Map data acquisition method and device and computer readable storage medium

Abstract

The invention discloses a map data collection method and device and a computer readable storage medium, and relates to the technical field of electronic maps, and the method comprises the steps: determining a starting position identifier when a data collection vehicle passes through a starting point of a pre-collection road, and obtaining a pre-collection road; determining an end position identifier when the data acquisition vehicle passes through the end point of the pre-acquisition road; determining target map data corresponding to the pre-acquired road from a map data set acquired by the data acquisition vehicle at least according to the starting position identifier and the ending position identifier; wherein the map data set is a set composed of map data collected in the process that the data collection vehicle travels along a data collection track, and the data collection track comprises a pre-collection road. The integrity of the map data collected by the vehicle can be improved, so that the accuracy of the map constructed or updated based on the map data is improved.

Description

Technical Field

[0001] The present application relates to the technical field of electronic maps, and in particular to a map data collection method, device and computer-readable storage medium. Background Art

[0002] With the rapid development of autonomous driving technology and intelligent transportation systems, accurate vehicle trajectory data is crucial for building and maintaining high-precision maps (HD maps or light maps).

[0003] At present, a commonly used map data collection method is to monitor the location information of vehicles used to collect road data through the cloud. When it is detected that a vehicle enters a specific section of road, the cloud matches the specific section of road where the vehicle is currently located with the track to be collected indicated by the collection task to be executed, and after matching the corresponding track to be collected, sends a data collection instruction to the vehicle, instructing the vehicle to start road data collection to perform the collection task, and returns the collected road data to the cloud after the vehicle completes the driving of the specific section of road. However, in this process, since the vehicle starts collecting data after receiving the data collection instruction sent by the cloud, and the vehicle is always driving, the road data corresponding to the distance from the entry point of the vehicle into the specific section of road to the position where the vehicle is when the data collection instruction is received is missing, thereby affecting the accuracy of the map constructed or updated based on the partially missing data.

[0004] Therefore, how to improve the integrity of map data collected by vehicles in order to improve the accuracy of maps built or updated based on the map data is a problem that urgently needs to be solved. Summary of the invention

[0005] The main purpose of the present application is to provide a map data collection method, device and computer-readable storage medium, aiming to improve the integrity of map data collected by a vehicle so as to improve the accuracy of maps constructed or updated based on the map data.

[0006] To achieve the above objectives, the present application provides a map data collection method, the map data collection method comprising: Determine a starting position mark when the data collection vehicle passes the starting point of the pre-collection road, and determine a termination position mark when the data collection vehicle passes the end point of the pre-collection road; Determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least according to the starting position identifier and the ending position identifier; The map data set is a set of map data collected by the data collection vehicle while traveling along a data collection track, and the data collection track includes the pre-collected road.

[0007] In one embodiment, the map data set is a video collected by the data collection vehicle during driving, the map data in the map data set is a video frame in the video, the starting position identifier is a timestamp of the video frame corresponding to the starting point, and the ending position identifier is a timestamp of the video frame corresponding to the end point.

[0008] In one embodiment, the step of determining the starting position mark when the data collection vehicle passes the starting point of the pre-collection road, and the step of determining the ending position mark when the data collection vehicle passes the end point of the pre-collection road, comprises: During the process of the data collection vehicle traveling along the data collection track, monitoring the real-time position information of the data collection vehicle; In response to monitoring that the data collection vehicle enters the pre-collection road from the starting point of the pre-collection road, triggering a starting position marker; and In response to monitoring that the data collection vehicle travels along the pre-collection road to an end point of the pre-collection road, triggering a termination position mark; or In response to monitoring that the data collection vehicle drives out of the pre-collection road from a non-end point of the pre-collection road, the step of monitoring the real-time position information of the data collection vehicle is returned to be executed.

[0009] In one embodiment, before the step of determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least based on the starting position identifier and the ending position identifier, the method further includes: Determining a target driving trajectory of the data collection vehicle on the pre-collection road; Determining whether a map data acquisition condition is met based on a match between the target driving trajectory and a reference trajectory indicated by the data collection task to be executed; When the map data acquisition condition is met, the target map data corresponding to the pre-collected road is determined from the map data set collected by the data collection vehicle at least according to the start position identifier and the end position identifier.

[0010] In one embodiment, before the step of determining whether a map data acquisition condition is met based on a match between the target driving trajectory and a reference trajectory indicated by the data collection task to be executed, the method further includes: In a case where the data collection task to be executed indicates a first road, determining a trajectory corresponding to the first road as a reference trajectory of the data collection task; In a case where the data collection task to be executed indicates a first lane, determining a trajectory corresponding to the first lane as a reference trajectory of the data collection task; In the case where the data collection task to be executed indicates a task type and collection trajectory information, a reference trajectory corresponding to the data collection task is determined according to the task type and the collection trajectory information.

[0011] In one embodiment, the task type is a road-level collection task or a lane-level collection task, and the collection trajectory information is a second road or a second lane; The step of determining the reference trajectory corresponding to the data collection task according to the task type and the collection trajectory information comprises: When the task type is a road-level data collection task and the collected trajectory information is a second road, determining a trajectory corresponding to the second road as a reference trajectory of the data collection task; When the task type is a road-level collection task and the collection trajectory information is a second lane, a trajectory corresponding to a third road where the second lane is located is determined as a reference trajectory of the data collection task, wherein a starting point of the second lane is the same as a starting point of the third road, and an end point of the second lane is the same as an end point of the third road; When the task type is a lane-level collection task and the collection trajectory information is for the second lane, determining the trajectory corresponding to the second lane as a reference trajectory corresponding to the data collection task; When the task type is a road-level data collection task and the collection trajectory information is a second road, a trajectory corresponding to a target lane in the second road is determined as a reference trajectory corresponding to the data collection task.

