Apparatus for controlling vehicle and method thereof

Abstract

The invention discloses an apparatus for controlling a vehicle and a method thereof. An apparatus for controlling a vehicle is presented. The apparatus is configured to generate and correct the road boundary based on the object detected by the sensor and map information associated with the global positioning system when it is difficult to determine the road boundary due to occlusion and disappearance of the boundary object.

Description

[0001] Related Applications

[0002] This application claims the benefit of priority from Korean Patent Application No. 0-2023-0124148 filed in the Korean Intellectual Property Office on September 18, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to a vehicle control device and a method thereof, and more particularly, to a technology for using light detection and ranging (LiDAR). Background Art

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

[0005] Specifically, when the host vehicle is driven in a driving assistance device activation mode or an autonomous driving mode, external objects may be recognized by using a sensor (eg, LiDAR).

[0006] It is necessary to identify the road edge through a sensor (e.g., LiDAR) to accurately identify the area where the host vehicle can drive. In particular, if the road edge is blocked by an external object (e.g., an external vehicle), problems may occur (e.g., the road edge disappears). Summary of the invention

[0007] According to the present disclosure, a device includes a sensor, a communication circuit, and a processor, wherein the processor is configured to determine a first reference point within a line segment corresponding to a rear surface of an external vehicle, wherein the line segment is one of line segments forming a first virtual frame corresponding to the external vehicle detected by the sensor, and based on tracking the first reference point in an area divided by a grid associated with a frame of a designated area, remove a point from a plurality of points obtained by the sensor relative to at least one of second reference points located within a second line segment corresponding to a rear surface of a first stationary object, wherein the second line segment is one of a line segment forming a second virtual frame corresponding to the first stationary object or a line segment of a third reference point located within a third line segment corresponding to the rear surface of the second stationary object, wherein the third line segment is a line segment forming a second virtual frame corresponding to the first stationary object, and wherein the third line segment is a line segment forming a third reference point located within a third line segment corresponding to the rear surface of the second stationary object. forming a line segment of a third virtual frame corresponding to the second stationary object, wherein the point is located in an area different from an area where a main vehicle is present, determining an error associated with the position of the main vehicle by comparing a first position of the main vehicle (which is included in map information received through a communication circuit of the main vehicle) with a second position of the main vehicle (which is included in global positioning system (GPS) information), based on determining that the error is less than a reference error, comparing a first width of a road included in the map information and on which the main vehicle is traveling with a second width based on a distance between the first stationary object and the second stationary object, determining at least one of the first stationary object or the second stationary object as a road edge based on the difference between the first width and the second width being less than a first reference width, and outputting a signal indicating a road edge.

[0008] The apparatus, wherein the processor is configured to determine that at least one of the first stationary object and the second stationary object is not a road edge based on a difference between the first width and the second width being greater than the first reference width.

[0009] The device, wherein the processor is configured to generate a histogram based on the coordinates of the second axis of a first reference point tracked on a plane formed by the first axis and the second axis and an area, wherein the area is divided by a grid, the first axis corresponds to the driving direction of the host vehicle, and the second axis is perpendicular to the first axis.

[0010] The device, wherein the processor is configured to generate the histogram based on the first reference point detected in the area divided by the grid and a partial area obtained by dividing the area at specified intervals, and wherein the area divided by the grid includes an area for dividing each lane in which the host vehicle can travel.

[0011] The device, wherein the processor is configured to determine at least one of a first coordinate of a second axis of the first reference point, a second coordinate of the second axis of the second reference point, or a third coordinate of the second axis of the third reference point, wherein the at least one of the first coordinate, the second coordinate, or the third reference point is identified on a plane formed by a first axis and a second axis perpendicular to the first axis, wherein the first axis corresponds to a driving direction of the host vehicle, determine that the first stationary object is located on a left side of the host vehicle based on the first coordinate of the second axis exceeding the second coordinate of the second axis, determine that the first stationary object is located on a right side of the host vehicle based on the first coordinate of the second axis being smaller than the second coordinate of the second axis, determine that the second stationary object is located on the left side of the host vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis, or determine that the second stationary object is located on the right side of the host vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis.

[0012] The device, wherein the processor is configured to determine the first stationary object as a first road edge based on the fact that the length of the second virtual frame is greater than or equal to the first reference length, no virtual frames different from the second virtual frame exist in the area where the second virtual frame is detected, the distance between the second reference point and the host vehicle is less than or equal to the first reference distance, and the second virtual frame includes a second reference number or more of points of the specified type, or determine the second stationary object as a second road edge based on the fact that the length of the third virtual frame is greater than or equal to the first reference length, no virtual frames different from the third virtual frame exist in the area where the third virtual frame is detected, the distance between the third reference point and the host vehicle is less than the first reference distance, and the third virtual frame includes a second reference number or more of points of the specified type.

[0013] The device, wherein the processor is configured to determine the first position and the second position in a grid for dividing a plane formed by a first axis and a second axis, wherein the first axis corresponds to a driving direction of the main vehicle and the second axis is perpendicular to the first axis, determine a first error in the direction of the first axis based on a first coordinate of the first axis included in the first position and a second coordinate of the first axis included in the second position, determine a second error in the direction of the second axis of the main vehicle based on a fourth coordinate of the second axis included in the first position and a fifth coordinate of the second axis included in the second position, and compare the first width and the second width based on the first error being less than a first reference error and the second error being less than a second reference error.

[0014] The device, wherein the processor is configured to determine an area in which the host vehicle can travel from among areas divided by the grid, and determine that at least one of the first stationary object or the second stationary object is not a road edge based on determining a stationary object different from at least one of the first stationary object or the second stationary object in an area adjacent to an area in which at least one of the first stationary object or the second stationary object exists.

[0015] The device, wherein the processor is configured to, based on at least one of the length of the second virtual frame or the length of the third virtual frame being greater than a second reference length, determine at least one of the first stationary object or the second stationary object as a road edge, determine a first point closest to the main vehicle from points included in the second virtual frame, determine a second point closest to the main vehicle from points included in the third virtual frame, and determine at least one of the first stationary object or the second stationary object as a road edge based on the difference between the distance between the first point and the second point and the road width included in the map information being less than a second reference width.

[0016] According to the present disclosure, a method includes determining a first reference point within a line segment corresponding to a rear surface of an external vehicle, wherein the line segment is one of line segments forming a first virtual frame corresponding to the external vehicle detected by a sensor, removing a point from a plurality of points obtained by the sensor relative to at least one of second reference points located within a second line segment corresponding to a rear surface of a first stationary object based on tracking the first reference point in an area divided by a grid associated with a frame of a designated area, wherein the second line segment is a line segment forming a second virtual frame corresponding to the first stationary object, or a line segment of a third reference point located within a third line segment corresponding to the rear surface of a second stationary object, wherein the third line segment is one of the line segments forming a third virtual frame corresponding to the second stationary object, by comparing the first position of the main vehicle (which is included in the map information received through the communication circuit) with the second position of the main vehicle (which is included in the GPS information), determining an error related to the position of the main vehicle, based on determining that the error is less than a reference error, comparing a first width of a road included in the map information and on which the main vehicle is traveling with a second width based on the distance between the first stationary object and the second stationary object, determining at least one of the first stationary object or the second stationary object as a road edge based on the difference between the first width and the second width being less than a first reference width, and outputting a signal indicating a road edge.

[0017] The method further includes determining that at least one of the first stationary object and the second stationary object is not a road edge based on a difference between the first width and the second width being greater than the first reference width.

[0018] The method also includes: generating a histogram based on the coordinates of the second axis of the first reference point tracked on the plane formed by the first axis and the second axis and the area, wherein the area is divided by a grid, the first axis corresponds to the driving direction of the host vehicle, and the second axis is perpendicular to the first axis.

[0019] The method further includes generating the histogram based on the first reference point detected in the area divided by the grid and a partial area obtained by dividing the area at specified intervals, and wherein the area divided by the grid includes an area for dividing each lane in which the host vehicle can travel.

[0020] The method further includes determining at least one of a first coordinate of a second axis of the first reference point, a second coordinate of the second axis of the second reference point, or a third coordinate of the second axis of the third reference point, wherein the at least one of the first coordinate, the second coordinate, or the third reference point is identified on a plane formed by a first axis and a second axis perpendicular to the first axis, wherein the first axis corresponds to a driving direction of the host vehicle, determining that the first stationary object is located on a left side of the host vehicle based on the first coordinate of the second axis exceeding the second coordinate of the second axis, determining that the first stationary object is located on a right side of the host vehicle based on the first coordinate of the second axis being smaller than the second coordinate of the second axis, determining that the second stationary object is located on a left side of the host vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis, or determining that the second stationary object is located on a right side of the host vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis.

