Patent ID: 12241981

DETAILED DESCRIPTION OF THE DISCLOSURE

It is understood that the term “vehicle” or “vehicular” or other similar term as used herein is inclusive of motor vehicles in general such as passenger automobiles including sports utility vehicles (SUV), buses, trucks, various commercial vehicles, watercraft including a variety of boats and ships, aircraft, and the like, and includes hybrid vehicles, electric vehicles, plug-in hybrid electric vehicles, hydrogen-powered vehicles and other alternative fuel vehicles (e.g. fuels derived from resources other than petroleum). As referred to herein, a hybrid vehicle is a vehicle that has two or more sources of power, for example both gasoline-powered and electric-powered vehicles.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. These terms are merely intended to distinguish one component from another component, and the terms do not limit the nature, sequence or order of the constituent components. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items. Throughout the specification, unless explicitly described to the contrary, the word “comprise” and variations such as “comprises” or “comprising” will be understood to imply the inclusion of stated elements but not the exclusion of any other elements. In addition, the terms “unit”, “-er”, “-or”, and “module” described in the specification mean units for processing at least one function and operation, and can be implemented by hardware components or software components and combinations thereof.

Although exemplary embodiment is described as using a plurality of units to perform the exemplary process, it is understood that the exemplary processes may also be performed by one or plurality of modules. Additionally, it is understood that the term controller/control unit refers to a hardware device that includes a memory and a processor and is specifically programmed to execute the processes described herein. The memory is configured to store the modules and the processor is specifically configured to execute said modules to perform one or more processes which are described further below.

Further, the control logic of the present disclosure may be embodied as non-transitory computer readable media on a computer readable medium containing executable program instructions executed by a processor, controller or the like. Examples of computer readable media include, but are not limited to, ROM, RAM, compact disc (CD)-ROMs, magnetic tapes, floppy disks, flash drives, smart cards and optical data storage devices. The computer readable medium can also be distributed in network coupled computer systems so that the computer readable media is stored and executed in a distributed fashion, e.g., by a telematics server or a Controller Area Network (CAN).

Unless specifically stated or obvious from context, as used herein, the term “about” is understood as within a range of normal tolerance in the art, for example within 2 standard deviations of the mean. “About” can be understood as within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. Unless otherwise clear from the context, all numerical values provided herein are modified by the term “about”.

Further, in describing the embodiments disclosed in the present specification, when it may be determined that a detailed description of related publicly known technology may obscure the gist of the embodiments disclosed in the present specification, the detailed description thereof will be omitted. The accompanying drawings may be used to help easily explain various technical features and it should be understood that the embodiments presented herein may not be limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which may be particularly set out in the accompanying drawings.

Although terms including ordinal numbers, such as “first”, “second”, etc., may be used herein only to differentiate elements, the elements may not be construed to be limited by these terms. These terms may be generally only used to distinguish one element from another.

When an element may be referred to as being “coupled” or “connected” to another element, the element may be directly coupled or connected to the other element. However, it should be understood that another element may be present therebetween. In contrast, when an element may be referred to as being “directly coupled” or “directly connected” to another element, it should be understood that there may be no other elements therebetween.

A singular expression includes the plural expression unless the context clearly dictates otherwise.

In the present specification, it should be understood that a term such as “include” or “have” may be intended to designate that the features, numbers, steps, operations, elements, parts, or combinations thereof described in the specification may be present, and does not preclude the possibility of addition or presence of one or more other features, numbers, steps, operations, elements, parts, or combinations thereof.

In addition, the term “unit” or “control unit” may be only a widely used term for a name of a controller for controlling a specific function of a vehicle, and does not mean a generic function unit. For example, each unit or control unit may include a communication device configured to communicate with another control device or sensor to control a function assigned thereto, a memory configured to store an operating system or logic command and input/output information, and one or more processors configured to perform determination, calculation, decision, etc. necessary for controlling the function assigned thereto.

Hereinafter, some embodiments of the present disclosure will be described in detail with reference to the exemplary drawings. In adding the reference numerals to the components of each drawing, it should be noted that the identical or equivalent component is designated by the identical numeral even when they are displayed on other drawings. Further, in describing the embodiment of the present disclosure, a detailed description of the related known configuration or function will be omitted when it is determined that it interferes with the understanding of the embodiment of the present disclosure.

First,FIG.2is a flowchart of clustering in an object detection method according to an embodiment of the present disclosure, andFIGS.3A to3Bare an example of a to-be-divided cluster.FIG.4illustrates an angle formed by a division point and adjacent points, andFIG.5is a conceptual diagram illustrating division points identified in one cluster.FIGS.6A to6Dillustrate a process of clustering division points and a representative point of the clustering, andFIG.7is a flowchart illustrating a process of dividing the to-be-divided cluster.FIGS.8A to8Care diagrams conceptually illustrating a process of dividing the to-be-divided cluster

The object detection method of the present embodiment includes a step S100of clustering points of a point cloud obtained from LiDAR, a step S200of selecting a to-be-divided candidate from among clusters generated in the step S100, and a step S300of dividing a to-be-divided cluster.

