Data processing method, device, apparatus, and computer-readable storage medium

Abstract

The present invention relates to a data processing method, apparatus, device, and computer-readable storage medium. The method includes: obtaining navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data includes the coordinates of multiple track points; determining a navigation start point from the multiple track points based on the coordinates of the multiple track points, the vehicle position coordinates, and the vehicle heading angle; and filtering high-precision map data based on the navigation start point and track points located after the navigation start point along the direction of track movement in the multiple track points to determine target map data. After matching the navigation start point, the navigation start point and the track points after it are used as valid track points, and the data corresponding to the valid track points are filtered in the high-precision map, which can greatly reduce the amount of data loaded into the high-precision map and reduce resource consumption.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving technology, and in particular to a data processing method, device, equipment and computer-readable storage medium. Background Art

[0002] With the development of intelligent driving (also known as autonomous driving, unmanned driving, etc.), the application of high-definition maps (HD maps) is becoming increasingly widespread. HD maps are high-precision maps used for autonomous driving. They contain map elements such as road shape, road markings, traffic signs, and obstacles. When navigating a vehicle, you can use the navigation map provided by the vehicle's computer system or HD maps.

[0003] Compared to high-precision maps, navigation maps are simpler and their data accuracy is not high. Therefore, high-precision maps are generally used for navigation in related technologies. However, due to the large amount of data in high-precision maps, loading data can easily cause the CPU (Central Processing Unit) and memory to be occupied, resulting in high resource consumption. Summary of the Invention

[0004] The embodiments of the present invention provide a data processing method, apparatus, device, and computer-readable storage medium, which reduce resource consumption.

[0005] The technical solution of the embodiment of the present invention is achieved as follows:

[0006] In a first aspect, an embodiment of the present invention provides a data processing method, comprising: acquiring navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data comprising coordinates of a plurality of trajectory points; determining a navigation starting point among the plurality of trajectory points based on the coordinates of the plurality of trajectory points, the vehicle position coordinates, and the vehicle heading angle; screening high-precision map data based on the navigation starting point and trajectory points among the plurality of trajectory points that are located after the navigation starting point along the trajectory running direction to determine target map data.

[0007] In a second aspect, an embodiment of the present invention provides a data processing device, comprising: an acquisition unit for acquiring navigation data, a vehicle position coordinate, and a vehicle heading angle; the navigation data comprises coordinates of a plurality of trajectory points; a determination unit for determining a navigation starting point among the plurality of trajectory points based on the coordinates of the plurality of trajectory points, the vehicle position coordinates, and the vehicle heading angle; and a screening unit for screening high-precision map data based on the navigation starting point and the trajectory points among the plurality of trajectory points that are located after the navigation starting point along the trajectory running direction, to determine target map data.

[0008] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory for storing an executable computer program; and a processor for implementing the data processing method described in the first aspect when executing the executable computer program stored in the memory.

[0009] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program for implementing the data processing method described in the first aspect when executed by a processor.

[0010] Beneficial Effects of the Invention: Embodiments of the present invention provide a data processing method, apparatus, device, and computer-readable storage medium. According to the solution provided by an embodiment of the present invention, the method includes: obtaining navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data includes the coordinates of multiple track points; determining a navigation start point from the multiple track points based on the coordinates of the multiple track points, the vehicle position coordinates, and the vehicle heading angle; the first track point from the multiple track points is not necessarily the actual start point; the vehicle position coordinates and the vehicle heading angle are provided by the vehicle positioning system and are more accurate than the navigation data; the navigation start point is matched from the multiple track points based on the vehicle position coordinates and the vehicle heading angle, combined with the coordinates of the multiple track points, thereby improving the accuracy of the navigation start point. High-precision map data is filtered based on the navigation start point and track points from the multiple track points that follow the navigation start point along the direction of the track to determine target map data. After matching the navigation start point, the navigation start point and the track points that follow it are considered valid track points, and the data corresponding to the valid track points is filtered in the high-precision map, which can significantly reduce the amount of data loaded into the high-precision map and reduce resource consumption.

[0011] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and are not intended to limit the technical solutions of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present invention and, together with the specification, are used to explain the technical solutions of the present invention.

[0013] Figure 1 Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 1 ;

[0014] Figure 2 Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 2 ;

[0015] Figure 3 Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 3 ;

[0016] Figure 4 Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 4 ;

[0017] Figure 5 A schematic diagram of the structure of a data processing device provided in an embodiment of the present invention;

[0018] Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention;

[0019] Figure 7 It is a schematic diagram of the structure of another electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable a more detailed understanding of the features and technical contents of the embodiments of the present invention, the implementation of the embodiments of the present invention is described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference only and are not intended to limit the embodiments of the present invention.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention pertains. The terms used herein are for the purpose of describing embodiments of the present invention only and are not intended to limit the present invention.

[0022] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0023] It should also be pointed out that the terms "first\second\third" involved in the embodiments of the present invention are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present invention described herein can be implemented in an order other than that illustrated or described herein.

[0024] In the embodiment of the present invention, the term "and / or" is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, object A and / or object B may represent three situations: object A exists alone, object A and object B exist at the same time, and object B exists alone.

[0025] In addition, in the embodiments of the present invention, “a plurality of” means two or more, unless otherwise clearly defined.

[0026] Navigation maps have low accuracy, reaching only the road level. Using a single centerline to represent a road, they cannot accurately describe lane information within that road. For example, a road can contain multiple lanes. High-precision maps, on the other hand, offer higher accuracy, reaching the lane level and describing the individual lanes within a road. Based on this, the present invention proposes a high-precision map data screening method based on vehicle-mounted navigation. This method filters high-precision map data based on navigation data provided by the vehicle-mounted system, thereby reducing the amount of data loaded into high-precision maps and lowering resource consumption.

