Multi-sensor fusion and dynamic path planning self-adaptive automobile tail door control method, device and equipment and storage medium

Abstract

The invention discloses a multi-sensor fusion and dynamic path planning adaptive automobile tail gate control method, device and equipment and a storage medium, and relates to the technical field of intelligent automobile tail gate control, and the method comprises the steps: obtaining obstacle information and a target safety distance; planning a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, controlling the vehicle to open a tail door, and determining tail space information; and a tail door closing instruction of a user is obtained, the vehicle is controlled to close a tail door based on the obstacle information, the vehicle tail space information, the target safety distance and the tail door closing instruction of the user, the vehicle is controlled to enter a target parking area to be parked, and the target parking area is the parking area recognized by the vehicle. The vehicle safety path is planned by precisely sensing the surrounding environment of the vehicle, the vehicle direction is automatically adjusted, vehicle tail door control is effectively achieved, user requirements are met, user operation is optimized, and the collision risk is remarkably reduced.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent automobile tailgate control, and in particular to an adaptive automobile tailgate control method, device, equipment and storage medium based on multi-sensor fusion and dynamic path planning. Background Art

[0002] With the continuous development of intelligent and automated automotive technology, consumers have higher expectations for vehicle convenience and safety. Automatic tailgate opening and closing, as a key convenience feature, has garnered widespread attention. However, in real-world scenarios, such as when the rear of a vehicle approaches an obstacle, automatic tailgate operation may be limited, even posing a collision risk. Furthermore, insufficient space for users to access and place luggage after the tailgate is open can be inconvenient. Therefore, intelligent environmental perception and dynamic adjustment of the vehicle's position for tailgate control are essential to enhance user experience and vehicle safety.

[0003] Currently, existing approaches use cameras to detect the distance between the rear of the vehicle and obstacles, prohibiting the tailgate from opening when the distance is insufficient, or use ultrasonic sensors to detect obstacles and plan the tailgate opening angle to avoid collisions. However, existing single-camera solutions are susceptible to environmental interference, resulting in high misjudgment rates. Alternatively, ultrasonic sensors have limited coverage and cannot fully perceive the vehicle's surroundings. Furthermore, they fail to consider the space required for users to move around when retrieving and placing luggage, focusing solely on mechanical obstacle avoidance and employing a single interactive method that fails to meet diverse user needs. Furthermore, they lack a dynamic vehicle position adjustment mechanism, forcing users to manually move the vehicle, a cumbersome operation. Therefore, intelligently adjusting the vehicle's position for personalized tailgate control has become a pressing issue.

[0004] The above content is only used to assist in understanding the technical solution of this application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide an adaptive automobile tailgate control method, device, equipment and storage medium with multi-sensor fusion and dynamic path planning, aiming to solve the technical problem of how to intelligently adjust the vehicle position to perform personalized control of the vehicle tailgate.

[0006] To achieve the above objectives, the present application proposes an adaptive automobile tailgate control method based on multi-sensor fusion and dynamic path planning, the method comprising:

[0007] Obtain obstacle information and target safety distance;

[0008] Planning a safe path for the vehicle and a target safe area based on the obstacle information and the target safety distance, and controlling the vehicle to open the tailgate to determine rear space information;

[0009] Obtain a user's tailgate closing instruction, control the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and control the vehicle to enter a target parking area for parking, where the target parking area is a parking area identified by the vehicle.

[0010] In one embodiment, the step of obtaining obstacle information and target safety distance includes:

[0011] Obtain tailgate activity distance, human activity space and scene intervention information;

[0012] Detect obstacle features and determine obstacle information, including obstacle distance in front of the vehicle, obstacle distance behind the vehicle, and obstacle type;

[0013] Selecting a safety distance based on the tailgate activity distance and the human activity space, and adjusting the safety distance threshold weight according to the scene intervention information to determine a target safety distance;

[0014] In one embodiment, the steps of planning a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, controlling the vehicle to open the tailgate, and determining the rear space information include:

[0015] Identifying vehicle adjustment space based on the obstacle information and the target safety distance, and determining vehicle safety redundancy and vehicle activity space operating condition information;

[0016] Planning a vehicle safety path and a target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, and determining the vehicle planning position information and the vehicle target tailgate deployment angle;

[0017] The vehicle tailgate is controlled to open based on the target safety distance, the planned vehicle position information, and the target tailgate deployment angle of the vehicle to obtain rear space information.

[0018] In one embodiment, the steps of planning a vehicle safety path and a target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, and determining the vehicle planned position information and the vehicle target tailgate deployment angle include:

[0019] Get path offset;

[0020] Planning a safe path for the vehicle based on the vehicle's activity space operating condition information and a dynamic path planning algorithm, and providing feedback with recommended adjustments to determine a circuitous path and a target tailgate deployment angle for the vehicle;

[0021] The vehicle movement is controlled according to the vehicle safety redundancy and the circuitous path, and the vehicle correction mechanism is triggered according to the path offset to adjust the vehicle target direction to obtain the vehicle planned position information.

[0022] In one embodiment, the step of controlling the vehicle tailgate opening based on the target safety distance, the planned vehicle position information, and the target tailgate deployment angle to obtain the vehicle rear space information further includes:

[0023] Obtain the sudden obstacle detection frequency;

[0024] detecting obstacle burst characteristics based on the obstacle burst detection frequency, and determining obstacle burst information, wherein the obstacle burst information includes obstacle burst distance and obstacle type;

[0025] Analyzing the obstacle avoidance urgency based on the obstacle sudden distance, the obstacle type, and the target safety distance, and determining a vehicle emergency obstacle avoidance mode, the vehicle obstacle avoidance mode including tailgate pausing, vehicle reverse movement, and sound and light alarms;

[0026] The vehicle is controlled to move in an emergency to avoid sudden obstacles based on the vehicle emergency obstacle avoidance mode.

[0027] In one embodiment, the steps of obtaining a user's tailgate closing instruction, controlling the vehicle to close the tailgate based on the obstacle information, the vehicle rear space information, the target safety distance, and the user's tailgate closing instruction, and controlling the vehicle to enter a target parking area for parking, wherein the target parking area is a parking area identified by the vehicle, include:

[0028] identifying a space to be adjusted for the vehicle's tailgate based on the obstacle information, the vehicle's rear space information, the target safety distance, and the user's tailgate closing instruction, and determining vehicle activity space information;

[0029] The vehicle is controlled to close its tailgate based on the vehicle activity space information, and the vehicle is controlled to enter a target parking area for parking.

[0030] In one embodiment, the step of controlling the vehicle to close its tailgate based on the vehicle activity space information and controlling the vehicle to enter a target parking area for parking further includes:

[0031] detecting a vehicle gap based on the vehicle activity space information and determining adjustment response information;

[0032] When the adjustment response information indicates that there is sufficient space to allow adjustment, controlling the vehicle to close the tailgate and adjust the vehicle clearance to enter the target parking area;

[0033] When the adjustment response information indicates that the space is insufficient and cannot be adjusted, the vehicle is controlled to generate feedback of detailed adjustment suggestions and issue an audible and visual alarm.

[0034] In addition, to achieve the above objectives, the present application also proposes an adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning, the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning comprising:

[0035] Acquisition module, used to obtain obstacle information and target safety distance;

[0036] a processing module, configured to plan a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, and control the vehicle to open the tailgate and determine the rear space information;

[0037] The execution module is used to obtain a user's tailgate closing instruction, control the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and control the vehicle to enter a target parking area for parking, where the target parking area is a parking area identified by the vehicle.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes an adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning, the device including: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning as described above.

[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning as described above are implemented.

