Vehicle avoidance control method and device

Abstract

The application provides a vehicle avoidance control method and device, the method comprising: acquiring a camera image and acquiring a side-by-side target radar data; determining a target fixed offset and an offset adjustment amount according to the camera image and the side-by-side target radar data; generating an avoidance control instruction according to the target fixed offset and the offset adjustment amount; and controlling the target vehicle to perform a corresponding avoidance operation according to the avoidance control instruction. It can be seen that the method and device can adjust the offset according to different side-by-side vehicles and different lane widths, effectively reducing the panic or dissatisfaction of the driver caused by excessive or insufficient offset, thereby improving the use experience of automatic driving.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and more specifically, to a vehicle avoidance control method and device. Background Technology

[0002] Currently, with the rapid development of autonomous driving technology, more and more functions are emerging, and autonomous driving is being applied in more scenarios, including automatic obstacle avoidance. Automatic obstacle avoidance refers to the function where, when the vehicle's cruise control is activated, it deviates a certain distance when passing other vehicles to avoid causing driver panic and requiring the driver to take over the vehicle due to high-speed passage over other vehicles. Existing technology can only control the vehicle to avoid obstacles based on a fixed offset, which may be insufficient and cause driver panic. Therefore, the existing method has poor applicability, easily causing driver panic and thus reducing the driving experience. Summary of the Invention

[0003] The purpose of this application is to provide a vehicle avoidance control method and device that can adjust the offset according to different adjacent vehicles and different lane widths, effectively reducing the panic or dissatisfaction of the driver caused by excessive or insufficient offset, thereby improving the autonomous driving user experience.

[0004] The first aspect of this application provides a vehicle avoidance control method, including:

[0005] Acquire camera images and radar data of nearby vehicles;

[0006] The target fixed offset and offset adjustment amount are determined based on the camera image and the target radar data of the adjacent vehicle.

[0007] Generate an avoidance control command based on the target fixed offset and the offset adjustment amount;

[0008] The target vehicle is controlled to perform a corresponding avoidance operation according to the avoidance control command.

[0009] Further, determining the target fixed offset and offset adjustment amount based on the camera image and the adjacent vehicle target radar data includes:

[0010] The width of the lane in which the target vehicle is traveling is determined based on the camera image.

[0011] Determine the target fixed offset based on the lane width;

[0012] The target image data of the adjacent vehicle is obtained through the camera image;

[0013] The radar data and image data of the adjacent vehicle target are fused to obtain fused data.

[0014] The offset adjustment amount is determined based on the fused data.

[0015] Further, determining the target fixed offset based on the lane width includes:

[0016] Determine whether the lane width is greater than a preset first width threshold;

[0017] If it is greater than the preset first width threshold, then the preset first fixed offset is determined as the target fixed offset.

[0018] Furthermore, the method also includes:

[0019] If the width is not greater than the preset first width threshold, then it is determined whether the lane width is greater than the preset second width threshold; wherein the preset second width threshold is less than the preset first width threshold.

[0020] If it is greater than the preset second width threshold, then the preset second fixed offset is determined as the target fixed offset.

[0021] Further, determining the offset adjustment amount based on the fused data includes:

[0022] The type of vehicle beside the target vehicle is determined based on the fused data;

[0023] The new offset is determined based on the vehicle type and the preset offset calibration value.

[0024] A second aspect of this application provides a vehicle avoidance control device, the vehicle avoidance control device comprising:

[0025] The acquisition unit is used to acquire camera images and radar data of nearby vehicle targets.

[0026] The determining unit is used to determine the target fixed offset and offset adjustment amount based on the camera image and the adjacent vehicle target radar data;

[0027] A generation unit is used to generate avoidance control commands based on the target fixed offset and the offset adjustment amount;

[0028] The control unit is used to control the target vehicle to perform corresponding avoidance operations according to the avoidance control command.

[0029] Furthermore, the determining unit includes:

[0030] The first determining subunit is used to determine the lane width of the lane in which the target vehicle is traveling based on the camera image;

[0031] The second determining subunit is used to determine the target fixed offset based on the lane width;

[0032] The acquisition subunit is used to acquire target image data of the adjacent vehicle through the camera image;

[0033] The fusion subunit is used to fuse the radar data of the adjacent vehicle target and the image data of the adjacent vehicle target to obtain fused data;

[0034] The third determining subunit is used to determine the offset adjustment amount based on the fused data.

[0035] Further, the second determining subunit includes:

[0036] The judgment module is used to determine whether the lane width is greater than a preset first width threshold.

[0037] The determination module is used to determine the preset first fixed offset as the target fixed offset when it is determined that the lane width is greater than the preset first width threshold.