[0021] The method also includes: determining the first stationary object as a first road edge based on the fact that the length of the second virtual frame is greater than or equal to the first reference length, there are no virtual frames different from the second virtual frame in the area where the second virtual frame is detected, the distance between the second reference point and the main vehicle is less than or equal to the first reference distance, and the second virtual frame includes a second reference number or more of points of the specified type, or determining the second stationary object as a second road edge based on the fact that the length of the third virtual frame is greater than or equal to the first reference length, there are no virtual frames different from the third virtual frame in the area where the third virtual frame is detected, the distance between the third reference point and the main vehicle is less than the first reference distance, and the third virtual frame includes a second reference number or more of points of the specified type.

[0022] The method also includes: determining the first position and the second position in a grid used to divide a plane formed by a first axis and a second axis, wherein the first axis corresponds to the driving direction of the main vehicle and the second axis is perpendicular to the first axis, determining a first error in the direction of the first axis based on a first coordinate of the first axis included in the first position and a second coordinate of the first axis included in the second position, determining a second error in the direction of the second axis of the main vehicle based on a fourth coordinate of the second axis included in the first position and a fifth coordinate of the second axis included in the second position, and comparing the first width and the second width based on the first error being less than a first reference error and the second error being less than a second reference error.

[0023] The method also includes: determining an area in which the host vehicle can travel from the areas divided by the grid, and determining that at least one of the first stationary object or the second stationary object is not a road edge based on determining a stationary object different from at least one of the first stationary object or the second stationary object in an area adjacent to the area in which at least one of the first stationary object or the second stationary object exists.

[0024] The method also includes: determining at least one of the first stationary object or the second stationary object as a road edge based on at least one of the length of the second virtual frame or the length of the third virtual frame being greater than a second reference length, determining a first point closest to the main vehicle from points included in the second virtual frame, determining a second point closest to the main vehicle from points included in the third virtual frame, and determining at least one of the first stationary object or the second stationary object as a road edge based on the difference between the distance between the first point and the second point and the road width included in the map information being less than a second reference width. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] 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:

[0026] Figure 1 An embodiment of a block diagram of a vehicle control device according to an embodiment of the present disclosure is shown;

[0027] Figure 2 An embodiment of recognizing an external object and a road edge by a vehicle control device according to an embodiment of the present disclosure is shown;

[0028] Figure 3 An embodiment in which a vehicle control device according to an embodiment of the present disclosure generates a histogram by tracking an external vehicle is shown;

[0029] Figure 4An embodiment of outputting a road edge through a vehicle control device according to an embodiment of the present disclosure is shown;

[0030] Figure 5 An embodiment of a vehicle control device identifying a road edge according to an embodiment of the present disclosure is shown;

[0031] Figure 6 An embodiment of a flow chart of a vehicle control method according to an embodiment of the present disclosure is shown;

[0032] Figure 7 An embodiment of a flow chart showing a vehicle control method according to an embodiment of the present disclosure; and

[0033] Figure 8 An embodiment of a computing system associated with a vehicle control device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0034] 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.

[0035] 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 this 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.

[0036] In the following, reference will be made to Figures 1 to 8 Various embodiments of the present disclosure are described in detail.

[0037] Figure 1 An embodiment of a block diagram of a vehicle control device according to an embodiment of the present disclosure is shown.

[0038] See also Figure 1The vehicle control device 100 according to an embodiment of the present disclosure may be implemented inside or outside a vehicle (e.g., a host 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 an 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.

[0039] See also Figure 1 The vehicle control device 100 according to the embodiment may include a processor 110, a sensor (eg, LiDAR 120), and a communication circuit 130. The processor 110, the LiDAR 120, or the communication circuit 130 may be electrically or operably coupled to each other through electronic components including a communication bus.

[0040] Hereinafter, the fact that hardware is operably coupled may include the fact that a direct and / or indirect connection between hardware is established by wire and / or wirelessly so that the second hardware is controlled by the first hardware in the hardware. Although different blocks are shown, the embodiment is not limited thereto.

[0041] Figure 1 Some of the hardware in the vehicle control device 100 may be included in a single integrated circuit including a system on a chip (SoC). The type and / 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 only include Figure 1 Some of the hardware is shown in FIG.

[0042] 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.

[0043] The vehicle control apparatus 100 according to an embodiment may include the LiDAR 120. For example, the LiDAR 120 may obtain a data set from identifying objects around the vehicle control apparatus 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, or the speed of the surrounding object, or any combination thereof based on a pulse laser signal emitted from the LiDAR 120 that is reflected by the surrounding object and returns.

[0044] For example, LiDAR 120 can obtain a data set including multiple points in a space defined by a first axis (e.g., x-axis), a second axis (e.g., y-axis), and a third axis (e.g., z-axis) based on a pulsed laser signal reflected from surrounding objects. For example, LiDAR 120 can obtain a data set including multiple points in a space formed by the first axis, the second axis, and the third axis based on receiving a pulsed laser signal during a specified time period.

[0045] Hereinafter, the first axis may include the x-axis; the second axis may include the y-axis; and the third axis may include the z-axis. However, the first axis, the second axis, and the third axis, respectively referred to as the "x-axis", the "y-axis", and the "z-axis", are not limited to the above description.

[0046] The processor 110 included in the vehicle control device 100 according to the embodiment may emit light from the host vehicle by using the LiDAR 120. For example, the processor 110 may receive the light emitted from the host vehicle. For example, the processor 110 may recognize at least one of the position, speed, or moving direction of the surrounding object or any combination thereof based on the time required to transmit the light emitted from the host vehicle and the time required to receive the light emitted from the host vehicle.

[0047] For example, the processor 110 may obtain a data set including a plurality of points based on the time required to transmit the light emitted from the host vehicle and the time required to receive the light emitted from the host vehicle. The processor 110 may obtain a data set for expressing a plurality of points in a three-dimensional virtual coordinate system including a first axis, a second axis, and a third axis.

[0048] The communication circuit 130 included in the vehicle control device 100 according to the embodiment may include hardware components for supporting transmission and / or reception of signals between the vehicle control device 100 and an external electronic device (or an external vehicle). For example, the communication circuit 130 may include at least one of a MODEM, an antenna, or an optical / electronic (O / E) converter, or any combination thereof.

[0049] For example, the communication circuit 130 can support the sending and / or receiving of signals based on various types of protocols, including Ethernet, local area network (LAN), wide area network (WAN), wireless fidelity (WiFi), Bluetooth, Bluetooth low energy (BLE), ZigBee, long term evolution (LTE), 5G new radio (NR), controller area network (CAN), or local interconnect network (LIN), or at least one of any combination thereof.

[0050] The processor 110 included in the vehicle control apparatus 100 according to the embodiment may obtain a first virtual frame corresponding to the external vehicle recognized by the LiDAR 120. The processor 110 may identify a first reference point within a line segment corresponding to the rear surface of the external vehicle among line segments forming the first virtual frame based on obtaining the first virtual frame corresponding to the external vehicle recognized by the LiDAR 120.

[0051] The number of first virtual frames is not limited to one. For example, the processor 110 included in the vehicle control device 100 may identify a virtual frame corresponding to an external vehicle. The processor 110 may identify reference points respectively included in the virtual frames corresponding to the external vehicles. Hereinafter, for ease of description, a description related to the first virtual frame corresponding to the external vehicle will be given later.

[0052] In an embodiment, the processor 110 may track the first reference point during frames of a specified region in the area divided by the grid. For example, the processor 110 may track the first reference point in the area divided by the grid during a specified number of frames (eg, approximately 10 frames).

[0053] For example, the processor 110 may identify a partial region obtained by dividing the divided region at designated intervals by the grid.

[0054] For example, an area divided by a grid may be referred to as a “lane grid.” For example, a partial area may be referred to as a “roadbim (RB) grid.”

[0055] In an embodiment, the processor 110 may identify a first reference point in an area indicating a road and a partial area obtained by dividing the area indicating a road at specified intervals. The processor 110 may track a first reference point in an area indicating a road and a partial area obtained by dividing the area for representing a road at specified intervals.

[0056] The processor 110 may generate a histogram based on the region indicating the road and the first reference point in the partial region obtained by dividing the region indicating the road at designated intervals.

[0057] In an embodiment, the processor 110 may track the first reference point on a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis. The processor 110 may identify the coordinates of the first reference point tracked on the plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis.

[0058] The processor 110 may generate a histogram based on tracking the first reference point during a frame of a designated area in an area divided by a grid. For example, the first reference point may be referred to as a "tracking point for tracking an external vehicle."

