Automobile headrest adjusting method and device and automobile

Abstract

The invention is suitable for the technical field of automobile safety, and provides an automobile headrest adjusting method and device and an automobile. The method comprises the following steps: acquiring first driving data of a vehicle, information of each passenger in the vehicle and second driving data of a rear vehicle; according to the first driving data and the second driving data, predicting a collision risk level of collision between the own vehicle and the rear vehicle; when the collision risk level meets a first preset condition, predicting the head off-position distance of each passenger according to the first driving data and the information of the passengers; and for each passenger whose head off-position distance satisfies a second preset condition, adjusting a headrest of a seat corresponding to the passenger based on the collision risk level and the head off-position distance. According to the method, the headrest of the seat corresponding to the passenger can be adjusted in advance before the rear-end collision based on the collision risk level and the head off-position distance, so that the injury to the head and the neck of the passenger in the scene that the rear-end collision occurs after the passenger in the vehicle is braked and off-position is reduced.

Description

Technical Field

[0001] The present application relates to the field of automobile safety technology, and in particular to an automobile headrest adjustment method, device and vehicle. Background Art

[0002] A rear-end collision is a typical road traffic accident. When a rear-end collision occurs, the relative movement of the head, neck and upper torso of the occupants of the hit vehicle (the front vehicle) is too large or too fast, causing head and neck injuries, which is called whiplash.

[0003] In the related art, in order to reduce the damage to the head and neck of the front vehicle occupant, the active headrest design is mainly adopted, and the headrest of the vehicle seat is connected to the pressure plate in the seat back by a connecting rod. When the front vehicle is rear-ended by the rear vehicle, the body of the front vehicle occupant will hit the backrest due to the impact force, pushing the pressure plate backwards, thereby prompting the headrest to move forward, so that the headrest can support the head and neck of the front vehicle occupant before the head and neck are violently shaken, preventing or reducing the possibility of injury.

[0004] However, the above design usually only has an effective head and neck protection effect in rear-end collisions when the front vehicle is driving normally and the front vehicle occupants are in a normal sitting position. In the special case of a rear-end collision with the front vehicle due to sudden braking of the front vehicle under certain circumstances, since the front vehicle occupants have been out of position due to the previous braking and deceleration (that is, the head and neck of the front vehicle occupants are moved forward under the inertia of braking and deceleration, and the distance between the head and neck and the headrest is too large), the above design cannot provide effective support for the head and neck, resulting in excessive head and neck injuries. Summary of the invention

[0005] In view of this, the embodiments of the present application provide a car headrest adjustment method, device and vehicle to solve the technical problem that the head and neck of the occupant of the front vehicle cannot be effectively supported due to the brake being out of position and then rear-ending a collision, causing excessive damage to the head and neck.

[0006] In a first aspect, an embodiment of the present application provides a method for adjusting a vehicle headrest, comprising:

[0007] Obtaining the first driving data of the own vehicle, the information of each passenger in the own vehicle, and the second driving data of the following vehicle;

[0008] Predicting a collision risk level of a collision between the vehicle and a rear vehicle based on the first driving data and the second driving data;

[0009] When the collision risk level meets a first preset condition, predicting the head distance of each occupant according to the first driving data and the occupant information;

[0010] For each occupant whose head distance meets the second preset condition, the headrest of the seat corresponding to the occupant is adjusted based on the collision risk level and the head distance.

[0011] In a possible implementation manner of the first aspect, the first driving data includes a vehicle speed and a braking deceleration of the vehicle, and the second driving data includes a vehicle speed of a rear vehicle and a relative distance between the rear vehicle and the vehicle;

[0012] The predicting, based on the first driving data and the second driving data, the collision risk level of the vehicle and the following vehicle, includes:

[0013] Inputting the vehicle speed, the braking deceleration of the vehicle, the speed of the rear vehicle and the relative vehicle distance into the trained collision risk prediction model to obtain a collision risk score output by the collision risk prediction model;

[0014] Determining a collision risk level according to the collision risk score; wherein the collision risk level is positively correlated with the collision risk score;

[0015] The collision risk prediction model is trained based on different vehicle speeds, vehicle braking decelerations, and corresponding rear vehicle speeds, relative vehicle distances, and collision risk scores.

[0016] In a possible implementation manner of the first aspect, the occupant information includes a backrest angle of a seat corresponding to the occupant, a leg bending angle of the occupant, a height of the occupant, and a weight of the occupant;

[0017] The step of predicting the head distance of each occupant based on the first driving data and the occupant information includes:

[0018] Inputting the backrest angle, leg bending angle, height and weight of each occupant, vehicle speed and braking deceleration of the vehicle into the trained departure prediction model to obtain the head departure distance of each occupant output by the departure prediction model;

[0019] The out-of-position prediction model is obtained through training based on the backrest angle, leg bending angle, height, weight and head out-of-position distance corresponding to different occupants, as well as the vehicle speed and braking deceleration of the vehicle.

[0020] In a possible implementation manner of the first aspect, the first preset condition includes that the collision risk level is greater than or equal to a preset level, and the second preset condition includes that the head distance is greater than a preset distance threshold;

[0021] The step of adjusting the headrest of the seat corresponding to the occupant based on the collision risk level and the head separation distance includes:

[0022] Predicting the degree of injury to the occupant based on the collision risk level and the head separation distance;

[0023] According to the injury degree of the occupant, protective measures are determined, and based on the protective measures, the headrest of the occupant's corresponding seat is adjusted to minimize the injury to the occupant.