In addition, the step S300of dividing the to-be-divided cluster includes a step S310of selecting division points (break points) from among LiDAR points belonging to the to-be-divided cluster, a step S320of clustering the division points, and a step S330of dividing the to-be-divided cluster using a division point cluster generated in the step S320.

The point cloud acquired from LiDAR first undergoes a preprocessing to delete points having low signal strength or reflectivity and points reflected by the vehicle body, thereby extracting only valid data, and calibration may be performed to match LiDAR points to a reference coordinate system of the vehicle.

Here, the present embodiment relates to a case where the point cloud acquired from LiDAR may be 3D data acquired by multi-layered scans. However, the present disclosure may not be limited thereto.

When the preprocessing for the point cloud ends, the step S100of clustering the points of the point cloud based on grids may be performed.

For clustering, the preprocessed point cloud may be mapped to the grids, features of the grids may be generated using points included in each grid, and the features may be compared between grids in terms of similarity to determine whether to process the grids as the same cluster.

Subsequently, a to-be-divided cluster may be selected from among the clusters generated through the clustering step (S200).

Mis-clustering may be mainly caused by a dynamic object (for example, moving vehicle) and a temporary wall or a guardrail being grouped into one cluster. In addition, when there may be a motorcycle inbetween vehicles, mis-clustering may occur by these objects grouped into one cluster or the vehicle and a person grouped into one cluster.

The to-be-divided cluster may be preferably selected so that such mis-clusters may be targets.

In the present embodiment, the to-be-divided cluster may be selected using a division point to be described later.

For example, a cluster in which the number of division points may be equal to or greater than a reference value may be selected as the to-be-divided cluster.

For example,FIGS.3A to3Care an example of a mis-cluster C in which a temporary wall and a vehicle may be grouped into one cluster (shown as a box), and illustrates the case where the cluster C may be selected as a to-be-divided cluster C based on a division point criterion. For reference,FIG.3Ais an actual photograph of an object detection target,FIG.3Bis a point cloud acquired by LiDAR, andFIG.3Cillustrates an example of a state in which clustering may be performed on the point cloud.

In the present embodiment, a division point may be selected based on a geometrical feature formed by adjacent points (S310).

For example, as illustrated inFIG.4, when an angle θ formed by two front and back points Pn−1and Pn+1with reference to the index may be an acute angle, the corresponding point Pnmay be selected as a division point.

Such angle detection described above may be performed for points in the same layer, and when there may be no valid point among three consecutive indices, a point of an index immediately after the invalid point index may be used. For example, when there may be no valid point for an index ‘Pn+1’ inFIG.4, although not illustrated, a point of an index ‘Pn+2’, which may be a subsequent index, may be used.

In addition, in determining whether the angle θ ofFIG.4may be an acute angle, the following expression may be used.
1−cos θ  [Expression 1]

Here, cos θ may be as follows.

cos⁢θ=a→·b→❘"\[LeftBracketingBar]"a→❘"\[RightBracketingBar]"⁢❘"\[LeftBracketingBar]"b→❘"\[RightBracketingBar]"[Expression⁢2]

The above Expression 1 has 0 as a minimum value and 2 as a maximum value in a range where θ may be greater than 0 and less than π, and tends to nonlinearly increase. That is, as the angle θ increases, the value of Expression 1 tends to increase.

Accordingly, through Expression 1, an angle corresponding to a center point in a triangle formed by three points may be digitized and used.

Expression 1 may be significantly useful in that it may be possible to check an acute angle condition for an angle without a trigonometric operation, the computational cost of which may be high.

Meanwhile, instead of the above-mentioned acute angle criterion, an optimal reference value may be determined based on data in an actual driving environment according to a sensor configuration and mounting position, and a point greater than or equal to the reference value may be selected as a division point.

FIG.5is an example of selecting a division point by applying the acute angle criterion.

First, a point cloud cluster ofFIG.5is a simplified simulation of the to-be-divided cluster illustrated inFIGS.3A to3C. In the point cloud cluster, points of indices ‘Pk+1’ to ‘Pk+7’ may be data related to the vehicle, and indices ‘Pk−7’ to ‘Pk’ may be data related to the temporary wall.

When the acute angle criterion may be applied to the points ofFIG.5, three points from ‘Pk−1’ to ‘Pk+1’ may be selected as division points. Even though three division points may be illustrated inFIG.5, this illustration may be merely an example. Division points may be present for each layer, and also more than three division points may be present on the same layer.

Once all the division points for the to-be-divided cluster may be selected, next, the step S320of clustering the division points may be performed.

Referring toFIGS.6A to6C, first, division points may be mapped to a 2D grid map as illustrated inFIG.6B. Here, a grid may be a square as an example, and the size of the grid may be preferably determined so that division points detected in the same object may be processed as one cluster by checking data in which division points may be dense.

