Lane line data association method and device, equipment and storage medium

Abstract

The invention relates to the technical field of vehicle positioning, and discloses a lane line data association method and device, equipment and a storage medium, and the method comprises the steps: obtaining a map lane line set and a perception lane line set; determining a map lane line number and a sensing lane line number according to the map lane line set and the sensing lane line set; and determining an association result of the map lane line and the sensing lane line according to the map lane line number and the sensing lane line number. According to the invention, the efficiency and accuracy of association between the perception lane line and the map lane line can be effectively improved, so that the precision and availability of lane line matching and positioning are improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle positioning technology, and in particular to a lane line data association method, device, equipment and storage medium. Background Art

[0002] With the continuous development of autonomous driving technology, NOA's intelligent driving function is gradually being recognized by the industry and users, and will become an important competitive advantage for car companies in the next stage. In NOA's intelligent driving system, positioning technology is very important, and the matching positioning of perception and map is the most core part of NOA positioning. In matching positioning, the association between perception and lane line data on the map is the most critical. In the current positioning method, when the initial value of vehicle positioning is inaccurate, the perception will be converted to the map coordinate system through this initial value, which will lead to incorrect association of lane lines, resulting in poor efficiency and accuracy in the association between perception lane lines and map lane lines.

[0003] Therefore, how to effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines, thereby improving the accuracy and availability of lane line matching and positioning, is a problem that needs to be solved urgently.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a lane line data association method, device, equipment and storage medium, aiming to solve the technical problem of how to effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines, thereby improving the accuracy and availability of lane line matching and positioning.

[0006] To achieve the above purpose, the present application proposes a lane line data association method, the method comprising:

[0007] Get the map lane line set and the perception lane line set;

[0008] Determine a map lane line number and a sensed lane line number according to the map lane line set and the sensed lane line set;

[0009] The association result between the map lane line and the perceived lane line is determined according to the map lane line number and the perceived lane line number.

[0010] In one embodiment, the determining the map lane line number and the perception lane line number according to the map lane line set and the perception lane line set includes:

[0011] Determine a first lateral distance between the vehicle and a target map lane line according to the map lane line set, and determine a second lateral distance between the vehicle and a target sensed lane line according to the sensed lane line set;

[0012] Sorting the map lane lines according to the first lateral distance to obtain a first position relationship, and sorting the sensed lane lines according to the second lateral distance to obtain a second position relationship;

[0013] The map lane line number is determined based on the first position relationship, and the perceived lane line number is determined based on the second position relationship.

[0014] In one embodiment, determining a first lateral distance between the vehicle and a target map lane line according to the map lane line set includes:

[0015] Determine a target map lane line based on the map lane line set;

[0016] Obtaining the coordinates of the vehicle in the map coordinate system, and determining the normal distance between the vehicle and the lane line of the target map according to the coordinates of the vehicle in the map coordinate system;

[0017] A first lateral distance between the vehicle and the lane line of the target map is determined according to the normal distance.

[0018] In one embodiment, determining the map lane line number according to the first position relationship includes:

[0019] Determine the adjacent map lane line of the target map lane line according to the first position relationship;

[0020] Obtaining the relative distance between the target map lane line and the adjacent map lane line;

[0021] The map lane lines in the map lane line set are numbered according to the first positional relationship and the relative distance to obtain map lane line numbers.

[0022] In one embodiment, determining the association result between the map lane line and the sensed lane line according to the map lane line number and the sensed lane line number includes:

[0023] Get the number of map lane lines and the number of perceived lane lines;

[0024] Determine an association result between a map lane line and a perceived lane line based on at least one of the number of map lane lines, the number of perceived lane lines, the map lane line number, and the perceived lane line number.

[0025] In one embodiment, determining the association result between the map lane line and the perceived lane line according to at least one of the number of the map lane lines, the number of the perceived lane lines, the map lane line number, and the perceived lane line number includes:

[0026] Determining, based on at least one of the number of map lane lines, the number of sensed lane lines, the number of map lane lines, and the number of sensed lane lines, that the association result between the map lane line and the sensed lane line is that there is no valid association relationship;

[0027] The association result between the map lane line and the perceived lane line is determined based on the map lane line number and the perceived lane line number to be a valid association relationship.