[0024] In a possible implementation of the first aspect, the headrest includes a headrest base, a front foam, and an air bag laid between the headrest base and the front foam; the seat also includes a backrest connected to the headrest, and a headrest rod, an air tube, and an air pump arranged in the backrest;

[0025] The headrest rod is a hollow tube, the first air hole of the headrest rod is connected to the air inlet of the air bag, and the second air hole of the headrest rod is connected to the air pump via an air pipe;

[0026] The step of adjusting the headrest of the seat corresponding to the occupant based on the protective measure includes:

[0027] Based on the protective measures, the air pump is controlled to inflate so that the headrest of the seat corresponding to the occupant is in the best protective state.

[0028] In a possible implementation of the first aspect, the protective measure includes moving the headrest forward;

[0029] The step of controlling the air pump to inflate based on the protective measures includes:

[0030] Determining the inflation time according to the correspondence between the head distance and the preset distance and the inflation time;

[0031] The air pump is controlled to inflate and last for the inflation time, so that the gas enters the air bag through the air pipe and the headrest rod, and the front foam is moved forward after the air bag is inflated.

[0032] In a possible implementation manner of the first aspect, before predicting the collision risk level of the vehicle and the following vehicle according to the first driving data and the second driving data, the method further includes:

[0033] If the relative vehicle distance is greater than a preset distance threshold, and / or the speed of the rear vehicle is less than the speed of the own vehicle and the speed difference with the speed of the own vehicle is greater than a preset speed difference threshold, the step of obtaining the first driving data of the own vehicle, the information of each occupant on the own vehicle, and the second driving data of the rear vehicle is re-executed.

[0034] In a possible implementation of the first aspect, the acquiring of first driving data of the vehicle, information of each occupant on the vehicle, and second driving data of the following vehicle includes:

[0035] Determine whether the vehicle is braking;

[0036] If the vehicle brakes, the first driving data of the vehicle, the information of each passenger in the vehicle, and the second driving data of the following vehicle are obtained.

[0037] In a second aspect, an embodiment of the present application provides a vehicle headrest adjustment device, comprising:

[0038] The acquisition module is used to acquire the first driving data of the own vehicle, the information of each passenger in the own vehicle, and the second driving data of the following vehicle.

[0039] The first prediction module is used to predict the collision risk level of the vehicle colliding with the rear vehicle based on the first driving data and the second driving data.

[0040] The second prediction module is used to predict the head distance of each occupant according to the first driving data and the occupant information when the collision risk level meets the first preset condition.

[0041] The adjustment module is used to adjust the headrest of the seat corresponding to each occupant whose head distance meets the second preset condition based on the collision risk level and the head distance.

[0042] In a third aspect, an embodiment of the present application provides a vehicle, comprising a memory and a controller, wherein the memory stores a computer program that can be run on the controller, and when the controller executes the computer program, the vehicle headrest adjustment method as described in any one of the first aspects is implemented.

[0043] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a controller, the vehicle headrest adjustment method as described in any one of the first aspects is implemented.

[0044] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0045] The automobile headrest adjustment method, device and vehicle provided in the embodiments of the present application predict the collision risk level of a collision between the own vehicle and the rear vehicle based on the first driving data and the second driving data, and predict the occupant's head distance when the collision risk level meets the first preset condition based on the first driving data and the occupant's information, so that for the occupant whose head distance meets the second preset condition, based on the collision risk level and the head distance, the headrest of the occupant's corresponding seat is adjusted in advance before a rear-end collision occurs, thereby reducing the injury to the occupant's head and neck in a scenario where a rear-end collision occurs after the occupant in the own vehicle is out of position due to braking, and also reducing the injury to the occupant's head and neck in an ordinary rear-end collision scenario.

[0046] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 It is a schematic diagram of a normal riding posture and a brake-out posture of an occupant;

[0049] Figure 2 It is a schematic diagram of an application scenario provided by an embodiment of the present application;

[0050] Figure 3 It is a flowchart of a method for adjusting a car headrest provided in one embodiment of the present application;

[0051] Figure 4 is a flow chart of a method for adjusting a vehicle headrest provided in another embodiment of the present application;

[0052] Figure 5 is a structural schematic diagram of a seat provided in one embodiment of the present application;

[0053] Figure 6 It is a structural schematic diagram of a vehicle headrest adjustment device provided by an embodiment of the present application;

[0054] Figure 7 It is a schematic diagram of the structure of a vehicle provided in one embodiment of the present application. DETAILED DESCRIPTION

[0055] The present application is described more clearly below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the effects of the present application, but are not intended to limit the present application in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present application. These all fall within the scope of protection of the present application.

[0056] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0057] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0058] In the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and should not be understood as indicating or implying relative importance.

[0059] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0060] In addition, the “plurality” mentioned in the embodiments of the present application should be interpreted as two or more.

[0061] In a rear-end collision, if the front vehicle suddenly brakes due to some circumstances, the rear vehicle collides with the front vehicle from behind. Since the occupants of the front vehicle have been displaced by the previous braking deceleration (refer to Figure 1 , Figure 1 The figure shows the brake-out posture of the occupant when the vehicle brakes suddenly, and the normal sitting posture when the vehicle is driving normally). The active headrest design in the related art cannot effectively support the head and neck of the occupant in the front vehicle, causing excessive damage to the head and neck.

