Vehicle back door control method and device, vehicle and storage medium

Abstract

The invention provides a control method and device for a vehicle back door, a vehicle and a storage medium, and the method comprises the steps: responding to an opening instruction of the vehicle back door, and determining the distance information between a first point location and a second point location of the vehicle and at least one obstacle at a plurality of time points; the distribution directions of the first point location and the second point location on the vehicle are different; based on the distance information between the first point location and the second point location of the vehicle and the at least one obstacle at the plurality of time points, determining the movement condition of a human body obstacle in the at least one obstacle; and based on the moving condition of the human body obstacle in the at least one obstacle, the vehicle back door is controlled to be opened or closed.

Description

Technical Field

[0001] The present application relates to the field of intelligent vehicle technology, and in particular to a method and device for controlling a vehicle back door, a vehicle, and a storage medium. Background Art

[0002] In the related art, a rear camera is used to recognize a kicking action to control the opening of the back door.

[0003] However, this solution only allows the back door to open. Once the back door is opened, the camera flips up with the bottom of the back door, preventing it from capturing the movements of people behind the vehicle and preventing the door from closing. Closing the back door still requires other methods, significantly impacting the user experience. Summary of the Invention

[0004] The present application mainly provides a vehicle tailgate control method and device, a vehicle, and a storage medium.

[0005] The technical solution of this application is achieved as follows:

[0006] In a first aspect, a method for controlling a vehicle tailgate is provided, the method comprising: determining distance information between a first point position and a second point position of the vehicle and at least one obstacle at multiple time points in response to an opening instruction of the vehicle tailgate; the first point position and the second point position have different distribution directions on the vehicle; based on the distance information between the first point position and the second point position of the vehicle and at least one obstacle at the multiple time points, determining the movement of a human obstacle in the at least one obstacle; and based on the movement of the human obstacle in the at least one obstacle, controlling the opening or closing of the vehicle tailgate.

[0007] In this embodiment, by setting up first and second points distributed in different directions and collecting distance information from obstacles at multiple time points, the system can more comprehensively detect changes in the position of obstacles. By analyzing the distance information between the first and second points and at least one obstacle at multiple time points, it can determine whether the person obstacle is far away from the vehicle's back door or close to the back door. When the conditions are met, the back door closing and opening operations are automatically triggered, effectively solving the problem of the back door not being able to close automatically after opening, as well as the cumbersome problem of opening the back door.

[0008] In some embodiments, determining the movement of a human obstacle in the at least one obstacle based on the distance information between the first point position and the second point position of the vehicle and the at least one obstacle at the multiple time points includes: determining the recognition result of the at least one obstacle based on the distance information corresponding to the first point position and the second point position at a preset time point among the multiple time points; and determining the movement of the human obstacle based on the distance information between the first point position of the vehicle and the at least one obstacle at the multiple time points when the recognition result indicates that there is a human obstacle in the at least one obstacle.

[0009] In this embodiment, obtaining distance information and performing identification at a preset time point helps to identify possible obstacles in advance, laying the foundation for subsequent movement trajectory analysis. This step enables the system to further track the changes in the position of the person after identification, improving the accuracy and timeliness of the judgment.

[0010] In some embodiments, multiple first points are distributed in the horizontal direction of the vehicle back door; multiple second points are distributed in the vertical direction of the vehicle back door; the identification result of the at least one obstacle is determined based on the distance information corresponding to the first points and the second points at preset time points among multiple time points, including: determining the width information of the at least one obstacle at the preset time point based on the distance information corresponding to the multiple first points at the preset time point; determining the height information of the at least one obstacle at the preset time point based on the distance information corresponding to the multiple second points at the preset time point; determining the identification result of the at least one obstacle based on at least one width information and at least one height information.

[0011] In this embodiment, the width and height of obstacles are obtained by measuring them at horizontal and vertical points, respectively, allowing for a more accurate determination of whether an obstacle is a person. Compared to traditional methods that rely solely on distance determination at a single point, this embodiment enhances obstacle recognition capabilities through multi-dimensional information fusion, improving the robustness of the vehicle's automatic tailgate closing system.

[0012] In some embodiments, the determining of the identification result of the at least one obstacle based on at least one of the width information and at least one of the height information includes: when at least one of the width information has target width information within a first preset range and at least one of the height information has target height information within a second preset range, determining that there is an identification result of a human obstacle in the at least one obstacle.

[0013] In the embodiment of the present application, by setting a reasonable width and height threshold range, people and other non-personnel obstacles such as suitcases, pets, etc. can be effectively distinguished, thereby improving the accuracy of recognition.

[0014] In some embodiments, the determining of the movement of the human obstacle based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points includes: determining the change information corresponding to the target width information in at least one width information based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points; and determining the movement of the human obstacle based on the change information.

[0015] In an embodiment of the present application, by determining the change information of the first point position corresponding to the target width information over time, the movement trajectory of the human obstacle can be accurately determined, thereby determining whether the human obstacle is away from the rear door area of the vehicle.

[0016] In some embodiments, the determining of the movement of the human obstacle based on the distance information between the first point position of the vehicle and at least one obstacle at the multiple time points includes: determining whether the human obstacle has moved based on the distance information between the target first point position among the multiple first point positions and at least one obstacle at two adjacent target time points; in the case that the human obstacle moves, determining the moving distance of the human obstacle at multiple other time points based on the distance information between the first point position of the vehicle and at least one obstacle at other time points among the multiple time points; and determining the movement of the human obstacle based on the moving distance of the human obstacle at multiple other time points.

