Vehicle control method and device, function pointing method, wearable device, and medium

Abstract

A vehicle control method applied to a vehicle end, the vehicle control method comprising: in response to selection information, receiving perception data collected by a wearable device, the perception data comprising image data and / or inertial measurement data; the selection information being used to determine at least one target adjustable structure of the vehicle; determining an adjustment parameter of the at least one target adjustable structure according to the perception data; performing an adjustment process, the adjustment process comprising: adjusting the corresponding target adjustable structure according to the adjustment parameter; or outputting guidance information corresponding to the adjustment parameter to guide a user to adjust the target adjustable structure. The present disclosure also provides a vehicle control device, a wearable device and a computer readable storage medium.

Description

Technical Field

[0001] This disclosure belongs to the field of vehicle control technology, specifically relating to a vehicle control method and device, an on-board function guidance method, a wearable device, and a computer-readable storage medium. Background Technology

[0002] With the development of automotive intelligence, personalized and comfortable configurations of the vehicle cabin are increasingly becoming key to user experience. Among them, the adjustable features of the driver's seat, steering wheel, and rearview mirrors directly affect the driver's seating comfort, ease of operation, and driving safety. Summary of the Invention

[0003] This disclosure provides a vehicle control method applied to a vehicle, the vehicle control method comprising:

[0004] In response to selection information, the wearable device receives perception data, including image data and / or inertial measurement data; the selection information is used to determine at least one target adjustable structure of the vehicle.

[0005] The adjustment parameters of the at least one target adjustable structure are determined based on the sensing data;

[0006] The adjustment process includes: adjusting the corresponding target adjustable structure according to the adjustment parameters; or outputting guidance information corresponding to the adjustment parameters to guide the user to adjust the target adjustable structure.

[0007] In some embodiments, the selection information is further used to determine the adjustment mode of the target adjustable structure;

[0008] When the adjustment mode is the first adjustment mode, the adjustment process includes: adjusting the corresponding target adjustable structure according to the adjustment parameters; when the adjustment mode is the second adjustment mode, the adjustment process includes: controlling the wearable device to output guidance information corresponding to the adjustment parameters.

[0009] In some embodiments, the at least one target adjustable structure includes a seat and / or a steering wheel, and the adjustment parameters of the target adjustable structure include at least adjustment distance and adjustment direction;

[0010] The step of determining the adjustment parameters of the at least one target adjustable structure based on the sensing data includes:

[0011] Based on the perceived data, the current state parameters of the user's body parts associated with the target adjustable structure are determined;

[0012] The adjustment parameters of the target adjustable structure are determined based on the difference between the current state parameters of the user's body parts and the preset target state parameters.

[0013] In some embodiments, the step of determining the current state parameters of a user's body part associated with the target adjustable structure based on the perceived data includes:

[0014] Based on the perceived data and preset vehicle calibration parameters, the pose of the wearable device is determined;

[0015] Based on the pose of the wearable device and the human body model, determine the position and / or orientation of the user's body parts in the vehicle coordinate system.

[0016] In some embodiments, the at least one target adjustable structure includes a seat, and the current state parameters of the user's body part include at least one of the following: the current normal distance between the user's eye position and the windshield, the current height of the projection of the user's eye position onto the windshield, and the angle of the user's torso;

[0017] Determining the adjustment parameter based on the difference between the current state parameter of the user's body part and the preset target state parameter includes at least one of the following steps:

[0018] The amount of horizontal adjustment of the seat is determined based on the difference between the current normal distance and the target normal distance between the user's eye position and the windshield.

[0019] The amount of vertical adjustment of the seat is determined based on the difference between the current height of the projection of the user's eye position on the windshield and the target height.

[0020] The adjustment parameters for the seat back angle are determined based on the difference between the angle of the user's torso and the target angle.

[0021] In some embodiments, the angle of the user's torso is obtained as follows:

[0022] Based on the determined positions of the user's hip and shoulder points, calculate the torso vector connecting the hip and shoulder points;

[0023] The angle of the user's torso is determined based on the angle between the torso vector and the reference direction.

[0024] In some embodiments, the at least one target adjustable structure includes a steering wheel.

[0025] The current state parameters of the user's body parts include: the relative positional relationship between the user's shoulder point and the center of the steering wheel;

[0026] The determination of the current state parameters of the user's body parts includes:

[0027] Based on the user's shoulder point position and the preset steering wheel center position, at least one of the following is determined: the straight-line distance between the shoulder point position and the steering wheel center, the height difference, and the arm bending angle.

[0028] In some embodiments, the perceived data includes image data; when the adjustment mode is the second adjustment mode and the at least one target adjustable structure includes a seat, the step of determining the adjustment parameters of the at least one target adjustable structure based on the perceived data includes:

[0029] Determine whether the image data collected by the wearable device contains a first preset area of ​​the vehicle engine hood; if not, determine the vertical adjustment amount of the seat.

[0030] The step of controlling the wearable device to output guidance information includes: based on the vertical adjustment of the seat, controlling the wearable device to output first guidance information, the first guidance information being used to guide the user to adjust the position of the seat in the vertical direction.

[0031] In some embodiments, the vehicle control method further includes:

[0032] After controlling the wearable device to output the first guidance information, the distance between the user's head and the roof of the car is obtained based on the perception data collected by the wearable device;

[0033] When the distance between the user's head and the roof of the vehicle is less than a preset safe distance, the wearable device is controlled to output a stop message.

[0034] In some embodiments, the step of determining the adjustment parameter based on the sensed data further includes:

[0035] The wearable device is controlled to output prompt information to prompt the user to perform a first action and a second action, including leaning the torso forward, in sequence;

[0036] When the user performs the first action and the second action, the first distance and the second distance between the user's knee and the fixed reference object inside the vehicle are obtained based on the sensing data collected by the wearable device.

[0037] The amount of adjustment for the seat's fore-aft position is determined based on the first distance and the second distance.

[0038] In some embodiments, the at least one target adjustable structure includes a rearview mirror, and the perception data includes image data;

[0039] The step of determining the adjustment parameters of the at least one target adjustable structure based on the sensing data includes:

[0040] Based on the image data collected by the wearable device, the mirror image presented in the rearview mirror is obtained;

[0041] The content of the mirror image is compared with the features of a preset reference image, and the adjustment parameters of the rearview mirror are determined based on the comparison results.

[0042] In some embodiments, the reference image features include: a preset area of ​​the vehicle body;

[0043] The content of the mirror image is compared with the features of a preset reference image, and the adjustment parameters of the rearview mirror are determined based on the comparison results, including:

[0044] Determine whether the mirror image contains a preset area of ​​the vehicle body. If not, determine the adjustment parameters of the rearview mirror so that the mirror image presented after the rearview mirror is adjusted based on the adjustment parameters contains the preset area of ​​the vehicle body.

[0045] In some embodiments, prior to the step of receiving sensing data collected by the wearable device, the method further includes:

[0046] Identify the user currently wearing the wearable device;

[0047] Based on the user's identity, query whether there are preset parameters stored that correspond to the user's identity and the selection information;

[0048] If the preset parameter is found, then the preset parameter is used as the adjustment parameter, and the adjustment process is executed;

[0049] If the preset parameters are not found, then the step of receiving the sensing data collected by the wearable device is executed.

[0050] In some embodiments, after performing the adjustment process, the method further includes:

[0051] In response to the adjustment completion confirmation signal, the adjustment parameters used by each of the target adjustable structures during the adjustment process are acquired;

[0052] The adjustment parameters are used as preset parameters and stored in association with the user identity and the selection information.

[0053] In some embodiments, it also includes:

[0054] Receive target image data including the area of ​​the vehicle's windshield, collected by the wearable device;

[0055] The target image data is analyzed to determine the fog obstruction index, which characterizes the degree of fogging of the windshield.

