Apparatus for controlling vehicle and method thereof

Abstract

The invention relates to an apparatus for controlling a vehicle and a method thereof. The vehicle control apparatus may include a sensor and a processor configured to determine a plane formed by a first axis and a second axis based on a frame obtained by using the sensor, the second axis corresponding to a traveling direction of the vehicle, and the first axis perpendicular to the second axis, detect an object in a region of interest of the plane, and transmit the detected object to the vehicle. Determining a virtual frame corresponding to the object, generating a first field of view (FOV) based on the virtual frame, determining a ground point, generating a second FOV based on the ground point, generating a third FOV based on at least one of the first FOV, the second FOV, and angle information included in specification information of the sensor, determining a state of a boundary region of the sensor based on the third FOV, and outputting a signal indicative of the determined state of the boundary region of the sensor.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of priority from Korean Patent Application No. 10-2023-0122061 filed in the Korean Intellectual Property Office on September 13, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to a vehicle control device and method thereof, and more particularly, to a technology for identifying a state of a sensor (eg, LiDAR). Background Art

[0004] Various studies are being conducted to assist a host vehicle in traveling to recognize external objects by using various sensors.

[0005] Specifically, when the host vehicle is traveling in a driving assist device activation mode or an autonomous driving mode, external objects may be recognized by using a sensor such as light detection and ranging (LiDAR).

[0006] The field of view (FOV) of the LiDAR may be protected so that the LiDAR recognizes external objects. For a user to remove contaminants on the surface of a sensor (eg, LiDAR) to fix the FOV of the LiDAR, different methods of recognizing contaminants on the surface of the LiDAR are considered. Summary of the invention

[0007] According to the present disclosure, a device for controlling a vehicle may include: a sensor; a processor; and a memory configured to store specification information of the sensor, wherein the processor is configured to: determine a plane formed by a first axis and a second axis based on a plurality of frames obtained by using the sensor, the second axis corresponding to the driving direction of the vehicle, and the first axis being perpendicular to the second axis; detect an object outside the vehicle in an area of ​​interest of the plane; determine a virtual frame corresponding to the object; generate a first field of view (FOV) based on the virtual frame; determine a ground point indicating the ground on the plane; generate a second FOV based on the ground point; generate a third FOV based on at least one of the following: the first FOV, the second FOV, and the angle information included in the specification information; determine a state of a boundary area of ​​the sensor based on the third FOV; and output a signal indicating the determined state of the boundary area of ​​the sensor.

[0008] The device, wherein the processor is configured to: specify a first region of interest (ROI) of the region of interest, wherein the first ROI includes an area between: a line rotated by a first angle from a half line facing the positive direction of the second axis and the half line; and determine a virtual box in the first ROI.

[0009] The device, wherein the processor is configured to: determine a plurality of line segments, each of the plurality of line segments connecting the vehicle and one of the plurality of points included in the virtual frame in the first ROI; determine a plurality of angles between the plurality of line segments and the half-line; determine a minimum angle among the plurality of angles in each of the plurality of frames; and store in the memory at least one of the following items: a first minimum angle including minimum angles, and a first minimum angle point among the plurality of points for forming each of the first minimum angles, wherein the first minimum angle point is determined in each of the plurality of frames.

[0010] The device, wherein the processor is configured to: obtain at least one of the following: a first global minimum angle, which is the maximum value among the first minimum angles; and a first global minimum angle point among the first minimum angle points for forming the first global minimum angle; and based on determining whether at least one of the number of the first minimum angles stored in the memory and the number of the first minimum angle points stored in the memory meets a threshold number, determine the reliability value of at least one of the following: the first global minimum angle and the first global minimum angle point.

[0011] The apparatus, wherein the processor is configured to: specify a second ROI, the second ROI including an area between: a line rotated from the half line by a second angle greater than the first angle and another line rotated from the half line by a third angle; and determine a virtual box in the second ROI.

[0012] The device, wherein the processor is configured to: determine a plurality of line segments, each of the plurality of line segments connecting the vehicle and one of the plurality of points included in the virtual frame in the second ROI; determine a plurality of angles between the plurality of line segments and the half-line; determine a maximum angle among the plurality of angles in each of the plurality of frames; and store in the memory at least one of the following items: a first maximum angle including a maximum angle, and a first maximum angle point among the plurality of points for forming each of the first maximum angles, wherein the first maximum angle point is determined in each of the plurality of frames.

[0013] The device, wherein the processor is configured to: obtain at least one of the following: a first global maximum angle, which is the maximum angle among the first maximum angles; and a first global maximum angle point among the first maximum angle points for forming the first global maximum angle; and determine a reliability value of at least one of the first global maximum angle and the first global maximum angle point based on determining whether at least one of the number of the first maximum angles stored in the memory and the number of the first maximum angle points stored in the memory meets a threshold number.

[0014] The device, wherein the processor is configured to: determine a plurality of third line segments, each of the plurality of third line segments connecting the vehicle and one of the grounding points; determine a plurality of angles between the plurality of third line segments and a half-line facing the positive direction of the second axis; identify a minimum angle among the plurality of angles in each of the plurality of frames; and store in the memory at least one of the following items: a minimum angle, and a second minimum angle point in the grounding point for forming each of the second minimum angles, wherein the second minimum angle point is determined in each of the plurality of frames.

[0015] The device, wherein the processor is configured to: obtain at least one of the following: a second global minimum angle, which is the minimum angle among the second minimum angles; and a second global minimum angle point among the second minimum angle points for forming the second global minimum angle; and determine a reliability value of at least one of the second global minimum angle and the second global minimum angle point based on determining whether at least one of the number of the second minimum angles stored in the memory and the number of the second minimum angle points stored in the memory meets a threshold number.

[0016] The device, wherein the processor is configured to: determine a plurality of fourth line segments, each of the plurality of fourth line segments connecting the vehicle and one of the grounding points; determine a plurality of angles between the plurality of fourth line segments and a half-line facing the positive direction of the second axis; in each of the plurality of frames, identify a maximum angle among the plurality of angles; and store in the memory at least one of the following items: a second maximum angle including a maximum angle, and a second maximum angle point in the grounding point for forming each of the second maximum angles, wherein the second maximum angle point is determined in each of the plurality of frames.

[0017] The device, wherein the processor is configured to: obtain at least one of the following: a second global maximum angle, which is the minimum value among the second maximum angles; and a second global maximum angle point among the second maximum angle points for forming the second global maximum angle; and determine a reliability value of at least one of the second global maximum angle and the second global maximum angle point based on determining whether at least one of the number of the second maximum angles stored in the memory and the number of the second maximum angle points stored in the memory meets a threshold number.

[0018] The apparatus, wherein the processor is configured to determine a normal state of a boundary area of ​​the sensor based on a difference between the third FOV and the angle information satisfying a threshold angle.

[0019] The apparatus, wherein the processor is configured to determine an abnormal state of the boundary area of ​​the sensor based on a difference between the third FOV and the angle information satisfying a threshold angle.

[0020] The device, wherein the processor is configured to: after determining the abnormal state of the boundary area, determine the abnormal state of at least one of the first ROI and the second ROI based on at least one of the first FOV, the second FOV, the third FOV and the angle information.

[0021] The device, wherein the processor is configured to: determine the state of the boundary area based on at least one of the following items before determining the contamination state of the sensor and including the contamination level of the sensor in the specification information: the first FOV, the second FOV, the third FOV, and the angle information, wherein the contamination state is determined based on the contamination level satisfying a threshold.

[0022] According to the present disclosure, a method for controlling a vehicle may include: obtaining multiple frames from a sensor; determining a plane formed by a first axis and a second axis based on the multiple frames, the second axis corresponding to the driving direction of the vehicle, and the first axis being perpendicular to the second axis; detecting an object outside the vehicle in an area of ​​interest of the plane; determining a virtual frame corresponding to the object; generating a first field of view (FOV) based on the virtual frame; determining a grounding point indicating the ground on the plane; generating a second FOV based on the grounding point; generating a third FOV based on at least one of the following: the first FOV, the second FOV, and angle information included in the specification information of the sensor; determining a state of a boundary area of ​​the sensor based on the third FOV; and outputting a signal indicating the determined state of the boundary area of ​​the sensor.

[0023] The method may further include: specifying a first region of interest (ROI) of an area of ​​interest, wherein the first ROI includes an area between a line rotated by a first angle from a half line facing the positive direction of the second axis and the half line; determining a virtual frame in the first ROI; specifying a second ROI, wherein the second ROI includes an area between a line rotated by a second angle greater than the first angle from the half line and another line rotated by a third angle from the half line; determining a virtual frame in the second ROI; determining a plurality of first line segments, each of the plurality of first line segments connecting the vehicle with a first point among a plurality of first points included in the virtual frame in the first ROI; determining a plurality of first angles between the plurality of first line segments and the half line; determining a minimum angle among the plurality of first angles in each of the plurality of frames; determining a plurality of second line segments, each of the plurality of second line segments connecting the vehicle with a plurality of first points included in the virtual frame in the second ROI a first global minimum angle, which is a minimum value among the first minimum angles; a first global minimum angle point among the first minimum angles for forming the first global minimum angles; a first global maximum angle, which is a maximum value among the first maximum angles; and a first global maximum angle point among the first maximum angle points for forming the first global maximum angles; and generating the first FOV based on at least one of the following: a first global minimum angle, which is a minimum value among the first minimum angles; a first global minimum angle point among the first minimum angle points for forming the first global minimum angle; a first global maximum angle, which is a maximum value among the first maximum angles; and a first global maximum angle point among the first maximum angle points for forming the first global maximum angle.

[0024] The method may also include: determining a plurality of third line segments, each of which connects the vehicle and one of the ground points; determining a plurality of first angles between the plurality of third line segments and a half-line facing the positive direction of the second axis; determining a minimum angle among the plurality of first angles in each of the plurality of frames; determining a plurality of fourth line segments, each of which connects the vehicle and one of the ground points; determining a plurality of second angles between the plurality of third line segments and the half-line; determining a maximum angle among the plurality of second angles in each of the plurality of frames; and generating the second FOV based on at least one of the following: a second global minimum angle, which is a minimum value among the second minimum angles; a second global minimum angle point among the second minimum angle points for forming the second global minimum angle; a second global maximum angle, which is a maximum value among the second maximum angles; and a second global maximum angle point among the second maximum angle points for forming a second global maximum angle among the second maximum angle points.

