KR102427810B1 - Method and apparatus for determining the lane's centerline network - Google Patents

Abstract

The present invention relates to a method and an apparatus for determining a lane centerline network. In accordance with one embodiment of the present disclosure, the method includes: the following steps of: acquiring a driving trajectory of a vehicle using a GPS mounted in the vehicle; matching a road map with the driving trajectory; generating road feature information considering the driving trajectory based on an image captured by a photographing device mounted in the vehicle; determining a position of a section node dividing a road of the road map into a plurality of sections based on the road feature information; determining a lane centerline for a driving lane of the vehicle among a plurality of lanes included in the sections based on the driving trajectory and estimating lane centerlines for the rest of the lanes, thereby determining lane centerline arrangement by section; determining a final longitudinal position of the section node based on the reliability of the section node with respect to each riving trajectory having repeatedly passed through the same road; determining a section network connection relationship between the section and a previous section and a next section based on the lane centerline arrangement by section; determining a geometric structure of the lane centerline arrangement by section based on the reliability of a section link connecting the section nodes to each other; and generating a lane centerline network based on the section network connection relationship and the geometric structure of lane centerlines in the sections. Therefore, the present invention is capable of accurately reflecting an actual road condition.

Description

METHOD AND APPARATUS FOR DETERMINING THE LANE'S CENTERLINE NETWORK

The present invention relates to a method and apparatus for determining a lane centerline network.

A vehicle traveling on a road may drive on any one of a plurality of lanes included in the road. A vehicle may frequently change lanes while driving, and a situation in which the number of lanes on a road is changed frequently also occurs.

Due to the convergence of information and communication technology and the vehicle industry, the smartization of vehicles is rapidly progressing. Due to smartization, vehicles are evolving from simple mechanical devices to smart cars, and autonomous driving is attracting attention as a core technology of smart cars. Autonomous driving is a technology that allows the vehicle to reach its destination on its own without the driver operating the steering wheel, accelerator pedal, or brake. Various additional functions related to autonomous driving are continuously being developed, and research on a method for providing a safe autonomous driving experience to passengers by recognizing and judging the driving environment using various data and controlling the vehicle is required.

Recently, in this regard, research for accurately generating a lane centerline network of a road map on which a vehicle travels is required.

The above-mentioned background art is technical information possessed by the inventor for the derivation of the present invention or acquired in the process of derivation of the present invention, and cannot necessarily be said to be a known technique disclosed to the general public prior to the filing of the present invention.

The present invention is to provide a method and apparatus for determining a lane centerline network. The problem to be solved by the present invention is not limited to the above-mentioned problems, and other problems and advantages of the present invention not mentioned can be understood by the following description, and more clearly understood by the embodiments of the present invention will be In addition, it will be appreciated that the problems and advantages to be solved by the present invention can be realized by means and combinations thereof indicated in the claims.

As a technical means for achieving the above technical problem, a first aspect of the present disclosure is a method for determining a lane's centerline network, using a GPS mounted on the vehicle to obtain a driving trajectory of the vehicle. step; matching a road map with the driving trajectory; generating road characteristic information in consideration of the driving trajectory based on an image captured by a vehicle-mounted photographing device; determining a location of a section node that divides a road of the road map into a plurality of sections based on the road characteristic information; Determine the lane centerline arrangement for each section by determining a lane centerline for the driving lane of the vehicle from among a plurality of lanes included in the section based on the driving trajectory and estimating the lane centerline for the remaining lanes step; determining a final longitudinal position of the section node based on the reliability of the section node for each of the driving trajectories that have repeatedly passed the same road; determining a section network connection relationship between the section and a previous section and a next section based on a centerline arrangement for each section; determining a geometry of a centerline arrangement for each section based on the reliability of a section link connecting the section nodes to each other; and generating a lane centerline network based on the section network connection relationship and a lane centerline geometry within the section.

A second aspect of the present disclosure provides an apparatus for determining a lane centerline network, comprising: a memory in which at least one program is stored; and a processor that performs an operation by executing the at least one program, wherein the processor obtains a driving trajectory of the vehicle using a GPS mounted on the vehicle, matches the road map with the driving trajectory, and provides the vehicle with a driving trajectory. generating road characteristic information in consideration of the driving trajectory based on the image captured by the mounted photographing device, and determining the location of a section node that divides the road of the road map into a plurality of sections based on the road characteristic information, and , by determining a lane centerline for the driving lane of the vehicle from among a plurality of lanes included in the section based on the driving trajectory and estimating the lane centerline for the remaining lanes to determine the lane centerline arrangement for each section The final longitudinal position of the section node is determined based on the reliability of the section node for each of the driving trajectories repeatedly passed on the same road, and based on the lane centerline arrangement for each section, the section and previous (previous) ) determines a section network connection relationship between a section and a next section, and determines a geometry of a centerline arrangement for each section lane based on the reliability of a section link connecting the section nodes to each other, and the section network connection relationship and generating a lane centerline network based on the lane centerline geometry in the section.

A third aspect of the present disclosure may provide a computer-readable recording medium recording a program for executing the method according to the first aspect on a computer.

In addition to this, another method for implementing the present invention, another system, and a computer-readable recording medium storing a computer program for executing the method may be further provided.

Other aspects, features and advantages other than those described above will become apparent from the following drawings, claims, and detailed description of the invention.

According to the problem solving means of the present disclosure described above, since only the vehicle trajectory and road characteristic information are used without using the image directly, lighter and faster production is possible compared to the LiDAR or image-based lane center line detection method.

