CN114880334A

CN114880334A - Map data updating method and electronic equipment

Info

Publication number: CN114880334A
Application number: CN202210262206.6A
Authority: CN
Inventors: 曹亮; 罗星; 宋志丹; 陈岳; 袁剑峰
Original assignee: Autonavi Software Co Ltd
Current assignee: Autonavi Software Co Ltd
Priority date: 2022-03-16
Filing date: 2022-03-16
Publication date: 2022-08-09

Abstract

The embodiment of the disclosure discloses a map data updating method and electronic equipment, wherein the method comprises the following steps: acquiring geographic data of a target area, wherein the geographic data comprises geographic point cloud data; extracting a map element vector to be updated in the target area based on the geographic data; after the target area is matched and aligned with a corresponding area in a pre-stored high-precision map, performing element difference on the element vector of the map to be updated and the existing element vector of the map in the corresponding area to determine whether the map element in the target area changes; and if the map elements in the target area are changed, carrying out map data updating processing. The technical scheme can improve the updating precision and updating timeliness of the high-precision map.

Description

Map data updating method and electronic equipment

Technical Field

The embodiment of the disclosure relates to the technical field of map making, in particular to a map data updating method and electronic equipment.

Background

With the development of science and technology, advanced assistant driving and automatic driving become a hot spot of technical research because of the ability to help drivers to drive safely. Currently, one technique for advanced driver assistance and autonomous driving requires reliance on "high-precision maps" in the path. Compared with a common map, the high-precision map can be more refined and more accurately express the real world, the large-range, high-freshness and high-quality updating of the high-precision map is the most critical problem in the field of the high-precision map, and the functional safety of the map in driving is determined. The technical acquisition vehicle of the high-precision map is too high in cost and cannot be spread in quantity, and the requirement for large-scale geographic data acquisition and updating cannot be met, so that the existing high-precision map updating method mainly comprises the steps of acquiring road images and corresponding position information by using a vision sensor and a positioning sensor which are mounted on a crowdsourcing vehicle in a front-loading or rear-loading mode, identifying and extracting high-precision map elements on the acquired road images by using an image processing technology, calculating three-dimensional coordinates of the elements, and then differentiating the high-precision map elements with the existing high-precision map data and updating the geographic data. However, such methods have the following disadvantages: 1) the monocular image acquired based on one camera has low ranging precision, the precision of the extracted map elements is poor, fine difference cannot be realized, the precision requirement of high-precision map updating is difficult to meet, small changes cannot be found, and the updating quality of the map is damaged; 2) the visual sensor is sensitive to illumination, and insufficient illumination (such as at night) causes system failure, so that freshness requirements (such as daily updating) of high-precision maps are difficult to meet.

Disclosure of Invention

The embodiment of the disclosure provides a map data updating method and electronic equipment.

In a first aspect, a map data updating method is provided in the embodiments of the present disclosure.

Specifically, the map data updating method includes:

acquiring geographic data of a target area, wherein the geographic data comprises geographic point cloud data;

extracting a map element vector to be updated in the target area based on the geographic data;

after the target area is matched and aligned with a corresponding area in a pre-stored high-precision map, performing element difference on the element vector of the map to be updated and the existing element vector of the map in the corresponding area to determine whether the map element in the target area changes;

and if the map elements in the target area are changed, performing map data updating processing.

In one possible implementation, the method is applied to an updating device, and if a map element in the target area changes, the performing the map data updating process includes:

if the map elements in the target area change, determining the change confidence of the changed elements;

if the change confidence coefficient is larger than a preset threshold value, sending a map element vector to be updated corresponding to the change element to a server;

and if the change confidence is less than or equal to a preset threshold, sending the map element vector to be updated and the geographic data corresponding to the changed element to the server.

In one possible embodiment, the method is applied to a server, and the performing the map data update process if the map element in the target area changes includes:

if the change confidence coefficient is larger than a preset threshold value, updating the map based on the to-be-updated map element vector corresponding to the change element;

if the change confidence coefficient is less than or equal to a preset threshold value, outputting a map element vector to be updated and original data corresponding to the changed element; and in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

In a possible embodiment, the acquiring geographic data of the target area includes:

acquiring original point cloud data of a target area;

and filtering the far road points and the dynamic object points in the original point cloud data to obtain the geographical point cloud data of the target area.

In a possible embodiment, the raw data further includes a real-time track height, and the filtering is performed on far-road points and dynamic object points in the raw point cloud data to obtain geographic point cloud data, including:

determining a ground elevation based on the actual track height and a prestored ground clearance of the equipment;

determining points, in the original point cloud data, of which the distance between the height and the ground elevation is within a preset range as ground points, and determining the rest points as non-ground points;

determining a road boundary of the target area based on pre-stored high-precision map data;

the road boundary is expanded outwards by a first preset distance to serve as a transverse effective boundary, and the ground elevation is expanded upwards by a second preset distance to serve as a longitudinal effective boundary;

filtering out useless points higher than the longitudinal effective boundary and useless points outside the transverse effective boundary;

and filtering dynamic object points with the height exceeding the third preset distance of the ground elevation in the non-ground points.