[0025] The method may also include: determining a normal state of a boundary area of ​​the sensor based on that a difference between a third FOV and the angle information satisfies a threshold angle; or determining an abnormal state of a boundary area of ​​the sensor based on that a difference between the third FOV and the angle information does not satisfy the threshold angle.

[0026] The method may further include storing at least one of a first maximum angle and a first maximum angle point used to form each first maximum angle in a memory, wherein the first maximum angle is determined in each frame of the plurality of frames. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description in conjunction with the accompanying drawings:

[0028] Figure 1 An embodiment of a block diagram showing a vehicle control device according to an embodiment of the present disclosure;

[0029] Figure 2 An embodiment of a vehicle control device that identifies a minimum angle to generate a first FOV in an embodiment of the present disclosure is shown;

[0030] Figure 3 An embodiment of a vehicle control device that identifies a maximum angle to generate a first FOV in an embodiment of the present disclosure is shown;

[0031] Figure 4 An embodiment of a vehicle control device that identifies a minimum angle and a maximum angle to generate a second FOV in an embodiment of the present disclosure is shown;

[0032] Figure 5An embodiment in which a vehicle control device according to an embodiment of the present disclosure determines an abnormal state of a boundary area is shown;

[0033] Figure 6 An embodiment of a flowchart related to a vehicle control method according to an embodiment of the present disclosure is shown;

[0034] Figure 7 An embodiment of a flowchart related to a vehicle control method according to an embodiment of the present disclosure is shown;

[0035] Figure 8 An embodiment of a flowchart related to a vehicle control method according to an embodiment of the present disclosure is shown;

[0036] Fig. 9 An embodiment showing a flowchart related to a vehicle control method according to an embodiment of the present disclosure; and

[0037] Fig.10 An embodiment of a computing system including a vehicle control device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0038] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. When adding reference numerals to components of the respective drawings, it should be noted that the same components have the same reference numerals even though they are shown in another drawing. In addition, when describing the embodiments of the present disclosure, if a well-known function or configuration may make the subject matter of the present disclosure unnecessarily obscure, the detailed description associated with the well-known function or configuration will be omitted.

[0039] When describing the elements of the embodiments of the present disclosure, the terms first, second, A, B, (a), (b) etc. can be used in this article. These terms are only used to distinguish one element from another element, but do not limit the corresponding elements, and are independent of the properties, order or priority of the corresponding elements. In addition, unless otherwise defined, all terms including technical terms and scientific terms used herein will be interpreted as the customary terms of the field to which the present disclosure belongs. It should be understood that the terms used in this article should be interpreted as having the same meaning as their meaning in the context of the present disclosure and the related art, and should not be interpreted in an idealized or overly formal sense, unless clearly defined in this article.

[0040] In the following, reference will be made to Figures 1 to 10 Various embodiments of the present disclosure are described in detail.

[0041] Figure 1 An embodiment of a block diagram of a vehicle control device according to an embodiment of the present disclosure is shown.

[0042] refer to Figure 1The vehicle control device 100 according to the embodiment of the present disclosure may be implemented inside or outside the vehicle, and some components included in the vehicle control device 100 may be implemented inside or outside the vehicle. In this case, the vehicle control device 100 may be integrated with the internal control unit of the vehicle, and may be implemented by a separate device so as to be connected to the control unit of the vehicle by means of a separate connection device. For example, the vehicle control device 100 may further include Figure 1 Components not shown.

[0043] See also Figure 1 , the vehicle control device 100 according to the embodiment may include a processor 110, a LiDAR 120, and a memory 130. The processor 110, the LiDAR 120, or the memory 130 may be electrically or operably connected to each other through electronic components including a communication bus.

[0044] Hereinafter, the fact that various hardware are operably coupled may include the fact that a direct or indirect connection between the various hardware is established wired or wirelessly so that the second hardware is controlled by the first hardware among the various hardware. Although different blocks are shown, the embodiment is not limited thereto. Figure 1 Some of the various hardware in the vehicle control device 100 may be included in a single integrated circuit including a system on a chip (SoC). The type or number of hardware included in the vehicle control device 100 is not limited to Figure 1 For example, the vehicle control device 100 may include Figure 1 Only some of the various hardware are shown.

[0045] The vehicle control device 100 according to the embodiment may include hardware for processing data based on one or more instructions. The hardware for processing data may include a processor 110. For example, the hardware for processing data may include an arithmetic and logic unit (ALU), a floating point unit (FPU), a field programmable gate array (FPGA), a central processing unit (CPU) and / or an application processor (AP). The processor 110 may have a structure of a single-core processor, or may have a structure of a multi-core processor including a dual-core, quad-core, hexa-core or octa-core.

[0046] The LiDAR 120 included in the vehicle control device 100 according to the embodiment may obtain a data set from identifying objects around the vehicle control device 100. For example, the LiDAR 120 may identify at least one of the position of the surrounding object, the moving direction of the surrounding object, the speed of the surrounding object, and any combination thereof based on a pulse laser signal emitted from the LiDAR 120, reflected by the surrounding object, and returned.

[0047] The memory 130 included in the vehicle control device 100 according to the embodiment may include a hardware component for storing data or instructions to be input or output to the processor 110 of the vehicle control device 100 .

[0048] For example, the memory 130 may include a volatile memory including a random access memory (RAM), or a nonvolatile memory including a read only memory (ROM).

[0049] For example, the volatile memory may include at least one of a dynamic RAM (DRAM), a static RAM (SRAM), a cache RAM, a pseudo SRAM (PSRAM), and any combination thereof.

[0050] For example, the non-volatile memory includes at least one of the following: programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, hard disk, compact disk, solid state drive (SSD), embedded multimedia card (eMMC), or any combination thereof.

[0051] In an embodiment, the memory 130 of the vehicle control apparatus 100 may store specification information of the LiDAR 120. For example, the memory 130 may receive specification information from an external device different from the vehicle control apparatus 100 and may store the received specification information.

[0052] The processor 110 of the vehicle control device 100 according to the embodiment may obtain multiple frames by using the LiDAR 120. For example, the multiple frames obtained by using the LiDAR 120 may include frames based on a three-dimensional virtual coordinate system including an x-axis, a y-axis, and a z-axis. In the following description, the first axis may include an x-axis. The second axis may include a y-axis. The third axis may include a z-axis. The x-axis, the y-axis, and the z-axis may be perpendicular to each other. In the following, for ease of description, the first axis is referred to as the "x-axis"; the second axis is referred to as the "y-axis"; and the third axis is referred to as the "z-axis". However, the embodiments of the present disclosure are not limited to the above description.

[0053] The processor 110 may identify a virtual frame corresponding to the external object in a plurality of frames obtained by using the LiDAR 120. For example, in a plurality of frames obtained by using the LiDAR 120, the processor 110 may identify a virtual frame corresponding to an external object map identified in a region of interest (ROI) of a plane formed by an x-axis and a y-axis among the x-axis, the y-axis, and the z-axis, and may generate a first FOV based on the virtual frame.

[0054] For example, the processor 110 may specify a first ROI from the ROIs, the first ROI including an area rotated clockwise by a first angle based on a half line facing the positive direction of the y-axis from the host vehicle. The processor 110 may identify a virtual box in the first ROI. For example, the first ROI may be referred to as a “lower limit area”.

[0055] According to an embodiment, the processor 110 may specify the first ROI based on at least one of the angle information included in the specification information, the area in the ROI rotated clockwise by the first angle based on the half line facing the positive direction of the host vehicle toward the y-axis, and any combination thereof. For example, the angle information may be referred to as a scalar gen2 FOV angle. For example, the angle information may include an angle of approximately 133 degrees.

[0056] For example, the processor 110 may specify a second ROI from the ROI, the second ROI including an area that is rotated clockwise by a second angle greater than the first angle based on a half line facing the positive direction of the y-axis from the main vehicle. The processor 110 may identify a virtual box in the second ROI. For example, the second ROI may be referred to as an "upper limit area".

[0057] According to an embodiment, the processor 110 may specify a second ROI based on at least one of angle information included in the specification information, an area in the ROI that is rotated clockwise by a second angle greater than the first angle based on a half line facing the positive direction of the y-axis from the host vehicle, and any combination thereof.

[0058] In an embodiment, the processor 110 may identify a ground point indicating a ground on a plane formed by the x-axis and the y-axis among the x-axis, the y-axis, and the z-axis. The processor 110 may identify a ground point indicating a ground on a plane formed by the x-axis and the y-axis among the x-axis, the y-axis, and the z-axis, and may generate a second FOV based on the ground point.

[0059] In an embodiment, the processor 110 may identify the third FOV based on at least one of the following: the first FOV based on the virtual frame, the second FOV based on the ground point, the angle information included in the specification information, and any combination thereof. For example, the third FOV may include a FOV closer to the angle information in the first FOV and the second FOV.

[0060] For example, if the angle information includes 133 degrees, the processor 110 may set the second FOV among the first FOV and the second FOV to the third FOV based on the first FOV being identified as 121 degrees and the second FOV being identified as 130 degrees.

[0061] The processor 110 may identify the third FOV based on at least one of the first FOV based on the virtual frame, the second FOV based on the ground point, the angle information included in the specification information, and any combination thereof, and may determine the state of the boundary area of ​​the LiDAR 120. For example, the processor 110 may determine the state of the boundary area of ​​the LiDAR 120 by comparing the third FOV with the angle information included in the specification information.

[0062] In an embodiment, the processor 110 may determine the normal state of the boundary area of ​​the LiDAR 120 based on the fact that the difference between the third FOV and the angle information included in the specification information is less than a specified angle.

[0063] In an embodiment, the processor 110 may determine the abnormal state of the boundary area of ​​the LiDAR 120 based on the fact that the difference between the third FOV and the angle information included in the specification information is not greater than a specified angle.

[0064] In an embodiment, after determining the abnormal state of the boundary area, the processor 110 may determine the abnormal state of at least one of the first ROI, the second ROI, and any combination thereof based on at least one of the first FOV, the second FOV, the third FOV, the angle information, and any combination thereof.

[0065] Hereinafter, an embodiment of the vehicle control device 100 that generates the first FOV will be described.

[0066] In an embodiment, the processor 110 may identify a first ROI from the ROIs, the first ROI including an area rotated clockwise by a first angle based on a half line facing the positive direction of the y-axis from the host vehicle. The processor 110 may identify a virtual frame corresponding to an external object in the first ROI.