[0017] In the embodiment of the present application, it is first determined whether the human obstacle is moving, and then, if moving, the movement of the human obstacle is determined. In this way, it is possible to filter out the situation where the human obstacle is swaying in a small range, thereby improving the efficiency and accuracy of determining whether the human obstacle is away from the rear door area.

[0018] In some embodiments, the method further includes: acquiring a side environmental image of the vehicle; identifying a target object in the side environmental image; and controlling the opening or closing of the vehicle tailgate based on the movement of a human obstacle among the at least one obstacle, including: controlling the vehicle tailgate to close when the movement indicates that the human obstacle is away from the vehicle tailgate and the target object includes the human obstacle.

[0019] In the embodiment of the present application, by combining environmental image recognition and radar data judgment to form a double verification mechanism, the accuracy and security of the judgment can be further improved.

[0020] In a second aspect, a vehicle tailgate control device is provided, the vehicle tailgate control device comprising:

[0021] a first determining unit configured to determine, in response to an opening instruction for a rear door of the vehicle, distance information between a first point and a second point of the vehicle and at least one obstacle at multiple time points; the first point and the second point being distributed in different directions on the vehicle;

[0022] a second determining unit, configured to determine a movement of a human obstacle in the at least one obstacle based on distance information between the first and second points of the vehicle and the at least one obstacle at the multiple time points;

[0023] A control unit is used to control the vehicle tailgate to close when the movement condition indicates that the human obstacle is away from the vehicle tailgate.

[0024] In a third aspect, a vehicle is provided, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, some or all of the steps in the above method are implemented.

[0025] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, some or all of the steps in the above method are implemented.

[0026] In a fifth aspect, a computer program product is provided, comprising a computer program or instructions, which implement some or all of the steps in the above method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1a Schematic diagram 1 of a vehicle tailgate control method according to an embodiment of the present application;

[0028] Figure 1b Scenario 1 of a vehicle back door control method provided in an embodiment of the present application;

[0029] Figure 2a A second schematic diagram of the implementation flow of a vehicle back door control method provided in an embodiment of the present application;

[0030] Figure 2b Scenario 2 of a vehicle back door control method provided in an embodiment of the present application;

[0031] Figure 2c Scenario 3 of a vehicle back door control method provided in an embodiment of the present application;

[0032] Figure 2dA scenario diagram of a vehicle back door control method provided in an embodiment of the present application Figure 4 ;

[0033] Figure 2e A scenario diagram of a vehicle back door control method provided in an embodiment of the present application Figure 5 ;

[0034] Figure 2f A scenario diagram of a vehicle back door control method provided in an embodiment of the present application Figure 6 ;

[0035] Figure 3a Schematic diagram 3 of the implementation flow of a vehicle back door control method provided in an embodiment of the present application;

[0036] Figure 3b A scenario diagram of a vehicle back door control method provided in an embodiment of the present application Figure 7 ;

[0037] Figure 3c Scenario 8 of a vehicle back door control method provided in an embodiment of the present application;

[0038] Figure 3d Scenario 9 of a vehicle back door control method provided in an embodiment of the present application;

[0039] Figure 4 A schematic diagram of the implementation process of a vehicle back door control method provided in an embodiment of the present application Figure 4 ;

[0040] Figure 5 A schematic diagram of the implementation process of a vehicle back door control method provided in an embodiment of the present application Figure 5 ;

[0041] Figure 6 A schematic diagram of the structure of a vehicle tailgate control device provided in an embodiment of the present application;

[0042] Figure 7 A schematic diagram of a hardware entity of a vehicle in an embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions of this application are further elaborated in detail below with reference to the accompanying drawings and embodiments. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0044] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0045] The terms "first / second / third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understandable that "first / second / third" can be interchanged with a specific order or sequence where permitted so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing this application only and are not intended to limit this application.

[0047] In order to solve the problem in the related art that the back door of a vehicle cannot be automatically closed, the embodiment of the present application provides a vehicle back door control method, which can be applied to a vehicle back door control device in a vehicle. In some embodiments, the vehicle back door control device can be located in the vehicle computer. Figure 1a A schematic diagram of a vehicle back door control method according to an embodiment of the present application is provided. Figure 1a As shown, the vehicle back door control method can be implemented through steps S101 to S103:

[0048] Step S101, in response to an opening instruction of the vehicle tailgate, determining distance information between a first point and a second point of the vehicle and at least one obstacle at multiple time points; the first point and the second point are distributed in different directions on the vehicle.

[0049] Here, the backdoor opening command can be triggered by the user or automatically by the vehicle. In the case where the backdoor opening command is user-triggered, it can be triggered by a physical button, wireless key, voice recognition, foot sensor, etc. In the case where the backdoor opening command is automatically triggered by the vehicle, it can be triggered by the vehicle automatically generating the backdoor opening command when it recognizes the user moving towards the backdoor.

[0050] In an embodiment of the present application, radar data collected by a radar in the rear door area of the vehicle can be obtained, and distance information between a first point position and a second point position of the vehicle and at least one obstacle at multiple time points can be determined based on the radar data. The first point position and the second point position are distributed in different directions on the vehicle. In some embodiments, the first point position can be distributed on a first coordinate axis of the vehicle coordinate system, and the second point position can be distributed on a second coordinate axis of the vehicle coordinate system. For example, the first coordinate axis can be the Y axis, and the second coordinate axis can be the Z axis.