[0028] In one embodiment, the determining, based on the map lane line number and the sensed lane line number, that the association result between the map lane line and the sensed lane line is a valid association relationship, includes:

[0029] Determine a first number deviation and a second number deviation according to the map lane line number and the sensed lane line number;

[0030] Determine a target deviation according to the first number deviation and the second number deviation;

[0031] When the sum of the perceived lane line number and the target deviation is equal to the map lane line number and the perceived lane line type is consistent with the map lane line type, it is determined that the association result between the map lane line and the perceived lane line is that a valid association relationship exists.

[0032] In addition, to achieve the above purpose, the present application also proposes a lane line data association device, the lane line data association device comprising:

[0033] An acquisition module is used to acquire a map lane line set and a perception lane line set;

[0034] A determination module, used to determine a map lane line number and a sensed lane line number according to the map lane line set and the sensed lane line set;

[0035] The determination module is further used to determine the association result between the map lane line and the perceived lane line according to the map lane line number and the perceived lane line number.

[0036] In addition, to achieve the above-mentioned purpose, the present application also proposes a lane line data association device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the lane line data association method described above.

[0037] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the lane line data association method described above are implemented.

[0038] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the lane line data association method described above are implemented.

[0039] The present application provides a lane line data association method, which can effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines by first obtaining a map lane line set and a perceived lane line set; determining a map lane line number and a perceived lane line number based on the map lane line set and the perceived lane line set; and determining an association result between map lane lines and perceived lane lines based on the map lane line number and the perceived lane line number, thereby improving the accuracy and availability of lane line matching and positioning.

[0040] In summary, the present application numbers the map lane lines and the perceived lane lines, and can accurately determine the relative distance of the lane lines based on the map lane line numbers and the perceived lane line numbers, and then quickly and accurately determine the association results between the map lane lines and the perceived lane lines, thereby overcoming the technical defects of poor efficiency and accuracy in the association between the perceived lane lines and the map lane lines, and can effectively improve the efficiency and accuracy of the association between the perceived lane lines and the map lane lines, thereby improving the accuracy and availability of lane line matching and positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0043] Figure 1 A flowchart of the first embodiment of the lane line data association method of the present application is provided;

[0044] Figure 2 A flowchart diagram of the second embodiment of the lane line data association method of the present application is provided;

[0045] Figure 3This is a schematic diagram of the module structure of the lane line data association device according to an embodiment of the present application;

[0046] Figure 4 A schematic diagram of the device structure of the hardware operating environment involved in the lane line data association method of an embodiment of the present application.

[0047] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0048] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0049] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0050] The main solution of the embodiment of the present application is: obtain a map lane line set and a perception lane line set; determine the map lane line number and the perception lane line number based on the map lane line set and the perception lane line set; determine the association result between the map lane line and the perception lane line based on the map lane line number and the perception lane line number.

[0051] With the continuous development of autonomous driving technology, NOA's intelligent driving function is gradually being recognized by the industry and users, and will become an important competitive advantage for car companies in the next stage. In NOA's intelligent driving system, positioning technology is very important, and the matching positioning of perception and map is the core part of NOA positioning. In matching positioning, the association between perception and lane line data of the map is the most critical. In the current positioning method, when the initial value of vehicle positioning is inaccurate, when the perception is converted to the map coordinate system through this initial value, it will cause the lane line to be incorrectly associated, resulting in poor efficiency and accuracy in the association between the perceived lane line and the map lane line. Therefore, how to effectively improve the efficiency and accuracy of the association between the perceived lane line and the map lane line, thereby improving the accuracy and availability of lane line matching positioning, is a problem that needs to be solved urgently.

[0052] The present application numbers map lane lines and perceived lane lines, and can accurately determine the relative distance of lane lines based on the map lane line numbers and the perceived lane line numbers, and then quickly and accurately determine the association results between map lane lines and perceived lane lines, thereby overcoming the technical defects of poor efficiency and accuracy in the association between perceived lane lines and map lane lines, and can effectively improve the efficiency and accuracy of the association between perceived lane lines and map lane lines, thereby improving the accuracy and availability of lane line matching and positioning.

[0053] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a lane line data association device, etc. The following takes the lane line data association device as an example to illustrate this embodiment and the following embodiments.