In addition, the map production cost is low, expensive equipment is not needed, a lot of manpower is not required, there are not many types of input information, and the phase information of the map is accurate.

In addition, since the trajectory of the vehicle is used, it is possible to accurately reflect the actual road conditions.

1 is a view for explaining an example of a driving trajectory of a driving vehicle and an image obtained from the driving vehicle according to an exemplary embodiment;
2A to 2B are exemplary views for explaining a method of determining a lane number change point and an intersection section using road characteristic information according to an exemplary embodiment.
3 is an exemplary diagram for explaining a method of determining a U-turn section using road characteristic information according to an embodiment.
4 is an exemplary diagram for explaining a method of determining a junction/junction section using road characteristic information according to an embodiment.
5 is an exemplary diagram for describing a method of determining a location of a section node that divides a road of a road map into a plurality of sections based on road characteristic information according to an exemplary embodiment.
6A to 6C are exemplary diagrams for explaining a method of determining a lane arrangement for each section according to an exemplary embodiment.
7A to 7D are exemplary diagrams for explaining a method of correcting a centerline network of a lane within a section according to an embodiment.
8A to 8B are exemplary diagrams for explaining a method of grouping a section node according to an embodiment.
9 is an exemplary diagram for explaining a method of determining a final longitudinal position of section nodes in a node group according to an embodiment.
10 is an exemplary diagram for explaining a method of determining a section network connection relationship according to an embodiment.
11A to 11B are exemplary views for explaining a method of determining a geometry of a lane arrangement for each section according to an exemplary embodiment.
12 is a diagram for explaining an example of a lane centerline network according to an embodiment.
13 is a flowchart of a method for determining a lane centerline network according to an embodiment.
14 is a block diagram of an apparatus for determining a lane centerline network according to an exemplary embodiment.

Advantages and features of the present invention, and a method for achieving them will become apparent with reference to the detailed description in conjunction with the accompanying drawings. However, it should be understood that the present invention is not limited to the embodiments presented below, but may be implemented in a variety of different forms, and includes all transformations, equivalents, and substitutes included in the spirit and scope of the present invention. . The embodiments presented below are provided to complete the disclosure of the present invention, and to completely inform those of ordinary skill in the art to the scope of the present invention. In describing the present invention, if it is determined that a detailed description of a related known technology may obscure the gist of the present invention, the detailed description thereof will be omitted.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It is to be understood that this does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Some embodiments of the present disclosure may be represented by functional block configurations and various processing steps. Some or all of these functional blocks may be implemented in various numbers of hardware and/or software configurations that perform specific functions. For example, the functional blocks of the present disclosure may be implemented by one or more microprocessors, or by circuit configurations for a given function. Also, for example, the functional blocks of the present disclosure may be implemented in various programming or scripting languages. The functional blocks may be implemented as an algorithm running on one or more processors. Further, the present disclosure may employ prior art techniques for electronic configuration, signal processing, and/or data processing, etc. Terms such as "mechanism", "element", "means" and "configuration" will be used broadly. and are not limited to mechanical and physical configurations.

In addition, the connecting lines or connecting members between the components shown in the drawings only exemplify functional connections and/or physical or circuit connections. In an actual device, a connection between components may be represented by various functional connections, physical connections, or circuit connections that are replaceable or added.

Hereinafter, a 'vehicle' may mean any type of transportation means used to move people or things with an engine, such as a car, a bus, a motorcycle, a kickboard, or a truck.

Hereinafter, a 'lane' may mean a portion of a roadway divided by lanes so that a vehicle may pass a predetermined portion of the road in one line. The 'lane center line' may mean a virtual line passing through the center of the 'lane'.

The 'lane centerline network determining device' may be mounted on the vehicle 110 . Alternatively, the 'lane centerline network determining device' may be located outside the vehicle 110 and form a communication network with other devices (GPS receiver, camera, etc.) located inside the vehicle 110 to exchange data. The 'lane centerline network determining device' may be implemented as a computer device or a plurality of computer devices communicating through a network to provide commands, codes, files, contents, services, and the like. Hereinafter, for convenience of description, it is assumed that the 'lane centerline network determining device' is mounted on the vehicle 110 .

Hereinafter, the present disclosure will be described in detail with reference to the accompanying drawings.

1 is a view for explaining an example of a driving trajectory of a driving vehicle and an image obtained from the driving vehicle according to an exemplary embodiment;

Referring to FIG. 1 , a GPS receiver is mounted on a vehicle 110 while driving, and the GPS receiver may receive a GPS signal from an artificial satellite. The GPS receiver mounted on the vehicle 110 may obtain GPS location information including information about latitude and longitude of the vehicle 110 from the GPS signal. Also, the lane centerline network determining device mounted on the vehicle 110 may generate the driving trajectory 120 of the vehicle 110 by connecting the GPS location information.

The driving trajectory 120 of the vehicle 110 may be matched with the road map 100 . The lane centerline network determining apparatus may match the driving trajectory 120 of the vehicle 110 with the road map 100 by matching the location information stored in the road map 100 with the location information of the driving trajectory 120 .

In addition, a photographing device such as a camera may be mounted on the vehicle 110 being driven. The photographing device may photograph the surroundings of the vehicle 110 . Referring to FIG. 1 , an image 130 captured by the vehicle 110 while driving is shown. In FIG. 1 , only the image 130 photographed by the photographing device mounted on the front of the vehicle 110 is shown, but a photographing apparatus for photographing the side, rear, surround views, etc. of the vehicle 110 is added to the vehicle 110 . may be mounted as

The photographing apparatus may transmit the photographed image 130 to the vehicle centerline network determining apparatus.