[0059] For example, the processor 110 may identify the second reference point from within the line segment corresponding to the rear surface of the first stationary object among the line segments forming the second virtual frame corresponding to the first stationary object. The processor 110 may identify the third reference point from within the line segment corresponding to the rear surface of the second stationary object among the line segments forming the third virtual frame corresponding to the second stationary object. For example, the second reference point may be referred to as a “tracking point for tracking the first stationary object”. For example, the third reference point may be referred to as a “tracking point for tracking the second stationary object”.

[0060] For example, the rear surface of the first stationary object and / or the rear surface of the second stationary object may include a direction opposite to the driving direction of the host vehicle. For example, in the case where the direction in which the host vehicle is traveling is the positive direction of the first axis among the first axis, the second axis, and the third axis, the rear surface of the first stationary object and / or the rear surface of the second stationary object may include a surface (or line segment) corresponding to a point identified by the minimum coordinate among the coordinates of the direction of the first axis.

[0061] In an embodiment, the processor 110 may be located based on the second reference point within the line segment corresponding to the rear surface of the first stationary object in the line segment forming the second virtual frame corresponding to the first stationary object, and / or the third reference point within the line segment corresponding to the rear surface of the second stationary object in the line segment forming the third virtual frame corresponding to the second stationary object, to identify at least one of an area in which the main vehicle can travel, or an area different from the area in which the main vehicle can travel, or any combination thereof.

[0062] For example, the processor 110 may identify the area between the second reference point and the third reference point as an area in which the host vehicle can travel. For example, the processor 110 may identify an area different from the area between the second reference point and the third reference point as an area different from the area in which the host vehicle can travel. For example, the area different from the area in which the host vehicle can travel may include an area outside the edge of the road.

[0063] In an embodiment, based on tracking a first reference point in an area divided by a grid during a frame of a designated area, the processor 110 may remove points in an area different from an area in which the main vehicle can travel, from among the points obtained by the LiDAR 120, relative to at least one of a second reference point located within a line segment corresponding to a rear surface of the first stationary object in a line segment forming a second virtual frame corresponding to the first stationary object, or a third reference point located within a line segment corresponding to the rear surface of the second stationary object in a line segment forming a third virtual frame corresponding to the second stationary object, or any combination thereof.

[0064] For example, the processor 110 may initialize the histogram by using points placed in an area different from an area in which the host vehicle is able to travel.

[0065] In an embodiment, the processor 110 may receive map information including the first position of the host vehicle through the communication circuit 130. For example, the map information may include precise map information. For example, the processor 110 may receive precise map information including the first position of the host vehicle through the communication circuit 130.

[0066] For example, the precise map information may include at least one of first information for determining whether the main vehicle has entered a precise map area, second information related to the longitudinal positioning accuracy of the main vehicle, third information related to the lateral positioning accuracy of the main vehicle, or fourth information related to the position of the main vehicle and the number of lanes on which the main vehicle is traveling, or any combination thereof.

[0067] For example, the longitudinal positioning accuracy of the host vehicle may include the position accuracy in the first axis direction on the plane formed by the first axis and the second axis. For example, the lateral positioning accuracy of the host vehicle may include the position accuracy in the second axis direction on the plane formed by the first axis and the second axis. For example, the fourth information related to the position of the host vehicle and the number of the lane in which the host vehicle is traveling may include information related to the position of the host vehicle and the lane in which the host vehicle is traveling based on the rear axle of the host vehicle.

[0068] For example, the processor 110 may identify at least one of the longitudinal positioning accuracy of the host vehicle, or the lateral positioning accuracy of the host vehicle, or any combination thereof based on the precise map information. For example, at least one of the longitudinal positioning accuracy of the host vehicle, the lateral positioning accuracy of the host vehicle, or any combination thereof may be related to an error between a position of the host vehicle included in the global positioning system (GPS) information and a position of the host vehicle included in the precise map information.

[0069] In an embodiment, the processor 110 may obtain GPS information. For example, the processor 110 may receive GPS information from an external electronic device (eg, a server) through the communication circuit 130 or may obtain GPS information from a vehicle control system (or computing system) associated with the vehicle control device 100 .

[0070] In an embodiment, processor 110 may compare the first location of the host vehicle with the second location of the host vehicle included in the GPS information based on receiving accurate map information including the first location of the host vehicle through communication circuit 130. Processor 110 may identify an error associated with the location of the host vehicle based on the second location.

[0071] For example, in a two-dimensional virtual coordinate system composed of a first axis and a second axis, the processor 110 may identify an error associated with the position of the host vehicle based on the second position included in the GPS information.

[0072] In an embodiment, the processor 110 may determine whether the magnitude / value of the error associated with the position of the host vehicle is less than the reference error based on the second position. Based on the fact that the error associated with the position of the host vehicle is identified as being less than the reference error based on the second position, the processor 110 may compare a first width of a road on which the host vehicle is traveling contained in the accuracy map with a second width based on the distance between the first stationary object and the second stationary object. For example, the distance between the first stationary object and the second stationary object may include a distance between the second virtual frame and the third virtual frame.

[0073] In an embodiment, the processor 110 may identify a difference between the first width and the second width. The processor 110 may identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge based on the difference between the first width and the second width being less than the first reference width. The processor 110 may output the identified road edge based on identifying at least one of the first stationary object or the second stationary object, or any combination thereof, as a road edge.

[0074] For example, the processor 110 may assign an identifier representing a road edge (e.g., RoadEdge) to the first stationary object or the second stationary object identified as a road edge based on at least one of the first stationary object or the second stationary object, or any combination thereof, being a road edge.

[0075] In one embodiment, the processor 110 may not identify at least one of the first stationary object, the second stationary object, and a combination thereof as a road edge based on a difference between the first width and the second width exceeding a first reference width.

[0076] In an embodiment, the processor 110 may identify at least one of the position of a first reference point, the position of a second reference point, or the position of a third reference point, or any combination thereof, identified on a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis.

[0077] The processor 110 may also identify the direction in which the first stationary object, the second stationary object, or at least one of any combinations thereof are located relative to the main vehicle based on at least one of the position of a first reference point, the position of a second reference point, or the position of a third reference point, or any combination thereof, identified on a plane formed by the first axis, the second axis, and the third axis.

[0078] For example, processor 110 may identify at least one of a first coordinate of a second axis of a first reference point, a second coordinate of a second axis of a second reference point, or a third coordinate of a second axis of a third reference point, or any combination thereof.

[0079] The processor 110 may compare at least one of the first coordinate of the second axis, the second coordinate of the second axis, or the third coordinate of the second axis, or any combination thereof.

[0080] For example, the processor 110 may compare the first coordinate of the second axis with the second coordinate of the second axis. The processor 110 may further identify that the first stationary object is located on the left side of the host vehicle based on the first coordinate of the second axis being greater than the second coordinate of the second axis.

[0081] For example, the processor 110 may further identify that the first stationary object is located on the right side of the host vehicle based on the first coordinate of the second axis being smaller than the second coordinate of the second axis.

[0082] For example, the processor 110 may compare the first coordinate of the second axis with the second coordinate of the second axis. The processor 110 may further identify that the second stationary object is located on the left side of the host vehicle based on the first coordinate of the second axis being greater than the third coordinate of the second axis.

[0083] For example, the processor 110 may further identify that the second stationary object is located on the right side of the host vehicle based on the first coordinate of the second axis being smaller than the third coordinate of the second axis.

[0084] In an embodiment, the processor 110 may identify the first location included in the precise map information and the second location included in the GPS information in a grid for dividing a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis.

[0085] The processor 110 may identify a first coordinate of a first axis included in the first position. The processor 110 may identify a second coordinate of the first axis included in the second position. The processor 110 may identify a first error in a first axis direction of the host vehicle based on the first coordinate of the first axis and the second coordinate of the first axis.

[0086] The processor 110 may identify a fourth coordinate of the second axis included in the first position. The processor 110 may identify a fifth coordinate of the second axis included in the second position. The processor 110 may identify a second error in the second axis direction of the host vehicle based on the fourth coordinate of the second axis and the fifth coordinate of the second axis.

[0087] In an embodiment, the processor 110 may determine whether the first error is smaller than a first reference error (eg, approximately 5 m). The processor 110 may determine whether the second error is smaller than a second reference error (eg, approximately 2 m).

[0088] The processor 110 may compare the first width with the second width based on the first error being less than the first reference error and the second error being less than the second reference error. The processor 110 may identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge based on the difference between the first width and the second width being less than the first reference width.