[0051] For example, Figure 1b As shown, the above-mentioned radar may be a reversing radar 102 arranged near the rear door area 101 .

[0052] In an embodiment of the present application, the number of radars in the rear door area of the vehicle may be less than the total number of first points and second points. The distance information between the obstacle and the radar, as well as the position information of the radar in the vehicle coordinate system, can be used to determine the distance information between the obstacle and multiple first points and multiple second points.

[0053] Step S102: determining a movement of a human obstacle in the at least one obstacle based on distance information between the first point position and the second point position of the vehicle and the at least one obstacle at the multiple time points.

[0054] In an embodiment of the present application, it is possible to determine whether there is a human obstacle in at least one obstacle based on the distance information between the first point position and the second point position of the vehicle and at least one obstacle at multiple time points. Then, if it is determined that there is a human obstacle in at least one obstacle, the movement of the human obstacle in at least one obstacle can be determined based on the distance information between the first point position and the second point position of the vehicle and at least one obstacle at multiple time points.

[0055] In some embodiments, whether there is a human obstacle in at least one obstacle can be determined by using distance information between the first point position, the second point position and at least one obstacle corresponding to one time point among multiple time points.

[0056] It can be understood that because the distribution directions of the multiple first points and the multiple second points on the vehicle are different, the width information of each obstacle can be determined by the distance information between the multiple first points and the obstacles at a certain time point, and the height information of each obstacle can be determined by the distance information between the multiple second points and the obstacles at the same time point, so that it can be determined whether at least one obstacle is a human obstacle based on the width information and height information of the obstacle.

[0057] In an embodiment of the present application, when it is determined that there is a human obstacle among at least one obstacle, the distance information between multiple first points and multiple second points and the human obstacle that changes over time can be used to determine whether the human obstacle has moved, that is, the movement status of the human obstacle can be obtained.

[0058] Step S103: Controlling the vehicle tailgate to open or close based on the movement of the human obstacle among the at least one obstacle.

[0059] In this embodiment of the present application, when the vehicle determines, based on the movement of at least one human obstacle, that the human obstacle has moved away from the vehicle's tailgate and is no longer in a position near the tailgate where it might interfere, the vehicle triggers the tailgate closing action. For example, if the human obstacle is detected gradually moving from the center of the tailgate to one side and ultimately completely out of the rear of the vehicle, the vehicle assumes that the person has completed the operation and no longer needs to keep the tailgate open, and thus automatically executes the closing command.

[0060] In practical implementation, the vehicle can also implement a delay mechanism to reduce the risk of incorrect closures due to brief obstructions or misjudgments. For example, if a human obstacle is detected to have temporarily left but quickly returned, the vehicle should reassess its behavior to prevent premature closing of the backdoor. Furthermore, the vehicle can incorporate other sensors (such as infrared and lidar) to further validate the judgment results, improving the overall robustness and reliability of the vehicle.

[0061] In some embodiments, when the vehicle determines that the human obstacle is close to the vehicle tailgate based on the movement of the human obstacle among at least one obstacle, the vehicle will trigger the tailgate opening action.

[0062] In some embodiments, when it is determined that a human obstacle is close to the back door of the vehicle, an image of the human obstacle may be captured by a camera, and then the image may be combined to determine whether to open the back door.

[0063] In this embodiment, by setting up first and second points distributed in different directions and collecting distance information from obstacles at multiple time points, the system can more comprehensively detect changes in the position of obstacles. By analyzing the distance information between the first and second points and at least one obstacle at multiple time points, it can determine whether the person obstacle is far away from the vehicle's back door or close to the back door. When the conditions are met, the back door closing and opening operations are automatically triggered, effectively solving the problem of the back door not being able to close automatically after opening, as well as the cumbersome problem of opening the back door.

[0064] In some embodiments, as Figure 2a As shown, the above step S102 can be implemented through steps S201 and S202:

[0065] Step S201: determining an identification result of the at least one obstacle based on distance information corresponding to the first point and the second point at a preset time point among a plurality of time points.

[0066] Here, the preset time point may be at least one of the multiple time points. That is, the identification result of the at least one obstacle may be determined based on the distance information between the first point and the second point corresponding to one of the multiple time points. To improve identification accuracy, the identification result of the at least one obstacle may also be determined based on the distance information between the first point and the second point corresponding to each of the at least two time points.

[0067] In some embodiments, when the preset time points include at least two time points, if the recognition results corresponding to each time point indicate that a human obstacle exists in at least one obstacle, it is determined that a human obstacle exists in at least one obstacle.

[0068] In some embodiments, the plurality of first points are distributed in the horizontal direction of the vehicle back door; the plurality of second points are distributed in the vertical direction of the vehicle back door; the above step S201 can be implemented by steps S2011 to S2013:

[0069] Step S2011: Determine the width information of the at least one obstacle at the preset time point based on the distance information corresponding to the plurality of first points at the preset time point.