[0056] Based on the fog obstruction index, the target airflow of the vehicle air conditioning system is determined, and the operation of the vehicle air conditioning system is controlled based on the target airflow.

[0057] In some embodiments, the step of determining the target airflow of the vehicle air conditioning system based on the fog obstruction index, and controlling the vehicle air conditioning system to output air based on the target airflow, includes:

[0058] When the fog obstruction index is in the first index range, the air conditioning system is controlled to operate at the first air volume.

[0059] When the fog obstruction index is in a second index range that is higher than the first index range, the air conditioning system is controlled to operate at a second air volume that is greater than the first air volume.

[0060] In some embodiments, the step of analyzing the target image data to determine a fog obstruction index characterizing the degree of fogging on the windshield includes:

[0061] Extract the region of interest (ROI) from the windshield area in the target image data;

[0062] Determine the image contrast score, edge sharpness score, and light scattering score of the region of interest;

[0063] Based on the current ambient brightness, assign weights to the image contrast score, edge sharpness score, and light scattering score;

[0064] The fog occlusion index is determined based on the image contrast score, edge sharpness score, and light scattering score, and their respective weights.

[0065] In some embodiments, the at least one target adjustable structure includes a rearview mirror; the vehicle control method further includes:

[0066] After the adjustment process is completed, based on the perception data including the image of the rearview mirror collected by the wearable device, environmental information of the side and rear of the vehicle is obtained.

[0067] Based on the environmental information, determine whether there are other vehicles or pedestrians gradually approaching within a preset range around the vehicle;

[0068] If present, a reminder message will be displayed on the vehicle's display screen.

[0069] In some embodiments, the method further includes:

[0070] Based on the sensing data collected by the wearable device, the horizontal turning angle of the user's head is detected;

[0071] When the user's head turns horizontally within the preset rearview mirror viewing angle range for a duration exceeding the preset time, the step of obtaining environmental information from the side and rear of the vehicle is executed.

[0072] This disclosure also provides a vehicle-mounted function guidance method, applied to wearable devices, wherein the vehicle-mounted function guidance method includes:

[0073] In response to function guidance commands, acquire target images inside the vehicle;

[0074] Identify the target objects contained in the target image;

[0075] Retrieve auxiliary information about the target object from the database and output it.

[0076] In some embodiments, identifying a target object contained in the target image includes:

[0077] When the target image contains a central control screen, identify the abnormal icons in the central control screen and use them as the target object;

[0078] When the target image contains physical buttons and directional gestures, the physical button pointed to by the gesture is identified and the target object is identified.

[0079] This disclosure also provides a vehicle control device, including a communication module, a memory, and a processor, wherein the communication module is used for communication connection with a wearable device;

[0080] The memory stores one or more programs, which, when executed by the processor, enable the processor to implement the vehicle control method described above.

[0081] This disclosure also provides a wearable device, comprising: a memory and a processor, the memory storing one or more programs; when the one or more programs are executed by the processor, the processor enables the processor to implement the above-described vehicle function guidance method.

[0082] This disclosure also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method described above is implemented. Attached Figure Description

[0083] Figure 1A This is a schematic diagram of a vehicle control method provided in some embodiments of this disclosure.

[0084] Figure 1BThis is another schematic diagram of the vehicle control method provided in some embodiments of this disclosure.

[0085] Figure 2 This is a schematic diagram of a vehicle control method provided in some other embodiments of this disclosure.

[0086] Figure 3 This is a schematic diagram illustrating the specific implementation of step S20 in Example 1 of this disclosure.

[0087] Figure 4 This is a schematic diagram illustrating the specific implementation of step S20 in Example 2 of this disclosure.

[0088] Figure 5 This is a schematic diagram illustrating the specific implementation of step S20 in Example 4 of this disclosure.

[0089] Figure 6 This is a schematic diagram of the automatic defogging process provided in Example 5 of this disclosure.

[0090] Figure 7 This is a schematic diagram of the reminder process when the driving direction is about to change, as provided in Example 6 of this disclosure.

[0091] Figure 8 This is a schematic diagram of the in-vehicle function guidance method provided in an embodiment of this disclosure.

[0092] Figure 9 A schematic diagram of a vehicle control device provided in an embodiment of this disclosure.

[0093] Figure 10 A schematic diagram of a wearable device provided in an embodiment of this disclosure. Detailed Implementation

[0094] To enable those skilled in the art to better understand the technical solutions of this disclosure, the disclosure will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0095] Unless otherwise defined, the technical or scientific terms used in this disclosure shall have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this disclosure do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this disclosure are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to such processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this disclosure are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” in this disclosure refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can indicate: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," "third," etc., used in this disclosure are merely to distinguish similar objects and do not represent a specific ordering of objects.

[0096] This disclosure provides a vehicle control method applied to a vehicle. Figure 1A This is a schematic diagram of a vehicle control method provided in some embodiments of this disclosure, such as... Figure 1A As shown, the vehicle control method includes: in response to selection information (i.e., upon receiving selection information), executing steps S10 to S30:

[0097] S10. Receive sensing data collected by the wearable device, including image data and / or inertial measurement data; select information to determine at least one target adjustable structure of the vehicle.

[0098] Among them, an adjustable target structure refers to a structure whose position, posture, or angle can be adjusted. For example, an adjustable target structure can be a seat, steering wheel, or rearview mirror (including interior and exterior rearview mirrors).

[0099] In one example, the source of the selection information could be the user. For instance, the user could actively input selection information into the vehicle control system or wearable device via voice, touch, gestures, or physical buttons. The user could say, "Adjust the seat automatically" or "Adjust the steering wheel for me."

[0100] In another example, the vehicle or wearable device can automatically generate selection information upon detecting a specific preset event, without requiring manual input from the user. For instance, when the vehicle's seat sensors detect that a user has sat down and the vehicle and wearable device establish a connection, selection information can be automatically generated to instruct the vehicle to automatically adjust the seat, steering wheel, and rearview mirrors.

[0101] For example, wearable devices can be smart glasses.

[0102] S20. Determine the adjustment parameters of at least one target adjustable structure based on the sensing data.

[0103] In this context, adjustment parameters refer to control quantities determined based on calculations and analysis of sensor data collected by wearable devices, used to instruct how to physically adjust one or more "target adjustable structures." For example, for a seat, adjustment parameters may include position adjustment parameters (e.g., adjustment distance and adjustment direction) and backrest angle adjustment parameters. As another example, for a steering wheel, adjustment parameters may include fore-aft adjustment distance and vertical adjustment distance.

[0104] S30. Execute the adjustment process, which includes: adjusting the corresponding target adjustable structure according to the adjustment parameters; or outputting guidance information corresponding to the adjustment parameters to guide the user to manually adjust the target adjustable structure.

[0105] When the adjustment mode is the first adjustment mode, the vehicle control system can directly drive the corresponding actuator (such as a motor) according to the calculated adjustment parameters to automatically complete the physical adjustment of the target adjustable structure (such as the seat height, steering wheel position, and rearview mirror angle), thereby providing users with the ultimate convenience experience.

[0106] When the adjustment mode is the second adjustment mode, the vehicle control system does not directly control the hardware, but controls the wearable device to convert the "adjustment parameters" into "guidance information" that the user can understand (for example, a voice prompt "please move the seat forward 20 centimeters") and output it, thereby guiding the user to complete the adjustment by himself, which takes into account both flexibility and user preference.

[0107] In this embodiment of the disclosure, the vehicle can automatically adjust the target adjustable structure of the vehicle based on the perception information collected by the wearable device, or output guidance information to guide the user to make adjustments. Compared with the method of adjustment based on personal feeling, the vehicle control method in this disclosure can provide a more objective and accurate adjustment method, thereby improving driving safety and comfort.

