A data processing method and device, electronic equipment and storage medium

Abstract

The application discloses a data processing method and device, electronic equipment and storage medium. The method comprises the following steps: performing type identification on a target region; in the case that the region type is a first type, determining an associated lane center line in a plurality of adjacent regions of the target region, a plurality of associated lane center lines, and a plurality of first intersection points of the plurality of associated lane center lines and the target region; based on the plurality of first intersection points and the center line node, generating a vector corresponding to each first intersection point; based on the target intersection point pair, extending the vector corresponding to the target intersection point pair, and generating a control point corresponding to the target intersection point pair; based on the target intersection point pair and the control point, performing curve fitting to generate a lane center line in the target region and generate a map of the target region. The application can make the generated lane center line smoother, more in line with the actual road form, ensure the accuracy of the lane center line, and further improve the effectiveness and generation efficiency of the generated map.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a data processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the rapid development of artificial intelligence technology, the demand for high-precision maps for autonomous vehicles is becoming increasingly urgent. Compared with navigation electronic maps, high-precision maps can provide lane-level road conditions, have a higher update frequency of road elements, and more detailed data models. The provided three-dimensional models, such as slope, curvature, and heading, can help autonomous vehicles better avoid potential risks.

[0003] In existing technologies, the data production of high-precision maps mainly involves professional mobile surveying and acquisition, with fieldwork collecting multi-dimensional road information and office work using automated algorithms and manual mapping to generate road elements, including lane centerlines. However, in more complex scenarios, such as intersections and interchanges, the lane centerlines generated by existing methods based on block segmentation or vehicle trajectory point fitting differ significantly from the actual road shape. Manual mapping still constitutes the majority of the workload, making it difficult to guarantee the accuracy and efficiency of lane centerline generation, thus affecting the effectiveness and generation efficiency of high-precision maps. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, this invention discloses a data processing method, apparatus, electronic device, and storage medium that enables the generated lane centerlines to be smoother, more closely resemble actual road conditions, ensure the accuracy of lane centerlines, and thereby improve the effectiveness and generation efficiency of the generated map. The technical solution disclosed in this invention is as follows:

[0005] According to one aspect of the embodiments disclosed in this invention, a data processing method is provided, comprising:

[0006] Type identification is performed on the target region to determine the region type of the target region;

[0007] When the area type is the first type, determine the associated lane centerlines in multiple adjacent areas of the target area;

[0008] Determine multiple first intersection points between the centerlines of multiple associated lanes and the target area;

[0009] Based on the plurality of first intersection points and centerline nodes, a vector is generated corresponding to each first intersection point, wherein the centerline node is the point on the centerline of the associated lane that is closest to the plurality of first intersection points;

[0010] Based on the target intersection pair, extend the vector corresponding to the target intersection pair to generate the control point corresponding to the target intersection pair. The target intersection pair is two first intersection points located in any two adjacent regions, and the control point is the endpoint of the extended vector corresponding to the target intersection pair.

[0011] Based on the target intersection points and the control points, curve fitting is performed to generate the lane centerline within the target area;

[0012] A map of the target area is generated based on the lane centerline.

[0013] Optionally, the method further includes:

[0014] Type identification is performed on the target region to determine the region type of the target region;

[0015] If the region type is the second type, determine the points to be projected within the target region;

[0016] The points to be projected are projected to obtain target projection points corresponding to each point to be projected. The points to be projected are located on the first boundary line and the target projection points are located on the second boundary line. The first boundary line and the second boundary line are the two boundary lines of the same lane.

[0017] Determine the midpoint position information of the point to be projected and the target projection point;

[0018] Based on the midpoint location information, the lane centerline of the target area is generated;

[0019] A map of the target area is generated based on the lane centerline.

[0020] Optionally, projecting the points to be projected to obtain the target projection point corresponding to each point to be projected includes:

[0021] If the first boundary line or the second boundary line is a curve, a boundary line node is determined, wherein the boundary line node is the point on the second boundary line that is closest to the point to be projected.

[0022] Connect the adjacent points of the boundary line nodes on the second boundary line to generate a first projection line;

[0023] The point to be projected is projected onto the first projection line to obtain the initial projection point corresponding to the point to be projected, and the initial projection point is located on the first projection line.

[0024] Connect the point to be projected and the initial projection point to obtain a connecting line;

[0025] The second intersection point of the connecting line and the second boundary line is taken as the target projection point.

[0026] Optionally, the step of projecting the points to be projected to obtain the target projection point corresponding to each point to be projected further includes:

[0027] If either the first boundary line or the second boundary line is a straight line, the point to be projected is projected onto the second boundary line to obtain the target projection point.