[0054] Based on this, the embodiment of the present application provides a lane line data association method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the lane line data association method of the present application.

[0055] In this embodiment, the lane line data association method includes steps S10 to S30:

[0056] Step S10, obtaining a map lane line set and a sensed lane line set.

[0057] It should be noted that the map lane line refers to the lane line information pre-defined in the electronic map or high-precision map, which contains static data such as the road geometry, lane direction, number of lanes, etc. The perceived lane line is the lane line information perceived in real time by the sensors (such as lidar, camera, etc.) on the vehicle, which reflects the lane layout in the vehicle's current driving environment.

[0058] It is understandable that the geometry of lane lines in the map is expressed as an ordered set of points, i.e., the map lane line set. The perceived lane line is generally a cubic equation (y=c0+c1*x+c2*x^2+c3*x^3). Using the equation sampling point set, the geometry of the perceived line is also expressed as an ordered set of points, i.e., the perceived lane line set.

[0059] Step S20, determining the map lane line number and the perception lane line number according to the map lane line set and the perception lane line set.

[0060] It should be noted that each lane line in the map lane line set is traversed and assigned a unique number based on its position, direction and relative relationship with other lane lines in the map. This number should be able to clearly reflect the position and attributes of the lane line in the map to facilitate subsequent processing and matching. The perception lane line set also needs to be numbered.

[0061] It can be understood that based on the map lane line number and the perceived lane line number, a preset association algorithm is used to associate the lane line data, such as a matching algorithm based on spatial position, direction, shape and other features, to match the map lane line number and the perceived lane line number to find the best matching pair between the two, that is, to find the map lane line that is closest to the perceived lane line in terms of position, direction, shape, etc. Through matching, the association relationship between the map lane line and the perceived lane line can be established, providing a basis for subsequent lane line matching and positioning.

[0062] In a feasible implementation, step S20 may include: determining a first lateral distance between the vehicle and the target map lane line based on the map lane line set, and determining a second lateral distance between the vehicle and the target perceived lane line based on the perceived lane line set; sorting the map lane lines according to the first lateral distance to obtain a first position relationship, and sorting the perceived lane lines according to the second lateral distance to obtain a second position relationship; determining the map lane line number based on the first position relationship, and determining the perceived lane line number based on the second position relationship.

[0063] It should be noted that the first lateral distance is the lateral distance between the ego vehicle and the target map lane line, which represents the horizontal offset between the ego vehicle's current position in the map coordinate system and the target map lane line. This distance is calculated based on the coordinates of the ego vehicle on the map and the coordinates of the center line of the target map lane line, and is obtained through geometric calculation. Similarly, the second lateral distance is the lateral distance between the ego vehicle and the target perceived lane line, which is the horizontal offset between the ego vehicle's position and the target perceived lane line perceived in real time by the sensors on the vehicle.

[0064] It can be understood that after determining these two lateral distances, the first lateral distance between the ego vehicle and the target map lane line is used to sort the lines in the map lane line set left and right (the distance here is positive and negative, positive on the left and negative on the right, that is, sorting from right to left), and the first position relationship can be obtained. Similarly, the second lateral distance between the ego vehicle and the target perceived lane line is used to sort the lines in the perceived lane line set left and right (the distance here is also positive and negative, positive on the left and negative on the right, that is, sorting from right to left), and the second position relationship can be obtained. This sorting method can intuitively reflect the position of the lane line relative to the ego vehicle, and provides a basis for the subsequent lane line numbering.

[0065] It is worth noting that both the first position relationship and the second position relationship are based on a coordinate system centered on the vehicle. This processing method with the vehicle as the reference point simplifies the complexity of the lane line numbering, so that the numbering can directly reflect the relative position relationship between the lane line and the vehicle.

[0066] In a feasible implementation, determining the first lateral distance between the vehicle and the target map lane line based on the map lane line set includes: determining the target map lane line based on the map lane line set; obtaining the coordinates of the vehicle in the map coordinate system, and determining the normal distance between the vehicle and the target map lane line based on the coordinates of the vehicle in the map coordinate system; and determining the first lateral distance between the vehicle and the target map lane line based on the normal distance.