[0040] One or more technical solutions proposed in this application have at least the following technical effects:

[0041] This embodiment proposes an adaptive automobile tailgate control method using multi-sensor fusion and dynamic path planning. The method obtains obstacle information and a target safety distance; plans a vehicle safe path and a target safety area based on the obstacle information and the target safety distance, controls the vehicle to open the tailgate, and determines the rear space information; obtains a user's tailgate closing command, controls the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance, and the user's tailgate closing command, and controls the vehicle to enter a target parking area for parking. The target parking area is the parking area identified by the vehicle. This application obtains obstacle information and a target safety distance, accurately perceives the vehicle's surrounding environment, plans a vehicle safe path, automatically adjusts the vehicle's direction, ensures that the tailgate can effectively avoid obstacles and meet user operation requirements during the opening and closing process, and controls the vehicle to enter the target safety area to open the tailgate or enter the target parking area to close the tailgate, thereby achieving personalized and intelligent tailgate control, making tailgate control safer and more convenient. Through technical means such as precise environmental perception, dynamic path planning, and AI learning optimization, the method effectively reduces collision risks, optimizes user operation, enhances the system's adaptability and intelligence, and significantly improves the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0044] Figure 1 This is a schematic diagram of the multi-sensor fusion layout of the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning in this application;

[0045] Figure 2 A flowchart illustrating the first embodiment of the adaptive automobile tailgate control method using multi-sensor fusion and dynamic path planning provided by this application;

[0046] Figure 3 A schematic diagram showing a target safety distance for the adaptive automobile tailgate control method based on multi-sensor fusion and dynamic path planning in this application, wherein the human activity space is set;

[0047] Figure 4 Schematic diagram of setting the tailgate activity distance as the target safety distance for the adaptive automobile tailgate control method based on multi-sensor fusion and dynamic path planning in this application;

[0048] Figure 5 This is an example diagram of the AR-HUD interactive interface of the adaptive car tailgate control method based on multi-sensor fusion and dynamic path planning in this application;

[0049] Figure 6 A flow chart illustrating a second embodiment of the adaptive automobile tailgate control method using multi-sensor fusion and dynamic path planning of this application is provided;

[0050] Figure 7 This is a schematic diagram of the module structure of the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning according to an embodiment of the present application;

[0051] Figure 8 This is a schematic diagram of the device structure of the hardware operating environment involved in the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning in the embodiment of the present application.

[0052] The purpose, features and advantages of this application will be further explained with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0054] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0055] The main solutions of the embodiments of the present application are: obtaining obstacle information and a target safety distance; planning a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, and controlling the vehicle to open the tailgate and determine the rear space information; obtaining a user's tailgate closing instruction, controlling the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and controlling the vehicle to enter a target parking area for parking, where the target parking area is a parking area identified by the vehicle.

[0056] In this embodiment, for ease of description, the following description is made by taking the adaptive automobile tailgate control device that recognizes multi-sensor fusion and dynamic path planning as the execution subject.

[0057] Because the single-camera solution of existing technology is easily affected by environmental interference, resulting in a high misjudgment rate, or the coverage of the ultrasonic sensor is limited, it cannot fully perceive the vehicle's surrounding environment, and does not consider the human activity space requirements when users pick up and put down luggage. It only focuses on mechanical obstacle avoidance and has a single interaction method, which cannot meet the diverse needs of users. In addition, there is a lack of a dynamic vehicle position adjustment mechanism, and users still need to move the vehicle manually, which is cumbersome.

[0058] This application provides a solution, such as Figure 1 As shown, Figure 1 This is a schematic diagram of the multi-sensor fusion layout of the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning in this application. The actual application scenario may include a binocular camera, millimeter-wave radar, ultrasonic sensor, TOF camera and ARHUD display area, wherein the binocular camera is used to resist strong light or weak light interference and generate a 3D point cloud around the vehicle in real time, the millimeter-wave radar is used to detect obstacle distances all day long, the ultrasonic sensor is used for close-range precise ranging and redundancy verification, the TOF camera is used to capture user body data in real time and dynamically adjust the lateral safety distance, and the ARHUD display area is used to display the tailgate opening path and safety area on the windshield.

[0059] It can be seen from the above embodiments that the present application obtains obstacle information and target safety distance, accurately perceives the vehicle's surrounding environment, plans a safe vehicle path, and automatically adjusts the vehicle direction to ensure that the tailgate can effectively avoid obstacles and meet user operation needs during the opening and closing process, and controls the vehicle to enter the target safety area to open the tailgate or enter the target parking area to close the tailgate, thereby realizing personalized and intelligent tailgate control, and making tailgate control safer and more convenient. Through technical means such as precise environmental perception, dynamic path planning, and AI learning optimization, the collision risk is effectively reduced, user operation is optimized, the system's adaptability and intelligence level are enhanced, and the user experience is significantly improved.

[0060] Based on this, the embodiment of the present application provides an adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the adaptive automobile tailgate control method based on multi-sensor fusion and dynamic path planning of the present application.

[0061] In this embodiment, the adaptive automobile tailgate control method based on multi-sensor fusion and dynamic path planning includes steps S10 to S30:

[0062] Step S10, obtaining obstacle information and target safety distance;

[0063] It should be noted that the obstacle information is obstacle data in the vehicle's surrounding environment that affects the opening or closing of the tailgate, identified by a multi-sensor fusion system. The target safety distance is a safety distance threshold dynamically calculated to ensure the safety of the vehicle and user when controlling the tailgate. The user tailgate closing command is a command regarding tailgate control issued by the user through gestures, voice, or mobile phone applications.

[0064] It is understandable that the obstacle information may include obstacle location, obstacle distance, obstacle type and obstacle size. The vehicle tailgate can be dynamically controlled based on the identified obstacle to ensure that the vehicle can effectively avoid obstacles during movement or tailgate operation. The target safety distance is used to ensure a safe gap between the vehicle and the obstacle during the opening and closing of the tailgate, leaving a certain degree of tolerance to avoid emergency avoidance in emergencies. The user's tailgate closing instruction can be a personalized control of the tailgate opening or closing by the user according to his or her own ideas to better meet user needs.

[0065] In addition, it should be noted that the use of the obstacle information, target safety distance and user tailgate closing command can realize intelligent tailgate operation, accurately perceive the vehicle's surrounding environment, effectively avoid the risk of collision caused by environmental interference or single sensor misjudgment, and dynamically calculate the target safety distance for adjustment according to different scenarios and user needs, optimize the tailgate operation space, and enhance the user experience. In addition, the introduction of the user tailgate closing command can make the tailgate control more convenient and diversified, meeting the personalized needs of different users.

[0066] For ease of understanding, obtaining obstacle information and target safety distance is taken as an example for explanation, wherein the information collection device is an information collection module, and the storage device is a memory.

[0067] The information acquisition module obtains the tailgate activity distance, human activity space and scene intervention information, that is, it collects data in real time through a multi-sensor fusion system, where the multi-sensor fusion system can be composed of a binocular camera, a millimeter-wave radar and an ultrasonic sensor. The binocular camera is used to resist strong light / weak light interference and generate a 3D point cloud around the vehicle in real time. The millimeter-wave radar is used to detect obstacle distances in all weather conditions, such as a coverage range of 0.1m-50m. The ultrasonic sensor is used for close-range precise distance measurement, such as 0.05m-2m, to perform redundancy verification, detect obstacle characteristics, and determine obstacles. Obstacle information includes the distance to the obstacle in front of the vehicle, the distance to the obstacle behind the vehicle, and the obstacle type. That is, the binocular camera detects the distance L1 from the rear of the vehicle to the obstacle and the obstacle type to obtain the distance L1 to the obstacle behind the vehicle and the obstacle type, where the obstacle types include static and dynamic. The millimeter-wave radar verifies the distance L1 to the obstacle behind the vehicle and detects the distance from the front of the vehicle to the obstacle in front to obtain the distance L2 to the obstacle in front of the vehicle. The ultrasonic sensor is used to verify the position of close-range obstacles, where close distance refers to a distance less than 2m from the obstacle position, thereby obtaining obstacle information. A safety distance is selected based on the tailgate movement distance and the human movement space, and the safety distance threshold weight is adjusted according to the scene intervention information to determine the target safety distance. That is, different vehicle models require different movement distances. Therefore, the tailgate opening envelope distance can be dynamically set according to vehicle model parameters to obtain the tailgate movement distance A1. The tailgate movement distance is the straight-line length of the tailgate when it opens in a curved arc. In order to ensure the safety space for the human body, it is obviously necessary to pre-set a certain safety distance to prevent unexpected emergencies. Therefore, the human movement space can be composed of two parts, one of which is the user-defined value A2_1, and the other is the user's body width dimension A2_2 detected in real time by the TOF camera. In this case, the human movement space A2 can be expressed as:

