A map, a map generation method, a map use method, and a map use device

Abstract

The application discloses a map, a map generation method, a map use method and device. The map generation method comprises the following steps: obtaining positioning position information, positioning quality reference information of a group of track points and position information of a plurality of driving areas in a map; determining a driving area (for example, an area, a road or a lane in the map) where the group of track points is located or associated in the plurality of driving areas according to the positioning position information and the position information of the plurality of driving areas; and obtaining a positioning quality statistical value in the driving area based on the positioning quality reference information of the group of track points. Finally, the positioning quality statistical value in the driving area can be added to the map. The application provides a map with better positioning reference, so that a map user can selectively use the positioning information in the map.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a map, a map generation method, a map usage method, and an apparatus. Background Technology

[0002] High-definition maps (HD maps), also known as high-definition maps or high-precision maps, are often used as auxiliary maps for autonomous driving. HD maps contain both static and dynamic information and can be loaded through cloud collaboration, vehicle-to-infrastructure (V2I) communication, and other methods to assist vehicles in perception, localization, planning, and control.

[0003] The generation of high-precision maps relies on location data. Since the collection of this data is easily affected by the surrounding environment, the quality of location data obtained from different map elements (e.g., roads, lanes) in a high-precision map varies. If low-quality location data from a high-precision map is used during autonomous driving, inaccurate positioning can easily cause deviations in the navigation route and even affect vehicle driving safety. Summary of the Invention

[0004] This application discloses a map, a map generation method, a map usage method, and an apparatus, enabling vehicles or portable terminals using the map to selectively use location information in high-precision maps, thereby improving the safety of autonomous driving.

[0005] In a first aspect, embodiments of this application provide a map generation method, which includes: obtaining location information of a set of trajectory points, location quality reference information, and location information of multiple driving areas in a map, wherein the multiple driving areas include regions, roads, or lanes in the map; associating the set of trajectory points with a first driving area among the multiple driving areas based on the location information and the location information of the multiple driving areas, wherein the first driving area is a region, road, or lane in the map; obtaining a location quality statistical value based on the location quality reference information; generating location quality indication information, wherein the location quality indication information is used to indicate that the location quality within the first driving area is the location quality statistical value; and adding the location quality indication information to the map.

[0006] In the above method, by associating a set of trajectory points with a certain driving area in the map, the statistical value obtained based on the positioning quality reference information of the set of trajectory points is used as the positioning quality of the driving area. Compared with the existing technology of maps that only provide location information, this method also provides positioning quality indication information for each driving area in the map. This positioning quality indication information allows map users to choose to avoid driving areas with poor positioning quality, or selectively set a lower confidence level for positioning information with poor positioning quality, thereby improving the safety of vehicle travel.

[0007] In one embodiment of the first aspect, the first trajectory point and the second trajectory point are any two adjacent trajectory points in a set of trajectory points. The process of associating a set of trajectory points with a first driving area in multiple driving areas can be as follows: when the first trajectory point and the second trajectory point are not located at an intersection in the map, and when the vertical distance between the first trajectory point and the first driving area meets a first preset condition, and the heading angle between the heading corresponding to the first trajectory point and the heading of the first driving area meets a second preset condition, the set of trajectory points is associated with the first driving area, where the first driving area is a road or a lane in the map; the heading corresponding to the first trajectory point is the heading from the first trajectory point to the second trajectory point.

[0008] By implementing the above method, for trajectory points outside intersections, the road or lane associated with a set of trajectory points is determined based on the vertical distance from the trajectory point to the driving area and the heading angle between the heading of adjacent trajectory points and the heading of the driving area. This achieves accurate matching between the trajectory points and the roads or lanes in the map, which helps to improve the accuracy and reliability of the positioning quality estimation based on the positioning quality reference information of this set of trajectory points.

[0009] In one embodiment of the first aspect, a set of trajectory points is located within an intersection on a map. The process of associating a set of trajectory points with a first driving area in multiple driving areas can be as follows: associating a set of trajectory points with a first driving area within the intersection. The first driving area is the only road or lane within the intersection that connects a second driving area adjacent to the intersection and a third driving area adjacent to the intersection. A trajectory point preceding a set of trajectory points is located within the second driving area, and a trajectory point following a set of trajectory points is located within the third driving area.

[0010] By implementing the above method, for trajectory points within an intersection, the road (or lane) associated with the trajectory point can be quickly determined based on the connection relationship between the road (or lane) within the intersection and the two roads (or lanes) adjacent to the intersection outside the intersection. This improves the matching efficiency between trajectory points and roads (or lanes) in the map and saves processing time.

[0011] In one embodiment of the first aspect, the first driving area is a road in a map, and the first driving area includes multiple lanes in the map. The method further includes: selecting at least one trajectory point from a set of trajectory points based on the distance from each trajectory point in the set to each lane in the multiple lanes; selecting one lane from the multiple lanes, wherein the lane is the lane in the multiple lanes that is closest to each of the at least one trajectory point; obtaining lane positioning quality statistics based on positioning quality reference information of the at least one trajectory point; generating lane positioning quality indication information, wherein the lane positioning quality indication information is used to indicate that the positioning quality within a lane is the lane positioning quality statistics; and adding the lane positioning quality indication information to the map.

[0012] By implementing the above method, for trajectory points outside intersections, if a set of trajectory points is determined to be associated with a road (e.g., the target road) on the map, the lanes associated with the trajectory points among multiple lanes on the target road can be quickly determined based solely on the vertical distance. This improves the matching efficiency and accuracy between trajectory points and lanes on the map, and saves processing time.

[0013] In one embodiment of the first aspect, the process of associating a set of trajectory points with a first driving area in multiple driving areas may be: determining that a set of trajectory points are located within a first driving area based on the location information of a set of trajectory points and the coordinates of multiple corner points in the first driving area, wherein the first driving area is an area in a map; and associating a set of trajectory points with the first driving area.

[0014] By implementing the above method, it is possible to quickly determine whether a trajectory point is associated with the first driving area simply by judging whether the location information of the trajectory point is within the first driving area. This improves the matching efficiency and accuracy of the trajectory point and the area in the map, and saves processing time.

[0015] Secondly, embodiments of this application provide a map usage method, which includes: receiving positioning quality indication information and driving area indication information from the map, wherein the positioning quality indication information is used to indicate the positioning quality within the driving area, the driving area indication information is used to indicate the driving area, the driving area is a region, road or lane in the map, and the positioning quality within the driving area is the statistical value of the positioning quality of multiple trajectory points within the driving area; and performing route planning, driving decision-making or vehicle control based on the positioning quality indication information and the driving area indication information.

[0016] The above method provides a map that includes positioning quality indication information and driving area indication information, enabling the terminal to avoid driving areas with poor positioning quality in a timely manner based on the map, and thus drive in driving areas with good positioning quality (e.g., roads, lanes, etc.), thereby obtaining accurate positioning information, which is beneficial to improving the accuracy of route planning, driving decisions, and travel safety.

[0017] In one embodiment of the second aspect, positioning quality indication information is displayed on a display device.

[0018] By implementing the above method, the positioning quality indication information in the map can be displayed intuitively and clearly.

[0019] In one embodiment of the second aspect, the positioning quality statistics include average positioning accuracy, average precision factor (DOP) value, average number of observable satellites, or statistics on whether the positioning position of a trajectory point is a fixed solution.

[0020] Among them, the average positioning accuracy is the standard deviation of the error of multiple position information relative to the reference true value. The smaller the average positioning accuracy, the better the positioning quality. The larger the average number of observable satellites, the better the positioning quality. The average precision factor DOP is used to measure the average error caused by the geometric position of the satellite relative to the observer (e.g., the data acquisition vehicle collecting the location point). The smaller the average precision factor DOP, the better the positioning quality. The positioning quality when the positioning position is a fixed solution is better than the positioning quality when the positioning position is a non-fixed solution. A fixed solution means that the ambiguity corresponding to the positioning position calculated based on the carrier phase is an integer.

[0021] Thirdly, embodiments of this application provide a map that includes positioning quality indication information and driving area indication information. The positioning quality indication information is used to indicate the positioning quality within the driving area, and the driving area indication information is used to indicate the driving area. The driving area is a region, road, or lane in the map, and the positioning quality within the driving area is the statistical value of the positioning quality of multiple trajectory points within the driving area.

[0022] The aforementioned map provides valuable and reliable information on the positioning quality of driving areas, offering map users more accurate prior information on the positioning quality of driving areas within the map.

[0023] In one embodiment of the third aspect, the positioning quality statistics include average positioning accuracy, average precision factor (DOP) value, average number of observable satellites, or statistics on whether the positioning position of the trajectory point is a fixed solution.

[0024] In one embodiment of the third aspect, the map also includes time information, which is used to indicate the effective time of positioning quality within the driving area.

[0025] By implementing the above method, the introduction of time information fully considers the impact of the surrounding environment (e.g., vegetation changes with seasons and climate) on positioning quality. Based on the time information, the effective time of positioning quality within the driving area is limited, which improves the reliability and reference value of positioning quality indication information.

[0026] Fourthly, embodiments of this application provide a map generation device, comprising: an acquisition unit, configured to acquire location information of a set of trajectory points, location quality reference information, and location information of multiple driving areas in a map, wherein the multiple driving areas include regions, roads, or lanes in the map; an association unit, configured to associate a set of trajectory points with a first driving area among the multiple driving areas based on the location information and the location information of the multiple driving areas, wherein the first driving area is a region, road, or lane in the map; a calculation unit, configured to obtain a location quality statistical value based on the location quality reference information; a processing unit, configured to generate location quality indication information, wherein the location quality indication information is used to indicate that the location quality within the first driving area is the location quality statistical value; and the processing unit is further configured to add the location quality indication information into the map. Typically, maps are generated by a server, so the map generation device can be a map server, or a component or chip within the map server. Furthermore, maps may also be generated by roadside equipment, vehicles, or mobile terminals, so the map generation device can also be the roadside equipment, vehicle, or mobile terminal, or a component or chip within the roadside equipment, vehicle, or mobile terminal.

[0027] In one embodiment of the fourth aspect, the first trajectory point and the second trajectory point are any two adjacent trajectory points in a set of trajectory points. The association unit is specifically used to: in one embodiment of the second aspect, when the first trajectory point and the second trajectory point are not located at an intersection in the map, and when the vertical distance between the first trajectory point and the first driving area meets a first preset condition, and the heading angle between the heading corresponding to the first trajectory point and the heading of the first driving area meets a second preset condition, associate a set of trajectory points with the first driving area, where the first driving area is a road or a lane in the map; the heading corresponding to the first trajectory point is the heading from the first trajectory point to the second trajectory point.

[0028] In one embodiment of the fourth aspect, a set of trajectory points is located within an intersection on a map, and the association unit is specifically used to: associate a set of trajectory points with a first driving area within the intersection, wherein the first driving area is the only road or lane within the intersection that connects a second driving area adjacent to the intersection and a third driving area adjacent to the intersection, wherein a trajectory point preceding a set of trajectory points is located within the second driving area, and a trajectory point following a set of trajectory points is located within the third driving area.

[0029] In one embodiment of the fourth aspect, the first driving area is a road in a map, the first driving area includes multiple lanes in the map, the association unit is further configured to select at least one trajectory point from the set of trajectory points and select one lane from the multiple lanes based on the distance from each trajectory point in the set of trajectory points to each lane in the multiple lanes, the lane being the lane closest to each of the at least one trajectory point in the multiple lanes; the calculation unit is further configured to obtain lane positioning quality statistics based on positioning quality reference information of at least one trajectory point; the processing unit is further configured to generate lane positioning quality indication information, the lane positioning quality indication information being used to indicate the positioning quality within a lane as the lane positioning quality statistics value; and add the lane positioning quality indication information to the map.