[0067] It should be noted that the target map lane line is a line segment formed by the two points closest to the vehicle's position in the map lane line set. This line segment represents the lane the vehicle is currently traveling or about to travel in. After determining the target map lane line, it is necessary to clarify the specific position of the vehicle in the map coordinate system. This position is usually obtained through the vehicle's GPS system or map positioning function. Next, calculate the normal distance between the vehicle and the target map lane line, that is, the shortest distance perpendicular to the center line of the lane line and pointing in the direction of the vehicle. The calculation of this normal distance can be achieved through vector operations. Specifically, the vehicle position is represented as a point in the map coordinate system, the center line of the target map lane line is represented as a series of points or linear equations, and then the vertical distance from the vehicle point to the center line of the lane line is solved.

[0068] It is understandable that after obtaining the normal distance, the first lateral distance can be further determined according to the vehicle's driving direction (such as the direction of the vehicle's head). If the normal distance is a positive number, it means that the vehicle is on the right side of the lane line; if it is a negative number, it means that the vehicle is on the left side of the lane line. The absolute value of the first lateral distance is the horizontal offset between the vehicle and the lane line of the target map. The determination of this value is crucial for the subsequent lane line numbering and matching.

[0069] It is worth noting that in the perception lane line set, the second lateral distance between the ego vehicle and the target perception lane line also needs to be determined. The calculation method of the second lateral distance is the same as the first lateral distance. The target perception lane line that is most relevant to the current driving state of the ego vehicle is identified from the perception lane line set. This target lane line is usually the lane line that is most consistent with the driving direction of the ego vehicle and is in front of the vehicle or on the current driving path. After determining the target perception lane line, the sensor data is used to calculate the normal distance between the ego vehicle and the target perception lane line. This process is similar to calculating the normal distance between the ego vehicle and the target map lane line, but the data sources are different. The former depends on the map data, and the latter depends on the real-time perception data. Through the position information and lane line contours in the sensor data, a mathematical model of the perception lane line (such as a polynomial curve, a spline curve, etc.) can be constructed, and then the vertical distance from the ego vehicle to the center line of the lane line, that is, the normal distance, can be calculated. Similarly, according to the sign (positive or negative) and absolute value of the normal distance, the second lateral distance between the ego vehicle and the target perception lane line can be determined. A positive value indicates that the ego vehicle is on the right side of the lane line, and a negative value indicates that the ego vehicle is on the left side of the lane line. The absolute value of the second lateral distance reflects the actual horizontal offset between the vehicle and the target perceived lane line. This information is also crucial for subsequent lane line matching and positioning.

[0070] After obtaining the first lateral distance and the second lateral distance, the map lane lines and the perceived lane lines are sorted from right to left (or from left to right, depending on the specific implementation and preference) to establish their respective lane line position relationships. This sorting method not only simplifies the complexity of lane line numbering, but also enables the numbering to directly reflect the relative position relationship between the lane line and the vehicle, providing a more intuitive and accurate basis for subsequent lane line matching and positioning.

[0071] In a feasible implementation manner, determining the map lane line number based on the first position relationship includes: determining the adjacent map lane line of the target map lane line based on the first position relationship; obtaining the relative distance between the target map lane line and the adjacent map lane line; and numbering the map lane lines in the map lane line set based on the first position relationship and the relative distance to obtain the map lane line number.

[0072] It should be noted that the first positional relationship is the left-right relationship of the map lane lines. The map lane lines are numbered according to the left-right relationship of the map lane lines and the relative distances between the adjacent map lane lines to obtain the map lane line number map_ind.

[0073] It can be understood that after completing the map lane line numbering, it is determined whether the distance between two adjacent map lane lines meets the standard width. If it does, it is recorded as is_normal_width, and is_normal_width and map_ind are two attributes of the map lane line.

[0074] It is worth noting that the same processing is performed on the sensed lane lines, that is, the adjacent sensed lane lines of the target sensed lane lines are determined according to the second positional relationship, and the relative distance between the target sensed lane lines and the adjacent sensed lane lines is calculated. Subsequently, based on the second positional relationship and these relative distances, the lane lines in the sensed lane line set are numbered to obtain the sensed lane line number. The second positional relationship is the left-right relationship of the sensed lane lines. The sensed lane lines are sorted according to the left-right relationship of the sensed lane lines and the relative distances of the adjacent sensed lane lines, and the sensed lane line number sort_ind can be obtained.