[0068] A2=A2_1+A2_2

[0069] Afterwards, the tailgate activity distance A1 and the human activity space A2 are compared, and the maximum value is selected as the target safety distance, such as Figure 3 As shown, Figure 3 The adaptive automobile tailgate control method of multi-sensor fusion and dynamic path planning in this application sets the human activity space as the target safety distance diagram. At this time, the arc of the tailgate opening is small, and its tailgate activity distance A1 is smaller than the human activity space A2. The obstacle distance should obviously be the human activity distance. In order to achieve safe obstacle avoidance, the human activity space A2 should obviously be used as the reference target safety distance. Figure 4 As shown, Figure 4The adaptive tailgate control method for this application using multi-sensor fusion and dynamic path planning sets the tailgate movement distance as the target safety distance. At this point, the tailgate opens with a large arc, and its tailgate movement distance A1 is larger than the human movement space A2. The obstacle distance should obviously be the distance when the tailgate is fully extended. To achieve safe obstacle avoidance, the tailgate movement distance A1 should obviously be used as a reference for the target safety distance, thereby obtaining the target safety distance. That is, the user can send a tailgate control request through gesture recognition, voice tailgate closing command, or a mobile phone app, such as waving twice, saying "close tailgate," or operating the terminal to control the tailgate. The user activity information is then used to identify the tailgate closing request feature. At this point, the tailgate can be closed and the user tailgate closing command is obtained.

[0070] In a feasible implementation, step S10 may include steps A11 to A13:

[0071] Step A11, obtaining tailgate activity distance, human activity space, and scene intervention information;

[0072] It should be noted that the tailgate activity distance is the distance range that the tailgate needs to move during the opening or closing process, the human activity space is the activity space required by the user during the tailgate operation process, and the scene intervention information is information for adjusting the tailgate operation strategy according to the scene in which the vehicle is located.

[0073] It is understandable that the tailgate activity distance can be dynamically adjusted according to the vehicle's tailgate design and user needs. It is the straight-line length when the tailgate opens in a curved arc. The human activity space needs to include sudden activities during human movement, such as the minimum space required for users to pick up and put away luggage. The scene intervention information needs to identify multiple current scenes, such as the obstacle layout or space restrictions in the scene, to dynamically adjust the safety distance threshold weight to better adapt to obstacle avoidance in the current scene.

[0074] In addition, it should be noted that AI learning optimization can be used. If the user manually intervenes in the same scene multiple times, the AI module will automatically record and optimize, adjust the safety distance threshold under the scene, and update the path planning strategy, such as giving priority to straight-line reversing rather than a roundabout path.

[0075] Step A12: Detect obstacle features and determine obstacle information, including obstacle distance in front of the vehicle, obstacle distance behind the vehicle, and obstacle type.

[0076] It should be noted that the obstacle distance in front of the vehicle is the horizontal distance between the front of the vehicle and the obstacle, the obstacle distance behind the vehicle is the horizontal distance between the rear of the vehicle and the obstacle, and the obstacle type is the nature and characteristics of the obstacle, such as a wall, vehicle, pedestrian or other object.

[0077] It can be understood that the obstacle distance in front of the vehicle is used to evaluate the safe distance in front of the vehicle, which can be directly detected by the vehicle's sensors. The obstacle distance behind the vehicle is used to evaluate the safe distance when the tailgate is opened or closed, which can also be directly detected by the vehicle's sensors. The obstacle type can classify different obstacles, and personalized obstacle avoidance can be performed for certain objects that need to be avoided. For example, for an irregular stone object, the distance closest to the rear end of the vehicle needs to be used as the actual safe distance. Accurate identification of environmental changes can enable adaptive obstacle avoidance.

[0078] In addition, it should be noted that obstacle characteristics are used to identify the specific status and properties of obstacles around the vehicle, including the location, distance, type, size and dynamic properties of the obstacles. These characteristics can be obtained through real-time detection and analysis by the vehicle's multi-sensor fusion system to provide accurate environmental information for tailgate control, thereby performing adaptive obstacle avoidance.

[0079] Step A13: selecting a safety distance based on the tailgate movement distance and the human movement space, and adjusting the safety distance threshold weight according to the scene intervention information to determine a target safety distance;

[0080] It can be understood that the safety distance is the minimum distance that needs to be set to ensure the safety of the vehicle and the user during the tailgate operation. This safety distance can ensure that the tailgate will not collide with obstacles when opening or closing, while providing the user with sufficient operating space. The safety distance threshold weight is the weight coefficient that adjusts the safety distance according to different scenarios and user needs when calculating the target safety distance. It is used to optimize the calculation of the safety distance to better suit actual usage scenarios and user habits.

[0081] Step S20, planning a safe path and a target safe area for the vehicle based on the obstacle information and the target safety distance, and controlling the vehicle's tailgate to open to determine rear space information, where the rear space information is the actual movement space between the vehicle's tailgate and the obstacle identified after the vehicle's tailgate is opened;

[0082] It can be understood that planning a safe vehicle path is based on obstacle information and target safety distance, and uses dynamic path planning algorithms, such as the improved A* algorithm, to generate a path that can avoid obstacles and ensure the safety of tailgate operation. This path not only takes into account the distance between the rear of the vehicle and the obstacle, but also reserves sufficient safety redundancy to ensure that the vehicle does not collide during movement. Adjusting the target direction of the vehicle is based on the planned safe path. Through the vehicle's steering system, such as the EPS electric power steering system, the vehicle's driving direction is adjusted so that it can accurately move to the target position along the planned path.

[0083] In addition, it should be noted that the target safety area is the safe location area that the vehicle needs to reach during the path planning process. The boundary of the target safety area can be calculated based on the path planning to always adapt to changes in the surrounding environment. Within this target safety area, no matter how the door is opened, it will not collide with obstacles, which significantly improves safety.

[0084] For ease of understanding, the following description is made by taking the determination of the rear space information as an example, wherein the information collection device is the information collection module, the storage device is the memory, and the processing device is the processing module.

[0085] The information acquisition module obtains obstacle information and target safety distance, identifies vehicle adjustment space based on the obstacle information and the target safety distance, determines vehicle safety redundancy and vehicle activity space working condition information, plans vehicle safety path and target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, determines vehicle planning position information and vehicle target tailgate deployment angle, that is, when the vehicle activity space working condition information indicates insufficient space at the rear of the vehicle, starts the dynamic path planning algorithm.

[0086] Among them, the dynamic path planning algorithm may include environmental modeling and initialization, improved AI algorithm, real-time dynamic adjustment, collaborative optimization of AI learning modules, and output and execution. In the environmental modeling and initialization stage, the input data includes a 3D point cloud model of the vehicle provided by the multi-sensor fusion system and the coordinates of the safety area required for opening or closing the tailgate. Subsequently, the vehicle's surrounding environment is divided into 10cm×10cm grid units to form a gridded map, and the grid is marked, that is, the grid where the obstacle is located is marked as impassable, the grid in the safety area is marked as passable, and the area where dynamic obstacles may appear is marked as probabilistically passable.