[0028] Optionally, the step of performing type identification on the target region to determine the region type of the target region includes:

[0029] Determine the endpoints of the lane boundaries within the target area;

[0030] Based on the endpoints of the boundary lines, a first connecting boundary line is determined, wherein the first connecting boundary line is a plurality of boundary lines connected to the endpoints of the boundary lines;

[0031] If the first connecting boundary line satisfies the first preset condition, the region type is determined to be the first type;

[0032] If the first connecting boundary line meets the second preset condition, the region type is determined to be the second type.

[0033] Optionally, when the area type is a first type, determining the associated lane centerlines within multiple adjacent areas of the target area includes:

[0034] When the area type is the first type, a target reference line corresponding to the first connecting boundary line is determined based on the first connecting boundary line and the first association relationship. The first association relationship represents the correspondence between the reference line and the boundary line, and the reference line indicates the driving direction of the lane where the boundary line is located.

[0035] Based on the target reference line, determine the target lane boundary line within the target area;

[0036] Based on the target lane boundary line and the first preset topological relationship, a second connecting boundary line of the target lane boundary line is determined. The second connecting boundary line is located in the adjacent area, and the first preset topological relationship represents the connection relationship between the boundary lines.

[0037] Based on the second connecting boundary line and the second association relationship, the center line of the associated lane is determined, wherein the second association relationship represents the correspondence between the boundary line and the center line;

[0038] Accordingly, generating a map of the target area based on the lane centerline includes:

[0039] Based on the lane centerline, the target lane boundary line, the target reference line, and preset topological relationships and preset association relationships, a map of the target area is generated. The preset topological relationships represent the connection relationships between lane lines, and the preset association relationships represent the road relationships of various lane lines.

[0040] Optionally, determining the first connecting boundary line based on the endpoints of the boundary line includes:

[0041] Based on the endpoints of the boundary line and the second preset topological relationship, a first connecting boundary line is determined, and the second preset topological relationship represents the connection relationship between the boundary line and the endpoints.

[0042] According to another aspect of the disclosed embodiments of the present invention, a data processing apparatus is provided, comprising:

[0043] The region type determination module is used to identify the type of the target region and determine the region type of the target region;

[0044] The associated lane centerline determination module is used to determine the associated lane centerlines in multiple adjacent areas of the target area when the area type is a first type.

[0045] The first intersection point determination module is used to determine multiple first intersection points between the center lines of multiple associated lanes and the target area;

[0046] The vector generation module is used to generate a vector corresponding to each first intersection point based on the plurality of first intersection points and centerline nodes, wherein the centerline node is the point on the centerline of the associated lane that is closest to the plurality of first intersection points;

[0047] A control point generation module is used to generate control points corresponding to the target intersection pair by extending the vector corresponding to the target intersection pair. The target intersection pair is two first intersection points located in any two adjacent regions, and the control point is the endpoint of the extended vector corresponding to the target intersection pair.

[0048] The first lane centerline generation module is used to perform curve fitting based on the target intersection pair and the control point to generate the lane centerline within the target area;

[0049] The first map generation module is used to generate a map of the target area based on the lane centerline.

[0050] According to another aspect of the embodiments disclosed in this invention, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the data processing method as described in any of the preceding claims.

[0051] According to another aspect of the disclosed embodiments of the present invention, a computer-readable storage medium is provided, wherein when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the data processing method according to any one of the disclosed embodiments of the present invention.

[0052] According to another aspect of the disclosed embodiments of the present invention, a computer program product containing instructions is provided, which, when run on a computer, causes the computer to perform the data processing method described in any one of the disclosed embodiments of the present invention.

[0053] The technical solutions provided by the embodiments disclosed in this invention bring at least the following beneficial effects:

[0054] The data processing method provided by this invention, when the target area is of the first type, determines the center lines of the associated lanes in adjacent areas and the intersection points of the associated lane center lines with the target area. Based on the intersection points and the point closest to the intersection points of the associated lane center lines, a vector corresponding to the intersection points is generated. Based on the two intersection points in any two adjacent areas, the corresponding vectors are extended to generate control points. Then, based on the two intersection points and the corresponding control points, curve fitting is performed to generate the lane center lines in the target area. This makes the generated lane center lines smoother and more consistent with the actual road shape, ensuring the accuracy of the lane center lines. Furthermore, by combining the smoother and more accurate lane center lines, a map of the target area is generated, which can improve the effectiveness and generation efficiency of the generated map.

[0055] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0056] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the disclosure of this invention and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit the scope of this disclosure.

