Methods, equipment and media for collecting geographic information

Abstract

The embodiments of the present application provide a method, device and medium for collecting geographic information. In this method, after the first device node of the device cluster system determines the target collection task that matches the target geographic area and at least one first vehicle trajectory in the target geographic area, a second vehicle trajectory that matches the task collection path indicated by the target collection task is determined from the first vehicle trajectory. Then, by collecting vehicles of each second vehicle trajectory, geographic information matching the target collection task is obtained. In this solution, the device nodes of the device cluster system collect geographic information, there are many device nodes, and each device node corresponds to a different target geographic area, and the determined target collection task and the first vehicle trajectory are also different, and then different geographic information is collected. The geographic information is collected by the device nodes in the device cluster system, which effectively improves the efficiency of collecting geographic information.

Description

Technical Field

[0001] The present application relates to the field of map construction technology, and in particular to a method, device and medium for collecting geographic information data. Background Art

[0002] With the continuous development of science and technology, maps have also evolved from the original paper maps to the current high-precision maps. In the process of building high-precision maps, it is necessary to collect geographic information such as point clouds and images for construction.

[0003] In the prior art, the method for collecting geographic information data that can be used to build high-precision maps is usually to first obtain all the original geographic information data collected by the vehicle. Since some of the data does not meet the conditions or is redundant, it is necessary to manually eliminate this data to obtain the geographic information data used to build high-precision maps.

[0004] In summary, the existing technology collects geographic information by first acquiring all original geographic information and then manually screening it, which results in low efficiency in collecting geographic information. Summary of the invention

[0005] The embodiments of the present application provide a method, device and medium for collecting geographic information data, so as to solve the problem of low efficiency in collecting geographic information data caused by first acquiring all original geographic information data and then manually screening the geographic information data in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for collecting geographic information data, which is applied to a first device node of a device cluster system, and the method includes:

[0007] Determine a target acquisition task matching a target geographical area, and determine at least one first vehicle trajectory within the target geographical area; the target geographical area is a service area corresponding to the first device node, and the service areas of at least two device nodes in the device cluster system do not completely overlap;

[0008] Determining, from the at least one first vehicle trajectory, at least one second vehicle trajectory that matches the task collection path indicated by the target collection task;

[0009] By collecting the vehicles of each second vehicle trajectory, geographic information data matching the target collection task is obtained.

[0010] In a possible implementation manner, acquiring geographic information data matching the target collection task by collecting the vehicles of each second vehicle trajectory includes:

[0011] The following processing is performed for each of the second vehicle trajectories:

[0012] Determining a data index point corresponding to the second vehicle trajectory according to a preset data acquisition rule;

[0013] By collecting the vehicles of the second vehicle trajectory, the geographic information data corresponding to each of the data index points is obtained.

[0014] In a possible implementation manner, determining the data index point corresponding to the second vehicle trajectory according to a preset data acquisition rule includes:

[0015] Acquire at least one first position point from the second vehicle trajectory, and use the first position point as the data index point;

[0016] or,

[0017] Acquire at least one second position point from the second vehicle trajectory; based on the position and generation time of each trajectory point in the second vehicle trajectory, determine the reference time point corresponding to each second position point as the data index point.

[0018] In a possible implementation manner, determining the target acquisition task matching the target geographical area includes:

[0019] receiving the target acquisition task sent by a second device node in the device cluster system, where the target acquisition task is determined by the second device node based on the target geographical area;

[0020] or,

[0021] Receive at least one initial collection task sent by the second device node, and determine the target collection task according to the task collection path indicated by the at least one initial collection task and the target geographical area.

[0022] In a possible implementation, the determining of at least one first vehicle trajectory within the target geographical area includes:

[0023] Acquire at least one original vehicle trajectory; determine the trajectory segment belonging to the target geographical area in each of the original vehicle trajectories as the first vehicle trajectory;

[0024] or,

[0025] At least a first vehicle trajectory sent by a second device node in the device cluster system is received, where the first vehicle trajectory is determined by the second device node based on the target geographical area.

[0026] In a possible implementation manner, the target collection task indicates the task collection path through a road segment identification sequence;

[0027] The step of determining, from the at least one first vehicle trajectory, at least one second vehicle trajectory that matches the task collection path indicated by the target collection task comprises:

[0028] Determining a task area according to the road segment identification sequence;

[0029] Determining a trajectory segment belonging to the task area in the at least one first vehicle trajectory as a third vehicle trajectory corresponding to the target acquisition task;

[0030] A third vehicle trajectory matching the road segment identification sequence is determined as the second vehicle trajectory.

[0031] In a possible implementation manner, determining the third vehicle trajectory that matches the road segment identification sequence as the second vehicle trajectory includes:

[0032] The following processing is performed for each of the third vehicle trajectories:

[0033] Determine a to-be-matched road segment identification sequence corresponding to the third vehicle trajectory according to the road segment identification sequence and the positions and generation times of the trajectory points in the third vehicle trajectory;

[0034] If the to-be-matched road segment identification sequence corresponding to the third vehicle trajectory is the same as the road segment identification sequence, the third vehicle trajectory is used as the second vehicle trajectory.

[0035] In a possible implementation, the road segment identifier sequence includes at least one first road segment identifier arranged according to a target sorting rule, wherein the first road segment identifier is identifier information of a road segment in the task collection path; the target sorting rule matches the task collection path indicated by the target collection task;

[0036] The determining, according to the road segment identification sequence and the positions and generation times of the trajectory points in the third vehicle trajectory, a to-be-matched road segment identification sequence corresponding to the third vehicle trajectory comprises:

[0037] Determine, according to the position of each trajectory point in the third vehicle trajectory, a second road segment identifier corresponding to each trajectory point, wherein the second road segment identifier is a first road segment identifier in the road segment identifier sequence that matches the trajectory point;

[0038] The second road segment identifiers corresponding to each trajectory point are sorted in order from early to late according to the generation time of each trajectory point, so as to obtain a sequence of to-be-matched road segment identifiers corresponding to the third vehicle trajectory.