[0012] In one embodiment, the step of determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least according to the starting position identifier and the ending position identifier comprises: Determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle according to the starting position identifier and the ending position identifier, wherein the map data set is uploaded by the data collection vehicle; or The starting position identifier and the ending position identifier are indicated to the data collection vehicle, and the target map data corresponding to the pre-collected road returned by the data collection vehicle according to the starting position identifier and the ending position identifier is received.

[0013] In addition, to achieve the above-mentioned purpose, the present application also provides a map data collection method, which is applied to a data collection vehicle, and the map data collection method includes: Collecting map data while the data collection vehicle is traveling along the data collection track, and determining a set of the collected map data as a map data set collected by the data collection vehicle; Among them, the data collection trajectory includes a pre-collected road, and the map data set includes at least the starting position mark when the data collection vehicle passes the starting point of the pre-collected road, and the ending position mark when the data collection vehicle passes the end point of the pre-collected road.

[0014] In addition, to achieve the above-mentioned purpose, the present application also provides a map data collection device, the map data collection device comprising: An identification determination module, used to determine a starting position identification when the data collection vehicle passes the starting point of the pre-collection road, and to determine a termination position identification when the data collection vehicle passes the end point of the pre-collection road; A data extraction module is used to determine the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle based on at least the starting position identifier and the ending position identifier; wherein the map data set is a set of map data collected by the data collection vehicle during the process of traveling along a data collection track, and the data collection track includes the pre-collected road.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a map data acquisition device, which is applied to a data acquisition vehicle, and the map data acquisition device includes: A data collection module is used to collect map data while the data collection vehicle is traveling along a data collection track, and determine a set of collected map data as a map data set collected by the data collection vehicle; wherein the data collection track includes a pre-collected road, and the map data set includes at least a starting position identifier when the data collection vehicle passes the starting point of the pre-collected road, and an ending position identifier when the data collection vehicle passes the end point of the pre-collected road.

[0016] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and a program for implementing the map data collection method is stored on the computer-readable storage medium. The program for implementing the map data collection method is executed by a processor to implement the steps of the map data collection method as described above.

[0017] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned map data collection method when executed by a processor.

[0018] The present application provides a map data collection method, which determines a starting position identifier when a data collection vehicle passes the starting point of a pre-collected road, and determines a termination position identifier when the data collection vehicle passes the end point of the pre-collected road, and then determines target map data corresponding to the pre-collected road from a map data set collected by the data collection vehicle based on at least the starting position identifier and the termination position identifier, wherein the map data set is a collection of map data collected by the data collection vehicle during the process of driving along a data collection track, and the data collection track includes the pre-collected road.

[0019] To summarize, compared to the traditional method of matching data collection tasks when a vehicle is detected entering a specific road section, and issuing data collection instructions to instruct the vehicle to start collecting data after the match is successful, the data collection vehicle in the present application can start collecting map data before entering the pre-collected road without waiting for external instructions, and determine the starting position identifier and the ending position identifier when the data collection vehicle passes the starting point and end point of the pre-collected road, so as to obtain the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle based on the two position identifiers representing the location of the data collection vehicle, thereby avoiding the problem of partial missing of map data on the pre-collected road due to untimely issuance of instructions from the cloud, improving the integrity of the map data collected by the vehicle, and thus providing more reliable data support for map construction or map update, and improving the accuracy of maps built or updated based on map data. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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.

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0022] Figure 1 This is a flowchart of the first embodiment of the map data collection method of the present application; Figure 2 A first schematic diagram of vehicle position monitoring involved in an embodiment of the map data collection method of the present application; Figure 3 A second schematic diagram of vehicle position monitoring involved in an embodiment of the map data collection method of the present application; Figure 4 A third schematic diagram of vehicle position monitoring involved in an embodiment of the map data collection method of the present application; Figure 5 A fourth schematic diagram of vehicle position monitoring involved in an embodiment of the map data collection method of the present application; Figure 6 A schematic diagram of a map data collection process involved in an embodiment of the map data collection method of the present application; Figure 7 This is a schematic diagram of the device structure of the hardware operating environment involved in the map data collection method in the embodiment of the present application.

[0023] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0024] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0025] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0026] The main solution of the present application is: determining the starting position mark when the data collection vehicle passes the starting point of the pre-collected road, and determining the ending position mark when the data collection vehicle passes the end point of the pre-collected road; determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least based on the starting position mark and the ending position mark; wherein the map data set is a set of map data collected by the data collection vehicle during the driving of the data collection vehicle along the data collection track, and the data collection track includes the pre-collected road.

[0027] At present, a commonly used map data collection method is to monitor the location information of vehicles used to collect road data through the cloud. When it is detected that a vehicle enters a specific section of road, the cloud matches the specific section of road where the vehicle is currently located with the track to be collected indicated by the collection task to be executed, and after matching the corresponding track to be collected, sends a data collection instruction to the vehicle, instructing the vehicle to start road data collection to perform the collection task, and returns the collected road data to the cloud after the vehicle completes the driving of the specific section of road. However, in this process, since the vehicle starts collecting data after receiving the data collection instruction sent by the cloud, and the vehicle is always driving, the road data corresponding to the distance from the entry point of the vehicle into the specific section of road to the position where the vehicle is when the data collection instruction is received is missing, thereby affecting the accuracy of the map constructed or updated based on the partially missing data.