[0030] In one embodiment of the fourth aspect, the association unit is specifically used to: determine that a set of trajectory points are located within a first driving area, where the first driving area is a region on a map, based on the location information of a set of trajectory points and the coordinates of multiple corner points of the first driving area; and associate the set of trajectory points with the first driving area.

[0031] Fifthly, embodiments of this application provide a map-using device, which includes: a receiving unit for receiving positioning quality indication information and driving area indication information from a map, wherein the positioning quality indication information is used to indicate the positioning quality within a driving area, and the driving area indication information is used to indicate the driving area, wherein the driving area is a region, road, or lane in the map, and the positioning quality within the driving area is a statistical value of the positioning quality of multiple trajectory points within the driving area; and a processing unit for performing route planning, driving decisions, or vehicle control based on the positioning quality indication information and the driving area indication information.

[0032] The map can be used on a vehicle, or on a component that can be used inside a vehicle (such as a navigation device or an autonomous driving device), or on a chip that can be used inside a vehicle.

[0033] In one embodiment of the fifth aspect, the device further includes a display unit for displaying positioning quality indication information in a map.

[0034] In one embodiment of the fifth aspect, the positioning quality statistics include average positioning accuracy, average accuracy factor (DOP) value, average number of observable satellites, or statistics on whether the positioning position of a trajectory point is a fixed solution.

[0035] Sixthly, embodiments of this application provide a map usage method, the method comprising: receiving a map, the map including positioning quality indication information and driving area indication information, the positioning quality indication information being used to indicate the positioning quality within a driving area, the driving area indication information being used to indicate the driving area, the driving area being a region, road or lane in the map, and the positioning quality within the driving area being a statistical value of the positioning quality of multiple trajectory points within the driving area; storing the map, or displaying the map on a display device.

[0036] In the above method, the received map is stored so that it can be quickly retrieved at any time later, and the map is displayed on the display device so that users can intuitively and clearly understand the positioning quality of each driving area in the map.

[0037] In one embodiment of the sixth aspect, navigation route planning, driving decisions, or vehicle control are performed based on positioning quality indication information and driving area indication information.

[0038] By implementing the above method, based on positioning quality indication information and driving area indication information, the positioning quality of each driving area in the map can be quickly known. This allows for timely avoidance of driving areas with poor positioning quality during driving, while driving in areas with better positioning quality. This helps improve the accuracy of navigation route planning, driving decisions, or vehicle control.

[0039] Seventhly, embodiments of this application provide a map-using device, comprising: a receiving unit for receiving a map, the map including positioning quality indication information and driving area indication information, the positioning quality indication information indicating positioning quality within a driving area, the driving area indicating a driving area (a region, road, or lane in the map), and the positioning quality within the driving area being statistical values ​​of positioning quality from multiple trajectory points within the driving area; a storage unit for storing the map; and a display unit for displaying the map. This map-using device can be a vehicle, a component usable within a vehicle (such as a navigation device or autonomous driving device within a vehicle), or a chip usable within a vehicle.

[0040] In one embodiment of the seventh aspect, the device further includes a processing unit for planning navigation routes, making driving decisions, or controlling the vehicle based on positioning quality indication information and driving area indication information.

[0041] Eighthly, embodiments of this application provide a computer program product including a map. The map includes positioning quality indication information and driving area indication information. The positioning quality indication information is used to indicate the positioning quality within a driving area, and the driving area indication information is used to indicate the driving area. The driving area is a region, road, or lane in the map, and the positioning quality within the driving area is a statistical value of the positioning quality of multiple trajectory points within the driving area.

[0042] In one embodiment of the eighth aspect, the positioning quality statistics include average positioning accuracy, average accuracy factor (DOP) value, average number of observable satellites, or statistics on whether the positioning position of the trajectory point is a fixed solution.

[0043] In one embodiment of the eighth aspect, the map also includes time information, which is used to indicate the effective time of positioning quality within the driving area.

[0044] Ninthly, embodiments of this application provide a computer-readable storage medium for storing a map, the map including positioning quality indication information and driving area indication information, the positioning quality indication information indicating positioning quality within a driving area, the driving area indicating a driving area, the driving area being a region, road or lane in the map, and the positioning quality within the driving area being a statistical value of the positioning quality of multiple trajectory points within the driving area.

[0045] In one embodiment of the ninth aspect, the positioning quality statistics include average positioning accuracy, average precision factor (DOP) value, average number of observable satellites, or statistics on whether the positioning position of the trajectory point is a fixed solution.

[0046] In one embodiment of the ninth aspect, the map further includes time information used to indicate the effective time of positioning quality within the driving area.

[0047] In a tenth aspect, embodiments of this application provide a map generation apparatus, which includes a processor and a memory, connected or coupled together via a bus; wherein the memory stores program instructions; the processor invokes the program instructions in the memory to execute the method in the first aspect or any possible implementation thereof. Typically, maps are generated by a server, so the map generation apparatus can be a map server, or a component or chip within the map server. Furthermore, maps may also be generated by roadside equipment, vehicles, or mobile terminals, in which case the map generation apparatus can also be the roadside equipment, vehicle, or mobile terminal, or a component or chip within the roadside equipment, vehicle, or mobile terminal.

[0048] Eleventhly, embodiments of this application provide a map-using device, which includes a processor and a memory, the processor and the memory being connected or coupled together via a bus; wherein the memory is used to store program instructions; the processor calls the program instructions in the memory to execute the method in the second aspect or any possible implementation of the second aspect. This map-using device can be a vehicle, a component usable within a vehicle (such as a navigation device or autonomous driving device within a vehicle), or a chip usable within a vehicle.

[0049] In a twelfth aspect, embodiments of this application provide a map-using device, which includes a processor and a memory, the processor and the memory being connected or coupled together via a bus; wherein the memory is used to store program instructions; the processor invokes the program instructions in the memory to execute the method in the sixth aspect or any possible implementation thereof. This map-using device can be a vehicle, a component usable within a vehicle (such as a navigation device or autonomous driving device within a vehicle), or a chip usable within a vehicle.

[0050] In a thirteenth aspect, embodiments of this application provide a computer-readable storage medium storing program code for execution by a device, the program code including instructions for performing the method in the first aspect or any possible implementation of the first aspect.

[0051] In a fourteenth aspect, embodiments of this application provide a computer-readable storage medium storing program code for execution by a device, the program code including instructions for performing the method in the second aspect or any possible implementation of the second aspect.

[0052] In a fifteenth aspect, embodiments of this application provide a computer-readable storage medium storing program code for execution by a device, the program code including instructions for performing the method in the sixth aspect or any possible implementation thereof.

[0053] In a sixteenth aspect, embodiments of this application provide a computer program product that, when executed by a processor, implements the method described in the first aspect or any possible implementation thereof. The computer program product may be, for example, a software installation package. When the method provided by any possible design of the first aspect is required, the computer program product can be downloaded and executed on a processor to implement the method described in the first aspect or any possible embodiment thereof.

[0054] In a seventeenth aspect, embodiments of this application provide a computer program product that, when executed by a processor, implements the methods of the second aspect or any possible implementation thereof. The computer program product may, for example, be a software installation package. When the methods provided by any possible design of the second aspect are required, the computer program product can be downloaded and executed on a processor to implement the methods of the second aspect or any possible embodiment thereof.

[0055] In an eighteenth aspect, embodiments of this application provide a computer program product that, when executed by a processor, implements the method in the sixth aspect or any possible implementation thereof. The computer program product may be, for example, a software installation package. When the method provided by any possible design of the sixth aspect is required, the computer program product can be downloaded and executed on a processor to implement the method in the sixth aspect or any possible embodiment thereof.

[0056] In a nineteenth aspect, embodiments of this application provide a vehicle that includes a map-using device as described in aspects five, seven, eleven, or twelve above, or a map-using device that includes any possible implementation of aspects five, seven, eleven, or twelve above. Attached Figure Description

[0057] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a schematic diagram of a system architecture provided in an embodiment of this application;

[0059] Figure 2 It is a regional schematic diagram of a high-precision map;

[0060] Figure 3 This is a flowchart illustrating a method for associating trajectory points with road IDs in a high-precision map, as provided in an embodiment of this application.

[0061] Figure 4 This is a regional-road schematic diagram provided in an embodiment of this application;

[0062] Figure 5 This is yet another area-road diagram provided in the embodiments of this application;

[0063] Figure 6This is a flowchart illustrating a method for associating trajectory points with lane IDs in a high-precision map, as provided in an embodiment of this application.

[0064] Figure 7 This is a road-lane diagram provided in an embodiment of this application;

[0065] Figure 8A This is yet another road-lane diagram provided in the embodiments of this application;

[0066] Figure 8B This is yet another road-lane diagram provided in the embodiments of this application;

[0067] Figure 9 This is a flowchart of a map generation method provided in an embodiment of this application;

[0068] Figure 10 This is a flowchart of a map usage method provided in an embodiment of this application;

[0069] Figure 11 This is a schematic diagram of an application scenario provided in this application and this embodiment;

[0070] Figure 12 This is a schematic diagram of the structure of a map generation device provided in this application and this embodiment;

[0071] Figure 13 This is a schematic diagram of the structure of a map-using device provided in this application and this embodiment;

[0072] Figure 14 This is a functional structure diagram of a map generation device provided in this application and this embodiment;

[0073] Figure 15 This is a functional structure diagram of a map-using device provided in this embodiment of the application. Detailed Implementation

[0074] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. Terms such as "first," "second," etc., in the specification and claims of this application are used to distinguish different objects, not to describe a particular order.

[0075] High-definition maps are auxiliary maps for autonomous driving. They display regions, roads, and lanes. Lanes can be upstream or downstream lanes, each with a unique lane ID. Each road segment includes multiple lanes, each with a unique road ID. Each region includes multiple road segments, each with a unique region ID. High-definition maps also include intersections, which can be crossroads and contain roads and lanes. Furthermore, they display the connections between roads and between lanes. It's important to note that each region in a high-definition map has a corresponding area boundary. For example, the coordinates of the four corner points of a region (e.g., latitude and longitude coordinates) determine the area boundary; each road has a corresponding road boundary, for example, the coordinates of the road's starting and ending points determine the road's boundary, and the starting and ending points also determine the road's centerline; each lane has a corresponding lane boundary, for example, the coordinates of the lane's starting and ending points determine the lane's boundary, and the starting and ending points also determine the lane's centerline; each intersection has a corresponding intersection boundary, for example, the coordinates of multiple corner points of an intersection (e.g., latitude and longitude coordinates) determine the intersection's boundary. In addition, high-definition maps also display parameters such as road slope, curvature, and heading.

[0076] The generation of high-precision maps relies on location data. The quality of this data is easily affected by the surrounding environment (e.g., tall buildings and trees) and satellite obstruction. For example, the more tall buildings and trees along a road, the more severe the satellite signal obstruction, resulting in greater deviations and lower quality of the location data collected on that road. Therefore, the quality of location data obtained from different map elements (e.g., roads, lanes) in a high-precision map varies. If low-quality location data from a high-precision map is used during autonomous driving, inaccurate positioning can easily cause navigation route deviations and even affect vehicle driving safety.