[0039] In a possible implementation manner, before acquiring geographic information data matching the target collection task by collecting the vehicles of each second vehicle trajectory, the method further includes:

[0040] Determining a quality screening parameter for each second vehicle trajectory according to a position and a generation time of a trajectory point in each second vehicle trajectory;

[0041] Filtering at least one fourth vehicle trajectory from the at least one second vehicle trajectory according to a quality screening parameter of each of the second vehicle trajectories;

[0042] Correspondingly, the step of acquiring geographic information matching the target collection task by collecting the vehicles of each second vehicle trajectory includes:

[0043] By collecting the vehicles of each of the fourth vehicle trajectories, geographic information data matching the target collection task is obtained.

[0044] In a second aspect, an embodiment of the present application provides a device for collecting geographic information, including:

[0045] Processing modules for:

[0046] Determine a target acquisition task matching a target geographic area, and determine at least one first vehicle trajectory within the target geographic area; the target geographic area is a service area corresponding to a first device node in a device cluster system, and the service areas of at least two device nodes in the device cluster system do not completely overlap;

[0047] Determining, from the at least one first vehicle trajectory, at least one second vehicle trajectory that matches the task collection path indicated by the target collection task;

[0048] The acquisition module is used to acquire geographic information data matching the target acquisition task by acquiring each vehicle of the second vehicle trajectory.

[0049] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0050] Processor, memory, communication interface;

[0051] The memory is used to store executable instructions of the processor;

[0052] Wherein, the processor is configured to execute the method for collecting geographic information data as described in any one of the first aspects by executing the executable instructions.

[0053] In a fourth aspect, an embodiment of the present application provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for collecting geographic information data described in any one of the first aspects is implemented.

[0054] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the method for collecting geographic information data as described in any one of the first aspects.

[0055] The method, device and medium for collecting geographic information provided in the embodiments of the present application, after determining the target collection task matching the target geographic area and at least one first vehicle track in the target geographic area through the first device node of the device cluster system, at least one second vehicle track matching the task collection path indicated by the target collection task is determined from the at least one first vehicle track. Then, by collecting vehicles of each second vehicle track, geographic information matching the target collection task is obtained. In this solution, the device nodes of the device cluster system collect geographic information, there are many device nodes, and each device node corresponds to a different target geographic area, and the determined target collection tasks and first vehicle tracks are also different, and then different geographic information is collected. The geographic information is collected by the device nodes in the device cluster system, which effectively improves the efficiency of collecting geographic information. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0057] Figure 1 A schematic diagram of an application scenario of the method for collecting geographic information provided in this application;

[0058] Figure 2 A flowchart of a first embodiment of a method for collecting geographic information provided in this application;

[0059] Figure 3 A flowchart of a second embodiment of a method for collecting geographic information provided in this application;

[0060] Figure 4 A flowchart of a third embodiment of the method for collecting geographic information provided in this application;

[0061] Figure 5 A schematic diagram of the structure of an embodiment of a device for collecting geographic information provided in this application;

[0062] Figure 6 A schematic diagram of the structure of an electronic device provided in this application.

[0063] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0064] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0065] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0066] With the development of science and technology, high-precision maps have emerged, providing technical support for intelligent driving and unmanned driving. When building high-precision maps, it is necessary to collect geographic information such as point clouds and images for construction.

[0067] In the prior art, the method for collecting geographic information data that can be used to build high-precision maps is usually to first obtain all the original geographic information data collected by the vehicle. Since some of the data does not meet the conditions or is redundant, it is necessary to manually eliminate these data to obtain the road geographic information data used to build high-precision maps.

[0068] Since it is necessary to first obtain all the original geographic information data and then collect the geographic information data by manual screening, it will lead to the problem of low efficiency in collecting geographic information data.

[0069] In view of the problems existing in the prior art, the inventor discovered in the process of studying the method of collecting geographic information that in order to improve the collection efficiency, the device nodes in the device cluster system can be used for collection, and different device nodes correspond to different target geographical areas, thereby determining the geographical information in the target geographical area that can be used to build a high-precision map, and then collecting these geographical information, which effectively improves the collection efficiency. Based on the above invention concept, the collection scheme of geographic information in this application is designed.

[0070] For example, Figure 1 A schematic diagram of the application scenario of the method for collecting geographic information data provided in this application, such as Figure 1 As shown, the application scenario may include: a device cluster system 11 and a vehicle 12, wherein the device cluster system 11 includes multiple device nodes (only four device nodes are shown in the figure, namely device node 111, device node 112, device node 113 and device node 114).

[0071] It should be noted that the device cluster system is a cluster composed of multiple device nodes. Those skilled in the art can set the total number of device nodes in the device cluster system according to actual needs, such as referring to one or more factors such as the overall service area of ​​the device cluster system, the computing power of a single device node, the processing efficiency of the device cluster system, and the service accuracy of the device cluster system, etc. to set the total number of device nodes in the device cluster system; the device node can be a terminal device, server, gateway, or other device with computing capabilities, and the device types of different device nodes in the device cluster system can be the same or different. The architecture of the device cluster system can be any architecture form such as distributed architecture, centralized architecture, master-slave architecture, cloud architecture, Internet of Things, or Internet of Vehicles. The embodiment of the present application does not limit the architecture of the device node and the device cluster system, which can be determined according to actual conditions.

[0072] In this application scenario, the vehicle 12 collects geographic information data through a laser radar, camera or other geographic information collection equipment and / or sensor installed on the vehicle.