[0062] In order to meet the idea of ​​effectively supporting the head and neck of the occupant of the front vehicle and reducing injuries to the head and neck in the scenario of a rear-end collision after the occupant of the front vehicle is out of position due to braking, the inventor has discovered through research that the collision risk level of a collision between the own vehicle (i.e., the front vehicle) and the rear vehicle can be predicted based on the driving data of the own vehicle (i.e., the front vehicle) and the rear vehicle, and the occupant's head distance can be predicted based on the driving data of the own vehicle and the information of the occupants in the own vehicle. Therefore, for the occupant whose head distance meets the preset conditions, the headrest of the occupant's corresponding seat can be adjusted in advance before a rear-end collision occurs based on the collision risk level and the head distance, so as to reduce injuries to the head and neck of the occupant of the front vehicle in the scenario of a rear-end collision after the occupant of the front vehicle is out of position due to braking.

[0063] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0064] First reference Figure 2 , Figure 2 The application scenario of the present application is schematically illustrated, in which the vehicle, a controller and a following vehicle are included.

[0065] The controller obtains first driving data of the own vehicle, information of each occupant in the own vehicle, and second driving data of the rear vehicle, and predicts a collision risk level of the own vehicle and the rear vehicle based on the first driving data and the second driving data; when the collision risk level meets a first preset condition, the controller predicts a head distance of each occupant based on the first driving data and the occupant's information; then, for each occupant whose head distance meets the second preset condition, the controller adjusts the headrest of the occupant's corresponding seat based on the collision risk level and the head distance.

[0066] Among them, the first driving data may include the vehicle speed and the braking deceleration of the vehicle, the second driving data may include the speed of the rear vehicle and the relative distance between the rear vehicle and the vehicle, and the occupant information may include the backrest angle of the corresponding seat of the occupant, the leg bending angle of the occupant, the height of the occupant and the weight of the occupant.

[0067] Correspondingly, the application scenario may also include radars, cameras, vehicle speed sensors, vehicle speed acceleration sensors, seat state sensors, weight sensors, and in-vehicle cameras (not shown) that are respectively connected to the controller for communication. Among them, radars such as millimeter-wave radars and cameras such as binocular cameras can be set on the vehicle, and the radar and / or camera are used to obtain the speed of the following vehicle and the relative distance between the following vehicle and the vehicle. The vehicle speed sensor and the vehicle speed acceleration sensor can be set on the vehicle, and are used to obtain the speed of the vehicle and the braking deceleration of the vehicle, respectively. The seat state sensor, the weight sensor, and the in-vehicle camera can be set on the vehicle, and the seat state sensor is used to obtain the backrest angle of the corresponding seat of the occupant, the weight sensor is used to obtain the weight of the occupant, and the in-vehicle camera is used to obtain the leg bending angle of the occupant and the height of the occupant.

[0068] Of course, other methods may also be used to obtain the first driving data, the second driving data and the passenger information, which are not specifically limited here.

[0069] Optionally, the controller may be an on-board controller, an off-board controller, or a combination of an on-board controller and an off-board controller, and may be a hardware device with data storage, processing, and analysis functions. Here, the controller is an on-board controller as an example, and may be an electronic control unit (ECU) or the like.

[0070] Combine the following Figure 2 ,refer to Figure 3-Figure 4A method for adjusting a vehicle headrest provided according to an exemplary embodiment of the present application will be described.

[0071] Figure 3 FIG. 1 is a flow chart of a method for adjusting a vehicle headrest provided in an embodiment of the present application. Figure 3 As shown, the method in the embodiment of the present application may include:

[0072] Step 301: Acquire first driving data of the vehicle, information of each passenger in the vehicle, and second driving data of the following vehicle.

[0073] As can be seen from the foregoing, in this embodiment, the first driving data can be obtained through the vehicle speed sensor and the vehicle speed acceleration sensor, the second driving data can be obtained through the radar and / or the camera, and the occupant information can be obtained through the seat state sensor, the weight sensor and the in-vehicle camera. Among them, the seat state sensor and the weight sensor can be set corresponding to each seat, and for each occupant, especially the front row occupant of the vehicle, the information of each occupant can be obtained through the seat state sensor and the weight sensor corresponding to the seat corresponding to each occupant.

[0074] Optionally, in this embodiment, the rear vehicle refers to a rear vehicle in the same lane or an adjacent lane as the vehicle. When there are multiple rear vehicles, the second driving data of each rear vehicle is obtained.

[0075] Step 302: predicting a collision risk level between the vehicle and the following vehicle based on the first driving data and the second driving data.

[0076] As can be seen from the foregoing, the first driving data may include the vehicle speed and the braking deceleration of the vehicle, and the second driving data may include the speed of the rear vehicle and the relative distance between the rear vehicle and the vehicle. The collision risk level may include high risk, medium risk and low risk.

[0077] In some embodiments, when predicting the collision risk level of a collision between a vehicle and a rear vehicle, the vehicle speed, braking deceleration, speed and relative distance of the vehicle can be input into a trained collision risk prediction model to obtain a collision risk score output by the collision risk prediction model. Thereafter, the collision risk level is determined based on the collision risk score, and the collision risk level is positively correlated with the collision risk score.