[0077] To address the aforementioned issues, this application proposes a positioning quality indication information. This information provides highly reliable and valuable positioning quality data, enabling map users to avoid driving areas with poor positioning quality and instead drive in areas with better positioning quality (e.g., roads, lanes). This allows them to obtain accurate positioning data, improving the accuracy of route planning, driving decisions, and overall travel safety.

[0078] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0079] See Figure 1 , Figure 1An exemplary system architecture diagram is provided. This system is used to generate positioning quality indication information, or to generate a map containing positioning quality indication information. Figure 1 As shown, the system includes a data acquisition device, a mapping device, and a terminal. The data acquisition device and the mapping device can be connected wirelessly or via wired means, and the mapping device and the terminal can be connected wirelessly.

[0080] Data acquisition equipment is typically mounted on a data acquisition vehicle. This equipment collects the raw data needed to generate positioning quality indication information. The data acquisition equipment can be an RTK device, which includes either GPS or GNSS, and obtains positioning information based on RTK measurement methods. For example, an RTK device can record the position and quality information of each trajectory point collected by the data acquisition vehicle as it travels in each lane. The quality information of each position point is used to indicate the positioning quality at that point.

[0081] The mapping device is used to generate positioning quality indication information based on multiple location and quality information of a set of trajectory points and the location information of multiple driving areas on the map. This positioning quality indication information is used to indicate the positioning quality of the driving areas. The driving areas are regions, roads, or lanes on the map. The mapping device can be a device with computing capabilities, such as a computer, server, or multi-access edge computing (MEC).

[0082] The terminal can be a vehicle, such as a regular vehicle or an autonomous vehicle. Vehicles can refer to cars, automobiles, tour buses, bicycles, tricycles, electric vehicles, motorcycles, trucks, etc. Vehicles can also be electric vehicles, hybrid electric vehicles, range-extended electric vehicles, plug-in hybrid electric vehicles, etc. In addition, the terminal can also be a roadside unit (RSU), an on-board unit (OBU), a portable mobile device (e.g., a mobile phone, a tablet, etc.), or other sensors or devices such as components or chips of a portable mobile device that can communicate with the mapping equipment. The embodiments of this application do not make specific limitations.

[0083] It should be noted that, Figure 1 This is merely an illustrative architecture diagram and is not intended to limit the scope of the invention. Figure 1 The system shown includes the number of network elements. Although Figure 1 Not shown, but except Figure 1 In addition to the functional entities shown, Figure 1 It may also include other functional entities. Furthermore, the method provided in the embodiments of this application can be applied to… Figure 1The communication system shown is applicable to other communication systems as well, and this application does not limit this application.

[0084] It should be noted that, for ease of description, the terminal in the following description may be a vehicle as an example of the solution, but the embodiments of this application do not limit the terminal to only vehicles.

[0085] It should be noted that the trajectory points are collected in advance by a data acquisition vehicle equipped with RTK equipment while driving along various lanes in the high-precision map. Each trajectory point has corresponding location information and quality information. The location information indicates the trajectory point's position in the high-precision map, and includes longitude and latitude coordinates. The quality information includes one or more of the following: the number of observable satellites at the location point, the Dilution of Precision (DOP) value, whether the location information is a fixed solution, and the offset of the location point relative to the true value in the east, north, and vertical directions. The quality information of the trajectory point can be used to measure the positioning quality of that trajectory point in the high-precision map.

[0086] The process of associating trajectory points specifically includes three parts:

[0087] Part 1: Associating trajectory points with region IDs in high-precision maps

[0088] Specifically, each region ID in a high-definition map indicates a specific area within the map, and the area range corresponding to each region ID is determined by the coordinates of multiple corner points within that area. For each trajectory point among multiple trajectory points, each trajectory point is sequentially compared with the area range corresponding to each region ID in the high-definition map based on its positional information. When a trajectory point is located within the area range corresponding to the target region ID in the high-definition map, the trajectory point is associated with the target region ID. Thus, the trajectory points corresponding to each region ID can be obtained. It should be noted that the process of determining whether a trajectory point is within the area indicated by a certain region ID can also be called the process of determining the positional relationship between the trajectory point and the area indicated by the region ID.

[0089] In some possible embodiments, since the areas in the high-definition map are divided multiple times according to a cross shape, there are several levels of areas in the high-definition map. The higher the level of the area, the larger the area it corresponds to. Each area has a unique area ID. It can be understood that a higher-level area in the high-definition map includes multiple lower-level areas; that is, a higher-level area ID corresponds to multiple lower-level area IDs. Therefore, when there are area IDs of different levels in the high-definition map, a trajectory point can be associated with multiple area IDs of different levels. In the case of multiple levels of area IDs in the high-definition map, in the embodiments of this application, the area ID associated with the trajectory point in the high-definition map is a lower-level area ID. The area indicated by the lower-level area ID is the smallest unit of area division in the high-definition map.

[0090] In a specific implementation, when there are multiple levels of distinct IDs in a high-precision map, the trajectory point can be directly compared with the positional relationship of each lower-level area ID in the high-precision map to determine the area ID associated with the trajectory point.

[0091] In another specific implementation, when there are multiple levels of distinguishing IDs in the high-precision map, the correlation between the trajectory point and the high-level area ID in the high-precision map can be determined first, and then the correlation between the trajectory point and the corresponding low-level area IDs can be determined, which effectively shortens the time consumed in determining the area ID in the high-precision map associated with the trajectory point.

[0092] In some possible embodiments, in addition to associating the trajectory point with the low-level area ID in the high-definition map, the trajectory point can also be associated with the high-level area ID in the high-definition map based on the correspondence between the low-level area ID and the high-level area ID in the high-definition map, thereby obtaining all area IDs associated with the trajectory point in the high-definition map.

[0093] See Figure 2 , Figure 2 It is a schematic diagram of the regional division of a high-precision map, such as... Figure 2As shown, there are two levels of area IDs in the high-precision map. The area IDs corresponding to one level are: 1-00, 1-01, 1-10 and 1-11. The area IDs belonging to the other level are 1-00-00, 1-00-01, 1-00-10 and 1-00-11 (these four correspond to 1-00), 1-01-00, 1-01-01, 1-01-10 and 1-01-11 (these four correspond to 1-01), 1-10-00, 1-10-01, 1-10-10 and 1-10-11 (these four correspond to 1-10), and 1-11-00, 1-11-01, 1-11-10 and 1-11-11 (these four correspond to 1-11), totaling 16 area IDs. Taking 1-00 and 1-00-01 as examples, it can be seen that the region level of 1-00 is higher than that of 1-00-01. The region's boundaries can be determined by the coordinates of its four corner points; that is, the rectangle defined by the coordinates of the four corner points of each region is the region's boundaries.

[0094] Taking trajectory point 1 as an example, the position information of trajectory point 1 is first sequentially compared with... Figure 2 The system compares the corresponding area ranges of 16 lower-level area IDs until it determines that trajectory point 1 falls within the area indicated by one of the 16 lower-level area IDs. For example, if trajectory point 1 is determined not to be within the area indicated by 1-00-00, it continues to check if trajectory point 1 is within the area indicated by 1-00-01, that is, whether trajectory point 1 is within the area defined by the four corner coordinates corresponding to 1-00-10. If trajectory point 1 is within the area indicated by 1-00-101, it is associated with area ID "1-00-01". If trajectory point 1 is not within the area indicated by 1-00-01, it continues to compare the positional relationship between trajectory point 1 and the areas indicated by the remaining lower-level area IDs until an area ID associated with trajectory point 1 is found.

[0095] In some possible embodiments, if trajectory point 1 is determined to be associated with 1-00-01, it can also be determined that... Figure 2 The high-level area ID associated with trajectory point 1 can also be associated with area ID "1-00" because there is a correspondence between the low-level area ID "1-00-01" and the high-level area ID "1-00" in the high-precision map.

[0096] For example, taking trajectory point 1 as an example, trajectory point 1 can also be first compared with... Figure 2 Positional relationships are determined within regions indicated by medium- to high-level region IDs (i.e., 1-00, 1-01, 1-10, and 1-11). Assuming trajectory point 1 is located within the region indicated by 1-00, in... Figure 2In the middle, since 1-00 corresponds to the lower-level region IDs "1-00-00, 1-00-01, 1-00-10, and 1-00-11", further, trajectory point 1 is associated with... Figure 2 The location relationship is determined by the area indicated by the lower-level area IDs (i.e., 1-00-00, 1-00-01, 1-00-10 and 1-00-11) corresponding to 1-00. Assuming that the trajectory point 1 is located in the area indicated by 1-00-01, the trajectory point 1 is associated with the area ID "1-00-01".

[0097] In some possible embodiments, the set 1 of the smallest region containing the longitude coordinate in the high-precision map can be determined based on the longitude coordinate in the location information of the trajectory point, and the set 2 of the smallest region containing the latitude coordinate in the high-precision map can be determined based on the latitude coordinate in the location information of the trajectory point. Finally, the region ID obtained by finding the intersection of set 1 and set 2 is the region ID associated with the trajectory point in the high-precision map.

[0098] Part Two: Associating Track Points with Road IDs in High-Precision Maps

[0099] Each trajectory point is associated with only one road ID in the high-definition map. The association between a trajectory point and a road ID in the high-definition map means that the trajectory point is located on the road indicated by that road ID in the high-definition map.

[0100] In a specific implementation, the area ID associated with the trajectory point in the high-precision map can be determined from the first part mentioned above. Since the area ID in the high-precision map includes multiple road segments, and each road segment has a unique road ID, multiple road IDs corresponding to the area ID in the high-precision map can be obtained, greatly reducing the number of road IDs to be compared and improving processing efficiency. Then, based on the location information of the trajectory point and the endpoint coordinates corresponding to each of the multiple road IDs, the road ID uniquely associated with the trajectory point is determined from the multiple road IDs.

[0101] In another specific implementation, the road IDs in the high-precision map can be obtained directly. Based on the location information of the trajectory point and the endpoint coordinates corresponding to each road ID in the high-precision map, the road ID uniquely associated with the trajectory point can be determined from each road ID.

[0102] See Figure 3 , Figure 3 This is a flowchart illustrating a method for determining the association between a trajectory point and a road ID, provided in an embodiment of this application. Taking trajectory point 1 as an example, the process of associating the trajectory point with the road ID in a high-precision map will be described. This method includes, but is not limited to, the following steps:

[0103] S11. Obtain multiple road IDs corresponding to the region ID1 where trajectory point 1 is located.

[0104] The area where trajectory point 1 is located is the area indicated by the low-level area ID1 associated with trajectory point 1 mentioned above. The area indicated by the low-level area ID1 is the smallest area division unit in the high-definition map. After determining the area ID1 where trajectory point 1 is located, since the high-definition map stores the mapping information between area IDs and road IDs, multiple road IDs corresponding to area ID1 can be obtained from the high-definition map based on area ID1.

[0105] S12. Determine whether trajectory point 1 is within the intersection in the high-precision map.

[0106] Specifically, each intersection in the high-precision map has a corresponding coordinate range, which is determined by the corner points (or inflection points) of the intersection. For each intersection in the high-precision map, it is determined whether trajectory point 1 is within the coordinate range of any intersection. If trajectory point 1 is not within the coordinate range of any intersection, it means that trajectory point 1 is not within any intersection in the high-precision map, and S13 is executed; if it is determined that trajectory point 1 is within the coordinate range of an intersection (for example, intersection 1), it means that trajectory point 1 is within an intersection in the high-precision map, and S16 is executed.

[0107] S13. Based on the location information of trajectory point 1 and the starting and ending coordinates of multiple road IDs, perform an initial screening of these multiple road IDs to obtain a set 1 of road IDs that meet the preset condition 1.