[0073] In the embodiments of the present application, different service areas can be set for different device nodes in the device cluster system, such as the service areas of at least two device nodes in the device cluster system can be set to not completely overlap; that is, the service areas of different device nodes in the device cluster system can be set to be completely different, or the service areas of at least two device nodes in the device cluster system can be set to be completely different, or the service areas of at least two device nodes in the device cluster system can be set to not completely overlap (that is, in this case, there can be a partial overlap in the service areas of at least two device nodes), etc. Those skilled in the art can flexibly set corresponding service areas for different device nodes by comprehensively considering factors such as the overall service area of ​​the device cluster system, the service efficiency and / or service accuracy of the device cluster system, the cost of the device nodes, the coverage range of the services provided by the device nodes, the service efficiency and / or accuracy of the device nodes, and the like.

[0074] For ease of description, the device node 111 is taken as the first device node as an example to provide a general description of the method for collecting geographic information data provided by the embodiment of the present application. In this method:

[0075] The device node 111 determines a target collection task that matches the target geographic area corresponding to itself, and determines at least one first vehicle trajectory within the target geographic area; from the at least one first vehicle trajectory, determines at least one second vehicle trajectory that matches the task collection path indicated by the target collection task; and then obtains geographic information data that matches the target collection task by collecting vehicles of each second vehicle trajectory.

[0076] Further, the target collection task may be determined by the device node 111 or by the second device node. For example, the device node 112 is used as the second device node as an example. The device node 112 may determine at least one first vehicle trajectory in the target geographical area according to the target geographical area of ​​the device node 111. The device node 112 may determine the target collection task according to the task collection path and the target geographical area indicated by the initial collection task, and send the target collection task and the at least one first vehicle trajectory to the device node 111. Then, the device node 111 may determine at least one second vehicle trajectory that matches the task collection path indicated by the target collection task from the at least one first vehicle trajectory. Trajectory, and by collecting vehicles of each second vehicle trajectory, obtain geographic information matching the target collection task; device node 112 can also send at least one initial collection task and the first vehicle trajectory to device node 111; then device node 111 determines the target collection task according to the task collection path and the target geographical area indicated by the initial collection task, and device node 111 determines at least one second vehicle trajectory matching the task collection path indicated by the target collection task from at least one first vehicle trajectory, and obtains geographic information matching the target collection task by collecting vehicles of each second vehicle trajectory, that is, obtains geographic information matching the target collection task through vehicle 12.

[0077] It should be noted that the first device node and the second device node in the embodiment of the present application may be the same device node or different device nodes, and those skilled in the art may determine the device according to actual conditions.

[0078] It should be noted that Figure 1 This is only a schematic diagram of an application scenario provided by the embodiment of the present application. Figure 1 The actual form of the various devices included in the Figure 1 The interaction mode between devices is limited, and in the specific application of the solution, it can be set according to actual needs.

[0079] The technical solution of the present application is described in detail below through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0080] Figure 2The flowchart of the first embodiment of the method for collecting geographic information provided by the present application is as follows. After the first device node in the device cluster system determines the target collection task and the first vehicle trajectory, the second vehicle trajectory matching the target collection task is determined from the first vehicle trajectory, and then the geographic information is obtained from the vehicles that collect the second vehicle trajectories. The method in this embodiment can be implemented by software, hardware, or a combination of software and hardware. Figure 2 As shown, the method for collecting geographic information data specifically includes the following steps:

[0081] S201: Determine a target acquisition task matching a target geographical area, and determine at least one first vehicle track within the target geographical area.

[0082] In order to improve the efficiency of collecting geographic information, the device nodes in the device cluster system can be used to collect the information separately.

[0083] In this step, in order to collect geographic information data, the first device node in the device cluster system first determines a target collection task that matches the target geographic area, and determines at least one first vehicle trajectory within the target geographic area.

[0084] Among them, the target geographical area is the service area corresponding to the first device node, and the service areas of at least two device nodes in the device cluster system do not completely overlap; in the embodiment of the present application, the service area corresponding to each device node may include one sub-area, or may include two or more sub-areas; in the embodiment of the present application, different sub-areas may be set by the regional division stipulated by the administrative management, such as each administrative area stipulated by the administrative management (such as including but not limited to the province area, autonomous region, municipal area, or any one or more combinations of the districts and counties under the jurisdiction of the city) may be set as a sub-area respectively; each sub-area may also be obtained by regional division according to the geographical longitude and latitude. The service areas corresponding to different device nodes may include the same sub-areas, and the service areas corresponding to different device nodes may also have no overlapping sub-areas at all. For ease of understanding, a specific example of the service areas divided for different device nodes is given here. The service area of ​​device node 1 may be set as a range consisting of sub-area A, sub-area B, and sub-area C, the service area of ​​device node 2 may be set as a range consisting of sub-area C, sub-area D, and sub-area E, and the service area of ​​device node 3 may be set as a range consisting of sub-area J, sub-area G, and sub-area Sin. The service areas of device node 1 and device node 2 have the same sub-area C, and the service areas of device node 1 and device node 3 have no overlapping sub-areas.

[0085] The method for the first device node to determine the target collection task can be: the second device node in the device cluster system stores the initial collection task, and the second device node processes the initial collection task based on the target geographical area to obtain the target collection task. The second device node sends the target collection task to the first device node, and the first device node can receive the target collection task.

[0086] The first device node may also determine the target collection task in the following manner: the second device node in the device cluster system stores the initial collection task, and the second device node sends the initial collection task to the first device node, so that the first device node can receive the initial collection task. The first device node then processes the initial collection task based on the target geographical area to obtain the target collection task, that is, determines the target collection task based on the task collection path and the target geographical area indicated by at least one initial collection task.

[0087] It should be noted that the initial collection task is processed based on the target geographical area to obtain the target collection task in the following manner:

[0088] For each initial collection task, the road segment identifier of the target geographical area corresponding to the road segment identifier sequence of the initial collection task is used as the target road segment identifier of the initial collection task. The road segment identifier sequence is a sequence composed of road segment identifiers, and the road segments corresponding to the road segment identifiers in the road segment identifier sequence can constitute the task collection path. The road segment identifier is the identification information of the road segment.

[0089] It should be noted that the target collection task determined by the first device node may be one or more.