[0108] In some embodiments, the selection information is further used to determine the adjustment mode of the target adjustable structure, which is one of a first adjustment mode and a second adjustment mode. For example, the first adjustment mode represents an automatic adjustment mode for the target adjustable structure, and the second adjustment mode represents a manual adjustment mode for the target adjustable structure.

[0109] In one example, users can actively input selection information into the vehicle control system or wearable device via voice, touch, gestures, or physical buttons. If a user says "Adjust the seat automatically" or "Adjust the steering wheel for me," the selection information indicates that the automatic adjustment mode has been entered. Alternatively, if a user says "Teach me how to adjust the seat" or "Tell me how to adjust it," the selection information indicates that the manual adjustment mode has been entered.

[0110] In another example, the vehicle or wearable device can automatically generate selection information upon detecting a specific preset event, without requiring manual input from the user. For instance, when the vehicle's seat sensor detects that a user has sat down and the vehicle and wearable device establish a connection, selection information can be automatically generated to instruct the vehicle to automatically adjust the seat, steering wheel, and rearview mirrors.

[0111] In some embodiments, such as Figure 1B As shown, when the adjustment mode is the first adjustment mode, the above adjustment process may include: adjusting the corresponding target adjustable structure according to the adjustment parameters; when the adjustment mode is the second adjustment mode, the adjustment process may include: outputting guidance information corresponding to the adjustment parameters. Specifically, when outputting guidance information, the vehicle end may directly output the guidance information through an output device (such as an audio playback device or a display screen), or the vehicle end may control the wearable device to output guidance information.

[0112] Figure 2 This is a schematic diagram of a vehicle control method provided in other embodiments of this disclosure, such as... Figure 2 As shown, the vehicle control method includes steps S01~S02 performed before step S10:

[0113] S01. Identify the user currently wearing the wearable device.

[0114] S02. Based on the user's identity, check whether there are preset parameters corresponding to the user's identity and selection information. If preset parameters are found, use them as adjustment parameters and proceed directly to step S30 to execute the adjustment process. If no preset parameters are found, proceed to step S10.

[0115] Step S02 can be either querying the local database to see if the preset parameters exist, or querying the cloud database.

[0116] Accordingly, after completing the adjustment process (whether automatic or manual) based on the adjustment parameters, the vehicle control method may also include:

[0117] S40. In response to the adjustment completion confirmation signal, acquire the adjustment parameters used by each target adjustable structure during the adjustment process.

[0118] S50. The adjustment parameters are set as preset parameters and stored in association with the user's identity and selection information, so that when the same user sends the same selection information again, the appropriate adjustment parameters can be quickly retrieved.

[0119] exist Figure 2 In the embodiment shown, after adjusting the target adjustable structure, the adjustment parameters, selection information and user identity can be associated and stored. When the user wants to adjust the same target adjustable structure again, the vehicle can quickly realize automatic or manual adjustment with the assistance of the user, and the adjustment parameters used in the adjustment process are more in line with the user's needs.

[0120] In some embodiments, at least one target adjustable structure includes a seat and / or a steering wheel, and the adjustment parameters of the target adjustable structure include at least adjustment distance and adjustment direction.

[0121] The vehicle control method in the embodiments of this disclosure will be described below with reference to different examples.

[0122] Figure 3 This is a schematic diagram illustrating a specific implementation of step S20 provided in one example of the present disclosure, as follows: Figure 3 As shown, when the target adjustable structure is a seat, step S20 includes steps S21 to S22:

[0123] S21. Based on the perception data, determine the current state parameters of the user's body parts associated with the target adjustable structure.

[0124] S22. Determine the adjustment parameters of the target adjustable structure based on the difference between the current state parameters of the user's body parts and the preset target state parameters.

[0125] Here, "user body parts associated with the target adjustable structure" refers to specific parts of the driver's body that are directly related to the function and comfort of a target adjustable structure, on which the adjustment method is determined. For example, the purpose of seat adjustment is to optimize the driver's seating posture. Therefore, the body parts directly associated with it include: eye position (e.g., in this embodiment, the midpoint between the eyes is used as the eye position), shoulder point (i.e., the connection point between the shoulder and arm), and hip point (i.e., the contact point between the user's hip and the seat). The eye position determines the forward field of vision, and it also determines the fore-aft position and height of the seat that need to be adjusted. For example, the suitability of the seat height can be determined by calculating the projection height of the eye position on the windshield plane. The shoulder point and hip point together determine the driver's torso posture. The angle formed by the torso vector connecting the shoulder point and hip point can be used to determine and adjust the angle of the seat back to ensure comfortable support and a reasonable operating posture.

[0126] The current state parameters of the user's body parts may include at least one of the following: current position, current orientation, and current angle. Correspondingly, the target state parameters include at least one of the following: target position, target orientation, and target angle. The current position may be a relative position to a reference point inside the vehicle.

[0127] In some embodiments, step S21 may specifically include steps S211 to S212:

[0128] S211. Based on the perceived data and preset vehicle calibration parameters, determine the pose of the wearable device in the vehicle coordinate system. This pose may include its position and orientation.

[0129] For example, in step S211, the 6-DOF pose of the wearable device in the camera coordinate system can be calculated based on the image data of the wearable device and the inertial measurement data obtained by the inertial measurement unit (IMU); then, using the pre-calibrated vehicle parameters, the 6-DOF pose is transformed into a unified vehicle coordinate system through coordinate transformation, thereby obtaining the position and orientation of the wearable device in the vehicle coordinate system.

[0130] The 6-DOF pose includes a rotation matrix and a translation vector. The rotation matrix describes the orientation of the wearable device, and the translation vector describes its position in space. Vehicle calibration parameters include the coordinates of fixed markers within the vehicle in the vehicle coordinate system, used to achieve coordinate transformation from the camera coordinate system to the vehicle coordinate system.

[0131] For example, smart glasses (as an example of wearable devices) acquire continuous image data (visual features) through their camera and high-frequency acceleration and angular velocity data through their inertial measurement unit. Using SLAM (Simultaneous Localization and Mapping) or VIO (Visual Inertial Odometry) algorithms, they calculate and output their own 6-DOF pose (rotation matrix R) in real time. C Translation vector t C This pose is typically expressed in the camera coordinate system of the smart glasses (the origin of the camera coordinate system is at the optical center of the front-facing camera of the glasses, the positive Z-axis is the forward direction, the positive Y-axis is the leftward direction, and the positive X-axis is the upward direction), in the following form:

[0132]

[0133] Where C represents the camera coordinate system, R C SO(3) is a 3x3 matrix. SO(3) is a special orthogonal group in mathematics, which specifically refers to the set of all "pure rotation matrices in three-dimensional space". express It is a valid matrix describing 3D rotation, used to describe the orientation of the wearable device in the vehicle coordinate system. C It is a vector with 3 components. It represents a three-dimensional real vector space.

[0134] To use the aforementioned 6-DOF pose within the vehicle space, pre-calibrated vehicle parameters (e.g., the known coordinates of fixed markers inside the vehicle in the vehicle coordinate system) can be used to transform the pose from the camera coordinate system to a unified vehicle coordinate system V (the origin of the vehicle coordinate system V is at the intersection of the vehicle's centerline and the front axle; the positive X-axis is forward, the positive Y-axis is leftward, and the positive Z-axis is upward), as follows:

[0135]

[0136] It is a 3x3 rotation matrix. It represents how to rotate a vector in the camera coordinate system to align it with the vehicle coordinate system. It is a coordinate system with three components, used to describe the position of the camera's optical center in the vehicle coordinate system.

[0137] S212. Based on the pose of the wearable device and the preset human body model, determine the position and / or posture of the user's body parts associated with the target adjustable structure in the vehicle coordinate system.