[0075] Step S30, determining the association result between the map lane line and the sensed lane line according to the map lane line number and the sensed lane line number.

[0076] It should be noted that the association result between the map lane line and the sensed lane line refers to whether there is a valid association relationship between the diameters of the map lane line and the sensed lane line.

[0077] It can be understood that the association process specifically involves the following sub-steps. First, by comparing the map lane line number map_ind with the perceived lane line number sort_ind, the candidate pairs that may correspond to each other are preliminarily screened out. An efficient matching algorithm, such as a quick search based on a hash table or an optimal matching algorithm based on dynamic programming, can be used to reduce the number of unnecessary comparisons and improve matching efficiency. Then, for each pair of candidate map lane lines and perceived lane lines, their attribute characteristics are further analyzed, including but not limited to the lane line's geometry, direction, length, width, lane line type (such as dotted line, solid line, double yellow line, etc.) and the relative position relationship between them, so as to confirm whether the two lane lines are associated.

[0078] In the specific implementation, based on the relative position relationship of the lane lines, the lane line type and the lane line spacing, it is possible to quickly and accurately determine whether there is an effective correlation between the map lane lines and the perceived lane line diameters, thereby effectively improving the efficiency and accuracy of the association between the perceived lane lines and the map lane lines, and further improving the accuracy and availability of lane line matching and positioning.

[0079] The present embodiment provides a lane line data association method, which can effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines, thereby improving the accuracy and availability of lane line matching and positioning, by first obtaining a map lane line set and a perceived lane line set; determining a map lane line number and a perceived lane line number based on the map lane line set and the perceived lane line set; and determining an association result between map lane lines and perceived lane lines based on the map lane line numbers and the perceived lane line numbers.

[0080] In summary, this embodiment numbers the map lane lines and the perceived lane lines, and can accurately determine the relative distance of the lane lines based on the map lane line numbers and the perceived lane line numbers, and then quickly and accurately determine the association results between the map lane lines and the perceived lane lines, thereby overcoming the technical defects of poor efficiency and accuracy in the association between the perceived lane lines and the map lane lines, and can effectively improve the efficiency and accuracy of the association between the perceived lane lines and the map lane lines, thereby improving the accuracy and availability of lane line matching and positioning.

[0081] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 2 , the step S30 further includes steps S301-S302:

[0082] Step S301, obtaining the number of map lane lines and the number of sensed lane lines.

[0083] It should be noted that the number of map lane lines hd_sz is directly obtained through map data, reflecting the number of lanes planned on the actual road, while the number of perceived lane lines per_sz is based on the lane line information perceived in real time by the vehicle sensors, which may be affected by multiple factors such as the environment and sensor performance.

[0084] Step S302, determining the association result between the map lane line and the perceived lane line according to at least one of the number of the map lane lines, the number of the perceived lane lines, the map lane line number and the perceived lane line number.

[0085] It should be noted that when determining the association result between the map lane lines and the perceived lane lines, the present embodiment further introduces the consideration of the number of lane lines. The number of map lane lines hd_sz and the number of perceived lane lines per_sz are compared to identify the difference between the two, which may be due to changes in actual road conditions (such as temporary lane settings, construction, etc.) or errors in sensor perception. When the numbers of the two are exactly the same, it can be preliminarily considered that the perceived lane lines more accurately reflect the actual road conditions. At this time, the association process can be relatively simplified, and a one-to-one match can be performed directly based on the number.

[0086] It is understandable that in most cases, there will be a difference between the two numbers. In this case, it is necessary to determine the correlation between the map lane line and the perception lane line by analyzing the relationship between the map lane line number and the perception lane line number.

[0087] In a feasible implementation, step S302 may include: determining that the association result between the map lane line and the perceived lane line is that there is no valid association relationship based on at least one of the number of map lane lines, the number of perceived lane lines, the map lane line number, and the perceived lane line number; determining that the association result between the map lane line and the perceived lane line is that there is a valid association relationship based on the map lane line number and the perceived lane line number.