[0027] The embodiment of the present invention provides a data processing method, such as Figure 1 As shown, Figure 1 Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 1 , the data processing method includes the following steps:

[0028] S110 , obtaining navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data includes coordinates of multiple trajectory points.

[0029] In some embodiments, the data processing method is applied to an electronic device, which is in communication with a vehicle system; Figure 1 The navigation data can be obtained in S110 by the following method: obtaining the navigation data sent by the vehicle system.

[0030] In an embodiment of the present invention, the data processing method is executed by an electronic device. The electronic device may be provided with a map engine, or provided with an application (also referred to as a program or software) for processing map data. The electronic device communicates with the vehicle system via the Transmission Control Protocol (TCP), and the electronic device receives navigation data sent by the vehicle system.

[0031] In this embodiment of the present invention, navigation data is collected from the vehicle system. The navigation data consists of multiple track points, including their coordinates. The direction of each track point can also be calculated based on the coordinates of the multiple track points. For each track point, the vector formed by the track point and its subsequent adjacent track points is used as the direction of the track point. The vehicle position point is obtained by the vehicle's Global Positioning System (GPS), which has higher accuracy than navigation data. The vehicle position point includes parameters such as the vehicle's position coordinates and the vehicle's direction. The vehicle's direction can be the vehicle's head heading angle.

[0032] S120: Determine a navigation start point among the multiple track points based on the coordinates of the multiple track points, the vehicle position coordinates, and the vehicle heading angle.

[0033] In an embodiment of the present invention, each trajectory point has coordinates and directions, wherein the direction of the first trajectory point (the first trajectory point) is the vector formed by the first trajectory point and the second trajectory point (adjacent to the first trajectory point) (the vector can be calculated using the coordinates of the two trajectory points), and the direction of the second trajectory point is the vector formed by the second trajectory point and the third trajectory point. By analogy, the direction of each trajectory point can be obtained. For each trajectory point, the distance between the two is calculated based on the coordinates of the trajectory point and the vehicle position coordinates; and the angle between the two is calculated based on the direction of the trajectory point and the vehicle heading angle. The closer the distance, the greater the possibility that the trajectory point will become the starting point of navigation. The distance weight is calculated based on the distance, and the distance weight reflects the possibility that the trajectory point will become the starting point of navigation; the smaller the angle, the greater the possibility that the trajectory point will become the starting point of navigation. The direction weight is calculated based on the angle, and the direction weight reflects the possibility that the trajectory point will become the starting point of navigation. The target weight of a track point is calculated based on the distance weight and direction weight. This can be obtained by directly adding the distance weight and direction weight together, or by adding a coefficient to each. The smaller the coefficient, the greater its importance in determining whether the track point is the navigation starting point. The target weight is calculated by adding the product of the distance weight and the distance coefficient, plus the product of the direction weight and the direction coefficient. Based on the target weight, the track point with the smallest target weight is selected from multiple track points as the navigation starting point.

[0034] Because the first track point among multiple trajectory points is not necessarily the actual starting point, the vehicle's position coordinates and heading angle are provided by the vehicle's positioning system, which is more accurate than navigation data. This method obtains the vehicle's position (including its position coordinates and heading angle) and matches it with the navigation data to determine the navigation starting point. During matching, the vehicle's position coordinates and heading angle are combined with the coordinates of multiple track points to match the navigation starting point among the multiple track points, thereby improving the accuracy of the navigation starting point.

[0035] Furthermore, since the navigation start point to be matched is not too far away, multiple candidate trajectory points that are not far from the first trajectory point can be selected from multiple trajectory points. The target weight of each candidate trajectory point is calculated based on its coordinates, the vehicle's position coordinates, and the vehicle's heading angle. Then, based on the target weight, the navigation start point is selected from the multiple candidate trajectory points. Compared to the solution of selecting the navigation start point from multiple trajectory points, this method can reduce the amount of computational data and resource consumption.

[0036] S130 , screening the high-precision map data based on the navigation starting point and the track points located after the navigation starting point along the track running direction among the multiple track points to determine the target map data.

[0037] In an embodiment of the present invention, multiple track points are arranged along the direction of track movement. After selecting the navigation start point, track points after the navigation start point are selected from the multiple track points. The navigation start point and the track points after it are regarded as valid track points. Based on the coordinates of the valid track points, the positions corresponding to the coordinates of the valid track points are found on the high-precision map, and then the data of the area around the valid track points in the high-precision map are filtered. In this way, data useful for the navigation is obtained, which reduces the amount of data loaded into the high-precision map during the navigation process and reduces resource consumption.

[0038] After matching the navigation start point, the present invention uses the navigation start point and subsequent trajectory points as valid trajectory points and filters the data corresponding to these valid trajectory points in the high-precision map. This solves the technical problem of extracting the required data from a large amount of data when using high-precision map data, significantly reducing the amount of data loaded into the high-precision map and lowering resource consumption. Fusion of the navigation map and the high-precision map not only utilizes the navigation map's road traffic information and marker point information for route planning, but also leverages the high-precision map's detailed lane-level information, improving navigation accuracy.

[0039] The present invention relates to the field of intelligent driving and proposes a high-precision map data screening method based on vehicle navigation. By parsing the navigation data of the vehicle system, navigation trajectory points (corresponding to the navigation starting point and the trajectory points located after the navigation starting point along the trajectory running direction among multiple trajectory points) are extracted. The navigation trajectory points are then matched with high-precision map data, thereby achieving the purpose of screening high-precision map data, reducing the CPU resource and memory usage caused by loading unnecessary data, and reducing resource consumption.