[0087] In the improved AI algorithm stage, the open list and the closed list are first initialized, where the open list is used to store the nodes to be explored, and the initial value is the current position of the vehicle, while the closed list is used to store the explored nodes, which is initially empty. Then the node expansion and cost calculation are performed: the movement cost G value includes the basic cost, the straight-line movement cost is 1, the diagonal movement cost is the square root of 2, and the dynamic weight factor, which is dynamically adjusted according to the obstacle density, such as multiplying the weight by 1.5 in dense areas. The heuristic cost H value uses the Manhattan distance to estimate the cost to the target point, and adds an additional 20% safety redundancy when the target point is in a narrow area. The total cost is expressed as:

[0088] F=G+H

[0089] The node with the lowest total cost is selected from the open list. If the current node is the target, a path is generated; otherwise, its 8-neighborhood grid is expanded. For each neighboring node, if it is an obstacle or already in the closed list, it is skipped. If it is passable, its G value is updated and it is added to the open list. The above steps are repeated until a path is found or the open list is empty. Path post-processing is then performed: the path is smoothed using a Bezier curve to generate an "S-shaped" circuitous trajectory, and a lateral clearance of ≥200mm is reserved on both sides of the path to avoid static obstacles.

[0090] During the real-time dynamic adjustment phase, the system provides both sudden obstacle response and path correction control. When a new obstacle is detected intruding into the planned path, the system immediately pauses execution of the current path and reruns the A* algorithm within 100 milliseconds to generate a detour. Simultaneously, the system monitors the vehicle's offset in real time through the onboard EPS. If the offset exceeds 50 mm, a correction command is triggered. At this point, the system calculates the corrected angular velocity according to the formula:

[0091] Δθ=arctan(offset / vehicle speed)

[0092] And control the steering wheel to make fine adjustments to ensure that the vehicle can accurately track the planned path.

[0093] During the collaborative optimization phase of the AI learning module, the system optimizes the path planning strategy through scene feature extraction and dynamic weight adaptation mechanisms. First, the system records high-frequency scene parameters, such as the height of a home basement and the size of a shopping mall parking space, and extracts key decision points in path planning, such as areas with frequent detours. Based on this historical data, the system trains a decision tree model to optimize the dynamic weight factor. For example, in a narrow alley scenario, the system automatically reduces the weight of diagonal movement and prioritizes straight-line movement, thereby improving the efficiency and adaptability of path planning.

[0094] During the output and execution phase, the system uses AR-HUD projection technology to visualize the planned path and safe areas for the driver. A green curve indicates a safe path, while a red area warns of obstacles. The system also converts path coordinates into specific vehicle control commands. For example, during a straight-ahead phase, the vehicle speed is set to 0.5 m / s and the steering angle to 0°; during a roundabout phase, the speed is adjusted to 0.3 m / s and the steering angle to 15°, thus achieving precise vehicle control.

[0095] Detection standards are pre-set on the left and right sides, such as 10cm. When the left side is less than the preset standard, the vehicle is adjusted to the right, and when the right side is less than the standard, the vehicle is adjusted to the left, thereby generating an "S-shaped" detour path to avoid side obstacles such as walls and pillars. During the movement, the path offset is monitored in real time. If the deviation is greater than a preset threshold, such as 50mm, the correction mechanism is triggered to fine-tune the direction through the EPS system to obtain the vehicle's planned position information. After reaching the target position, the vehicle's target tailgate deployment angle is the preset angle, where the preset angle is manually pre-set. At this time, the tailgate opens at the preset angle, and the opening path and safety area are projected through the AR-HUD. When the vehicle activity space working condition information shows that there is sufficient space at the rear of the vehicle, the vehicle's target tailgate deployment angle is the maximum angle, where the maximum angle is set according to the vehicle model, and the maximum deployment angle of different vehicles may also be different. The tailgate is opened to the maximum angle, and the AR-HUD prompts "The safety area is unobstructed."

[0096] Based on the target safety distance, the planned vehicle position information and the target tailgate deployment angle of the vehicle, the vehicle tailgate is controlled to open to obtain the rear space information. That is, after the vehicle enters the target safety area and opens the tailgate, the distance from the obstacle behind the vehicle after the tailgate is opened is detected, and the distance to the rear obstacle is detected using the millimeter wave radar to obtain the rear space information L3.

[0097] If an obstacle is detected entering the safe distance during the opening process, such as a pedestrian approaching, the tailgate will immediately pause and move in the opposite direction a preset distance, such as 5cm, while triggering an audible and visual alarm.

[0098] Step S30, obtaining the user's tailgate closing instruction, controlling the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and controlling the vehicle to enter the target parking area for parking, where the target parking area is the parking area identified by the vehicle.

[0099] It should be noted that the user's tailgate closing command includes a gesture tailgate closing command, a voice tailgate closing command and an application tailgate closing command. The gesture tailgate closing command is a control command issued by the user to the vehicle through a specific gesture action, the voice tailgate closing command is a control command issued by the user to the vehicle through a voice command, and the application tailgate closing command is a control command issued by the user through a mobile phone application or an operating interface on other smart devices.

[0100] It is understood that the target parking area is a parking area identified by the vehicle, such as a parking lot or road boundary and a designated parking area. Parking the vehicle in the target parking area can maximize vehicle safety and avoid corresponding safety hazards, such as Figure 5 As shown, Figure 5This is an example diagram of the AR-HUD interactive interface of the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning in this application, which can display the tailgate path and safety area in this scenario. The tailgate path is an arc, and the safety area is a green area, followed by an obstacle area.

[0101] In addition, it should be noted that the use of the user's tailgate closing command can enable the system to meet the operational needs of different users in different scenarios, significantly improving the convenience and flexibility of interaction. Users can choose the most appropriate operation method according to their habits and current environment without relying on a single control method, which significantly improves the system's usability and user experience. The vehicle activity space is the available space range around the rear of the vehicle for vehicle movement and operation during the tailgate closing process, and the vehicle clearance is the actual distance between the rear of the vehicle and surrounding obstacles.

[0102] For ease of understanding, the following is an example of obtaining obstacle information, rear space information, target safety distance, and user tailgate closing instructions, where the information collection device is an information collection module, the storage device is a memory, and the execution device is an execution module.

[0103] The information acquisition module obtains obstacle information, rear space information, target safety distance and user tailgate closing instruction, identifies the space to be adjusted for the vehicle tailgate based on the obstacle information, the rear space information, the target safety distance and the user tailgate closing instruction, and determines the vehicle activity space information, that is, the user sends a closing request through gesture recognition, voice command or mobile phone APP, performs dual redundant detection, the millimeter wave radar detects the distance to the rear obstacle, obtains the rear space information L3, the binocular camera verifies the rear space information L3 and identifies the obstacle type, such as a wall or a vehicle, if the rear space information L3 is greater than or equal to the target safety distance, the vehicle activity space information is that the rear space is sufficient, if the rear space information L3 is less than the target safety distance, the vehicle activity space information is that the rear space is insufficient, and the vehicle gap is detected based on the vehicle activity space information to determine the adjustment response information, that is, whether the vehicle gap needs to be adjusted to ensure that The rear obstacle maintains a preset gap, such as 100mm, and an adjustment response message is obtained. If there is sufficient space to allow adjustment or insufficient space to allow adjustment, when the adjustment response message is that there is sufficient space to allow adjustment, the vehicle is controlled to close the tailgate and adjust the vehicle gap to enter the target parking area. That is, when the adjustment response message is that there is sufficient space to allow adjustment, the tailgate is closed at a constant speed. After closing, the vehicle automatically moves backward until a gap of 100mm is maintained with the rear obstacle, and the AR-HUD displays "Tailgate closed, vehicle position adjusted". When the adjustment response message is that there is insufficient space to adjust, the vehicle is controlled to generate feedback detailed adjustment suggestions and issue an audible and visual alarm. That is, when the adjustment response message is that there is insufficient space to adjust, a level 3 alarm is triggered, a pop-up window is displayed on the vehicle screen prompting "Insufficient space at the rear, cannot be closed", and a mobile phone APP pushes detailed adjustment suggestions, such as "Move forward 0.5 meters", and an audible and visual alarm is issued, such as the double flash lights and buzzer lasting 10 seconds.