[0067] For example, the processor 110 may identify a virtual frame in the current frame. The processor 110 may identify a plurality of points included in the virtual frame identified in the current frame. The processor 110 may identify an angle between a half line from the host vehicle facing the positive direction of the y-axis and a first line segment connecting a plurality of points from the plurality of points included in the virtual frame.

[0068] In an embodiment, in each of the plurality of frames, the processor 110 may identify a first line segment from connecting the host vehicle with each of the plurality of points included in the virtual frame identified in the first ROI. The processor 110 may identify an angle between the first line segment and a half line facing the positive direction of the y-axis from the host vehicle. The processor 110 may identify a minimum angle among the angles between the first line segment and the half line facing the positive direction of the y-axis from the host vehicle.

[0069] The processor 110 may identify at least one of the identified first minimum angle in each of the plurality of frames, the first minimum angle point in the plurality of points used to form the first minimum angle, and any combination thereof. The processor 110 may store at least one of the identified first minimum angle in each of the plurality of frames, the first minimum angle point in the plurality of points used to form the first minimum angle, and any combination thereof in the memory 130.

[0070] In an embodiment, the processor 110 may obtain at least one of a first global minimum angle, a first global minimum angle point, or any combination thereof, the first global minimum angle being the minimum value among the first minimum angles, the first global minimum angle point being used to form the first global minimum angle among the first minimum angle points. The processor 110 may determine whether at least one of the first minimum angle, the first minimum angle point, and any combination thereof is stored in the memory 130 up to a specified number or more. For example, the global minimum angle may include the minimum angle among the angles identified by the points in a plurality of frames. For example, the global maximum angle may include the maximum angle among the angles identified by the points in a plurality of frames.

[0071] The processor 110 may determine the reliability of at least one of the first global minimum angle, the first global minimum angle point, and any combination thereof based on determining whether at least one of the first minimum angle, the first minimum angle point, and any combination thereof is stored in the memory for more than a specified number. For example, the specified number may include approximately 50.

[0072] For example, based on identifying at least one of a first minimum angle stored more than a specified number, a first minimum angle point stored more than a specified number, and any combination thereof, the processor can identify a reliability indicating the availability of at least one of the first global minimum angle, the first global minimum angle point, and any combination thereof, which reliability is based on at least one of the first minimum angle, the first minimum angle point, and any combination thereof.

[0073] For example, the processor 110 may identify at least one of the first global minimum angle, the first global minimum angle point, and any combination thereof based on identifying that at least one of the first minimum angle, the first minimum angle point, and any combination thereof is stored more than a specified number.

[0074] For example, if at least one of the first minimum angle, the first minimum angle point, and any combination thereof is identified such that the number of first minimum angles, the first minimum angle points, and any combination thereof is less than a specified number, then the processor 110 may additionally or alternatively perform processing to obtain the first minimum angle and the first minimum angle point.

[0075] In an embodiment, in each of the plurality of frames, the processor 110 may identify a second line segment from connecting the host vehicle to each of the plurality of points included in the virtual frame identified in the first ROI. The processor 110 may identify an angle between the second line segment and a half line facing the positive direction of the y-axis from the host vehicle. The processor 110 may identify a maximum angle among the angles between the second line segment and the half line facing the positive direction of the y-axis from the host vehicle.

[0076] The processor 110 may identify at least one of a first maximum angle identified in each of the plurality of frames, a first maximum angle point among a plurality of points used to form the first maximum angle, and any combination thereof. The processor 110 may store at least one of the first maximum angle identified in each of the plurality of frames, a first maximum angle point among a plurality of points used to form the first maximum angle, and any combination thereof in the memory 130.

[0077] In an embodiment, the processor 110 may obtain at least one of a first global maximum angle, a first global maximum angle point, and any combination thereof, wherein the first global maximum angle is the maximum value among the first maximum angles, and the first global maximum angle point is used to form the first global maximum angle among the first maximum angle points. The processor 110 may determine whether at least one of the first maximum angle, the first maximum angle point, and any combination thereof is stored in the memory 130 more than a specified number.

[0078] The processor 110 may determine the reliability of at least one of the first global maximum angle, the first global maximum angle point, and any combination thereof based on determining whether at least one of the first maximum angle, the first maximum angle point, and any combination thereof is stored in the memory for more than a specified number. For example, the specified number may include approximately 50.

[0079] For example, based on identifying at least one of the first maximum angle stored up to the specified number or more, the first maximum angle point stored up to the specified number or more, and any combination thereof, the processor can identify a reliability indicating the availability of at least one of the first global maximum angle, the first global maximum angle point, and any combination thereof, which reliability is based on at least one of the first maximum angle, the first maximum angle point, and any combination thereof.

[0080] For example, the processor 110 may identify at least one of the first global maximum angle, the first global maximum angle point, and any combination thereof based on identifying that at least one of the first maximum angle, the first maximum angle point, and any combination thereof is stored more than a specified number.

[0081] For example, if at least one of the first maximum angle, the first maximum angle point, and any combination thereof is identified as making the number of the first maximum angle, the first maximum angle point, and any combination thereof less than a specified number, then the processor 110 may additionally or alternatively perform processing to obtain the first maximum angle and the first maximum angle point.

[0082] In an embodiment, the processor 110 may generate the first FOV based on at least one of a first global minimum angle, a first global minimum angle point, a first global maximum angle, a first global maximum angle point, and any combination thereof.

[0083] For example, the processor 110 may generate a second FOV based on an area between a line segment connecting the host vehicle and the second global minimum angle point and a line segment connecting the host vehicle and the second global maximum angle point. For example, the processor 110 may generate a first FOV including a first global minimum angle point and a first global maximum angle point.

[0084] Hereinafter, an embodiment of the vehicle control device 100 that generates the second FOV will be described.

[0085] In an embodiment, in each of the plurality of frames, the processor 110 may identify a minimum angle among angles between a half line from the host vehicle facing in the positive direction of the y-axis and a third line segment connecting the host vehicle and each of the grounding points.

[0086] The processor 110 may identify at least one of the second minimum angle identified in each of the plurality of frames, the second minimum angle point in the grounding point used to form the second minimum angle, and any combination thereof. The processor 110 may store in the memory 130 at least one of the second minimum angle identified in each of the plurality of frames, the second minimum angle point in the grounding point used to form the second minimum angle, and any combination thereof.

[0087] In an embodiment, the processor 110 may obtain at least one of a second global minimum angle, a second global minimum angle point, and any combination thereof, wherein the second global minimum angle is the minimum value among the second minimum angles, and the second global minimum angle point is used to form a second global minimum angle in the second minimum angle point.

[0088] The processor 110 may determine the reliability of at least one of the second global minimum angle, the second global minimum angle point, and any combination thereof based on determining whether at least one of the second minimum angle, the second minimum angle point, and any combination thereof is stored in the memory 130 more than a specified number.

[0089] For example, based on identifying at least one of storing a second minimum angle of more than a specified number, storing a second minimum angle point of more than a specified number, and any combination thereof, the processor can identify a reliability indicating the availability of at least one of the second global minimum angle, the second global minimum angle point, and any combination thereof, the reliability being based on at least one of the second minimum angle, the second minimum angle point, and any combination thereof.

[0090] For example, based on identifying that at least one of the second minimum angle, the second minimum angle point, and any combination thereof is stored more than a specified number, the processor 110 may identify at least one of the second global minimum angle, the second global minimum angle point, and any combination thereof.

[0091] For example, if at least one of the second minimum angle, the second minimum angle point, and any combination thereof is identified such that the number of second minimum angles, the second minimum angle points, and any combination thereof is less than a specified number, then the processor 110 may additionally or alternatively perform processing to obtain at least one of the second minimum angle, the second minimum angle point, and any combination thereof.

[0092] In an embodiment, in each of the plurality of frames, the processor 110 may identify a maximum angle among angles between a half line from the host vehicle facing the positive direction of the y-axis and a fourth line segment connecting the host vehicle and each of the grounding points.

[0093] The processor 110 may identify at least one of the second maximum angle identified in each of the plurality of frames, the second maximum angle point in the grounding point used to form the first maximum angle, and any combination thereof. The processor 110 may store at least one of the second maximum angle identified in each of the plurality of frames, the second maximum angle point in the grounding point used to form the second maximum angle, and any combination thereof in the memory 130.

[0094] In an embodiment, the processor 110 may obtain at least one of a second global maximum angle, a second global maximum angle point, and any combination thereof, wherein the second global maximum angle is the maximum value among the second maximum angles, and the second global maximum angle point is used to form a second global maximum angle among the second maximum angle points.

[0095] The processor 110 may determine the reliability of at least one of the second global maximum angle, the second global maximum angle point, and any combination thereof based on determining whether at least one of the second maximum angle, the second maximum angle point, and any combination thereof is stored in the memory 130 more than a specified number.

[0096] For example, based on identifying at least one of storing a second maximum angle of more than a specified number, storing a second maximum angle point of more than a specified number, and any combination thereof, the processor may identify a reliability indicating the availability of at least one of the second global maximum angle, the second global maximum angle point, and any combination thereof, which reliability is based on at least one of the second maximum angle, the second maximum angle point, and any combination thereof.

[0097] For example, the processor 110 may identify at least one of a second global maximum angle, a second global maximum angle point, and any combination thereof based on identifying that at least one of the second maximum angle, the second maximum angle point, and any combination thereof is stored more than a specified number.

[0098] For example, if at least one of the second minimum angle, the second minimum angle point, and any combination thereof is identified such that the number of second minimum angles, the second minimum angle points, and any combination thereof is less than a specified number, then the processor 110 may additionally or alternatively perform processing to obtain at least one of the second minimum angle, the second minimum angle point, and any combination thereof.

[0099] In an embodiment, the processor 110 may generate the second FOV based on at least one of a second global minimum angle, a second global minimum angle point, a second global maximum angle, a second global maximum angle point, and any combination thereof.

[0100] According to an embodiment, when at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point and any combination thereof is identified based on the grounding point, the processor 110 may store at least one of the identified second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point and any combination thereof in the memory 130.

[0101] If at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is stored in the memory 130 for more than a specified number, the processor 110 may obtain at least one of the second global minimum angle, the second global minimum angle point, the second global maximum angle, the second global maximum angle point, and any combination thereof.

[0102] In an embodiment, the processor 110 may generate the second FOV based on at least one of a second global minimum angle, a second global minimum angle point, a second global maximum angle, a second global maximum angle point, and any combination thereof.