In a possible embodiment, the geographic data further includes image data, and the extracting a map element vector to be updated in the target area based on the geographic data includes:

extracting map elements based on the geographic point cloud data to obtain a first map element vector in the target area;

extracting map elements based on the geographic point cloud data and the image data to obtain a second map element vector in the target area;

and fusing the first map element vector and the second map element vector to obtain the map element vector to be updated.

In a possible implementation, the performing map element extraction based on the geographic point cloud data to obtain a first map element vector in the target area includes:

generating a point cloud intensity map based on intensity information of ground points in the geographical point cloud data;

generating a point cloud density map based on density information corresponding to non-ground points in the geographic point cloud data, wherein the density information comprises density information when the non-ground points are projected to the ground;

extracting a first map element of the target area from the point cloud intensity map and the point cloud density map;

and performing boundary fitting of the first map element based on the geographic point cloud data corresponding to the first map element to obtain the first map element vector.

In a possible implementation manner, the performing map element extraction based on the geographic point cloud data and the image data to obtain a second map element vector in the target area includes:

carrying out image segmentation and identification on the image data to obtain a second map element;

acquiring geographic point cloud data corresponding to the second map element based on the corresponding relation between the image data and the geographic point cloud data;

and performing boundary fitting of the second map element based on the geographic point cloud data corresponding to the second map element to obtain the second map element vector.

In a possible implementation manner, the fusing the first map element vector and the second map element vector to obtain the map element vector to be updated includes:

calculating a first fitting residual fitting the first map element vector and a second fitting residual fitting the second map element vector;

determining a first confidence level of the first map element vector based on the first fitted residual, and determining a second confidence level of the second map element vector based on the second fitted residual;

and fusing the first map element vector and the second map element vector based on the first confidence coefficient and the second confidence coefficient to obtain the map element vector to be updated.

In a possible embodiment, the determining the confidence of the change element includes:

and determining the change confidence coefficient of the changed element based on the confidence coefficient of the map element vector to be updated corresponding to the changed element, the type of the changed element and the change type, wherein the change type comprises addition and deletion.

In a second aspect, a map data updating method is provided in the embodiments of the present disclosure.

Specifically, the map data updating method includes:

receiving map information of the changed elements sent by the updating equipment;

if the map information comprises the map element vector to be updated, updating the map based on the map element vector to be updated corresponding to the changed element;

if the map information comprises a map element vector to be updated, geographical point cloud data and image data, displaying the map element vector to be updated, the geographical point cloud data and the image data; and in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

In a third aspect, a map data updating method is provided in the embodiments of the present disclosure.

Specifically, the map data updating method includes:

the method comprises the steps that an updating device obtains geographic data of a target area, and extracts a map element vector to be updated in the target area based on the geographic data; after the target area is matched and aligned with a corresponding area in a pre-stored high-precision map, performing element difference on the element vector of the map to be updated and the existing element vector of the map in the corresponding area to determine whether the map element in the target area changes; if the map elements in the target area change, sending the map element vector to be updated of the changed elements to a server;

and the server updates the map data based on the map element vector to be updated of the change element.

In a third aspect, an embodiment of the present disclosure provides a map data updating apparatus.

Specifically, the map data updating apparatus includes:

a first acquisition module configured to acquire geographic data of a target area, the geographic data including geographic point cloud data;

an extraction module configured to extract a map element vector to be updated within the target region based on the geographic data;

the difference module is configured to match and align the target area with a corresponding area in a pre-stored high-precision map, and then perform element difference on the map element vector to be updated and the existing map element vector in the corresponding area to determine whether the map element in the target area changes;

and the first updating module is configured to update the map data if the map elements in the target area are changed.

In a possible implementation, the apparatus is applied to an update device, and the first update module is configured to:

and if the change confidence coefficient is less than or equal to a preset threshold value, sending the map element vector to be updated and the geographic data corresponding to the changed element to the server.

In a possible embodiment, the apparatus is applied to a server, and the first updating module is configured to:

if the change confidence is smaller than or equal to a preset threshold value, outputting a map element vector to be updated and geographic data corresponding to the changed element; and in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

In one possible implementation, the obtaining module is configured to:

acquiring original point cloud data of a target area;

and filtering the far road points and the dynamic object points in the original point cloud data to obtain the geographical point cloud data.

In a possible embodiment, the raw data further includes a real-time track height, and the filtering in the obtaining module is configured to filter the far road point and the dynamic object point in the raw point cloud data, and obtain a portion of the geographical point cloud data:

In a possible embodiment, the geographic data further comprises image data, the extraction module being configured to:

In a possible implementation, the extraction module performs map element extraction based on the geographic point cloud data, and the portion of the map element vector that is obtained in the target area is configured to:

In a possible implementation, the extracting module performs map element extraction based on the geographic point cloud data and the image data, and the portion of the second map element vector in the target area is configured to:

In a possible implementation manner, the merging, by the extraction module, the first map element vector and the second map element vector to obtain the map element vector to be updated is configured to:

In one possible embodiment, the part of the first updating module that determines the confidence of the change of the changed element is configured to:

In a fourth aspect, a map data updating apparatus is provided in the embodiments of the present disclosure.