The lane centerline network determining apparatus may generate road characteristic information in consideration of the driving trajectory 120 based on the image 130 captured by the photographing apparatus. This will be described later with reference to FIG. 2 .

2A to 2B are exemplary views for explaining a method of determining a lane number change point and an intersection section using road characteristic information according to an exemplary embodiment.

In an embodiment, the road characteristic information may include at least one of a lane number change point, an intersection section, a U-turn section, and a junction/junction section.

Referring to FIG. 2A , the apparatus for determining a lane centerline network may determine the point at which the number of lanes is changed while the vehicle is driving by calculating the number of left/right lanes at predetermined time intervals based on the driving lane in which the vehicle is currently driving. . For example, when a point where the rightmost lane is merged with the adjacent left lane occurs in a situation in which the vehicle is driving in the same lane, the lane centerline network determining apparatus may determine the merging point as a point at which road characteristic information is changed. .

Referring to FIG. 2B , the apparatus for determining a lane centerline network may determine an intersection section. The lane centerline network determining device analyzes the object in the image captured by the photographing device mounted on the vehicle, and when the object is identified as a traffic light, crosswalk, or stop line, it can be determined that the point at which the image was captured corresponds to the intersection section. have. The apparatus for determining a lane centerline network may determine a point at which an intersection section starts or ends as a point at which road characteristic information is changed.

3 is an exemplary diagram for explaining a method of determining a U-turn section using road characteristic information according to an embodiment.

The lane centerline network determining apparatus may determine the U-turn section based on the curvature value of the driving trajectory of the vehicle.

Specifically, referring to FIG. 3 , the apparatus for determining a lane centerline network may calculate curvature values at a plurality of points on the driving trajectory of the vehicle. Also, the apparatus for determining a lane centerline network may select a section in which the calculated curvature values are equal to or greater than the threshold value and the rotation direction is the same as the candidate section. Also, when the angular change amount of the candidate section is similar to the preset U-turn trajectory, the lane centerline network determining apparatus may determine the candidate section as the U-turn section.

The apparatus for determining a lane centerline network may determine a point at which the U-turn section starts or ends as a point at which road characteristic information is changed.

4 is an exemplary diagram for explaining a method of determining a junction/junction section using road characteristic information according to an embodiment.

The lane centerline network determining apparatus may determine the U-turn section based on the curvature value of the driving trajectory of the vehicle.

Specifically, referring to FIG. 4 , the apparatus for determining a lane centerline network may calculate curvature values at a plurality of points on the driving trajectory of the vehicle. Also, the apparatus for determining a lane centerline network may select a section in which the calculated curvature values are equal to or greater than the threshold value and the rotation direction is the same as the candidate section. In addition, the lane centerline network determining device determines the candidate section as the confluence/junction section when the amount of change in the angle of the candidate section corresponds to a left turn or a right turn, and an object in the image captured by the vehicle-mounted photographing device is identified as a crosswalk. can

The apparatus for determining a lane centerline network may determine a point at which a junction/junction section starts or ends as a point at which road characteristic information is changed.

5 is an exemplary diagram for explaining a method of determining a location of a section node that divides a road of a road map into a plurality of sections based on road characteristic information according to an embodiment.

When it is detected that the road characteristic information of the road on which the vehicle 510 is traveling is changed, the lane centerline network determining apparatus may classify a section of the road based on the detected point.

Referring to FIG. 5 , it is shown that road characteristic information is changed at a first point 521 and a second point 522 while the vehicle 510 is driving along the driving trajectory 500 . Specifically, when the lane change of the vehicle 510 occurs at the first point 521 and the change in the number of lanes of the road occurs at the second point 522 , the lane centerline network determining device includes the first point 521 and It may be detected that the road characteristic information is changed at the second point 522 .

The lane centerline network determining apparatus may determine the first point 521 and the second point 522 of which road characteristic information is changed as a section node, and classify the section 520 based on the determined section node. Meanwhile, a line connecting the first point 521 and the second point 522 which are nodes of the section 520 may be referred to as a section link. That is, the section 520 may include a section node and a section link connecting the section node.

In an embodiment, the apparatus for determining the lane centerline network may determine the reliability of the section node. The reliability of the section node may affect determining the longitudinal position of the section node in FIG. 9 .

The reliability of the section node may be determined by the reliability and accuracy weights of the road characteristic information.

The reliability of the road characteristic information may vary each time the road characteristic information is generated. For example, the reliability of road characteristic information may be determined according to factors (resolution, distance to an object, ambient brightness, etc.) affecting detection accuracy of road characteristic information.

The accuracy weight may be determined in consideration of a driving lane of the vehicle. For example, the accuracy weight for the driving lane of the vehicle may be determined to be the highest, and the accuracy weight may be determined to be lower as the distance from the driving lane is increased. Also, when the driving lane of the vehicle is changed or the vehicle is rotating, the accuracy weight may be determined to be low.

In an embodiment, the lane centerline network determining apparatus may determine the reliability of the section link. The reliability of the section link may have an effect on determining the final number of lanes and road types such as intersections when merging section links in FIG. 10 .

The reliability of the section link may be determined by the reliability of the road characteristic information and the section link weight.

The reliability of the road characteristic information may vary each time the road characteristic information is generated. For example, the reliability of road characteristic information may be determined according to factors (resolution, distance to an object, ambient brightness, etc.) affecting detection accuracy of road characteristic information.

The section link weight may be adjusted downward as the detection rate of the number of lanes decreases due to a lane change or the like.