[0103] For example, the processor 110 may generate a second FOV based on an area between a line segment connecting the host vehicle and the second global minimum angle point and a line segment connecting the host vehicle and the second global maximum angle point. For example, the processor 110 may generate a second FOV including a second global minimum angle point and a second global maximum angle point.

[0104] Hereinafter, an embodiment of the vehicle control device 100 that recognizes the third FOV will be described.

[0105] In an embodiment, the processor 110 may generate a first FOV and a second FOV. The processor 110 may identify the first FOV, the second FOV, and the third FOV based on the angle information included in the specification information. For example, the third FOV may include a FOV that is closer to the angle information included in the specified information between the first FOV and the second FOV.

[0106] The processor 110 may determine the state of the boundary area of ​​the LiDAR 120 by identifying the third FOV. For example, the boundary area of ​​the LiDAR 120 may include a boundary line of an area different from the entire area in which the LiDAR 120 detects an external object.

[0107] In an embodiment, the processor 110 may determine the normal state of the boundary area of ​​the LiDAR 120 based on the fact that the difference between the third FOV and the angle information included in the specification information is less than a specified angle. For example, the specified angle may include about 3 degrees.

[0108] In an embodiment, the processor 110 may determine the abnormal state of the boundary area of ​​the LiDAR 120 based on the fact that the difference between the third FOV and the angle information included in the specification information is not greater than a specified angle.

[0109] In an embodiment, after determining the abnormal state of the boundary area of ​​the LiDAR 120, the processor 110 may determine the abnormal state of at least one of the first ROI, the second ROI, and any combination thereof based on at least one of the first FOV, the second FOV, the third FOV, the angle information, and any combination thereof.

[0110] For example, the processor 110 may identify an abnormal state of at least one of the first ROI, the second ROI, and any combination thereof based on the third FOV and the angle information. For example, the processor 110 may identify an abnormal state of at least one of the first ROI, the second ROI, and any combination thereof based on at least one of the first global minimum angle point, the first global maximum angle point, and any combination thereof for identifying the third FOV.

[0111] For example, the processor 110 may identify an abnormal state of at least one of the first ROI, the second ROI, and any combination thereof based on the fact that at least one of the first global minimum angle point, the first global maximum angle point, and any combination thereof is outside a specified distance from a point included in the angle information.

[0112] For example, the processor 110 may include the following operation: determining the abnormal state of the first ROI based on the fact that the global minimum angle included in the third FOV is greater than the minimum angle included in the angle information. For example, the global minimum angle included in the third FOV may include at least one of a first global minimum angle, a first global minimum angle point, and any combination thereof for generating the first FOV. For example, the global minimum angle included in the third FOV may include at least one of a second global minimum angle, a second global minimum angle point, and any combination thereof for generating the second FOV.

[0113] For example, the processor 110 may include the following operation: determining the abnormal state of the second ROI based on the fact that the global maximum angle included in the third FOV is less than the maximum angle included in the angle information. For example, the global maximum angle included in the third FOV may include at least one of the first global maximum angle, the first global maximum angle point, and any combination thereof for generating the first FOV. For example, the global maximum angle included in the third FOV may include at least one of the second global maximum angle, the second global maximum angle point, and any combination thereof for generating the second FOV.

[0114] In an embodiment, the processor 110 may identify a contamination level of the LiDAR 120. For example, the processor 110 may identify the contamination level of the LiDAR 120 based on the specification information. Before the contamination level of the LiDAR 120 is included in the specification information and identified as a threshold for determining the contamination state of the LiDAR 120, the processor 110 may determine the state of the boundary area based on the first FOV, the second FOV, the third FOV, the angle information included in the specification information, and any combination thereof.

[0115] In an embodiment, the processor 110 may provide guidance to the user based on the fact that the state of the boundary area is determined to be an abnormal state. For example, the processor 110 may provide a notification that the state of the boundary area of ​​the LiDAR 120 is determined to be an abnormal state by using at least one of a display device including a display, an output device including a speaker, and any combination thereof in a vehicle control system including the vehicle control device 100.

[0116] As described above, the processor 110 of the vehicle control device 100 according to the embodiment may determine the state of the boundary area of ​​the LiDAR 120 based on at least one of the first FOV, the second FOV, the third FOV, the angle information included in the specification information, and any combination thereof. The processor 110 may recognize that the state of the boundary area of ​​the LiDAR 120 is an abnormal state, and may guide the user so that he / she may take action, thereby preventing the performance of the LiDAR 120 from being deteriorated.

[0117] Figure 2 An embodiment of a vehicle control device that identifies a minimum angle to generate a first FOV in an embodiment of the present disclosure is shown.

[0118] Figure 2 The host vehicle 200 may include Figure 1 A vehicle control device 100 is provided.

[0119] See also Figure 2 , the processor of the vehicle control device according to the embodiment may recognize a virtual frame 230 corresponding to an external object different from the host vehicle 200. For example, the external object may include at least one of an external vehicle, a guardrail, a pedestrian, a stationary object, and any combination thereof.

[0120] For example, the virtual frame 230 may refer to a meta-object. For example, the meta-object may include an object having the same data format as a tracking channel for tracking an external object.

[0121] For example, the processor may identify a half line 210 facing the positive direction of the y-axis from the host vehicle 200. The processor may specify a first ROI 220 that includes an area rotated clockwise by a first angle from the half line 210. For example, the first ROI 220 may include an area rotated clockwise by about 20 degrees from the half line 210.

[0122] In an embodiment, the processor may use the specification information of the LiDAR when specifying the first ROI 220. For example, the processor may specify the first ROI 220 by using angle information included in the specification information of the LiDAR.

[0123] The processor may identify virtual frames 231 and 233 in the first ROI 220. The processor may identify a plurality of points included in the virtual frames 231 and 233 identified in the first ROI 220.

[0124] In an embodiment, the processor may obtain a first line segment from each of the plurality of points connecting the host vehicle 200 and included in the virtual frames 231 and 233. The processor may identify an angle between the first line segment and the half line 210. The processor may identify a minimum angle among the angles between the first line segment and the half line 210.

[0125] In an embodiment, the processor may identify the minimum angle based on identifying a virtual frame that satisfies a specified condition. For example, the processor may identify the minimum angle by using the virtual frame 231 based on identifying the virtual frame 231 in which, in the first ROI 220, the external object is spaced apart by more than a specified distance in the lateral direction (e.g., the y-axis direction) of the host vehicle 200 and is not blocked by another external object.

[0126] In an embodiment, in each of the plurality of frames, the processor may obtain a first line segment from each of the plurality of points connecting the host vehicle 200 and included in the virtual frames 231 and 233. The processor may identify an angle between the first line segment and the half-line 210 in each of the plurality of frames. In each of the plurality of frames, the processor may identify a first minimum angle based on identifying a minimum angle among the angles between the first line segment and the half-line 210.

[0127] In an embodiment, the processor may store the identified first minimum angle in a memory.The processor may store the first minimum angles sequentially in the memory.

[0128] In an embodiment, the processor may store at least one of the first minimum angle, the first minimum angle point, and any combination thereof in a memory, and the processor may also store at least one of the direction the LiDAR is facing, an index, and any combination thereof.

[0129] For example, the direction the LiDAR is facing may include an identifier corresponding to the left side or an identifier corresponding to the right side.For example, the index may include identifying a frame of a first minimum angle and a location of the first minimum angle stored in a memory.

[0130] In an embodiment, the processor may identify a first global minimum angle that is a minimum of the first minimum angles. The processor may identify a first global minimum angle point from the first minimum angle points for forming the first global minimum angle.

[0131] In an embodiment, the processor may determine whether at least one of the first minimum angle, the first minimum angle point, and any combination thereof is stored in the memory up to a specified number (e.g., about 50) or more based on identifying the first global minimum angle point. The processor may identify the maximum angle in a second ROI different from the first ROI 220 based on identifying that the first minimum angle and the first minimum angle point are stored up to a specified number or more, the first minimum angle point is stored up to a specified number or more, or any combination thereof. See below Figure 3 The operation of identifying the maximum angle in the second ROI is described.

[0132] In an embodiment, the processor may perform processing to additionally or alternatively obtain at least one of a first minimum angle, a first minimum angle point, and any combination thereof from the first ROI 220 based on identifying the first minimum angle and the first minimum angle point, the first minimum angle and the first minimum angle point being stored such that the number of the first minimum angles and the first minimum angle points is less than a specified number.

[0133] Figure 3 An embodiment of a vehicle control device that identifies a maximum angle to generate a first FOV in an embodiment of the present disclosure is shown.

[0134] Figure 3 The host vehicle 300 may include Figure 1 A vehicle control device 100 is provided.

[0135] See also Figure 3 , the processor of the vehicle control device according to the embodiment may recognize a virtual frame 330 corresponding to an external object different from the host vehicle 300 .

[0136] In an embodiment, the processor may identify a half line 310 facing the positive direction of the y-axis from the host vehicle 300. The processor may identify a second ROI 320 that includes an area rotated clockwise from the half line 310 by a second angle greater than the first angle.

[0137] In an embodiment, the processor may use the specification information of the LiDAR when specifying the second ROI 320. For example, the processor may specify the second ROI 320 by using the angle information included in the specification information of the LiDAR.

[0138] For example, the second ROI 320 may include a region between a half line rotated approximately 110 degrees clockwise from the half line 310 and a half line rotated approximately 140 degrees clockwise from the half line 310 .

[0139] The processor may identify a virtual frame 335 in the second ROI 320. The processor may identify a plurality of points included in the virtual frame 335 identified in the second ROI 320.

[0140] In an embodiment, the processor may obtain a second line segment from connecting the host vehicle 300 and each of the plurality of points included in the virtual frame 335. The processor may identify an angle between the second line segment and the half-line 310. The processor may identify a maximum angle among the angles between the second line segment and the half-line 310.

[0141] In an embodiment, in each of the plurality of frames, the processor may obtain a second line segment from connecting the host vehicle 300 and each of the plurality of points included in the virtual frame 335. The processor may identify an angle between the second line segment and the half-line 310 in each of the plurality of frames. In each of the plurality of frames, the processor may identify a first maximum angle based on identifying a maximum angle among the angles between the second line segment and the half-line 310.

[0142] In an embodiment, the processor may store the identified first maximum angle in a memory.The processor may store the first maximum angles sequentially in the memory.

[0143] In an embodiment, the processor may store at least one of the first maximum angle, the first maximum angle point, and any combination thereof in a memory, and the processor may also store at least one of the direction the LiDAR is facing, an index, and any combination thereof.