[0078] In this embodiment, the current driving environment and braking of the vehicle are considered to construct a collision risk prediction model, which inputs the vehicle speed, braking deceleration, rear vehicle speed and relative vehicle distance, and outputs a collision risk score. The collision risk prediction model can be an artificial intelligence model, which is trained based on different vehicle speeds, braking decelerations, and corresponding rear vehicle speeds, relative vehicle distances and collision risk scores.

[0079] Optionally, the collision risk level is positively correlated with the collision risk score. For example, high risk corresponds to a collision risk score greater than 60 points and less than or equal to 100 points, medium risk corresponds to a collision risk score greater than 40 points and less than or equal to 60 points, and low risk corresponds to a collision risk score greater than or equal to 0 points and less than or equal to 40 points.

[0080] It should be noted that when training the collision risk prediction model, the training set also includes training samples in which the braking deceleration of the own vehicle is 0. That is, the collision risk prediction model is not only applicable to the scenario in which the occupants of the front vehicle first brake out of position and then rear-end collision occurs, but also to the scenario in which the front vehicle does not brake and rear-end collision occurs (ordinary rear-end collision).

[0081] In some embodiments, before predicting the collision risk level of the self-vehicle and the rear vehicle, the step of obtaining the first driving data of the self-vehicle, the information of each occupant on the self-vehicle, and the second driving data of the rear vehicle may be re-executed when the relative vehicle distance is greater than a preset distance threshold and / or the speed of the rear vehicle is less than the speed of the self-vehicle and the speed difference with the speed of the self-vehicle is greater than a preset speed difference threshold. Otherwise, the step of predicting the collision risk level of the self-vehicle and the rear vehicle is performed based on the first driving data and the second driving data.

[0082] In this embodiment, the relative vehicle distance and the speed difference between the rear vehicle speed and the vehicle speed can be judged first. When the relative vehicle distance is greater than a preset distance threshold, and / or the rear vehicle speed is less than the vehicle speed and the speed difference between the rear vehicle speed and the vehicle speed is greater than a preset speed difference threshold, it can be considered that there is no risk of rear-end collision or the risk of rear-end collision is low. In this way, by simply judging whether to execute step 302, the calculation task of the controller is reduced.

[0083] Step 303: When the collision risk level meets the first preset condition, predict the head distance of each occupant based on the first driving data and the occupant information.

[0084] As can be seen from the foregoing, the passenger information may include the backrest angle of the corresponding seat of the passenger, the leg bending angle of the passenger, the height of the passenger and the weight of the passenger. The first preset condition includes that the collision risk level is greater than or equal to the preset level, and the preset level may be a medium risk, that is, when the collision risk level is a high risk or a medium risk, it is considered that the vehicle and the following vehicle have a risk of rear-end collision at this time. When the collision risk level is a low risk, that is, the collision risk level does not meet the first preset condition, it is considered that there is no risk of rear-end collision at this time or the risk of rear-end collision is low, and the steps of obtaining the first driving data of the vehicle, the information of each passenger on the vehicle, and the second driving data of the following vehicle are re-executed.

[0085] Optionally, an occupant of the self-vehicle may be dislocated due to the braking and deceleration of the self-vehicle, and the occupant's head dislocation distance refers to the distance between the occupant's head and neck and the headrest of the occupant's corresponding seat.

[0086] It should be noted that, since there may be multiple rear vehicles located in different lanes, after obtaining the corresponding collision risk level for each rear vehicle, it is determined whether the highest collision risk level meets the first preset condition.

[0087] In some embodiments, when predicting the head distance of each occupant, the backrest angle, leg bending angle, height and weight of each occupant, as well as the vehicle speed and braking deceleration can be input into the trained departure prediction model to obtain the head distance of each occupant output by the departure prediction model.

[0088] Exemplarily, considering the driving data of the vehicle, the posture and height and weight of the occupants, a departure prediction model is constructed, which inputs the backrest angle of the seat corresponding to the occupant, the leg bending angle of the occupant, the height and weight of the occupant, as well as the vehicle speed and the braking deceleration of the vehicle, and outputs the distance of the occupant's head from the position. The departure prediction model can be an artificial intelligence model, such as a deep learning model, which realizes efficient processing and prediction of complex data by setting a multi-layer neural network structure including a variable layer, a hidden layer and a target layer. The departure prediction model is obtained based on the backrest angle corresponding to different occupants, the leg bending angle of the occupant, the height, the weight of the occupant and the distance of the occupant's head from the position, as well as the vehicle speed and the braking deceleration of the vehicle. During the training process, the model parameters can be optimized by constructing a loss function to improve the accuracy of the prediction.

[0089] Optionally, the out-of-position prediction model can be trained and set in the controller before the vehicle leaves the factory. During the driving process of the vehicle, this embodiment predicts the head out-of-position distance of each occupant based on the trained out-of-position prediction model and the first driving data and the occupant's information.

[0090] Alternatively, the departure prediction model can be trained and set in the controller before the vehicle leaves the factory. After the vehicle leaves the factory, the controller can also obtain the backrest angle, leg bending angle, height, weight and head departure distance corresponding to different occupants in the vehicle, as well as the vehicle speed and braking deceleration, and train and adjust the departure prediction model to obtain a departure prediction model associated with the occupant characteristics in the vehicle, thereby improving the accuracy of the departure prediction model.

[0091] In this way, based on the trained departure prediction model, the distance of head departure of each occupant due to vehicle braking can be predicted.