[0038] Furthermore, the judgment module is also used to determine whether the lane width is greater than a preset second width threshold when it is determined that the lane width is not greater than the preset first width threshold; wherein the preset second width threshold is less than the preset first width threshold;

[0039] The determining module is further configured to determine the preset second fixed offset as the target fixed offset when the lane width is greater than the preset second width threshold.

[0040] Furthermore, the third determining subunit is specifically used to determine the type of the adjacent vehicle target based on the fused data; and to determine the additional offset based on the type of the adjacent vehicle and a preset offset calibration value.

[0041] A third aspect of this application provides an electronic device including a memory and a processor, the memory storing a computer program, and the processor running the computer program to cause the electronic device to perform the vehicle avoidance control method described in any one of the first aspects of this application.

[0042] The fourth aspect of this application provides a computer-readable storage medium storing computer program instructions, which, when read and executed by a processor, perform the vehicle avoidance control method described in any one of the first aspects of this application.

[0043] The beneficial effects of this application are: the method and device can make different offset adjustments according to different adjacent vehicles and different lane widths, effectively reducing the panic or dissatisfaction of drivers caused by excessive or insufficient offset, thereby improving the user experience of autonomous driving. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A schematic flowchart illustrating a vehicle avoidance control method provided in an embodiment of this application;

[0046] Figure 2 A flowchart illustrating another vehicle avoidance control method provided in this application embodiment;

[0047] Figure 3 A schematic diagram of a vehicle avoidance control device provided in an embodiment of this application;

[0048] Figure 4 This is a schematic diagram of another vehicle avoidance control device provided in an embodiment of this application. Detailed Implementation

[0049] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0050] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0051] Example 1

[0052] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a vehicle collision avoidance control method provided in this embodiment. The vehicle collision avoidance control method includes:

[0053] S101. Acquire camera images and acquire radar data of nearby vehicle targets.

[0054] In this embodiment, the method can acquire forward-looking camera images through the forward-looking smart camera on the target vehicle, and acquire radar data of the adjacent vehicle target through the forward-looking radar on the target vehicle.

[0055] S102. Determine the target fixed offset and offset adjustment amount based on the camera image and the target radar data of the adjacent vehicle.

[0056] In this embodiment, the camera image is a front-view camera image.

[0057] S103. Generate avoidance control commands based on the target fixed offset and offset adjustment.

[0058] S104. Control the target vehicle to perform the corresponding avoidance operation according to the avoidance control command.

[0059] In this embodiment, the subject executing the method can be a computing device such as a computer or server, and no limitation is made in this embodiment.

[0060] In this embodiment, the subject executing the method can also be a smart device such as a smartphone or tablet, and no limitation is made in this embodiment.

[0061] As can be seen, the vehicle avoidance control method described in this embodiment can adjust the offset differently according to different adjacent vehicles and different lane widths, effectively reducing the panic or dissatisfaction of the driver caused by excessive or insufficient offset, thereby improving the autonomous driving user experience.

[0062] Example 2

[0063] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating a vehicle collision avoidance control method provided in this embodiment. The vehicle collision avoidance control method includes:

[0064] S201. Acquire camera images and acquire radar data of nearby vehicle targets.

[0065] S202. Determine the lane width of the lane in which the target vehicle is traveling based on the camera image.

[0066] S203. Determine whether the lane width is greater than the preset first width threshold. If yes, proceed to step S204; otherwise, proceed to step S205.

[0067] S204. Determine the preset first fixed offset as the target fixed offset and execute step S207.

[0068] S205. Determine whether the lane width is greater than the preset second width threshold. If yes, proceed to step S206; otherwise, end the process.

[0069] In this embodiment, the preset second width threshold is less than the preset first width threshold.

[0070] S206. Determine the preset second fixed offset as the target fixed offset and execute step S207.

[0071] In this embodiment, the method can be accomplished using a forward-looking intelligent camera (IFC) and a forward-facing radar. The IFC is used to determine the lane width.

[0072] For example, when the IFC determines that the lane width is greater than 3.5m, it can output the determination result to the controller so that the controller can give an instruction when triggering intelligent avoidance: deviate 30cm from the side with the vehicle.

[0073] When the IFC determines that the lane width is less than 3.5m but greater than 3.2m, it can output the determination result to the controller so that the controller can give an instruction when triggering intelligent avoidance: deviate 20-25cm from the side with the vehicle.

[0074] The aforementioned deviation distances can all be adjusted through calibration and are not fixed values.

[0075] S207. Obtain target image data of the adjacent vehicle through camera images.