[0144] In an embodiment, the processor may identify a first global maximum angle that is a maximum value among the first maximum angles. The processor may identify a first global maximum angle point from among the first maximum angle points for forming the first global maximum angle.

[0145] In an embodiment, the processor may determine whether at least one of the first maximum angle, the first maximum angle point, and any combination thereof is stored in the memory up to a specified number (e.g., about 50) based on identifying the first global maximum angle point. In an embodiment, the processor may generate a first FOV by using at least one of the first global minimum angle, the first global minimum angle point, the first global maximum angle, the first global maximum angle point, and any combination thereof based on identifying that the first maximum angle is stored up to a specified number or more and the first maximum angle point is stored up to a specified number or more.

[0146] Figure 4 An embodiment of a vehicle control device that identifies a minimum angle and a maximum angle to generate a second FOV in an embodiment of the present disclosure is shown.

[0147] Figure 4 The host vehicle 400 may include Figure 1 A vehicle control device 100 is provided.

[0148] See also Figure 4 , the processor of the vehicle control device according to the embodiment can identify a grounding point showing the ground. Figure 4 The point shown in may be referred to as a "ground point".

[0149] In an embodiment, the processor may identify a grounding point in a layer at or below the specified level. For example, the specified level may include about 5 levels. The processor may identify a grounding point in a layer below level 5. For example, the processor may identify a grounding point in a layer between the lowest layer of level 1 and the layer of level 5.

[0150] In an embodiment, the processor may identify a half-line 410 facing in the positive direction of the y-axis from the host vehicle 400. The processor may identify an angle between the half-line 410 and the ground contact point.

[0151] In an embodiment, the processor may identify the angle between the half line 410 and the ground point in a plurality of frames. In a plurality of frames, the processor may identify at least one of a minimum angle, a maximum angle, and any combination thereof among the angles between the half line 410 and the ground point.

[0152] In an embodiment, in each frame of the plurality of frames, the processor may obtain the second minimum angle based on identifying the minimum angle between the half-line 410 and the grounding point. The processor may identify the second minimum angle point for forming the second minimum angle between the grounding points.

[0153] In an embodiment, in each frame of the plurality of frames, the processor may obtain the second maximum angle based on identifying the maximum angle between the half line 410 and the grounding point. The processor may identify the second maximum angle point for forming the second maximum angle between the grounding points.

[0154] In an embodiment, the processor may identify at least one of a second minimum angle, a second minimum angle point, a second maximum angle, a second maximum angle point, and any combination thereof. The processor may store at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof in a memory.

[0155] In an embodiment, the processor may store at least one of a second minimum angle, a second minimum angle point, a second maximum angle, the second maximum angle point, and any combination thereof in the memory, and the processor may also store at least one of a direction facing the LiDAR, an index, and any combination thereof.

[0156] In an embodiment, the processor may determine whether at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is stored in the memory up to a specified number (eg, approximately 50).

[0157] Based on the fact that at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is stored in the memory for more than a specified number, the processor 110 can identify at least one of the second global minimum angle, the second global minimum angle point, the second global maximum angle, the second global maximum angle point, and any combination thereof.

[0158] For example, the processor may identify a second global minimum angle that is a minimum value among the second minimum angles. The processor may identify a second global minimum angle point from among the second minimum angle points for forming the second global minimum angle.

[0159] For example, the processor may identify a second global maximum angle that is a maximum value among the second maximum angles. The processor may identify a second global maximum angle point from among the second maximum angle points for forming the second global maximum angle.

[0160] The processor may establish a second FOV based on at least one of a second global minimum angle, a second global minimum angle point, a second global maximum angle, a second global maximum angle point, and any combination thereof.

[0161] For example, the processor may generate a second FOV including a second global minimum angle point and a second global maximum angle point.

[0162] Based on the fact that at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is stored in the memory so that the number of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is less than a specified number, the processor 110 may additionally or alternatively perform processing to obtain at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof.

[0163] Figure 5 An example is shown in which the vehicle control device according to the embodiment of the present disclosure determines an abnormal state of a boundary area.

[0164] Figure 5 The host vehicle 500 may include Figure 1 A vehicle control device 100 is provided.

[0165] See also Figure 5 The processor of the vehicle control device according to the embodiment can identify the abnormal state of the boundary area based on the third FOV and the angle information. For example, the processor can specify at least one of the first ROI, the second ROI, and any combination thereof based on the first angle, the second angle, and any combination thereof of the half line 510 facing the positive direction of the y-axis from the host vehicle 500.

[0166] In an embodiment, the processor may identify the angle 535 included in the angle information included in the specification information. The processor may identify the difference between the third FOV 530 and the angle 535 included in the angle information. The processor may determine the state of the boundary area 520 of the LiDAR based on the difference between the third FOV 530 and the angle 535 included in the angle information.

[0167] The processor may determine that the state of the boundary area 520 of the LiDAR is an abnormal state based on that the difference between the third FOV 530 and the angle 535 included in the angle information is identified as being greater than or equal to a designated angle.

[0168] In an embodiment, before the contamination level of the LiDAR is included in the specification information and identified as a threshold for determining the contamination state of the LiDAR, the processor may determine the abnormal state of the boundary area 520 based on the difference between the third FOV 530 and the angle 535 included in the angle information.

[0169] As described above, in an embodiment, before the contamination level of the LiDAR is included in the specification information and is identified as a threshold for determining the contamination state of the LiDAR, the processor may determine the abnormal state of the boundary area 520 based on the difference between the third FOV 530 and the angle 535 included in the angle information, and then may provide guidance to the user. The processor may determine the abnormal state of the boundary area 520 and may guide the user so that he / she may take action to prevent the performance degradation of the LiDAR.

[0170] Figure 6 An embodiment of a flowchart related to a vehicle control method according to an embodiment of the present disclosure is shown.

[0171] In the following, it is assumed Figure 1 The vehicle control device 100 executes Figure 6 Additionally or alternatively, Figure 6 In the description, it can be understood that the operations described as being performed by the device are controlled by the processor 110 of the vehicle control device 100.

[0172] Figure 6 At least one of the operations may be performed by Figure 1 The vehicle control device 100 is executed. Figure 6 Each operation in can be performed sequentially, but not necessarily sequentially. For example, the order of the operations can be changed, and at least two operations can be performed in parallel.

[0173] See also Figure 6In operation S601, the vehicle control method according to the embodiment may include: identifying a virtual frame corresponding to an external object identified in an ROI of a plane formed by an x-axis and a y-axis among an x-axis, a y-axis, and a z-axis, and generating a first FOV based on the virtual frame. Figure 7 The operation of generating the first FOV is described in .

[0174] In operation S603, the vehicle control method according to the embodiment may include an operation of identifying a ground point indicating the ground on a plane formed by the x-axis and the y-axis and generating a second FOV based on the ground point. Figure 8 The operation of generating the second FOV is described in .

[0175] In operation S605, the vehicle control method according to the embodiment may include an operation of determining the state of the boundary area of ​​the LiDAR by identifying the third FOV based on at least one of the first FOV, the second FOV, the angle information included in the specification information, and any combination thereof. For example, the specification information may include information stored in a memory or transmitted from the outside.

[0176] The vehicle control method according to the embodiment may include an operation of determining a state of a boundary area of ​​the LiDAR based on a difference between the third FOV and the angle information.

[0177] For example, the vehicle control method may include an operation of determining a normal state of a boundary area of ​​the LiDAR based on the difference between the third FOV and the angle information being less than a specified angle.

[0178] For example, the vehicle control method may include an operation of determining an abnormal state of a boundary area of ​​the LiDAR based on the difference between the third FOV and the angle information being greater than or equal to a specified angle. In an embodiment, the vehicle control method may include an operation of determining an abnormal state of at least one of the first ROI, the second ROI, and any combination thereof based on at least one of the first FOV, the second FOV, the third FOV, the angle information, and any combination thereof after determining the abnormal state of the boundary area.

[0179] For example, the vehicle control method may include an operation of determining an abnormal state of the first ROI based on the fact that a global minimum angle included in the third FOV is greater than a minimum angle included in the angle information. For example, the vehicle control method may include an operation of determining an abnormal state of the second ROI based on the fact that a global maximum angle included in the third FOV is less than a maximum angle included in the angle information.

[0180] Figure 7 An embodiment of a flowchart related to a vehicle control method according to an embodiment of the present disclosure is shown.

[0181] In the following, it is assumed Figure 1 The vehicle control device 100 executes Figure 7 Additionally or alternatively, Figure 7 In the description, it can be understood that the operations described as being performed by the device are controlled by the processor 110 of the vehicle control device 100.

[0182] Figure 7 At least one of the operations may be performed by Figure 1 The vehicle control device 100 is executed. Figure 7 Each operation in can be performed sequentially, but not necessarily sequentially. For example, the order of the operations can be changed, and at least two operations can be performed in parallel.

[0183] See also Figure 7 In operation S701, the vehicle control method according to the embodiment may include: an operation of specifying a first ROI from the ROI, the first ROI including an area rotated clockwise by a first angle based on a half line facing the positive direction of the y-axis from the main vehicle. For example, the first ROI may be referred to as a "lower limit area".

[0184] In operation S703, the vehicle control method according to the embodiment may include an operation of identifying a virtual frame in the first ROI. For example, the virtual frame may include a virtual frame corresponding to an external object.

[0185] In operation S705, the vehicle control method according to the embodiment may include the following operation: in each frame of a plurality of frames, identifying a minimum angle among angles between a half line and a first line segment connecting the host vehicle and each of a plurality of points included in a virtual frame identified in a first ROI.

[0186] In operation S707, the vehicle control method according to the embodiment may include the following operation: storing at least one of the first minimum angle identified in each frame of multiple frames, the first minimum angle point among multiple points used to form the first minimum angle, and any combination thereof in a memory.

[0187] For example, the vehicle control method may include an operation of sequentially storing at least one of the first minimum angle, the first minimum angle point, and any combination thereof in a designated area of ​​a memory.

[0188] For example, the vehicle control method may include an operation of storing at least one of the first minimum angle, the first minimum angle point, and any combination thereof in a designated area of ​​a memory. For example, the designated area of ​​the memory may be referred to as a "queue."

[0189] In operation S709, the vehicle control method according to the embodiment may include the following operation: identifying at least one of a first global minimum angle as a minimum value among the first minimum angles, a first global minimum angle point among the first minimum angle points for forming the first global minimum angle, and any combination thereof.