[0092] It should be noted that when training the out-of-position prediction model, the training set also includes training samples in which the braking deceleration of the own vehicle is 0. The label corresponding to the training sample can be the distance between the occupant's head and neck and the headrest when a rear-end collision occurs without braking. That is, the out-of-position prediction model is not only applicable to the scenario in which a rear-end collision occurs after the occupant of the front vehicle is out of position due to braking, but also to the scenario in which a rear-end collision occurs without braking (ordinary rear-end collision).

[0093] Step 304: For each occupant whose head distance meets the second preset condition, adjust the headrest of the seat corresponding to the occupant based on the collision risk level and the head distance.

[0094] In this embodiment, the second preset condition includes that the head distance is greater than a preset distance threshold, and the preset distance threshold can be set as needed. For an occupant whose head distance does not meet the second preset condition, the headrest of the seat corresponding to the occupant can be adjusted according to fixed measures, such as moving the headrest forward by a fixed distance, or not adjusting the headrest of the seat corresponding to the occupant. Here, the forward movement of the headrest refers to the movement of the headrest towards the occupant.

[0095] In some embodiments, for each occupant whose head distance meets the second preset condition, when adjusting the headrest of the occupant's corresponding seat, the occupant's injury degree can be predicted based on the collision risk level and the head distance. Thereafter, according to the occupant's injury degree, protective measures are determined, and based on the protective measures, the headrest of the occupant's corresponding seat is adjusted to minimize the occupant's injury.

[0096] In this embodiment, an injury degree prediction model can be constructed, which can be an artificial intelligence model, which inputs the collision risk level and the head separation distance, and outputs the occupant injury degree such as mild, moderate or severe. The injury degree prediction model can be trained based on different collision risk levels, head separation distances, and corresponding occupant injury degrees.

[0097] In this way, protective measures are determined based on the predicted degree of injury to the occupant. For example, for mild injuries, the protective measures may be to control the support wings arranged on both sides of the seat headrest to pop out forward to support the head and neck of the occupant, or the protective measures may be to adjust the headrest to move forward a first distance. For moderate injuries, the protective measures may be to adjust the headrest to move forward a second distance. For severe injuries, the protective measures may be to adjust the headrest to move forward a third distance and control the support wings to pop out forward at the same time. The third distance is greater than the second distance, and the second distance is greater than the first distance. In this embodiment, support wings that can pop out forward to support the head and neck of the occupant are arranged on both sides of the seat headrest, and the headrest of the seat can move forward.

[0098] In this way, for each occupant whose head is out of position at a distance that meets the second preset condition, a corresponding protective measure is determined according to the corresponding occupant injury degree, and then based on the corresponding protective measure, the headrest of the seat corresponding to the occupant is adjusted in advance before a rear-end collision occurs, so that the occupant injury is minimized in the scenario of a rear-end collision after the occupant on the vehicle is out of position due to braking, and at the same time, the occupant injury can also be minimized in the scenario of a normal rear-end collision. In this way, the method provided in this embodiment can be applied to the scenario of a rear-end collision after the occupant on the vehicle is out of position due to braking, and can also be applied to the scenario of a normal rear-end collision.

[0099] The automobile headrest adjustment method provided in the embodiment of the present application predicts the collision risk level of the collision between the own vehicle and the rear vehicle based on the first driving data and the second driving data, and predicts the head distance of the occupant based on the first driving data and the occupant's information when the collision risk level meets the first preset condition, so that for the occupant whose head distance meets the second preset condition, based on the collision risk level and the head distance, the headrest of the occupant's corresponding seat is adjusted in advance before the rear-end collision occurs, thereby reducing the damage to the occupant's head and neck in the scenario of a rear-end collision caused by the occupant in the own vehicle being out of position due to braking, and also reducing the damage to the occupant's head and neck in ordinary rear-end collision scenarios.

[0100] In some embodiments, before obtaining the first driving data of the vehicle, the information of each passenger on the vehicle, and the second driving data of the following vehicle, it is also possible to determine whether the vehicle is braking. If the vehicle is braking, the first driving data of the vehicle, the information of each passenger on the vehicle, and the second driving data of the following vehicle are obtained. If the bicycle is not braking, the step of determining whether the vehicle is braking is re-executed after a preset time period.

[0101] In this embodiment, the first driving data of the vehicle, the information of each occupant on the vehicle, and the second driving data of the rear vehicle can be obtained only after the braking of the vehicle is detected. That is, only for the rear-end collision scenario where the occupant on the vehicle is out of position due to braking, the headrest of the corresponding seat of the occupant is adjusted by the automobile headrest adjustment method provided in the embodiment of the present application. When the braking of the vehicle is not detected, it indicates that the vehicle is driving normally without braking, and there is no occupant out of position or the occupant is slightly out of position. At this time, other methods such as active headrest design can be used to adjust the headrest of the corresponding seat of the occupant.

[0102] In addition, consideration should be given to further accurately adjusting the headrests of the corresponding seats of the occupants to reduce injuries to the heads and necks of the occupants in the event of a rear-end collision after the occupants are out of position due to braking. The seat structure can also be improved by adding structures such as the headrest base, front foam, air bags, headrest rods, air pipes and air pumps, and by controlling the inflation of the air pump, the headrests of the seats can be in the best protective state.