[0070] In an embodiment of the present application, the distance information corresponding to the plurality of first points at the preset time points can be classified to obtain a plurality of first distance sets. The difference between the plurality of distance information in each first distance set is within a preset range. Then, a first target distance set is determined from the plurality of first distance sets. The distribution positions of the first points corresponding to the plurality of distance information in the first target distance set on the back door of the vehicle are continuous. The width information of at least one obstacle at the preset time point is then determined based on the position information of the first points corresponding to the plurality of distance information in the first target distance set.

[0071] For example, Figure 2b 、 Figure 2c and Figure 2d As shown, multiple first points are distributed in the horizontal direction 201 of the vehicle's rear door, and multiple second points are distributed in the vertical direction 202 of the vehicle's rear door. The multiple first points may include points A through G, and the multiple second points may include points a through e. Radar data from four parking sensors distributed on the vehicle can be used to determine the distances between points A through G and obstacles, as well as the distances between points a through e and obstacles.

[0072] like Figure 2e As shown, the distance information between points A through G and the obstacle at a preset time point is provided. Points C, D, and E have the same distance information to the obstacle, and their locations on the vehicle's rear door are continuous. Therefore, the first target distance set includes the distance information between points C, D, and E and the obstacle. Using the location information of points C, D, and E on the vehicle's rear door, the width of the obstacle can be determined as "L."

[0073] Step S2012: Determine the height information of the at least one obstacle at the preset time point based on the distance information corresponding to the plurality of second points at the preset time point.

[0074] In an embodiment of the present application, the distance information corresponding to the plurality of second points at the preset time points can be classified to obtain a plurality of second distance sets. The difference between the plurality of distance information in each second distance set is within a preset range. Then, a second target distance set is determined from the plurality of second distance sets. The distribution positions of the second points corresponding to the plurality of distance information in the second target distance set on the back door of the vehicle are continuous. The height information of at least one obstacle at the preset time point is then determined based on the position information of the second points corresponding to the plurality of distance information in the second target distance set.

[0075] like Figure 2f As shown in the figure, the distance information between points a through e and the obstacle at a preset time point is provided. The distance information between points b, c, and d and the obstacle is identical, and their locations on the vehicle's rear door are continuous. Therefore, the second target distance set includes the distance information between points b, c, and d and the obstacle. The height of the obstacle, "h," can then be determined based on the location information of points b, c, and d on the vehicle's rear door.

[0076] Step S2013: Determine the recognition result of the at least one obstacle based on the at least one width information and the at least one height information.

[0077] In an embodiment of the present application, it is possible to determine whether at least one width information is within a first preset range and whether at least one height information is within a second preset range. If at least one width information has target width information within the first preset range and at least one height information has target height information within the second preset range, then it is determined that there is a human obstacle in at least one obstacle. The first preset range and the second preset range are size threshold intervals set according to the average body shape of the human body, which are used to distinguish human obstacles from other types of obstacles (such as cargo, animals, trees, etc.). For example, the first preset range can be set to a width interval of 30cm to 60cm, and the second preset range can be set to a height interval of 80cm to 170cm. These ranges can be adjusted according to different vehicle models and usage scenarios to adapt to different passenger groups and environmental conditions.

[0078] It's understood that target width information is the horizontal dimension of an obstacle recorded at a specific point in time. This data reflects the horizontal space occupied by the obstacle and is typically used to determine whether a person or similarly sized object is near the rear door area. Target height information is the vertical dimension of an obstacle recorded at a specific point in time. This data is used to determine whether the obstacle has a typical human height, such as a standing person or child. Target height information and target width information together form the basis for determining obstacle type.

[0079] When both the target width and height fall within the corresponding preset ranges, the vehicle identifies the obstacle as a human obstacle. This recognition result serves as an important input to the subsequent control logic, determining whether to execute automatic door closing and opening operations.

[0080] In this embodiment, there's a close data correlation between target width and height information. Together, they form a comprehensive basis for determining the shape and volume of obstacles, thereby improving recognition accuracy and robustness. For example, when determining whether a person has left the rear door area, relying solely on width information might not be able to distinguish between a person and a box. However, adding height information allows the vehicle to more reliably identify human features.

[0081] Step S202 , when the recognition result indicates that there is a human obstacle among the at least one obstacle, determine the movement of the human obstacle based on the distance information between the first point position of the vehicle and the at least one obstacle at the multiple time points.

[0082] Here, movement can represent the changing trend of the human obstacle's position within the back door area, such as moving from the center of the back door to the side, leaving the back door area, or remaining stationary. These states can be determined by comparing distance information at multiple time points. In particular, the movement path and direction can be determined by comparing the distance differences between the same obstacle at multiple detection points (such as the first and second points) at different time points.

[0083] In an embodiment of the present application, by further analyzing the movement of human obstacles after identifying them, the user's behavioral intention can be judged more accurately, thereby achieving more intelligent and safe automatic backdoor control, which can significantly improve the vehicle's human-computer interaction experience and ease of use.

[0084] In some embodiments, as Figure 3a As shown, the above step S202 of "determining the movement of the human obstacle based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points" can be implemented through steps S301 and S302:

[0085] Step S301: Based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points, determine the change information corresponding to the target width information in at least one width information; the change information is the change information of the first point corresponding to the target width information over time.

[0086] Here, the target width information may refer to width information of a target obstacle among the at least one obstacle.

[0087] In an embodiment of the present application, based on the distance information between the first point of the vehicle and at least one obstacle at multiple time points, the change information corresponding to the target width information in at least one width information is determined, including: for each time point, determining the position information of the first point corresponding to the target width information at that time point; based on the position information of the first point corresponding to multiple time points, respectively, determining the change information of the first point corresponding to the target width information over time.