[0090] Then, for each initial collection task, the target road segment identifiers of the initial collection task are sorted according to the order of the road segment identifiers in the road segment identifier sequence of the initial collection task to obtain a new road segment identifier sequence, and the new road segment identifier sequence is used as the road segment identifier sequence of the target collection task to obtain the target collection task.

[0091] Exemplarily, the road segment identification sequence of the initial collection task is: A, B, C, D, E, F, where the road segments corresponding to B, C, D belong to the target geographical area, so the road segment identification sequence of the target collection task is B, C, D.

[0092] The manner in which the first device node determines the first vehicle trajectory may be: the first device node obtains at least one original vehicle trajectory, and then determines a trajectory segment in each original vehicle trajectory that belongs to a target geographical area as the first vehicle trajectory.

[0093] It should be noted that the first device node may obtain the original vehicle trajectory in the following manner: the second node device sends the original vehicle trajectory to the first device node, and the first device node can obtain the original vehicle trajectory. It can also be that the first device node obtains the original vehicle trajectory from the cloud platform storing the vehicle trajectory. It can also be that the staff uses the terminal device to send the original vehicle trajectory to the first device node, and the first device node can obtain the original vehicle trajectory. The embodiment of the present application does not limit the manner in which the first device node obtains the original vehicle trajectory, and it can be determined according to actual conditions.

[0094] The first device node may also determine the first vehicle trajectory in the following manner: the second device node stores the original vehicle trajectory, and the second device node determines the first vehicle trajectory based on the target geographical area, that is, the trajectory segment belonging to the target geographical area in each original vehicle trajectory is determined as the first vehicle trajectory, and then the first vehicle trajectory is sent to the first device node. The first device node receives at least one first vehicle trajectory sent by the first device node, and thus determines the first vehicle trajectory.

[0095] It should be noted that the vehicle trajectory can be composed of trajectory points.

[0096] S202: Determine at least one second vehicle trajectory that matches the task collection path indicated by the target collection task from the at least one first vehicle trajectory.

[0097] In this step, after the first device node determines the target collection task and the first vehicle trajectory, it determines at least one second vehicle trajectory matching the task collection path indicated by the target collection task from the at least one first vehicle trajectory.

[0098] The road segments corresponding to the road segment identifiers in the road segment identifier sequence of the target collection task can constitute the task collection path, so the first vehicle trajectory can be segmented and screened according to the road segment identifier sequence of the target collection task to obtain the second vehicle trajectory.

[0099] The second vehicle trajectory matches the mission collection path, indicating that the geographic information data collected by the vehicle on the road corresponding to the second vehicle trajectory can be used to construct a high-precision map.

[0100] S203: Acquire geographic information data matching the target collection task by collecting vehicles of each second vehicle trajectory.

[0101] In this step, after obtaining the second vehicle trajectory, the first device node acquires geographic information data matching the target collection task by collecting vehicles of each second vehicle trajectory.

[0102] Since the vehicle collects a lot of geographic information data on the road corresponding to the second vehicle trajectory, if all of them are acquired, there will be redundant geographic information data, so it is sufficient to acquire part of the geographic information data.

[0103] Specifically, the following processing is performed for each second vehicle trajectory:

[0104] According to the preset data acquisition rule, the data index point corresponding to the second vehicle trajectory is determined.

[0105] The data index point can be a location point, indicating the location of the vehicle when the corresponding geographic information data is collected; the data index point can also be a time point, indicating the moment when the vehicle collects the corresponding geographic information data.

[0106] In one implementation, at least one first position point is obtained from the second vehicle trajectory, and the first position point is used as a data index point.

[0107] It should be noted that the method of obtaining the first position point from the second vehicle trajectory can be equidistant acquisition, random acquisition, or selecting a preset number of first position points with equal spacing. The distance of equidistant points can be 3 meters, 5 meters, 10 meters, etc., and the preset number can be 10, 20, 50, 100, 500, etc. The embodiment of the present application does not limit the distance of equidistant points, the preset number, and the method of obtaining the first position point from the second vehicle trajectory, which can be determined according to actual conditions.

[0108] In another implementation, at least one second position point is obtained from the second vehicle trajectory, and then based on the position and generation time of each trajectory point in the second vehicle trajectory, a reference time point corresponding to each second position point is determined as a data index point.

[0109] It should be noted that the method of obtaining at least one second position point from the second vehicle trajectory is similar to the method of obtaining the first position point from the second vehicle trajectory, which will not be described in detail here.

[0110] The vehicle driving model can be constructed based on the position and generation time of the trajectory point in the second vehicle trajectory, and then the corresponding reference time point can be determined in combination with the position of the second position point. For example, the average speed of the vehicle in the second vehicle trajectory can be determined based on the position and generation time of the starting and ending trajectory points in the second vehicle trajectory, and then the vehicle driving model can be constructed as a uniform speed driving model, and the time when the vehicle drives to the second position point can be determined based on the average speed, the position and generation time of the starting trajectory point in the second vehicle trajectory, as the reference time point.

[0111] After the data index points are determined, the geographic information data corresponding to each data index point is obtained by collecting vehicles of each second vehicle trajectory.

[0112] That is, for each second vehicle trajectory, a data collection request is sent to the vehicle that collects the second vehicle trajectory, and the data collection request includes the data index point corresponding to the second vehicle trajectory. Since the geographic information data in the vehicle and the data index point are used as indexes, the vehicle sends the geographic information data corresponding to the data index point to the first device node according to the data index point in the data collection request, and the first device node can receive the geographic information data, thereby realizing the collection of geographic information data.