6A to 6C are exemplary diagrams for explaining a method of determining a lane arrangement for each section according to an exemplary embodiment.

The lane center line network determining apparatus may determine a lane center line for a lane passed by the vehicle 610 in units of sections. For example, when the vehicle 610 continues to travel on two lanes, the lane center line network determining apparatus may determine a lane center line for the two lanes.

In addition, when a lane change of the vehicle 610 occurs, the lane center line network determining device determines the lane center line for the changed lane based on the current driving trajectory, and the lane center line for the lane before the change linearly estimates the past driving trajectory can be decided by

Referring to FIGS. 6A and 6B , it is illustrated that the vehicle 610 changed to a first lane while driving in a second lane. In this case, the lane center line network determining apparatus may determine the lane center line for the first lane based on the current driving trajectory, and the lane center line for the second lane may be determined by linearly estimating the past driving trajectory.

In addition, in the case of a lane center line for a non-driving lane, the lane center line network determining device laterally duplicates the lane center line for the driving lane and estimates the lane center line for the remaining lanes that have not been driven to determine the lane arrangement for each section. can

Referring to FIG. 6C , the vehicle 610 has changed a lane from a two-lane to a first-lane, and the lane centerline network determining device transversely replicates the lane centerline for the first and second lanes in the third lane and It is possible to estimate the lane center line for the four lanes.

Through the above-described process, the lane center line network determining apparatus may determine the lane center line arrangement in the corresponding section.

7A to 7D are exemplary diagrams for explaining a method of correcting a centerline network of a lane within a section according to an embodiment.

When predetermined road characteristic information is generated, the apparatus for determining a lane centerline network may correct a lane centerline network in a section based on a preset criterion. The predetermined road characteristic information may include an intersection section, a U-turn section, and the like. That is, since the lane center line is not displayed in the intersection section and the U-turn section, the lane is unclear, and accordingly, it is impossible to determine whether the lane has been changed. Therefore, the lane center line network in the section needs to be corrected based on a preset criterion.

In an embodiment, when the road characteristic information is an intersection section or a U-turn section, the device for determining a lane center line network determines a lane center line network within a section by applying an intersection traffic rule or a U-turn traffic rule regardless of the driving trajectory of the vehicle (or, can be corrected).

Referring to FIG. 7A , as an example of a vehicle turning right at an intersection, even if the vehicle actually enters from the third lane and exits from the first lane, the lane centerline network determining device determines that the vehicle enters from the fourth lane and exits from the fourth lane. One can determine the centerline network of lanes within a section.

Referring to FIG. 7B , as an example of a vehicle turning left at an intersection, even when the vehicle actually enters from the first lane and exits from the third lane, the lane centerline network determining device determines that the vehicle enters from the first lane and exits from the first lane. One can determine the centerline network of lanes within a section.

Referring to FIG. 7C , as an example in which the vehicle goes straight at the intersection, the lane center line network in the section may be determined as the vehicle entered and exited through the most straightened connection method.

Referring to FIG. 7D , as an example of a vehicle making a U-turn, even when the vehicle actually enters from the fourth lane and exits from the fourth lane, the lane centerline network determining device indicates that the vehicle enters from the fourth lane and exits from the third lane. Section I can determine the centerline network with my car.

8A to 8B are exemplary diagrams for explaining a method of grouping a section node according to an embodiment.

8A to 8B , driving trajectories of three vehicles passing the same road in different lanes are illustrated. Specifically, trajectory A may be a trajectory of vehicle A traveling in the first lane, trajectory B may be a trajectory of vehicle B traveling in the second lane, and trajectory C may be a trajectory of vehicle C traveling in 5 lanes.

In an embodiment, the apparatus for determining a lane centerline network may extract, as a node list, section nodes generated from each of driving trajectories estimated to have traveled on the same road based on a predetermined criterion. The predetermined criterion may include, but is not limited to, map matching information of a road, shape characteristics such as a direction and distance of a road, and a relational similarity.

Meanwhile, the apparatus for determining a lane centerline network may extract a section link list for a trajectory estimated to have passed the same road, based on the node list. The section link list can then be the subject of section link and lane centerline merging.

The lane centerline network determining apparatus may designate section nodes in the node list located within a predetermined distance as a node group by tracking the section links. Referring to FIG. 8A , the apparatus for determining a lane centerline network may designate two section nodes near an intersection entry stop line located within a predetermined distance as a node group.

The predetermined section node may be matched with road characteristic information corresponding to the section to which the predetermined section node belongs. The characteristic information of the section node may include, but is not limited to, a lane number change type, an intersection section, a U-turn section, a junction/junction section of a road, and the like.

The apparatus for determining a lane centerline network may designate section nodes in a node list having the same road characteristic information as a node group while being located within a predetermined distance. Referring to FIG. 8A , the apparatus for determining a lane centerline network may designate, as a node group, two section nodes near an intersection entry stop line, which are located within a predetermined distance and have the same road characteristic information as an intersection section.

Meanwhile, when a matching section node is not found on the trajectory, the lane centerline network determining apparatus may insert a section node into a section link having a similar direction and a shortest distance and separate the lane centerline. Referring to FIG. 8B , since there is no node matching the section node indicating the road junction section in the above two section links, the lane centerline network determining apparatus inserts the section node indicating the road junction section into the two section links above, The center line can be separated.

In an embodiment, the apparatus for determining a lane centerline network may remove at least some of the section nodes in the node group. Specifically, the apparatus for determining a lane centerline network may remove erroneously matched section nodes due to a position error of a trajectory, erroneous detection of road characteristics, and the like.