[0040] Embodiments of the present invention provide a data processing method, apparatus, device, and computer-readable storage medium. According to the solution provided by the embodiments of the present invention, the method includes: obtaining navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data includes the coordinates of multiple track points; determining a navigation start point from the multiple track points based on the coordinates of the multiple track points, the vehicle position coordinates, and the vehicle heading angle; the first track point from the multiple track points is not necessarily the actual start point; the vehicle position coordinates and the vehicle heading angle are provided by the vehicle positioning system and are more accurate than the navigation data; the navigation start point is matched from the multiple track points based on the vehicle position coordinates and the vehicle heading angle, combined with the coordinates of the multiple track points, thereby improving the accuracy of the navigation start point. High-precision map data is filtered based on the navigation start point and track points from the multiple track points that follow the navigation start point along the direction of the track to determine target map data. After matching the navigation start point, the navigation start point and the track points that follow it are considered valid track points, and the data corresponding to the valid track points is filtered in the high-precision map. This can significantly reduce the amount of data loaded into the high-precision map and reduce resource consumption.

[0041] In some embodiments, in the above Figure 1 After S130, the data processing method further includes: converting the target map data into a format to determine vehicle control data corresponding to a data format of the vehicle control system; and sending the vehicle control data to the vehicle control system so that the vehicle control system performs navigation based on the vehicle control data.

[0042] In an embodiment of the present invention, after determining the target map data, the filtered high-precision map (corresponding to the target map data) can be stored and converted into a data format executable by the downstream vehicle control system. When converting the format of the target map data, the filtered high-precision map (corresponding to the target map data) can be first parsed by SDK (Software Development Kit) and then filled into the data parameters of the vehicle control system. After completing the format conversion, the vehicle control data is obtained. The vehicle control data corresponds to the data format of the vehicle control system. The vehicle control system can recognize the vehicle control data and send the vehicle control data to the vehicle control system, and the vehicle control system performs navigation based on the vehicle control data.

[0043] Since the vehicle control data is converted based on the target map data, based on the accuracy of the above target map data and the technical effect of reducing resource consumption, the vehicle control system navigates based on the vehicle control data, which can improve the accuracy and efficiency of navigation.

[0044] In some embodiments, the above Figure 1 S120 may include S210-S240, such as Figure 2 As shown, Figure 2Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 2 .

[0045] S210: Select at least two candidate trajectory points from multiple trajectory points.

[0046] In this embodiment of the present invention, since the navigation start point to be matched is not too far away, at least two candidate trajectory points that are not far from the first trajectory point can be selected from the multiple trajectory points. The distance between adjacent candidate trajectory points in at least two candidate trajectory points is the same. By uniformly selecting candidate trajectory points, the effectiveness of the candidate trajectory points can be improved.

[0047] In some embodiments, the above Figure 2 S210 can be implemented in the following manner: based on a first trajectory point from among the plurality of trajectory points, one trajectory point is selected from among the plurality of trajectory points at intervals of a first preset distance along the trajectory running direction, or one trajectory point is selected from among the plurality of trajectory points at intervals of a preset number of trajectory points along the trajectory running direction, until a distance between the selected trajectory point and the first trajectory point is greater than a second preset distance value, thereby obtaining at least two candidate trajectory points; wherein the at least two candidate trajectory points include the first trajectory point and a trajectory point whose distance from the first trajectory point along the trajectory running direction is less than or equal to the second preset distance value.

[0048] In an embodiment of the present invention, starting from the first trajectory point among the multiple trajectory points, a trajectory point is selected from the multiple trajectory points at intervals of a first preset distance value along the trajectory running direction. The distance between the selected trajectory point 1 and the first trajectory point is the first preset distance value, the distance between the selected trajectory point 2 and the first trajectory point is the first preset distance value × 2, and so on, until the distance between the selected trajectory point N and the first trajectory point is greater than the second preset distance value, the first preset distance value × (N-1) ≤ the second preset distance value < the first preset distance value × N, and N candidate trajectory points are obtained (including the first trajectory point, as well as trajectory point 1, trajectory point 2...trajectory point N-1), and the distances between adjacent candidate trajectory points among these N candidate trajectory points are the same.

[0049] For example, the navigation data is processed by selecting a track point every 140 meters from the navigation start point and accumulating the distance from the first track point until the distance from the first track point exceeds 2 km. In other words, the track points within 2 km of the first track point are selected from the multiple track points in the navigation data. The number of candidate track points is approximately 2 km / 140 meters, rounded down to 14.

[0050] In an embodiment of the present invention, starting from the first trajectory point among the multiple trajectory points, a trajectory point is selected every preset number of trajectory points among the multiple trajectory points along the trajectory running direction, and the selected trajectory point 1 is separated from the first trajectory point by M trajectory points, and the selected trajectory point 2 is separated from the trajectory point 1 by M trajectory points, and so on, until the distance between the selected trajectory point N and the first trajectory point is greater than a second preset distance value, thereby obtaining N candidate trajectory points (including the first trajectory point, as well as trajectory point 1, trajectory point 2...trajectory point N-1), and the number of trajectory points between adjacent candidate trajectory points in these N candidate trajectory points is the same.

[0051] It should be noted that the first preset distance value and the second preset distance value can be appropriately set by technical personnel in this field according to actual conditions. The first preset distance value can be 140m, 100m, 50m, 160m, etc., and the second preset distance value can be 1.5km, 2km, 3km, 2.5km, etc., which is not limited to this embodiment of the present invention.

[0052] Because multiple trajectory points are densely packed, selecting trajectory points at intervals of a first preset distance or a preset number of intervals can increase the distribution of candidate trajectory points and improve their effectiveness. Furthermore, compared to directly selecting a trajectory point at a second preset distance from the first trajectory point, this present invention's method of selecting trajectory points at intervals reduces the number of trajectory points, lowers the computational load, and improves data processing efficiency.

[0053] S220 , determining a direction weight of each candidate trajectory point based on the vehicle heading angle and the direction of each candidate trajectory point; the direction of a candidate trajectory point represents a vector formed by the candidate trajectory point and the next adjacent candidate trajectory point.