Specifically, the map data updating apparatus includes:

a second obtaining module configured to obtain the map information of the changed elements sent by the updating device;

the second updating module is configured to update the map based on the to-be-updated map element vector corresponding to the change element if the map information comprises the to-be-updated map element vector; if the map information comprises a map element vector to be updated, geographical point cloud data and image data, displaying the map element vector to be updated, the geographical point cloud data and the image data; and in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

In a fifth aspect, the disclosed embodiments provide an electronic device, including a memory for storing one or more computer instructions that support the above apparatus to perform the above method, and a processor configured to execute the computer instructions stored in the memory.

In a sixth aspect, the disclosed embodiments provide a computer-readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the method steps of any of the above aspects.

In a seventh aspect, the disclosed embodiments provide a computer program product comprising a computer program/instructions, wherein the computer program/instructions, when executed by a processor, implement the method steps of any one of the above aspects.

In an eighth aspect, an embodiment of the present disclosure provides a navigation method, where a navigation route calculated based on at least a starting point, an end point, and a road condition is obtained based on an electronic map, and a carrier is guided by navigation based on the navigation route, where the electronic map is implemented based on any one of the above methods.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

according to the technical scheme, the laser radar can be used as a data acquisition main sensor for updating the high-precision map, high-precision point cloud data can be acquired, and compared with a measuring mode based on monocular vision, map element vector extraction is carried out based on the point cloud data, so that the precision of the map element vector can be improved to a great extent, and thus, when the map is updated, the precision of the high-precision map is not reduced; meanwhile, fine element vector extraction is also beneficial to realizing fine element difference, so that the detail change of the map can be found, and the quality of map updating is improved; moreover, the measurement of the laser radar is independent of the illumination environment, the usability of the updating system is improved due to the characteristic, and the updating timeliness of the night change is obviously improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of embodiments of the disclosure.

Drawings

Other features, objects, and advantages of embodiments of the disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:

fig. 1 is a schematic diagram of a map data update scenario.

Fig. 2 shows a schematic diagram of a map data update system according to an embodiment of the present disclosure.

Fig. 3 shows a schematic structural diagram of an update apparatus according to an embodiment of the present disclosure.

Fig. 4 illustrates a flowchart of a map data update method according to an embodiment of the present disclosure.

Fig. 5 illustrates a flowchart of a map data update method according to an embodiment of the present disclosure.

Fig. 6 illustrates a flowchart of a map data update method according to an embodiment of the present disclosure.

Fig. 7 shows a block diagram of a map data update apparatus according to an embodiment of the present disclosure.

Fig. 8 shows a block diagram of a map data update apparatus according to an embodiment of the present disclosure.

Fig. 9 shows a block diagram of an electronic device according to an embodiment of the present disclosure.

FIG. 10 is a block diagram of a computer system suitable for use in implementing the methods according to embodiments of the present disclosure.

Detailed Description

Hereinafter, exemplary embodiments of the disclosed embodiments will be described in detail with reference to the accompanying drawings so that they can be easily implemented by those skilled in the art. Furthermore, parts that are not relevant to the description of the exemplary embodiments have been omitted from the drawings for the sake of clarity.

In the disclosed embodiments, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.

It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Fig. 1 is a schematic diagram of a map data update scenario. As shown in fig. 1, vehicle 101, vehicle 102, and vehicle 103 are crowd-sourced vehicles having respective collection devices mounted thereon to collect respective geographic data. For example, the three vehicles travel on the road along the respective planned routes, and collect corresponding road environment data, such as lane line information and road sign information, while traveling. It should be understood that the three vehicles described above are merely exemplary, that more or fewer vehicles are possible, and that the travel routes described above are also exemplary. As shown in fig. 1, when a change occurs in the real-world environment (e.g., a newly added lane line, a changed lane line, a newly added road sign, a changed road sign, or the like), the collection of corresponding road environment data by crowd-sourced vehicles facilitates the quick update of geographic data.

In the prior art, a crowd-sourced vehicle collects road images and corresponding position information by using a vision sensor (such as a vehicle data recorder) and a positioning sensor which are arranged in front of or behind the crowd-sourced vehicle, then identifies and extracts high-precision map elements on the collected road images by using an image processing technology, calculates three-dimensional coordinates of the elements, and then differentiates the high-precision map elements from existing high-precision map data and updates geographic data. However, such methods have the following disadvantages: 1) the distance measurement precision of a monocular image acquired based on one camera is not high, the precision of an extracted map element is poor, fine difference cannot be realized, the precision requirement of high-precision map updating is difficult to meet, tiny changes cannot be discovered, and the updating quality of a map is damaged; 2) the visual sensor is sensitive to light, and the system fails due to insufficient light (such as at night), so that the freshness requirement (such as daily update) of the high-precision map is difficult to meet. In order to solve the problem, the application provides a map data updating scheme so as to form a map data updating with high freshness and high quality.