For example, the apparatus for determining a lane centerline network may remove a section node having a different front/rear positional relationship based on an intersection section included in the road characteristic information from among the section nodes in the node group.

In addition, when a predetermined section node belongs to a plurality of node groups, the apparatus for determining a lane centerline network converts a node group having a high degree of similarity between the predetermined section node and road characteristic information and having a shorter distance to the node group of the predetermined section node. can be specified. That is, a predetermined section node may be removed from an unspecified node group.

9 is an exemplary diagram for explaining a method of determining a final longitudinal position of section nodes in a node group according to an embodiment.

Referring to FIG. 9 , it is assumed that the first section node 510 and the second section node 520 belong to the same node group.

8A to 8D, only the section nodes for the lane on which the vehicle has traveled are shown, whereas in FIG. 9, the lane centerline for the lane on which the vehicle has traveled and the lane centerline for the other lanes other than the lane on which the vehicle has traveled are shown, each The nodes of the lane centerline are shown.

The lane centerline network determining apparatus uses the node reliability of each of the plurality of section nodes 510 and 520 included in the node group as a weight, and a representative section node 530 that merges the section nodes 510 and 520 in the node group. ) can be determined in the final longitudinal position. Although the representative section node 530 is illustrated as a plurality of nodes in FIG. 9 , the representative section node 530 may be displayed as a single node because information about the longitudinal position on the road is the key.

The reliability of the section node may be determined by the reliability and accuracy weights of the road characteristic information.

The reliability of the road characteristic information may vary each time the road characteristic information is generated. For example, the reliability of road characteristic information may be determined according to factors (resolution, distance to an object, ambient brightness, etc.) affecting detection accuracy of road characteristic information.

The accuracy weight may be determined in consideration of a driving lane of the vehicle. For example, the accuracy weight for the driving lane of the vehicle may be determined to be the highest, and the accuracy weight may be determined to be lower as the distance from the driving lane is increased. Also, when the driving lane of the vehicle is changed or the vehicle is rotating, the accuracy weight may be determined to be low.

The lane centerline network determining apparatus may correct and match the lane centerline longitudinal positions of sections to be merged based on the final longitudinal position of the representative section node.

Also, the lane centerline network determining apparatus may correct the final longitudinal position of the representative section node so that the length of the front/rear section of the representative section node is equal to or greater than a predetermined length.

Also, the apparatus for determining the lane centerline network may determine the road characteristic information of the representative section node based on the reliability of the section nodes included in the node group and the road characteristic information matched with the nodes. For example, among 10 section nodes included in the node group, when road characteristic information of 9 section nodes is an intersection section and road characteristic information of one section node is a pocket section, the lane centerline network determining device is representative The road characteristic information of the section node may be determined as an intersection section.

10 is an exemplary diagram for explaining a method of determining a section network connection relationship according to an embodiment.

In an embodiment, the apparatus for determining a lane centerline network may determine a section network connection relationship between a reference section and a previous section and a next section based on the lane centerline arrangement for each section.

Specifically, the apparatus for determining a lane centerline network may select an anchor section having the highest reliability from among a plurality of sections. For example, the lane centerline network determining apparatus may designate links connected to the representative section node as a link group. Also, the apparatus for determining a lane centerline network may select a section corresponding to a link group having the highest reliability from among a plurality of link groups as an anchor section based on a predetermined criterion. The predetermined criterion may include, for example, whether the number of lanes in the section link group matches, whether the number of lanes in front/rear sections match, and the maximum number of lanes.

Referring to FIG. 10 , since the first section link group 610 has the smallest number of lane centerlines and the number of lanes also coincide with each other, a section corresponding to the first section link group 610 may be an anchor section.

The lane centerline network determining device may connect the previous section and the subsequent section based on the anchor section.

Specifically, the lane centerline network determining apparatus may number the lanes of the front/rear section based on the lane number of the anchor section. For example, the lane numbers indicated as 1, 2, 3, and 4 lanes may be changed to -1, 0, 1, and 2 lanes to correspond to the lane numbers of the anchor section in FIG. 10 .

In addition, the lane centerline network determining apparatus may calculate the probability (possibility of the existence of a lane) for each lane for each section, and the probability may decrease as the distance from the driving lane increases. For example, for a section created by driving in lane 1 on a three-lane road, the probability that the lane exists is 100% in lane 1, 75% in lane 2, 50% in lane 3, and -25 lane in non-existence. %, the 0th order becomes -75%. The lane centerline network determining apparatus may obtain the final number of lanes by excluding lanes having a sum of probability less than 0% by additionally considering the reliability of the section link described in FIG. 5 . For example, since the number of lanes of the anchor section is two in FIG. 10 , the number of final lanes of the next section 620 connected to the anchor section may also be determined to be two.

In one embodiment, the lane centerline network determining device iteratively determines the number of final lanes for the connected front/rear section link group, and if there is no connected section link group, iteratively determines the number of lanes of the next-highest reliable section link group. can be merged with In addition, the lane centerline network determining device may differentially apply the influence of the side closer to the driving lane, thereby driving the lanes at both ends to quickly and accurately complete the lane structure.

11A to 11B are exemplary views for explaining a method of determining a geometry of a lane arrangement for each section according to an exemplary embodiment.

In an embodiment, the apparatus for determining a lane center line network may adjust a lateral position of a lane center line within a section by determining a linear weight to be higher as the lane center line is closer to the driving lane of the vehicle. Also, the lane centerline network determining apparatus may determine the lane centerline geometry within the section according to the adjusted lateral position.