[0054] In an embodiment of the present invention, based on the coordinates of the current candidate trajectory point and the coordinates of the next candidate trajectory point adjacent to it along the trajectory running direction, the vector between the two is calculated, and the vector is used as the direction of the current candidate trajectory point. By analogy, the direction of each candidate trajectory point can be calculated. For each candidate trajectory point, the vector similarity between the heading angle of the vehicle and the direction of the candidate trajectory point is calculated, for example, cosine similarity (also known as cosine distance), Euclidean distance, Hamming distance, etc. The direction weight is determined based on the vector similarity. The greater the vector similarity, the greater the possibility that the candidate trajectory point is used as the starting point of navigation.

[0055] In some embodiments, the above Figure 2 S220 can be implemented in the following manner: determining each included angle according to the heading angle of the vehicle and the direction of each candidate trajectory point; and determining the ratio of each included angle to a preset angle as the direction weight of each candidate trajectory point.

[0056] In this embodiment of the present invention, for each candidate trajectory point, the angle between the direction of the vehicle's position (i.e., the vehicle's heading angle) and the direction of the candidate trajectory point is calculated. The smaller the angle, the greater the likelihood that the candidate trajectory point will be the navigation starting point. The ratio of the angle to a preset angle is used as the direction weight. The smaller the direction weight, the greater the likelihood that the candidate trajectory point will be the navigation starting point.

[0057] It should be noted that the preset angle can be appropriately set by those skilled in the art according to actual conditions, for example, 110°, 100°, 120°, etc., and the present invention does not limit this.

[0058] In some embodiments, the data processing method further includes: for each candidate trajectory point, if the included angle is greater than a preset angle, no longer calculating the distance weight and the direction weight.

[0059] In this embodiment of the present invention, after determining each included angle for each candidate trajectory point, if the included angle is less than or equal to a preset angle, the ratio of the included angle to the preset angle is determined as the directional weight. If the included angle is greater than the preset angle, neither the directional weight nor the distance weight for the candidate trajectory point is calculated. Compared to a technical solution that directly calculates the directional weight of each candidate trajectory point, this reduces the amount of computation and improves data processing efficiency.

[0060] For example, taking the preset angle of 110° as an example, the direction weight = angle / 110°. Angles greater than 110° are discarded and no longer calculated for direction weight and distance weight. The smaller the angle, the smaller the weight, and the more likely it is to be used as the navigation starting point.

[0061] S230 : Determine the distance weight of each candidate trajectory point based on the vehicle position coordinates and the coordinates of each candidate trajectory point.

[0062] In some embodiments, the above Figure 2 S230 can be implemented in the following manner: determining each distance value according to the vehicle position coordinates and the coordinates of each candidate trajectory point; and determining the ratio of each distance value to the second preset distance value as the distance weight of each candidate trajectory point.

[0063] In this embodiment of the present invention, for each candidate trajectory point, the distance between the vehicle's position coordinates and the candidate trajectory point's coordinates is calculated. The smaller the distance, the greater the likelihood that the candidate trajectory point will be the navigation starting point. The ratio of the distance value to a second preset distance value is used as a weighted distance. The smaller the distance weight, the greater the likelihood that the candidate trajectory point will be the navigation starting point.

[0064] For example, taking the second preset distance value of 2 km as an example, the distance between the vehicle position point and each candidate trajectory point is calculated. The closer the distance, the smaller the weight. Distance weight = actual distance value / 2 km.

[0065] S240: Determine a navigation start point among at least two candidate trajectory points according to the direction weight of each candidate trajectory point and the distance weight of each candidate trajectory point.

[0066] In an embodiment of the present invention, for each candidate trajectory point, one approach is to add the distance weight and the direction weight to obtain a target weight. The smaller the target weight, the greater the likelihood that the target weight is used as the navigation starting point. The candidate trajectory point corresponding to the minimum target weight among at least two candidate trajectory points is selected as the navigation starting point. Another approach is to perform a weighted summation of the distance weight and the direction weight. That is, a coefficient is added to the distance weight and the direction weight. The smaller the coefficient, the more important the weight is in determining whether the trajectory point is a navigation starting point. The product of the distance weight and the distance coefficient is added to the product of the direction weight and the direction coefficient to obtain the target weight. The candidate trajectory point corresponding to the minimum target weight among at least two candidate trajectory points is selected as the navigation starting point.

[0067] In some embodiments, the above Figure 2 S240 can be implemented in the following manner: the sum of the direction weight of each candidate trajectory point and the distance weight of each candidate trajectory point is determined as the target weight of each candidate trajectory point; and the candidate trajectory point corresponding to the minimum value of the target weights of at least two candidate trajectory points is determined as the navigation start point.

[0068] In the embodiment of the present invention, for each candidate trajectory point, the direction weight plus the distance weight is used as the target weight of the candidate trajectory point, and then the candidate trajectory point corresponding to the minimum value is selected as the navigation starting point.

[0069] For example, if we select multiple trajectory points within 2 km of the first trajectory point from the navigation data every 140 meters, there are approximately 14 candidate trajectory points. The 14 candidate trajectory points are weighted using the same method to obtain 14 target weights, and the trajectory point with the smallest target weight is selected as the navigation start point.

[0070] In this embodiment of the present invention, by selecting at least two candidate trajectory points from multiple trajectory points, the amount of computational data is reduced and data processing efficiency is improved. A direction weight is determined based on the vehicle's heading angle and the direction of the candidate trajectory points, and a distance weight is determined based on the vehicle's position coordinates and the coordinates of the candidate trajectory points. Based on the direction weight and distance weight of each candidate trajectory point, a navigation start point is selected from the at least two candidate trajectory points. The likelihood of a candidate trajectory point being a navigation start point is considered from both the direction and distance dimensions, improving the accuracy of the selection result.

[0071] In some embodiments, the above Figure 1 S130 may include S310-S330, such as Figure 3 As shown, Figure 3 Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 3 .