[0057] Figure 1 This is a flowchart illustrating a data processing method according to an exemplary embodiment;

[0058] Figure 2 This is a flowchart illustrating a method for determining a region type according to an exemplary embodiment;

[0059] Figure 3 This is a schematic diagram illustrating the generation of lane centerlines in a data processing method according to an exemplary embodiment;

[0060] Figure 4 This is a flowchart illustrating another data processing method according to an exemplary embodiment;

[0061] Figure 5 This is a flowchart illustrating a method for determining a target projection point according to an exemplary embodiment;

[0062] Figure 6 This is a schematic diagram illustrating a method for determining a target projection point according to an exemplary embodiment;

[0063] Figure 7 This is a block diagram of a data processing apparatus according to an exemplary embodiment;

[0064] Figure 8 This is a block diagram illustrating a terminal electronic device for data processing according to an exemplary embodiment;

[0065] Figure 9 This is a block diagram illustrating a server electronic device for data processing according to an exemplary embodiment. Detailed Implementation

[0066] To enable those skilled in the art to better understand the technical solutions disclosed in this invention, the technical solutions in the disclosed embodiments will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0067] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention disclosed herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0068] This invention provides a data processing method that can be applied to the generation of map data.

[0069] Figure 1 This is a flowchart illustrating a data processing method according to an exemplary embodiment, such as... Figure 1 As shown, the data processing method includes the following steps.

[0070] S101: Perform type identification on the target area to determine the area type of the target area.

[0071] In one specific embodiment, the target area can be the area where a map needs to be generated; the area type can include a first type and a second type. Specifically, the first type can include types such as intersection areas and interchange areas, and interchange areas can be areas where the number of lanes changes. The second type can be other area types besides intersection areas and interchange areas, such as straight-ahead areas, curve areas, etc.

[0072] In an optional embodiment, Figure 2 This is a flowchart illustrating a method for determining a region type according to an exemplary embodiment, such as... Figure 2 As shown, the step of identifying the type of the target region and determining the region type of the target region may include:

[0073] S201: Determine the endpoints of the boundary lines of the lanes within the target area.

[0074] In one specific embodiment, the boundary line endpoints can be the boundary line endpoints of multiple road segments in the lane, with each road segment having a corresponding boundary line endpoint.

[0075] In one specific embodiment, the lane boundary line can be obtained by processing road point cloud data collected by acquisition devices such as LiDAR.

[0076] S203: Determine the first connecting boundary line based on the endpoints of the boundary line.

[0077] In one specific embodiment, the first connecting boundary line can be multiple boundary lines connected to the endpoints of the boundary lines. Specifically, depending on the driving direction of the lane where the endpoint of the boundary line is located, the first connecting boundary line can include an entry boundary line and an exit boundary line. The entry boundary line can be the boundary line that enters the endpoint of the boundary line along the driving direction of the lane where the endpoint of the boundary line is located, and the exit boundary line can be the boundary line that exits the endpoint of the boundary line along the driving direction of the lane where the endpoint of the boundary line is located.

[0078] In an optional embodiment, determining the first connecting boundary line based on the boundary line endpoints may include:

[0079] The first connecting boundary line is determined based on the endpoints of the boundary line and the second preset topological relationship.

[0080] In one specific embodiment, the second preset topological relationship can characterize the connection relationship between the boundary line and the endpoint.

[0081] S205: If the first connecting boundary line satisfies the first preset condition, the region type is determined to be the first type.

[0082] In one specific embodiment, the first preset condition may be that the number of first connecting boundary lines at any boundary line endpoint meets a first preset quantity. Specifically, the first preset condition may be that the number of the aforementioned entering boundary lines or the aforementioned exiting boundary lines at any boundary line endpoint meets a first preset quantity. For example, the first preset quantity may be 2.

[0083] S207: If the first connecting boundary line satisfies the second preset condition, the region type is determined to be the second type.

[0084] In one specific embodiment, the first preset condition may be that the number of first connecting boundary lines at any boundary line endpoint satisfies the second preset quantity. Specifically, the first preset condition may be that the number of the aforementioned entering boundary lines and the number of the aforementioned exiting boundary lines at any boundary line endpoint both satisfy the second preset quantity. For example, the second preset quantity may be 1.

[0085] In the above embodiments, the number of connecting boundary lines at the endpoints of the boundary lines can quickly and accurately identify the type of road segment area. Furthermore, by adopting the corresponding lane centerline generation method for different area types, the accuracy and efficiency of subsequent lane centerline generation can be improved.

[0086] S103: When the area type is the first type, determine the associated lane center lines in multiple adjacent areas of the target area.

[0087] In one specific embodiment, the associated lane centerline can be the lane centerlines of multiple lanes in an adjacent area.

[0088] In an optional embodiment, when the area type is a first type, determining the associated lane centerlines within multiple adjacent areas of the target area may include:

[0089] When the region type is the first type, the target reference line corresponding to the first connecting boundary line is determined based on the first connecting boundary line and the first association relationship;

[0090] Based on the target reference line, determine the target lane boundary line within the target area;

[0091] Based on the target lane boundary line and the first preset topological relationship, determine the second connecting boundary line of the target lane boundary line;

[0092] Based on the second connecting boundary line and the second association relationship, the center line of the associated lane is determined.

[0093] In one specific embodiment, the first association relationship can characterize the correspondence between the reference line and the boundary line, wherein the reference line can indicate the driving direction of the lane where the corresponding boundary line is located.