Referring to FIG. 11A , the geometry of the lane centerline arrangement may be determined by combining the sections based on the lane centerline linear weight.

The lane centerline network determining apparatus may reflect the lane centerline reliability in which the linear weight decreases as the driving lane and the farther away centerline of the vehicle increase, and the lane centerline linearity accuracy of the section in which the linear distortion decreases as the linear distortion occurs. That is, the closer to the driving lane, the more differentially applied the influence of the lane centerline alignment, so that the asymmetrical lane creation and linearity accuracy can be quickly secured.

In addition, the apparatus for determining the lane centerline network may determine the geometry of the lane centerline within the section along by removing the step difference occurring in the connection portion between the sections.

Referring to FIG. 11B , the lane centerline network determining apparatus may generate a final lane centerline geometry by removing a lateral step between front and rear lane centerlines occurring near an intersection. For example, if you drive straight/left/right turn at an intersection and drive 3 times on the same general road, a step difference occurs because the combination of trajectories is different between the intersection and the general road. can be removed

12 is a diagram for explaining an example of a lane centerline network according to an embodiment.

The lane centerline network determining apparatus may generate the lane centerline network based on the section network connection relationship and the lane centerline geometry within the section described above with reference to FIGS. 1 to 11 .

Referring to FIG. 12 , a lane center line link is indicated by a black line, a section node is indicated by a dot, and a section is indicated by a box.

Meanwhile, the number of driving per section may be additionally considered in various evaluation criteria used in the process of generating the lane centerline network.

Specifically, when the node reliability of each of the plurality of section nodes included in the node group is used as a weight, the number of trips per section may be additionally considered in the corresponding weight. In addition, as the number of trips per section increases, the longitudinal position of the section node may be greatly affected. In addition, the number of trips per section may be further considered in correcting the longitudinal position of the section and the lane center line. For example, when a section junction is encountered, the longitudinal position can be corrected in the same way for section links at all junctions. In addition, the number of driving per section may be additionally considered to determine road characteristic information of the representative section node. In addition, the number of driving visits of the section link may be applied as a weight to the possibility of existence or nonexistence of the lane. In addition, when the connection relationship of the sections to be merged is different, in selecting the connection relationship, the number of driving visits of the section link may be added as a weight. In addition, the number of driving visits of the section link may be added to the linear weight of the lane centerline.

13 is a flowchart of a method for determining a lane centerline network according to an embodiment.

The method for determining the lane centerline network shown in FIG. 13 is related to the embodiments described in the drawings described above, and therefore, even if omitted below, the contents described in the drawings are the method of FIG. 13 . can also be applied to

Referring to FIG. 13 , in operation 1310 , the processor may acquire the driving trajectory of the vehicle using the GPS mounted on the vehicle.

In operation 1320, the processor may match a road map with the driving trajectory.

In operation 1330, the processor may generate road characteristic information in consideration of the driving trajectory based on the image captured by the photographing device mounted on the vehicle.

The road characteristic information may include at least one of a lane number change point, an intersection section, a U-turn section, and a junction/junction section.

The processor may calculate curvature values at a plurality of points on the driving trajectory of the vehicle, select a section in which the calculated curvature values are equal to or greater than a threshold value and have the same rotational direction as a candidate section, and the amount of angular change of the candidate section When similar to the preset U-turn trajectory, the candidate section may be determined as the U-turn section.

In addition, the processor may calculate curvature values at a plurality of points on the driving trajectory of the vehicle, select a section in which the calculated curvature values are equal to or greater than a threshold value and have the same rotational direction as the candidate section, and the angle of the candidate section When the amount of change corresponds to a left turn or a right turn, and an object in an image captured by a vehicle-mounted photographing device is identified as a crosswalk, the candidate section may be determined as the junction/junction section.

In operation 1340, the processor may determine a location of a section node that divides the road of the road map into a plurality of sections based on the road characteristic information.

A section may include a section node and a section link connecting the section nodes to each other.

When a change in road characteristic information is detected, the processor may determine the detected point as a section node and classify the section based on the determined section node.

The processor may determine the reliability of the section node. The reliability of the section node may be determined by the reliability of the road characteristic information and the accuracy weight considering the driving lane. The accuracy weight for the driving lane of the vehicle may be determined to be the highest, and the accuracy weight may be determined to be lower as the lane is further away from the driving lane. When the driving lane of the vehicle is changed or the vehicle is rotating, the accuracy weight may be determined to be low.

The processor may determine the reliability of the section link. The reliability of the section link may be determined by the reliability of the road characteristic information and the section link weight. The lower the detection rate of the number of lanes, the lower the link accuracy weight may be determined.

In step 1350, the processor determines a lane centerline for the driving lane of the vehicle from among a plurality of lanes included in the section based on the driving trajectory and estimates the lane centerline for the remaining lanes, thereby estimating the lane for each section. The centerline placement can be determined.

When the road characteristic information is an intersection section or a U-turn section, the processor may determine the lane centerline arrangement in the section by applying the intersection traffic rule or the U-turn traffic rule regardless of the driving trajectory of the vehicle.

In operation 1360 , the processor may determine the final longitudinal position of the section node based on the reliability of the section node for each of the driving trajectories repeatedly passed on the same road.

The processor may extract, as a node list, section nodes generated from each of the driving trajectories estimated to have traveled on the same road based on a predetermined criterion. Road characteristic information corresponding to the section to which the predetermined section node belongs may be matched with the predetermined section node.

The processor may designate section nodes in the node list located within a predetermined distance as a node group by tracking the section links.