[0072] S310: Construct a coverage area of ​​the target trajectory point based on the target trajectory point; the target trajectory point includes the navigation start point and trajectory points located after the navigation start point along the trajectory running direction among the multiple trajectory points.

[0073] S320. Filter the data corresponding to the coverage area in the high-precision map data in sequence to determine the map elements of the coverage area; the map elements include at least lane lines, road markings, traffic signs, and obstacles.

[0074] In an embodiment of the present invention, the navigation starting point and the track points located after the navigation starting point along the direction of the track among the multiple track points are all track points related to the navigation process, which are used as target track points. For each track point in the target track points, a coverage area is constructed with each track point as the center. The coverage area can be an area of ​​any shape, which is not limited by the embodiment of the present invention, for example, a square, circle, rectangle, irregular shape, etc. The target track point has coordinates and can be represented by longitude and latitude information. The high-precision map data is data about multiple tiles, which has longitude and latitude information. The position corresponding to the target track point and the position corresponding to its coverage area can be found in the high-precision map data. These are all data related to the navigation process. The data corresponding to the coverage area in the high-precision map data is filtered according to the coordinates to filter out the map elements within the coverage area. Map elements include at least lane lines, road markings, traffic signs and obstacles.

[0075] In some embodiments, the above Figure 3 S310-S320 can be realized through S410-S440, such as Figure 4 As shown, Figure 4 Schematic diagram of an optional process of a data processing method provided by an embodiment of the present invention Figure 4 .

[0076] S410. Construct a first coverage area with the navigation starting point as the center, so that the first track point is located within the first coverage area; the first track point is the next track point adjacent to the navigation starting point among the multiple track points, or is a track point along the track running direction and at a preset distance from the navigation starting point among the multiple track points.

[0077] In an embodiment of the present invention, starting from the navigation start point, along the trajectory direction, a trajectory point located after the navigation start point is selected from a plurality of trajectory points, and these trajectory points are used as target trajectory points. Based on this, the first trajectory point selected is the next trajectory point adjacent to the navigation start point from the plurality of trajectory points. Alternatively, according to the aforementioned method of selecting candidate trajectory points at intervals of a first preset distance value, starting from the navigation start point, along the trajectory direction, a trajectory point is selected from a plurality of trajectory points at intervals of a preset value until the last trajectory point from the plurality of trajectory points, and the trajectory points selected at intervals are used as target trajectory points. Based on this, the first trajectory point selected is a trajectory point from the plurality of trajectory points along the trajectory direction and at a preset distance from the navigation start point from the plurality of trajectory points. Alternatively, according to the aforementioned method of selecting candidate trajectory points at intervals of a preset number of trajectory points, starting from the navigation start point, along the trajectory direction, a trajectory point is selected from a plurality of trajectory points at intervals of a preset number of trajectory points until the last trajectory point from the plurality of trajectory points, and the trajectory points selected at intervals are used as target trajectory points.

[0078] It should be noted that the preset value can be appropriately set by those skilled in the art according to actual conditions. The preset value can be 140m, 100m, 50m, 160m, etc. The preset value can be the same as or different from the first preset distance value, and this embodiment of the present invention does not limit this.

[0079] In the embodiment of the present invention, a first coverage area is constructed with the navigation start point as the center. The first coverage area may be an area of ​​any shape as long as it can cover the first track point.

[0080] For example, the first track point is 140m away from the navigation starting point. When processing navigation data, starting from the navigation starting point, a track point (first track point) is taken every 140m. With the navigation starting point as the center, a square first coverage area of ​​200m×200m is constructed. In this way, the first track point is located within the range of the first coverage area.

[0081] S420: Filter data corresponding to the first coverage area in the high-precision map data according to the coordinates of the first track point and the vector formed by the navigation start point and the first track point, and determine map elements of the first coverage area.

[0082] In this embodiment of the present invention, the coordinates of the first trajectory point are used to locate the same location and its first coverage area in the high-precision map data. For complex road sections, such as intersections and T-junctions, which include multiple roads, the vector formed by the navigation start point and the first trajectory point can be used to determine the road, and then select one of the multiple roads. Based on the above two conditions, the data corresponding to the first coverage area in the high-precision map data is filtered to determine the map element. The map element is relevant to the navigation process and is effective and highly accurate.

[0083] For example, the first track point is 140m away from the navigation starting point. For the navigation starting point, the first track point on the navigation data is obtained along the track direction (140m away from the navigation starting point). With the navigation starting point as the center, a rectangular box of 200m×200m is constructed (which can cover the first track point). The data in the rectangular box at the same position on the high-precision map is parsed. According to the coordinates and direction of the first track point, map elements such as lane lines, road markings, traffic signs and obstacles in the first coverage area can be screened out.

[0084] S430. Continue to construct a second coverage area with the first trajectory point as the center, so that the second trajectory point is located in the second coverage area; the second trajectory point is the next trajectory point adjacent to the first trajectory point among the multiple trajectory points, or is a trajectory point along the trajectory running direction among the multiple trajectory points and is a preset distance away from the first trajectory point.

[0085] S440. Filter data corresponding to the second coverage area in the high-precision map data according to the coordinates of the second trajectory point and the vector formed by the first trajectory point and the second trajectory point to determine the map elements of the second coverage area; until the map elements of the last coverage area are determined; wherein the last coverage area is the coverage area corresponding to the last trajectory point among the multiple trajectory points, and the coverage areas include at least the first coverage area, the second coverage area, and the last coverage area.

[0086] For example, the second track point is 140m away from the first track point. For the first track point, the second track point (140m away from the first track point) on the navigation data is obtained along the track direction. With the first track point as the center, a rectangular box of 200m×200m is constructed (which can cover the second track point). The data in the rectangular box at the same position on the high-precision map is analyzed. According to the coordinates and direction of the second track point, map elements such as lane lines, road markings, traffic signs and obstacles in the second coverage area can be screened out.