[0113] The method for collecting geographic information provided in this embodiment determines the target collection task that matches the target geographic area and at least one first vehicle track in the target geographic area through the first device node of the device cluster system, and then determines at least one second vehicle track that matches the task collection path indicated by the target collection task from the at least one first vehicle track. Then, by collecting vehicles of each second vehicle track, the geographic information that matches the target collection task is obtained. In this solution, the device nodes of the device cluster system collect geographic information, there are many device nodes, and each device node corresponds to a different target geographic area, and the determined target collection tasks and first vehicle tracks are also different, and then different geographic information is collected. The geographic information is collected by the device nodes in the device cluster system, and no manual collection is required, which effectively improves the efficiency of collecting geographic information and also improves the accuracy of the collected geographic information.

[0114] After the device nodes in the device cluster system obtain the original vehicle trajectory, each device node determines the trajectory segment in each original vehicle trajectory that belongs to its own corresponding target geographical area as the first vehicle trajectory, that is, the complete trajectory of the same vehicle is divided into different device nodes for processing. Each device node processes the first vehicle trajectory in its corresponding target geographical area to obtain geographic information data, so that the device nodes in the entire device cluster system can collect geographic information data, and each device node is responsible for collecting geographic information data in its own corresponding target geographical area, which effectively improves the efficiency of collecting geographic information data.

[0115] In addition, the device nodes do not need to store all geographic information, which reduces the storage pressure of the device nodes. And by increasing the number of device nodes in the device cluster system, the ability to collect geographic information can be expanded.

[0116] Figure 3 This is a flow chart of the second embodiment of the method for collecting geographic information provided by this application. Based on the above embodiment, this embodiment of the application describes the situation where the first device node determines the second vehicle trajectory from the first vehicle trajectory. Figure 3 As shown, the method for collecting geographic information data specifically includes the following steps:

[0117] S301: Determine a task area according to a road segment identification sequence.

[0118] In this step, after the first device node determines the target collection task and the first vehicle trajectory, since each target collection task includes a road segment identification sequence, the target collection task indicates the task collection path through the road segment identification sequence, that is, the road segments corresponding to the road segment identifications in the road segment identification sequence can constitute the task collection path.

[0119] Therefore, it is necessary to collect the geographic information data of the road section corresponding to the road section identification sequence, which requires determining the task area based on the road section identification sequence.

[0120] The area formed by the road segments corresponding to the road segment identifiers in the road segment identifier sequence is used as the task area.

[0121] S302: Determine a trajectory segment belonging to the task area in the at least one first vehicle trajectory as a third vehicle trajectory corresponding to the target collection task.

[0122] In this step, after the first device node determines the task area, the trajectory segment belonging to the task area in each first vehicle trajectory is determined as the third vehicle trajectory corresponding to the target collection task.

[0123] Since the vehicle trajectory can be composed of trajectory points, the trajectory points belonging to the task area in the first vehicle trajectory are used as the third vehicle trajectory.

[0124] For example, the road segment identification sequence of target collection task A is: A, B, C, D, E, F, the road segments corresponding to AF constitute the task area, and the first vehicle trajectory is track point 1-track point 5, where track point 1 belongs to the road segment corresponding to A, track point 2 belongs to the road segment corresponding to B, track point 3 belongs to the road segment corresponding to C, and track point 4 and track point 5 do not belong to the road segment corresponding to AF. Therefore, track point 1-track point 3 constitute the third vehicle trajectory.

[0125] S303: Using the third vehicle trajectory that matches the road segment identification sequence as the second vehicle trajectory.

[0126] In this step, after the first device node determines the third vehicle trajectory corresponding to the target collection task, it is also necessary to determine the second vehicle trajectory that matches the task collection path indicated by the target collection task, that is, the third vehicle trajectory that matches the road segment identification sequence is used as the second vehicle trajectory.

[0127] The road segment identifier sequence includes at least one first road segment identifier arranged according to a target sorting rule, the first road segment identifier being identifier information of a road segment in a task collection path, and the target sorting rule matches the task collection path indicated by the target collection task.

[0128] Therefore, the geographic information data collected when the vehicle passes through the sections corresponding to the section marks in the order of the section marks in the road section mark sequence is the data required to build a high-precision map, so it is necessary to match the third vehicle trajectory according to the road section mark sequence.

[0129] Specifically, the following processing is performed for each third vehicle trajectory:

[0130] According to the road segment identification sequence and the positions and generation times of the trajectory points in the third vehicle trajectory, a to-be-matched road segment identification sequence corresponding to the third vehicle trajectory is determined.

[0131] First, according to the position of each trajectory point in the third vehicle trajectory, the second road segment identifier corresponding to each trajectory point is determined, and the second road segment identifier is the first road segment identifier in the road segment identifier sequence that matches the trajectory point.

[0132] Exemplarily, the road segment identifier sequence is: A, B, C, D, E, where A, B, C, D, E are all first segment identifiers. Track point 1 belongs to the segment corresponding to the first segment identifier B, and track point 2 belongs to the segment corresponding to the first segment identifier C, so the second segment identifier corresponding to track point 1 is B, and the second segment identifier corresponding to track point 2 is C.

[0133] Then, the second road segment identifiers corresponding to each trajectory point are sorted in order from early to late according to the generation time of each trajectory point, so as to obtain a sequence of to-be-matched road segment identifiers corresponding to the third vehicle trajectory.

[0134] It should be noted that after sorting the second road segment identifiers corresponding to each trajectory point in the third vehicle trajectory, duplicate removal can be performed on the consecutive identical second road segments to obtain a sequence of road segment identifiers to be matched. Exemplarily, the second road segment identifiers corresponding to each trajectory point in the third vehicle trajectory are sorted to obtain A, B, B, B, C, D, E, E, F, and the sequence of road segment identifiers to be matched obtained by deduplication is A, B, C, D, E, F.

[0135] After the first device node determines the to-be-matched road segment identification sequence corresponding to the third vehicle trajectory, if the to-be-matched road segment identification sequence corresponding to the third vehicle trajectory is the same as the road segment identification sequence, the third vehicle trajectory is used as the second vehicle trajectory.

[0136] Exemplarily, the road segment identification sequence is A, B, C, D, E, F, G, and the to-be-matched road segment identification sequence is also A, B, C, D, E, F, G, which are the same, and the third vehicle trajectory is the second vehicle trajectory.