[0089] In an embodiment, the processor 110 may identify an area in which the host vehicle can travel from the areas divided by the grid. In an embodiment, the processor 110 may identify an area adjacent to the area in which the host vehicle can travel from the areas divided by the grid.

[0090] The processor 110 may identify at least one of a first stationary object, a second stationary object, and a combination thereof in an area adjacent to an area where the host vehicle can travel. The processor 110 may identify at least one of the first stationary object, the second stationary object, and a combination thereof as a road edge based on identifying at least one of the first stationary object, the second stationary object, and a combination thereof in an area adjacent to an area where the host vehicle can travel.

[0091] In one embodiment, the processor 110 does not identify the first stationary object or the second stationary object, or at least one of the any combination thereof, as a road edge based on identifying a stationary object different from the first stationary object, the second stationary object, or at least one of the any combination thereof in an area adjacent to an area where at least one of the first stationary object, the second stationary object, or a combination thereof exists.

[0092] In an embodiment, the processor 110 may identify a length of a second virtual frame corresponding to the first stationary object. The processor 110 may identify a length of a third virtual frame corresponding to the second stationary object.

[0093] In an embodiment, the processor 110 may identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge based on at least one of the length of the second virtual frame, the length of the third virtual frame, or any combination thereof being greater than the second reference length.

[0094] In an embodiment, the processor 110 may identify a first point closest to the host vehicle from among the points included in the second virtual frame. The processor 110 may identify a second point closest to the host vehicle from among the points included in the third virtual frame.

[0095] In an embodiment, the processor 110 may identify a distance between the first point and the second point. The processor 110 may identify a difference between road widths included in the accurate map information. The processor 110 may determine whether the difference between the road width included in the accurate map information and the distance between the first point and the second point is less than or equal to a second reference width (e.g., approximately 3.5 m).

[0096] The processor 110 may identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge based on the fact that the difference between the distance between the first point and the second point and the road width included in the precise map information is less than or equal to the second reference width. For example, at least one of the first point or the second point or any combination thereof may include a vertex, which is included in at least one of the second virtual frame or the third virtual frame or any combination thereof.

[0097] As described above, the processor 110 of the vehicle control device 100 according to the embodiment can identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge based on the first reference point. Even if occlusion or loss of a boundary object occurs, the processor 110 can identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge based on the first reference point, thereby identifying the road edge with high accuracy.

[0098] Figure 2 An embodiment of identifying external objects and road edges (e.g., grass strips, concrete or curbs, emergency or bicycle lanes, gutters, reflective markers or contours, guardrails, trees, bushes, or painted lines, etc.) by a vehicle control device according to an embodiment of the present disclosure is shown.

[0099] See also Figure 2 , a processor included in the vehicle control apparatus according to the embodiment may recognize the surroundings of the host vehicle including the first embodiment 201. For example, the processor may recognize the surroundings of the host vehicle based on at least one of a camera or a sensor (e.g., LiDAR) or any combination thereof. While recognizing the surroundings of the host vehicle, the processor may recognize an external object 210 located outside the edge of the road. The external object 210 needs to be recognized as a stationary object outside the edge of the road.

[0100] The second embodiment 203 may include an embodiment of generating a frame based on points obtained by LiDAR included in the vehicle control apparatus according to the embodiment.

[0101] For example, in the second embodiment 203, the virtual frame 220 may correspond to the external object 210 in the first embodiment 201. The processor needs to identify the virtual frame 220 as a stationary object on the outside of the road edge. However, if the stationary object is close to the road edge (e.g., within a threshold distance), the virtual frame 220 may also be identified as an object on the inside of the road edge. In addition, the virtual frame 220 may be identified as a moving body that enters from the outside of the road edge to the inside of the road edge, rather than a stationary object on the outside of the road edge. For example, the outside of the road edge may be referred to as an "area where the host vehicle cannot travel" (e.g., a drainage ditch, an unpaved road such as a gravel or muddy road, a raised road marking, trees, bushes, guardrails, etc.). For example, the inside of the road edge may be referred to as an "area where the host vehicle can travel."

[0102] If it is recognized that the virtual frame 220 enters the inner side of the road edge from the outer side of the road edge, an error of the vehicle control system associated with the vehicle control device may occur. For example, because the virtual frame 220 enters the inner side of the road edge from the outer side of the road edge, the vehicle control system associated with the vehicle control device may perform an operation of adjusting the speed of the host vehicle or changing the driving route of the host vehicle. Because the driving of the host vehicle is unstable, the vehicle control system associated with the vehicle control device performs an operation of adjusting the speed of the host vehicle or changing the driving route of the host vehicle. Therefore, there is a need for a solution to the unstable driving of the host vehicle.

[0103] Figure 3 An embodiment is shown in which the vehicle control apparatus according to an embodiment of the present disclosure generates a histogram by tracking an external vehicle.

[0104] See also Figure 3 , a processor included in the vehicle control apparatus according to the embodiment may identify a first virtual frame 310 corresponding to an external vehicle. The processor may identify a first reference point 311 of the first virtual frame 310 corresponding to the external vehicle. For example, the processor may identify a first reference point 311 within a line segment corresponding to a rear surface of the external vehicle among line segments forming the first virtual frame 310.

[0105] The processor may track the first reference point 311. For example, the processor may track the first reference point 311 during a frame of the designated area. For example, the frame of the designated area may include about 10 frames.

[0106] In an embodiment, the processor may generate a histogram 315 based on the points 313 tracked during the frame of the specified zone.

[0107] For example, the processor may generate the histogram 315 based on the grid 301 for dividing the lane and the partial grid 303 obtained by dividing the grid 301 at specified intervals.

[0108] In an embodiment, the processor may identify a virtual box 320 corresponding to a road edge (e.g., a grass strip, concrete or curb, an emergency or bicycle lane, a gutter, a reflective marker or contour, a guardrail, a tree, a bush, or a painted line, etc.) based on generating the histogram 315. For example, a designated identifier may be assigned to the virtual box 320 corresponding to the road edge. For example, the designated identifier may include an identifier indicating that the virtual box 320 is a road edge.

[0109] In an embodiment, the processor may remove points located outside the area of ​​the virtual frame 320 identified or detected as corresponding to the road edge. For example, outside the area where the virtual frame 320 is identified or detected may include an area where the first reference point 311 of the virtual frame 310 corresponding to the external vehicle is not identified or detected.

[0110] In one embodiment, the processor may identify the virtual frame 320 as a stationary object (e.g., concrete or curb, guardrail, tree, bush, road sign post, etc.) based on the generated histogram 315, and then may determine that the identified stationary object is a road edge. The operation of determining the virtual frame 320 as a road edge is described later.

[0111] Figure 4 An example of outputting a road edge through a vehicle control device according to an embodiment of the present disclosure is shown.

[0112] See also Figure 4 , a processor included in the vehicle control apparatus according to the embodiment may identify road edges 413 and 415 .

[0113] For example, when it is not possible to Figure 3 When the histogram 315 obtained in the process identifies a road edge, the processor may generate a road edge candidate based on a virtual box corresponding to the external object.

[0114] In an embodiment, when the host vehicle 411 is traveling, the processor may identify a virtual frame corresponding to an external object. When the host vehicle 411 is traveling, the processor may identify a road edge based on the external object.

[0115] For example, the processor may identify a plurality of virtual frames in the first area 413 .

[0116] In an embodiment, the processor may identify the lengths occupied by the plurality of virtual frames based on identifying the plurality of virtual frames. For example, the lengths occupied by the plurality of virtual frames may be identified based on the direction of the first axis among the first axis, the second axis, and the third axis. For example, the first axis may be referred to as the x-axis; the second axis may be referred to as the y-axis; and the third axis may be referred to as the z-axis. However, the embodiment is not limited thereto.

[0117] For example, the length occupied by the multiple virtual frames may include the length from the minimum coordinate of the first axis to the maximum coordinate of the first axis.

[0118] For example, the processor may identify the road edge corresponding to the plurality of virtual frames based on the length occupied by the plurality of virtual frames being greater than or equal to a reference length (e.g., approximately 10m to 20m) and the number of points of a specified type among the points included in the plurality of virtual frames being greater than or equal to a reference number (e.g., approximately 10 to 20). For example, the specified type of point may be referred to as a “free space point”. For example, the free space point may be identified based on receiving light emitted from a LiDAR at specified intervals.

[0119] In an embodiment, the processor may identify a virtual box in the second area 415. For example, the processor may identify a single virtual box as a road edge by using a histogram based on identifying the single virtual box. For example, a histogram may be generated based on tracking points of moving objects including external vehicles.