[0087] In an embodiment of the present invention, starting from the navigation starting point, all subsequent track points (first track point, second track point...) on the navigation data are obtained along the track direction, and the tile data (tiledata) in the high-precision map data are matched, thereby filtering the high-precision map data. When performing data filtering, the high-precision map data is parsed, and a rectangular frame is first constructed with the extracted navigation starting point as the center point, and the parsed high-precision map data is matched to achieve data filtering. For other subsequent track points on the navigation data (for example, the first track point, the second track point...), according to the calculation method of the navigation starting point, the data in the high-precision map corresponding to all track points are filtered in turn to obtain map elements of multiple coverage areas (for example, the first coverage area, the second coverage area, and the last coverage area).

[0088] S330: Determine target map data according to the map elements of the coverage area.

[0089] In an embodiment of the present invention, a coverage area of ​​the target trajectory point is constructed based on the target trajectory point. The target trajectory point is no longer an isolated point, but a related area connected by roads, intersections, road signs, indicator lights, etc. during the navigation process. Then, the data corresponding to the coverage area in the high-precision map data is filtered to obtain filtered high-precision map data. The filtered high-precision map data includes map elements within the coverage area. The coverage area includes the coverage area of ​​multiple trajectory points (referring to the target trajectory point). In order to ensure the continuity and integrity of the data, the areas of multiple trajectory points are crossed and overlapped. After obtaining the map elements within the coverage area, they are deduplicated and integrated as target map data. The target map data includes the road traffic information and marker point information of the navigation map to complete the path planning, and also includes the detailed lane-level information of the high-precision map, which improves the accuracy of the target map data.

[0090] The preferred embodiments of the present invention are described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, the technical solution of the present invention can be subjected to a variety of simple modifications, and these simple modifications all fall within the scope of protection of the present invention. For example, the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will no longer describe various possible combinations separately. For another example, the various different embodiments of the present invention can also be arbitrarily combined, as long as they do not violate the idea of ​​the present invention, they should also be regarded as the contents disclosed by the present invention. For another example, under the premise of no conflict, the various embodiments and / or the technical features in each embodiment described in the present invention can be arbitrarily combined with the prior art, and the technical solution obtained after the combination should also fall within the scope of protection of the present invention.

[0091] It should also be understood that in the various method embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0092] In yet another embodiment of the present invention, based on the same inventive concept as the above embodiment, see Figure 5 , which shows a schematic diagram of the structure of the data processing device provided by an embodiment of the present invention. Figure 5 As shown, the data processing device 500 may include: an acquisition unit 510, used to acquire navigation data, vehicle position coordinates and vehicle heading angle; the navigation data includes coordinates of multiple track points; a determination unit 520, used to determine a navigation start point among multiple track points based on the coordinates of the multiple track points, the vehicle position coordinates and the vehicle heading angle; a screening unit 530, used to screen high-precision map data based on the navigation start point and track points among the multiple track points that are located after the navigation start point along the track running direction, to determine target map data.

[0093] In some embodiments, the determination unit 520 is further used to select at least two candidate trajectory points from the multiple trajectory points; determine the direction weight of each candidate trajectory point based on the heading angle of the vehicle and the direction of each candidate trajectory point; the direction of the candidate trajectory point represents the vector formed by the candidate trajectory point and the next adjacent candidate trajectory point; determine the distance weight of each candidate trajectory point based on the position coordinates of the vehicle and the coordinates of each candidate trajectory point; and determine the navigation start point from the at least two candidate trajectory points based on the direction weight of each candidate trajectory point and the distance weight of each candidate trajectory point.

[0094] In some embodiments, the determination unit 520 is further configured to select, based on a first trajectory point among the multiple trajectory points, a trajectory point every first preset distance value along the trajectory running direction, or to select a trajectory point every preset number of trajectory points along the trajectory running direction, until the distance between the selected trajectory point and the first trajectory point is greater than a second preset distance value, thereby obtaining the at least two candidate trajectory points; wherein the at least two candidate trajectory points include the first trajectory point, and a trajectory point whose distance from the first trajectory point along the trajectory running direction is less than or equal to the second preset distance value.

[0095] In some embodiments, the determination unit 520 is further configured to determine each included angle based on the vehicle heading angle and the direction of each candidate trajectory point; and determine the ratio of each included angle to a preset angle as the direction weight of each candidate trajectory point.

[0096] In some embodiments, the determination unit 520 is further configured to, for each candidate trajectory point, no longer calculate the distance weight and the direction weight if the included angle is greater than a preset angle.

[0097] In some embodiments, the determination unit 520 is further configured to determine each distance value based on the vehicle position coordinates and the coordinates of each candidate trajectory point; and determine the ratio of each distance value to a second preset distance value as the distance weight of each candidate trajectory point.

[0098] In some embodiments, the determination unit 520 is further used to determine the sum of the direction weights of each candidate trajectory point and the distance weights of each candidate trajectory point as the target weights of each candidate trajectory point; and determine the candidate trajectory point corresponding to the minimum value of the target weights of at least two candidate trajectory points as the navigation start point.

[0099] In some embodiments, the screening unit 530 is further used to construct a coverage area of ​​the target trajectory point based on the target trajectory point; the target trajectory point includes the navigation start point and the trajectory point located after the navigation start point along the trajectory running direction among the multiple trajectory points; the data corresponding to the coverage area in the high-precision map data is screened in turn to determine the map elements of the coverage area; the map elements include at least lane lines, road markings, traffic signs and obstacles; the target map data is determined according to the map elements of the coverage area.