[0103] Figure 4 It is a flow chart of a method for adjusting a car headrest provided in another embodiment of the present application. Figure 5 Schematic diagram of the structure of a seat provided by an embodiment of the present application. Figure 5 As shown, the headrest in this embodiment includes a headrest base 52 , a front foam 53 , and an air bag 54 laid between the headrest base 52 and the front foam 53 .

[0104] The seat further includes a backrest 51 connected to the headrest, and a headrest rod 55, an air pipe 56 and an air pump 57 arranged in the backrest 51. The headrest rod 55 is a hollow tube, the first air hole of the headrest rod 55 is connected to the air inlet of the air bag 54, and the second air hole of the headrest rod 55 is connected to the air pump 57 via the air pipe 56.

[0105] Optionally, the headrest base 52, the front foam 53 and the surface of the air bag 54 are covered by a seat skin to form a complete headrest shape.

[0106] like Figure 4 As shown, the method in the embodiment of the present application may include:

[0107] Step 401: Acquire first driving data of the own vehicle, information of each passenger in the own vehicle, and second driving data of the following vehicle.

[0108] Step 402: predicting a collision risk level between the vehicle and the following vehicle based on the first driving data and the second driving data.

[0109] Step 403: When the collision risk level meets the first preset condition, predict the head distance of each occupant based on the first driving data and the occupant information.

[0110] Step 404: For each occupant whose head distance meets the second preset condition, predict the occupant's injury degree based on the collision risk level and the head distance, and determine protective measures according to the occupant's injury degree.

[0111] The specific implementation process and principle of steps 401 to 404 in this embodiment can refer to the relevant description in the above-mentioned embodiment, which will not be repeated here.

[0112] Step 405: Based on the protective measures, control the air pump to inflate so that the headrest of the seat corresponding to the occupant is in the best protective state.

[0113] In this embodiment, the protection measure may include moving the headrest forward. The headrest base is an immovable component, the front foam is a movable component, and the airbag is made of elastic material. When the inflator pumps air, the gas enters the airbag through the air tube and the headrest rod, causing the airbag to expand and thus pushing the movable front foam forward to reduce the distance between the occupant's head and neck and the headrest. When the inflator pumps air out, the gas is drawn out of the airbag, and the airbag contracts, causing the movable front foam to move backward and fit with the headrest base, and the headrest returns to its original state. The size of the airbag can be controlled by controlling the inflation time of the inflator for the airbag, and further the distance that the front foam moves forward can be controlled. After the rear-end collision ends, the inflator can be controlled to pump air to evacuate the gas from the airbag to achieve the reuse of the headrest.

[0114] In some embodiments, based on the protection measure, when controlling the inflator to inflate, the inflation time can be determined according to the head displacement distance and the corresponding relationship between the preset distance and the inflation time. Then, the inflator is controlled to inflate and continue to inflate for the inflation time, so that the gas enters the airbag through the air tube and the headrest rod, and after the airbag is inflated, the front foam is moved forward.

[0115] Optionally, referring to Figure 5 , the headrest rod 55 can specifically be in a "冂" shape, composed of a crossbar and two vertical rods 58 connected to the crossbar. An air hole 59 is provided on the crossbar, which serves as the first air hole of the headrest rod 55 to connect the air inlet of the airbag 54, and the lower ports of the two vertical rods 58 serve as the second air holes of the headrest rod 55 to be connected to the inflator 57 through the air tube 56.

[0116] Exemplarily, after determining the inflation time, the inflator is controlled to inflate and continue to inflate for the inflation time so that the gas enters the airbag. After the airbag is inflated, the front foam is moved forward by a target distance, and the target distance can be equal to the head displacement distance. For example, if the calculated head displacement distance is 50 millimeters, then according to the corresponding relationship between the preset distance and the inflation time, the inflation time corresponding to 50 millimeters is determined. Then, the inflator is controlled to inflate and continue to inflate for the inflation time, so that after the airbag is inflated and expanded, it pushes the front foam forward by 50 millimeters, realizing the pre-adjustment of the headrest of the corresponding seat of the occupant before a rear-end collision and reducing the injury to the head and neck of the front vehicle occupant in the scenario of a rear-end collision after the front vehicle occupant is displaced due to braking.

[0117] In this embodiment, the seat structure is improved by adding a headrest base, front foam, airbag, headrest rod, air pipe and air pump, and by controlling the air pump to inflate, the headrest of the seat is in the best protection state before a rear-end collision occurs. The headrest of the seat corresponding to the occupant can be further accurately adjusted to reduce the damage to the head and neck of the occupant in the scenario of a rear-end collision after the occupant is out of position due to braking. At the same time, compared with the disadvantage of the active design in the related art that it cannot be reused, the headrest in this embodiment can be repeatedly moved forward and backward, that is, it can be reused.

[0118] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0119] Figure 6 Schematic diagram of the structure of the automobile headrest adjustment device provided by an embodiment of the present application. Figure 6 As shown, the automobile headrest adjustment device provided in this embodiment may include: an acquisition module 601 , a first prediction module 602 , a second prediction module 603 and an adjustment module 604 .

[0120] The acquisition module 601 is used to acquire the first driving data of the vehicle, the information of each passenger in the vehicle, and the second driving data of the following vehicle.

[0121] The first prediction module 602 is used to predict the collision risk level of the vehicle and the following vehicle according to the first driving data and the second driving data.

[0122] The second prediction module 603 is used to predict the head distance of each occupant according to the first driving data and the occupant information when the collision risk level meets the first preset condition.