[0108] Optionally, if trajectory point 1 is not located within the intersection, the start-point and end-point coordinates corresponding to the road ID can be obtained from the high-precision map. The start-point coordinates represent the starting point of the road indicated by the road ID, and the end-point coordinates represent the ending point of the road indicated by the road ID. Based on the location information of trajectory point 1 and the start-point and end-point coordinates corresponding to multiple road IDs, multiple road IDs are filtered to obtain a set 1 of road IDs that meet the preset condition 1.

[0109] The start and end coordinates corresponding to the road ID are the start and end coordinates of the road centerline indicated by the road ID. The start and end points of the road corresponding to the road ID are defined based on the vehicle's direction of travel on the road; that is, the position where a vehicle enters the road is called the start point, and the position where a vehicle leaves the road is called the end point. It should be noted that both the start and end coordinates corresponding to the road ID are represented by longitude and latitude.

[0110] Let's take road ID1 as an example to illustrate preset condition 1. Based on the location information of trajectory point 1 and the starting and ending coordinates of road ID1, we can determine whether trajectory point 1 is within the coordinate range corresponding to road ID1. If trajectory point 1 is within the coordinate range corresponding to road ID1, then road ID1 meets preset condition 1; if trajectory point 1 is not within the coordinate range corresponding to road ID1, then road ID1 does not meet preset condition 1. Therefore, we sequentially compare trajectory point 1 with each of the multiple road IDs, and initially filter out a set 1 of road IDs that meet preset condition 1 from the multiple road IDs.

[0111] The statement that road ID1 meets preset condition 1 (or that trajectory point 1 is located within the coordinate range corresponding to road ID1) means that: the longitude coordinates of trajectory point 1 are located within the longitude range determined by the longitude of the starting coordinates and the longitude of the ending coordinates of road ID1, or the latitude coordinates of trajectory point 1 are located within the latitude range determined by the latitude of the starting coordinates and the latitude of the ending coordinates of road ID1.

[0112] See Figure 4 , Figure 4 This is a schematic diagram of a region-road scene provided in an embodiment of this application. Figure 4 The image shows 11 road segments within a certain area on a high-precision map. Roads 1, 2, 3, and 4 are connected to each other; roads 5, 6, 7, and 8 are connected to each other; and roads 9, 10, and 11 are connected to each other. Only roads 3, 7, and 11 are located within the intersection plane. Figure 4 The black triangles in the diagram represent points on the trajectory. It should be noted that... Figure 4 The road shown can be considered as the centerline of the corresponding road.

[0113] Assumption Figure 4 The area shown is area ID1 in S11 above. Since there are 11 road segments in area ID1, there are also 11 road IDs corresponding to area ID1. Trajectory point 1 is located outside the intersection. Trajectory point 1 is compared with... Figure 4 From the 11 road IDs, a set 1 of road IDs that meets preset condition 1 is selected. Based on the above explanation of preset condition 1, it is easy to see that trajectory point 1 is located within the coordinate range corresponding to roads 1, 5, 10, and 3. Since trajectory point 1 is not located within the intersection, while road 3 is, the selected set 1 of road IDs for trajectory point 1 includes roads 1, 5, and 10.

[0114] It should be noted that by filtering multiple road segments within the area where the trajectory point is located through preset condition 1, roads within the area that do not meet the conditions are quickly eliminated, which greatly reduces the number of road IDs to be processed subsequently, effectively saves the consumption of computing resources, and accelerates the processing speed of determining the road ID associated with the trajectory point.

[0115] S14. Calculate the distance from trajectory point 1 to the road indicated by each road ID in the road ID set 1, and calculate the heading corresponding to trajectory point 1 based on the adjacent trajectory points of trajectory point 1, as well as the heading angle between the heading corresponding to trajectory point 1 and the heading of each road.

[0116] If trajectory point 1 is not located within the intersection, let's take road i as an example to illustrate the three items that need to be calculated in this step, where road i is any road ID in the road ID set 1:

[0117] The first item is the distance from trajectory point 1 to the road indicated by road i: the distance from trajectory point 1 to the road indicated by road i is the perpendicular distance from trajectory point 1 to the center line of road i. The center line of road i can be determined by the starting coordinates and the ending coordinates of road i.

[0118] The second item, the heading corresponding to trajectory point 1: The heading corresponding to trajectory point 1 is calculated based on the position information of trajectory point 1 and the position information of its adjacent trajectory points. Since the trajectory points are collected in a chronological order, the adjacent trajectory points can be either the previous or the next adjacent trajectory point; this application does not impose a specific limitation. When the adjacent trajectory point of trajectory point 1 is the previous adjacent trajectory point, the heading corresponding to trajectory point 1 is the direction from the previous adjacent trajectory point to trajectory point 1; when the adjacent trajectory point of trajectory point 1 is the next adjacent trajectory point, the heading corresponding to trajectory point 1 is the direction from trajectory point 1 to the next adjacent trajectory point.

[0119] For example, see Figure 4 , Figure 4 The diagram also shows trajectory point 2, which is the next adjacent trajectory point of trajectory point 1. Therefore, the heading corresponding to trajectory point 1 is the heading from trajectory point 1 to trajectory point 2.

[0120] The third item is the heading angle between the heading of trajectory point 1 and the heading of road i: The heading of trajectory point 1 can be obtained from the second item above, while the heading of road i can be calculated based on the coordinates of the starting point and ending point of road i. Finally, the heading angle between the two is calculated based on the heading of trajectory point 1 and the heading of road i. Here, the road heading represents the direction from the starting point of the road to its ending point. In some possible embodiments, the road heading can also be obtained directly from a high-precision map; this application does not impose specific limitations on this embodiment.

[0121] Therefore, by performing the above steps on each road ID in the road ID set 1, we can obtain the vertical distance (hereinafter referred to as "vertical distance") from trajectory point 1 to the road indicated by each road ID in the road ID set 1, and the heading angle (hereinafter referred to as "heading angle") between the heading corresponding to trajectory point 1 and the heading of each road. Thus, we can see that each road ID in the road ID set 1 corresponds to a vertical distance and a heading angle.

[0122] S15. Based on preset condition 2, filter each road ID in road ID set 1 to determine the road ID that is uniquely associated with trajectory point 1 in road ID set 1.

[0123] Specifically, since each road ID in the road ID set 1 corresponds to a vertical distance and a heading angle, it is determined whether the vertical distance and heading angle corresponding to each road ID in the road ID set 1 meet the preset condition 2, and the target road ID that meets the preset condition 2 is taken as the road ID in the road ID set 1 that is uniquely associated with the trajectory point 1.

[0124] In a specific implementation, the preset condition 2 can be: in the road ID set 1, the vertical distance corresponding to the target road ID is the smallest and the heading angle corresponding to the target road ID is the smallest.

[0125] In another specific implementation, the preset condition 2 can be: the vertical distance corresponding to the target road ID is less than or equal to a preset distance threshold and the heading angle corresponding to the target road ID is less than or equal to a preset angle threshold.

[0126] For example, with Figure 4 For example, suppose Figure 4Roads 1 and 10 are both downstream roads (i.e., vehicles travel from left to right), while road 5 is an upstream road (i.e., vehicles travel from right to left). This indicates that roads 1 and 10 travel in the same direction, while roads 1 and 10 travel in the opposite direction to road 5. From S13 above, we know that the road ID set 1 for trajectory point 1 includes roads 1, 5, and 10. Based on S14 above, we calculate the vertical distance and heading angle for each road in roads 1, 5, and 10. Assuming the vertical distance for road 1 is distance 1 and the heading angle for road 1 is 0 degrees, the vertical distance for road 5 is distance 5 and the heading angle for road 5 is 180 degrees, and the vertical distance for road 10 is distance 10 and the heading angle for road 10 is 0 degrees, and distance 10 > distance 5 > distance 1, it is easy to see that road 1 has the shortest vertical distance and the smallest heading angle in the road ID set 1 for trajectory point 1. Therefore, road 1 is determined as the road ID uniquely associated with trajectory point 1 in the high-precision map.

[0127] S16. Based on the first road ID adjacent to the intersection where the previous trajectory point of trajectory point 1 is located and the second road ID adjacent to the intersection where the subsequent trajectory point of trajectory point 1 is located, determine the road ID uniquely associated with trajectory point 1.

[0128] Specifically, when trajectory point 1 is located within an intersection, since the connection between each road segment within the intersection and the two adjacent road segments outside the intersection in the high-precision map is uniquely determined, the unique road ID associated with trajectory point 1 can be determined based on the ID of the first road adjacent to the intersection where the previous trajectory point of trajectory point 1 is located and the ID of the second road adjacent to the intersection where the subsequent trajectory point of trajectory point 1 is located.

[0129] In this case, neither the preceding nor following trajectory point of trajectory point 1 is located within the intersection, and the first road ID is different from the second road ID. It should be noted that the road indicated by the first road ID is equivalent to the road leading into the intersection where trajectory point 1 is located, while the road indicated by the second road ID is equivalent to the road leading out of the intersection where trajectory point 1 is located.

[0130] It is understandable that the acquisition time of the preceding trajectory point of trajectory point 1 is earlier than the acquisition time of trajectory point 1, and the acquisition time of trajectory point 1 is earlier than the acquisition time of the following trajectory point of trajectory point 1. Furthermore, the road IDs corresponding to trajectory point 1, its preceding trajectory point, and its following trajectory point are all different, and all three belong to the same trajectory line. It should be noted that there may be at least one trajectory point located within the intersection where trajectory point 1 is located between the preceding trajectory point and trajectory point 1; similarly, there may be at least one trajectory point located within the intersection where trajectory point 1 is located between trajectory point 1 and its following trajectory point.

[0131] See Figure 5, Figure 5 This is a regional-road schematic diagram provided in an embodiment of this application. Figure 5 middle, Figure 5 The image shows 12 road segments within a certain area on a high-precision map. Roads 1, 2, 3, and 4 are connected to each other; roads 5 and 6 are connected; road 6 is connected to roads 7, 10, and 11; road 7 is connected to road 8; road 10 is connected to road 9; and road 11 is connected to road 12. Only roads 3, 7, 10, and 11 lie within an intersection plane. Let's assume that roads 3, 7, 10, and 11 are located at the same intersection with the intersection ID 1. Figure 5 (the gray area in the middle) Figure 5 The black triangles in the diagram represent trajectory points.

[0132] like Figure 5 Trajectory point 1 in the data is determined to be located within intersection 1. Figure 5 It can be seen that there are roads 3, 7, 10 and 11 within intersection 1. Taking trajectory point 2 as the preceding trajectory point of trajectory point 1 and trajectory point 3 as the following trajectory point of trajectory point 1, if trajectory point 2 is located on road 2 and trajectory point 3 is located on road 4, since the connection relationship between the roads within the intersection and the two adjacent road segments outside the intersection is determined in the high-precision map, it can be determined that trajectory point 1 is located on road 3. Therefore, the unique road ID associated with trajectory point 1 is road 3. If trajectory point 2 is located on road 6 and trajectory point 3 is located on road 12, it can be determined that trajectory point 1 is located on road 11. Therefore, the unique road ID associated with trajectory point 1 is road 11.

[0133] Part Three: Linking Track Points with Lane IDs in High-Precision Maps

[0134] Each trajectory point is associated with only one lane ID in the high-definition map. The association between a trajectory point and a lane ID in the high-definition map means that the trajectory point is located in the lane indicated by that lane ID in the high-definition map.