[0100] In some embodiments, the screening unit 530 is further configured to construct a first coverage area with the navigation starting point as the center, so that the first track point is located within the first coverage area; the first track point is the next track point adjacent to the navigation starting point among the multiple track points, or is a track point along the track running direction and at a preset distance from the navigation starting point among the multiple track points; based on the coordinates of the first track point and the vector formed by the navigation starting point and the first track point, the data corresponding to the first coverage area in the high-precision map data is screened to determine the map elements of the first coverage area; and the second coverage area is continuously constructed with the first track point as the center, so that the second track point is located within the second coverage area. area; the second track point is the next track point adjacent to the first track point among the multiple track points, or is a track point along the track running direction among the multiple track points and at a preset distance from the first track point; according to the coordinates of the second track point and the vector formed by the first track point and the second track point, the data corresponding to the second coverage area in the high-precision map data is filtered to determine the map elements of the second coverage area; until the map elements of the last coverage area are determined; wherein the last coverage area is the coverage area corresponding to the last track point among the multiple track points, and the coverage area includes at least the first coverage area, the second coverage area and the last coverage area.

[0101] In some embodiments, the data processing device 500 further includes a conversion unit 540;

[0102] The conversion unit 540 is further configured to convert the target map data into a format, determine vehicle control data corresponding to a data format of the vehicle control system, and send the vehicle control data to the vehicle control system so that the vehicle control system performs navigation based on the vehicle control data.

[0103] In some embodiments, the method is applied to an electronic device, which is communicatively connected to a vehicle system; the acquisition unit 510 is further used to acquire the navigation data sent by the vehicle system.

[0104] It is understood that in this embodiment, a "unit" can be a portion of a processor, a portion of a program or software, etc., and can also be a module or non-modular. Furthermore, the various components in this embodiment can be integrated into a single processing unit, each unit can exist physically separately, or two or more units can be integrated into a single unit. The aforementioned integrated units can be implemented in the form of hardware or software functional modules.

[0105] If the integrated unit is implemented as a software functional module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, or the portion that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0106] Therefore, this embodiment provides a computer storage medium storing a computer program. When the computer program is executed by at least one processor, the steps of the method described in any one of the above embodiments are implemented.

[0107] Based on the above-mentioned composition of the data processing device 500 and the computer storage medium, see Figure 6 , which shows a schematic diagram of the composition structure of an electronic device provided by an embodiment of the present invention. Figure 6 As shown, the electronic device 600 may include: a communication interface 610, a memory 620 and a processor 630; each component is coupled together via a bus system 640. It is understood that the bus system 640 is configured to achieve connection and communication between these components. In addition to the data bus, the bus system 640 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 6 Various buses are labeled as bus system 640. Among them, the communication interface 610 is configured to receive and send signals in the process of sending and receiving information between other external devices or applications;

[0108] Memory 620 , configured to store computer programs that can be executed on processor 630 ;

[0109] The processor 630 is configured to, when running the computer program, execute:

[0110] Obtain navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data includes coordinates of multiple track points; determine a navigation start point among the multiple track points based on the coordinates of the multiple track points, the vehicle position coordinates, and the vehicle heading angle; filter high-precision map data based on the navigation start point and track points that follow the navigation start point along the track running direction among the multiple track points to determine target map data.

[0111] It is understood that the memory 620 in the embodiment of the present invention can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory 620 of the systems and methods described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0112] Processor 630 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits or software instructions in processor 630. Processor 630 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in conjunction with the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. This storage medium is located in memory 620. Processor 630 reads information from memory 620 and, in conjunction with its hardware, completes the steps of the above method.

[0113] It is understood that the embodiments described in the present invention may be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present invention, or a combination thereof.

[0114] For software implementation, the techniques described herein can be implemented through modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0115] Optionally, as another embodiment, the processor 630 is further configured to execute the steps of the method in any one of the aforementioned embodiments when running the computer program.

[0116] Based on the above-mentioned composition of the data processing device 500 and the computer storage medium, see Figure 7 , which shows a schematic diagram of the composition structure of another electronic device provided by an embodiment of the present invention. Figure 7 As shown, the electronic device 600 may include the data processing device 500 according to any one of the aforementioned embodiments.

[0117] In an embodiment of the present invention, navigation data, vehicle position coordinates, and vehicle heading angle are acquired; the navigation data includes the coordinates of multiple track points; and a navigation start point is determined from the multiple track points based on the coordinates of the multiple track points, the vehicle position coordinates, and the vehicle heading angle. The first track point among the multiple track points is not necessarily the actual starting point. The vehicle position coordinates and the vehicle heading angle are provided by the vehicle positioning system and are more accurate than the navigation data. Based on the vehicle position coordinates and the vehicle heading angle, combined with the coordinates of the multiple track points, the navigation start point is matched from the multiple track points, thereby improving the accuracy of the navigation start point. Based on the navigation start point and the track points that follow the navigation start point along the direction of the track, high-precision map data is filtered to determine target map data. After matching the navigation start point, the navigation start point and the track points that follow it are treated as valid track points, and the data corresponding to the valid track points is filtered in the high-precision map. This can significantly reduce the amount of data loaded into the high-precision map and reduce resource consumption.

[0118] It should be noted that, in the present invention, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0119] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0120] The methods disclosed in the several method embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0121] The features disclosed in several product embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new product embodiments.

[0122] The features disclosed in several method or device embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0123] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A data processing method, characterized in that: The method comprises: Obtaining navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data includes coordinates of multiple trajectory points; Selecting at least two candidate trajectory points from the plurality of trajectory points; Determining a direction weight of each candidate trajectory point based on the vehicle heading angle and the direction of each candidate trajectory point; the direction of the candidate trajectory point represents a vector formed by the candidate trajectory point and the next adjacent candidate trajectory point; Determining a distance weight for each candidate trajectory point based on the vehicle position coordinates and the coordinates of each candidate trajectory point; determining a navigation start point among the at least two candidate trajectory points according to the direction weights of the respective candidate trajectory points and the distance weights of the respective candidate trajectory points; According to the navigation starting point and the track points located after the navigation starting point along the track running direction among the multiple track points, the high-precision map data is screened to determine the target map data.