[0076] S208. The radar data and image data of the target vehicle are fused to obtain fused data.

[0077] S209. Determine the type of vehicle to be parked next to the target vehicle based on the fused data.

[0078] S210. Determine the new offset based on the vehicle type and the preset offset calibration value.

[0079] S211. Generate avoidance control commands based on the target fixed offset and offset adjustment.

[0080] S212. Control the target vehicle to perform the corresponding avoidance operation according to the avoidance control command.

[0081] In this embodiment, the method can also lock the type of the vehicle by fusing the IFC and the forward radar to detect the vehicle, locate the vehicle position by the radar outputting point cloud information, and output the vehicle height and width by the IFC.

[0082] In this embodiment, if the adjacent vehicle is a large vehicle, an additional 10-15cm of deviation can be added on top of the original deviation, ensuring that the vehicle does not cross the lane line on the other side.

[0083] If the vehicle next to you is a small truck, you can add 5-10cm of deviation on top of the original deviation, ensuring that the vehicle does not cross the lane line on the other side.

[0084] If the adjacent vehicle is a small car, the original deviation amount remains unchanged.

[0085] All of the above values ​​are calibration values ​​and can be adjusted according to different vehicle types; they are not fixed.

[0086] It is evident that implementing this method allows the approach to further achieve adaptive deviation adjustment on the basis of the original intelligent avoidance scheme, thereby effectively improving the autonomous driving experience.

[0087] In this embodiment, the subject executing the method can be a computing device such as a computer or server, and no limitation is made in this embodiment.

[0088] In this embodiment, the subject executing the method can also be a smart device such as a smartphone or tablet, and no limitation is made in this embodiment.

[0089] As can be seen, the vehicle avoidance control method described in this embodiment can adjust the offset differently according to different adjacent vehicles and different lane widths, effectively reducing the panic or dissatisfaction of the driver caused by excessive or insufficient offset, thereby improving the autonomous driving user experience.

[0090] Example 3

[0091] Please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of a vehicle avoidance control device provided in this embodiment. Figure 3 As shown, the vehicle avoidance control device includes:

[0092] Acquisition unit 310 is used to acquire camera images and acquire radar data of nearby vehicle targets;

[0093] The determining unit 320 is used to determine the target fixed offset and offset adjustment amount based on the camera image and the side vehicle target radar data;

[0094] The generation unit 330 is used to generate avoidance control commands based on the target fixed offset and the offset adjustment amount;

[0095] The control unit 340 is used to control the target vehicle to perform corresponding avoidance operations according to the avoidance control command.

[0096] In this embodiment, the explanation of the vehicle avoidance control device can be referred to the description in Embodiment 1 or Embodiment 2, and will not be repeated here.

[0097] As can be seen, the vehicle avoidance control device described in this embodiment can make different offset adjustments according to different adjacent vehicles and different lane widths, effectively reducing the panic or dissatisfaction of the driver caused by excessive or insufficient offset, thereby improving the autonomous driving user experience.

[0098] Example 4

[0099] Please refer to Figure 4 , Figure 4This is a schematic diagram of the structure of a vehicle avoidance control device provided in this embodiment. Figure 4 As shown, the vehicle avoidance control device includes:

[0100] The acquisition unit 310 is used to acquire camera images and acquire radar data of the target vehicle from the forward-facing radar on the target vehicle.

[0101] The determining unit 320 is used to determine the target fixed offset and offset adjustment amount based on the camera image and the side vehicle target radar data;

[0102] The generation unit 330 is used to generate avoidance control commands based on the target fixed offset and the offset adjustment amount;

[0103] The control unit 340 is used to control the target vehicle to perform corresponding avoidance operations according to the avoidance control command.

[0104] As an optional implementation, the determining unit 320 includes:

[0105] The first determining subunit 321 is used to determine the lane width of the lane in which the target vehicle is traveling based on the camera image;

[0106] The second determining subunit 322 is used to determine the target fixed offset based on the lane width;

[0107] Acquisition subunit 323 is used to acquire target image data of the adjacent vehicle through camera images;

[0108] The fusion subunit 324 is used to fuse the radar data and image data of the side vehicle target to obtain fused data;

[0109] The third determining subunit 325 is used to determine the offset adjustment amount based on the fused data.

[0110] As an optional implementation, the second determining subunit 322 includes:

[0111] The judgment module is used to determine whether the lane width is greater than a preset first width threshold.

[0112] The determination module is used to determine the preset first fixed offset as the target fixed offset when it is determined that the lane width is greater than the preset first width threshold.