[0135] In a specific implementation, the road ID uniquely associated with the trajectory point in the high-precision map can be determined from the second part mentioned above. Since the road ID in the high-precision map indicates multiple lanes, and each lane has a unique lane ID, multiple lane IDs corresponding to the road ID in the high-precision map can be obtained. Then, based on the location information of the trajectory point and the endpoint coordinates corresponding to each lane ID, the lane ID uniquely associated with the trajectory point can be determined from the multiple lane IDs.

[0136] In another specific implementation, the lane IDs in the high-precision map can be directly obtained. Based on the location information of the trajectory point and the endpoint coordinates corresponding to each lane ID in the high-precision map, the lane ID uniquely associated with the trajectory point can be determined from among the lane IDs. This embodiment can be further described in the following text and will not be repeated here.

[0137] See Figure 6 , Figure 6 This is a flowchart illustrating a method for associating trajectory points with lane IDs according to an embodiment of this application. Taking trajectory 1 as an example, the process of associating trajectory points with lane IDs in a high-precision map will be described. This method includes, but is not limited to, the following steps:

[0138] S21. Obtain multiple lane IDs corresponding to the road ID1 associated with trajectory point 1.

[0139] Specifically, after determining that the road ID associated with trajectory point 1 in the high-precision map is road ID1, since the high-precision map stores the mapping information between road IDs and lane IDs, multiple lane IDs corresponding to road ID1 can be obtained from the high-precision map based on road ID1.

[0140] S22. Determine whether trajectory point 1 is within the intersection on the high-precision map.

[0141] Specifically, the step of determining whether trajectory 1 is within the intersection on the high-precision map is... Figure 1 The steps in S12 have already been executed. Please refer to the relevant description in S12 for details. They will not be repeated here.

[0142] It should be noted that if trajectory point 1 is not located within an intersection in the high-precision map, the road indicated by road ID1 associated with trajectory point 1 is also not located within the intersection, and the lanes indicated by the multiple lane IDs corresponding to road ID1 are also not located within the intersection; if trajectory point 1 is located within an intersection in the high-precision map, the road indicated by road ID1 associated with trajectory point 1 is also located within the intersection, and the lanes indicated by the multiple lane IDs corresponding to road ID1 are also located within the intersection.

[0143] If trajectory point 1 is not located within the intersection on the high-precision map, execute S23; if trajectory point 1 is located within the intersection on the high-precision map, execute S24.

[0144] S23. Calculate the distance from trajectory point 1 to the lane indicated by each of the multiple lane IDs corresponding to road ID1, and take the lane ID corresponding to the minimum distance as the lane ID uniquely associated with trajectory point 1.

[0145] Specifically, assuming that lane c is any one of the multiple lane IDs corresponding to road ID1, the distance from trajectory point 1 to the lane indicated by lane c refers to the perpendicular distance from trajectory point 1 to the center line of lane c. The center line of lane c can be determined by the starting coordinates and ending coordinates of lane c, which can be obtained from a high-precision map.

[0146] By obtaining the vertical distance of each lane ID from trajectory point 1 to road ID1 in the above manner, multiple vertical distances corresponding to trajectory point 1 can be obtained. The minimum vertical distance among the multiple vertical distances corresponding to trajectory point 1 is determined, and the lane ID corresponding to the minimum vertical distance is used as the lane ID uniquely associated with trajectory point 1.

[0147] See Figure 7 , Figure 7 This is a road-lane diagram provided in an embodiment of this application. Figure 7 The image shows two road segments in a high-resolution map. Road 1 includes lanes 11 and 12, and road 2 includes lanes 21 and 22. Figure 7 Each dashed line in the diagram represents the center line of a lane. Since neither Road 1 nor Road 2 is located within the intersection, lanes 11, 12, 21, and 22 are also not located within the intersection. Figure 7 The black triangle in the image represents trajectory point 1. Assuming the road ID associated with trajectory point 1 in the high-precision map is determined to be road 1, since road 1 is not located within the intersection, we only need to calculate the perpendicular distance from trajectory point 1 to the center line of each lane within road 1. If the perpendicular distance from trajectory point 1 to the center line of lane 11 is distance 1, and the perpendicular distance from trajectory point 1 to the center line of lane 12 is distance 2, it is easy to see that distance 2 is less than distance 1. Therefore, the lane that matches trajectory point 1 is lane 12, so trajectory point 1 is associated with lane 12.

[0148] S24. Based on the first lane ID adjacent to the intersection where the previous trajectory point of trajectory point 1 is located and the second lane ID adjacent to the intersection where the subsequent trajectory point of trajectory point 1 is located, determine the lane ID uniquely associated with trajectory point 1.

[0149] Specifically, when trajectory point 1 is located within an intersection, since the connection between each lane within the intersection and the two adjacent lanes outside the intersection is uniquely determined in the high-precision map, the lane ID uniquely associated with trajectory point 1 among the multiple lane IDs corresponding to road ID1 can be determined based on the ID of the first lane adjacent to the intersection where the previous trajectory point of trajectory point 1 is located and the ID of the second lane adjacent to the intersection where the subsequent trajectory point of trajectory point 1 is located.

[0150] In this case, neither the preceding nor following trajectory point of trajectory point 1 is located within the intersection, and the first lane ID is different from the second lane ID. It should be noted that the lane indicated by the first lane ID is the lane entering the intersection where trajectory point 1 is located, while the lane indicated by the second lane ID is the lane exiting the intersection where trajectory point 1 is located.

[0151] It is understandable that the acquisition time of the preceding trajectory point of trajectory point 1 is earlier than the acquisition time of trajectory point 1, and the acquisition time of trajectory point 1 is earlier than the acquisition time of the following trajectory point of trajectory point 1. Furthermore, the lane IDs corresponding to trajectory point 1, its preceding trajectory point, and its following trajectory point are all different, but they are all located on the same trajectory line. It should be noted that there may be at least one trajectory point within the intersection where trajectory point 1 is located between the preceding trajectory point and trajectory point 1; similarly, there may be at least one trajectory point within the intersection where trajectory point 1 is located between trajectory point 1 and its following trajectory point.

[0152] For example, suppose the intersection where trajectory point 1 is located is intersection 1, and lane 1 is a lane within intersection 1. Lane 1 is connected to two lanes outside the intersection (i.e., lane 2 and lane 3). When a vehicle travels, it passes through lane 2, lane 1 and lane 3 in sequence. Then lane 2 can be called the lane entering intersection 1, and lane 3 can be called the lane exiting intersection 1.

[0153] See Figure 8A and Figure 8B , Figure 8A and Figure 8B These are all intersection diagrams. Figure 8A and Figure 8B The image shows eight road segments in the high-precision map that are not within the road: Road 1, Road 2, ..., Road 7 and Road 8. These eight road segments are numbered clockwise with a certain intersection as the center. Figure 8A and Figure 8B The gray square areas in the diagram represent intersections. Each direction of an intersection corresponds to two road segments outside the intersection, and the headings of the two road segments corresponding to the same direction at an intersection differ by 180 degrees. For example, in... Figure 8A In the diagram, a certain direction at the intersection corresponds to Road 1 and Road 2, and Road 1 and Road 2 are in opposite directions. Figure 8A In the diagram, Road 1 and Road 6 are in the same direction, with Road 1 being the road leading into the intersection and Road 6 being the road leading out of the intersection.

[0154] Why not Figure 8ATaking road ID1, which connects roads 1 and 6 at an intersection, as an example, assuming that trajectory point 1 is associated with road ID1, the black triangle in road ID1 represents trajectory point 1, which is located within the intersection. Assuming that road 1 has only one lane (let's call it lane 1-1), road 6 has only one lane (let's call it lane 6-1), and road ID1 has only one lane (let's call it lane ID1-1), the dashed line in road ID1 represents the center line of lane ID1-1, and lane ID1-1 is connected to lane 1-1 and lane 6-1 at both ends. Assuming trajectory point 2 is the preceding trajectory point of trajectory point 1 and is located on lane 1-1, and trajectory point 3 is the following trajectory point and is located on lane 6-1, then based on the connection relationship between lanes within the intersection and lanes outside the intersection, it can be determined that trajectory point 1 is located in lane ID1-1. Therefore, trajectory point 1 is associated with lane ID1-1.

[0155] by Figure 8B Taking road ID1, which connects road 1 and road 6 within the intersection, as an example, assuming that trajectory point 1 is associated with road ID1, the black triangle in road ID1 represents trajectory point 1, which is located within the intersection. Assume that there are two lanes in road 1, denoted as lane 1-1 and lane 1-2, and two lanes in road 6, denoted as lane 6-1 and lane 6-2. There are four lanes in road ID1. For simplification, the four dashed lines in road ID1 represent the center lines of the four lanes, denoted from left to right as lane ID1-1, lane ID1-2, lane ID1-3, and lane ID1-4. Lane ID1-1 connects lane 1-1 and lane 6-1, lane ID1-2 connects lane 1-1 and lane 6-2, lane ID1-3 connects lane 1-2 and lane 6-1, and lane ID1-4 connects lane 1-2 and lane 6-2. Assuming trajectory point 2 is the preceding trajectory point of trajectory point 1 and trajectory point 3 is the following trajectory point, if it is determined that trajectory point 2 is associated with lane 1-1 and trajectory point 3 is associated with lane 6-2, then only lane ID1-2 connects lane 1-1 and lane 6-2 within the intersection. Therefore, it can be determined that trajectory point 1 is located in lane ID1-2. Thus, the lane ID that trajectory point 1 is uniquely associated with is lane ID1-2.

[0156] It should be noted that the method for associating trajectory points and lane IDs outside intersections can be implemented through S23 described above.

[0157] In some possible embodiments, when trajectory point 1 is located within an intersection in a high-precision map, the lane ID uniquely associated with trajectory point 1 can also be determined based on one of the preceding or following trajectory points and the heading corresponding to trajectory point 1.

[0158] The preceding and following trajectory points of trajectory point 1 can be referred to in the above-mentioned descriptions. The heading corresponding to trajectory point 1 is obtained based on the position information of trajectory point 1 and the position information of the adjacent trajectory points of trajectory point 1. The heading corresponding to trajectory point 1 can be referred to in the above-mentioned description in S14, and will not be repeated here.

[0159] In one specific implementation, the lane ID of the intersection where the trajectory point 1 is located is determined based on the previous trajectory point of the trajectory point 1. Based on the connection relationship between the lanes within the intersection and the lanes outside the intersection, among the multiple lane IDs that are connected to the lane ID of the previous trajectory point, the lane ID corresponding to the minimum value of the heading angle between the trajectory point 1 and the heading corresponding to the trajectory point 1 is determined in combination with the heading corresponding to the trajectory point 1. This lane ID is the unique lane ID associated with the trajectory point 1.

[0160] For example, see Figure 8B ,about Figure 8B The description can be found in the above explanation. Assuming that trajectory point 2 is the previous trajectory point of trajectory point 1, and trajectory point 2 is associated with lane 1-1, the heading corresponding to trajectory point 1 is calculated based on the adjacent trajectory points of trajectory point 1. Since the lane entering the intersection is lane 1-1, the heading angle between the heading corresponding to trajectory point 1 and the headings of lanes ID1-1 and ID1-2 in road ID1 is compared. It is easy to see that the heading angle between the heading of lane ID1-2 and the heading corresponding to trajectory point 1 is the smallest. Therefore, trajectory point 1 is uniquely associated with lane ID1-2 in road ID1.