[0028] Compared to the traditional method of matching data collection tasks when a vehicle is detected entering a specific road section, and issuing data collection instructions to instruct the vehicle to start collecting data after the match is successful, the data collection vehicle in the present application can start collecting map data before entering the pre-collected road without waiting for external instructions, and determine the starting position identifier and the ending position identifier when the data collection vehicle passes the starting point and end point of the pre-collected road, so as to obtain the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle based on the two position identifiers representing the location of the data collection vehicle, thereby avoiding the problem of partial loss of map data on the pre-collected road due to untimely issuance of instructions from the cloud, improving the integrity of the map data collected by the vehicle, and thus providing more reliable data support for map construction or map update, and improving the accuracy of maps built or updated based on map data.

[0029] It should be noted that the execution subject of the method in each embodiment of the map data collection method of the present application can be the cloud, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an Internet of Things or Internet of Vehicles terminal with computing and processing capabilities, or a distributed system that can realize the above functions, etc. This embodiment does not specifically limit this. The following takes the cloud as the execution subject as an example to illustrate this embodiment and the following embodiments.

[0030] Based on this, the present application proposes a map data collection method of the first embodiment. The execution subject of the map data collection method is the cloud. For the convenience of description, the following content is described by omitting the execution subject. Figure 1 , the map data collection method includes steps S10 to S20: Step S10, determining a starting position mark when the data collection vehicle passes the starting point of the pre-collection road, and determining a termination position mark when the data collection vehicle passes the end point of the pre-collection road; It should be noted that the map data collection method of the embodiment of the present application is applied to the cloud, and the cloud is connected to multiple data collection vehicles in communication, wherein the data collection vehicle refers to a vehicle used to collect map data, and the embodiment of the present application does not limit the specific type of the data collection vehicle, and the data collection vehicle includes but is not limited to a collection vehicle, a crowdsourcing vehicle, a surveying vehicle, a non-operating vehicle using a corresponding electronic map, and a third-party professional vehicle, etc., wherein the crowdsourcing vehicle has the characteristics of disordered trajectory and large scale, and can meet the needs of local map updates. After starting, the data collection vehicle collects map data and its own location information (hereinafter referred to as real-time location information for distinction) in real time. The road section that needs to be collected for map data is configured in advance in the cloud, that is, the above-mentioned pre-collected road. It should be understood that the cloud is connected to the data collection vehicle in communication, and the cloud will select the pre-collected road in the map based on the user's instructions or the data collection task to be executed, and can obtain the real-time location information of the data collection vehicle to monitor the real-time location of the data collection vehicle. The starting position mark represents the location information of the data collection vehicle when collecting the starting point of the pre-collected road, and the ending position mark represents the location information of the data collection vehicle when collecting the end point of the pre-collected road. That is, it should be understood that there is a corresponding relationship between the location information of the data collection vehicle and the map data collected by the data collection vehicle.

[0031] Step S20, determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least according to the starting position identifier and the ending position identifier; It should be noted that the map data set is a set of map data collected by the data collection vehicle while driving along the data collection track, and the data collection track includes the pre-collected road. That is, the map data set includes the map data collected by the data collection vehicle on the pre-collected road.

[0032] Since there is a corresponding relationship between the starting position mark when the data collection vehicle passes the starting point of the pre-collected road and the map data collected by the data collection vehicle at the starting point, and there is a corresponding relationship between the ending position mark when the data collection vehicle passes the end point of the pre-collected road and the map data collected by the data collection vehicle at the end point, the map data corresponding to the starting position mark and the ending position mark can be determined from the map data set collected by the data collection vehicle according to the corresponding relationship between the starting position mark, the ending position mark and the vehicle position mark and the map data collected by the data collection vehicle, thereby determining that the starting map data of the map data corresponding to the pre-collected road (hereinafter referred to as the target map data for distinction) is the map data corresponding to the starting position mark, and the ending map data of the target map data is the map data corresponding to the ending position mark. Among them, the vehicle position mark includes at least the starting position mark and the ending position mark. And the target map data includes the map data collected by the data collection vehicle at each position on the pre-collected road.

[0033] In this way, compared with the traditional method of matching data collection tasks when a vehicle is monitored to enter a specific road section, and issuing a data collection instruction to instruct the vehicle to start collecting data after the match is successful, the data collection vehicle in the embodiment of the present application can start collecting map data before entering the pre-collected road without waiting for external instructions, and determine the starting position identifier and the ending position identifier when the data collection vehicle passes the starting point and end point of the pre-collected road, so as to obtain the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle based on the two position identifiers representing the location of the data collection vehicle, thereby avoiding the problem of partial loss of map data on the pre-collected road due to untimely issuance of instructions from the cloud, improving the integrity of the map data collected by the vehicle, and thus providing more reliable data support for map construction or map update, and improving the accuracy of maps built or updated based on map data.