Fig. 2 is a schematic diagram of a map data updating system according to an embodiment of the present disclosure, as shown in fig. 2, the system includes an updating device 201 and a cloud server 202, and data transmission is performed between the updating device 201 and the cloud server 202 through a network. In recent years, the laser radar technology is rapidly developed, the mass production technology of the vehicle-level laser radar is broken through, and the laser radar has the advantages of low cost, high reliability, small size and portability; meanwhile, the high-speed development of an AI (artificial intelligence) algorithm and an AI computing chip enables the real-time processing of multi-source collected data on the end to be possible. Therefore, the updating device 201 provided by the application can be configured with a plurality of sensors which are mainly based on the laser radar, the updating device 201 can be configured on a crowdsourcing vehicle, the laser radar in the updating device 201 can collect point cloud data in the running process of the crowdsourcing vehicle, an AI computing chip can be configured on the updating device 201, the multisource sensing and computing capability of the AI computing chip is utilized to perform data processing or directly send the collected point cloud data to a cloud server for data processing, the specific processing process can be to process the collected point cloud data to obtain a map element vector to be updated, the map element vector to be updated is matched and aligned with a pre-stored existing map element vector and element difference is obtained, whether the map element is changed or not is judged, and when the map element is changed, the map data is updated. According to the scheme, the laser radar is used as a data acquisition main sensor for updating the high-precision map, high-precision point cloud data can be obtained, and compared with a measuring mode based on monocular vision, map element vector extraction is carried out based on the point cloud data, so that the precision of the map element vector can be greatly improved, and thus, when the map is updated according to the method, the precision of the high-precision map is not reduced; meanwhile, fine element vector extraction is also beneficial to realizing fine element difference, so that the detail change of the map can be found, and the quality of map updating is improved; moreover, the measurement of the laser radar is independent of the illumination environment, the usability of the updating system is improved due to the characteristic, and the updating timeliness of the night change is obviously improved.

Fig. 3 shows a schematic structural diagram of an update apparatus according to an embodiment of the present disclosure, and as shown in fig. 3, the update apparatus may include the following three modules: an acquisition module 301, a software module 302, and an accessory module 303. The acquisition module 301 includes a plurality of sensors for acquiring road data, such as a sensor that may include a laser radar, a camera, a GNSS (Global Navigation Satellite System) (RTK (Real Time Kinematic), IMU (Inertial Measurement Unit)), and the like, wherein the laser radar and the camera belong to a Measurement sensor for acquiring laser point cloud data and image data of a road element; the GNSS/IMU is a positioning and attitude-fixing sensor and is used for acquiring the spatial position and attitude angle of the acquired data; the GNSS system generally refers to all satellite navigation systems, and can provide positioning location information; the GNSS system is accessed to an RTK technology, the RTK technology can obviously improve the GNSS measurement accuracy, and the measuring method can obtain centimeter-level positioning accuracy in real time in the field; the IMU is a sensor that can measure angular attitude. The software module 302 mainly performs sensor control and data analysis, data quality inspection and status monitoring, logging, and exception handling. That is, through the software module 302, the sensors can be controlled and data can be collected, then quality inspection (for example, data integrity) is performed on the collected data, and meanwhile, the operation state of each sensor is monitored all the time, when the data quality is abnormal or the sensor state is abnormal, the log system can record and transmit the data back to the data center, and meanwhile, the abnormal grade can be followed up, and a driver can be reminded in a proper form. The accessory module 303 comprises a control system, a computing unit, a communication unit, a storage unit, a power supply unit, a cable, a mechanical structure, etc., which together form a complete update device. The control system comprises a time synchronization subsystem, so that time synchronization among the sensors in the acquisition module 301 can be guaranteed, and after equipment integration is completed, internal calibration parameters and external calibration parameters of the sensors can be acquired and the ground clearance of the equipment can be updated through sensor calibration, so that the space-time consistency of multiple sensors is realized. The computing Unit comprises a Central Processing Unit (CPU) and a Graphics Processing Unit (GPU) computing capability, an ARM (Advanced RISC Machines, RISC (Reduced Instruction Set Computer) microprocessor) architecture operating system is built in, and data acquired by the GNSS/IMU can be combined, navigated and resolved in real time to obtain a high-precision track file; the communication unit comprises 4G/5G and WIFI communication functions. The updating equipment can also have the capacities of rain prevention, dust prevention, shock resistance and the like so as to meet the requirements of safety and stability of equipment in the operation of a complex environment.

Fig. 4 shows a flowchart of a map data updating method according to an embodiment of the present disclosure, which includes the following steps S401 to S404, as shown in fig. 4:

in step S401, geographic data of a target area is acquired, where the geographic data includes geographic point cloud data;

in step S402, extracting a map element vector to be updated in the target area based on the geographic data;

in step S403, after matching and aligning the target area with a corresponding area in a pre-stored high-precision map, performing element difference between the map element vector to be updated and an existing map element vector in the corresponding area, and determining whether a map element in the target area changes;

in step S404, if the map element in the target area changes, a map data update process is performed.