[0161] In a specific implementation, the lane ID uniquely associated with trajectory point 1 can also be determined based on the lane ID of the intersection where trajectory point 1 exits and the heading corresponding to trajectory point 1. For example, see... Figure 8B ,about Figure 8B The description can be found in the above explanation. Assuming that trajectory point 3 is determined to be the subsequent trajectory point of trajectory point 1, and trajectory point 3 is associated with lane 6-2, while the lanes connected to lane 6-2 within the intersection are lane ID1-2 and lane ID1-4, the heading corresponding to trajectory point 1 is calculated based on the adjacent trajectory points of trajectory point 1. The heading angle between the heading corresponding to trajectory point 1 and the headings of lane ID1-2 and lane ID1-4 in road ID1 is compared. It is easy to see that the heading angle between the heading of lane ID1-2 and the heading corresponding to trajectory point 1 is the smallest. Therefore, trajectory point 1 is uniquely associated with lane ID1-2 in road ID1.

[0162] In some possible embodiments, if the coordinate system to which the location information of the trajectory point belongs is inconsistent with the coordinate system to which the coordinate information in the high-precision map belongs, before associating the trajectory point with the area ID, road ID, or lane ID in the high-precision map, it is necessary to first convert the coordinate system to which the location information of the trajectory point belongs to the coordinate system corresponding to the coordinate information in the high-precision map, so that the coordinate system to which the location information of the trajectory point belongs to the coordinate system to which the coordinate information in the high-precision map belongs to the same coordinate system.

[0163] In summary, this study achieves accurate association between trajectory points and region IDs, road IDs, and lane IDs in high-precision maps, and effectively matches trajectory points to various map elements in the high-precision map. This is beneficial for the subsequent accurate representation of the positioning quality of various map elements in the high-precision map by the associated trajectory points.

[0164] As can be seen from the above, the trajectory point is associated with the area ID, road ID, and lane ID in the high-precision map in sequence according to the principle of from large to small. That is, first determine the area ID corresponding to the trajectory point in the high-precision map, then the road ID corresponding to the trajectory point in the high-precision map, and finally determine the lane ID corresponding to the trajectory point in the high-precision map.

[0165] In some possible embodiments, the lane IDs in the high-definition map can be directly obtained. Based on the location information of the trajectory point and the endpoint coordinates corresponding to each lane ID, the lane ID uniquely associated with the trajectory point in each lane ID can be determined. Given the lane IDs associated with the trajectory point, the road ID associated with the trajectory point in the high-definition map can be quickly determined based on the correspondence between lane IDs and road IDs in the high-definition map. Similarly, the lane ID associated with the trajectory point in the high-definition map can be quickly determined based on the correspondence between road IDs and region IDs in the high-definition map, thus achieving the association between the trajectory point and the road ID and region ID.

[0166] In some possible embodiments, it may be possible to simply associate the trajectory points with regions, roads, or lanes in the high-precision map. This application does not impose any specific limitations on the embodiments.

[0167] Specifically, let's take trajectory point 1 as an example to illustrate another method for determining the lane ID association in a high-precision map of trajectory points:

[0168] If trajectory point 1 is not located within the intersection on the high-precision map, first obtain the lane IDs from the high-precision map. Based on the coordinate range of each lane (i.e., the starting and ending coordinates of the lane) and the location information of trajectory point 1, filter out the set of lane IDs that meet preset condition 3. Calculate the vertical distance from trajectory point 1 to the centerline of each lane ID in the lane ID set, and calculate the heading angle between the heading of trajectory point 1 and the heading of each lane ID in the lane ID set. Thus, each lane ID in the lane ID set corresponds to a calculated vertical distance and heading angle. Based on the vertical distance and heading angle, filter each lane ID in the lane ID set, and use the target lane ID that meets preset condition 4 as the unique lane ID associated with trajectory point 1. Preset condition 3 can be one or more of the following: the longitude coordinates of trajectory point 1 are within the longitude range limited by the starting and ending coordinates of the lane ID; or the latitude coordinates of trajectory point 1 are within the latitude range limited by the starting and ending coordinates of the lane ID. Preset condition 4 can be that the vertical distance corresponding to the target lane ID is less than threshold 1 and the heading angle corresponding to the target lane ID is less than threshold 2. In this embodiment, the heading corresponding to trajectory point 1 can be referred to the relevant description in S14. The process of determining the lane ID associated with trajectory point 1 is similar to the process of determining the road ID associated with trajectory point 1 in S13-S15 above, so please refer to the relevant description in S13-S15 above for details.

[0169] If trajectory point 1 is located within an intersection on a high-precision map, assuming trajectory point 1 is within intersection 1, the lane IDs of each lane within intersection 1 are obtained from the high-precision map. Then, the lane ID uniquely associated with trajectory point 1 is determined based on the lane IDs of the preceding and following trajectory points entering and exiting intersection 1. In some possible embodiments, the lane ID uniquely associated with trajectory point 1 can also be determined based on the heading corresponding to one of the preceding or following trajectory points. The specific process can be referred to in the relevant description in S24 above; for the sake of brevity, it will not be repeated here.

[0170] It should be noted that the heading corresponding to the lane ID mentioned above can be obtained from a high-precision map, or it can be calculated based on the starting and ending coordinates of the lane. This application embodiment does not impose specific limitations. The calculation of the heading corresponding to trajectory point 1 can be referred to the relevant description in S14 above, and will not be repeated here for the sake of brevity.

[0171] In summary, other trajectory points can be identified using the same method as trajectory point 1 described above to determine their associated lane IDs in the high-precision map. Finally, by combining the correspondence between lane IDs and road IDs, and the correspondence between road IDs and region IDs in the high-precision map, the corresponding road ID and region ID can be determined.

[0172] See Figure 9 , Figure 9 This is a flowchart of a map generation method provided in an embodiment of this application, applied to a cartographic device. The method includes, but is not limited to, the following steps:

[0173] S101. Obtain the location information of a set of trajectory points, the location quality reference information, and the location information of multiple driving areas in the map.

[0174] In this embodiment, the mapping device can acquire a set of trajectory points from a data acquisition device or a data acquisition vehicle, for example, by receiving a set of trajectory points sent by a data acquisition vehicle. The map can be a high-precision map, or other types of maps including areas, roads, and lanes; this embodiment does not specifically limit the scope. In one specific implementation, the map can be pre-stored in the mapping device's memory, and the mapping device can obtain the location information of multiple driving areas in the map by calling the map in its own memory. In another specific implementation, the map can also be acquired by the mapping device from other devices (e.g., vehicles, cloud servers, etc.). Multiple driving areas in the map include areas, roads, or lanes in the map.

[0175] Each trajectory point has corresponding location information and positioning quality reference information. The location information indicates the point's position on the high-precision map; for example, it can be represented by longitude and latitude. The positioning quality reference information measures the positioning quality at that point on the map. This information includes the point's positioning accuracy, DOP value, the number of satellites observed at the point, or whether the location information is a fixed solution. It should be noted that the location information of the trajectory point is the same as the location information of the trajectory point in the above embodiment, and the positioning quality reference information is the same as the quality information of the trajectory point in the above embodiment.

[0176] S102. Based on the location information of a set of trajectory points and the location information of multiple driving areas, associate the set of trajectory points with the first driving area among the multiple driving areas.

[0177] In this embodiment of the application, based on the location information of a set of trajectory points and the location information of multiple driving areas, the set of trajectory points is associated with a first driving area among the multiple driving areas. The first driving area is a region, road or lane in the map.

[0178] In a specific implementation, the association process is illustrated using the first trajectory point and the second trajectory point as an example: The first trajectory point and the second trajectory point are any two adjacent trajectory points in the group of trajectory points. When the first trajectory point and the second trajectory point are not located at an intersection on the map, and the vertical distance between the first trajectory point and the first driving area meets the first preset condition, and the angle between the heading corresponding to the first trajectory point and the heading of the first driving area meets the second preset condition, the group of trajectory points is associated with the first driving area, which is a road or a lane on the map; the heading corresponding to the first trajectory point is the heading from the first trajectory point to the second trajectory point.

[0179] As can be seen, the above implementation method is suitable for associating a set of trajectory points with a road in a map. For details, please refer to the above. Figure 3 In the description of S14-S15 in the embodiment, the first trajectory point is trajectory point 1, the second trajectory point is the next adjacent trajectory point of the trajectory point, and the first preset condition and the first and second preset conditions are equivalent to preset condition 2 in the above embodiment.

[0180] The above implementation method is also applicable to associating a set of trajectory points with a lane in a map. For details, please refer to the description of the lane ID associated with the trajectory points in the above embodiments. The first preset condition and the first and second preset conditions are equivalent to preset condition 4 in the above embodiments, and will not be repeated here.

[0181] In another specific implementation, the set of trajectory points is located within an intersection on the map. In this case, associating the set of trajectory points with the first driving area can be done by associating the set of trajectory points with the first driving area within the intersection. The first driving area is the only road or lane within the intersection that connects the second driving area adjacent to the intersection and the third driving area adjacent to the intersection. The trajectory point preceding the set of trajectory points is located within the second driving area, and the trajectory point following the set of trajectory points is located within the third driving area.

[0182] The above implementation method is applicable when the trajectory point is located within an intersection on the map, associating the trajectory point with a road within the intersection, and is consistent with the above. Figure 3 In the embodiment, the relevant description of S16 corresponds to the following: in this case, the second driving area can be the road indicated by the first road ID in S16, and the third driving area is equivalent to the road indicated by the second road ID in S16. The first driving area is the road connecting the first road ID and the second road ID within the intersection.

[0183] The above implementation method is applicable when the trajectory point is located within an intersection on the map, and associates the trajectory point with a lane within the intersection, as described above. Figure 6In the embodiment, the relevant description of S24 corresponds to the following: in this case, the second driving area can be the lane indicated by the first lane ID in S24, and the third driving area is equivalent to the lane indicated by the second lane ID in S24. The first driving area is the lane connecting the first lane ID and the second lane ID within the intersection.

[0184] In another specific implementation, based on the location information of the set of trajectory points and the coordinates of multiple corner points in the first driving area, it is determined that the set of trajectory points is located within the first driving area, which is a region in the map. The set of trajectory points is then associated with the first driving area. This implementation corresponds to the description of determining the region ID associated with the trajectory points in the first part of the above embodiment. It can be understood that the first driving area can be any region ID indicated by any region ID in the map. For example, if the first driving area is region 1-00-00, the set of trajectory points is a plurality of trajectory points within region 1-00-00.

[0185] S103. Obtain the positioning quality statistics based on the positioning quality reference information of this set of trajectory points.

[0186] In this embodiment, the set of trajectory points includes at least one trajectory point, and each trajectory point has corresponding positioning quality reference information. For details regarding the positioning quality reference information of the trajectory points, please refer to the relevant description in S101 above. Positioning quality statistics are obtained based on the positioning quality reference information of this set of trajectory points.

[0187] The positioning quality statistics include average positioning accuracy, average accuracy factor (DOP) value, average number of observable satellites, or whether the positioning position of the trajectory point is a fixed solution.

[0188] Among them, the average positioning accuracy is the standard deviation of the error of the position information of multiple trajectory points relative to the reference true value. The smaller the average positioning accuracy, the better the positioning quality. The larger the average number of observable satellites, the better the positioning quality. The average precision factor DOP is used to measure the average error caused by the geometric position of the satellite relative to the observer (e.g., the data acquisition vehicle collecting the location points). The smaller the average precision factor DOP, the better the positioning quality. The positioning quality of a fixed solution is better than that of a non-fixed solution. A fixed solution means that the ambiguity corresponding to the positioning position calculated based on the carrier phase is an integer.