[0088] It is understandable that when the human obstacle is located in the middle area of the vehicle's back door area, the first point corresponding to the target width information is located in the middle area of the vehicle's back door. Figure 2d As shown in the figure, when the human obstacle is in the middle of the vehicle's tailgate area, the first points corresponding to the target width information are points C, D, and E. Points C, D, and E are all located in the middle of the vehicle's tailgate area. When the human obstacle moves to the edge of the vehicle's tailgate area, the first points corresponding to the target width information change, thereby obtaining information on the change of the first points corresponding to the target width information over time.

[0089] Step S302: Determine the movement of the human obstacle based on the change information.

[0090] In an embodiment of the present application, when the change information indicates that the position change of the first point is from the middle area of the vehicle tailgate area to the edge area of the vehicle tailgate area, it can be determined that the human obstacle is moving away from the vehicle tailgate.

[0091] It can be understood that when the human obstacle is located in the middle of the vehicle's tailgate area, the first point corresponding to the target width information is located in the middle of the vehicle's tailgate area. When the human obstacle is located in the edge of the vehicle's tailgate area, the first point corresponding to the target width information is located in the edge of the vehicle's tailgate area. Therefore, when the change information indicates that the position of the first point has changed from the middle of the vehicle's tailgate area to the edge of the vehicle's tailgate area, it can be determined that the human obstacle is away from the vehicle's tailgate.

[0092] In this embodiment, by modeling the width variation trend of obstacles at multiple time points, the trajectory characteristics of people's movement can be more precisely captured. This method can determine whether the person has left the vehicle's tailgate area, providing a more reliable basis for whether to execute the tailgate closing or opening operation.

[0093] In some embodiments, the step S202 of "determining the movement of the human obstacle based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points" can be implemented through steps S11 to S13:

[0094] Step S11: determining whether the human obstacle has moved based on distance information between a target first point among the plurality of first points and at least one obstacle at two adjacent target time points.

[0095] Here, the two target time points refer to any two adjacent time points among the multiple time points, and the target first point position refers to any point position among the multiple first point positions.

[0096] In an embodiment of the present application, the distance information corresponding to two adjacent target time points can be compared. When the difference between the two is greater than the maximum value of the above-mentioned first preset range, it is determined that the human obstacle has moved; when the difference between the two is less than or equal to the maximum value of the above-mentioned first preset range, it is determined that the human obstacle has not moved.

[0097] For example, at time t1, the distance between point A and the obstacle is L1, and at time t2, the distance between point A and the obstacle is L1'. When L1'-L1 is greater than the preset value M of the human body width (i.e., the maximum value of the first preset range), it is preliminarily determined that the human obstacle has moved.

[0098] Step S12, when the human obstacle moves, based on the distance information between the first point of the vehicle and at least one obstacle at other time points among the multiple time points, determining the moving distance of the human obstacle at multiple other time points.

[0099] Here, the other time points may be time points later than the target time point among the multiple time points. For example, when the movement of the human obstacle is determined by the distance information corresponding to time point t1 and the distance information corresponding to time point t2, the movement distance of the human obstacle can be determined by the distance information corresponding to time point t3 to time point tn.

[0100] In the embodiment of the present application, the moving distance of the human obstacle at each time point can be determined by comparing the distance information between other time points and at least one obstacle at other adjacent time points.

[0101] For example, Figure 3b As Figure 3d As shown, there are human obstacles 301 and other obstacles 302 near the back door area 101 of the vehicle. Figure 3b In the figure, the human obstacle 301 is in the back door area 101. At a certain time point, the human obstacle 301 moves from Figure 3b Move to the position in Figure 3c When the vehicle is in the position Figure 3b 、 Figure 3c The distance information between the human obstacle 301 and the corresponding time point is used to determine the moving distance of the human obstacle 301, and then at the next time point, the human obstacle 301 moves from Figure 3c Move to the position in Figure 3d The position of the vehicle can also be determined by the first point of the vehicle Figure 3c 、 Figure 3d The distance information between the corresponding time point and the human obstacle 301 is used to determine the moving distance of the human obstacle 301.

[0102] Step S13: determining the movement of the human obstacle based on the movement distance of the human obstacle.

[0103] In this embodiment of the present application, the sum of the movement distances of the human obstacle at all time points can be determined, and based on this sum of the movement distances at all time points, it can be determined whether the human obstacle is away from the vehicle's tailgate area. The sum of the movement distances at all time points can be compared with a preset range. If the sum of the movement distances at all time points is greater than the maximum value of the preset range, it is determined that the human obstacle is away from the vehicle's tailgate area.

[0104] In some embodiments, as Figure 4 As shown, the above method can also be implemented through step S401 and step S402, and the above step S103 can be implemented through step S403:

[0105] Step S401: Acquire a side environmental image of the vehicle.

[0106] Here, the side environment image refers to an environment image captured by a camera located on the side of the vehicle.

[0107] For example, Figure 2b As shown, the camera 401 may be located in the rearview mirror area of the vehicle.

[0108] In the embodiment of the present application, the timing for the camera to collect the side environment image is the time point after the end time point of the other time points mentioned above. For example, the timing for the camera to collect the side environment image may be when the human obstacle moves to Figure 3d When the position shown.