[0137] Exemplarily, the road segment identification sequence is A, B, C, D, E, F, G, and the road segment identification sequence to be matched is also A, B, C, D. Although the first four road segment identifications of the two are the same, the number of road segment identifications of the two is different, and the two are still different. The third vehicle trajectory is not the second vehicle trajectory.

[0138] Exemplarily, the road segment identification sequence is A, B, C, D, E, F, G, and the to-be-matched road segment identification sequence is B, C, A, D, G, F, E. Although the two have the same number of road segment identifications, the order of their road segment identifications is different, and the two are still not the same. The third vehicle trajectory is not the second vehicle trajectory.

[0139] It should be noted that after the server obtains the third vehicle trajectory, the third vehicle trajectory can be corrected according to the position and generation time of the trajectory point in the third vehicle trajectory, as well as the driving direction and speed of the vehicle, and then the corrected third vehicle trajectory matching the road segment identification sequence is used as the second vehicle trajectory.

[0140] The method for collecting geographic information provided in this embodiment determines the task area and uses the part of the first vehicle trajectory that belongs to the task area as the third vehicle trajectory. If the road segment identification sequence to be matched of the third vehicle trajectory is the same as the road segment identification sequence of the collection task, the third vehicle trajectory is used as the second vehicle trajectory. Since the target sorting rule of the first road segment identification in the road segment identification sequence represents the task collection path indicated by the target collection task, the road segment identification sequence to be matched is the same as the road segment identification sequence, indicating that the vehicle is the second vehicle trajectory formed by driving in the task collection path. Therefore, the subsequent collection of geographic information based on the second vehicle trajectory can effectively improve the accuracy of the geographic information.

[0141] Figure 4 This is a flow chart of the third embodiment of the method for collecting geographic information provided by this application. Based on the above embodiment, this embodiment of the application describes the situation where the first device node obtains geographic information by quality screening the second vehicle trajectory to obtain the fourth vehicle trajectory. Figure 4 As shown, the method for collecting geographic information data specifically includes the following steps:

[0142] S401: Determine a quality screening parameter for each second vehicle trajectory according to the position and generation time of a trajectory point in each second vehicle trajectory.

[0143] In this step, after the first device node determines the second vehicle trajectory, in order to improve the quality of the geographic information data, the second vehicle trajectory can be screened. First, the quality screening parameters of each second vehicle trajectory are determined according to the position and generation time of the trajectory point in each second vehicle trajectory. The quality screening parameters include at least one of weather visibility, collection period, and sun angle.

[0144] Since weather visibility, collection period and sun angle will affect the quality of geographic information data, and further affect the generated high-precision map, the second vehicle trajectory can be screened according to at least one of weather visibility, collection period and sun angle.

[0145] The time between the generation time of the starting track point in the second vehicle track and the generation time of the ending track point can be used as the collection period. The corresponding weather visibility and sun angle can be queried and obtained according to the position and generation time of any track point.

[0146] S402: Filter out at least one fourth vehicle trajectory from at least one second vehicle trajectory according to the quality screening parameter of each second vehicle trajectory.

[0147] In this step, after the first device node determines the quality screening parameter, it screens out at least one fourth vehicle trajectory from at least one second vehicle trajectory according to the quality screening parameter of each second vehicle trajectory.

[0148] The second vehicle trajectory whose quality screening parameter satisfies the preset quality screening condition is used as the fourth vehicle trajectory. The preset quality screening condition retains at least one of the first condition, the second condition, and the third condition.

[0149] The first condition is that the weather visibility falls within the preset visibility range.

[0150] The second condition is that the collection period belongs to the preset period.

[0151] The third condition is that the sun's radiation angle is within a preset angle range.

[0152] It should be noted that the preset visibility range can be [3, +∞], [5, +∞], [10, +∞], etc., in kilometers; the preset time period can be 6:00-18:00, 8:00-16:00, 10:00-14:00, etc.; the preset angle range includes the solar altitude angle range and the solar azimuth angle range, the solar altitude angle range can be 10 degrees-90 degrees, 20 degrees-90 degrees, 30 degrees-90 degrees, etc., the solar azimuth angle range can be 100 degrees-260 degrees, 120 degrees-240 degrees, 135 degrees-225 degrees, etc., the solar radiation angle also includes the solar altitude angle and the solar azimuth angle, the solar radiation angle belonging to the preset angle range means that the solar altitude angle belongs to the solar altitude angle range, and the solar azimuth angle belongs to the solar azimuth angle range. The embodiment of the present application does not limit the preset visibility range, the preset time period, the solar altitude angle range and the solar azimuth angle range, and can be determined according to actual conditions.

[0153] S403: Acquire geographic information data matching the target collection task by collecting vehicles of each fourth vehicle trajectory.

[0154] It should be noted that this step is similar to step S203 in the first embodiment and will not be described in detail here.

[0155] The method for collecting geographic information data provided in this embodiment obtains the fourth vehicle trajectory by screening the second vehicle trajectory according to weather visibility, collection period and sun angle, and then obtains geographic information data matching the target collection task by collecting vehicles in each fourth vehicle trajectory, thereby effectively improving the quality of the geographic information data.

[0156] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0157] Figure 5 This is a schematic diagram of the structure of an embodiment of a device for collecting geographic information provided in this application; the device can be integrated into the first node device in the above method embodiment, or can be implemented by the first node device in the above method embodiment. Figure 5 As shown, the geographic information data collection device 50 includes:

[0158] The processing module 51 is used for:

[0159] Determine a target acquisition task matching a target geographic area, and determine at least one first vehicle trajectory within the target geographic area; the target geographic area is a service area corresponding to a first device node in a device cluster system, and the service areas of at least two device nodes in the device cluster system do not completely overlap;

[0160] Determining, from the at least one first vehicle trajectory, at least one second vehicle trajectory that matches the task collection path indicated by the target collection task;

[0161] The acquisition module 52 is used to acquire geographic information data matching the target acquisition task by acquiring vehicles with the second vehicle trajectory.