[0088] It should be noted that the association result between the map lane line and the perceived lane line is determined to be that there is no valid association relationship based on at least one of the number of map lane lines, the number of perceived lane lines, the map lane line number and the perceived lane line number. That is, in certain specific cases, if the difference between the number of map lane lines and the number of perceived lane lines is too large, or no reasonable correspondence can be found between the map lane line number and the perceived lane line number, the system may determine that there is no valid lane line association relationship in the current scenario.

[0089] In a specific implementation, if any one of the following conditions is met: the number of perceived lane lines per_sz is 0, the number of map lane lines hd_sz is less than the number of perceived lane lines per_sz, and the difference offset_min between the number of the first map lane line map_ind and the number of the first perceived lane line sort_ind is greater than the difference offset_max between the number of the last map lane line map_ind and the number of the last perceived lane line sort_ind, it is determined that the map lane line has no effective association with the perceived lane line, that is, the algorithm has no solution to this situation.

[0090] In a feasible implementation manner, the association result between the map lane line and the perceived lane line is determined as the existence of a valid association relationship based on the map lane line number and the perceived lane line number, including: determining a first number deviation and a second number deviation based on the map lane line number and the perceived lane line number; determining a target deviation based on the first number deviation and the second number deviation; and determining that the association result between the map lane line and the perceived lane line is the existence of a valid association relationship when the sum of the perceived lane line number and the target deviation is equal to the map lane line number and the perceived lane line type is consistent with the map lane line type.

[0091] It should be noted that the first numbering deviation is the difference offset_min between the number map_ind of the first map lane line and the number sort_ind of the first sensed lane line, and the second numbering deviation is the difference offset_max between the number map_ind of the last map lane line and the number sort_ind of the last sensed lane line.

[0092] It can be understood that the target deviation offset is an integer in the range of the first numbered deviation offset_min to the second numbered deviation offset_max. All values ​​of offset are traversed. In a certain traversal, if the number sort_ind+offset of a perceived line is equal to the number map_ind of a line in the map, and the type of lane line (types are divided into road boundaries, real lane lines, virtual lane lines, etc.) is consistent, then the perception and the two lines of the map form an effective association. If in this traversal, all perceived lines form an effective association with the lines of the map, then this set of associations is a solution to the data association between the perception and the map lane lines, and the solution is recorded.

[0093] It is worth noting that if the solution of the data association between perception and map lane lines is unique and the number of associated lines in the solution is greater than 2 pairs, and the distances from the associated perception and map lines in the solution to the vehicle are within a threshold (recommended 20 meters, which can be adjusted), then this solution is available, that is, the association relationship between the perception and map lane lines required to be solved is met.

[0094] It is worth noting that the lane line numbers reflect the positional relationship and relative distance of the lane lines. Therefore, determining the association between the map lane lines and the perceived lane lines based on the lane line numbers reduces the possibility of lane line misassociation and improves the efficiency of lane line association. In addition, the association relationship is further verified using the lane line type to improve the robustness of the system.

[0095] In this embodiment, the association results between the map lane lines and the perceived lane lines can be quickly and accurately determined from multiple dimensions based on the number of lane lines and the lane line numbers, thereby reducing the possibility of lane line misassociation and improving the efficiency of lane line association.

[0096] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the lane line data association method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0097] This application also provides a lane line data association device, please refer to Figure 3 , the lane line data association device comprises:

[0098] The acquisition module 10 is used to acquire a map lane line set and a perception lane line set.

[0099] The determination module 20 is used to determine the map lane line number and the perception lane line number according to the map lane line set and the perception lane line set.

[0100] The determination module 20 is further used to determine the association result between the map lane line and the perceived lane line according to the map lane line number and the perceived lane line number.

[0101] The present embodiment provides a lane line data association device, which obtains a map lane line set and a perception lane line set; determines a map lane line number and a perception lane line number based on the map lane line set and the perception lane line set; determines an association result between a map lane line and a perception lane line based on the map lane line number and the perception lane line number, which can effectively improve the efficiency and accuracy of associating perception lane lines with map lane lines, thereby improving the accuracy and availability of lane line matching and positioning.