[0034] In one feasible implementation, the map data set is a collection of map data collected by the data collection vehicle during driving, wherein the map data may be image data, point cloud data or other data types. Since the data collection vehicle collects map data and its own real-time location information in real time during driving, the data collection vehicle can record the collection location of the map data when collecting the map data, and save the mapping relationship between the map data and the collection location. Among them, the collection location recorded by the data collection vehicle is the GPS positioning point (track point) of the data collection vehicle, etc. In this way, the cloud can request the map data corresponding to each collection location on the pre-collected road from the data collection vehicle based on the starting position identifier and the end position identifier, that is, obtain the target map data of the pre-collected road in the map data set from the vehicle side.

[0035] In another feasible implementation, the map data set is a video collected by the data collection vehicle during driving, the map data in the map data set are video frames in the video, the starting position identifier is a timestamp of the video frame corresponding to the starting point, and the ending position identifier is a timestamp of the video frame corresponding to the end point.

[0036] It should be noted that the map data set is the video collected by the data collection vehicle during driving, and the map data in the map data set is the video frame in the video. The data type of the map data collected in real time by the data collection vehicle in the startup state is the video data type. Among them, when the map data set is a video, the video encoding method of the video collected by the data collection vehicle can be H.26X (such as H264, H265 or H266, etc.), AVSX (AVS1, AVS2 or AVS3) or other video encoding methods. The starting position identifier is the timestamp of the video frame collected by the data collection vehicle at the starting point of the pre-collected road, that is, the time information when the data collection vehicle is located at the starting point of the pre-collected road, and the ending position identifier is the timestamp of the video frame collected by the data collection vehicle at the end point of the pre-collected road, that is, the time information when the data collection vehicle is located at the end point of the pre-collected road. That is, there is a corresponding relationship between the vehicle position identifier and the map data, and the vehicle position identifier represents the position information of the data collection vehicle, so the corresponding relationship between the position information of the data collection vehicle and the map data can be determined based on the vehicle position identifier to determine the target map data corresponding to the pre-collected road from the map data set.

[0037] Thus, compared to the traditional method of collecting image data and saving it on the vehicle side, the embodiment of the present application compresses the map data of the video data type and saves it on the vehicle side, which can save two-thirds of the storage space and improve the efficiency of data storage to a certain extent, extending the life cycle of the data collection vehicle to achieve the purpose of reducing operating costs. And compared to the traditional data collection method of uploading image data to the cloud, the embodiment of the present application uploads map data to the cloud in the form of video stream, saving bandwidth resources. In addition, it should be understood that collecting map data by video can reduce redundant data storage, save traffic, and video supports complete data storage throughout the day.

[0038] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. On this basis, the step S10 may include: Step S101, monitoring the real-time position information of the data collection vehicle while the data collection vehicle is traveling along the data collection track; The data collection vehicle detects its own location information in real time during driving, i.e., the above-mentioned real-time location information. Specifically, this application does not limit how the cloud monitors the real-time location information of the data collection vehicle. In one feasible implementation, the data collection vehicle feeds back its real-time location information to the cloud in real time. In another feasible implementation, the cloud sends a location request instruction to the data collection vehicle, so that the data collection vehicle returns its real-time location information based on the location request instruction.

[0039] While the data collection vehicle is traveling along the data collection track, the cloud can monitor the real-time location information of the data collection vehicle.

[0040] Step S102, in response to monitoring that the data collection vehicle enters the pre-collection road from the starting point of the pre-collection road, triggering a starting position mark; When the cloud monitors that the data collection vehicle enters the pre-collected road from the starting point of the pre-collected road, the starting position mark is automatically triggered.

[0041] In one feasible implementation, the starting position marker represents the starting position information of the pre-collected road, and after the starting position marker is triggered, the mapping relationship between the starting position marker and the map data collected when the data collection vehicle enters the pre-collected road from the starting point of the pre-collected road is recorded. In another feasible implementation, the step of triggering the starting position marker specifically includes: determining the timestamp when the data collection vehicle enters the pre-collected road from the starting point of the pre-collected road as the starting position marker, so as to subsequently determine the mapping relationship between the corresponding starting position marker and the map data based on the timestamp.

[0042] Step S103, in response to monitoring that the data collection vehicle travels along the pre-collection road to the end point of the pre-collection road, triggering a termination position mark; When the cloud monitors that the data collection vehicle is driving along the pre-collected road to the end of the pre-collected route, the starting position mark is automatically triggered.

[0043] In one feasible implementation, the end position mark represents the terminal position information of the pre-collected road, and after the end position mark is triggered, the mapping relationship between the end position mark and the map data collected when the data collection vehicle exits the pre-collected road from the end point of the pre-collected road along the pre-collected road is recorded. In another feasible implementation, the step of triggering the start position mark specifically includes: determining the timestamp when the data collection vehicle exits the pre-collected road from the end point of the pre-collected road as the start end position mark, so as to determine the mapping relationship between the corresponding end position mark and the map data based on the timestamp later.

[0044] Step S104, in response to monitoring that the data collection vehicle drives out of the pre-collection road from a non-end point of the pre-collection road, returning to the step of monitoring the real-time position information of the data collection vehicle.

[0045] It should be noted that the positions on the pre-collected road other than the end of the pre-collected road are called non-end positions. The end of the pre-collected road is the position of the other end of the pre-collected road except the end where the data collection vehicle enters.

[0046] When the cloud monitors that the data collection vehicle drives out of the pre-collected road from a non-end point of the pre-collected road, the step of returning to execute the step of detecting the real-time position information of the data collection vehicle is performed.