[0189] For example, if the positioning quality reference information for a trajectory point is the number of observable satellites for that trajectory point, the positioning quality statistics are obtained by counting the number of observable satellites for each trajectory point in the group. The positioning quality statistics are the average number of observable satellites corresponding to the group of trajectory points. The more average observable satellites corresponding to the group of trajectory points, the better the positioning quality of the driving area where the group of trajectory points is located.

[0190] S104. Generate positioning quality indication information.

[0191] In this embodiment, positioning quality indication information is generated based on positioning quality statistics. Since this set of trajectory points is associated with a first driving area, the positioning quality indication information is used to indicate that the positioning quality within the first driving area is the positioning quality statistics. The first driving area is a region, road, or lane in a map.

[0192] The positioning quality indication information can be represented in the form of tables, graphics, text, etc., and this application embodiment does not specifically limit it. It should be noted that the positioning quality indication information can also be called the positioning quality information layer, positioning quality mapping table, etc.

[0193] For example, positioning quality indication information can be represented as shown in Table 1. Table 1 lists the mapping relationship between the driving area and the positioning quality. For example, the positioning quality of area 1 in the map includes: an average number of observable satellites of 6; the positioning quality of area 2 in the map includes: an average number of observable satellites of 6.

[0194] Table 1

[0195] Driving area Positioning quality Area 1 on the map The average number of observable satellites is 6 Area 2 on the map The average number of observable satellites is 4 … …

[0196] S105. Add the positioning quality indication information to the map.

[0197] In this embodiment of the application, after generating the positioning quality indication information, the positioning quality indication information can also be added to the map. Since the first driving area in the positioning quality indication information corresponds to the area, road or lane in the map, after the positioning quality indication information is added to the map, the corresponding positioning quality can be marked at the corresponding area, road or lane in the map.

[0198] In some possible embodiments, the association method in S102 can also be as follows: the first driving area is a road in the map, and the first driving area includes multiple lanes in the map. When the set of trajectory points is associated with the first driving area, at least one trajectory point is selected from the set of trajectory points based on the distance from each trajectory point in the set to each lane in the multiple lanes within the first driving area. Then, one lane is selected from the multiple lanes, for example, lane A, which is the lane closest to each of the at least one trajectory point. A lane positioning quality statistical value is obtained based on the positioning quality reference information of the at least one trajectory point. Then, lane positioning quality indication information can be generated based on the lane positioning quality statistical value. The lane positioning quality indication information is used to indicate that the positioning quality within lane A is the lane positioning quality statistical value. The lane positioning quality indication information is then added to the map.

[0199] In a specific implementation, the map with added positioning quality indication information can also be stored, or the map with added positioning quality indication information can be sent to the terminal. The description of the terminal can be referred to the relevant description in the above embodiments, and will not be repeated here.

[0200] In some possible embodiments, time information can also be added to indicate the effective time of positioning quality within the driving area. Since the positioning quality reference information obtained based on trajectory points collected at different times varies—for example, since trees in winter are mostly bare trunks while trees in summer are generally full of foliage—the positioning quality obtained based on trajectory points collected in winter is generally better than that obtained based on trajectory points collected in summer. Therefore, time information can be introduced to define the effective time of positioning quality within the driving area.

[0201] Typically, location quality indication information can be generated by a map server. Figure 9 The mapping device executing the method shown can be a map server, or a component or chip within the map server. Furthermore, the positioning quality indication information may also be generated by roadside equipment, vehicles, or mobile terminals. Figure 9 The mapping device that performs the method shown can also be the roadside equipment, vehicle, or mobile terminal, or a component or chip of the roadside equipment, vehicle, or mobile terminal.

[0202] As can be seen, implementing the embodiments of this application accurately associates trajectory points with various driving areas on the map. The positioning quality of the driving area generated based on the statistical values ​​of positioning quality reference information of multiple trajectory points associated with the driving area is of reference value and high reliability. Positioning quality indication information for each driving area is provided in the map. This positioning quality indication information allows map users to choose to avoid driving areas with poor positioning quality, or selectively set a lower confidence level for positioning information with poor positioning quality, thereby improving vehicle travel safety.

[0203] See Figure 10 , Figure 10 This is a flowchart illustrating a map usage method provided in an embodiment of this application. Figure 10 Can be independent of Figure 9 Implementation examples can also be... Figure 9 Supplement to the embodiments. In Figure 9 In this embodiment, the mapping device may be a server, and the terminal may be a vehicle; however, this does not limit the mapping device to a server or the terminal to a vehicle. The method includes, but is not limited to, the following steps:

[0204] S201, The server sends a map to the vehicle.

[0205] In this embodiment, the server sends a map to the vehicle. The map includes positioning quality indication information and driving area indication information. The positioning quality indication information indicates the positioning quality within the driving area, and the driving area indication information indicates the driving area, which is a region, road, or lane in the map. The positioning quality within the driving area is a statistical value of the positioning quality of multiple trajectory points within that driving area.

[0206] The positioning quality statistics include average positioning accuracy, average precision factor (DOP) value, average number of observable satellites, or statistics on whether the positioning position of the trajectory point is a fixed solution.

[0207] In a specific implementation, the positioning quality indication information and driving area indication information are carried in the map, which can be sent to the vehicle by the server in any of the following ways: broadcast, multicast, or unicast.

[0208] In another specific implementation, the server can send a map containing positioning quality indication information and driving area indication information to the roadside unit, which then sends the map to the vehicle.

[0209] It should be noted that the map can be generated by the server based on... Figure 9 Generated as shown, it can also be generated by other devices according to... Figure 9 The map generated in the manner shown is sent to the server, but this application embodiment does not impose specific limitations.

[0210] S202. The vehicle receives the map and obtains the positioning quality indication information and driving area indication information from the map.

[0211] Accordingly, the vehicle receives the map and obtains the positioning quality indication information and driving area indication information from the map. It should be noted that the map received by the vehicle can be sent by the server or sent by the server through the roadside unit; this embodiment of the application does not make specific limitations.

[0212] In a specific implementation, the positioning quality indication information includes the mapping relationship between the driving area number and the positioning quality, and the driving area indication information includes the mapping relationship between the driving area number and the identifier of map elements in the map. The map elements are areas, roads or lanes in the map.

[0213] For example, the positioning quality indication information can be represented as Table 2, and the driving area indication information can be represented as Table 3. For example, in Table 2, the positioning quality of driving area number 1 is: the average number of observable satellites is 6. According to Table 3, driving area number 1 is area 1 in the map. Therefore, combining Table 1 and Table 2, the positioning quality of area 1 in the map is: the average number of observable satellites is 6.

[0214] Table 2

[0215] Driving area number Positioning quality 1 The average number of observable satellites is 6 2 The average number of observable satellites is 4 … …

[0216] Table 3

[0217] Driving area number Map element identifiers 1 Area 1 2 Road 2 … …

[0218] S203. The vehicle performs route planning, driving decisions, or vehicle control based on positioning quality indication information and driving area indication information.

[0219] In this embodiment, the vehicle can know the positioning quality of each driving area in the map in advance based on the positioning quality indication information and the driving area indication information, which helps it to plan the route, make driving decisions or control the vehicle, thereby effectively avoiding areas, roads or lanes with poor positioning quality and improving its travel safety.

[0220] See Figure 11 , Figure 11 This is a schematic diagram of an application scenario provided by an embodiment of this application. Suppose that a vehicle wants to travel from point A to destination point F. Based on the positioning quality indication information and the driving area indication information, the vehicle knows that the positioning quality of all roads is good except for road BC, which has poor positioning quality. Then, the navigation route determined by the vehicle after route planning is: ABEFCD. It can be seen that the poor positioning quality of road BC is avoided, and the vehicle's positioning on each road on this navigation route is accurate, which improves the vehicle's travel safety rate.

[0221] For example, see Figure 11 Assuming a vehicle wants to travel from point A to its destination point F, the vehicle knows the destination based on the positioning quality indication information and the driving area indication information. Figure 11 If the positioning quality of lanes BC is the worst, then when the vehicle reaches point B, the driving decision made by the vehicle is to turn left into lanes BE to avoid lanes BC with the worst positioning quality and to choose to drive in lanes with better positioning quality as much as possible.

[0222] In some possible implementations, the vehicle can store the received map for later retrieval when needed. Alternatively, the vehicle can display the received map on a screen, allowing the user to intuitively and clearly understand the positioning quality of each driving area on the map.

[0223] In this embodiment, the map-using device can be a vehicle, a component inside the vehicle (such as a navigation device or an autonomous driving device inside the vehicle), or a chip that can be used inside the vehicle.

[0224] As can be seen, implementing the embodiments of this application provides a map that includes positioning quality indication information and driving area indication information, enabling vehicles to avoid driving areas with poor positioning quality in a timely manner based on the map, or selectively set a lower confidence level for positioning information with poor positioning quality, so as to drive in driving areas with better positioning quality (e.g., roads, lanes, etc.), thereby obtaining accurate positioning information, which is beneficial to improving the accuracy of route planning, driving decisions, and travel safety.

[0225] See Figure 12 , Figure 12 This is a schematic diagram of a map generation apparatus provided in an embodiment of this application. The apparatus 30 includes at least a processor 110, a memory 111, and a receiver 112. In some possible embodiments, the apparatus 30 further includes a transmitter 113. The receiver 112 and transmitter 113 can also be replaced with communication interfaces for providing information input and / or output to the processor 110. Optionally, the memory 111, receiver 112, transmitter 113, and processor 110 are connected or coupled via a bus. The apparatus 30 may be... Figure 1 The mapping device in the embodiment can also be Figure 10 The server in the middle.

[0226] In this embodiment of the application, the device 30 is used to implement the above. Figure 9 The method described in the embodiments can also be used to implement Figure 10 The server-side method described in the embodiments.

[0227] Receiver 112 is used to obtain location information of a set of trajectory points, location quality reference information, and location information of multiple driving areas in a map. In some possible embodiments, transmitter 113 is used to transmit generated location quality indication information, or to transmit a map including location quality indication information and driving area indication information. Receiver 112 and transmitter 113 may include antennas and chipsets for communicating directly or via an air interface with devices, sensors, or other physical devices within the vehicle. Transmitter 113 and receiver 112 constitute a communication module that can be configured to receive and transmit information according to one or more other types of wireless communication (e.g., protocols), such as Bluetooth, IEEE 802.11, cellular technology, Worldwide Interoperability for Microwave Access (WiMAX) or LTE (Long Term Evolution), ZigBee, Dedicated Short Range Communications (DSRC), and RFID (Radio Frequency Identification) communication, etc.

[0228] The receiver 112 and transmitter 113 can have wired or wireless interfaces. The wired interface can be an Ethernet interface, a Local Interconnect Network (LIN), etc., while the wireless interface can be a cellular network interface or a wireless LAN interface, etc.

[0229] Processor 110 can be used to perform operations such as associating a set of trajectory points with a first driving area based on the positioning information of a set of trajectory points and the positioning information of multiple driving areas, and generating positioning quality indication information indicating the positioning quality of the first driving area. Processor 110 can be composed of one or more general-purpose processors, such as a central processing unit (CPU), or a combination of a CPU and hardware chips. The aforementioned hardware chips can be application-specific integrated circuits (ASICs), programmable logic devices (PLDs), or combinations thereof. The aforementioned PLDs can be complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), generic array logic (GALs), or any combination thereof.