[0094] In one specific embodiment, the target reference line can be a reference line for multiple road segments in the lane, with each road segment having a corresponding reference line, and the target lane boundary line can be multiple boundary lines corresponding to the target reference line within the target area.

[0095] In one specific embodiment, the first preset topological relationship can characterize the connection relationship between boundary lines. The second connecting boundary line is located in the aforementioned adjacent area. Specifically, the second connecting boundary line can be a boundary line connected to the target lane boundary line through two endpoints. According to the driving direction of the lane where the target lane boundary line is located, the second connecting boundary line can include a preceding boundary line and a succeeding boundary line. Specifically, the preceding boundary line can be the connecting boundary line before the target lane boundary line along the driving direction of the lane where the target lane boundary line is located, and the succeeding boundary line can be the connecting boundary line after the target lane boundary line along the driving direction of the lane where the target lane boundary line is located.

[0096] In one specific embodiment, the second association relationship can characterize the correspondence between the boundary line and the center line, and the associated lane center line can be the lane center line of the lane where the second connecting boundary line is located.

[0097] S105: Determine multiple first intersection points between the center lines of multiple associated lanes and the target area.

[0098] S107: Based on the multiple first intersection points and centerline nodes, generate a vector corresponding to each first intersection point.

[0099] In one specific embodiment, the centerline node can be the point on the centerline of the associated lane that is closest to multiple first intersection points. Specifically, the centerline node can be the endpoint of the centerline or the inflection point of the centerline. The starting point of the vector corresponding to each of the first intersection points can be the centerline node, and the ending point of the vector can be the first intersection point.

[0100] In one specific embodiment, the above vector can be represented as

[0101]

[0102] Where A1 represents the first intersection point, and A2 represents the centerline node corresponding to A1. This represents the vector from the origin of the coordinate system to the first intersection point. This represents the vector from the origin of the coordinate system to the node of the center line.

[0103] Specifically, the coordinate system mentioned above can be the Earth coordinate system.

[0104] S109: Extend the vector corresponding to the target intersection point pair based on the target intersection point pair to generate the control point corresponding to the target intersection point pair.

[0105] In one specific embodiment, the target intersection pair can be two first intersection points located in any two adjacent regions, and the control point can be the endpoint of the extended vector corresponding to the target intersection pair.

[0106] In one specific embodiment, the control point can be determined according to the following formula:

[0107]

[0108]

[0109] Where A1 and B1 represent the two first intersection points of a pair of target intersection points, and C1 represents the control point corresponding to the first intersection point A1. This represents the vector from the origin of the coordinate system to the control point. This represents the vector from the centerline node to the control point. This represents the straight-line distance between the two first intersection points of the target intersection point pair, and k represents the distance coefficient.

[0110] In one specific embodiment, the distance coefficient k can be set according to the actual application. Specifically, when the distance coefficient k is... Under these conditions, by combining the control points and target intersection points determined by the above methods, the generated curve has the most regular curvature and the smoothest shape.

[0111] S111: Based on the target intersection pair and the control point, perform curve fitting to generate the lane centerline within the target area.

[0112] In one specific embodiment, curve fitting based on the target intersection pair and control points can be performed by fitting a Bézier curve based on the target intersection pair and the two control points corresponding to the target intersection pair.

[0113] Specifically, the formula for a third-order Bézier curve can be expressed as follows:

[0114] B(t)=P0*(1-t) 3 +3*P1*t*(1-t) 2 +

[0115] 3*P2*t 2 *(1-t)+P3*t 3 ,t∈[0,1]

[0116] Where P0 represents the starting point of the curve, P1 and P2 represent two control points, P3 represents the ending point of the curve, and t represents the curve length ratio.

[0117] Specifically, the starting point and ending point of the curve can be the two first intersection points of the aforementioned target intersection point pair.

[0118] In one specific embodiment, the curve length ratio t can be set according to the actual application. Specifically, when the curve length ratio t is 0.01, the generated third-order Bézier curve has the optimal point density.

[0119] like Figure 3 The diagram illustrates a data processing method for generating lane centerlines. A1 and B1 are a pair of target intersection points, representing the two first intersection points of target region A with the associated lane lines in adjacent regions B and C, respectively. A1 and A2 are located on the same associated lane centerline in adjacent region B, with A2 being the centerline node corresponding to A1 on that associated lane centerline. Similarly, B1 and B2 are located on the same associated lane centerline in adjacent region C, with B2 being the centerline node corresponding to B1 on that associated lane centerline. Control point C1 is the endpoint of the extended vector A2A1, and control point C2 is the endpoint of the extended vector B2B1. Based on the target intersection point pair A1 and B1 and their corresponding control points C1 and C2, a third-order Bézier curve is fitted to generate a lane centerline for the target region. Figure 3 The middle part is curve A1B1.