[0102] In summary, this embodiment numbers the map lane lines and the perceived lane lines, and can accurately determine the relative distance of the lane lines based on the map lane line numbers and the perceived lane line numbers, and then quickly and accurately determine the association results between the map lane lines and the perceived lane lines, thereby overcoming the technical defects of poor efficiency and accuracy in the association between the perceived lane lines and the map lane lines, and can effectively improve the efficiency and accuracy of the association between the perceived lane lines and the map lane lines, thereby improving the accuracy and availability of lane line matching and positioning.

[0103] Optionally, the determination module 20 is also used to determine a first lateral distance between the vehicle and the target map lane line based on the map lane line set, and determine a second lateral distance between the vehicle and the target perceived lane line based on the perceived lane line set; sort the map lane lines according to the first lateral distance to obtain a first position relationship, and sort the perceived lane lines according to the second lateral distance to obtain a second position relationship; determine the map lane line number based on the first position relationship, and determine the perceived lane line number based on the second position relationship.

[0104] Optionally, the determination module 20 is also used to determine the target map lane line based on the map lane line set; obtain the coordinates of the vehicle in the map coordinate system, and determine the normal distance between the vehicle and the target map lane line according to the coordinates of the vehicle in the map coordinate system; determine the first lateral distance between the vehicle and the target map lane line according to the normal distance.

[0105] Optionally, the determination module 20 is also used to determine the adjacent map lane line of the target map lane line based on the first position relationship; obtain the relative distance between the target map lane line and the adjacent map lane line; and number the map lane lines in the map lane line set based on the first position relationship and the relative distance to obtain the map lane line numbers.

[0106] Optionally, the determination module 20 is also used to obtain the number of map lane lines and the number of perceived lane lines; and determine the association result between the map lane line and the perceived lane line based on at least one of the number of map lane lines, the number of perceived lane lines, the map lane line number and the perceived lane line number.

[0107] Optionally, the determination module 20 is further used to determine that the association result between the map lane line and the perceived lane line does not have a valid association relationship based on at least one of the number of map lane lines, the number of perceived lane lines, the map lane line number and the perceived lane line number; and to determine that the association result between the map lane line and the perceived lane line does not have a valid association relationship based on the map lane line number and the perceived lane line number.

[0108] Optionally, the determination module 20 is also used to determine a first number deviation and a second number deviation based on the map lane line number and the perceived lane line number; determine a target deviation based on the first number deviation and the second number deviation; and when the sum of the perceived lane line number and the target deviation is equal to the map lane line number and the perceived lane line type is consistent with the map lane line type, determine that the association result between the map lane line and the perceived lane line is that there is a valid association relationship.

[0109] The lane line data association device provided by the present application adopts the lane line data association method in the above embodiment, which can solve the technical problem of how to effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines, thereby improving the accuracy and availability of lane line matching and positioning. Compared with the prior art, the beneficial effects of the lane line data association device provided by the present application are the same as the beneficial effects of the lane line data association method provided by the above embodiment, and the other technical features in the lane line data association device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0110] The present application provides a lane line data association device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the lane line data association method in the above-mentioned embodiment 1.

[0111] Reference below Figure 4 , which shows a schematic diagram of the structure of a lane data association device suitable for implementing the embodiment of the present application. The lane data association device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The lane line data association device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0112] like Figure 4 As shown, the lane data association device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the lane data association device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the lane data association device to communicate with other devices wirelessly or by wire to exchange data. Although the lane data association device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0113] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0114] The lane line data association device provided by the present application adopts the lane line data association method in the above embodiment, which can solve the technical problem of how to effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines, thereby improving the accuracy and availability of lane line matching and positioning. Compared with the prior art, the beneficial effects of the lane line data association device provided by the present application are the same as the beneficial effects of the lane line data association method provided by the above embodiment, and the other technical features in the lane line data association device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0115] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0116] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0117] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the lane line data association method in the above-mentioned embodiment.

[0118] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0119] The computer-readable storage medium may be included in the lane data association device; or may exist independently without being assembled into the lane data association device.

[0120] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the lane line data association device, the lane line data association device: obtains a map lane line set and a perception lane line set; determines a map lane line number and a perception lane line number based on the map lane line set and the perception lane line set; determines an association result between a map lane line and a perception lane line based on the map lane line number and the perception lane line number.

[0121] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0122] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0123] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0124] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above lane line data association method, and can solve the technical problem of how to effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines, thereby improving the accuracy and availability of lane line matching and positioning. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the lane line data association method provided in the above embodiment, and will not be repeated here.