[0230] The memory 111 may include volatile memory, such as random access memory (RAM); it may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or it may include a combination of the above types. The memory 111 can store programs and data. The stored programs include: vertical distance calculation algorithms, heading angle calculation programs, association establishment algorithms, etc., and the stored data includes: trajectory point positioning information, positioning quality reference information, and the mapping relationship between the driving area and positioning quality, etc. The memory 111 may exist independently or be integrated within the processor 110.

[0231] also, Figure 11 Just one example of device 30, which may include compared to Figure 11 The number of components displayed may be more or fewer, or there may be different component configuration methods. Meanwhile, Figure 11 The various components shown can be implemented in hardware, software, or a combination of both.

[0232] See Figure 13 , Figure 13This is a schematic diagram of a map-using device provided in an embodiment of this application. The device 40 includes at least a processor 210, a memory 211, a receiver 212, and a display 213. The receiver 212 can provide information input to the processor 210. Optionally, the memory 211, receiver 212, display 213, and processor 210 are connected or coupled via a bus. The device 40 can be... Figure 1 The terminal can also be Figure 10 The vehicle in the embodiment. In this embodiment, device 40 is used to implement the above. Figure 10 The vehicle-side method described in the embodiments.

[0233] Receiver 212 is used to receive positioning quality indication information and driving area indication information from the map. For example, receiver 212 can be used to perform... Figure 10 S202 in the example. Receiver 112 may include an antenna and chipset for communicating directly or via an air interface with a server, drive unit, sensor, or other physical device. Receiver 212 may be a wireless interface, such as a cellular network interface or a wireless LAN interface.

[0234] The processor 210 is used to perform path planning, driving decisions, or vehicle control based on the positioning quality indication information and the driving area indication information. For example, the processor 210 can be used to perform... Figure 10 S203 in the diagram. Processor 210 can be composed of one or more general-purpose processors, such as a central processing unit (CPU), or a combination of a CPU and hardware chips. The aforementioned hardware chips can be application-specific integrated circuits (ASICs), programmable logic devices (PLDs), or combinations thereof. The aforementioned PLDs can be complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), generic array logic (GALs), or any combination thereof.

[0235] The memory 211 may include volatile memory, such as random access memory (RAM); the memory 211 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); the memory 211 may also include combinations of the above types. The memory 211 can store programs and data, wherein the stored programs include vehicle control programs, navigation planning programs, etc., and the stored data includes positioning quality indication information, driving area indication information, etc. The memory 211 may exist independently or be integrated within the processor 110.

[0236] The display 213 is used to display positioning quality indication information in the map. The display 213 can be a display screen, which can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active matrix organic light-emitting diode (AMOLED), etc.

[0237] also, Figure 13 Just one example of device 40, device 40 may include compared to Figure 13 The number of components displayed may be more or fewer, or there may be different component configuration methods. Meanwhile, Figure 13 The various components shown can be implemented in hardware, software, or a combination of both.

[0238] See Figure 14 , Figure 14 This is a functional structure diagram of a map generation device provided in an embodiment of this application. The device 31 includes an acquisition unit 310, an association unit 311, a calculation unit 312, and a processing unit 313. The device 31 can be implemented by hardware, software, or a combination of hardware and software.

[0239] The acquisition unit 310 is used to acquire the location information of a set of trajectory points, the location quality reference information, and the location information of multiple driving areas in the map. The multiple driving areas include areas, roads, or lanes in the map. The association unit 311 is used to associate a set of trajectory points with a first driving area in the multiple driving areas based on the location information and the location information of the multiple driving areas. The first driving area is an area, road, or lane in the map. The calculation unit 312 is used to acquire the location quality statistical value based on the location quality reference information. The processing unit 313 is used to generate location quality indication information, which indicates that the location quality in the first driving area is the location quality statistical value. The processing unit 313 is used to add the location quality indication information to the map.

[0240] The various functional modules of the device 31 can be used to achieve Figure 9 The method described in the embodiments. Figure 9 In this embodiment, the acquisition unit 310 can be used to execute S101, the association unit 311 can be used to execute S102, the calculation unit 312 can be used to execute S103, and the processing unit 313 can be used to execute S104 and S105.

[0241] In some possible embodiments, device 31 further includes a transmitting unit for transmitting a map with the added positioning quality indication information; the transmitting unit can be used to perform... Figure 10 S201 in the middle.

[0242] The various functional modules of the device 31 can be used to achieve Figure 3 and Figure 6 The methods described in the embodiments will not be repeated here for the sake of brevity.

[0243] See Figure 15 , Figure 15 This is a functional structure diagram of a map-using device provided in an embodiment of this application. The device 41 includes a receiving unit 410 and a processing unit 411. In some possible embodiments, the device 41 also includes a display unit 412. The device 41 can be implemented by hardware, software, or a combination of hardware and software.

[0244] The receiving unit 410 receives positioning quality indication information and driving area indication information from the map. The positioning quality indication information indicates the positioning quality within the driving area, and the driving area indication information indicates the driving area, which is a region, road, or lane on the map. The positioning quality within the driving area is a statistical value of the positioning quality of multiple trajectory points within the driving area. The processing unit 411 performs route planning, driving decisions, or vehicle control based on the positioning quality indication information and driving area indication information. The display unit 412 displays the positioning quality indication information from the map.

[0245] The functional modules of the device 41 can be used to achieve Figure 10 The method described in the embodiments. Figure 10 In this embodiment, the receiving unit 410 can be used to execute S202, and the processing unit 411 can be used to execute S203.

[0246] In the embodiments described above, each embodiment has its own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0247] It should be noted that those skilled in the art will recognize that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0248] The technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer program product is stored in a storage medium and includes several instructions to cause a device (which may be a personal computer, server, network device, robot, microcontroller, chip, robot, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

Claims

1. A map generation method, characterized in that, The method includes: The system obtains location information of a set of trajectory points, location quality reference information, and location information of multiple driving areas in a map. The multiple driving areas include regions, roads, or lanes in the map. The trajectory points are collected in advance by the data collection vehicle while driving on each lane in the map. Based on the location information and the location information of the multiple driving areas, the set of trajectory points are associated with the first driving area among the multiple driving areas, where the first driving area is a region, road, or lane in the map; The positioning quality statistics are obtained based on the positioning quality reference information. Generate positioning quality indication information, wherein the positioning quality indication information is used to indicate that the positioning quality within the first driving area is the positioning quality statistical value; The positioning quality indication information is added to the map.

2. The method according to claim 1, characterized in that, The first trajectory point and the second trajectory point are any two adjacent trajectory points in the set of trajectory points. The step of associating the set of trajectory points with the first driving area among the multiple driving areas based on the positioning information and the location information of the multiple driving areas includes: If the first trajectory point and the second trajectory point are not located at an intersection in the map, and if the vertical distance between the first trajectory point and the first driving area meets a first preset condition, and the heading angle between the heading corresponding to the first trajectory point and the heading of the first driving area meets a second preset condition, then the set of trajectory points is associated with the first driving area, which is a road or a lane in the map; the heading corresponding to the first trajectory point is the heading from the first trajectory point to the second trajectory point.

3. The method according to claim 1, characterized in that, The set of trajectory points is located within the intersection in the map. Associating the set of trajectory points with a first driving area among the multiple driving areas based on the location information and the location information of the multiple driving areas includes: The set of trajectory points is associated with the first driving area within the intersection. The first driving area is the only road or lane within the intersection that connects the second driving area adjacent to the intersection and the third driving area adjacent to the intersection. The trajectory point preceding the set of trajectory points is located within the second driving area, and the trajectory point following the set of trajectory points is located within the third driving area.

4. The method according to claim 2, characterized in that, The first driving area is a road in the map, and the first driving area includes multiple lanes in the map. The method further includes: Based on the distance from each trajectory point in the set of trajectory points to each lane in the plurality of lanes, at least one trajectory point is selected from the set of trajectory points, and one lane is selected from the plurality of lanes, wherein the selected lane is the lane in the plurality of lanes that is closest to each of the at least one trajectory point. The lane positioning quality statistics are obtained based on the positioning quality reference information of at least one trajectory point. Generate lane positioning quality indication information, wherein the lane positioning quality indication information is used to indicate that the positioning quality within a lane is the lane positioning quality statistical value; The lane positioning quality indication information is added to the map.

5. The method according to claim 1, characterized in that, The step of associating the set of trajectory points with the first driving area among the multiple driving areas based on the positioning information and the location information of the multiple driving areas includes: Based on the location information of the set of trajectory points and the coordinates of multiple corner points in the first driving area, it is determined that the set of trajectory points are located within the first driving area, where the first driving area is the area in the map. Associate the set of trajectory points with the first driving area.

6. A map generation device, characterized in that, The device includes: The acquisition unit is used to obtain the location information of a set of trajectory points, the location quality reference information, and the location information of multiple driving areas in the map. The multiple driving areas include areas, roads, or lanes in the map. The trajectory points are collected in advance by the data collection vehicle while driving on each lane in the map. The association unit is used to associate the set of trajectory points with a first driving area among the multiple driving areas based on the positioning information and the location information of the multiple driving areas. The first driving area is a region, road or lane in the map. The calculation unit is used to obtain positioning quality statistics based on the positioning quality reference information; The processing unit is configured to generate positioning quality indication information, wherein the positioning quality indication information is used to indicate that the positioning quality within the first driving area is the positioning quality statistical value; The processing unit is also used to add the positioning quality indication information into the map.

7. The apparatus according to claim 6, characterized in that, The first trajectory point and the second trajectory point are any two adjacent trajectory points in the set of trajectory points, and the association unit is specifically used for: If the first trajectory point and the second trajectory point are not located at an intersection in the map, and if the vertical distance between the first trajectory point and the first driving area meets a first preset condition, and the heading angle between the heading corresponding to the first trajectory point and the heading of the first driving area meets a second preset condition, then the set of trajectory points is associated with the first driving area, which is a road or a lane in the map. The heading corresponding to the first trajectory point is the heading from the first trajectory point to the second trajectory point.

8. The apparatus according to claim 6, characterized in that, The set of trajectory points is located within the intersections on the map, and the association unit is specifically used for: The set of trajectory points is associated with the first driving area within the intersection. The first driving area is the only road or lane within the intersection that connects the second driving area adjacent to the intersection and the third driving area adjacent to the intersection. The trajectory point preceding the set of trajectory points is located within the second driving area, and the trajectory point following the set of trajectory points is located within the third driving area.

9. The apparatus according to claim 7, characterized in that, The first driving area is the road in the map, and the first driving area includes multiple lanes in the map. The association unit is further configured to select at least one trajectory point from the set of trajectory points and select one lane from the plurality of lanes based on the distance from each trajectory point in the set of trajectory points to each lane in the plurality of lanes, wherein the selected lane is the lane in the plurality of lanes that is closest to each of the at least one trajectory point in the set of trajectory points. The calculation unit is also used to obtain lane positioning quality statistics based on the positioning quality reference information of the at least one trajectory point; The processing unit is further configured to generate lane positioning quality indication information, which indicates that the positioning quality within a lane is the lane positioning quality statistical value; and to add the lane positioning quality indication information to the map.

10. The apparatus according to claim 6, characterized in that, The association unit is specifically used for: Based on the location information of the set of trajectory points and the coordinates of multiple corner points in the first driving area, it is determined that the set of trajectory points are located within the first driving area, where the first driving area is the area in the map. Associate the set of trajectory points with the first driving area.

11. A map generation device, characterized in that, The device includes a memory and a processor, the memory storing computer program instructions, and the processor executing the computer program instructions to cause the device to perform the method as described in any one of claims 1-5.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method as described in any one of claims 1-5.

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