[0120] In the above embodiments, the control points of the Bézier curve are generated based on the straight-line distance between the intersection points of two adjacent regions and the vectors corresponding to the intersection points. This enables the generated curves to have smooth curvature and slope, conforming to the actual road shape and ensuring the accuracy of lane centerline generation. Furthermore, the automatic generation of lane centerlines in complex road areas such as intersections and interchanges is achieved based on vector calculation and curve fitting, improving the efficiency of lane centerline generation.

[0121] S113: Generate a map of the target area based on the lane centerline.

[0122] In an optional embodiment, generating a map of the target area based on the lane centerline may include:

[0123] A map of the target area is generated based on the lane centerline, the target lane boundary line, the target reference line, and preset topological and association relationships.

[0124] In one specific embodiment, a preset topology relationship can characterize the connection relationship between lane lines, and a preset association relationship can characterize the road relationship where multiple lane lines are located.

[0125] In an optional embodiment, Figure 4 This is a flowchart illustrating another data processing method according to an exemplary embodiment, such as... Figure 4As shown, the above method includes:

[0126] S401: Perform type identification on the target area to determine the area type of the target area.

[0127] In one specific embodiment, the detailed steps for identifying the type of the target region and determining the region type of the target region can be found in the foregoing detailed description, and will not be repeated here.

[0128] S403: If the region type is the second type, determine the point to be projected within the target region.

[0129] In one specific embodiment, the point to be projected can be a point on the boundary line. Specifically, the point to be projected can be the endpoint of the boundary line and the inflection point of the boundary line.

[0130] S405: Project the points to be projected to obtain the target projection point corresponding to each point to be projected.

[0131] In one specific embodiment, the point to be projected is located on the first boundary line, and the target projection point is located on the second boundary line. The first boundary line and the second boundary line are the two boundary lines of the same lane.

[0132] In an optional embodiment, Figure 5 This is a flowchart illustrating a method for determining a target projection point according to an exemplary embodiment, such as... Figure 5 As shown, projecting the points to be projected to obtain the target projection point corresponding to each point to be projected may include:

[0133] S501: If the first boundary line or the second boundary line is a curve, determine the boundary line node.

[0134] In one specific embodiment, the boundary line node can be the point on the second boundary line that is closest to the point to be projected. Specifically, the boundary line node can be the endpoint of the boundary line or the inflection point of the boundary line.

[0135] S503: Connect the adjacent points of the boundary line node on the second boundary line to generate a first projection line.

[0136] In one specific embodiment, the first projection line can be a straight line connecting the aforementioned adjacent points.

[0137] In one specific embodiment, if a boundary line node has only one adjacent point on the second boundary line, the first projection line can be a straight line connecting the boundary line node and the adjacent point.

[0138] S505: Project the point to be projected onto the first projection line to obtain the initial projection point corresponding to the point to be projected.

[0139] In one specific embodiment, the initial projection point is located on the aforementioned first projection line. Specifically, the coordinate information of the initial projection point can be expressed as follows:

[0140] in,

[0141] Among them, (X) s ,Y s Z s () represents the coordinate information of the initial projection point, and (X0,Y0,Z0) and (X1,Y1,Z1) represent the coordinate information of the adjacent points mentioned above, respectively. t ,Y t Z t ) represents the coordinate information of the point to be projected, and k represents the slope of the first projection line mentioned above.

[0142] S507: Connect the point to be projected and the initial projection point to obtain a connecting line.

[0143] In one specific embodiment, the connecting line can be a straight line segment connecting the point to be projected and the initial projection point.

[0144] S509: The second intersection point of the connecting line and the second boundary line is taken as the target projection point.

[0145] like Figure 6 The diagram illustrates a method for determining a target projection point. The point to be projected is D, located on the first boundary line. The boundary line node is E, located on the second boundary line. The first and second boundary lines are the boundary lines of the same lane on both sides. Points adjacent to E on the second boundary line are F1 and F2. The initial projection point G is obtained by projecting the point D onto the straight line segment F1F2. The intersection point H of the straight line segment DG and the second boundary line is the target projection point of the point D on the second boundary line.

[0146] In an optional embodiment, the step of projecting the points to be projected to obtain the target projection point corresponding to each point to be projected may further include:

[0147] If either the first boundary line or the second boundary line is a straight line, the point to be projected is projected onto the second boundary line to obtain the target projection point.

[0148] In one specific embodiment, if the first boundary line or the second boundary line is a straight line, the target projection point will necessarily fall on the second boundary line.

[0149] S407: Determine the midpoint position information of the point to be projected and the target projection point.

[0150] In one specific embodiment, the midpoint position information can be the position information of the midpoint of the straight line segment connecting the point to be projected and its corresponding target projection point.

[0151] S409: Based on the midpoint position information, generate the lane centerline of the target area.