[0047] For example, Figure 2 FIG. 1 is a first schematic diagram of vehicle position monitoring, in which the data collection vehicle is located at the starting point of the pre-collection road selected in the frame, and enters the pre-collection road from the starting point of the pre-collection road; Figure 3 FIG. 2 is a second schematic diagram of vehicle position monitoring, where the data collection vehicle is traveling on a pre-collection road; Figure 4 FIG. 3 is a third schematic diagram of vehicle position monitoring, in which the data collection vehicle is located at the end of the pre-collection road and drives out of the pre-collection road from the end of the pre-collection road. Figure 5 It is shown as a fourth schematic diagram of vehicle position monitoring, in which the data collection vehicle drives out of the pre-collection road from a non-end point of the pre-collection road.

[0048] In this embodiment, before step S20, the map data collection method of this application further includes: Step A10, determining the target driving trajectory of the data collection vehicle on the pre-collection road; Determine the driving trajectory of the data collection vehicle on the pre-collected road (hereinafter referred to as the target driving trajectory for distinction). It should be understood that the starting point of the target driving trajectory coincides with the starting point of the pre-collected road, the end point of the target driving trajectory coincides with the end point of the pre-collected road, and the target driving trajectory is distributed within the range of the pre-collected road.

[0049] Step A20, judging whether a map data acquisition condition is met according to a matching condition between the target driving trajectory and a reference trajectory indicated by the data collection task to be executed; It should be noted that each data collection task to be executed corresponds to an area to be collected, and the area to be collected indicated by the data collection task is called a reference trajectory.

[0050] According to the matching of the target driving trajectory and the reference trajectory indicated by the data collection task to be executed, it is judged whether the map data acquisition condition is met. Specifically, when the target driving trajectory and the reference trajectory are the same, it is considered that the matching of the target driving trajectory and the reference trajectory is a successful match, and it is determined that the map data acquisition condition is met.

[0051] Step A30, when the map data acquisition condition is met, the target map data corresponding to the pre-collected road is determined from the map data set collected by the data collection vehicle at least according to the start position identifier and the end position identifier.

[0052] When the data acquisition conditions are met, the target map data corresponding to the pre-collected road is determined from the map data set collected by the data collection vehicle at least according to the starting position identifier and the ending position identifier.

[0053] In this embodiment, before step A20, the map data collection method of this application further includes: Step B10, when the data collection task to be executed indicates a first road, determining a trajectory corresponding to the first road as a reference trajectory of the data collection task; When the area to be collected indicated by the data collection task to be executed is a road (hereinafter referred to as the first road for distinction), the trajectory corresponding to the first road is determined as the reference trajectory indicated by the data collection task. It should be understood that the starting point of the trajectory corresponding to the road coincides with the starting point of the road, the end point of the trajectory corresponding to the road coincides with the end point of the road, and the trajectory corresponding to the road is distributed within the range of the road.

[0054] Step B20, when the data collection task to be executed indicates a first lane, determining a trajectory corresponding to the first lane as a reference trajectory of the data collection task; When the area to be collected indicated by the data collection task to be executed is a lane (hereinafter referred to as the first lane for distinction), the trajectory corresponding to the first lane is determined as the reference trajectory indicated by the data collection task. It should be understood that the starting point of the trajectory corresponding to the lane coincides with the starting point of the lane, the end point of the trajectory corresponding to the lane coincides with the end point of the lane, and the trajectory corresponding to the lane is distributed within the range of the lane.

[0055] Step B30: when the data collection task to be executed indicates a task type and collection trajectory information, determine a reference trajectory corresponding to the data collection task according to the task type and the collection trajectory information.

[0056] It should be noted that the task types indicated by the data collection task include road-level collection tasks and lane-level collection tasks. The collection trajectory information indicated by the data collection task includes roads and lanes.

[0057] In the case where the data collection task to be executed indicates a task type and collection trajectory information, a reference trajectory indicated by the data collection task is determined according to the task type and the collection trajectory information.

[0058] In a specific implementation, the task type is a road-level collection task or a lane-level collection task, and the collection trajectory information is a second road or a second lane. Step B30 may include: Step B301, when the task type is a road-level data collection task and the collected trajectory information is a second road, determining the trajectory corresponding to the second road as a reference trajectory of the data collection task; It should be noted that, when the data collection task indicates the task type and the collected trajectory information, the road in the collected trajectory information is called the second road for distinction, and the lane in the collected trajectory information is called the second lane for distinction.

[0059] When the task type indicated by the data collection task is a road-level collection task and the collection trajectory information is the second road, the trajectory corresponding to the second road is determined as the reference trajectory indicated by the data collection task.

[0060] Step B302, when the task type is a road-level collection task and the collection trajectory information is a second lane, determining a trajectory corresponding to a third road where the second lane is located as a reference trajectory of the data collection task, wherein a starting point of the second lane is the same as a starting point of the third road, and an end point of the second lane is the same as an end point of the third road; When the task type indicated by the data collection task is a road-level collection task and the collection trajectory information is the second lane, the accumulation corresponding to the road where the second lane is located (hereinafter referred to as the third road for distinction) is determined as the reference trajectory of the data collection task, wherein the starting point of the second lane is the same as the starting point of the third road, and the end point of the second lane is the same as the end point of the third road.

[0061] Step B303, when the task type is a lane-level collection task and the collection trajectory information is for the second lane, determining the trajectory corresponding to the second lane as a reference trajectory corresponding to the data collection task; When the task type indicated by the data collection task is a lane-level collection task and the collection trajectory information is for the second lane, the trajectory corresponding to the second lane is determined as the reference trajectory indicated by the data collection task.