In a possible implementation manner, the execution subject of the map data updating method may be an updating device disposed on the acquisition carrier, or may be a server. The collection carrier can be a crowdsourcing vehicle, and can also be equipment which can normally run on a road, such as a professional collection vehicle or a collection robot.

In a possible embodiment, the target area refers to an area acquired by the updating device in real time during the driving process of the acquisition carrier, and the updating device is provided with a laser radar which can acquire the geographic point cloud data of the target area. The point cloud data is information of a plurality of points in a target area, which is generally acquired by a 3D scanning device such as a laser radar, and includes XYZ position information, RGB color information, intensity information, and the like, and is multi-dimensional complex data, and the point cloud data of the target area refers to a mass point set of surface characteristics of each object in the target area.

In one possible embodiment, the map elements refer to basic contents constituting a map, such as buildings, roads, road signs, guideboards, and the like, and the map element vector refers to spatial coordinates and attribute information of the map elements. The artificial intelligence technology is adopted to carry out semantic segmentation on the geographic point cloud data, the outlines, the positions and the corresponding coordinates of all map elements in the geographic point cloud data can be obtained, therefore, all map element vectors in the target area can be obtained, and the map element vectors obtained based on the geographic data collected in real time are called as map element vectors to be updated.

In one possible embodiment, since the map element vector to be updated may have a deviation from the position of the map elements on the pre-stored high-accuracy map, and cannot be directly used for updating, matching and aligning with the area in the pre-stored high-accuracy map is required, for example, assuming that the target area refers to the middle 50m area of the road section a, the target area needs to be matched with the pre-stored high-accuracy map, and the target area matches and aligns with the middle 50m area of the road section a on the high-accuracy map. Then, performing element difference on the map element vector to be updated and the existing map element vector in the matching area, and comparing whether the map elements change, such as whether a newly added lane, a mark line is rewashed, a sign is increased or decreased, and the like, wherein the element difference refers to performing difference operation on the map elements corresponding to the map element vectors to be updated in the target area and the map elements corresponding to the existing map element vectors in the matching area, and if the operation result is 0, the fact that the elements in the current target area are completely the same as the existing elements is indicated, and the map elements in the target area do not change; if the operation result is not 0, it indicates that each element in the current target area is different from the existing element, and the map element in the target area changes, in this case, each element in the current target area may have at least one more or less map element than the existing element. For example, the element vector of the map to be updated in the target area has 2 guideboards, the existing element vector of the map in the corresponding area in the high-precision map has only 1 guideboard, and after the target area is aligned with the corresponding area, 1 guideboard in the corresponding area is completely overlapped with 1 guideboard in the element vector of the map to be updated, after element difference, it is determined that there are 1 more guideboards in the current target area, which indicates that the element vector of the map changes, and one guideboard is newly added.

In a possible embodiment, the execution subject of the local map data updating method is an updating device, and when a map element in the target area changes, the updating device performs a map data updating process, including: the updating device sends the map element vector to be updated of the changed element to the server so that the server can update the map data according to the map element vector. At this time, the updating device can only send the map element vector to be updated of the changed element to the server, thereby reducing the return data volume and saving the return flow charge.

In a possible embodiment, the execution subject of the local map data update is a server, and when the map element in the target area changes, the server may directly update the map data based on the to-be-updated map element vector of the changed element.

It should be noted that the changed element may be a newly added or modified map element, or may be a deleted map element, and when the changed element is a deleted map element, the map element vector to be updated corresponding to the changed element is null.

In the embodiment, the laser radar can be used as a data acquisition main sensor for updating the high-precision map, so that high-precision point cloud data can be obtained, and compared with a measuring mode based on monocular vision, map element vector extraction is performed based on the point cloud data, so that the precision of the map element vector can be improved to a great extent, and thus, when the map is updated, the precision of the high-precision map is not reduced; meanwhile, fine element vector extraction is also beneficial to realizing fine element difference, so that the detail change of the map can be found, and the quality of map updating is improved; and the measurement of the laser radar is independent of the illumination environment, the usability of the updating system is improved by the characteristic, and the updating timeliness of the night change is obviously improved.

In one possible embodiment, when the map data update is applied to an update device, if the map element in the target area is changed in step S104, the performing the map data update process includes:

and if the change confidence coefficient is less than or equal to a preset threshold value, sending the element vector of the map to be updated and the original data corresponding to the changed element to the server.

In this embodiment, the change confidence of the change element refers to the reliability of the change element, and may be configured according to a preset rule, and in general, road signs on a road are easily blocked by vehicles driving on the road, and road signs beside the road are easily blocked by trees, so the change element may be a cut change, the change element type may be that the change confidence of the easily blocked elements is a lower value equal to or less than the preset threshold, and the change confidence of other change elements may be the extraction accuracy of the change elements.

In this embodiment, when the change confidence is greater than the preset threshold, it indicates that the change element has a high probability of actually changing, and at this time, map updating is required, and in order to reduce the data transmission amount, the updating device may send only the to-be-updated map element vector corresponding to the change element to the server, and the server may perform operations such as addition and deletion, and the like on the high-precision base map directly based on the to-be-updated map element vector, and then perform incremental compilation and reissue on the high-precision map.