[0190] In operation S711 , the vehicle control method according to the embodiment may include an operation of determining whether at least one of a first minimum angle, a first minimum angle point, and any combination thereof is stored in a memory more than a specified number.

[0191] If at least one of the first minimum angle, the first minimum angle point, and any combination thereof is stored in the memory more than a specified number ("Yes" in operation S711), then in operation S713, the vehicle control method according to the embodiment may include the following operations: specifying a second ROI from the ROI, the second ROI including an area rotated clockwise by a second angle greater than the first angle based on a half line facing the positive direction of the y-axis from the main vehicle.

[0192] If at least one of the first minimum angle, the first minimum angle point, and any combination thereof is stored in the memory so that the number of the first minimum angle, the first minimum angle point, and any combination thereof is less than a specified number (No in operation S711), then in operation S703, the vehicle control method according to the embodiment may include an operation of identifying a virtual box in the first ROI.

[0193] For example, the vehicle control method may include the following operations: additionally or alternatively identifying these virtual frames and obtaining at least one of the first minimum angle, the first minimum angle point, and any combination thereof until at least one of the first minimum angle, the first minimum angle point, and any combination thereof is stored in the memory up to a specified number.

[0194] In operation S715, the vehicle control method according to the embodiment may include the following operation: in each of the plurality of frames, identifying a maximum angle among angles between a half line and a second line segment connecting the host vehicle and each of the plurality of points included in the virtual frame identified in the second ROI.

[0195] In operation S717, the vehicle control method according to the embodiment may include an operation of identifying at least one of a first global maximum angle, a first global maximum angle point, and any combination thereof, wherein the first global maximum angle is the maximum value of the first maximum angles included in each frame of a plurality of frames, and the first global maximum angle point is used to form a first global maximum angle in the first maximum angle point.

[0196] In operation S719 , the vehicle control method according to the embodiment may include an operation of generating a first FOV based on at least one of a first global minimum angle, a first global minimum angle point, a first global maximum angle, a first global maximum angle point, and any combination thereof.

[0197] For example, the vehicle control method may include an operation of generating a first FOV based on an area between a first global minimum angle point and a first global maximum angle point.

[0198] Figure 8 An embodiment of a flowchart related to a vehicle control method according to an embodiment of the present disclosure is shown.

[0199] In the following, it is assumed Figure 1 The vehicle control device 100 executes Figure 8 Additionally or alternatively, Figure 8 In the description, it can be understood that the operations described as being performed by the device are controlled by the processor 110 of the vehicle control device 100.

[0200] Figure 8 At least one of the operations may be performed by Figure 1 The vehicle control device 100 is executed. Figure 8 Each operation in can be performed sequentially, but not necessarily sequentially. For example, the order of the operations can be changed, and at least two operations can be performed in parallel.

[0201] See also Figure 8 In operation S801, the vehicle control method according to the embodiment may include the following operation: in multiple frames, identifying the minimum angle and the maximum angle between the third line segment or the fourth line segment connecting the main vehicle to each of the grounding points and the half line facing the positive direction of the y-axis from the main vehicle.

[0202] For example, the vehicle control method may include an operation of identifying a third line segment connecting the host vehicle and each ground point. For example, the vehicle control method may include an operation of identifying a fourth line segment connecting the host vehicle to each ground point.

[0203] For example, the vehicle control method may include an operation of identifying an angle between a third line segment and a half line facing the positive direction of the y-axis from the host vehicle. For example, the vehicle control method may include an operation of identifying an angle between a fourth line segment and a half line facing the positive direction of the y-axis from the host vehicle.

[0204] For example, the vehicle control method may include an operation of identifying the minimum angle among the angles between the third line segment and the half line facing the positive direction of the y-axis from the host vehicle. For example, the vehicle control method may include an operation of identifying the maximum angle among the angles between the fourth line segment and the half line facing the positive direction of the y-axis from the host vehicle.

[0205] In operation S803, the vehicle control method according to the embodiment may include the following operations: storing at least one of the second minimum angle identified in each frame of multiple frames, the second minimum angle point in the grounding point used to form each second minimum angle, the second maximum angle, the second maximum angle point in the grounding point used to form each second maximum angle, and any combination thereof in a memory.

[0206] For example, the vehicle control method may include an operation of sequentially storing at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof in a memory.

[0207] In operation S805 , the vehicle control method according to the embodiment may include the following operation: determining whether at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, or any combination thereof is stored in the memory for more than a specified number.

[0208] For example, the vehicle control method may include the following operation: determining whether at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is stored in a specific area of ​​the memory more than a specified number.

[0209] If at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is stored in the memory for more than a specified number ("Yes" in operation S805), in operation S807, the vehicle control method according to the embodiment may include the following operations: obtaining a second global minimum angle as the minimum value among the second minimum angles, a second global minimum angle point among the second minimum angle points for forming a second global minimum angle, a second global maximum angle as the maximum value among the second maximum angles, a second global maximum angle point for forming the second global maximum angle, and at least one of any combination thereof.

[0210] If at least one of the second minimum angle, the second minimum angle point, the second maximum angle, the second maximum angle point, and any combination thereof is stored in the memory for more than a specified number (No in operation S805), in operation S803, the vehicle control method according to the embodiment may include the following operation: additionally or alternatively performing an operation of storing in the memory at least one of the second minimum angle identified in each frame of a plurality of frames, the second minimum angle point in the grounding point for forming each second minimum angle, the second maximum angle, the second maximum angle point in the grounding point for forming each second maximum angle, and any combination thereof.

[0211] In operation S809, the vehicle control method according to the embodiment may include the following operation: an operation of generating a second FOV based on at least one of a second global minimum angle, a second global minimum angle point, a second global maximum angle, a second global maximum angle point, and any combination thereof.

[0212] For example, the vehicle control method may include an operation of generating a second FOV including an area between a second global minimum angle and a second global maximum angle.

[0213] Fig. 9 An embodiment of a flowchart related to a vehicle control method according to an embodiment of the present disclosure is shown.

[0214] In the following, it is assumed Figure 1 The vehicle control device 100 executes Fig. 9 Additionally or alternatively, Fig. 9 In the description, it can be understood that the operations described as being performed by the device are controlled by the processor 110 of the vehicle control device 100.

[0215] Fig. 9 At least one of the operations may be performed by Figure 1 The vehicle control device 100 is executed. Fig. 9 Each operation in can be performed sequentially, but not necessarily sequentially. For example, the order of the operations can be changed, and at least two operations can be performed in parallel.

[0216] See also Fig. 9 In operation S901, the vehicle control method according to the embodiment may include the following operation: identifying a third FOV based on at least one of the first FOV, the second FOV, angle information included in the specification information, and any combination thereof.

[0217] For example, the vehicle control method may include an operation of identifying a FOV closer to the angle information among the first FOV and the second FOV. For example, the vehicle control method may include an operation of identifying a third FOV based on identifying a FOV closer to the angle information among the first FOV and the second FOV.

[0218] In operation S903, the vehicle control method according to the embodiment may include an operation of determining whether the difference between the third FOV and the angle information is less than a specified angle. The vehicle control method may include an operation of determining the state of the boundary area of ​​the LiDAR based on the difference between the third FOV and the angle information.

[0219] If the difference between the third FOV and the angle information is less than the designated angle (Yes in operation S903 ), the vehicle control method according to the embodiment may include an operation of determining a normal state of a boundary area of ​​the LiDAR in operation S905 .

[0220] If the difference between the third FOV and the angle information is greater than or equal to the designated angle (No in operation S903 ), the vehicle control method according to the embodiment may include an operation of determining an abnormal state of a boundary area of ​​the LiDAR in operation S907 .

[0221] Fig.10 A computing system including a vehicle control device according to an embodiment of the present disclosure is shown.

[0222] See also Fig.10 , the computing system 1000 may include at least one processor 1100 , a memory 1300 , a user interface input device 1400 , a user interface output device 1500 , a storage device 1600 , and a network interface 1700 connected to each other via a bus 1200 .

[0223] The processor 1100 may be a central processing unit (CPU) or a semiconductor device that processes instructions stored in the memory 1300 and / or the storage device 1600. Each of the memory 1300 and the storage device 1600 may include various types of volatile or non-volatile storage media. For example, the memory 1300 may include a read-only memory (ROM) and a random access memory (RAM).

[0224] Therefore, the operation of the method or algorithm described in conjunction with the embodiments disclosed in the specification can be directly implemented using a hardware module, a software module, or a combination of a hardware module and a software module, which is executed by the processor 1100. The software module may reside on a storage medium (i.e., the memory 1300 and / or the storage device 1600), such as a random access memory (RAM), a flash memory, a read-only memory (ROM), an erasable and programmable ROM (EPROM), an electrically EPROM (EEPROM), a register, a hard disk drive, a removable disk, or a compact disk ROM (CD-ROM).

[0225] The storage medium may be coupled to the processor 1100. The processor 1100 may read information from the storage medium and may write information into the storage medium. Alternatively, the storage medium may be integrated with the processor 1100. The processor and the storage medium may be implemented with an application specific integrated circuit (ASIC). The ASIC may be provided in a user terminal. Alternatively, the processor and the storage medium may be implemented with separate components in a user terminal.

[0226] The present disclosure has been made to solve the above-mentioned problems occurring in the prior art while keeping the advantages achieved by the prior art intact.

[0227] An embodiment of the present disclosure provides a vehicle control apparatus and method thereof, which recognizes a FOV of a LiDAR by using a virtual frame corresponding to an external object obtained by using the LiDAR or a ground point indicating the ground.

[0228] Embodiments of the present disclosure provide a vehicle control apparatus and method thereof for determining a state of a boundary area of ​​a LiDAR by identifying a FOV of the LiDAR and comparing the identified FOV with specification information of the LiDAR.

[0229] An embodiment of the present disclosure provides a vehicle control apparatus and method thereof for determining a state of a boundary area of ​​a LiDAR by using a FOV before recognizing a contamination level of the LiDAR as a threshold value.

[0230] The technical problems to be solved by the present disclosure are not limited to the above-mentioned problems, and any other technical problems not mentioned herein will be clearly understood by those skilled in the art to which the present disclosure belongs from the accompanying description.