[0152] In one specific embodiment, generating the lane centerline of the target area based on the midpoint position information may include: based on the midpoint position information, sequentially connecting the midpoints of the point to be projected and its corresponding target projection point to obtain the lane centerline of the target area.

[0153] In the above embodiments, when the target area is not an intersection or exchange area and the lane boundary line is curved, the curve is divided into multiple straight line segments, and the curve projection point is determined based on the projection point on the straight line segment. This ensures that the midpoint of the line connecting the projection point to be projected and the corresponding curve projection point falls in the center of the lane. The generated lane center line is more in line with the actual road shape and better serves the driving of autonomous vehicles.

[0154] S411: Generate a map of the target area based on the lane centerline.

[0155] In one specific embodiment, the detailed steps for generating a map of the target area based on the lane centerline can be found in the foregoing detailed description, and will not be repeated here.

[0156] As can be seen from the technical solutions provided in the embodiments of this specification above, when the target area includes an intersection area or a transfer zone, this specification determines the associated lane centerlines in multiple adjacent areas of the target area, and the multiple intersection points of the associated lane centerlines with the target area. Based on the multiple intersection points and the point closest to the associated lane centerline and the intersection point, a vector corresponding to each intersection point is generated. Control points are generated by extending the corresponding vectors of any two intersection points in any two adjacent areas. Curve fitting is then performed based on the two intersection points and the corresponding control points to generate the lane centerlines within the target area. This results in smoother lane centerlines that better conform to the actual road shape, ensuring the accuracy of the lane centerlines. Furthermore, combining these smoother and more accurate lane centerlines with the generated map of the target area improves the effectiveness and efficiency of the generated map. Additionally, by controlling the number of boundary lines connecting the endpoints of the boundary lines, the type of road segment area can be quickly and accurately identified. Using corresponding lane centerline generation methods for different area types can improve the accuracy and efficiency of subsequent lane centerline generation. Furthermore, when the target area is not an intersection or interchange and the lane boundary line is curved, the curve is divided into multiple straight line segments. Based on the projection points on the straight line segments, the curve projection points are determined, ensuring that the midpoint of the straight line between the projection point and the corresponding projection point falls at the geometric center of the lane. The generated lane center line is more in line with the actual road shape and better serves the driving of autonomous vehicles.

[0157] Figure 7 This is a block diagram of a data processing apparatus according to an exemplary embodiment. (Refer to...) Figure 7 The device may include:

[0158] The region type determination module 710 is used to identify the type of the target region and determine the region type of the target region.

[0159] The associated lane centerline determination module 720 is used to determine the associated lane centerlines in multiple adjacent areas of the target area when the area type is a first type.

[0160] The first intersection point determination module 730 is used to determine multiple first intersection points between multiple associated lane centerlines and the target area;

[0161] The vector generation module 740 is used to generate a vector corresponding to each first intersection point based on the plurality of first intersection points and centerline nodes, wherein the centerline node is the point on the centerline of the associated lane that is closest to the plurality of first intersection points;

[0162] The control point generation module 750 is used to generate control points corresponding to the target intersection pair by extending the vector corresponding to the target intersection pair. The target intersection pair is two first intersection points located in any two adjacent regions, and the control point is the endpoint of the extended vector corresponding to the target intersection pair.

[0163] The first lane centerline generation module 760 is used to perform curve fitting based on the target intersection pair and the control point to generate the lane centerline within the target area.

[0164] The first map generation module 770 is used to generate a map of the target area based on the lane centerline.

[0165] Optionally, the device may further include:

[0166] The region type determination module is used to identify the type of the target region and determine the region type of the target region;

[0167] The projection point determination module is used to determine the projection point within the target area when the area type is the second type.

[0168] The target projection point determination module is used to project the point to be projected to obtain the target projection point corresponding to each point to be projected. The point to be projected is located on the first boundary line, and the target projection point is located on the second boundary line. The first boundary line and the second boundary line are the two boundary lines of the same lane.

[0169] The midpoint position information determination module is used to determine the midpoint position information of the point to be projected and the target projection point;

[0170] The second lane centerline generation module is used to generate the lane centerline of the target area based on the midpoint position information.

[0171] The second map generation module is used to generate a map of the target area based on the lane centerline.

[0172] Optionally, the target projection point determination module may include:

[0173] A boundary line node determination unit is used to determine boundary line nodes when the first boundary line or the second boundary line is a curve, wherein the boundary line node is the point on the second boundary line that is closest to the point to be projected;

[0174] The first projection line generation unit is used to connect the adjacent points of the boundary line node on the second boundary line to generate the first projection line;

[0175] An initial projection point determination unit is used to project the point to be projected onto the first projection line to obtain an initial projection point corresponding to the point to be projected, wherein the initial projection point is located on the first projection line.

[0176] A connecting line determining unit is used to connect the point to be projected and the initial projection point to obtain a connecting line;

[0177] The first target projection point determination unit is used to determine the second intersection point of the connecting line and the second boundary line as the target projection point.