[0062] Step B304, when the task type is a road-level data collection task and the collection trajectory information is a second road, determine the trajectory corresponding to the target lane in the second road as a reference trajectory corresponding to the data collection task.

[0063] When the task type indicated by the data collection task is a road-level collection task and the collection trajectory information is the second road, the trajectory corresponding to the lane included in the second road (hereinafter referred to as the target lane for distinction) is determined as the reference trajectory corresponding to the data collection task.

[0064] In this embodiment, the step S30 may include: Step S301, determining target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle according to the start position identifier and the end position identifier, wherein the map data set is uploaded by the data collection vehicle; The cloud receives the map data set uploaded by the data collection vehicle, and then determines the target map data corresponding to the pre-collected road from the map data according to the starting position identifier and the ending position identifier.

[0065] Step S302, indicating the start position identifier and the end position identifier to the data collection vehicle, and receiving the target map data corresponding to the pre-collected road returned by the data collection vehicle according to the start position identifier and the end position identifier.

[0066] The map data set is stored on the data collection vehicle. The cloud indicates the starting location identifier and the ending location identifier to the data collection vehicle, and receives the target map data corresponding to the pre-collected road returned by the data collection vehicle based on the starting location identifier and the ending location identifier.

[0067] The embodiments of the present application do not limit the specific method of determining the target map data from the map data set based on the vehicle position identifier. For example, in one feasible implementation, when the data collection vehicle stops driving, it uploads the map data set collected during the current driving process to the cloud. The cloud receives the map data set uploaded by the data collection vehicle, and determines the video frame corresponding to the vehicle position identifier in the map data set based on the starting position identifier and the ending position identifier, and then uses the video frame corresponding to the starting position identifier as the starting frame and the video frame corresponding to the ending position identifier as the ending frame to determine the target map data of the pre-collected road. For example, in another feasible implementation, the cloud generates a data request instruction based on the starting position identifier and the ending position identifier, and sends the data request instruction to the data collection vehicle. After receiving the data request instruction, the data collection vehicle parses the data request instruction to obtain the starting position identifier and the ending position identifier, and determines the target map data corresponding to the pre-collected road based on the starting position identifier and the ending position identifier, and returns the target map data to the cloud.

[0068] For example, Figure 6The figure shows a schematic diagram of the map data collection process, in which the cloud receives the real-time location information uploaded by the data collection vehicle; based on the real-time location information, it is determined whether the data collection vehicle is located at the starting point of the pre-collected road; if it is detected that the data collection vehicle is at the starting point, the driving trajectory of the data collection vehicle is recorded; it is monitored whether the data collection vehicle travels along the pre-collected road from the starting point of the pre-collected road to the end point of the pre-collected road; if so, a target driving trajectory of the data collection vehicle on the pre-collected road is generated; then the target driving trajectory is matched with the reference trajectory indicated by the data collection task to be executed to obtain a matching result; when the matching result is a successful match, a data request instruction containing a starting position identifier and an ending position identifier is sent to the data collection vehicle to obtain the target map data collected by the data collection vehicle on the pre-collected road.

[0069] In this embodiment, after step S30, the map data collection method of the present application further includes: determining the amount to be collected of the reference trajectory indicated by the data collection task to be executed, subtracting one from the amount to be collected to obtain a new amount to be collected; and when it is detected that the new amount to be collected is zero, determining that the data collection task is completed.

[0070] It should be noted that each data collection task to be executed corresponds to a to-be-collected area, which is used to indicate the to-be-collected area and the amount to be collected. For example, the data collection task specifies a certain road as the to-be-collected area, and specifies that the road needs to be collected 3 times (i.e., the amount to be collected). The data collection task specifies the amount to be collected in the to-be-collected area. Each time it is detected that the data collection vehicle performs a map data collection of the reference trajectory, the amount to be collected is reduced by one to update the amount to be collected, until the amount to be collected is zero, and the data collection task is considered to be completed.

[0071] After acquiring the target map data collected by the target data collection vehicle, determine the amount to be collected of the reference track indicated by the data collection task, subtract one from the amount to be collected of the data collection task to obtain a new amount to be collected; and detect whether the new amount to be collected is zero. When it is detected that the new amount to be collected is zero, determine that the data collection task is completed.

[0072] Exemplarily, the data collection task that successfully matches the target driving trajectory is a road-level collection task. The reference trajectory specified by the data collection task is the first road, and three trips are required to collect data on the first road. That is, when the data collection vehicle is a crowdsourcing vehicle, as long as three vehicles pass through the first road completely, the map data collected by each of the three vehicles on the first road can be obtained from the three vehicles to complete the data collection task. In this way, due to the large number of crowdsourcing vehicles, the method of using crowdsourcing vehicles as data collection vehicles for map data collection can shorten the data collection cycle and improve data collection efficiency. In addition, after obtaining the map data uploaded by each data collection vehicle for the road to be collected, each map data is fused and analyzed to update the current electronic map based on the results of the fusion analysis.

[0073] The embodiment of the present application determines the location information of the data collection vehicle when it passes the starting point and the end point of the pre-collected road, and establishes the correspondence between the map data and the collection location based on the starting location identifier corresponding to the starting point and the ending location identifier corresponding to the end point, so as to determine the map data corresponding to the two location information from the map data set collected by the data collection vehicle based on the starting location identifier and the ending location identifier, thereby determining the target map data corresponding to the pre-collected road. In this way, the problem of incomplete map data collection is avoided, and the accuracy of the map constructed or updated based on the target map data is improved.