[0231] According to an embodiment of the present disclosure, a vehicle control device may include a light detection and ranging (LiDAR), a processor, and a memory. The processor may identify a virtual frame corresponding to an external object identified in a region of interest (ROI) of a plane formed by a first axis and a second axis among a first axis, a second axis, and a third axis in a plurality of frames obtained by using the LiDAR, and generate a first field of view (FOV) based on the virtual frame, may identify a ground point indicating the ground on the plane and generate a second FOV based on the ground point, and determine the state of a boundary area of ​​the LiDAR by identifying a third FOV based on at least one of the first FOV, the second FOV, the angle information included in the specification information, and a combination of the first FOV, the second FOV, and the angle information.

[0232] In an embodiment, the processor may specify a first region of interest (ROI) from the ROI and may identify the virtual box in the first ROI, the first region of interest including an area rotated clockwise by a first angle based on a half line facing the positive direction of the second axis from the host vehicle.

[0233] In an embodiment, the processor may identify, in each of a plurality of frames, a minimum angle among angles between a half-line and a first line segment connecting the host vehicle and each of a plurality of points included in a virtual frame identified in a first ROI, and may store in the memory at least one of the first minimum angle identified in each of the plurality of frames, the first minimum angle point used to form each of the first minimum angles among the plurality of points, or a combination of the first minimum angle and the first minimum angle point.

[0234] In an embodiment, the processor can obtain at least one of the following: a first global minimum angle, which is the minimum value among the first minimum angles; a first global minimum angle point, which is used to form the first global minimum angle among the first minimum angle points; and a combination of the first global minimum angle and the first global minimum angle point, and can determine the reliability of at least one of the first global minimum angle, the first global minimum angle point, and the combination of the first global minimum angle and the first global minimum angle point based on determining whether at least one of the first minimum angle, the first minimum angle point, and the combination of the first minimum angle and the first minimum angle point is stored in the memory for more than a specified number.

[0235] In an embodiment, the processor may specify a second ROI from the ROIs and may identify the virtual frame in the second ROI, the second ROI including an area rotated clockwise by a second angle greater than the first angle based on a half line facing the positive direction of the second axis from the host vehicle.

[0236] In an embodiment, the processor may identify, in each of a plurality of frames, a maximum angle among angles between a half line and a second line segment connecting the host vehicle and each of a plurality of points in a virtual frame identified in a second ROI, and may store in the memory at least one of a first maximum angle identified in each of the plurality of frames, a first maximum angle point used to form each of the first maximum angles among the plurality of points, and a combination of the first maximum angle and the first maximum angle point.

[0237] In an embodiment, the processor can obtain at least one of the following: a first global maximum angle, which is the minimum value among the first maximum angles; a first global maximum angle point, which is used to form the first global maximum angle among the first maximum angle points; and a combination of the first global maximum angle and the first global maximum angle point, and based on determining whether at least one of the first maximum angle, the first maximum angle point, and the combination of the first maximum angle and the first maximum angle point is stored in the memory for more than a specified number, the reliability of at least one of the first global maximum angle, the first global maximum angle point, and the combination of the first global maximum angle and the first global maximum angle point can be determined.

[0238] In an embodiment, the processor may identify, in each of a plurality of frames, a minimum angle among angles between a half-line facing the main vehicle in the positive direction of the second axis and a third line segment connecting the main vehicle and each ground contact point, and may store in a memory at least one of a second minimum angle identified in each of a plurality of frames, a second minimum angle point in the ground contact point used to form each of the second minimum angles, and a combination of the second minimum angle and the second minimum angle point.

[0239] In an embodiment, the processor can obtain at least one of the following items: a second global minimum angle, the second global minimum angle being the minimum value among the second minimum angles; a second global minimum angle point, the second global minimum angle point being used to form the second global minimum angle among the second minimum angle points, and a combination of the second global minimum angle and the second global minimum angle point, and based on determining whether at least one of the second minimum angle, the second minimum angle point, and the combination of the second minimum angle and the second minimum angle point is stored in the memory for more than a specified number, the reliability of at least one of the second global minimum angle, the second global minimum angle point, and the combination of the second global minimum angle and the second global minimum angle point can be determined.

[0240] In an embodiment, the processor may identify, in each of a plurality of frames, a maximum angle among angles between a half-line facing the main vehicle in the positive direction of the second axis and a fourth line segment connecting the main vehicle and each ground contact point, and may store in a memory at least one of the second maximum angle identified in each of the plurality of frames, a second maximum angle point in the ground contact point used to form each of the second maximum angles, and a combination of the second maximum angle and the second maximum angle point.

[0241] In an embodiment, the processor may obtain at least one of the following: a second global maximum angle, which is the minimum value among the second maximum angles; a second global maximum angle point, which is used to form the second global maximum angle among the second maximum angle points, and a combination of the second global maximum angle and the second global maximum angle point, and based on determining whether at least the second maximum angle, the second maximum angle point, and the combination of the second maximum angle and the second maximum angle point are stored in the memory for more than a specified number, the reliability of at least one of the second global maximum angle, the second global maximum angle point, and the combination of the second global maximum angle and the second global maximum angle point can be determined.

[0242] In an embodiment, the processor may determine the normal state of the boundary area of ​​the LiDAR based on that a difference between the third FOV and the angle information included in the designated information is less than a designated angle.

[0243] In an embodiment, the processor may determine the abnormal state of the boundary area of ​​the LiDAR based on that a difference between the third FOV and the angle information included in the designated information is greater than or equal to a designated angle.

[0244] In an embodiment, after determining the abnormal state, the processor may determine the abnormal state of at least one of the first ROI, the second ROI, and the combination of the first ROI and the second ROI based on at least one of the first FOV, the second FOV, the third FOV, the angle information, and the combination of the first FOV, the second FOV, the third FOV, and the angle information.

[0245] In an embodiment, the processor may determine the state of the boundary area based on at least one of the first FOV, the second FOV, the third FOV, the angle information included in the specification information, and a combination of the first FOV, the second FOV, the third FOV and the angle information before the contamination level of the LiDAR is included in the specification information and identified as a threshold for determining the contamination state of the LiDAR.

[0246] According to an embodiment of the present disclosure, a vehicle control method may include: identifying a virtual frame corresponding to an external object identified in an ROI of a plane formed by a first axis and a second axis among a first axis, a second axis, and a third axis, among a plurality of frames obtained by using a LiDAR, and generating a first FOV based on the virtual frame, identifying a ground point indicating a ground on the plane and generating a second FOV based on the ground point, and determining a state of a boundary area of ​​the LiDAR by identifying a third FOV based on at least one of the first FOV, the second FOV, angle information included in specification information of the LiDAR, and a combination of the first FOV, the second FOV, and the angle information.

[0247] According to an embodiment, the vehicle control method may further include, in each of the plurality of frames, specifying a first ROI from the ROIs, the first ROI including an area rotated clockwise by a first angle based on a half line facing the main vehicle in a positive direction of a second axis; specifying a second ROI including an area rotated clockwise by a second angle greater than the first angle based on the half line, identifying a minimum angle among angles between the half line and a first line segment connecting each of a plurality of points included in the virtual frame identified with the first ROI, and identifying a maximum angle among angles between the half line and the second line segment connecting each of a plurality of points included in the virtual frame identified with the second ROI, identifying a first minimum angle identified in each of the plurality of frames, wherein the first minimum angle is the maximum angle among the angles between the half line and the second line segment connecting the main vehicle and each of the plurality of points included in the virtual frame identified with the second ROI. a first minimum angle point for forming each angle in the first minimum angle, a first maximum angle identified in each frame in the multiple frames, a first maximum angle point for forming each angle in the first maximum angle in the multiple points, and at least one of the first minimum angle, the first minimum angle point, the first maximum angle and the first maximum angle point in combination, and generating a first FOV based on a first global minimum angle, which is the minimum value of the first minimum angle; a first global minimum angle point, which is the maximum value of the first maximum angles; a first global maximum angle point, which is the first global maximum angle in the first maximum angle points, and at least one of the first global minimum angle, the first global minimum angle point, the first global maximum angle and the first global maximum angle point in combination.

[0248] According to an embodiment, the vehicle control method may further include: in each of a plurality of frames, identifying the minimum angle among the angles between a half-line from the main vehicle facing the positive direction of the second axis and a third line segment connecting the main vehicle and each of the grounding points; and in each of a plurality of frames, identifying the maximum angle among the angles between a half-line from the main vehicle facing the positive direction of the second axis and a fourth line segment connecting the main vehicle and each of the grounding points, and generating a second FOV based on: a second global minimum angle, which is the minimum value of the second minimum angle; a second global minimum angle point, which is used to form a second global minimum angle in the second minimum angle point; a second global maximum angle, which is the maximum value in the second maximum angle; a second global maximum angle point, which is used to form a second global maximum angle in the second maximum angle point; and a second global minimum angle, at least one of the combinations of the second global minimum angle point, the second global maximum angle and the second global maximum angle point.

[0249] According to an embodiment, the vehicle control method may further include determining a normal state of a boundary area of ​​the LiDAR based on that a difference between the third FOV and the angle information included in the specified information is less than a specified angle, or determining an abnormal state of a boundary area of ​​the LiDAR based on that a difference between the third FOV and the angle information included in the specified information is greater than or equal to a specified angle.

[0250] According to an embodiment, the vehicle control method may further include: identifying, in each of a plurality of frames, a maximum angle between a half line and an angle between a second line segment connecting the host vehicle and each of a plurality of points included in a virtual frame identified in a second ROI, and storing in the memory at least one of a first maximum angle identified in each of the plurality of frames, a first maximum angle point used to form each of the plurality of points, and a combination of the first maximum angle and the first maximum angle point.

[0251] The above description is merely an embodiment of the technical concept of the present disclosure, and various modifications and changes may be made by those skilled in the art without departing from the essential features of the present disclosure.

[0252] Therefore, the embodiments of the present disclosure are not intended to limit but to explain the technical concept of the present disclosure, and the scope and spirit of the present disclosure are not limited by the above embodiments. The protection scope of the present disclosure should be interpreted by the attached claims, and all equivalents thereof should be interpreted as included in the scope of the present disclosure.

[0253] According to an embodiment of the present disclosure, the vehicle control device may recognize the FOV of the LiDAR by using a virtual frame corresponding to an external object obtained by using the LiDAR or a ground point indicating the ground.

[0254] Furthermore, according to an embodiment of the present disclosure, the vehicle control device may determine the state of the boundary area of ​​the LiDAR by identifying the FOV of the LiDAR and comparing the identified FOV with the specification information of the LiDAR.

[0255] According to an embodiment of the present disclosure, the vehicle control device may determine the state of the boundary area of ​​the LiDAR by using the FOV before the contamination level of the LiDAR is recognized as a threshold value.