[0162] Furthermore, when the acquisition module 52 is used to acquire geographic information data matching the target acquisition task by acquiring the vehicles of each second vehicle trajectory, it is specifically used to:

[0163] The following processing is performed for each of the second vehicle trajectories:

[0164] Determining a data index point corresponding to the second vehicle trajectory according to a preset data acquisition rule;

[0165] By collecting the vehicles of the second vehicle trajectory, the geographic information data corresponding to each of the data index points is obtained.

[0166] Furthermore, when the acquisition module 52 is used to determine the data index point corresponding to the second vehicle trajectory according to the preset data acquisition rule, it is specifically used to:

[0167] Acquire at least one first position point from the second vehicle trajectory, and use the first position point as the data index point;

[0168] or,

[0169] Acquire at least one second position point from the second vehicle trajectory; based on the position and generation time of each trajectory point in the second vehicle trajectory, determine the reference time point corresponding to each second position point as the data index point.

[0170] Furthermore, when the processing module 51 is used to determine the target acquisition task matching the target geographical area, it is specifically used to:

[0171] receiving the target acquisition task sent by a second device node in the device cluster system, where the target acquisition task is determined by the second device node based on the target geographical area;

[0172] or,

[0173] Receive at least one initial collection task sent by the second device node, and determine the target collection task according to the task collection path indicated by the at least one initial collection task and the target geographical area.

[0174] Furthermore, when the processing module 51 is used to determine at least one first vehicle trajectory in the target geographical area, it is specifically used to:

[0175] Acquire at least one original vehicle trajectory; determine the trajectory segment belonging to the target geographical area in each of the original vehicle trajectories as the first vehicle trajectory;

[0176] Alternatively, at least a first vehicle trajectory sent by a second device node in the device cluster system is received, where the first vehicle trajectory is determined by the second device node based on the target geographical area.

[0177] Furthermore, the target collection task indicates the task collection path through a road segment identification sequence.

[0178] When the processing module 51 is used to determine at least one second vehicle trajectory matching the task collection path indicated by the target collection task from the at least one first vehicle trajectory, it is specifically used to:

[0179] Determining a task area according to the road segment identification sequence;

[0180] Determining a trajectory segment belonging to the task area in the at least one first vehicle trajectory as a third vehicle trajectory corresponding to the target acquisition task;

[0181] A third vehicle trajectory matching the road segment identification sequence is determined as the second vehicle trajectory.

[0182] Further, when the processing module 51 is used to determine the third vehicle trajectory matching the road segment identification sequence as the second vehicle trajectory, it is specifically used to:

[0183] The following processing is performed for each of the third vehicle trajectories:

[0184] Determine a to-be-matched road segment identification sequence corresponding to the third vehicle trajectory according to the road segment identification sequence and the positions and generation times of the trajectory points in the third vehicle trajectory;

[0185] If the to-be-matched road segment identification sequence corresponding to the third vehicle trajectory is the same as the road segment identification sequence, the third vehicle trajectory is used as the second vehicle trajectory.

[0186] Further, the road segment identifier sequence includes at least one first road segment identifier arranged according to a target sorting rule, wherein the first road segment identifier is identifier information of a road segment in the task collection path; the target sorting rule matches the task collection path indicated by the target collection task;

[0187] When the processing module 51 is used to determine the to-be-matched road segment identification sequence corresponding to the third vehicle trajectory according to the road segment identification sequence and the position and generation time of the trajectory point in the third vehicle trajectory, it is specifically used to:

[0188] According to the position of each trajectory point in the third vehicle trajectory, a second road segment identifier corresponding to each trajectory point is determined, where the second road segment identifier is a first road segment identifier in the road segment identifier sequence that matches the trajectory point.

[0189] The second road segment identifiers corresponding to each trajectory point are sorted in order from early to late according to the generation time of each trajectory point, so as to obtain a sequence of to-be-matched road segment identifiers corresponding to the third vehicle trajectory.

[0190] Furthermore, before acquiring geographic information data matching the target collection task by collecting the vehicles of each second vehicle trajectory, the processing module 51 is further used to:

[0191] Determining a quality screening parameter for each second vehicle trajectory according to a position and a generation time of a trajectory point in each second vehicle trajectory;

[0192] Filtering at least one fourth vehicle trajectory from the at least one second vehicle trajectory according to a quality screening parameter of each of the second vehicle trajectories;

[0193] When the acquisition module 52 is used to acquire geographic information data matching the target acquisition task by acquiring the vehicles of each second vehicle trajectory, it is specifically used to:

[0194] By collecting the vehicles of each of the fourth vehicle trajectories, geographic information data matching the target collection task is obtained.

[0195] The device for collecting geographic information provided in this embodiment is used to execute the technical solution of the first device node in any of the aforementioned method embodiments. Its implementation principle and technical effects are similar and will not be repeated here.

[0196] Figure 6 This is a schematic diagram of the structure of an electronic device provided in this application. Figure 6 As shown, the electronic device 60 includes:

[0197] Processor 61, memory 62, and communication interface 63;

[0198] The memory 62 is used to store executable instructions of the processor 61;

[0199] The processor 61 is configured to execute the technical solution of the first device node in any of the aforementioned method embodiments by executing the executable instructions.

[0200] Optionally, the memory 62 may be independent or integrated with the processor 61 .

[0201] Optionally, when the memory 62 is a device independent of the processor 61, the electronic device 60 may further include:

[0202] The bus 64 , the memory 62 and the communication interface 63 are connected to the processor 61 via the bus 64 and communicate with each other. The communication interface 63 is used to communicate with other devices.

[0203] Optionally, the communication interface 63 may be implemented by a transceiver. The communication interface is used to implement communication between the database access device and other devices (such as a client, a read-write library, and a read-only library). The memory may include a random access memory (RAM) and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage.