For the division point clustering, when there may be a grid adjacent to a certain grid as illustrated inFIG.6C, division points of those grids may be labeled as belonging to the same cluster.

In addition, for the division point cluster determined in this way, a representative point may be determined using an average value of the division points belonging thereto as illustrated inFIG.6D.

In the present embodiment, the representative point may be newly created as a point having average (coordinate) values of the corresponding division points. However, the representative point may be only used to represent the corresponding division point cluster, and may not be used as an object detection point.

In addition, determination of the representative point may not be limited to the above case, and for example, unlike the present embodiment, a division point closest to the average-valued coordinates may be determined as the representative point.

A plurality of division point clusters may be present in one to-be-divided cluster C, and it may be necessary to select an optimum division point cluster among these division point clusters.

FIG.7illustrates a process in which a final division point cluster to be used for division of the to-be-divided cluster may be selected, which will be described in detail below with reference toFIG.7.

First, it may be determined whether the number of division points may be equal to or greater than a first reference value for each of the division point clusters (S331and S332).

Determining whether the number of division points may be equal to or greater than the first reference value serves to determine the validity of the corresponding division point cluster, and an invalid cluster may be excluded from the division point clusters.

Here, the first reference value, which may be a criterion for determining validity, may be experimentally obtained through data on actual driving, and an optimal value may be preferably determined through many experiments.

A final cluster may be selected from among the valid clusters remaining. In order to minimize the amount of calculation, candidates may be first selected using feature angles θfof the clusters, and among the candidate clusters, one that satisfies conditions to be described later may be finally selected (S333).

In the present embodiment, among the valid clusters, a cluster having the largest feature angle θfand a cluster having the smallest feature angle θfmay be selected as candidates (S3331). When the to-be-divided cluster may be divided by straight lines of the two feature angle θfSof the two clusters selected as candidates, the one having the smaller difference in the number of points between the two divided clusters may be selected as the final cluster (S3332).

Here, the feature angle θfmay be an angle of a straight line L connecting the representative point of the division point cluster and the origin P0, as illustrated inFIGS.8Ato8C. In addition, here, the origin P0may be determined as coordinates corresponding to a LiDAR position.

In the present embodiment, the amount of calculation may be significantly reduced by selecting two clusters of the maximum and minimum values as final candidates based on the feature angle θf. Since clusters each having the number of division points equal to or greater than the first reference value may be targeted, an effective division point cluster may be obtained with only two candidates, which was confirmed proved to be through actual data.

Once the final division point cluster may be selected, it may be determined whether, when the to-be-divided cluster may be divided by the straight line L of the feature angle θfof the selected division point cluster, a ratio of the number of points of the one of the divided clusters DC1and DC2, which has more points than the other, to the total number of points may be smaller than a second reference value (S334).

Here, when it may be determined that the corresponding ratio may be equal to or greater than the second reference value, it may be determined that the corresponding cluster may be an invalid division point cluster, and a division process may be ended without change in order to prevent additional calculation costs.

When it may be determined that the ratio may be smaller than the second reference value, final division may be performed by the straight line L of the feature angle θfto obtain final two clusters C1and C2from the to-be-divided cluster C (S335). After division, the existing cluster C may be deleted and the final two clusters C1and C2may be registered as new clusters.

Here, the second reference value may be experimentally obtained through actual driving data, and an optimal value may be preferably determined through many experiments.

Meanwhile, a LiDAR-based object detection apparatus20according to an embodiment of the present disclosure may be an apparatus made to execute the method of the above-described embodiment, and may be included in a driving control system together with a driving strategy unit30and a vehicle control unit40as illustrated inFIG.9.

As illustrated inFIG.9, the object detection apparatus20receives point cloud data from a LiDAR 10, executes object detection, and outputs a result to the driving strategy unit30.

As illustrated in the figure, the object detection apparatus20may include a microprocessor, a memory, and an input/output device.

Here, the input/output device may be a device configured to receive data from the LiDAR 10 and output a detection result to the driving strategy unit.

In addition, the microprocessor may be a place for detecting an object by performing necessary data processing on a point cloud, and the method of the above-described embodiment may be loaded thereon as a program.

The memory stores a detection program executed by the microprocessor and related data such as the reference values.

In addition, the driving strategy unit30establishes a driving strategy for the vehicle according to a result detected by the object detection apparatus20, and outputs a result to the vehicle control unit40.

According to the result, the vehicle control unit40transmits a control signal for a steering device and/or a braking device to each corresponding device so that the driving strategy established by the driving strategy unit30may be executed.

According to the present disclosure, it may be possible to obtain improved object detection capability by providing an improved clustering result for LiDAR point data.

In addition, according to at least one embodiment of the present disclosure, it may be possible to perform such improved clustering without significantly increasing computational cost.

It will be apparent to those skilled in the art that various modifications and variations may be made in the present disclosure without departing from the spirit or scope of the disclosure. Thus, it may be intended that the present disclosure cover the modifications and variations of this disclosure provided they come within the scope of the appended claims and their equivalents.