[0138] Here, posture refers to the orientation and angle of a body part. Orientation refers to the direction the body part is facing, and angle refers to the angle the body part is in (e.g., the bending angle of the torso). For "point"-shaped parts (e.g., eyes, shoulder points, and hip points), the position of the eyes can be obtained in step S212; for "body"-shaped or "axis"-shaped parts (e.g., torso, arms, head), the position and posture of the body part can be obtained in step S212.

[0139] Once the pose of the smart glasses is determined, the coordinates of the eye position in the vehicle coordinate system can be obtained. :

[0140]

[0141] in, This represents a fixed spatial offset from the origin of the camera coordinate system to the eye position.

[0142] Furthermore, after determining the eye position, the coordinates of other body parts (such as shoulder points and hip points) in the vehicle coordinate system can be obtained based on the preset human body model.

[0143] In some embodiments, when at least one target adjustable structure includes a seat, the current state parameters of the user's body parts may specifically include at least one of the following: the current normal distance between the user's eye position and the windshield. The current height of the user's eye position projected onto the windshield. The angle of the user's torso. The current state parameters of the user's body parts include the current normal distance between the user's eye position and the windshield. At that time, the target state parameters may include the target normal distance. (For example, between 0.6 and 0.7 m); when the current state parameters of the user's body parts include the current height of the projection of the user's eye position onto the windshield. At that time, the target state parameters may include the target height. When the current state parameter of a user's body part includes the angle of the user's torso, the target state parameter may include the target angle.

[0144] In this context, the windshield can be considered as a plane, and the current normal distance between the user's eye position and the windshield refers to the actual distance between the eye position and the windshield along the normal direction of the windshield.

[0145] Specifically, step S22 (determining the adjustment parameter) may include at least one of steps S221 to S223:

[0146] S221. Based on the difference between the current normal distance and the target normal distance between the user's eye position and the windshield, determine the adjustment amount of the seat in the horizontal direction. Specifically, the adjustment amount in the horizontal direction can be the adjustment amount of the seat in the fore-aft direction.

[0147] S222. Determine the vertical adjustment amount of the seat based on the difference between the current height of the projection of the user's eye position onto the windshield and the target height.

[0148] In this application, "vertical direction" refers to the direction of the Z-axis extension of the vehicle coordinate system, that is, the height direction of the vehicle.

[0149] S223. Determine the adjustment parameters of the seat back angle based on the difference between the angle of the user's torso and the target angle.

[0150] In one example, step S22 includes each of steps S221 to S223, namely, adjusting the seat in both the fore-aft and vertical directions, and adjusting the backrest angle, thereby maximizing driving safety and comfort. When step S22 includes each of steps S221 to S223, the order of S221 to S223 is not limited.

[0151] For example, when determining the adjustment parameters for the fore-and-aft position of the seat, the process is as follows:

[0152] First, obtain the geometric parameters required for the calculation: (1) Eye position coordinates, i.e., the above (2) The planar model of the windshield, which is based on preset vehicle calibration parameters and is usually described by plane equations. In one example, this plane is represented as passing through point p0 and having a normal vector of... A plane. Where p0 is the coordinates of a known reference point on the windshield plane. This is a unit normal vector perpendicular to the windshield plane and pointing inwards from the vehicle; this vector defines the positive direction of the windshield. Next, the current normal distance from the eye position to the windshield is calculated. As shown in the following formula:

[0153]

[0154] The current normal distance This determines whether the seat needs to be adjusted forward or backward.

[0155] Next, the calculated current normal distance is compared with the target normal distance, the difference is calculated, and based on this difference, the gain coefficient is adjusted using a preset horizontal adjustment factor. Calculate the amount of seat adjustment needed. For example, the amount of fore-and-aft adjustment. The following formula can be used for calculation:

[0156]

[0157] if A positive value indicates that the seat needs to be adjusted forward to reduce the distance; a negative value indicates that it needs to be adjusted backward.

[0158] Similarly, when determining the seat height adjustment parameters, first, determine the coordinates of the vertical projection point of the eye position on the windshield plane. :

[0159]

[0160] After obtaining the coordinates of the projection point, extract its coordinate components in the vertical direction (such as the z-axis) of the vehicle coordinate system. This value is the actual height of the projection of the eye position onto the windshield plane. :

[0161]

[0162] Next, the calculated actual height is compared with the target height, and the difference between the two is calculated. Based on this difference, the vertical adjustment gain coefficient is adjusted using a preset value. Calculate the amount Δz that the seat needs to be adjusted vertically, which can be expressed by the following formula:

[0163] .

[0164] For example, the target height can be 30% to 40% of the windshield height.

[0165] In this disclosure, the seat is adjusted forward and backward based on the difference between the actual normal distance from the eye position to the windshield and the target normal distance; the seat is adjusted vertically based on the difference between the actual height of the projection of the eye position onto the plane of the windshield and the target height, thereby ensuring that each driver can obtain the most ergonomic forward vision, greatly improving driving safety and comfort, and avoiding obstruction of vision or inconvenience of operation caused by improper seat position.

[0166] For example, the angle of the user's torso By connecting shoulder points and buttocks The formed torso vector The angle with a reference direction is used for calculation. The reference direction is, for example, the vertical direction, i.e., the vehicle's height direction. (Torso vector) :

[0167]

[0168] angle

[0169]

[0170] Seat backrest angle adjustment range As shown in the following formula:

[0171]

[0172] in, This is the gain coefficient for angle adjustment.

[0173] in, Through experimental or simulation calibration, the values ​​of each gain coefficient are determined to be around 1.0.

[0174] After determining the seat adjustment parameters, the seat is automatically adjusted according to the adjustment parameters (i.e., automatic adjustment), or guidance information is output according to the seat adjustment parameters to guide the user to adjust the seat (i.e., manual adjustment).

[0175] By measuring the user's actual torso angle in real time and comparing it with a target angle (e.g., 105°), this method can automatically adjust the seat back to the angle that provides optimal support for the driver's spine. This helps alleviate lower back fatigue during long drives, maintains a good driving posture, and thus further improves driving comfort and health.

[0176] Figure 4 This is a schematic diagram illustrating a specific implementation of step S20 provided in another example of this disclosure. Figure 4 In the provided example, the adjustment mode is the second adjustment mode, and at least one target adjustable structure includes a seat (i.e., the seat is manually adjusted), such as Figure 4 As shown, step S20 (determining the adjustment parameter) in the aforementioned embodiment may specifically include:

[0177] S201a. Determine whether the front view image data collected by the wearable device contains a first preset area of ​​the vehicle's engine hood, for example, the front end area of ​​the vehicle's engine hood.

[0178] S201b: If the image data does not contain the first preset area, determine the vertical adjustment amount of the seat. If it exists, there is no need to adjust the seat in the vertical direction, and the process can proceed directly to the next step S201c.

[0179] Accordingly, step S30, controlling the wearable device to output guidance information, includes: based on the amount of adjustment of the seat in the vertical direction, controlling the wearable device to output first guidance information, which is used to guide the user to adjust the position of the seat in the vertical direction, such as a voice prompt "The current field of vision is too low, please adjust the seat upwards".

[0180] This embodiment provides a simple, intuitive, and computationally intensive adjustment method. With clear guidance from the wearable device, users can quickly adjust the seat to a safe position that ensures basic forward visibility (being able to see the front of the car). This is especially suitable for novice drivers or when temporarily switching between different car models, effectively reducing the safety risk of poor visibility caused by a seat that is too low.

[0181] Furthermore, the vehicle control method may also include: after controlling the wearable device to output first guidance information, obtaining the distance between the user's head and the vehicle roof based on the perception data collected by the wearable device; and when the distance is less than a preset safe distance, controlling the wearable device to output a stop message. For example, a voice warning "Insufficient headroom, please stop adjusting" to prevent the user's head from hitting the vehicle roof.

[0182] In obtaining the distance between a user's head and the roof of the car, the position of the eyes can be determined based on the perception data of the wearable device, and the position of the top of the head can be determined by combining the human body model, thereby determining the distance between the head and the roof of the car.