[0074] It should be noted that the execution subject of the map data collection method of the present application is a data collection vehicle. Based on the first and second embodiments of the present application, in the third embodiment of the present application, the same or similar contents as those of the first and second embodiments can be referred to the above introduction and will not be repeated in the following. On this basis, the map data collection method further includes: Step C10, collecting map data while the data collection vehicle is traveling along the data collection track, and determining a set of the collected map data as a map data set collected by the data collection vehicle; Among them, the data collection trajectory includes a pre-collected road, and the map data set includes at least the starting position mark when the data collection vehicle passes the starting point of the pre-collected road, and the ending position mark when the data collection vehicle passes the end point of the pre-collected road.

[0075] It should be noted that the executor of the embodiment of the present application is a data collection vehicle. The data collection vehicle collects map data while traveling along the data collection track, and determines the set of collected map data as the map data set collected by the data collection vehicle. Among them, the data collection track contains the pre-collected road, that is, the data collection vehicle can collect complete map data on the pre-collected road. And the map data set at least includes the starting position identifier when the data collection vehicle passes the starting point of the pre-collected road, and the ending position identifier when the data collection vehicle passes the end point of the pre-collected road. In addition, it should be understood that the data collection vehicle records the corresponding relationship between each collected map data and the collection position of the map data, that is, the map data set includes the position identifier of the data collection vehicle when it passes each position on the data collection track.

[0076] In a specific implementation, the data collection vehicle is connected to the cloud through communication. After the data collection vehicle stops driving, it returns the map data set collected at that time to the cloud, so that the cloud can obtain the target map data corresponding to the pre-collected road from the map data set based on the starting position identifier and the ending position identifier; or, the data collection vehicle receives a data request instruction issued by the cloud, parses the data request instruction, obtains the starting position identifier and the ending position identifier, and then determines the corresponding video frame from the map data set based on the starting position identifier and the ending position identifier, takes the video frame corresponding to the starting position identifier as the starting frame, takes the video frame corresponding to the ending position identifier as the ending frame, determines the target map data corresponding to the pre-collected road, and returns the target map data to the cloud in the form of a video stream. This saves broadband resources.

[0077] The data collection vehicle may collect map data in the form of H264, H265, H266, AVS1, AVS2, AVS3 or other video technologies. It should be understood that, compared to the traditional method of collecting image data and saving it to the vehicle, in the embodiment of the present application, the data collection vehicle compresses the map data of the video data type and saves it to the vehicle, which can save two-thirds of the storage space and improve the efficiency of data storage to a certain extent, extend the life cycle of the data collection vehicle, and achieve the purpose of reducing operating costs.

[0078] Thus, the embodiment of the present application is applied to a data collection vehicle. The embodiment of the present application collects map data while the data collection vehicle is traveling along a data collection track, and determines a set of collected map data as a map data set collected by the data collection vehicle, wherein the data collection track includes a pre-collected road, and the map data set includes at least a starting position identifier when the data collection vehicle passes the starting point of the pre-collected road, and an ending position identifier when the data collection vehicle passes the end point of the pre-collected road. Thus, compared with the traditional method of matching data collection tasks through the cloud when a vehicle enters a specific road section, and issuing a data collection instruction to instruct the vehicle to start collecting data after the match is successful, the data collection vehicle in the embodiment of the present application can collect complete map data on the pre-collected road, and record the position identifiers when the data collection vehicle passes the starting point and end point of the pre-collected road, so as to determine the map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle based on the two position identifiers, thereby avoiding the problem of partial loss of map data on the pre-collected road due to untimely issuance of instructions from the cloud, improving the integrity of the map data collected by the vehicle, and thus providing more reliable data support for map construction or map update, and improving the accuracy of the map constructed or updated based on the map data.

[0079] The present application provides a map data collection device, which is a cloud or a data collection vehicle. The map data collection device includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the map data collection method in the above-mentioned embodiment 1.

[0080] Reference below Figure 7 , which shows a structural schematic diagram of a map data acquisition device suitable for implementing an embodiment of the present application. Figure 7 The map data collection device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0081] like Figure 7As shown, the map data acquisition device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the map data acquisition device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the map data acquisition device to communicate with other devices wirelessly or by wire to exchange data. Although the map data acquisition device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0082] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0083] The map data collection device provided by the present application adopts the map data collection method in the above embodiment, which can solve the technical problem of how to improve the integrity of the map data collected by the vehicle to improve the accuracy of the map built or updated based on the map data. Compared with the prior art, the beneficial effects of the map data collection device provided by the present application are the same as the beneficial effects of the map data collection method provided by the above embodiment, and the other technical features in the map data collection device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0084] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0085] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0086] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the map data collection method in the above-mentioned embodiment.

[0087] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0088] The computer-readable storage medium may be included in the map data acquisition device; or may exist independently without being assembled into the map data acquisition device.

[0089] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the map data acquisition device, the map data acquisition device: determines the starting position identifier when the data acquisition vehicle passes the starting point of the pre-collected road, and determines the ending position identifier when the data acquisition vehicle passes the end point of the pre-collected road; determines the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least based on the starting position identifier and the ending position identifier; wherein the map data set is a set of map data collected by the data collection vehicle during the driving of the data collection vehicle along the data collection track, and the data collection track contains the pre-collected road.