[0113] As an optional implementation, the judgment module is further configured to determine whether the lane width is greater than a preset second width threshold when it is determined that the lane width is not greater than a preset first width threshold; wherein the preset second width threshold is less than the preset first width threshold.

[0114] The determination module is also used to determine the preset second fixed offset as the target fixed offset when the lane width is greater than the preset second width threshold.

[0115] As an optional implementation, the third determining subunit 325 is specifically used to determine the type of the vehicle to which the vehicle is located based on the fused data; and to determine the new offset based on the type of vehicle and the preset offset calibration value.

[0116] In this embodiment, the explanation of the vehicle avoidance control device can be referred to the description in Embodiment 1 or Embodiment 2, and will not be repeated here.

[0117] As can be seen, the vehicle avoidance control device described in this embodiment can make different offset adjustments according to different adjacent vehicles and different lane widths, effectively reducing the panic or dissatisfaction of the driver caused by excessive or insufficient offset, thereby improving the autonomous driving user experience.

[0118] This application provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor runs the computer program to enable the electronic device to perform the vehicle avoidance control method in embodiment 1 or embodiment 2 of this application.

[0119] This application provides a computer-readable storage medium storing computer program instructions. When the computer program instructions are read and executed by a processor, the vehicle avoidance control method in embodiment 1 or embodiment 2 of this application is performed.

[0120] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0121] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0122] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0123] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0124] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0125] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A vehicle avoidance control method, characterized in that, include: The system acquires images from the forward-facing smart camera on the target vehicle and acquires radar data from the target vehicle's forward-facing radar. The target fixed offset and offset adjustment amount are determined based on the forward-looking camera image and the adjacent vehicle target radar data. Generate an avoidance control command based on the target fixed offset and the offset adjustment amount; The target vehicle is controlled to perform a corresponding avoidance operation according to the avoidance control command; The step of determining the target fixed offset and offset adjustment amount based on the forward-looking camera image and the adjacent vehicle target radar data includes: The lane width of the lane in which the target vehicle is traveling is determined based on the image from the forward-facing camera. Determine the target fixed offset based on the lane width; The image data of the target vehicle next to it is obtained through the image of the forward-looking camera; The radar data and image data of the adjacent vehicle target are fused to obtain fused data. The offset adjustment amount is determined based on the fused data; The step of determining the target fixed offset based on the lane width includes: Determine whether the lane width is greater than a preset first width threshold; If it is greater than the preset first width threshold, then the preset first fixed offset is determined as the target fixed offset.

2. The vehicle avoidance control method according to claim 1, characterized in that, The method further includes: If the width is not greater than the preset first width threshold, then it is determined whether the lane width is greater than the preset second width threshold; wherein the preset second width threshold is less than the preset first width threshold. If it is greater than the preset second width threshold, then the preset second fixed offset is determined as the target fixed offset.

3. The vehicle avoidance control method according to claim 1, characterized in that, Determining the offset adjustment amount based on the fused data includes: The type of vehicle beside the target vehicle is determined based on the fused data; The new offset is determined based on the vehicle type and the preset offset calibration value.

4. A vehicle avoidance control device, characterized in that, The vehicle avoidance control device includes: The acquisition unit is used to acquire forward-looking camera images through the forward-looking smart camera on the target vehicle, and to acquire radar data of the target vehicle from the forward-looking radar on the target vehicle. The determining unit is used to determine the target fixed offset and offset adjustment amount based on the forward-looking camera image and the side vehicle target radar data; A generation unit is used to generate avoidance control commands based on the target fixed offset and the offset adjustment amount; The control unit is used to control the target vehicle to perform corresponding avoidance operations according to the avoidance control command; The determining unit includes: The first determining subunit is used to determine the lane width of the lane in which the target vehicle is traveling based on the image from the forward-looking camera; The second determining subunit is used to determine the target fixed offset based on the lane width; The acquisition subunit is used to acquire target image data of the adjacent vehicle through the image of the forward-looking camera; The fusion subunit is used to fuse the radar data of the adjacent vehicle target and the image data of the adjacent vehicle target to obtain fused data; The third determining subunit is used to determine the offset adjustment amount based on the fused data; The second determining subunit includes: The judgment module is used to determine whether the lane width is greater than a preset first width threshold. The determination module is used to determine the preset first fixed offset as the target fixed offset when it is determined that the lane width is greater than the preset first width threshold.

5. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor running the computer program to cause the electronic device to perform the vehicle avoidance control method according to any one of claims 1 to 3.

6. A readable storage medium, characterized in that, The readable storage medium stores computer program instructions, which, when read and executed by a processor, perform the vehicle avoidance control method according to any one of claims 1 to 3.

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