48.

55. A computer program product, characterized in that, The computer program product includes: computer program code, which, when run on a computer, causes the computer to perform the method described in any one of claims 1-48.

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