[0104] In a feasible implementation, step S30 may include steps B11 to B12:

[0105] Step B11, identifying the space to be adjusted for the vehicle's tailgate based on the obstacle information, the vehicle's rear space information, the target safety distance, and the user's tailgate closing instruction, and determining vehicle activity space information;

[0106] It should be noted that the vehicle activity space information is specific data of the available space around the rear of the vehicle that can be used for tailgate operation and vehicle movement.

[0107] It is understandable that the vehicle activity space information may include the horizontal and vertical distances between the rear of the vehicle and obstacles, the space range required for opening or closing the tailgate, and the additional space required by users when picking up and placing luggage. It can perceive changes in the environment around the rear of the vehicle in real time to dynamically adjust the tailgate operation strategy, significantly improve the safety and convenience of tailgate operation, and avoid collision risks caused by obstacles. At the same time, combined with obstacle information and target safety distance, the vehicle's movement path can be optimized to ensure that the tailgate can be operated smoothly when opening or closing, providing users with sufficient space, better coping with complex and changing usage scenarios, and significantly improving user experience.

[0108] In addition, it should be noted that the space to be adjusted of the vehicle tailgate is an adjustable range reserved to ensure that the tailgate can be opened and closed normally, and effective obstacle avoidance is achieved by adjusting the position and angle of the tailgate.

[0109] Step B12: controlling the vehicle to close its tailgate based on the vehicle activity space information, and controlling the vehicle to enter a target parking area for parking.

[0110] It is understandable that by detecting the gap between vehicles, the risk of collision caused by insufficient space or interference from obstacles can be avoided. By dynamically adjusting the vehicle position and optimizing the tailgate closing strategy, it can better adapt to complex and changing usage scenarios, significantly improving the system's intelligence level and user experience.

[0111] In a feasible implementation, step B12 may include steps C11 to C13:

[0112] Step C11, detecting the vehicle gap based on the vehicle activity space information, and determining adjustment response information;

[0113] It should be noted that the adjustment response information is adjustment suggestions or feedback information on the vehicle tailgate operation generated by the system based on the vehicle activity space information and the vehicle gap detection result.

[0114] It can be understood that the adjustment response information can represent the judgment of the vehicle clearance. If the vehicle clearance is sufficient, the adjustment response information can be used to control the vehicle to safely close the tailgate. If the vehicle clearance is insufficient, the adjustment response information can be used to control the vehicle to move or adjust its position first, thereby effectively avoiding obstacles.

[0115] Additionally, it should be noted that the vehicle gap is the space or distance reserved between vehicle body components or between the vehicle and its surroundings to ensure that the tailgate can open and close normally.

[0116] Step C12: When the adjustment response information indicates that the space is sufficient and adjustment is allowed, controlling the vehicle to close the tailgate and adjust the vehicle clearance to enter the target parking area;

[0117] It can be understood that when the adjustment response information indicates that there is sufficient space to allow adjustment, the system detects that the gap between the rear of the vehicle and the surrounding obstacles is large enough to meet the safety distance requirements for the tailgate closing operation. At this time, the system will generate a response signal allowing the vehicle to close the tailgate and adjust the vehicle gap, control the vehicle to close the tailgate and adjust the vehicle gap to enter the target parking area, and ensure that the tailgate does not collide with obstacles during the closing process.

[0118] Step C13: When the adjustment response information indicates that the space is insufficient and cannot be adjusted, the vehicle is controlled to generate feedback of detailed adjustment suggestions and issue an audible and visual alarm.

[0119] It is understandable that when the adjustment response information is insufficient space and cannot be adjusted, the system detects that the gap between the rear of the vehicle and the surrounding obstacles is insufficient to meet the safety distance requirements for the tailgate closing operation. At this time, the system will generate a feedback signal, indicating that the tailgate closing operation cannot be performed safely under the current environment, and prompts the user to take further adjustment measures.

[0120] This embodiment proposes an adaptive automobile tailgate control method using multi-sensor fusion and dynamic path planning, which obtains obstacle information and a target safety distance; plans a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, controls the vehicle to open the tailgate, and determines the rear space information; obtains a user's tailgate closing instruction, controls the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance, and the user's tailgate closing instruction, and controls the vehicle to enter a target parking area for parking, where the target parking area is a parking area identified by the vehicle. It solves the technical problem of how to intelligently adjust the vehicle position for personalized control of the vehicle tailgate. Compared with the existing technology, this application uses binocular cameras, millimeter-wave radars, ultrasonic sensors and other equipment to perceive the vehicle's surrounding environment in real time, achieve accurate environmental perception, and reduce the misjudgment rate based on multi-sensor fusion. It also plans the vehicle's safe path based on the improved A* algorithm, automatically adjusts the vehicle's target direction, and realizes intelligent vehicle moving. Dynamic path planning supports narrow alley scenarios, improves applicability, realizes effective control of the vehicle's tailgate, improves the safety of tailgate control, optimizes the user's operating experience, and has a humanized design. The TOF camera realizes "one person, one space" and is suitable for more than 95% of user body shapes. The scene mode reduces user operation steps, gesture control and AR prompts reduce learning costs, combined with emergency reverse braking and dual redundant detection, the risk of accidents is reduced, and the intelligence level and adaptability of the system are significantly enhanced.

[0121] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction and will not be repeated later.

[0122] In this embodiment, refer to Figure 6 , Figure 6 This is a flow chart of the second embodiment of the adaptive automobile tailgate control method using multi-sensor fusion and dynamic path planning of this application. Step S20 specifically includes steps S21 to S23:

[0123] Step S21, identifying the vehicle adjustment space based on the obstacle information and the target safety distance, and determining vehicle safety redundancy and vehicle activity space working condition information;

[0124] It should be noted that the vehicle safety redundancy is an additional safety distance set during tailgate operation to ensure the safety of the vehicle and the user, and the vehicle activity space operating condition information is detailed information on the specific state of the environment around the rear of the vehicle and the available space.

[0125] It can be understood that the vehicle safety redundancy is a safety buffer distance further increased on the basis of the calculated target safety distance, which is used to deal with emergencies or sensor misjudgments. The vehicle activity space operating condition information can represent the system's ability to dynamically adjust the tailgate operation strategy according to environmental changes, thereby improving the system's intelligence level and user experience, and enhancing the system's adaptability in complex environments.

[0126] In addition, it should be noted that the vehicle adjustment space is the position range that needs to be adjusted after the vehicle is captured by the recognition device in order to more accurately identify the vehicle. For example, when the vehicle enters the license plate recognition area of the parking lot, the vehicle adjustment space is the area where the vehicle can be placed in the best obstacle avoidance position by moving forward and backward, left and right, and other operations.

[0127] For ease of understanding, the following is explained by taking determination of vehicle safety redundancy and vehicle activity space working condition information as an example, wherein the information collection device is an information collection module, the storage device is a memory, and the processing device is a processing module.

[0128] The information acquisition module obtains obstacle information and target safety distance, identifies vehicle adjustment space based on the obstacle information and target safety distance, and determines vehicle safety margin and vehicle activity space working condition information. That is, when the obstacle distance L1 behind the vehicle in the obstacle information is less than the target safety distance, the vehicle activity space working condition information indicates insufficient rear space. In this case, the vehicle automatically moves forward, and the safety margin is calculated, that is, the moving distance is expressed as:

[0129] D=A-L1+100mm

[0130] The 100mm in the formula can be adjusted according to actual conditions.

[0131] When the obstacle distance L1 behind the vehicle in the obstacle information is greater than the target safety distance, the vehicle activity space working condition information shows that there is sufficient space at the rear of the vehicle. At this time, there is no need for safety redundancy, the tailgate can be opened directly to the maximum angle, and the AR-HUD prompts "the safe area is unobstructed".