[0183] Alternatively, in the example of manually adjusting the seat, step S20 (determining adjustment parameters) may also include:

[0184] S201c, Control the wearable device to output prompts to prompt the user to perform a first action and a second action in sequence, including leaning the torso forward (e.g., outputting the prompt "Please lower your head and bring your knees as close to the center console as possible").

[0185] S201d: When the user performs the first action, a first distance between the user's knee and a fixed reference object inside the vehicle (such as the lower edge of the center console) is obtained based on the sensing data from the wearable device (e.g., knee position recognition via image recognition). When the user performs the second action, a second distance is obtained in the same manner.

[0186] S201e: Based on the difference between the first distance and the second distance, determine the amount of seat adjustment in the fore-and-aft direction. For example, a small difference may mean the seat is too far forward and needs to be adjusted backward; a large difference may mean it needs to be adjusted forward. This adjustment amount is the adjustment parameter in this example and is used to generate the corresponding second guidance information.

[0187] In another example of this disclosure, the steering wheel can be adjusted (e.g., manually or automatically). Specifically, when at least one target adjustable structure includes a steering wheel, the current state parameters of the user's body parts can include the relative positional relationship between the user's shoulder point and the center of the steering wheel. Step S20 includes steps S21-S22.

[0188] S21. Based on the perception data, determine the current state parameters of the user's body parts associated with the target adjustable structure.

[0189] As described above, "the user's body part associated with the target adjustable structure" refers to a specific part of the driver's body that is directly related to the function and comfort of a target adjustable structure, and is used as the basis for determining how to adjust it. The purpose of steering wheel adjustment is to make the driver's arm operation comfortable and safe. Therefore, the directly associated body part can be the shoulder point. By adjusting the position of the steering wheel, the user's bending posture when using the steering wheel can be adjusted to avoid slouching or drooping arms.

[0190] Step S21 (the process of determining the current state parameters) may include: based on the user's shoulder point position. With respect to the preset steering wheel center coordinates W V Calculate the straight-line distance between the two. And the height difference in the vertical direction.

[0191] S22. Determine the adjustment parameters of the target adjustable structure based on the difference between the current state parameters of the user's body parts and the preset target state parameters.

[0192] Step S22 (the process of determining the adjustment parameters) may include: calculating the... The vertical height difference and the preset target distance Compare with the target height difference (e.g., the target height difference is less than 0.05 meters), and calculate the steering wheel adjustment amount in the forward and vertical directions based on the difference.

[0193] Among them, the amount of steering wheel adjustment forward and backward. As shown in the following formula:

[0194]

[0195] For example, The height is 0.6 times the user's arm length, which can be estimated based on human body parameters, such as 0.45 to 0.55 times the height. The calculation process for the user's height includes: obtaining the sitting height (i.e., the distance from the hip point to the top of the head) based on the sensor data from the wearable device and a preset human body model, and obtaining the height based on general human body proportions (e.g., the ratio of sitting height to height).

[0196] The amount of vertical adjustment of the steering wheel As shown in the following formula:

[0197]

[0198] in, and This is the preset gain coefficient.

[0199] By adjusting the fore-and-aft position and vertical position (i.e., height) of the steering wheel, the straight-line distance from the driver's shoulder to the steering wheel, as well as the vertical distance between the shoulder and the steering wheel, can be adjusted to allow the driver's arms to bend naturally at approximately 120°. This is the most effortless and responsive operating posture. Simultaneously, controlling a small height difference avoids cramming the arms or letting the hands hang down. Together, these factors ensure that the driver can quickly, forcefully, and precisely control the steering wheel in emergency situations, significantly improving active safety.

[0200] In yet another example of this disclosure, at least one target adjustable structure includes a rearview mirror, which can be an interior rearview mirror or an exterior rearview mirror. The perception data collected by the wearable device includes at least image data.

[0201] Figure 5 This is a schematic diagram illustrating a specific implementation of step S20 provided in yet another example of this disclosure. For example... Figure 5 As shown, step S20 includes S202a~S202b:

[0202] S202a. Based on the image data collected by the wearable device, obtain the mirror image presented in the rearview mirror. The rearview mirror can be a reflective mirror, and the mirror image it presents can be a reflected image; alternatively, the rearview mirror can also have a display function, and the mirror image it presents can be a displayed image.

[0203] S202b: Compare the content of the mirror image with the features of the preset reference image, and determine the adjustment parameters of the rearview mirror based on the comparison results.

[0204] The reference image features include a preset area of ​​the vehicle body. For example, for an exterior rearview mirror, the preset reference image feature could be a "preset area of ​​the vehicle body" (such as a door handle or part of the body's waistline). If the mirror image does not contain this area, the adjustment parameters of the rearview mirror (such as the yaw angle adjustment amount) are determined so that the adjusted mirror image can include this area. For an interior rearview mirror, the reference image feature could be a "specific location of the vehicle's rear window area." If this location does not appear in the mirror image, the pitch angle adjustment amount of the interior rearview mirror is determined so that the interior rearview mirror, after adjustment based on this pitch angle adjustment amount, can present the specific location of the rear window area.

[0205] Specifically, a specific location in the rear window area is recorded as... In order for the rearview mirror to allow the driver to see the specific positions mentioned above, the following is required: Regarding the normal vector of the rearview mirror Symmetry, mirror normal The following can be calculated:

[0206]

[0207] Will The pitch angle of the rearview mirror With yaw angle We can obtain:

[0208]

[0209] in, They are vectors Projected components on the three coordinate axes of the vehicle coordinate system.

[0210] After determining the adjustment parameters (i.e. angle adjustment amount) of the rearview mirror in step S20, the adjustment process in step S30 is executed.

[0211] exist Figure 5 In the example, the adjustment process of the rearview mirror no longer relies on the user's experience, but provides objective adjustment parameters based on the actual image presented by the rearview mirror, ensuring that each adjustment can achieve a standard and safe field of vision, eliminating blind spots caused by improper rearview mirror angles, and improving safety when changing lanes and reversing.

[0212] In some embodiments, the vehicle control method can also automate the defogging process. Figure 6 This is a schematic diagram illustrating an automatic defogging process provided in one example of this disclosure. For example, the automatic defogging process can begin automatically after the vehicle is started; or, for example, it can begin after receiving a defogging command input by the user; or, for example, the vehicle starts the automatic defogging process when the humidity detected by the humidity sensor reaches a certain threshold. Figure 6 As shown, the defogging process includes S61~S63:

[0213] S61. Receive target image data including the area of ​​the vehicle's windshield collected by the wearable device.

[0214] S62. Analyze the target image data to determine the fog obstruction index, which characterizes the degree of fogging on the windshield. The fog obstruction index characterizes the severity of fogging on the windshield; the smaller the fog obstruction index, the lower the degree of fogging; the larger the fog obstruction index, the higher the degree of fogging.

[0215] For example, step S62 may include:

[0216] S621. Extract the region of interest (ROI) of the windshield area in the target image data.

[0217] In step S621, the ROI (Region of Interest) algorithm is used to identify the windshield area in the image captured by the wearable device, and image interference from the center console, steering wheel, and interior is removed. The focus is on high-frequency details of the road surface, such as lane lines, the outline of the vehicle in front, and streetlights.

[0218] S622. Determine the image contrast score, edge sharpness score, and light scattering score for the region of interest.

[0219] The image contrast score represents the overall contrast of an image. Fog can cause a significant decrease in image contrast, so image contrast can reflect the severity of fogging to some extent.

[0220] In this context, fog acts like a low-pass filter, narrowing the image histogram distribution and reducing the standard deviation of pixel values. The heavier the fog, the grayer the image, and the more concentrated the grayscale values. Therefore, the root mean square contrast ratio or grayscale variance can be used to calculate the contrast score.