[0123] The adjustment module 604 is configured to adjust the headrest of the seat corresponding to each occupant whose head distance meets the second preset condition based on the collision risk level and the head distance.

[0124] Optionally, the first driving data includes the vehicle speed and the braking deceleration of the vehicle, and the second driving data includes the speed of the rear vehicle and the relative distance between the rear vehicle and the vehicle; the first prediction module 602 is further used for:

[0125] Inputting the vehicle speed, the braking deceleration of the vehicle, the speed of the rear vehicle and the relative vehicle distance into the trained collision risk prediction model to obtain a collision risk score output by the collision risk prediction model;

[0126] Determining a collision risk level according to the collision risk score; wherein the collision risk level is positively correlated with the collision risk score;

[0127] The collision risk prediction model is trained based on different vehicle speeds, vehicle braking decelerations, and corresponding rear vehicle speeds, relative vehicle distances, and collision risk scores.

[0128] Optionally, the passenger information includes the backrest angle of the seat corresponding to the passenger, the leg bending angle of the passenger, the height of the passenger and the weight of the passenger; the second prediction module 603 is further used for:

[0129] Inputting the backrest angle, leg bending angle, height and weight of each occupant, vehicle speed and braking deceleration of the vehicle into the trained departure prediction model to obtain the head departure distance of each occupant output by the departure prediction model;

[0130] The out-of-position prediction model is obtained through training based on the backrest angle, leg bending angle, height, weight and head out-of-position distance corresponding to different occupants, as well as the vehicle speed and braking deceleration of the vehicle.

[0131] Optionally, the first preset condition includes that the collision risk level is greater than or equal to a preset level, and the second preset condition includes that the head distance is greater than a preset distance threshold; the adjustment module 604 is further used to:

[0132] Predicting the degree of injury to the occupant based on the collision risk level and the head separation distance;

[0133] According to the injury degree of the occupant, protective measures are determined, and based on the protective measures, the headrest of the occupant's corresponding seat is adjusted to minimize the injury to the occupant.

[0134] Optionally, the headrest includes a headrest base, front foam, and an air bag laid between the headrest base and the front foam; the seat also includes a backrest connected to the headrest, and a headrest rod, an air pipe and an air pump arranged in the backrest; the headrest rod is a hollow tube, the first air hole of the headrest rod is connected to the air inlet of the air bag, and the second air hole of the headrest rod is connected to the air pump via the air pipe; the adjustment module 604 is also used for:

[0135] Based on the protective measures, the air pump is controlled to inflate so that the headrest of the seat corresponding to the occupant is in the best protective state.

[0136] Optionally, the protective measure includes moving the headrest forward; the adjustment module 604 is further used for:

[0137] Determining the inflation time according to the correspondence between the head distance and the preset distance and the inflation time;

[0138] The air pump is controlled to inflate and last for the inflation time, so that the gas enters the air bag through the air pipe and the headrest rod, and the front foam is moved forward after the air bag is inflated.

[0139] Optionally, the acquisition module 601 is further used for:

[0140] If the relative vehicle distance is greater than a preset distance threshold, and / or the speed of the rear vehicle is less than the speed of the own vehicle and the speed difference with the speed of the own vehicle is greater than a preset speed difference threshold, the step of obtaining the first driving data of the own vehicle, the information of each occupant on the own vehicle, and the second driving data of the rear vehicle is re-executed.

[0141] Optionally, the acquisition module 601 is further used for:

[0142] Determine whether the vehicle is braking;

[0143] If the vehicle brakes, the first driving data of the vehicle, the information of each passenger in the vehicle, and the second driving data of the following vehicle are obtained.

[0144] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0145] Figure 7 Schematic diagram of the structure of a vehicle provided by an embodiment of the present application. Figure 7 As shown, the vehicle 700 of this embodiment includes: a controller 710 and a memory 720, wherein the memory 720 stores a computer program 721 that can be run on the controller 710. When the controller 710 executes the computer program 721, the steps in any of the above-mentioned method embodiments are implemented, for example Figure 3 Alternatively, the controller 710 implements the functions of each module / unit in the above-mentioned device embodiments when executing the computer program 721, for example Figure 6 Functions of modules 601 to 604 are shown.

[0146] Exemplarily, the computer program 721 may be divided into one or more modules / units, one or more modules / units are stored in the memory 720, and executed by the controller 710 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 721 in the vehicle 700.

[0147] Those skilled in the art will understand that Figure 7These are merely examples of vehicles and do not constitute a limitation on the vehicle, and may include more or fewer components than those shown in the figure, or a combination of certain components, or different components, such as input and output devices, network access devices, buses, etc.

[0148] The controller 710 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0149] The memory 720 may be an internal storage unit of the vehicle, such as a hard disk or memory of the vehicle, or an external storage device of the vehicle, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the vehicle. The above-mentioned memory 720 may also include both an internal storage unit of the vehicle and an external storage device. The above-mentioned memory 720 is used to store computer programs and other programs and data required by the vehicle. The memory 720 may also be used to temporarily store data that has been output or is to be output.

[0150] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0151] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a controller, the above-mentioned vehicle headrest adjustment method is implemented.