[0120] As described above, the processor of the vehicle control device according to the embodiment can identify the virtual frame as the road edge by using the histogram. The processor can reduce errors in the vehicle control system related to the vehicle control device by identifying the virtual frame as the road edge by using the histogram.

[0121] Figure 5 An embodiment in which a vehicle control device recognizes a road edge according to an embodiment of the present disclosure is shown.

[0122] See also Figure 5 , the processor included in the vehicle control device according to the embodiment can identify the area divided by the plurality of grids. For example, the processor can identify the grid 511 corresponding to the lane in which the host vehicle is traveling based on the area divided by the plurality of grids.

[0123] For example, the processor may identify an area 513 (e.g., an asphalt road) in which the host vehicle can travel based on a reference point for tracking an external vehicle. The processor may identify virtual frames 515 and 519 in an area different from the area 513 in which the host vehicle can travel. For example, the virtual frames 515 and 519 may include virtual frames 515 and 519 output as road edges, respectively.

[0124] For example, the processor may perform verification to determine whether the virtual frames 515 and 519 correspond to road edges, respectively. For example, the processor may identify that the regions in which the virtual frames 515 and 519 are identified are road edges 523 and 525 among the regions divided by the plurality of grids.

[0125] The processor may verify the road edges 523 and 525. For example, the processor may determine whether there are stationary objects (eg, post office boxes, road signs, etc.) in areas adjacent to the areas identified as the road edges 523, 525.

[0126] For example, the processor may determine whether there is a stationary object in a plurality of grids located in an adjacent area of ​​grids (e.g., grid 5 and grid 11) identified as road edges 523 and 525. For example, the processor may determine whether there is a stationary object in area 513 between road edges 523 and 525 where the host vehicle can travel.

[0127] For example, in Figure 5 In the example, the processor may determine whether a stationary object is placed in a grid 6 adjacent to a grid 5 determined as a road edge. For example, the processor may determine whether a stationary object exists in a grid 10 adjacent to a grid 11 determined as a road edge. For example, each of the above-mentioned grids 6 and 11 may be referred to as a grid adjacent to a grid identified as a road edge within an area in which the host vehicle can travel.

[0128] In an embodiment, the processor may identify the size of each of the virtual frames 515 and 519. For example, the processor may identify at least one of the width, or length, or any combination of each of the virtual frames 515 and 519. The processor may determine whether to output the virtual frames 515 and 519 as road edges based on identifying at least one of the width, or length, or any combination of each of the virtual frames 515 and 519.

[0129] For example, the processor can identify virtual frames 515 and 519 as road edges based on the length of each of the virtual frames 515 and 519 exceeding a reference length (e.g., about 10-20 m), and can then output the identified road edges. For example, the length of each virtual frame 515 and 519 can include the length in the first axis direction.

[0130] In an embodiment, the processor may include reference points respectively included in the virtual frames 515 and 519. For example, the processor may identify vertices 517 and 521 closest to the host vehicle from among the vertices forming the virtual frames 515 and 519. The processor may identify each of the virtual frames 515 and 519 as a road edge based on the fact that the length of each of the vertices 517 and 521 tracked during the frame of the designated area is less than a reference length (e.g., about 10-20 m), and may then output the identified road edge.

[0131] Figure 6 An embodiment of a flowchart of a vehicle control method according to an embodiment of the present disclosure is shown.

[0132] 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.

[0133] Figure 6 At least one of the operations may be Figure 1 The vehicle control device 100 executes. 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.

[0134] refer to Figure 6 In operation S601, the vehicle control method according to the embodiment may include an operation of generating a histogram based on identifying a moving object. For example, the vehicle control method may include an operation of generating a histogram based on identifying a moving object corresponding to an external vehicle.

[0135] For example, the vehicle control method may include an operation of identifying a reference point of a virtual frame corresponding to a moving object. The vehicle control method may include an operation of tracking the reference point during a frame of a designated area based on identifying the reference point of the virtual frame corresponding to the moving object. The vehicle control method may include an operation of generating a histogram based on tracking the reference point during a frame of a designated area.

[0136] In operation S603, the vehicle control method according to the embodiment may include an operation of identifying a stationary object. The vehicle control method may include the following operation: initializing a portion of the histogram based on determining the stationary object. For example, the vehicle control method may include an operation of initializing the histogram in an area different from the area where the reference point is identified. For example, the vehicle control method may include the following operation: initializing the histogram of the area where the stationary object is identified and the area different from the area where the reference point included in the mobile object is identified.

[0137] For example, the operation of initializing the histogram may include an operation of removing values ​​of the histogram.

[0138] In operation S605, the vehicle control method according to the embodiment may include an operation of determining whether to generate a histogram based on a specified number of frames. For example, the specified number of frames may include approximately 10 frames.

[0139] If the histogram is not generated based on the designated number of frames (No in operation S605 ), the vehicle control method according to the embodiment may include an operation of generating a histogram by additionally or alternatively recognizing or detecting a moving object.

[0140] If the histogram is generated based on the designated number of frames (Yes in operation S605 ), the vehicle control method according to the embodiment may include an operation of generating roadside road edge candidates in operation S607 .

[0141] For example, the vehicle control method may include an operation of selecting the recognized stationary object as a candidate included in the road edge candidates.

[0142] In operation S609, the vehicle control method according to the embodiment may include an operation of receiving accurate map information. For example, the vehicle control method may include an operation of receiving accurate map information through a communication circuit. For example, the accurate map information may include at least one of the following: first information related to whether the host vehicle has entered the road section using accurate map information, second information related to the longitudinal positioning accuracy of the host vehicle, third information related to the lateral positioning accuracy of the host vehicle, or fourth information related to the lane in which the host vehicle is traveling, or any combination thereof.

[0143] In operation S611 , the vehicle control method according to the embodiment may include an operation of identifying whether precise map information is valid.

[0144] If the precise map information is invalid (No in operation S611), the vehicle control method according to the embodiment may include an operation of receiving the precise map information again.

[0145] If the precise map information is valid (yes in operation S611), then in operation S613, the vehicle control method according to the embodiment may include an operation of identifying a road width based on the precise map information. For example, the vehicle control method may include an operation of identifying a road width based on road information included in the precise map information. For example, the vehicle control method may include an operation of identifying a road width corresponding to a width between road edges.

[0146] In operation S615 , the vehicle control method according to an embodiment may include an operation of determining whether a difference between a first road width based on the road edge candidate and a second road width included in the precise map information is less than or equal to a reference width (eg, approximately 3.5 m).

[0147] The vehicle control method according to the embodiment may include an operation of identifying a first road width based on a distance between a first candidate located on a left side of the host vehicle and a second candidate located on a right side of the host vehicle among candidates included in the road edge candidates.

[0148] The vehicle control method according to the embodiment may include an operation of identifying whether a difference between a first road width based on the road edge candidate and a second road width included in the precise map information is less than or equal to a reference width.

[0149] For example, the reference width may include a width corresponding to one lane.

[0150] If the difference between the first road width based on the road edge candidate and the second road width included in the accurate map information is less than or equal to the reference width (yes in operation S615), the vehicle control method according to the embodiment may include an operation of outputting the road edge candidate in operation S617. For example, the vehicle control method may include an operation of outputting a candidate included in the road edge candidate.

[0151] Figure 7 An embodiment of a flow chart of a vehicle control method according to an embodiment of the present disclosure is shown.

[0152] 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.

[0153] Figure 7 At least one of the operations may be performed by Figure 1 The vehicle control device 100 executes. 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.

[0154] See also Figure 7 In operation S701, the vehicle control method may include an operation of identifying a first reference point within a line segment corresponding to a rear surface of the external vehicle among line segments forming the first virtual frame based on obtaining a first virtual frame corresponding to the external vehicle identified by LiDAR.

[0155] According to an embodiment, the vehicle control method may include: based on the coordinates of the second axis of the first reference point tracked on the plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis, an operation of generating a histogram based on the area divided by the grid. For example, the first axis may include an x-axis. For example, the second axis may include a y-axis. For example, the third axis may include a z-axis. However, the first axis, the second axis, and the third axis are not limited to the above embodiments.

[0156] According to an embodiment, the vehicle control method may include an operation of generating a histogram based on a first reference point identified in an area divided by a grid and a partial area obtained by dividing the area at specified intervals. The area divided by the grid may include an area for dividing lanes on each of which the host vehicle can travel.

[0157] In operation S703, the vehicle control method according to the embodiment may include: based on tracking a first reference point in the area divided by a grid during a frame of a designated area, relative to a second reference point in a second virtual frame in a line segment forming the first stationary object corresponding to the rear surface of the first stationary object, or a third reference point in a third virtual frame in a line segment forming the second stationary object corresponding to the rear surface of the second stationary object, or at least one of any combination thereof, an operation of removing points located in an area different from an area in which the main vehicle can travel from the points obtained by LiDAR.