[0221] First, calculate the standard deviation of pixel grayscale values ​​in the region of interest using the following formula:

[0222]

[0223] Where N is the total number of pixels in the region of interest. It is the pixel value of the i-th pixel. It is the average gray level.

[0224] Secondly, normalization is performed: a clear threshold is set. and a fogging threshold Contrast score is defined as follows: :

[0225]

[0226] The contrast score should be controlled between 0 and 1. The closer the result is to 1, the lower the contrast and the greater the fogging.

[0227] Edge sharpness score is the degree of edge sharpness of high-frequency details (such as lane lines) in the region of interest. If the edges of the lane lines become blurry or broken, it indicates that there is water fog interference on the windshield.

[0228] For example, the calculation process for edge sharpness score is as follows:

[0229] First, the high-frequency information of each pixel is calculated using the Sobel operator, specifically including: (1) applying the Sobel operator to the image and calculating the gradient magnitude of each pixel. (2) Calculate the average gradient parameter using the following formula:

[0230]

[0231] Secondly, the edge sharpness score is calculated according to the following formula. :

[0232]

[0233] Here, E1 is a preset sharpness threshold, and E2 is a preset fogging threshold. The edge sharpness score is controlled between 0 and 1. The closer it is to 1, the more blurred the edges are and the more severe the fogging is.

[0234] Light scattering score indicates the severity of halos or scattering on the windshield. When a vehicle is in motion, if the headlights of an oncoming vehicle produce abnormal halos or scattered spots on the windshield, it indicates the presence of tiny water droplets, i.e., fogging. This is because at night or in tunnels, point light sources (streetlights, vehicle headlights) experience the Tyndall effect on fogged glass, causing the brightness of pixels around the light source to spread in a Gaussian distribution.

[0235] For example, the calculation process for the light astigmatism score is as follows:

[0236] First, extract the brightest pixels in the image whose grayscale value is higher than the preset grayscale value (e.g., 240). The area formed by all the brightest pixels is the light source area, and the total number of brightest pixels is denoted as A1.

[0237] Next, detect the pixels surrounding the bright spot. If the brightness of surrounding pixels decreases slowly with a gentle gradient, it indicates a halo; if the brightness drops sharply with a steep gradient, it indicates a clear light source. Halo detection requires two conditions: a brightness value between 100 and 240 and the location being a neighborhood of the light source area. This neighborhood is based on the dynamic range of connected components. Starting from the edge of the light source area, neighboring pixels are checked outwards until the brightness drops below 100 or a dark area is encountered. The total number of pixels in the halo area is recorded as A2.

[0238] Next, the light scattering factors A1 / A2 are calculated, and the light scattering factors are mapped to 0-1 using the Sigmoid function to obtain the light scattering score. The larger the halo, the higher the score.

[0239]

[0240] in, .

[0241] S623. Assign weights to the image contrast score, edge sharpness score, and light scattering score based on the current ambient brightness.

[0242] For example, edge detection is most accurate during the day, while halo detection is ineffective. In this case, the weight corresponding to the image contrast score can be adjusted. Set to 0.4, 0.6, the weight corresponding to the light scattering score Set to 0. At night, edges are difficult to distinguish, and the fogging situation is mainly determined by light scattering score and contrast score. For example, the weight corresponding to the contrast score is... 0.3, the weight corresponding to the edge sharpness score. Set it to 0.2, and adjust the weights corresponding to the light scattering scores. Set it to 0.5.

[0243] S624. Determine the fog obstruction index based on the image contrast score, edge sharpness score, and light scattering score and their respective weights.

[0244] Specifically, the fog obscuration index F is calculated using the following formula:

[0245]

[0246] S63. Determine the target airflow of the vehicle air conditioning system based on the fog obstruction index, and control the operation of the vehicle air conditioning system based on the target airflow.

[0247] Step S63 includes: when the fog obscuration index is in the first index range, controlling the air conditioning system to operate at the first air volume; when the fog obscuration index is in the second index range higher than the first index range, controlling the air conditioning system to operate at the second air volume greater than the first air volume.

[0248] Compared to relying on the driver's experience to turn on the air conditioning, this embodiment can more directly and promptly detect the fogging status of the windshield that affects the driver's vision. By quantifying the degree of fogging through image analysis, the air conditioning system is controlled to perform graded and precise automatic defogging, quickly eliminating safety hazards while avoiding the high energy consumption and discomfort caused by excessive defogging.

[0249] In some embodiments, the vehicle control method may further include: after the target adjustable structure has been adjusted, a process of environmental perception and alerting based on a wearable device. Figure 7 This is a schematic diagram illustrating a notification process when the driving direction is about to change, as provided in one example of this disclosure. Figure 7 As shown, the reminder process includes steps S71 to S73 after adjusting the rearview mirror according to the adjustment parameters:

[0250] S71. Based on the perception data including the image of the rearview mirror collected by the wearable device, obtain environmental information of the side and rear of the vehicle.

[0251] In this embodiment, after adjusting the rearview mirror to its optimal field of vision, the vehicle control system can continuously or periodically collect the mirror image presented in the rearview mirror using a wearable device (such as smart glasses). This mirror image reflects the actual traffic conditions to the side and rear of the vehicle.

[0252] In some embodiments, the vehicle control method may further include: detecting the user's head horizontal turning angle based on the perception data collected by the wearable device; when the user's head horizontal turning angle falls into a preset rearview mirror viewing angle range and the duration exceeds a preset duration (e.g., 2 seconds or 3 seconds), determining that the user is observing the rearview mirror, and then executing step S71.

[0253] In this embodiment, the unique head posture perception capability of wearable devices is utilized, which can trigger S71 (i.e., the process of acquiring environmental information) when the user has not yet operated the turn signal and is only preparing to change lanes by observing the rearview mirror, thus giving the user more reaction time.

[0254] In some other embodiments, the triggering conditions for step S71 may also include other conditions, such as receiving a lane change or U-turn command input by the user, or determining that the vehicle is approaching the lane change or U-turn position based on navigation information. This disclosure does not limit this.

[0255] S72. Based on the surrounding environment information, determine whether there are other vehicles or pedestrians gradually approaching within a preset range around the vehicle.

[0256] S73. If present, display a reminder message on the vehicle's display screen or control the wearable device to output a reminder message.

[0257] The display screen can be a central control screen or an interior rearview mirror capable of displaying information. For example, the displayed alert information could be images of other vehicles or pedestrians approaching, with the brightness of these images exceeding that of other display elements on the screen; it could also be an audio message. Alternatively, if the wearable device is smart glasses, the alert information can also be displayed on the smart glasses, such as highlighting approaching vehicles using AR technology and overlaying text or icons as warnings; it could also be an audio message.

[0258] For example, step S74 may also be included: dynamically adjusting the alert information based on changes in the distance to the vehicle or pedestrian.

[0259] For example, the device can continuously monitor the distance between an approaching vehicle (or pedestrian) and the vehicle itself, and dynamically adjust the alert information based on changes in distance. For instance, when the distance between the approaching vehicle (or pedestrian) and the vehicle is below a first threshold, the wearable device outputs a warning message prohibiting operation. For example, the wearable device can verbally announce "Vehicle approaching from behind, U-turn prohibited" or "Please wait" to alert the driver that it is not suitable to change lanes or make a U-turn at this time. When the distance between the approaching vehicle (or pedestrian) and the vehicle is above a second threshold (the second threshold is greater than the first threshold), the wearable device outputs a warning message allowing operation. For example, it can verbally announce "Vehicle behind has moved away, U-turn is permitted" to indicate to the driver that the current environment is safe and the operation can proceed. The warning message disappears after the vehicle completes the U-turn or lane change operation.