2. The method according to claim 1, characterized in that The selecting at least two candidate trajectory points from the plurality of trajectory points comprises: Based on a first trajectory point among the plurality of trajectory points, one trajectory point is selected from the plurality of trajectory points at intervals of a first preset distance along a trajectory running direction, or one trajectory point is selected from the plurality of trajectory points at intervals of a preset number of trajectory points along a trajectory running direction, until a distance between the selected trajectory point and the first trajectory point is greater than a second preset distance value, thereby obtaining the at least two candidate trajectory points; The at least two candidate trajectory points include the first trajectory point and a trajectory point whose distance from the first trajectory point along the trajectory running direction is less than or equal to a second preset distance value.

3. The method according to claim 1, characterized in that Determining the direction weight of each candidate trajectory point according to the vehicle heading angle and the direction of each candidate trajectory point includes: Determining each angle according to the vehicle heading angle and the direction of each candidate trajectory point; The ratios of the respective included angles to the preset angles are respectively determined as the direction weights of the respective candidate trajectory points.

4. The method according to claim 3, characterized in that The method further comprises: For each candidate trajectory point, if the included angle is greater than the preset angle, the distance weight and direction weight are no longer calculated.

5. The method according to claim 1, characterized in that The step of determining the distance weight of each candidate trajectory point based on the vehicle position coordinates and the coordinates of each candidate trajectory point includes: Determine each distance value according to the vehicle position coordinates and the coordinates of each candidate trajectory point; The ratio of each distance value to the second preset distance value is respectively determined as the distance weight of each candidate trajectory point.

6. The method according to any one of claims 2 to 5, characterized in that: The determining the navigation start point among the at least two candidate trajectory points according to the direction weights of the respective candidate trajectory points and the distance weights of the respective candidate trajectory points comprises: Determine the sum of the direction weight of each candidate trajectory point and the distance weight of each candidate trajectory point as the target weight of each candidate trajectory point; The candidate trajectory point corresponding to the minimum value of the target weights of at least two candidate trajectory points is determined as the navigation starting point.

7. The method according to any one of claims 1 to 5, characterized in that The step of screening the high-precision map data based on the navigation starting point and the track points located after the navigation starting point along the track running direction among the multiple track points to determine the target map data includes: Based on the target trajectory point, a coverage area of ​​the target trajectory point is constructed; the target trajectory point includes the navigation start point and a trajectory point located after the navigation start point along the trajectory running direction among the multiple trajectory points; Sequentially screening the data corresponding to the coverage area in the high-precision map data to determine map elements of the coverage area; the map elements include at least lane lines, road markings, traffic signs, and obstacles; The target map data is determined according to the map elements of the coverage area.

8. The method according to claim 7, characterized in that The step of constructing a coverage area of ​​the target trajectory point based on the target trajectory point, sequentially screening data corresponding to the coverage area in the high-precision map data, and determining map elements of the coverage area includes: A first coverage area is constructed with the navigation starting point as the center, so that a first track point is located within the first coverage area; the first track point is the next track point adjacent to the navigation starting point among the multiple track points, or is a track point among the multiple track points that is along the track running direction and is a preset distance from the navigation starting point; Filtering data corresponding to the first coverage area in the high-precision map data according to the coordinates of the first track point and a vector formed by the navigation start point and the first track point to determine a map element of the first coverage area; Continuing to construct a second coverage area with the first trajectory point as the center, such that a second trajectory point is located within the second coverage area; the second trajectory point is the next trajectory point adjacent to the first trajectory point among the multiple trajectory points, or is a trajectory point among the multiple trajectory points that is along the trajectory running direction and is a preset distance away from the first trajectory point; Filtering data corresponding to the second coverage area in the high-precision map data according to the coordinates of the second track point and a vector formed by the first track point and the second track point to determine a map element of the second coverage area; Until the map element of the last coverage area is determined; wherein the last coverage area is the coverage area corresponding to the last track point among the multiple track points, and the coverage area at least includes the first coverage area, the second coverage area and the last coverage area.

9. The method according to any one of claims 1 to 5, characterized in that The method further comprises: Performing format conversion on the target map data to determine vehicle control data corresponding to the data format of the vehicle control system; The vehicle control data is sent to a vehicle control system, so that the vehicle control system performs navigation based on the vehicle control data.

10. The method according to any one of claims 1 to 5, characterized in that The method is applied to an electronic device, which is communicatively connected to a vehicle system; Get navigation data, including: Obtain the navigation data sent by the vehicle system.

11. A data processing device, characterized in that: The device comprises: An acquisition unit, configured to acquire navigation data, vehicle position coordinates, and vehicle heading angle; the navigation data includes coordinates of a plurality of trajectory points; a determination unit configured to select at least two candidate trajectory points from the plurality of trajectory points; determine a direction weight for each candidate trajectory point based on the vehicle heading angle and the direction of each candidate trajectory point; the direction of each candidate trajectory point representing a vector formed by the candidate trajectory point and the next adjacent candidate trajectory point; determine a distance weight for each candidate trajectory point based on the vehicle position coordinates and the coordinates of each candidate trajectory point; and determine a navigation start point from the at least two candidate trajectory points based on the direction weight and the distance weight of each candidate trajectory point. The screening unit is used to screen the high-precision map data according to the navigation starting point and the track points located after the navigation starting point along the track running direction among the multiple track points to determine the target map data.

12. An electronic device, characterized in that: The device comprises: a memory for storing executable computer programs; The processor is configured to implement the method according to any one of claims 1 to 10 when executing the executable computer program stored in the memory.

13. A computer-readable storage medium, characterized in that A computer program is stored, which is used to implement the method according to any one of claims 1 to 10 when executed by a processor.

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