In this embodiment, when the change confidence is less than or equal to the preset threshold, in order to avoid false update, the map element vector to be updated and the geographic data corresponding to the change element may be sent to the server, the server may display the map element vector to be updated and the original data of the change element for an updater, the updater may manually confirm whether the change element is a true change, if the change element is not a true change, the map update is not performed, and if the change element is a true change and the map element vector to be updated of the change element is accurate, an update instruction may be input to perform the map update, where the update instruction indicates that the map update is performed based on the map element vector to be updated corresponding to the change element; if the change is really happened and the element vector of the map to be updated of the changed element is not accurate, the updating personnel can input the accurate element vector of the changed element by himself and then input the updating instruction, and the updating instruction indicates to update based on the input element vector of the changed element.

In one possible embodiment, when the map data update is applied to the server, if the map element in the target area is changed in step S104, the performing the map data update process includes:

if the change confidence coefficient is less than or equal to a preset threshold value, outputting a map element vector to be updated and original data corresponding to the changed element; and responding to a received input updating instruction, and updating a map based on the updating instruction, wherein the updating instruction indicates that the map is updated based on the to-be-updated map element vector corresponding to the change element or the map is updated based on the change element vector carried in the updating instruction.

In the embodiment, with the popularization of the 5G network, when the network transmission rate and the traffic fee are not problems, the data processing is not required on the updating device, the acquired geographic data can be transmitted back to the server, and the more intensive and complicated data processing is performed by means of stronger calculation power and historical data storage of the server, so that the map updating quality can be further improved.

In this embodiment, after acquiring the geographic data of the target area from the acquisition device, the server executes the above steps, and determines the change confidence of the changed elements when the map elements in the target area change; when the change confidence coefficient is greater than the preset threshold value, the changed element is indicated to have a very high probability of changing, and map updating is needed, at the moment, the server can directly perform operations such as addition, deletion, modification and the like on the high-precision base map based on the element vector of the map to be updated, and then perform incremental compiling and reissue on the high-precision map.

In this embodiment, when the change confidence is less than or equal to the preset threshold, in order to avoid false update, the server may display, for an update person, a to-be-updated map element vector and original data of the changed element, and the update person may manually confirm whether the changed element is a true change, if not, the update person does not perform map update, and if the changed element is a true change and the to-be-updated map element vector of the changed element is accurate, an update instruction may be input to perform map update, where the update instruction indicates that the map update is performed based on the to-be-updated map element vector corresponding to the changed element; if the change is really happened and the element vector of the map to be updated of the changed element is not accurate, the updating personnel can input the accurate element vector of the changed element by himself and then input the updating instruction, and the updating instruction indicates to update based on the input element vector of the changed element.

In a possible implementation manner, the step S101 of the map data updating method, namely the step of obtaining the geographic data of the target area, may include the following steps:

acquiring original point cloud data of a target area;

In this embodiment, when the method is applied to the updating device, in order to reduce the data amount of point cloud processing, reduce the requirement on computational power, meet the requirement on real-time performance, improve the quality of the point cloud data, enable the updating device to better process the acquired point cloud data in real time, filter the acquired original point cloud data, and filter the far-road points and dynamic object points in the original point cloud data.

In this embodiment, if the above method is applied to a server, in order to reduce the data amount of point cloud processing, make the data processing lighter, and meet the real-time requirement, improve the quality of point cloud data, reduce the amount of returned data, and save the returned flow rate fee, the updating device may also filter the road-far point and the dynamic object point in the original point cloud data and then return the filtered points to the server, and at this time, the geographical power data acquired by the server does not include the road-far point and the dynamic object point.

In a possible embodiment, the raw data further includes an actual track height, and the filtering is performed on far road points and dynamic object points in the raw point cloud data to obtain geographic point cloud data, including:

in this embodiment, the updating device is configured with GNSS, RTK, IMU, and other mapping sensors, and after performing combined navigation processing based on the RTK, IMU, and positioning data, a real-time trajectory file may be obtained, where a specific processing process is the prior art and is not described herein any more, the real-time trajectory file includes a real-time trajectory height, the real-time trajectory height refers to a real-time trajectory height of the updating device, the pre-stored device ground clearance height refers to a height of the updating device from the ground, and may be stored in the updating device after being measured in advance, or may be calculated by the updating device. And subtracting the ground clearance of the equipment from the real-time track height of the updated equipment to obtain the real-time ground elevation.

In this embodiment, for the original point cloud data collected in real time, points with a height near the ground elevation belong to ground points, and the rest points are non-ground points, for example, the pre-stored equipment ground clearance speed is 2m, and the real-time track height of the target area collected at a certain time is 40m, then the ground elevation at the current time is 40m-2 m-38 m, and the elevation is floated upwards by 0.05m as the elevation h of the ground point, and the point clouds in the target area are classified by the elevation h, and if the height of the midpoint of the point cloud is greater than the elevation h, the point cloud belongs to a non-ground point, and if the height of the midpoint of the point cloud is less than or equal to the elevation h, the point cloud belongs to a ground point.