[0158] In operation S705, the vehicle control method according to the embodiment may include an operation of receiving accurate map information including a first position of the main vehicle through a communication circuit, comparing the first position of the main vehicle with a second position of the main vehicle included in the GPS information, and identifying an error related to the position of the main vehicle based on the second position.

[0159] In operation S707, the vehicle control method according to the embodiment may have the following operation: based on identifying that the error is less than the reference error, a first width of the road on which the main vehicle is traveling contained in the precise map information and a second width based on the distance between the first stationary object and the second stationary object are compared.

[0160] The vehicle control method according to the embodiment may include an operation of identifying at least one of a first coordinate of a second axis of a first reference point identified on a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis, a second coordinate of a second axis of a second reference point, or a third coordinate of a second axis of a third reference point, or any combination thereof. The vehicle control method according to the embodiment may include the following operations: based on the first coordinate of the second axis exceeding the second coordinate of the second axis, further identifying that the first stationary object is located on the left side of the main vehicle, based on the first coordinate of the second axis being smaller than the second coordinate of the second axis, further identifying that the first stationary object is located on the right side of the main vehicle, based on the first coordinate of the second axis exceeding the third coordinate of the second axis, further identifying that the second stationary object is located on the left side of the main vehicle, or based on the first coordinate of the second axis being smaller than the third coordinate of the second axis, further identifying that the second stationary object is located on the right side of the main vehicle.

[0161] According to an embodiment, a vehicle control method may include the following operations: identifying a first position and a second position in a grid used to divide a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis, identifying a first error in the direction of the first axis of the main vehicle based on a first coordinate of the first axis included in the first position and a second coordinate of the first axis included in the second position, identifying a second error in the direction of the second axis of the main vehicle based on a fourth coordinate of the second axis included in the first position and a fifth coordinate of the second axis included in the second position, and comparing a first width with a second width based on the first error being less than a first reference error and the second error being less than a second reference error.

[0162] In operation S709 , the vehicle control method according to the embodiment may include the following operation: based on the difference between the first width and the second width being less than the first reference width, identifying at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge.

[0163] According to an embodiment, the vehicle control method may include the following operation: based on the difference between the first width and the second width being greater than the first reference width, not recognizing at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge.

[0164] According to an embodiment, the vehicle control method may include the following operations: based on identifying a stationary object different from the first stationary object or the second stationary object or at least one of the combinations thereof in an area adjacent to an area where at least one of the first stationary object, the second stationary object, or any combination thereof exists, identifying an area in which the main vehicle can travel from the area divided by a grid, and not identifying at least one of the first stationary object or the second stationary object, or any combination thereof, as a road edge.

[0165] According to an embodiment, the vehicle control method may include the following operations: based on the fact that the length of the second virtual frame is greater than or equal to the first reference length, there are no virtual frames different from the second virtual frame in the area where the second virtual frame is identified, the distance between the second reference point and the main vehicle is less than or equal to the first reference distance, and the second virtual frame contains more than the second reference number of points of the specified type, identifying the first stationary object as the first road edge, or based on the fact that the length of the third virtual frame is greater than or equal to the first reference length, there are no virtual frames different from the third virtual frame in the area where the third virtual frame is identified, the distance between the third reference point and the main vehicle is less than the first reference distance, and the third virtual frame includes the second reference number or more of points of the specified type, identifying the second stationary object as the second road edge.

[0166] According to an embodiment, the vehicle control method may include the following operations: based on at least any one of the length of the second virtual frame, the length of the third virtual frame, or any combination thereof being greater than a second reference length, identifying at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge.

[0167] According to an embodiment, the vehicle control method may include the following operations: based on the fact that the difference between the distance between the first point and the second point and the road width contained in the precise map information is less than or equal to the second reference width, identifying the first point closest to the main vehicle from the points included in the second virtual frame, identifying the second point closest to the main vehicle from the points included in the third virtual frame, and identifying at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge.

[0168] Figure 8 An embodiment of a computing system associated with a vehicle control device according to an embodiment of the present disclosure is shown.

[0169] See also Figure 8 , 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 .

[0170] 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).

[0171] 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, or 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).

[0172] The storage medium may be coupled to the processor 1100. The processor 1100 may read information from the storage medium and may write information to the storage medium. Alternatively or additionally, the storage medium may be integrated with the processor 1100. The processor and the storage medium may be implemented using an application specific integrated circuit (ASIC). The ASIC may be provided in a user terminal. Alternatively or additionally, the processor and the storage medium may be implemented using separate components in a user terminal.

[0173] 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.

[0174] One embodiment of the present disclosure provides a vehicle control apparatus and method thereof for recognizing a road edge by using a histogram generated based on tracking a moving object.

[0175] One embodiment of the present disclosure provides a vehicle control apparatus and method thereof for identifying an area in which a host vehicle can travel by using width information included in map information and distance information between virtual frames.

[0176] One embodiment of the present disclosure provides a vehicle control device and method thereof for reducing the occurrence of errors in a vehicle control system associated with the vehicle control device by accurately identifying a road edge.

[0177] 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 following description.

[0178] According to an embodiment of the present disclosure, a vehicle control device may include a laser radar (LiDAR) and a processor. The processor may identify a first reference point within a line segment corresponding to a rear surface of the external vehicle among line segments forming the first virtual frame based on obtaining a first virtual frame corresponding to an external vehicle identified by the LiDAR, and may remove a first reference point within a line segment corresponding to a rear surface of the external vehicle from points obtained by the LiDAR based on tracking the first reference point in an area divided by a grid during a frame of a designated area, relative to a second reference point within a line segment corresponding to the rear surface of the first stationary object among line segments forming a second virtual frame corresponding to the first stationary object, or a third reference point within a line segment corresponding to the rear surface of the second stationary object among line segments forming a third virtual frame corresponding to the second stationary object, or any combination thereof. Points in different areas where the main vehicle can be driven can be based on receiving accurate map information including a first position of the main vehicle through a communication circuit, by comparing the first position of the main vehicle with a second position of the main vehicle included in global positioning system (GPS) information, identifying an error related to the position of the main vehicle based on the second position, and based on identifying that the error is less than a reference error, comparing a first width and a second width of a road on which the main vehicle is traveling contained in the accurate map information based on a distance between the first stationary object and the second stationary object, and identifying at least one of the first stationary object or the second stationary object or any combination thereof as a road edge based on the difference between the first width and the second width being less than a first reference width.

[0179] In an embodiment, the processor does not identify at least one of the first stationary object, the second stationary object, and any combination thereof as a road edge based on a difference between the first width and the second width being greater than a first reference width.

[0180] In an embodiment, the processor may generate a histogram based on the area divided by the grid based on the coordinate of the second axis of the first reference point tracked on a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis.

[0181] In an embodiment, the processor may generate a histogram based on the first reference point identified in the area divided by the grid and the partial area obtained by dividing the area at specified intervals. The area divided by the grid may include an area for dividing lanes on each of which the host vehicle can travel.

[0182] In an embodiment, the processor can identify at least one of the first coordinate of the second axis of a first reference point identified on a plane formed by the first axis and the second axis among the first axis, the second axis and the third axis, the second coordinate of the second axis of the second reference point, or the third coordinate of the second axis of the third reference point, or any combination thereof, and can further identify that the first stationary object is located on the left side of the main vehicle based on the first coordinate of the second axis exceeding the second coordinate of the second axis, can further identify that the first stationary object is located on the right side of the main vehicle based on the first coordinate of the second axis being smaller than the second coordinate of the second axis, can further identify that the second stationary object is located on the left side of the main vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis, or can further identify that the second stationary object is located on the right side of the main vehicle based on the first coordinate of the second axis being smaller than the third coordinate of the second axis.

[0183] In an embodiment, the processor may identify the first stationary object as a first road edge based on the fact that the length of the second virtual frame is greater than or equal to the first reference length, no virtual frames different from the second virtual frame exist in the area where the second virtual frame is identified, the distance between the second reference point and the main vehicle is less than or equal to the first reference distance, and the second virtual frame includes more than a second reference number of points of a specified type, or identify the second stationary object as a second road edge based on the fact that the length of the third virtual frame is greater than or equal to the first reference length, no virtual frames different from the third virtual frame exist in the area where the third virtual frame is identified, the distance between the third reference point and the main vehicle is less than the first reference distance, and the third virtual frame includes a second reference number or more of points of the specified type.