[0109] It is understandable that when it is determined that the human obstacle has moved, the human obstacle may leave the door area at the termination time point at other time points, so the side environment image can be collected by the camera at the next time point after the termination time point to determine whether the human obstacle has moved from the rear door area of the vehicle to the side area of the vehicle.

[0110] Step S402: Identify a target object in the side environment image.

[0111] In this embodiment of the present application, an image recognition algorithm can be used to extract and identify key target objects that may affect the opening and closing of the tailgate, such as pedestrians, pets, or other obstacles, from the image acquired in step 401. This recognition process is typically based on a deep learning model, such as a convolutional neural network (CNN), which trains on a large number of samples to achieve high-accuracy recognition of specific targets. The system will mark key features of the target object, such as its location, size, and shape, for use in the next logical decision.

[0112] In the embodiment of the present application, through image recognition technology, the system can accurately identify people or obstacles approaching the vehicle, thereby avoiding misjudgment or missed judgment, and improving the safety and accuracy of back door control.

[0113] Step S403 : When the movement condition indicates that the human obstacle is away from the vehicle tailgate, and the target object includes the human obstacle, controlling the vehicle tailgate to close.

[0114] In an embodiment of the present application, when the vehicle detects that a human obstacle is gradually moving away from the vehicle's rear door and eventually leaves its influence range, in order to determine whether the human obstacle continues to move away from the vehicle's rear door, it is necessary to determine it in combination with the image recognition result.

[0115] By combining distance detection and image recognition results, the system can more comprehensively assess the relative position relationship between people and vehicles, thereby achieving intelligent closing of the back door without manual operation by the user, improving user experience and operational convenience.

[0116] In this embodiment, by acquiring an image of the vehicle's side environment and identifying a target object within it, the vehicle's back door is controlled to close if a human obstacle is determined to be away from the back door. This improves the automation level of the vehicle's back door control, thereby reducing the user's operational burden and improving driving safety and ease of use.

[0117] In some embodiments, when the movement condition indicates that the human obstacle is close to the vehicle tailgate, and the target object includes the human obstacle, the vehicle tailgate is controlled to open.

[0118] The following describes the application of the vehicle back door control method provided by the embodiment of the present application in actual scenarios:

[0119] Traditional back door opening mainly relies on buttons, wireless keys, cables, central control, kick sensors, etc.

[0120] The related technology uses a rear camera to detect kicking movements to control the back door opening. It has a strong sense of technology and does not require additional sensors, which has both technological and cost advantages.

[0121] However, this solution only performs the opening action. When the tailgate is opened, the camera flips up with the bottom of the tailgate, so it cannot capture the movements of people behind the car and cannot perform the door closing action. Closing the door still requires other methods. This significantly affects the scene function experience.

[0122] The vehicle tailgate control method provided in the embodiment of the present application can optimize the tailgate opening and closing scenarios, realize automatic execution of the closing action after the camera recognizes the opening, or automatically close the tailgate in other ways without additional actions.

[0123] In this embodiment of the present application, when the tailgate is opened, the tailgate's reversing radar is activated to identify the position and distance of the rear obstacle, namely the person. After the passenger has finished taking or placing items through the tailgate, they can simply exit the tailgate. The tailgate's reversing radar continuously detects and determines the movement and departure of the person. In this embodiment of the present application, the rearview mirror camera is activated to identify the person's position. When the obstacle is detected to have disappeared and the person has left, the tailgate can automatically close.

[0124] like Figure 5 As shown, the above-mentioned vehicle back door control method can also be implemented through steps S501 to S507:

[0125] Step S501: When a back door opening instruction is received, the algorithm is started.

[0126] Step S502: Invoke the vehicle's reversing radar to detect obstacles behind the vehicle.

[0127] Step S503: Identify and determine the change in the position of the obstacle.

[0128] In the embodiment of the present application, the vehicle's reversing radar is called to detect obstacles behind the vehicle, record them at multiple points, and compare the changes over time.

[0129] For example, at time t1, the distance to the obstacle at point A is L1, the distance to points B on either side is L2, and the distance to point C is L3. At time t2, the distance to the obstacle at point A is L1', and L1'-L1 is greater than the preset human width M, indicating a preliminary determination of human movement. Multiple comparisons are then performed at points B and C to determine the location, sequence, and time of movement of the moving obstacle. This comprehensive assessment of human movement and departure is then made.

[0130] In an embodiment of the present application, the width and height of the obstacle can be determined through radar data. By checking the width and height, a preliminary judgment can be made as to whether it is a human obstacle. Then, by observing the movement of the width and height over time, it can be judged whether the human obstacle has moved and left.

[0131] In the embodiment of the present application, when the back door is opened, the reversing radar starts detecting the position of people / moving obstacles and recording multi-point distance judgments.

[0132] After the backdoor is opened, the rearview radar continuously detects the position of people and moving obstacles, comparing multiple points with the position at the time of opening to determine whether the moving obstacle has moved from the center of the backdoor to the side and then disappeared. Simultaneously, the rearview mirror camera continuously detects the position of people and compares multiple points with the position at the time of opening to determine whether the person has moved from the rear to the front.

[0133] Step S504: Call the vehicle's exterior rearview mirror camera to identify whether a person moves away from the rear of the vehicle.

[0134] Step S505: Whether the obstacle moves and leaves the candidate area.