[0090] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0091] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0092] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0093] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned map data collection method, and can solve the technical problem of how to improve the integrity of the map data collected by the vehicle to improve the accuracy of the map constructed or updated based on the map data. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the map data collection method provided in the above-mentioned embodiment, and will not be repeated here.

[0094] An embodiment of the present application provides a computer program product, including a computer program, which implements the steps of the above-mentioned map data collection method when executed by a processor.

[0095] The computer program product provided in this application can improve the integrity of the map data collected by the vehicle, so as to improve the accuracy of the map constructed or updated based on the map data. Compared with the prior art, the beneficial effects of the computer program product provided in the embodiment of this application are the same as the beneficial effects of the map data collection method provided in the above embodiment, which will not be described in detail here.

[0096] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A map data collection method, characterized in that: The map data collection method comprises: Determine a starting position mark when the data collection vehicle passes the starting point of the pre-collection road, and determine a termination position mark when the data collection vehicle passes the end point of the pre-collection road; Determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least according to the starting position identifier and the ending position identifier; The map data set is a set of map data collected by the data collection vehicle while traveling along a data collection track, and the data collection track includes the pre-collected road.

2. The method according to claim 1, characterized in that The map data set is a video collected by the data collection vehicle during driving, the map data in the map data set is a video frame in the video, the starting position identifier is a timestamp of the video frame corresponding to the starting point, and the ending position identifier is a timestamp of the video frame corresponding to the end point.

3. The method according to claim 1, characterized in that The step of determining the starting position mark when the data collection vehicle passes the starting point of the pre-collection road, and determining the ending position mark when the data collection vehicle passes the end point of the pre-collection road, comprises: During the process of the data collection vehicle traveling along the data collection track, monitoring the real-time position information of the data collection vehicle; In response to monitoring that the data collection vehicle enters the pre-collection road from the starting point of the pre-collection road, triggering a starting position marker; and In response to monitoring that the data collection vehicle travels along the pre-collection road to an end point of the pre-collection road, triggering a termination position mark; or In response to monitoring that the data collection vehicle drives out of the pre-collection road from a non-end point of the pre-collection road, the step of monitoring the real-time position information of the data collection vehicle is returned to be executed.

4. The method according to claim 1, characterized in that Before the step of determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least according to the starting position identifier and the ending position identifier, the method further comprises: Determining a target driving trajectory of the data collection vehicle on the pre-collection road; Determining whether a map data acquisition condition is met based on a match between the target driving trajectory and a reference trajectory indicated by the data collection task to be executed; When the map data acquisition condition is met, the target map data corresponding to the pre-collected road is determined from the map data set collected by the data collection vehicle at least according to the start position identifier and the end position identifier.

5. The method according to claim 4, characterized in that Before the step of judging whether the map data acquisition condition is met according to the matching condition between the target driving trajectory and the reference trajectory indicated by the data collection task to be executed, the method further comprises: In a case where the data collection task to be executed indicates a first road, determining a trajectory corresponding to the first road as a reference trajectory of the data collection task; In a case where the data collection task to be executed indicates a first lane, determining a trajectory corresponding to the first lane as a reference trajectory of the data collection task; In the case where the data collection task to be executed indicates a task type and collection trajectory information, a reference trajectory corresponding to the data collection task is determined according to the task type and the collection trajectory information.

6. The method according to claim 5, characterized in that The task type is a road-level collection task or a lane-level collection task, and the collection trajectory information is a second road or a second lane; The step of determining the reference trajectory corresponding to the data collection task according to the task type and the collection trajectory information comprises: When the task type is a road-level data collection task and the collected trajectory information is a second road, determining a trajectory corresponding to the second road as a reference trajectory of the data collection task; When the task type is a road-level collection task and the collection trajectory information is a second lane, a trajectory corresponding to a third road where the second lane is located is determined as a reference trajectory of the data collection task, wherein a starting point of the second lane is the same as a starting point of the third road, and an end point of the second lane is the same as an end point of the third road; When the task type is a lane-level collection task and the collection trajectory information is for the second lane, determining the trajectory corresponding to the second lane as a reference trajectory corresponding to the data collection task; When the task type is a road-level data collection task and the collection trajectory information is a second road, a trajectory corresponding to a target lane in the second road is determined as a reference trajectory corresponding to the data collection task.

7. The method according to claim 1, characterized in that The step of determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle at least according to the starting position identifier and the ending position identifier comprises: Determining the target map data corresponding to the pre-collected road from the map data set collected by the data collection vehicle according to the starting position identifier and the ending position identifier, wherein the map data set is uploaded by the data collection vehicle; or The starting position identifier and the ending position identifier are indicated to the data collection vehicle, and the target map data corresponding to the pre-collected road returned by the data collection vehicle according to the starting position identifier and the ending position identifier is received.

8. A map data collection method, characterized in that: The map data collection method is applied to a data collection vehicle, and the map data collection method comprises: Collecting map data while the data collection vehicle is traveling along the data collection track, and determining a set of the collected map data as a map data set collected by the data collection vehicle; Among them, the data collection trajectory includes a pre-collected road, and the map data set includes at least the starting position mark when the data collection vehicle passes the starting point of the pre-collected road, and the ending position mark when the data collection vehicle passes the end point of the pre-collected road.

9. A map data collection device, characterized in that: The map data collection device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the map data collection method according to any one of claims 1 to 7 or 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the map data collection method according to any one of claims 1 to 7 or 8 are implemented.

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