[0184] In an embodiment, the processor can identify a first position and a second position in a grid used to divide a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis, can identify a first error in the direction of the first axis of the main vehicle based on a first coordinate of the first axis included in the first position and a second coordinate of the first axis included in the second position, can identify a second error in the direction of the second axis of the main vehicle based on a fourth coordinate of the second axis included in the first position and a fifth coordinate of the second axis included in the second position, and can compare the first width with the second width based on the first error being less than a first reference error and the second error being less than a second reference error.

[0185] In an embodiment, the processor can identify an area in which the main vehicle can travel from the area divided by the grid, based on identifying at least one stationary object different from the first stationary object or the second stationary object, or any combination thereof, in an area adjacent to the area where at least one of the first stationary object or the second stationary object, or any combination thereof, exists, without identifying at least one of the first stationary object or the second stationary object, or any combination thereof, as a road edge.

[0186] In an embodiment, the processor may identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge based on at least one of the length of the second virtual frame, the length of the third virtual frame, and a combination thereof being greater than or equal to the second reference length.

[0187] In an embodiment, the processor may identify a first point closest to the main vehicle from the points included in the second virtual frame based on the fact that the difference between the distance between the first point and the second point and the road width included in the precise map information is less than or equal to the second reference width, may identify a second point closest to the main vehicle from the multiple points included in the third virtual frame, and may identify at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge.

[0188] According to an embodiment of the present disclosure, a vehicle control method may include: based on obtaining a first virtual frame corresponding to an external vehicle recognized by LiDAR, identifying a first reference point within a line segment corresponding to a rear surface of the external vehicle among line segments forming the first virtual frame, and tracking the first reference point in an area divided by a grid during a frame of a designated area, relative to at least one of a second reference point located within a line segment corresponding to the rear surface of the first stationary object among line segments forming a second virtual frame corresponding to the first stationary object, or a third reference point located within a line segment corresponding to the rear surface of the second stationary object among line segments forming a third virtual frame corresponding to the second stationary object, or any combination thereof, from the first reference point obtained by LiDAR. Removing points located in an area different from an area in which the main vehicle can travel from the points obtained can be based on receiving accurate map information including a first position of the main vehicle through a communication circuit, by comparing the first position of the main vehicle with a second position of the main vehicle included in the GPS information, identifying an error related to the position of the main vehicle based on the second position, based on identifying that the error is less than a reference error, based on comparing a first width and a second width of a road on which the main vehicle is traveling contained in the accurate map information based on a distance between the first stationary object and the second stationary object, and based on the difference between the first width and the second width being less than a first reference width, identifying at least one of the first stationary object or the second stationary object or any combination thereof as a road edge.

[0189] According to an embodiment, the vehicle control method may further include not recognizing at least one of the first stationary object, the second stationary object, and any combination thereof as a road edge based on a difference between the first width and the second width being greater than a first reference width.

[0190] According to an embodiment, the vehicle control method may further include generating a histogram based on the area divided by the grid based on the coordinates of the second axis of the first reference point tracked on the plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis.

[0191] According to an embodiment, the vehicle control method may further include: generating a histogram based on a first reference point identified in an area divided by a grid and a partial area obtained by dividing the area at a specified interval. The area divided by the grid may include an area for dividing a lane on each of which the host vehicle can travel.

[0192] According to an embodiment, the vehicle control method may further include: identifying at least one of a first coordinate of the second axis of a first reference point identified on a plane formed by the first axis and the second axis among the first axis, the second axis and the third axis, a second coordinate of the second axis of the second reference point, or a third coordinate of the second axis of the third reference point, or any combination thereof; further identifying that the first stationary object is located on the left side of the main vehicle based on the first coordinate of the second axis exceeding the second coordinate of the second axis; further identifying that the first stationary object is located on the right side of the main vehicle based on the first coordinate of the second axis being smaller than the second coordinate of the second axis; further identifying that the second stationary object is located on the left side of the main vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis; or further identifying that the second stationary object is located on the right side of the main vehicle based on the first coordinate of the second axis being smaller than the third coordinate of the second axis.

[0193] According to an embodiment, the vehicle control method may further include: identifying the first stationary object as a first road edge based on the fact that the length of the second virtual frame is greater than or equal to the first reference length, there are no virtual frames different from the second virtual frame in the area where the second virtual frame is identified, the distance between the second reference point and the main vehicle is less than or equal to the first reference distance, and the second virtual frame includes a second reference number or more of points of a specified type, or identifying the second stationary object as a second road edge based on the fact that the length of the third virtual frame is greater than or equal to the first reference length, there are no virtual frames different from the third virtual frame in the area where the third virtual frame is identified, the distance between the third reference point and the main vehicle is less than the first reference distance, and the third virtual frame includes a second reference number or more of points of the specified type.

[0194] In an embodiment, the vehicle control method may further include: identifying a first position and a second position in a grid used to divide a plane formed by the first axis and the second axis among the first axis, the second axis, and the third axis, identifying a first error in the direction of the first axis of the main vehicle based on a first coordinate of the first axis included in the first position and a second coordinate of the first axis included in the second position, identifying a second error in the direction of the second axis of the main vehicle based on a fourth coordinate of the second axis included in the first position and a fifth coordinate of the second axis included in the second position, and comparing the first width with the second width based on the first error being less than the first reference error and the second error being less than the second reference error.

[0195] According to an embodiment, the vehicle control method may further include: identifying an area in which the main vehicle can travel from the area divided by the grid, based on identifying a stationary object different from the first stationary object or the second stationary object, or at least one of the first stationary object or the second stationary object, or any combination thereof, in an area adjacent to an area in which at least one of the first stationary object or the second stationary object, or any combination thereof, exists, without identifying at least one of the first stationary object or the second stationary object, or any combination thereof, as a road edge.

[0196] According to an embodiment, the vehicle control method may further include: identifying the first stationary object, the second stationary object, or at least one of their combinations as a road edge based on at least one of the length of the second virtual frame, the length of the third virtual frame, and their combination being greater than or equal to the second reference length.

[0197] According to an embodiment, the vehicle control method may further include: based on the fact that the difference between the distance between the first point and the second point and the road width included in the precise map information is less than or equal to the second reference width, identifying a first point closest to the main vehicle from the points included in the second virtual frame, identifying a second point closest to the main vehicle from the multiple points included in the third virtual frame, and identifying at least one of the first stationary object, the second stationary object, or any combination thereof as a road edge.

[0198] The above description is merely an embodiment of the technical concept of the present disclosure, and those skilled in the art may make various modifications and changes without departing from the characteristics of the present disclosure.

[0199] 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.

[0200] The present technology can identify road edges by using a histogram generated based on tracking a moving object.

[0201] Furthermore, the present technology can identify an area in which the host vehicle can travel by using width information included in map information and distance information between virtual frames.

[0202] Furthermore, the present technology may reduce the occurrence of errors in a vehicle control system associated with a vehicle control device by accurately identifying road edges.

[0203] Furthermore, various effects understood directly or indirectly through the specification can be provided.

[0204] 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, comprising: sensor; Communication circuits; as well as processor, Wherein, the processor is configured to: determining a first reference point within a line segment corresponding to a rear surface of an external vehicle, wherein the line segment is one of line segments forming a first virtual frame corresponding to the external vehicle detected by the sensor; Based on tracking the first reference point in an area partitioned by a grid associated with a frame of a designated area, removing points from a plurality of points obtained by the sensor with respect to at least one of: a second reference point located within a second line segment corresponding to a rear surface of the first stationary object, wherein the second line segment is one of line segments forming a second virtual frame corresponding to the first stationary object, or a third reference point located within a third line segment corresponding to a rear surface of a second stationary object, wherein the third line segment is one of line segments forming a third virtual frame corresponding to the second stationary object, wherein the point is located in an area different from an area where the host vehicle exists; The error associated with the position of the host vehicle is determined by comparing: a first location of the host vehicle included in map information received via the communication circuit; and a second location of the host vehicle included in global positioning system information; Based on determining that the error is less than the reference error, the following are compared: a first width of a road on which the host vehicle is traveling and which is included in the map information; and a second width based on a distance between the first stationary object and the second stationary object; determining at least one of the first stationary object and the second stationary object as a road edge based on a difference between the first width and the second width being less than or equal to a first reference width; and A signal indicative of the edge of the road is output.

2. The device according to claim 1, wherein: The processor is configured to: Based on the difference between the first width and the second width being greater than the first reference width, it is determined that at least one of the first stationary object and the second stationary object is not a road edge.