In this embodiment, when the above-described method is applied to an update apparatus, the server may periodically synchronously update the latest high-precision map data in the server to the update apparatus via the network.

In this embodiment, the update device or server may use existing high-precision map data as a priori information to quickly filter away road points. High-accuracy map updating focuses mainly on roads and map elements around the roads, points far away from the roads belong to useless points, and existing high-accuracy maps provide road boundary information, and can be used for setting an effective boundary range of point cloud data, wherein in the transverse direction, a first preset distance such as 3m outside the road boundary is used as a transverse effective boundary, and in the longitudinal direction, a second preset distance such as 12m in the ground elevation direction is used as a longitudinal effective boundary. And filtering the original point cloud data in the target area by using the two effective boundaries, filtering useless points higher than the longitudinal effective boundary and useless points outside the transverse effective boundary, wherein the residual point cloud data is the point cloud data of the road and objects around the road, and the amount of the point cloud data can be simply and effectively reduced.

In this embodiment, for dynamic objects (such as vehicles and people driving on the road surface) in the point cloud, extraction of map elements is obviously interfered, in order to improve the quality of the point cloud data, dynamic object points need to be filtered in advance, points which are not on the ground and have a height less than 3m from the ground usually belong to dynamic objects within a road range, and based on this rule, dynamic object points with a height exceeding the ground height by a third preset distance, such as 3m, in the non-ground points can be filtered, so that the dynamic object points can be simply and effectively filtered.

In this embodiment, in order to make the extracted map element vectors more accurate, different map element vectors may be extracted in different ways, and then the extracted map element vectors are fused to obtain the map element vector to be updated, where the different extracted map element vectors have certain repetition and complementation, and the fusion refers to merging the repeated vectors, and the different vectors complement each other.

In this embodiment, the map element extraction may be performed in two different ways, one way is to perform element extraction based on only the geographic point cloud data, resulting in a first map element vector; and the other method is to extract map elements by adopting a dot-image fusion method to obtain a second map element vector. And then, fusing the two map element vectors to obtain the map element vector to be updated.

The method can be used for extracting the element vector by combining the advantages of two perception extraction schemes of the laser point cloud and the visual image, and can improve the adaptability of the system while ensuring the high accuracy of the elements.

In an embodiment of the present disclosure, the step of extracting a map element based on the geographic point cloud data to obtain a first map element vector in the target area may include the following steps:

in this embodiment, the geographic point cloud data includes point cloud data of ground points and point cloud data of non-ground points, and the specific distinguishing manner may refer to the other embodiments described above, which is not described herein again.

In this embodiment, since the difference between the reflection intensities of the road and the road marking on the ground is generally large and the reflection intensity of the road marking is large, when map elements are extracted from the point cloud data of the ground points, the three-dimensional point cloud data can be converted into a two-dimensional point cloud intensity map, which is an image having the intensity values of the respective ground points as pixel values, based on the intensity information of the respective points in the point cloud data. Here, the conversion process of the two-dimensional point cloud intensity map may be to project three-dimensional ground points onto the ground, and count the intensity value of each ground grid point (e.g., the average value of the intensity values of all projected points within the ground grid point) as the image pixel value, so as to obtain the corresponding point cloud intensity map.

In this embodiment, the reflection intensity differences of the non-ground points are not large, the extraction effect by using the point cloud intensity map is not good, but the density of the point cloud projections of different map elements projected on the ground is very different, and different density characteristics can reflect the spatial characteristics of the map elements, such as a rod, the projection of which has only a circle, but the point cloud data corresponding to the rod is cylindrical point cloud data, and after the point cloud data is projected on the ground, the density is very large in a local range, so that the density characteristics can be used for identifying different non-ground elements. Therefore, when the map elements of the point cloud data of the non-ground points are extracted, the non-ground points can be projected on the ground, and the density value of each ground grid point (such as the number of all projected points in the ground grid point) is counted as the image pixel value, so that the corresponding point cloud density map can be obtained.

In this embodiment, the image recognition segmentation technology is already a very mature image processing technology, and here, a trained image segmentation model can be used to recognize and segment a first map element such as a lane line, a ground marking, a road rod, a guideboard and the like in the target area on the point cloud intensity map and the point cloud density map respectively.

In this embodiment, after obtaining the first map element by segmentation, three-dimensional geographic point cloud data corresponding to the first map element may be obtained, for example, assuming that the first map element is a lane line on the ground, after obtaining the lane line by segmentation, the position of the lane line in the point cloud intensity map may be obtained, and based on the geographic point cloud data at each position in the point cloud intensity map, the geographic point cloud data corresponding to the lane line may be obtained.

In this embodiment, the boundary fitting may be performed on the geographic point cloud data corresponding to the first map element to obtain the boundary point of the first map element, and the boundary point represents the map element, that is, the extraction of the first map element vector is completed.