The processor may designate section nodes in the node list having the same road characteristic information as a node group while being located within a predetermined distance.

When there is no section node having the same road characteristic information within a predetermined distance, the processor may insert the predetermined section node into a section link having a similar direction and a shortest distance, and separate the lane centerline.

The processor may remove a section node having a different front/rear positional relationship based on an intersection section included in the road characteristic information from among the section nodes in the node group.

When a predetermined section node belongs to a plurality of node groups, the processor may designate a node group having a high degree of similarity between the predetermined section node and road characteristic information and having a shorter distance as the node group of the predetermined section node.

In operation 1370 , the processor may determine a section network connection relationship between a section and a previous section and a next section based on the centerline arrangement for each section.

The processor may determine the final longitudinal position of the representative section node in which the section nodes in the node group are merged by using the node reliability of each of the plurality of section nodes included in the node group as a weight.

The processor may correct the final longitudinal positions of the section nodes in the node group so that the front/rear section length of the representative section node is equal to or greater than a predetermined length.

The processor may determine the road characteristic information of the representative section node based on the reliability of the section nodes included in the node group and the road characteristic information matched with the section nodes.

The processor designates links connected to the representative section node as a link group, selects a section corresponding to a link group having the highest reliability from among a plurality of link groups, based on a predetermined criterion, as an anchor section, and based on the selected anchor section can determine the section network connection relationship between the previous section and the subsequent section.

The processor may determine the reliability of the link group by determining the possibility of the existence of the lane to be higher as the lane is closer to the driving lane of the vehicle.

In operation 1380, the processor may determine the geometry of the centerline arrangement for each section based on the reliability of the section links connecting the section nodes to each other.

The processor may adjust the lateral position of the lane center line within the section by determining a linear weight to be higher as the center line of the lane closer to the driving lane of the vehicle is, and determine the geometry of the lane center line within the section according to the adjusted lateral position.

The processor may determine the geometry of the difference within the section along by removing the step that occurs in the connection portion between the sections.

In operation 1390 , the processor may generate the lane centerline network based on the section network connection relationship and the lane centerline geometry within the section.

14 is a block diagram of an apparatus for determining a lane centerline network according to an exemplary embodiment.

Referring to FIG. 14 , the lane centerline network determining apparatus 1400 may include a communication unit 1410 , a processor 1420 , and a DB 1430 . Only the components related to the embodiment are shown in the lane centerline network determining apparatus 1400 of FIG. 14 . Accordingly, it can be understood by those skilled in the art that other general-purpose components may be further included in addition to the components shown in FIG. 14 .

The communication unit 1410 may include one or more components for performing wired/wireless communication with an external server or an external device. For example, the communication unit 1410 may include at least one of a short-range communication unit (not shown), a mobile communication unit (not shown), and a broadcast receiving unit (not shown).

The DB 1430 is hardware for storing various data processed in the lane centerline network determining apparatus 1400 , and may store a program for processing and controlling the processor 1420 . The DB 1430 may store payment information, user information, and the like.

DB 1430 is a random access memory (RAM), such as dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), CD- It may include ROM, Blu-ray or other optical disk storage, a hard disk drive (HDD), a solid state drive (SSD), or flash memory.

The processor 1420 controls the overall operation of the lane centerline network determining apparatus 1400 . For example, the processor 1420 may generally control the input unit (not shown), the display (not shown), the communication unit 1410 , the DB 1430 , and the like by executing programs stored in the DB 1430 . The processor 1420 may control the operation of the lane centerline network determining apparatus 1400 by executing programs stored in the DB 1430 .

The processor 1420 may control at least some of the operations of the lane centerline network determining apparatus 1400 described above with reference to FIGS. 1 to 13 .

The processor 1120 is ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), controllers (controllers), microcontroller It may be implemented using at least one of (micro-controllers), microprocessors, and other electrical units for performing functions.

As an embodiment, the lane centerline network determining apparatus 1400 may be an electronic device having mobility. For example, the traffic information providing apparatus 800 may be implemented as a smartphone, a tablet PC, a PC, a smart TV, a personal digital assistant (PDA), a laptop, a media player, a navigation device, a device equipped with a camera, and other mobile electronic devices. can In addition, the lane centerline network determining apparatus 1400 may be implemented as a wearable device such as a watch, glasses, a hair band, and a ring having a communication function and a data processing function.

In another embodiment, the lane centerline network determining device 1400 may be an electronic device embedded in a vehicle. For example, the lane centerline network determining apparatus 1400 may be an electronic device inserted into a vehicle through tuning after a production process.

In another embodiment, the lane centerline network determining apparatus 1400 may be a server located outside the vehicle. The server may be implemented as a computer device or a plurality of computer devices that communicate through a network to provide commands, codes, files, contents, services, and the like. The server may receive data necessary to determine a moving path of the vehicle from devices mounted on the vehicle, and determine the moving path of the vehicle based on the received data.

Embodiments according to the present invention may be implemented in the form of a computer program that can be executed through various components on a computer, and such a computer program may be recorded in a computer-readable medium. In this case, the medium includes a hard disk, a magnetic medium such as a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floppy disk, and a ROM. , RAM, flash memory, and the like, hardware devices specially configured to store and execute program instructions.

Meanwhile, the computer program may be specially designed and configured for the present invention, or may be known and used by those skilled in the computer software field. Examples of the computer program may include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like.