3. The device according to claim 1, wherein: The processor is configured to: A histogram is generated based on the coordinates of the second axis and the area of ​​the first reference point tracked on a plane formed by the first axis and the second axis, wherein: The area is divided by the grid, The first axis corresponds to the direction of travel of the host vehicle, and The second axis is perpendicular to the first axis.

4. The device according to claim 3, wherein: The processor is configured to: generating the histogram based on the first reference points detected in the area divided by the grid and a partial area obtained by dividing the area at specified intervals, and The area divided by the grid includes an area for dividing lanes, wherein the host vehicle can travel in each of the lanes.

5. The device according to claim 1, wherein: The processor is configured to: Identify at least one of the following: a first coordinate of the second axis of the first reference point, a second coordinate of the second reference point along a second axis, or a third coordinate of a second axis of the third reference point, wherein at least one of the first coordinate, the second coordinate, and the third reference point is identified on a plane formed by a first axis and a second axis perpendicular to the first axis, wherein the first axis corresponds to a direction of travel of the host vehicle; and determining that the first stationary object is located to the left of the host vehicle based on the first coordinate of the second axis exceeding the second coordinate of the second axis, determining that the first stationary object is located to the right of the host vehicle based on the first coordinate of the second axis being less than the second coordinate of the second axis, determining that the second stationary object is located to the left of the host vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis, or Based on the first coordinate of the second axis being less than the third coordinate of the second axis, it is determined that the second stationary object is located on the right side of the host vehicle.

6. The device according to claim 1, wherein: The processor is configured to: The first stationary object is determined to be a first road edge based on: The length of the second virtual frame is greater than or equal to the first reference length, Each virtual frame different from the second virtual frame does not exist in the area where the second virtual frame is detected, The distance between the second reference point and the host vehicle is less than or equal to the first reference distance, and The second virtual frame includes a second reference number or more of points of a specified type; or The second stationary object is determined to be a second road edge based on: The length of the third virtual frame is greater than or equal to the first reference length, each virtual frame different from the third virtual frame does not exist in the area where the third virtual frame is detected, The distance between the third reference point and the host vehicle is less than or equal to the first reference distance, and The third virtual frame includes the second reference number or more of points of the specified type.

7. The device according to claim 1, wherein: The processor is configured to: determining the first position and the second position in a grid for dividing a plane formed by a first axis and a second axis, wherein the first axis corresponds to a travel direction of the host vehicle and the second axis is perpendicular to the first axis; A first error in the direction of the first axis is determined based on: a first coordinate of a first axis included in said first position, and a second coordinate of the first axis included in the second position; A second error in the direction of the second axis of the host vehicle is determined based on: a fourth coordinate of the second axis included in the first position, and a fifth coordinate of the second axis included in the second position; and Based on the first error being smaller than a first reference error and the second error being smaller than a second reference error, the first width and the second width are compared.

8. The device according to claim 1, wherein: The processor is configured to: Determining an area in which the host vehicle can travel from the areas divided by the grid; as well as Based on determining a stationary object different from at least one of the first and second stationary objects in an area adjacent to an area where at least one of the first and second stationary objects exists, determining that at least one of the first and second stationary objects is not a road edge.

9. The device according to claim 1, wherein: The processor is configured to: At least one of the first stationary object and the second stationary object is determined to be a road edge based on at least one of the length of the second virtual frame and the length of the third virtual frame being greater than or equal to a second reference length.

10. The device according to claim 9, wherein: The processor is configured to: determining a first point closest to the host vehicle from among the points included in the second virtual frame; determining a second point closest to the host vehicle from among the points included in the third virtual frame; as well as At least one of the first stationary object and the second stationary object is determined to be a road edge based on: A difference between a distance between the first point and the second point and a road width included in the map information is less than or equal to a second reference width.

11. A method for controlling a vehicle, comprising: determining a first reference point within a line segment corresponding to a rear surface of an external vehicle, wherein the line segment is one of line segments forming a first virtual frame corresponding to the external vehicle detected by a sensor; Based on tracking the first reference point in an area partitioned by a grid associated with a frame of a designated area, removing points from a plurality of points obtained by a sensor with respect to at least one of: a second reference point located within a second line segment corresponding to a rear surface of the first stationary object, wherein the second line segment is one of line segments forming a second virtual frame corresponding to the first stationary object, or a third reference point located within a third line segment corresponding to a rear surface of a second stationary object, wherein the third line segment is one of line segments forming a third virtual frame corresponding to the second stationary object; The error associated with the host vehicle's position is determined by comparing: a first position of the host vehicle included in map information received via a communications circuit; and a second location of the host vehicle included in global positioning system information; Based on determining that the error is less than the reference error, the following are compared: a first width of a road on which the host vehicle is traveling and which is included in the map information; and a second width based on a distance between the first stationary object and the second stationary object; determining at least one of the first stationary object and the second stationary object as a road edge based on a difference between the first width and the second width being less than or equal to a first reference width; and A signal indicative of the edge of the road is output.

12. The method according to claim 11, further comprising: Based on the difference between the first width and the second width being greater than the first reference width, it is determined that at least one of the first stationary object and the second stationary object is not a road edge.

13. The method according to claim 11, further comprising: A histogram is generated based on the coordinates of the second axis and the area of ​​the first reference point tracked on the plane formed by the first axis and the second axis, wherein: The area is divided by the grid, The first axis corresponds to the direction of travel of the host vehicle, and The second axis is perpendicular to the first axis.

14. The method according to claim 13, further comprising: generating the histogram based on the first reference points detected in the area divided by the grid and a partial area obtained by dividing the area at specified intervals, and The area divided by the grid includes an area for dividing lanes, wherein the host vehicle can travel in each of the lanes.

15. The method according to claim 11, further comprising: Identify at least one of the following: a first coordinate of the second axis of the first reference point, a second coordinate of the second reference point along a second axis, or a third coordinate of a second axis of the third reference point, wherein at least one of the first coordinate, the second coordinate, and the third reference point is identified on a plane formed by a first axis and a second axis perpendicular to the first axis, wherein the first axis corresponds to a direction of travel of the host vehicle; and determining that the first stationary object is located to the left of the host vehicle based on the first coordinate of the second axis exceeding the second coordinate of the second axis; determining that the first stationary object is located to the right of the host vehicle based on the first coordinate of the second axis being less than the second coordinate of the second axis; determining that the second stationary object is located to the left of the host vehicle based on the first coordinate of the second axis exceeding the third coordinate of the second axis; or Based on the first coordinate of the second axis being less than the third coordinate of the second axis, it is determined that the second stationary object is located on the right side of the host vehicle.

16. The method according to claim 11, further comprising: The first stationary object is determined to be a first road edge based on: The length of the second virtual frame is greater than or equal to the first reference length, Each virtual frame different from the second virtual frame does not exist in the area where the second virtual frame is detected, The distance between the second reference point and the host vehicle is less than or equal to the first reference distance, and The second virtual frame includes a second reference number or more of points of a specified type; or The second stationary object is determined to be a second road edge based on: The length of the third virtual frame is greater than or equal to the first reference length, each virtual frame different from the third virtual frame does not exist in the area where the third virtual frame is detected, The distance between the third reference point and the host vehicle is less than or equal to the first reference distance, and The third virtual frame includes the second reference number or more of points of the specified type.

17. The method according to claim 11, further comprising: determining the first position and the second position in a grid for dividing a plane formed by a first axis and a second axis, wherein the first axis corresponds to a travel direction of the host vehicle and the second axis is perpendicular to the first axis; A first error in the direction of the first axis is determined based on: a first coordinate of a first axis included in said first position, and a second coordinate of the first axis included in the second position; A second error in the direction of the second axis of the host vehicle is determined based on: a fourth coordinate of the second axis included in the first position, and a fifth coordinate of the second axis included in the second position; and Based on the first error being smaller than a first reference error and the second error being smaller than a second reference error, the first width and the second width are compared.

18. The method according to claim 11, further comprising: Determining an area in which the host vehicle can travel from the areas divided by the grid; as well as Based on determining a stationary object different from at least one of the first and second stationary objects in an area adjacent to an area where at least one of the first and second stationary objects exists, determining that at least one of the first and second stationary objects is not a road edge.

19. The method according to claim 11, further comprising: At least one of the first stationary object and the second stationary object is determined to be a road edge based on at least one of the length of the second virtual frame and the length of the third virtual frame being greater than or equal to a second reference length.

20. The method according to claim 19, further comprising: determining a first point closest to the host vehicle from among the points included in the second virtual frame; determining a second point closest to the host vehicle from among the points included in the third virtual frame; as well as At least one of the first stationary object and the second stationary object is determined to be a road edge based on: A difference between a distance between the first point and the second point and a road width included in the map information is less than or equal to a second reference width.

Images