[0132] When the obstacle distance L2 in front of the vehicle is less than the difference between the target safety distance and the obstacle distance L1 behind the vehicle in the obstacle information, the vehicle activity space working condition information is insufficient space in front, and a prompt "Obstacle ahead is blocked, manual adjustment of parking space is recommended" is pushed through the mobile phone APP, and the obstacle position and recommended operations are displayed on the vehicle screen, such as "Reverse 0.3 meters".

[0133] Step S22, planning a vehicle safety path and a target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, and determining the vehicle planned position information and the vehicle target tailgate deployment angle;

[0134] It should be noted that the vehicle planned position information is the specific coordinate information of the target position to which the vehicle needs to move during the tailgate operation, and the vehicle target tailgate deployment angle is the target angle that the tailgate needs to reach during the opening process.

[0135] It can be understood that the use of the vehicle's planned position information can enable the vehicle to safely move to the target position during the tailgate operation and smoothly open the tailgate, while using the vehicle's target tailgate deployment angle to open the tailgate can prevent the tailgate from colliding with surrounding obstacles when opening and leave sufficient operating space for the user.

[0136] For ease of understanding, the following description is made by taking the determination of the planned vehicle position information and the target tailgate deployment angle of the vehicle as an example, wherein the information collection device is the information collection module, the storage device is the memory, and the processing device is the processing module.

[0137] The information acquisition module obtains the path offset, plans a safe path for the vehicle based on the vehicle activity space operating condition information and the dynamic path planning algorithm, and provides feedback with recommended adjustments to determine a detour path and a target tailgate deployment angle. Specifically, when the vehicle activity space operating condition information indicates insufficient rear space, the dynamic path planning algorithm is activated, and detection standards are pre-set on the left and right sides, such as 10 cm. If the left side is less than the pre-set standard, the vehicle is adjusted to the right, and if the right side is less than the standard, the vehicle is adjusted to the left, thereby generating an "S-shaped" detour path to avoid side obstacles such as walls and pillars. Upon reaching the target position, the vehicle's target tailgate deployment angle is a preset angle, where the preset angle is manually pre-set. At this point, the tailgate opens at the preset angle, and the opening path and safety zone are projected on the AR-HUD. When the vehicle activity space operating condition information indicates sufficient rear space, the vehicle's target tailgate deployment angle is the maximum angle, where the maximum angle is set based on the vehicle model and may vary from vehicle to vehicle. The tailgate is then opened to the maximum angle, and a prompt "Safety Zone Unobstructed" is displayed on the AR-HUD. The vehicle movement is controlled according to the vehicle safety redundancy and the circuitous path, and the vehicle correction mechanism is triggered to adjust the vehicle target direction according to the path offset to obtain the vehicle planned position information. That is, during the movement process, the path offset is monitored in real time. If the deviation is greater than a preset threshold, such as 50mm, the correction mechanism is triggered to fine-tune the direction through the EPS system, thereby obtaining the vehicle planned position information.

[0138] In a feasible implementation, step S22 may include steps D11 to D13:

[0139] Step D11, obtaining the path offset;

[0140] It should be noted that the path offset is the deviation distance between the actual driving trajectory of the vehicle and the planned path when the vehicle moves along the planned safe path.

[0141] It is understandable that the path offset can be monitored in real time by the vehicle's sensor system, such as GPS, IMU and camera, to evaluate the tracking accuracy of the vehicle during movement. The larger the path offset, the greater the distance that needs to be adjusted.

[0142] Step D12, planning a safe path for the vehicle based on the vehicle activity space operating condition information and a dynamic path planning algorithm, and providing feedback on recommended adjustments to determine a circuitous path and a target tailgate deployment angle for the vehicle;

[0143] It should be noted that the circuitous path is a non-linear path that bypasses obstacles or other restrictions when the vehicle encounters obstacles or other restrictions during tailgate operation, and is generated by the system through a dynamic path planning algorithm.

[0144] It can be understood that the circuitous path can enable the vehicle to safely avoid obstacles when the tailgate is opened or closed while maintaining the stability of the vehicle, wherein the specific shape and length of the circuitous path depend on the location and size of the obstacle and the distance between the vehicle and the obstacle.

[0145] Additionally, it should be noted that the recommended adjustment suggestion is a lateral adjustment suggestion generated based on the actual obstacle situation, such as adjusting the vehicle left or right to avoid collision with the obstacle.

[0146] Step D13: Control the movement of the vehicle according to the vehicle safety redundancy and the detour path, and trigger the vehicle correction mechanism to adjust the vehicle target direction according to the path offset to obtain the vehicle planned position information.

[0147] It can be understood that by combining vehicle safety redundancy and detour paths to control the vehicle, the vehicle's movement trajectory and speed can be dynamically adjusted to complete tailgate control safely and efficiently in complex environments. Among them, vehicle safety redundancy provides an additional safety buffer distance for tailgate operation, while the detour path ensures that the vehicle can avoid obstacles and reach the target location.

[0148] In addition, it should be noted that the vehicle correction mechanism monitors the vehicle's driving status in real time. When it detects that the vehicle deviates from the predetermined route, the system will calculate the optimal correction strategy based on the degree of vehicle deviation and trajectory trend, and adjust the vehicle's target direction, such as by controlling the vehicle's left and right steering, combined with the throttle and braking systems to achieve correction, such as controlling the vehicle's steering through an electric drive to perform correction.

[0149] Step S23 , controlling the vehicle to open the tailgate based on the target safety distance, the planned vehicle position information, and the target tailgate deployment angle of the vehicle to obtain rear space information.

[0150] It can be understood that the rear space information can characterize the specific state and available space of the environment around the rear of the vehicle. By combining the rear space information for control, the changes in the environment around the rear of the vehicle can be accurately perceived, and the tailgate can be effectively controlled to avoid the risk of collision due to insufficient space or obstacles.

[0151] For ease of understanding, the following description is made by taking the determination of the rear space information as an example, wherein the information collection device is the information collection module, the storage device is the memory, and the processing device is the processing module.

[0152] The information acquisition module obtains the obstacle burst detection frequency, detects the obstacle burst characteristics based on the obstacle burst detection frequency, and determines the obstacle burst information. The obstacle burst information includes the obstacle burst distance and obstacle type. That is, during the tailgate opening or closing process, the ultrasonic sensor detects the distance between the tailgate and the obstacle and the obstacle type at a frequency of 100Hz. If the obstacle distance is less than or equal to a preset threshold, such as 20mm, the tailgate movement is immediately paused and an alarm is triggered. The obstacle avoidance urgency is analyzed based on the obstacle burst distance, the obstacle type and the target safety distance, and the vehicle's emergency obstacle avoidance mode is determined. The vehicle obstacle avoidance mode includes pausing and unfolding the tailgate, moving the vehicle in the opposite direction, and sound and light alarms. That is, if an obstacle is detected to have entered a safe distance during the opening process, such as a pedestrian approaching, the obstacle avoidance urgency is analyzed, and the vehicle emergency obstacle avoidance mode is determined, such as immediately pausing the tailgate, moving the vehicle in the opposite direction a preset distance, such as 5 cm, or triggering an sound and light alarm. Based on the vehicle emergency obstacle avoidance mode, the vehicle is controlled to make emergency avoidance of the sudden movement of the obstacle, that is, after the vehicle is controlled to enter the target safe area and open the tailgate, the distance from the obstacle behind the vehicle after the tailgate is opened is detected, and the distance to the rear obstacle is detected using the millimeter-wave radar to obtain the rear space information L3.

[0153] In a feasible implementation, step S23 may include steps E11 to E14:

[0154] Step E11, obtaining the obstacle sudden detection frequency;

[0155] It should be noted that the sudden obstacle detection frequency is the ratio of the number of times the system detects sudden obstacles in the surrounding area during tailgate operation to the unit time. It is used to evaluate the dynamic changes in the vehicle's surrounding environment and determine whether emergency obstacle avoidance measures are needed.