[0178] Optionally, the target projection point determination module may also include:

[0179] The second target projection point determination unit is used to project the point to be projected onto the second boundary line when the first boundary line or the second boundary line is a straight line, so as to obtain the target projection point.

[0180] Optionally, the region type determination module 710 may include:

[0181] Boundary line endpoint determination unit, used to determine the boundary line endpoints of lanes within the target area;

[0182] The first connecting boundary line determining unit is used to determine a first connecting boundary line based on the endpoints of the boundary line, wherein the first connecting boundary line is a plurality of boundary lines connected to the endpoints of the boundary line;

[0183] The first type determination unit is used to determine the region type as the first type when the first connecting boundary line meets the first preset condition;

[0184] The second type determination unit is used to determine the region type as the second type when the first connecting boundary line meets the second preset condition.

[0185] Optionally, the associated lane centerline determination module 720 may include:

[0186] The target reference line determination unit is used to determine the target reference line corresponding to the first connecting boundary line based on the first connecting boundary line and the first association relationship when the area type is the first type. The first association relationship represents the correspondence between the reference line and the boundary line, and the reference line indicates the driving direction of the lane where the boundary line is located.

[0187] The target lane boundary line determination unit is used to determine the target lane boundary line within the target area based on the target reference line.

[0188] The second connecting boundary line determination unit is used to determine the second connecting boundary line of the target lane boundary line based on the target lane boundary line and the first preset topological relationship. The second connecting boundary line is located in the adjacent area, and the first preset topological relationship represents the connection relationship between the boundary lines.

[0189] The associated lane centerline determination unit is used to determine the associated lane centerline based on the second connecting boundary line and the second association relationship, wherein the second association relationship represents the correspondence between the boundary line and the centerline;

[0190] Accordingly, the first lane centerline generation module 760 may include:

[0191] The first lane centerline generation unit is used to generate a map of the target area based on the lane centerline, the target lane boundary line, the target reference line, and preset topological relationships and preset association relationships. The preset topological relationships represent the connection relationships between lane lines, and the preset association relationships represent the road relationships of various lane lines.

[0192] Optionally, the first connection boundary line determining unit may include:

[0193] The boundary line endpoint topology boundary line determination unit is used to determine a first connecting boundary line based on the boundary line endpoints and a second preset topology relationship, wherein the second preset topology relationship characterizes the connection relationship between the boundary line and the endpoints.

[0194] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0195] Figure 8 This is a block diagram illustrating an electronic device for data processing according to an exemplary embodiment. The electronic device may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown, the electronic device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a data processing method. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0196] Figure 9 This is a block diagram illustrating an electronic device for data processing according to an exemplary embodiment. The electronic device may be a server, and its internal structure diagram may be as follows: Figure 9 As shown, this electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a data processing method.

[0197] Those skilled in the art will understand that Figure 8 or Figure 9 The structures shown are merely block diagrams of some structures related to the disclosed solutions of this invention, and do not constitute a limitation on the electronic devices to which the disclosed solutions of this invention are applied. Specific electronic devices may include more or fewer components than those shown in the figures, or combine certain components, or have different component arrangements.

[0198] In an exemplary embodiment, an electronic device is also provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement a data processing method as disclosed in the embodiments of the present invention.

[0199] In an exemplary embodiment, a computer-readable storage medium is also provided, wherein when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the data processing method disclosed in this invention.

[0200] In an exemplary embodiment, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform the data processing method disclosed in this invention.

[0201] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), and double data rate RAM.

[0202] SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus Direct RAM (RDRAM), Direct Memory Bus Dynamic RAM (DRDRAM), and Memory Bus Dynamic RAM (RDRAM), etc.

[0203] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles disclosed herein and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0204] It should be understood that the present invention is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

Claims

1. A data processing method, characterized in that, include: The target area is identified by type recognition to determine the area type of the target area, including: determining the boundary line endpoints of the lanes within the target area; determining a first connecting boundary line based on the boundary line endpoints, wherein the first connecting boundary line is a plurality of boundary lines connected to the boundary line endpoints; determining the area type as a first type if the first connecting boundary line meets a first preset condition; and determining the area type as a second type if the first connecting boundary line meets a second preset condition. When the area type is the first type, determine the associated lane centerlines in multiple adjacent areas of the target area; Determine multiple first intersection points between the centerlines of multiple associated lanes and the target area; Based on the plurality of first intersection points and centerline nodes, a vector is generated corresponding to each first intersection point, wherein the centerline node is the point on the centerline of the associated lane that is closest to the plurality of first intersection points; Based on the target intersection point pair, extend the vector corresponding to the target intersection point pair to generate the control point corresponding to the target intersection point pair. The target intersection point pair is two first intersection points located in any two adjacent regions, and the control point is the endpoint of the extended vector corresponding to the target intersection point pair. Based on the target intersection points and the control points, curve fitting is performed to generate the lane centerline within the target area; A map of the target area is generated based on the lane centerline.