[0260] This embodiment first uses wearable devices to sense data and adjust the rearview mirror to the optimal field of view. Then, the same wearable device collects the adjusted rearview mirror image for environmental perception and alerts. This "adjust first, monitor later" approach optimizes the rearview mirror's field of view before each drive, providing more reliable image input for subsequent lane-changing safety monitoring and significantly improving the safety of high-risk maneuvers such as lane changes and U-turns. Simultaneously, by outputting alerts through the wearable device, the driver avoids having to shift their gaze to the central control screen when changing lanes, further enhancing driving safety.

[0261] This disclosure also provides a method for guiding in-vehicle functions performed by a wearable device. Figure 8 This is a schematic diagram of the vehicle function guidance method provided in the embodiments of this disclosure, such as... Figure 8 As shown, the in-vehicle function guidance method includes steps S81 to S83:

[0262] S81, in response to function guidance commands, acquires target images inside the vehicle.

[0263] Function guidance commands can be input by the user into the wearable device via voice or keypad input. These commands are inquiries about the functions of internal vehicle components (such as icons on the central control screen or function buttons). For example, if a user wants to know the function of a specific internal component, they can input the corresponding function guidance command into the wearable device, which will then capture images of the vehicle's interior.

[0264] S82. Identify the target objects contained in the target image.

[0265] For example, when the target image contains a central control screen, an abnormal icon on the central control screen is identified and used as the target object. The abnormal icon can be an alarm icon.

[0266] When the target image contains physical buttons and directional gestures, the physical button pointed to by the gesture is identified and designated as the target object. The directional gesture can be a user's gesture; for example, if the target image contains an image of a user's finger pointing to a physical button, that physical button is then designated as the target object.

[0267] S83. Retrieve auxiliary description information of the target object from the database and output it. The auxiliary description information is used to describe the attributes of the target object and / or guide the user based on those attributes. Attributes may include at least one of the following: the target object's identity, function, status, and meaning.

[0268] The database can include a local database or a cloud database. The guidance information can be voice information, or, when the wearable device is smart glasses, it can be an AR image.

[0269] In one example, the wearable device responds to function guidance commands by acquiring target images of the vehicle interior (primarily the dashboard or center console area). After acquiring the target image, it undergoes preprocessing. This preprocessing includes high dynamic range (HDR) processing and reflection reduction. HDR processing ensures that bright areas are not overexposed and dark areas retain detail, providing a uniform image quality for subsequent recognition. Reflection reduction filters out interference noise such as reflections from the windshield into the displayed image, ensuring accurate target recognition.

[0270] Next, a lightweight, high-precision object detection model (such as YOLOv5) capable of recognizing thousands of car icons and buttons can be used to identify target objects in the preprocessed target image. After identifying the target object (specific icon / button) and its status, the wearable device queries and outputs auxiliary information associated with the target object from a local or cloud database. For example, when the target object is a fault icon on the dashboard, a voice announcement might be made: "The engine malfunction light is on. There is a non-emergency fault in the engine or emission system. The vehicle is still drivable, but please go to a repair shop for inspection as soon as possible."

[0271] In this embodiment, when a user wants to understand the function of a certain icon or physical button, the wearable device can provide the user with guidance information for the icon or physical button, so that the user does not need to check it on the central control screen, thus improving the intuitiveness and efficiency of human-computer interaction.

[0272] This disclosure also provides a navigation method applied to a wearable device, the method comprising:

[0273] S91. In response to the search command, obtain information on nearby points of interest.

[0274] The command can be a search command entered by the user via voice, such as "What are some good restaurants nearby?" or "Find me a parking lot nearby." Alternatively, the user can enter the search command into the vehicle's central control screen, which then sends the command to a wearable device.

[0275] S92, Push relevant information to the user and receive confirmation.

[0276] Wearable devices will present nearby parking information to users using augmented reality (AR) and / or voice input. For example, the location, distance, and number of available parking spaces of nearby parking lots can be overlaid on the lenses of smart glasses, and a voice announcement can be made such as, "There is a parking lot XX 200 meters ahead with 50 available spaces. Do you want to go there?"

[0277] S93. In response to the user's confirmation instruction (such as a voice reply "Okay, I'll go here" or a nod to confirm), set the parking lot as the navigation destination and start the vehicle navigation system.

[0278] S94. Upon arrival at the destination, automatically switch to pedestrian navigation mode.

[0279] Once the vehicle arrives at the target parking lot and parks, the wearable device automatically switches the navigation mode from driving navigation to walking navigation, guiding the user from the parking location to the final destination. For example, smart glasses can display walking route arrows on the lenses and announce via voice, "Please walk straight ahead for 100 meters, then turn right to enter the mall."

[0280] This example demonstrates seamless integration of driving and walking navigation, resolving navigation interruptions that often occur as the user approaches their destination. Users no longer need to retrieve their phones to set up walking navigation after parking; the wearable device automatically switches modes, enhancing the overall smoothness and convenience of the travel experience. Furthermore, by presenting parking information and walking directions in AR format through the wearable device, users don't need to look away from the central control screen or their phone, further improving operational safety and intuitiveness.

[0281] This disclosure also provides a vehicle control device, such as... Figure 9 As shown, the vehicle control device includes a communication module 10, a memory 103, and a processor 102. The communication module 10 is used for communication with wearable devices. The memory 103 stores one or more programs, which, when executed by the processor 102, enable the processor 102 to implement the vehicle control method.

[0282] The processor 102 is a device with data processing capabilities, including but not limited to a central processing unit 102 (CPU); the memory 103 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH).

[0283] This disclosure also provides a wearable device, such as... Figure 10 As shown, the wearable device includes a memory 203 and a processor 202, wherein the memory 203 stores one or more programs; when the one or more programs are executed by the processor 202, the processor 202 implements the above-described vehicle function guidance method.

[0284] Additionally, the wearable device may include a data acquisition module 201 for collecting sensory data. The data acquisition module may include a camera, inertial sensors, etc.

[0285] This disclosure also provides a computer-readable storage medium storing a computer program thereon. When the program is executed by a processor, it implements the vehicle control method or the vehicle function guidance method provided in this embodiment. To avoid repetition, the specific steps of the method will not be repeated here.

[0286] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0287] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as integrated circuits, such as application-specific integrated circuits (ASICs).

[0288] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0289] It is understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of this disclosure, and this disclosure is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this disclosure, and these modifications and improvements are also considered to be within the scope of protection of this disclosure.

Claims

1. A vehicle control method, applied to a vehicle, the vehicle control method comprising: In response to selection information, the device receives sensing data collected by the wearable device, the sensing data including image data and / or inertial measurement data; The selection information is used to determine at least one target adjustable structure of the vehicle; The adjustment parameters of the at least one target adjustable structure are determined based on the sensing data; The adjustment process includes: adjusting the corresponding target adjustable structure according to the adjustment parameters; Alternatively, it can output guidance information corresponding to the adjustment parameters to guide the user in adjusting the target adjustable structure.

2. The vehicle control method according to claim 1, wherein, The selection information is also used to determine the adjustment mode of the target adjustable structure; When the adjustment mode is the first adjustment mode, the adjustment process includes: adjusting the corresponding target adjustable structure according to the adjustment parameters; when the adjustment mode is the second adjustment mode, the adjustment process includes: controlling the wearable device to output guidance information corresponding to the adjustment parameters.

3. The vehicle control method according to claim 1, wherein, The at least one target adjustable structure includes a seat and / or a steering wheel, and the adjustment parameters of the target adjustable structure include at least adjustment distance and adjustment direction; The step of determining the adjustment parameters of the at least one target adjustable structure based on the sensing data includes: Based on the perceived data, the current state parameters of the user's body parts associated with the target adjustable structure are determined; The adjustment parameters of the target adjustable structure are determined based on the difference between the current state parameters of the user's body parts and the preset target state parameters.