[0152] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0153] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0154] In the embodiments provided by the present invention, it should be understood that the disclosed devices / vehicles and methods can be implemented in other ways. For example, the device / vehicle embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0155] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0156] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0157] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the controller. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0158] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for adjusting a car headrest, characterized in that: include: Obtaining the first driving data of the own vehicle, the information of each passenger in the own vehicle, and the second driving data of the following vehicle; Predicting a collision risk level of a collision between the vehicle and a rear vehicle based on the first driving data and the second driving data; When the collision risk level meets a first preset condition, predicting the head distance of each occupant according to the first driving data and the occupant information; For each occupant whose head distance meets the second preset condition, the headrest of the seat corresponding to the occupant is adjusted based on the collision risk level and the head distance.

2. The method for adjusting the automobile headrest according to claim 1, characterized in that: The first driving data includes the vehicle speed and the braking deceleration of the vehicle, and the second driving data includes the vehicle speed of the rear vehicle and the relative distance between the rear vehicle and the vehicle. The predicting, based on the first driving data and the second driving data, the collision risk level of the vehicle and the following vehicle, includes: Inputting the vehicle speed, the braking deceleration of the vehicle, the speed of the rear vehicle and the relative vehicle distance into the trained collision risk prediction model to obtain a collision risk score output by the collision risk prediction model; Determining a collision risk level according to the collision risk score; wherein the collision risk level is positively correlated with the collision risk score; The collision risk prediction model is trained based on different vehicle speeds, vehicle braking decelerations, and corresponding rear vehicle speeds, relative vehicle distances, and collision risk scores.

3. The method for adjusting the automobile headrest according to claim 2, characterized in that: The passenger information includes the seat back angle of the passenger, the leg bending angle of the passenger, the passenger's height and the passenger's weight; The step of predicting the head distance of each occupant based on the first driving data and the occupant information includes: Inputting the backrest angle, leg bending angle, height and weight of each occupant, vehicle speed and braking deceleration of the vehicle into the trained departure prediction model to obtain the head departure distance of each occupant output by the departure prediction model; The out-of-position prediction model is obtained through training based on the backrest angle, leg bending angle, height, weight and head out-of-position distance corresponding to different occupants, as well as the vehicle speed and braking deceleration of the vehicle.

4. The method for adjusting the automobile headrest according to any one of claims 1 to 3, characterized in that: The first preset condition includes that the collision risk level is greater than or equal to the preset level, and the second preset condition includes that the head distance is greater than a preset distance threshold; The step of adjusting the headrest of the seat corresponding to the occupant based on the collision risk level and the head separation distance includes: Predicting the degree of injury to the occupant based on the collision risk level and the head separation distance; According to the injury degree of the occupant, protective measures are determined, and based on the protective measures, the headrest of the occupant's corresponding seat is adjusted to minimize the injury to the occupant.

5. The method for adjusting the automobile headrest according to claim 4, characterized in that: The headrest includes a headrest base, a front foam, and an air bag laid between the headrest base and the front foam; the seat also includes a backrest connected to the headrest, and a headrest rod, an air pipe and an air pump arranged in the backrest; The headrest rod is a hollow tube, the first air hole of the headrest rod is connected to the air inlet of the air bag, and the second air hole of the headrest rod is connected to the air pump via an air pipe; The step of adjusting the headrest of the seat corresponding to the occupant based on the protective measure includes: Based on the protective measures, the air pump is controlled to inflate so that the headrest of the seat corresponding to the occupant is in the best protective state.

6. The method for adjusting the automobile headrest according to claim 5, characterized in that: The protective measure includes moving the head restraint forward; The step of controlling the air pump to inflate based on the protective measures includes: Determining the inflation time according to the correspondence between the head distance and the preset distance and the inflation time; The air pump is controlled to inflate and last for the inflation time, so that the gas enters the air bag through the air pipe and the headrest rod, and the front foam is moved forward after the air bag is inflated.

7. The method for adjusting the automobile headrest according to claim 2, characterized in that: Before predicting the collision risk level of the vehicle and the following vehicle according to the first driving data and the second driving data, the method further includes: If the relative vehicle distance is greater than a preset distance threshold, and / or the speed of the rear vehicle is less than the speed of the own vehicle and the speed difference with the speed of the own vehicle is greater than a preset speed difference threshold, the step of obtaining the first driving data of the own vehicle, the information of each occupant on the own vehicle, and the second driving data of the rear vehicle is re-executed.

8. The method for adjusting the automobile headrest according to any one of claims 1 to 3, characterized in that: The obtaining of the first driving data of the vehicle, the information of each passenger in the vehicle, and the second driving data of the following vehicle includes: Determine whether the vehicle is braking; If the vehicle brakes, the first driving data of the vehicle, the information of each passenger in the vehicle, and the second driving data of the following vehicle are obtained.

9. An automobile headrest adjustment device, characterized in that: include: An acquisition module, used to acquire first driving data of the vehicle, information of each passenger in the vehicle, and second driving data of the following vehicle; A first prediction module, configured to predict a collision risk level of a collision between the vehicle and a rear vehicle based on the first driving data and the second driving data; A second prediction module, configured to predict the head separation distance of each occupant according to the first driving data and the occupant information when the collision risk level meets a first preset condition; The adjustment module is used to adjust the headrest of the seat corresponding to each occupant whose head distance meets the second preset condition based on the collision risk level and the head distance.

10. A vehicle, comprising a memory and a controller, wherein the memory stores a computer program that can be run on the controller, characterized in that: When the controller executes the computer program, the vehicle headrest adjustment method according to any one of claims 1 to 8 is implemented.

Images