[0125] The present application also provides a computer program product, including a computer program, which implements the steps of the lane line data association method as described above when executed by a processor.

[0126] The computer program product provided by this application can solve the technical problem of how to effectively improve the efficiency and accuracy of associating perceived lane lines with map lane lines, thereby improving the accuracy and usability of lane line matching and positioning. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the lane line data association method provided by the above embodiment, which will not be repeated here.

[0127] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A lane line data association method, characterized in that: The method comprises: Get the map lane line set and the perception lane line set; Determine a map lane line number and a sensed lane line number according to the map lane line set and the sensed lane line set; The association result between the map lane line and the perceived lane line is determined according to the map lane line number and the perceived lane line number.

2. The method according to claim 1, characterized in that The determining the map lane line number and the sensed lane line number according to the map lane line set and the sensed lane line set includes: Determine a first lateral distance between the vehicle and a target map lane line according to the map lane line set, and determine a second lateral distance between the vehicle and a target sensed lane line according to the sensed lane line set; Sorting the map lane lines according to the first lateral distance to obtain a first position relationship, and sorting the sensed lane lines according to the second lateral distance to obtain a second position relationship; The map lane line number is determined based on the first position relationship, and the perceived lane line number is determined based on the second position relationship.

3. The method according to claim 2, characterized in that The determining a first lateral distance between the vehicle and the target map lane line according to the map lane line set includes: Determine a target map lane line based on the map lane line set; Obtaining the coordinates of the vehicle in the map coordinate system, and determining the normal distance between the vehicle and the lane line of the target map according to the coordinates of the vehicle in the map coordinate system; A first lateral distance between the vehicle and the lane line of the target map is determined according to the normal distance.

4. The method according to claim 2, characterized in that The determining the map lane line number according to the first position relationship includes: Determine the adjacent map lane line of the target map lane line according to the first position relationship; Obtaining the relative distance between the target map lane line and the adjacent map lane line; The map lane lines in the map lane line set are numbered according to the first positional relationship and the relative distance to obtain map lane line numbers.

5. The method according to claim 1, characterized in that The determining the association result between the map lane line and the sensed lane line according to the map lane line number and the sensed lane line number includes: Get the number of map lane lines and the number of perceived lane lines; Determine an association result between a map lane line and a perceived lane line based on at least one of the number of map lane lines, the number of perceived lane lines, the map lane line number, and the perceived lane line number.

6. The method according to claim 5, characterized in that The determining the association result between the map lane line and the perceived lane line according to at least one of the number of the map lane lines, the number of the perceived lane lines, the number of the map lane lines, and the number of the perceived lane lines includes: Determining, based on at least one of the number of map lane lines, the number of sensed lane lines, the number of map lane lines, and the number of sensed lane lines, that the association result between the map lane line and the sensed lane line is that there is no valid association relationship; The association result between the map lane line and the perceived lane line is determined based on the map lane line number and the perceived lane line number to be a valid association relationship.

7. The method according to claim 6, characterized in that The determining, based on the map lane line number and the sensed lane line number, that the association result between the map lane line and the sensed lane line is a valid association relationship includes: Determine a first number deviation and a second number deviation according to the map lane line number and the sensed lane line number; Determine a target deviation according to the first number deviation and the second number deviation; When the sum of the perceived lane line number and the target deviation is equal to the map lane line number and the perceived lane line type is consistent with the map lane line type, it is determined that the association result between the map lane line and the perceived lane line is that a valid association relationship exists.

8. A lane line data association device, characterized in that: The lane line data association device comprises: An acquisition module is used to acquire a map lane line set and a perception lane line set; A determination module, used to determine a map lane line number and a sensed lane line number according to the map lane line set and the sensed lane line set; The determination module is further used to determine the association result between the map lane line and the perceived lane line according to the map lane line number and the perceived lane line number.

9. A lane line data association device, characterized in that: The lane line data association device includes: a memory, a processor, and a lane line data association program stored in the memory and executable on the processor, wherein the lane line data association program is configured to implement the lane line data association method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a lane line data association program, and when the lane line data association program is executed by the processor, the lane line data association method according to any one of claims 1 to 7 is implemented.

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