4. The vehicle control method according to claim 3, wherein, The step of determining the current state parameters of the user's body parts associated with the target adjustable structure based on the perceived data includes: Based on the perceived data and preset vehicle calibration parameters, the pose of the wearable device is determined; Based on the pose of the wearable device and the human body model, determine the position and / or orientation of the user's body parts in the vehicle coordinate system.

5. The vehicle control method according to claim 3, wherein, The at least one target adjustable structure includes a seat, and the current state parameters of the user's body part include at least one of the following: the current normal distance between the user's eye position and the windshield, the current height of the projection of the user's eye position on the windshield, and the angle of the user's torso. Determining the adjustment parameter based on the difference between the current state parameter of the user's body part and the preset target state parameter includes at least one of the following steps: The amount of horizontal adjustment of the seat is determined based on the difference between the current normal distance and the target normal distance between the user's eye position and the windshield. The amount of vertical adjustment of the seat is determined based on the difference between the current height of the projection of the user's eye position on the windshield and the target height. The adjustment parameters for the seat back angle are determined based on the difference between the angle of the user's torso and the target angle.

6. The vehicle control method according to claim 5, wherein, The angle of the user's torso is obtained in the following way: Based on the determined positions of the user's hip and shoulder points, calculate the torso vector connecting the hip and shoulder points; The angle of the user's torso is determined based on the angle between the torso vector and the reference direction.

7. The vehicle control method according to claim 3, wherein, The at least one target adjustable structure includes a steering wheel. The current state parameters of the user's body parts include: the relative positional relationship between the user's shoulder point and the center of the steering wheel; The determination of the current state parameters of the user's body parts includes: Based on the user's shoulder point position and the preset steering wheel center position, at least one of the following is determined: the straight-line distance between the shoulder point position and the steering wheel center, the height difference, and the arm bending angle.

8. The vehicle control method according to claim 2, wherein, The sensed data includes image data; when the adjustment mode is the second adjustment mode and the at least one target adjustable structure includes a seat, the step of determining the adjustment parameters of the at least one target adjustable structure based on the sensed data includes: Determine whether the image data collected by the wearable device contains a first preset area of ​​the vehicle engine hood; if not, determine the vertical adjustment amount of the seat. The step of controlling the wearable device to output guidance information includes: based on the vertical adjustment of the seat, controlling the wearable device to output first guidance information, the first guidance information being used to guide the user to adjust the position of the seat in the vertical direction.

9. The vehicle control method according to claim 8, wherein, The vehicle control method further includes: After controlling the wearable device to output the first guidance information, the distance between the user's head and the roof of the car is obtained based on the perception data collected by the wearable device; When the distance between the user's head and the roof of the vehicle is less than a preset safe distance, the wearable device is controlled to output a stop message.

10. The vehicle control method according to claim 8, wherein, The step of determining the adjustment parameter based on the sensed data further includes: The wearable device is controlled to output prompt information to prompt the user to perform a first action and a second action, including leaning the torso forward, in sequence; When the user performs the first action and the second action, the first distance and the second distance between the user's knee and the fixed reference object inside the vehicle are obtained based on the sensing data collected by the wearable device. The amount of adjustment for the seat's fore-aft position is determined based on the first distance and the second distance.

11. The vehicle control method according to claim 1, wherein, The at least one target adjustable structure includes a rearview mirror, and the perception data includes image data; The step of determining the adjustment parameters of the at least one target adjustable structure based on the sensing data includes: Based on the image data collected by the wearable device, the mirror image presented in the rearview mirror is obtained; The content of the mirror image is compared with the features of a preset reference image, and the adjustment parameters of the rearview mirror are determined based on the comparison results.

12. The vehicle control method according to claim 11, wherein, The reference image features include: a preset area of ​​the vehicle body; The content of the mirror image is compared with the features of a preset reference image, and the adjustment parameters of the rearview mirror are determined based on the comparison results, including: Determine whether the mirror image contains a preset area of ​​the vehicle body. If not, determine the adjustment parameters of the rearview mirror so that the mirror image presented after the rearview mirror is adjusted based on the adjustment parameters contains the preset area of ​​the vehicle body.

13. The vehicle control method according to claim 1, wherein, Prior to the step of receiving the sensing data collected by the wearable device, the method further includes: Identify the user currently wearing the wearable device; Based on the user's identity, query whether there are preset parameters stored that correspond to the user's identity and the selection information; If the preset parameter is found, then the preset parameter is used as the adjustment parameter, and the adjustment process is executed; If the preset parameters are not found, then the step of receiving the sensing data collected by the wearable device is executed.

14. The vehicle control method according to claim 13, wherein, After performing the adjustment process, the method further includes: In response to the adjustment completion confirmation signal, the adjustment parameters used by each of the target adjustable structures during the adjustment process are acquired; The adjustment parameters are used as preset parameters and stored in association with the user identity and the selection information.

15. The vehicle control method according to any one of claims 1 to 14, wherein, Also includes: Receive target image data including the area of ​​the vehicle's windshield, collected by the wearable device; The target image data is analyzed to determine the fog obstruction index, which characterizes the degree of fogging of the windshield. Based on the fog obstruction index, the target airflow of the vehicle air conditioning system is determined, and the operation of the vehicle air conditioning system is controlled based on the target airflow.

16. The vehicle control method according to claim 15, wherein, The step of determining the target airflow of the vehicle air conditioning system based on the fog obstruction index, and controlling the vehicle air conditioning system to output air based on the target airflow, includes: When the fog obstruction index is in the first index range, the air conditioning system is controlled to operate at the first air volume. When the fog obstruction index is in a second index range that is higher than the first index range, the air conditioning system is controlled to operate at a second air volume that is greater than the first air volume.

17. The vehicle control method according to claim 15, wherein, The step of analyzing the target image data to determine the fog obstruction index, which characterizes the degree of fogging on the windshield, includes: Extract the region of interest (ROI) from the windshield area in the target image data; Determine the image contrast score, edge sharpness score, and light scattering score of the region of interest; Based on the current ambient brightness, assign weights to the image contrast score, edge sharpness score, and light scattering score; The fog occlusion index is determined based on the image contrast score, edge sharpness score, and light scattering score, and their respective weights.

18. The vehicle control method according to any one of claims 1 to 14, wherein, The at least one target adjustable structure includes a rearview mirror; the vehicle control method further includes: After the adjustment process is completed, based on the perception data including the image of the rearview mirror collected by the wearable device, environmental information of the side and rear of the vehicle is obtained. Based on the environmental information, determine whether there are other vehicles or pedestrians gradually approaching within a preset range around the vehicle; If present, a reminder message will be displayed on the vehicle's display screen.

19. The vehicle control method according to claim 18, wherein, The method further includes: Based on the sensing data collected by the wearable device, the horizontal turning angle of the user's head is detected; When the user's head turns horizontally within the preset rearview mirror viewing angle range for a duration exceeding the preset time, the step of obtaining environmental information from the side and rear of the vehicle is executed.

20. A method for guiding in-vehicle functions, applied to wearable devices, wherein, The in-vehicle function guidance method includes: In response to function guidance commands, acquire target images inside the vehicle; Identify the target objects contained in the target image; Retrieve auxiliary information about the target object from the database and output it.

21. The method according to claim 20, wherein, Identifying target objects contained in the target image includes: When the target image contains a central control screen, identify the abnormal icons in the central control screen and use them as the target object; When the target image contains physical buttons and directional gestures, the physical button pointed to by the gesture is identified and the target object is identified.

22. A vehicle control device, wherein, It includes a communication module, a memory, and a processor, wherein the communication module is used for communicating with wearable devices; The memory stores one or more programs that, when executed by the processor, cause the processor to implement the method according to any one of claims 1 to 19.

23. A wearable device, wherein, include: A memory and a processor, wherein the memory stores one or more programs; When the processor executes the one or more programs, the processor performs the method of claim 20 or 21.

24. A computer-readable storage medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 21.

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