According to an embodiment, the method according to various embodiments of the present disclosure may be included and provided in a computer program product. Computer program products may be traded between sellers and buyers as commodities. The computer program product is distributed in the form of a machine-readable storage medium (eg compact disc read only memory (CD-ROM)), or via an application store (eg Play Store™) or between two user devices. It can be distributed directly or online (eg, downloaded or uploaded). In the case of online distribution, at least a part of the computer program product may be temporarily stored or temporarily created in a machine-readable storage medium such as a memory of a server of a manufacturer, a server of an application store, or a relay server.

The steps constituting the method according to the present invention may be performed in an appropriate order, unless explicitly stated or contrary to the order. The present invention is not necessarily limited to the order in which the steps are described. The use of all examples or exemplary terms (eg, etc.) in the present invention is merely for the purpose of describing the present invention in detail, and the scope of the present invention is limited by the examples or exemplary terms unless defined by the claims. it's not going to be In addition, those skilled in the art will recognize that various modifications, combinations, and changes may be made in accordance with design conditions and factors within the scope of the appended claims or their equivalents.

Therefore, the spirit of the present invention should not be limited to the above-described embodiments, and the scope of the spirit of the present invention is not limited to the scope of the scope of the present invention. will be said to belong to

Claims (14)

A method for determining a lane's centerline network, comprising:
obtaining a driving trajectory of the vehicle using a GPS mounted on the vehicle;
matching a road map with the driving trajectory;
generating road characteristic information in consideration of the driving trajectory based on an image captured by a vehicle-mounted photographing device;
determining a location of a section node that divides a road of the road map into a plurality of sections based on the road characteristic information;
Determine the lane centerline arrangement for each section by determining a lane centerline for the driving lane of the vehicle from among a plurality of lanes included in the section based on the driving trajectory and estimating the lane centerline for the remaining lanes step;
determining a final longitudinal position of the section node based on the reliability of the section node for each of the driving trajectories that have repeatedly passed the same road;
determining a section network connection relationship between the section and a previous section and a next section based on a centerline arrangement for each section;
determining a geometry of a centerline arrangement for each section based on the reliability of a section link connecting the section nodes to each other; and
generating a lane centerline network based on the section network connection relationship and a lane centerline geometry within the section;
A method comprising The method of claim 1,
the section includes a section node and a section link connecting the section nodes to each other;
The method is
extracting, as a node list, section nodes generated from each of the driving trajectories estimated to have traveled on the same road based on a predetermined criterion;
include more
The method of claim 1, wherein road characteristic information corresponding to the section to which the predetermined section node belongs is matched to the predetermined section node. 3. The method of claim 2,
The method is
designating section nodes in the node list located within a predetermined distance as a node group by tracking the section links;
A method further comprising: 4. The method of claim 3,
The step of designating the node group includes:
designating section nodes in the node list that are located within the predetermined distance and have the same road characteristic information as a node group;
A method comprising 5. The method of claim 4,
The step of designating the node group includes:
if there is no section node having the same road characteristic information within the predetermined distance, inserting the predetermined section node into a section link having a similar direction and having a shortest distance and separating a lane centerline;
A method comprising 4. The method of claim 3,
The method is
removing a section node having a different front/rear positional relationship based on an intersection section included in the road characteristic information from among the section nodes in the node group;
A method further comprising: 4. The method of claim 3,
The method is
when a predetermined section node belongs to a plurality of node groups, designating a node group having a high degree of similarity between the predetermined section node and road characteristic information and having a shorter distance as the node group of the predetermined section node;
A method further comprising: 4. The method of claim 3,
The method is
determining a final longitudinal position of a representative section node in which the section nodes in the node group are merged by using the node reliability of each of the plurality of section nodes included in the node group as a weight;
A method further comprising: 9. The method of claim 8,
The method is
correcting the final longitudinal positions of the section nodes in the node group so that the front/rear section length of the representative section node is equal to or greater than a predetermined length;
A method comprising 9. The method of claim 8,
The method is
determining road characteristic information of the representative section node based on reliability of section nodes included in the node group and road characteristic information matched with the section nodes;
A method comprising 9. The method of claim 8,
designating links connected to the representative section node as a link group;
selecting, as an anchor section, a section corresponding to a link group having the highest reliability from among a plurality of link groups based on a predetermined criterion; and
determining a section network connection relationship between a previous section and a subsequent section based on the selected anchor section;
A method comprising 12. The method of claim 11,
The method is
determining the reliability of the link group by determining a higher likelihood of the existence of a lane as the lane is closer to the driving lane of the vehicle;
A method comprising An apparatus for determining a lane centerline network, comprising:
a memory in which at least one program is stored; and
A processor for performing an operation by executing the at least one program,
The processor is
Acquire the driving trajectory of the vehicle using the GPS mounted on the vehicle,
Matching the road map and the driving trajectory,
generating road characteristic information in consideration of the driving trajectory based on an image captured by a vehicle-mounted photographing device;
determining a location of a section node that divides a road of the road map into a plurality of sections based on the road characteristic information;
Determine the lane centerline arrangement for each section by determining a lane centerline for the driving lane of the vehicle from among a plurality of lanes included in the section based on the driving trajectory and estimating the lane centerline for the remaining lanes, and ,
Determine the final longitudinal position of the section node based on the reliability of the section node for each of the driving trajectories repeatedly passed on the same road,
determining a section network connection relationship between the section and a previous section and a next section based on the lane centerline arrangement for each section;
Based on the reliability of the section link connecting the section nodes to each other, the geometry of the center line arrangement is determined by the section by section,
and generating a lane centerline network based on the section network connection relationship and a lane centerline geometry within the section. A computer-readable recording medium in which a program for executing the method of claim 1 in a computer is recorded.

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