[0256] Furthermore, various effects understood directly or indirectly through the specification can be provided.

[0257] Although the present disclosure has been described above with reference to the embodiments and the accompanying drawings, the present disclosure is not limited thereto, but various modifications and changes may be made by those skilled in the art without departing from the spirit and scope of the present disclosure as claimed in the appended claims.

Claims

1. A device for controlling a vehicle, the device comprising: sensor; processor; as well as a memory configured to store specification information of the sensor, Wherein, the processor is configured to: determining, based on a plurality of frames obtained by using the sensor, a plane formed by a first axis and a second axis, the second axis corresponding to a traveling direction of the vehicle, and the first axis being perpendicular to the second axis; detecting objects external to the vehicle in a region of interest in the plane; determining a virtual frame corresponding to the object; generating a first field of view based on the virtual frame; determining a ground point indicating ground on the plane; generating a second field of view based on the ground point; The third field of view is generated based on at least one of the following: The first field of view, the second field of view, and Angle information included in the specification information; determining a state of a boundary region of the sensor based on the third field of view; and A signal is outputted indicating a determined state of the boundary region of the sensor.

2. The device according to claim 1, wherein: The processor is configured to: Specifying a first region of interest among the regions of interest, wherein the first region of interest includes an area between: line, rotated by a first angle from a half line facing in the positive direction of the second axis, and the half line; and A virtual box in the first region of interest is determined.

3. The device according to claim 2, wherein: The processor is configured to: determining a plurality of line segments, each of the plurality of line segments connecting the vehicle and one of the plurality of points contained in the virtual frame in the first region of interest; Determine multiple angles between: the plurality of line segments, and said half line; determining, in each frame of the plurality of frames, a minimum angle among the plurality of angles; as well as At least one of the following is stored in the memory: a first minimum angle including said minimum angle, and A first minimum angle point among the plurality of points is used to form each of the first minimum angles, wherein the first minimum angle point is determined in each frame among the plurality of frames.

4. The device according to claim 3, wherein: The processor is configured to: Get at least one of the following: a first global minimum angle, the first global minimum angle being the minimum of the first minimum angles, and A first global minimum angle point among the first minimum angle points for forming the first global minimum angle; as well as Based on determining whether at least one of the number of the first minimum angles stored in the memory and the number of the first minimum angle points stored in the memory satisfies a threshold number, Determine a reliability value for at least one of the following: the first global minimum angle, and The first global minimum angle point.

5. The device according to claim 2, wherein: The processor is configured to: Specify a second region of interest that includes the area between: line, rotated from the half line by a second angle greater than the first angle, and another line, rotated from the half line by a third angle; and A virtual box in the second region of interest is determined.

6. The device according to claim 5, wherein: The processor is configured to: determining a plurality of line segments, each of the plurality of line segments connecting the vehicle and one of the plurality of points included in the virtual frame in the second region of interest; Determine multiple angles between: the plurality of line segments, and said half line; In each frame of the plurality of frames, determining a maximum angle of the plurality of angles; as well as At least one of the following is stored in the memory: a first maximum angle including said maximum angle, and A first maximum angle point among the plurality of points is used to form each of the first maximum angles, wherein the first maximum angle point is determined in each frame among the plurality of frames.

7. The device according to claim 6, wherein: The processor is configured to: Get at least one of the following: a first global maximum angle, the first global maximum angle being a minimum value among the first maximum angles, and A first global maximum angle point among the first maximum angle points for forming the first global maximum angle; as well as Based on determining whether at least one of the number of the first maximum angles stored in the memory and the number of the first maximum angle points stored in the memory satisfies a threshold number, Determine a reliability value for at least one of the following: the first global maximum angle, and The first global maximum angle point.

8. The device according to claim 1, wherein: The processor is configured to: determining a plurality of third line segments, each line segment of the plurality of third line segments connecting the vehicle and one of the grounding points; Determine multiple angles between: the plurality of third line segments, and a half line, facing in the positive direction of the second axis; identifying, in each frame of the plurality of frames, a minimum angle among the plurality of angles; as well as At least one of the following is stored in the memory: a second minimum angle including said minimum angle, and A second minimum angle point in the grounding point for forming each of the second minimum angles, wherein the second minimum angle point is determined in each of the plurality of frames.

9. The device according to claim 8, wherein: The processor is configured to: Get at least one of the following: a second global minimum angle, the second global minimum angle being the minimum of the second minimum angles, and A second global minimum angle point among the second minimum angle points for forming the second global minimum angle; as well as Based on determining whether at least one of the number of the second minimum angles stored in the memory and the number of the second minimum angle points stored in the memory satisfies a threshold number, Determine a reliability value for at least one of the following: the second global minimum angle, and The second global minimum angle point.

10. The device according to claim 1, wherein: The processor is configured to: determining a plurality of fourth line segments, each line segment of the plurality of fourth line segments connecting the vehicle and one of the grounding points; Determine multiple angles between: the plurality of fourth line segments, and a half line, facing in the positive direction of the second axis; identifying, in each frame of the plurality of frames, a maximum angle among the plurality of angles; as well as At least one of the following is stored in the memory: a second maximum angle including said maximum angle, and A second maximum angle point in the grounding point for forming each of the second maximum angles, wherein the second maximum angle point is determined in each of the plurality of frames.

11. The device according to claim 10, wherein: The processor is configured to: Get at least one of the following: a second global maximum angle, the second global maximum angle being the minimum of the second maximum angles, and a second global maximum angle point among the second maximum angle points for forming the second global maximum angle; as well as Based on determining whether at least one of the number of the second maximum angles stored in the memory and the number of the second maximum angle points stored in the memory satisfies a threshold number, Determine a reliability value for at least one of the following: the second global maximum angle, and The second global maximum angle point.

12. The device according to claim 1, wherein: The processor is configured to: A normal state of the boundary area of ​​the sensor is determined based on a difference between the third field of view and the angle information satisfying a threshold angle.

13. The device according to claim 5, wherein: The processor is configured to: An abnormal state of the boundary area of ​​the sensor is determined based on a difference between the third field of view and the angle information satisfying a threshold angle.

14. The device according to claim 13, wherein: The processor is configured to: After determining the abnormal state of the boundary area, Based on at least one of the following: The first field of view, The second field of view, the third field of view, and The angle information, An abnormal state of at least one of the first region of interest and the second region of interest is determined.

15. The device according to claim 1, wherein: The processor is configured to: Prior to determining the contamination state of the sensor and including the contamination level of the sensor in the specification information, determining the state of the boundary area is based on at least one of: The first field of view, The second field of view, the third field of view, and The angle information, wherein the pollution state is determined based on the pollution level satisfying a threshold.

16. A method for controlling a vehicle, the method comprising: A plurality of frames are obtained by a sensor; determining a plane formed by a first axis and a second axis based on the plurality of frames, the second axis corresponding to a traveling direction of the vehicle, and the first axis being perpendicular to the second axis; detecting objects external to the vehicle in a region of interest in the plane; determining a virtual frame corresponding to the object; generating a first field of view based on the virtual frame; determining a ground point indicating ground on the plane; generating a second field of view based on the ground point; The third field of view is generated based on at least one of: The first field of view, the second field of view, and Angle information included in the sensor's specification information; determining a state of a boundary region of the sensor based on the third field of view; as well as A signal representing a determined state of the boundary region of the sensor is output.

17. The method according to claim 16, further comprising: A first region of interest is specified among the regions of interest, wherein the first region of interest includes a region between: line, rotated by a first angle from a half line facing in the positive direction of the second axis, and said half line; determining a virtual frame in the first region of interest; Specify a second region of interest that includes the area between: a line rotated from the half-line by a second angle greater than the first angle, and another line rotated from the half-line by a third angle; determining a virtual frame in the second region of interest; determining a plurality of first line segments, each of the plurality of first line segments connecting the vehicle and a first point among a plurality of first points included in the virtual frame in the first region of interest; Determine multiple first angles between: the plurality of first line segments, and said half line; In each frame of the plurality of frames, determining a minimum angle of the plurality of first angles; determining a plurality of second line segments, each of the plurality of second line segments connecting the vehicle and one of the plurality of second points included in the virtual frame in the second region of interest; Determine a plurality of second angles between: the plurality of second line segments, and said half line; In each frame of the plurality of frames, determining a maximum angle of the plurality of second angles; Identify at least one of the following: a first minimum angle determined in each frame of the plurality of frames, A first minimum angle point for forming each first minimum angle among the plurality of first points, a first maximum angle determined in each frame of the plurality of frames, and a first maximum angle point among the plurality of second points for forming each first maximum angle; as well as The first field of view is generated based on at least one of the following: a first global minimum angle, the first global minimum angle being the minimum value of the first minimum angles, A first global minimum angle point among the first minimum angle points for forming the first global minimum angle, a first global maximum angle, the first global maximum angle being the maximum value of the first maximum angles, and A first global maximum angle point among the first maximum angle points is used to form the first global maximum angle.

18. The method according to claim 16, further comprising: determining a plurality of third line segments, each line segment of the plurality of third line segments connecting the vehicle and one of the grounding points; Determine multiple first angles between: the plurality of third line segments, and a half line, facing in the positive direction of the second axis; In each frame of the plurality of frames, determining a minimum angle of the plurality of first angles; determining a plurality of fourth line segments, each line segment of the plurality of fourth line segments connecting the vehicle and one of the grounding points; Determine a plurality of second angles between: the plurality of third line segments, and said half line; In each frame of the plurality of frames, determining a maximum angle among the plurality of second angles; as well as The second field of view is generated based on at least one of the following: a second global minimum angle, the second global minimum angle being the minimum value of the second minimum angles, A second global minimum angle point in the second minimum angle point for forming the second global minimum angle, a second global maximum angle, a maximum of the second global maximum angle and the second maximum angle, and A second global maximum angle point in the second maximum angle point is used to form a second global maximum angle in the second maximum angle point.

19. The method according to claim 16, further comprising: determining a normal state of a boundary area of ​​the sensor based on that a difference between the third field of view and the angle information satisfies a threshold angle; and An abnormal state of a boundary area of ​​the sensor is determined based on that a difference between the third field of view and the angle information does not satisfy the threshold angle.

20. The method of claim 17, further comprising: At least one of the following is stored in memory: the first maximum angle, and The first maximum angle point is used to form each of the first maximum angles, wherein the first maximum angle is determined in each frame of the plurality of frames.

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