[0204] The bus 64 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0205] The above-mentioned processor can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0206] The electronic device is used to execute the technical solution of the first device node in any of the aforementioned method embodiments, and its implementation principle and technical effect are similar and will not be repeated here.

[0207] An embodiment of the present application also provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the technical solution provided by any of the aforementioned method embodiments is implemented.

[0208] An embodiment of the present application also provides a computer program product, including a computer program, which is used to implement the technical solution provided by any of the aforementioned method embodiments when executed by a processor.

[0209] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0210] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for collecting geographic information, characterized in that: Applied to a device cluster system including a plurality of device nodes, each device node is responsible for collecting geographic information data within a target geographical area corresponding to itself, wherein when a first device node in the device cluster system collects geographic information data within a target geographical area corresponding to itself, it includes: Determine a target acquisition task matching a target geographical area, and determine at least one first vehicle trajectory within the target geographical area, wherein the target geographical area is a service area corresponding to the first device node, and the service areas of at least two device nodes in the device cluster system do not completely overlap; wherein the at least one first vehicle trajectory is a trajectory segment in each original vehicle trajectory that belongs to the target geographical area; Determining, from the at least one first vehicle trajectory, at least one second vehicle trajectory that matches the task collection path indicated by the target collection task; By collecting the vehicles of each second vehicle trajectory, geographic information data matching the target collection task is obtained.

2. The method according to claim 1, characterized in that The acquiring of geographic information data matching the target acquisition task by collecting the vehicles of each second vehicle trajectory includes: The following processing is performed for each of the second vehicle trajectories: Determining a data index point corresponding to the second vehicle trajectory according to a preset data acquisition rule; By collecting the vehicles of the second vehicle trajectory, the geographic information data corresponding to each of the data index points is obtained.

3. The method according to claim 2, characterized in that The step of determining the data index point corresponding to the second vehicle trajectory according to a preset data acquisition rule includes: Acquire at least one first position point from the second vehicle trajectory, and use the first position point as the data index point; or, Acquire at least one second position point from the second vehicle trajectory; based on the position and generation time of each trajectory point in the second vehicle trajectory, determine the reference time point corresponding to each second position point as the data index point.

4. The method according to claim 1, characterized in that: The determining of the target acquisition task matching the target geographical area includes: receiving the target acquisition task sent by a second device node in the device cluster system, where the target acquisition task is determined by the second device node based on the target geographical area; or, Receive at least one initial collection task sent by the second device node, and determine the target collection task according to the task collection path indicated by the at least one initial collection task and the target geographical area.

5. The method according to claim 1, characterized in that The determining of at least one first vehicle trajectory within the target geographic area comprises: Acquire at least one original vehicle trajectory; determine the trajectory segment belonging to the target geographical area in each of the original vehicle trajectories as the first vehicle trajectory; or, At least a first vehicle trajectory sent by a second device node in the device cluster system is received, where the first vehicle trajectory is determined by the second device node based on the target geographical area.

6. The method according to claim 1, characterized in that The target collection task indicates the task collection path through a road segment identification sequence; The step of determining, from the at least one first vehicle trajectory, at least one second vehicle trajectory that matches the task collection path indicated by the target collection task comprises: Determining a task area according to the road segment identification sequence; Determining a trajectory segment belonging to the task area in the at least one first vehicle trajectory as a third vehicle trajectory corresponding to the target acquisition task; A third vehicle trajectory matching the road segment identification sequence is determined as the second vehicle trajectory.

7. The method according to claim 6, characterized in that The step of determining the third vehicle trajectory matched with the road segment identification sequence as the second vehicle trajectory includes: The following processing is performed for each of the third vehicle trajectories: Determine a to-be-matched road segment identification sequence corresponding to the third vehicle trajectory according to the road segment identification sequence and the positions and generation times of the trajectory points in the third vehicle trajectory; If the to-be-matched road segment identification sequence corresponding to the third vehicle trajectory is the same as the road segment identification sequence, the third vehicle trajectory is used as the second vehicle trajectory.

8. The method according to claim 7, characterized in that The road segment identification sequence includes at least one first road segment identification arranged according to a target sorting rule, wherein the first road segment identification is identification information of a road segment in the task collection path; the target sorting rule matches the task collection path indicated by the target collection task; The determining, according to the road segment identification sequence and the positions and generation times of the trajectory points in the third vehicle trajectory, a to-be-matched road segment identification sequence corresponding to the third vehicle trajectory comprises: Determine, according to the position of each trajectory point in the third vehicle trajectory, a second road segment identifier corresponding to each trajectory point, wherein the second road segment identifier is a first road segment identifier in the road segment identifier sequence that matches the trajectory point; The second road segment identifiers corresponding to each trajectory point are sorted in order from early to late according to the generation time of each trajectory point, so as to obtain a sequence of to-be-matched road segment identifiers corresponding to the third vehicle trajectory.

9. The method according to any one of claims 1 to 8, characterized in that: Before acquiring geographic information data matching the target collection task by collecting the vehicles of each second vehicle trajectory, the method further includes: Determining a quality screening parameter for each second vehicle trajectory according to a position and a generation time of a trajectory point in each second vehicle trajectory; Filtering at least one fourth vehicle trajectory from the at least one second vehicle trajectory according to a quality screening parameter of each of the second vehicle trajectories; Correspondingly, the step of acquiring geographic information matching the target collection task by collecting the vehicles of each second vehicle trajectory includes: By collecting the vehicles of each of the fourth vehicle trajectories, geographic information data matching the target collection task is obtained.

10. An electronic device, characterized in that: include: Processor, memory, communication interface; The memory is used to store executable instructions of the processor; Wherein, the processor is configured to execute the method for collecting geographic information material as described in any one of claims 1 to 9 by executing the executable instructions.

11. A readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for collecting geographic information data as described in any one of claims 1 to 9 is implemented.

Images