[0135] If yes, execute step S506; if no, execute step S503.

[0136] Step S506: the back door closes.

[0137] Step S507: determine whether the back door is anti-pinch or closed.

[0138] If no, execute step S503.

[0139] Figure 6 A schematic diagram of the structure of a vehicle back door control device provided in an embodiment of the present application is shown in FIG. Figure 6 As shown, the vehicle back door control device 600 includes: a first determination unit 601, a second determination unit 602 and a control unit 603, wherein:

[0140] A first determining unit 601 is configured to determine, in response to an opening instruction for a rear door of the vehicle, distance information between a first point and a second point of the vehicle and at least one obstacle at multiple time points; the first point and the second point are distributed in different directions on the vehicle;

[0141] A second determining unit 602 is configured to determine a movement of a human obstacle in the at least one obstacle based on distance information between the first and second points of the vehicle and the at least one obstacle at the multiple time points;

[0142] The control unit 603 is configured to control the vehicle tailgate to be opened or closed based on the movement of the human obstacle among the at least one obstacle.

[0143] In some embodiments, the second determination unit 602 is further used to determine the identification result of the at least one obstacle based on the distance information corresponding to the first point position and the second point position at a preset time point among multiple time points; when the identification result indicates that there is a human obstacle among the at least one obstacle, the movement of the human obstacle is determined based on the distance information between the first point position of the vehicle and the at least one obstacle at the multiple time points.

[0144] In some embodiments, multiple first points are distributed in the horizontal direction of the vehicle back door; multiple second points are distributed in the vertical direction of the vehicle back door; the second determination unit 602 is also used to determine the width information of the at least one obstacle at the preset time point based on the distance information corresponding to the multiple first points at the preset time point; determine the height information of the at least one obstacle at the preset time point based on the distance information corresponding to the multiple second points at the preset time point; determine the identification result of the at least one obstacle based on at least one width information and at least one height information.

[0145] In some embodiments, the second determination unit 602 is further used to determine the recognition result of a human obstacle existing in the at least one obstacle when at least one of the width information has target width information within a first preset range and at least one of the height information has target height information within a second preset range.

[0146] In some embodiments, the second determination unit 602 is also used to determine the change information corresponding to the target width information in at least one width information based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points; the change information is the change information of the first point corresponding to the target width information over time; based on the change information, the movement of the human obstacle is determined.

[0147] In some embodiments, the second determination unit 602 is further used to determine whether the human obstacle has moved based on the distance information between the target first point among the multiple first points and at least one obstacle at two adjacent target time points; in the case of the human obstacle moving, based on the distance information between the first point of the vehicle and at least one obstacle at other time points among the multiple time points, determine the moving distance of the human obstacle at multiple other time points; based on the moving distance of the human obstacle at multiple other time points, determine the movement of the human obstacle

[0148] In some embodiments, the control device 600 for the above-mentioned vehicle tailgate also includes: an image acquisition unit and a recognition unit; the image acquisition unit is used to acquire the side environment image of the vehicle; the recognition unit is used to identify the target object in the side environment image; the control unit 603 is also used to control the closing of the vehicle tailgate when the movement condition indicates that the human obstacle is away from the vehicle tailgate and the target object includes the human obstacle.

[0149] The description of the above device embodiment is similar to the description of the above method embodiment and has similar beneficial effects as the method embodiment. In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to perform the methods described in the above method embodiments. For technical details not disclosed in the device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0150] It should be noted that, in the embodiment of the present application, if the above-mentioned data processing method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific hardware, software or firmware, or any combination of hardware, software and firmware.

[0151] An embodiment of the present application provides a computer device including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, some or all of the steps in the above method are implemented.

[0152] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements some or all of the steps in the above method. The computer-readable storage medium may be transient or non-transient.

[0153] An embodiment of the present application provides a computer program, including computer-readable code. When the computer-readable code runs in a computer device, a processor in the computer device executes some or all of the steps for implementing the above method.

[0154] The present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, some or all of the steps in the above method are implemented. The computer program product can be implemented in hardware, software, or a combination thereof. In some embodiments, the computer program product is embodied as a computer storage medium. In other embodiments, the computer program product is embodied as a software product, such as a software development kit (SDK).

[0155] It should be noted that the descriptions of the various embodiments above tend to emphasize the differences between the various embodiments, and their similarities or similarities can be referenced to each other. The descriptions of the above device, storage medium, computer program, and computer program product embodiments are similar to the descriptions of the above method embodiments and have similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the device, storage medium, computer program, and computer program product of this application, please refer to the description of the method embodiments of this application for understanding.

[0156] Figure 7 This is a schematic diagram of a hardware entity of a vehicle in an embodiment of the present application, such as Figure 7 As shown, the vehicle 700 includes: a vehicle body (not shown), a vehicle side door (not shown), a vehicle back door (not shown), a distance sensor (not shown), a controller 701, a communication interface 702 and a memory 703, wherein:

[0157] a distance sensor, configured to detect distance information between a first point position and a second point position of the vehicle and at least one obstacle at multiple time points;

[0158] The controller 701 generally controls the overall operation of the vehicle 700 , and the overall operation may be to implement the vehicle back door control method provided in an embodiment of the present application.

[0159] The communication interface 702 enables the computer device to communicate with other terminals or servers through a network.