[0156] It is understandable that the system has a self-checking and fault-tolerant mechanism, which verifies the consistency of sensor data every predetermined time threshold, such as 5 seconds. If the deviation exceeds the preset threshold, such as 10%, it switches to redundant sensor dominance and enables the local decision-making module based on the pre-stored scenario library when the network is interrupted.

[0157] Step E12: detecting obstacle burst characteristics based on the obstacle burst detection frequency, and determining obstacle burst information, wherein the obstacle burst information includes obstacle burst distance and obstacle type;

[0158] It should be noted that the sudden obstacle information is data detected by the system regarding the sudden appearance or movement of an obstacle during the tailgate operation.

[0159] It can be understood that the use of the sudden obstacle information can perceive the specific situation of sudden obstacles around the vehicle in real time, quickly evaluate the urgency of obstacle avoidance and take corresponding emergency obstacle avoidance measures, reduce the risk of collision caused by sudden obstacles, enhance the adaptability and fault tolerance of the system, and enable it to control the tailgate more safely in complex and changing environments.

[0160] In addition, it should be noted that the sudden features of obstacles are collected in real time using multiple sensors to extract characteristic information such as the shape, size, texture or reflection intensity of the obstacles, and the collected features are analyzed and classified to determine the position, posture, speed and movement trend of the obstacles.

[0161] Step E13: analyzing the urgency of obstacle avoidance based on the sudden obstacle distance, the obstacle type, and the target safety distance, and determining a vehicle emergency obstacle avoidance mode, wherein the vehicle obstacle avoidance mode includes tailgate pausing, vehicle reverse movement, and sound and light alarms;

[0162] It should be noted that the vehicle emergency obstacle avoidance mode is a series of preset emergency obstacle avoidance measures taken by the system according to the urgency of obstacle avoidance after detecting sudden obstacle information.

[0163] It is understandable that the specific selection of the vehicle emergency obstacle avoidance mode depends on the sudden distance, type, moving direction and speed factors of the obstacle, so as to effectively avoid obstacles and perform tailgate control more safely.

[0164] In addition, it should be noted that the obstacle avoidance urgency is the severity of the collision risk assessed by the system based on sudden obstacle information. It is a quantitative indicator used to measure the potential threat of the current sudden obstacle to the safety of tailgate operation. The higher the value, the greater the collision risk and the need for more urgent obstacle avoidance measures.

[0165] Step E14: controlling the vehicle to avoid sudden movement of an obstacle based on the vehicle emergency obstacle avoidance mode.

[0166] It can be understood that by implementing the control of the vehicle emergency obstacle avoidance mode, a quick response can be made when a sudden obstacle is detected, effectively avoiding the occurrence of collision accidents and significantly improving the safety and reliability of tailgate control.

[0167] This embodiment proposes an adaptive automobile tailgate control method using multi-sensor fusion and dynamic path planning. The method identifies the vehicle adjustment space based on the obstacle information and the target safety distance, determines the vehicle safety redundancy and vehicle activity space working condition information; plans the vehicle safe path and target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, determines the vehicle planned position information and the vehicle target tailgate deployment angle; and controls the vehicle to open the tailgate based on the target safety distance, the vehicle planned position information, and the vehicle target tailgate deployment angle, thereby obtaining the vehicle tailgate space information. This method solves the technical problem of how to intelligently adjust the vehicle position for personalized vehicle tailgate control. Compared with the prior art, this application obtains obstacle information and target safety distance, identifies the vehicle adjustment space, and determines the vehicle safety redundancy and activity space working condition information, thereby planning the vehicle safe path, adjusting the vehicle target direction, determining the vehicle planned position information and tailgate deployment angle, controlling the vehicle to enter the target safety area to open the tailgate, and determining the vehicle tailgate space information. It realizes intelligent vehicle maneuvering, and dynamic path planning supports narrow alley scenarios. It improves applicability, realizes effective control of the vehicle tailgate, improves the safety of tailgate control, optimizes the user operation experience, enhances the intelligence level and adaptability of the system, and better copes with complex and changing usage scenarios.

[0168] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the adaptive automobile tailgate control method of multi-sensor fusion and dynamic path planning of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0169] This application also provides an adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning, please refer to Figure 7 The adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning includes:

[0170] Acquisition module 10, used to obtain obstacle information and target safety distance;

[0171] The processing module 20 is used to plan a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, and control the vehicle to open the tailgate and determine the rear space information;

[0172] The execution module 30 is used to obtain the user's tailgate closing instruction, control the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and control the vehicle to enter the target parking area for parking, where the target parking area is the parking area identified by the vehicle.

[0173] The acquisition module 10 is further used to obtain tailgate activity distance, human activity space and scene intervention information;

[0174] Detect obstacle features and determine obstacle information, including obstacle distance in front of the vehicle, obstacle distance behind the vehicle, and obstacle type;

[0175] A safety distance is selected based on the tailgate activity distance and the human activity space, and the safety distance threshold weight is adjusted according to the scene intervention information to determine a target safety distance.

[0176] The processing module 20 is further configured to identify the vehicle adjustment space based on the obstacle information and the target safety distance, and determine the vehicle safety redundancy and vehicle activity space working condition information;

[0177] Planning a vehicle safety path and a target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, and determining the vehicle planning position information and the vehicle target tailgate deployment angle;

[0178] The vehicle tailgate is controlled to open based on the target safety distance, the planned vehicle position information, and the target tailgate deployment angle of the vehicle to obtain rear space information.

[0179] The processing module 20 is further configured to obtain a path offset;

[0180] Planning a safe path for the vehicle based on the vehicle's activity space operating condition information and a dynamic path planning algorithm, and providing feedback with recommended adjustments to determine a circuitous path and a target tailgate deployment angle for the vehicle;

[0181] The vehicle movement is controlled according to the vehicle safety redundancy and the circuitous path, and the vehicle correction mechanism is triggered according to the path offset to adjust the vehicle target direction to obtain the vehicle planned position information.

[0182] The processing module 20 is further configured to obtain a sudden obstacle detection frequency;

[0183] detecting obstacle burst characteristics based on the obstacle burst detection frequency, and determining obstacle burst information, wherein the obstacle burst information includes obstacle burst distance and obstacle type;

[0184] Analyzing the obstacle avoidance urgency based on the obstacle sudden distance, the obstacle type, and the target safety distance, and determining a vehicle emergency obstacle avoidance mode, the vehicle obstacle avoidance mode including tailgate pausing, vehicle reverse movement, and sound and light alarms;

[0185] The vehicle is controlled to move in an emergency to avoid sudden obstacles based on the vehicle emergency obstacle avoidance mode.

[0186] The execution module 30 is further configured to identify the space to be adjusted for the vehicle tailgate based on the obstacle information, the vehicle tailgate space information, the target safety distance, and the user's tailgate closing instruction, and determine the vehicle activity space information;

[0187] The vehicle is controlled to close its tailgate based on the vehicle activity space information, and the vehicle is controlled to enter a target parking area for parking.

[0188] The execution module 30 is further configured to detect the vehicle gap based on the vehicle activity space information and determine adjustment response information;

[0189] When the adjustment response information indicates that there is sufficient space to allow adjustment, controlling the vehicle to close the tailgate and adjust the vehicle clearance to enter the target parking area;

[0190] When the adjustment response information indicates that the space is insufficient and cannot be adjusted, the vehicle is controlled to generate feedback of detailed adjustment suggestions and issue an audible and visual alarm.

[0191] The adaptive tailgate control device with multi-sensor fusion and dynamic path planning provided in this application, which employs the adaptive tailgate control method with multi-sensor fusion and dynamic path planning in the above-mentioned embodiments, can solve the technical problem of how to intelligently adjust the vehicle position for personalized tailgate control. Compared with the prior art, the beneficial effects of the adaptive tailgate control device with multi-sensor fusion and dynamic path planning provided in this application are the same as those of the adaptive tailgate control method with multi-sensor fusion and dynamic path planning provided in the above-mentioned embodiments. Other technical features of the adaptive tailgate control device with multi-sensor fusion and dynamic path planning are the same as those disclosed in the above-mentioned embodiments and are not further described here.