2. A data processing method, characterized in that, include: The target area is identified by type recognition to determine the area type of the target area, including: determining the boundary line endpoints of the lanes within the target area; determining a first connecting boundary line based on the boundary line endpoints, wherein the first connecting boundary line is a plurality of boundary lines connected to the boundary line endpoints; determining the area type as a first type if the first connecting boundary line meets a first preset condition; and determining the area type as a second type if the first connecting boundary line meets a second preset condition. If the region type is the second type, determine the points to be projected within the target region; The points to be projected are projected to obtain target projection points corresponding to each point to be projected. The points to be projected are located on the first boundary line and the target projection points are located on the second boundary line. The first boundary line and the second boundary line are the two boundary lines of the same lane. Determine the midpoint position information of the point to be projected and the target projection point; Based on the midpoint position information, the lane centerline of the target area is generated; A map of the target area is generated based on the lane centerline; The step of projecting the points to be projected to obtain target projection points for each point includes: when the first boundary line or the second boundary line is a curve, determining boundary line nodes, where the boundary line node is the point on the second boundary line closest to the point to be projected; connecting the adjacent points of the boundary line node on the second boundary line to generate a first projection line; projecting the point to be projected onto the first projection line to obtain an initial projection point corresponding to the point to be projected, where the initial projection point is located on the first projection line; connecting the point to be projected and the initial projection point to obtain a connecting line; and taking the second intersection of the connecting line and the second boundary line as the target projection point.

3. The data processing method according to claim 2, characterized in that, The step of projecting the points to be projected to obtain the target projection points corresponding to each point to be projected includes: If either the first boundary line or the second boundary line is a straight line, the point to be projected is projected onto the second boundary line to obtain the target projection point.

4. The data processing method according to claim 1, characterized in that, When the area type is the first type, determining the associated lane centerlines within multiple adjacent areas of the target area includes: When the area type is the first type, a target reference line corresponding to the first connecting boundary line is determined based on the first connecting boundary line and the first association relationship. The first association relationship represents the correspondence between the reference line and the boundary line, and the reference line indicates the driving direction of the lane where the boundary line is located. Based on the target reference line, determine the target lane boundary line within the target area; Based on the target lane boundary line and the first preset topological relationship, a second connecting boundary line of the target lane boundary line is determined. The second connecting boundary line is located in the adjacent area. The first preset topological relationship represents the connection relationship between the boundary lines. Based on the second connecting boundary line and the second association relationship, the center line of the associated lane is determined, wherein the second association relationship represents the correspondence between the boundary line and the center line; The process of generating a map of the target area based on the lane centerline includes: Based on the lane centerline, the target lane boundary line, the target reference line, and preset topological relationships and preset association relationships, a map of the target area is generated. The preset topological relationships represent the connection relationships between lane lines, and the preset association relationships represent the road relationships of various lane lines.

5. A data processing method according to claim 1 or 2, characterized in that, Determining the first connecting boundary line based on the endpoints of the boundary line includes: Based on the endpoints of the boundary line and the second preset topological relationship, the first connecting boundary line is determined, and the second preset topological relationship represents the connection relationship between the boundary line and the endpoints.

6. A data processing apparatus, characterized in that, include: The region type determination module is used to identify the type of the target region and determine the region type of the target region; The associated lane centerline determination module is used to determine the associated lane centerlines in multiple adjacent areas of the target area when the area type is a first type. The first intersection point determination module is used to determine multiple first intersection points between the center lines of multiple associated lanes and the target area; The vector generation module is used to generate a vector corresponding to each first intersection point based on the plurality of first intersection points and centerline nodes, wherein the centerline node is the point on the centerline of the associated lane that is closest to the plurality of first intersection points; A control point generation module is used to generate control points corresponding to the target intersection pair by extending the vector corresponding to the target intersection pair. The target intersection pair is two first intersection points located in any two adjacent regions, and the control point is the endpoint of the extended vector corresponding to the target intersection pair. The first lane centerline generation module is used to perform curve fitting based on the target intersection pair and the control point to generate the lane centerline within the target area; The first map generation module is used to generate a map of the target area based on the lane centerline; The region type determination module includes: Boundary line endpoint determination unit, used to determine the boundary line endpoints of lanes within the target area; The first connecting boundary line determining unit is used to determine a first connecting boundary line based on the endpoints of the boundary line, wherein the first connecting boundary line is a plurality of boundary lines connected to the endpoints of the boundary line; The first type determination unit is used to determine the region type as the first type when the first connecting boundary line meets the first preset condition; The second type determination unit is used to determine the region type as the second type when the first connecting boundary line meets the second preset condition.

7. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the data processing method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform the data processing method as described in any one of claims 1 to 5.

Images