[0160] The memory 703 is configured to store instructions and applications executable by the controller 701. It can also cache data to be processed or processed by the controller 701 and various modules in the vehicle 700 (e.g., image data, audio data, voice communication data, and video communication data). This can be implemented using flash memory (FLASH) or random access memory (RAM). Data can be transmitted between the controller 701, the communication interface 702, and the memory 703 via a bus 704.

[0161] An embodiment of the present application provides a computer storage medium storing one or more programs, which can be executed by one or more processors to implement the steps of the vehicle tailgate control method as described in any of the above embodiments.

[0162] It should be noted that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0163] The processor may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor. It is understood that the electronic device that implements the functions of the processor may also be other electronic devices, which are not specifically limited in the embodiments of the present application.

[0164] The above-mentioned computer storage medium / memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory (Flash Memory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); it can also be various terminals including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0165] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned steps / processes does not mean the order of execution, and the execution order of each step / 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. The above-mentioned serial numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments.

[0166] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0167] The above are only implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the protection scope of the present application.

Claims

1. A method for controlling a vehicle back door, characterized in that: The method comprises: In response to an opening instruction for the vehicle tailgate, determining distance information between a first point and a second point on the vehicle and at least one obstacle at multiple time points; the first point and the second point are distributed in different directions on the vehicle; Determining a movement of a human obstacle in the at least one obstacle based on distance information between the first point position and the second point position of the vehicle and the at least one obstacle at the multiple time points; Based on the movement of the human obstacle among the at least one obstacle, the vehicle tailgate is controlled to be opened or closed.

2. The method according to claim 1, characterized in that The determining, based on the distance information between the first point position and the second point position of the vehicle and the at least one obstacle at the multiple time points, of the movement of a human obstacle in the at least one obstacle includes: determining an identification result of the at least one obstacle based on distance information corresponding to the first point and the second point at a preset time point among a plurality of time points; When the recognition result indicates that a human obstacle exists among the at least one obstacle, the movement of the human obstacle is determined based on distance information between the first point position of the vehicle and the at least one obstacle at the multiple time points.

3. The method according to claim 2, characterized in that The plurality of first points are distributed in a horizontal direction of the vehicle back door; the plurality of second points are distributed in a vertical direction of the vehicle back door; and the determining of the recognition result of the at least one obstacle based on distance information corresponding to the first points and the second points at a preset time point among a plurality of time points includes: Determining the width information of the at least one obstacle at the preset time point based on the distance information corresponding to the plurality of first points at the preset time point; Determining the height information of the at least one obstacle at the preset time point based on the distance information corresponding to the plurality of second points at the preset time point; Based on the at least one piece of width information and the at least one piece of height information, a recognition result of the at least one obstacle is determined.

4. The method according to claim 3, characterized in that The determining, based on the at least one piece of width information and the at least one piece of height information, a recognition result of the at least one obstacle includes: When at least one of the width information includes target width information within a first preset range and at least one of the height information includes target height information within a second preset range, it is determined that there is a recognition result of a human obstacle in the at least one obstacle.

5. The method according to claim 2, characterized in that The determining of the movement of the human obstacle based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points includes: Determining, based on distance information between a first point of the vehicle and at least one obstacle at the multiple time points, change information corresponding to target width information in at least one width information; the change information is change information of the first point corresponding to the target width information over time; Based on the change information, the movement status of the human obstacle is determined.

6. The method according to claim 2, characterized in that The determining of the movement of the human obstacle based on the distance information between the first point of the vehicle and at least one obstacle at the multiple time points includes: determining whether the human obstacle has moved based on distance information between a target first point among the plurality of first points and at least one obstacle at two adjacent target time points; In the case where the human obstacle moves, determining the movement distance of the human obstacle at multiple other time points based on distance information between the first point position of the vehicle and at least one obstacle at other time points among the multiple time points; The movement status of the human obstacle is determined based on the movement distance of the human obstacle at multiple other time points.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: Acquiring a side environmental image of the vehicle; Identifying a target object in the side environment image; The controlling the opening or closing of the vehicle tailgate based on the movement of the human obstacle among the at least one obstacle includes: When the movement condition indicates that the human obstacle is away from the vehicle tailgate, and the target object includes the human obstacle, the vehicle tailgate is controlled to be closed.

8. A vehicle back door control device, characterized in that: The device comprises: a first determining unit configured to determine, in response to an opening instruction for a rear door of the vehicle, distance information between a first point and a second point of the vehicle and at least one obstacle at multiple time points; the first point and the second point being distributed in different directions on the vehicle; a second determining unit, configured to determine a movement of a human obstacle in the at least one obstacle based on distance information between the first and second points of the vehicle and the at least one obstacle at the multiple time points; A control unit is used to control the opening or closing of the vehicle tailgate based on the movement of a human obstacle among the at least one obstacle.

9. A vehicle, characterized in that: include: Vehicle body, vehicle side doors, vehicle back doors; a distance sensor, configured to detect distance information between a first point position and a second point position of the vehicle and at least one obstacle at multiple time points; a memory for storing executable instructions; A controller is configured to implement the steps of the vehicle tailgate control method according to any one of claims 1 to 7 when executing the executable instructions stored in the memory.

10. A computer-readable storage medium, characterized in that The storage medium stores executable instructions, and when the executable instructions are executed by the processor, the steps in the vehicle tailgate control method according to any one of claims 1 to 7 are implemented.

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