[0192] The present application provides an adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning. The adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning in the above-mentioned embodiment one.

[0193] Reference below Figure 8, which shows a schematic structural diagram of an adaptive automobile tailgate control device suitable for implementing multi-sensor fusion and dynamic path planning in the embodiments of the present application. The adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 8 The adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0194] like Figure 8 As shown, the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in ROM (Read Only Memory) 1002 or the program loaded from the storage device 1003 to RAM (Random Access Memory) 1004. In RAM 1004, various programs and data required for the operation of the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning are also stored. The processing device 1001, ROM 1002 and RAM 1004 are connected to each other via a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, hard disk, etc.; and communication devices 1009. Communication devices 1009 can allow the adaptive tailgate control device with multi-sensor fusion and dynamic path planning to communicate wirelessly or wired with other devices to exchange data. While the figure shows an adaptive tailgate control device with multi-sensor fusion and dynamic path planning having various systems, it should be understood that implementation or presence of all the illustrated systems is not required. More or fewer systems may alternatively be implemented or present.

[0195] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0196] The adaptive tailgate control device with multi-sensor fusion and dynamic path planning provided in this application, which employs the adaptive tailgate control method with multi-sensor fusion and dynamic path planning described in the aforementioned embodiment, can solve the technical problem of intelligently adjusting the vehicle's position for personalized tailgate control. Compared to the prior art, the adaptive tailgate control device with multi-sensor fusion and dynamic path planning provided in this application has the same beneficial effects as the adaptive tailgate control method with multi-sensor fusion and dynamic path planning described in the aforementioned embodiment. Other technical features of the adaptive tailgate control device with multi-sensor fusion and dynamic path planning are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0197] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0198] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0199] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, and the computer-readable program instructions are used to execute the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning in the above-mentioned embodiment.

[0200] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0201] The above-mentioned computer-readable storage medium can be included in the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning; or it can exist independently without being assembled into the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning.

[0202] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning, the adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning enables the following: to obtain obstacle information and target safety distance; to plan a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, and to control the vehicle to open the tailgate and determine the rear space information; to obtain a user's tailgate closing instruction, and to control the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and to control the vehicle to enter the target parking area for parking, where the target parking area is the parking area identified by the vehicle.

[0203] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0204] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0205] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0206] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned adaptive tailgate control method using multi-sensor fusion and dynamic path planning. This computer-readable storage medium addresses the technical problem of intelligently adjusting vehicle position for personalized tailgate control. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the adaptive tailgate control method using multi-sensor fusion and dynamic path planning provided in the aforementioned embodiments, and are not further elaborated here.

[0207] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. An adaptive automobile tailgate control method based on multi-sensor fusion and dynamic path planning, characterized in that: The method includes: Obtain obstacle information and target safety distance; Planning a safe path and a target safe area for the vehicle based on the obstacle information and the target safety distance, and controlling the vehicle's tailgate to open to determine rear space information, where the rear space information is the actual movement space between the vehicle's tailgate and the obstacle identified after the vehicle's tailgate is opened; Obtain a user's tailgate closing instruction, control the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and control the vehicle to enter a target parking area for parking, where the target parking area is a parking area identified by the vehicle.

2. The method according to claim 1, wherein The step of obtaining obstacle information and target safety distance includes: Obtain tailgate activity distance, human activity space and scene intervention information; Detect obstacle features and determine obstacle information, including obstacle distance in front of the vehicle, obstacle distance behind the vehicle, and obstacle type; A safety distance is selected based on the tailgate activity distance and the human activity space, and the safety distance threshold weight is adjusted according to the scene intervention information to determine a target safety distance.

3. The method according to claim 1, wherein The steps of planning a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, controlling the vehicle to open the tailgate, and determining the rear space information include: Identifying vehicle adjustment space based on the obstacle information and the target safety distance, and determining vehicle safety redundancy and vehicle activity space operating condition information; Planning a vehicle safety path and a target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, and determining the vehicle planning position information and the vehicle target tailgate deployment angle; The vehicle tailgate is controlled to open based on the target safety distance, the planned vehicle position information, and the target tailgate deployment angle of the vehicle to obtain rear space information.

4. The method according to claim 3, wherein The steps of planning a vehicle safety path and a target safety area based on the vehicle safety redundancy and the vehicle activity space working condition information, and determining the vehicle planning position information and the vehicle target tailgate deployment angle include: Get path offset; Planning a safe path for the vehicle based on the vehicle's activity space operating condition information and a dynamic path planning algorithm, and providing feedback with recommended adjustments to determine a circuitous path and a target tailgate deployment angle for the vehicle; The vehicle movement is controlled according to the vehicle safety redundancy and the circuitous path, and the vehicle correction mechanism is triggered according to the path offset to adjust the vehicle target direction to obtain the vehicle planned position information.

5. The method according to claim 3, wherein The step of controlling the vehicle to open the tailgate based on the target safety distance, the planned vehicle position information, and the target tailgate deployment angle to obtain the vehicle rear space information further includes: Obtain the sudden obstacle detection frequency; detecting obstacle burst characteristics based on the obstacle burst detection frequency, and determining obstacle burst information, wherein the obstacle burst information includes obstacle burst distance and obstacle type; Analyzing the obstacle avoidance urgency based on the obstacle sudden distance, the obstacle type, and the target safety distance, and determining a vehicle emergency obstacle avoidance mode, the vehicle obstacle avoidance mode including tailgate pausing, vehicle reverse movement, and sound and light alarms; The vehicle is controlled to move in an emergency to avoid sudden obstacles based on the vehicle emergency obstacle avoidance mode.

6. The method according to claim 1, wherein The steps of obtaining a tailgate closing instruction from a user, controlling the vehicle to close the tailgate based on the obstacle information, the vehicle rear space information, the target safety distance, and the tailgate closing instruction from the user, and controlling the vehicle to enter a target parking area for parking include: identifying a space to be adjusted for the vehicle's tailgate based on the obstacle information, the vehicle's rear space information, the target safety distance, and the user's tailgate closing instruction, and determining vehicle activity space information; The vehicle is controlled to close its tailgate based on the vehicle activity space information, and the vehicle is controlled to enter a target parking area for parking.

7. The method according to claim 6, wherein The step of controlling the vehicle to close the tailgate based on the vehicle activity space information and controlling the vehicle to enter the target parking area for parking further includes: detecting a vehicle gap based on the vehicle activity space information and determining adjustment response information; When the adjustment response information indicates that there is sufficient space to allow adjustment, controlling the vehicle to close the tailgate and adjust the vehicle clearance to enter the target parking area; When the adjustment response information indicates that the space is insufficient and cannot be adjusted, the vehicle is controlled to generate feedback of detailed adjustment suggestions and issue an audible and visual alarm.

8. An adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning, characterized in that: The device comprises: Acquisition module, used to obtain obstacle information and target safety distance; a processing module, configured to plan a vehicle safety path and a target safety area based on the obstacle information and the target safety distance, and control the vehicle to open the tailgate and determine the rear space information; The execution module is used to obtain a user's tailgate closing instruction, control the vehicle to close the tailgate based on the obstacle information, the rear space information, the target safety distance and the user's tailgate closing instruction, and control the vehicle to enter a target parking area for parking, where the target parking area is a parking area identified by the vehicle.

9. An adaptive automobile tailgate control device with multi-sensor fusion and dynamic path planning, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the adaptive automobile tailgate control method based on multi-sensor fusion and dynamic path planning as claimed in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a machine-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the adaptive automobile tailgate control method with multi-sensor fusion and dynamic path planning as described in any one of claims 1 to 7 are implemented.

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