In an embodiment of the present disclosure, the extracting a map element based on the geographic point cloud data and the image data to obtain a second map element vector in the target area includes:

acquiring geographic point cloud data corresponding to the second map element;

In this embodiment, the map element vector may be extracted by a dot-map fusion method, and first, the image data may be subjected to image segmentation recognition by using a trained image segmentation extraction model to obtain the second map element. By combining the internal calibration parameters, the external calibration parameters and the ground clearance of the devices of the sensors, the image data and the geographic point cloud data (point cloud projection) can be synchronized in time and space in a one-to-one correspondence (this is the prior art, and no further description is given here). And thus, the geographic point cloud data corresponding to the second map element in the image data can be obtained, the boundary fitting is carried out on the geographic point cloud data corresponding to the second map element to obtain the boundary point of the second map element, and the boundary point represents the map element, so that the extraction of the second map element vector is completed.

In an embodiment of the present disclosure, the fusing the first map element vector and the second map element vector to obtain the map element vector to be updated includes:

In this embodiment, the fitting residual refers to a difference between an actual observation vector of the map element and a fitted map element vector, and is used to indicate whether the fitting of the map element vector is good or bad.

In this embodiment, when performing boundary matching of the first map element based on the geographical point cloud data corresponding to the first map element, a first fitting residual to which the first map element vector is fitted is also calculated, and when performing boundary matching of the second map element based on the geographical point cloud data corresponding to the second map element, a second fitting residual to which the second map element vector is fitted is also calculated. And according to the rule that the larger the fitting residual error is, the lower the confidence coefficient is, determining a first confidence coefficient of the first map element vector based on the first fitting residual error, and determining a second confidence coefficient of the second map element vector based on the second fitting residual error, wherein the confidence coefficient represents the reliability of the map element vector.

In this embodiment, the first map element vector and the second map element vector may be fused based on the first confidence degree and the second confidence degree to obtain the map element vector to be updated; for example, when the first map element vector and the second map element vector that overlap each other are combined, the map element vector with a low degree of confidence may be deleted, and the map element vector with a high degree of confidence may be retained.

In this embodiment, since the road sign on the road is normally easily blocked by the vehicle running on the road and the road sign on the road side is easily blocked by the tree, the change element may be a cut change, the change element type may be such that the change confidence of the easily blocked elements is a lower value equal to or less than the preset threshold, and the change confidence of the other change elements may be the confidence of the change elements.

Fig. 5 shows a flowchart of a map data updating method according to an embodiment of the present disclosure, which includes the following steps S501-S503, as shown in fig. 5:

in step S501, receiving map information of a changed element sent by an updating device, where the map information includes a to-be-updated map element vector corresponding to the changed element;

in step S502, if the map information includes a to-be-updated map element vector, performing map updating based on the to-be-updated map element vector corresponding to the changed element;

in step S503, if the map information includes a map element vector to be updated, geographical point cloud data, and image data, displaying the map element vector to be updated, the geographical point cloud data, and the image data; and in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

In one possible embodiment, the map data update method is executed by a server.

In a possible embodiment, an updating device is provided on the collecting carrier that can be normally driven on the road, and the updating device can perform the above steps S401 to S404. The updating device extracts the map element vector to be updated in the target area based on the geographic data acquired by the device, performs element difference with the existing map element vector, and sends the map information of the changed element to the server when comparing whether the map element in the target area is changed, and the server can update the map based on the geographic information of the changed element after receiving the map information of the changed element.

In one possible implementation, when the map element in the target area changes, the updating device determines the change confidence of the changed element; the change confidence of the change element refers to the reliability of the change element, and may be configured according to a preset rule, for example, the change confidence of the change element is determined based on the confidence of the map element vector to be updated corresponding to the change element, the type of the change element, and the change type, where the change type includes addition and deletion.

In a possible implementation manner, when the change confidence is greater than a preset threshold, it indicates that the change element has a high probability of being actually changed, at this time, map updating is required, and in order to reduce the data transmission amount, the updating device may send only the to-be-updated map element vector corresponding to the change element to the server, and the server may perform operations such as addition, deletion, and modification on the high-precision base map directly based on the to-be-updated map element vector, and then perform incremental compiling on the high-precision map, and reissue the high-precision map.

In a possible implementation manner, when the change confidence is less than or equal to a preset threshold, in order to avoid false update, a map element vector to be updated and geographic data corresponding to a change element may be sent to a server, the server may display the map element vector to be updated and original data of the change element for an updater, the updater may manually confirm whether the change element is a true change, if the change element is not a true change, the map update is not performed, and if the change element is a true change and the map element vector to be updated of the change element is accurate, an update instruction may be input to perform the map update, and the update instruction indicates that the map update is performed based on the map element vector to be updated corresponding to the change element; if the change is really happened and the element vector of the map to be updated of the changed element is not accurate, the updating personnel can input the accurate element vector of the changed element by himself and then input the updating instruction, and the updating instruction indicates to update based on the input element vector of the changed element.

In the present embodiment, the update device may transmit only the map information of the changed elements to the server, thereby reducing the amount of transmission data.

Fig. 6 shows a flowchart of a map data updating method according to an embodiment of the present disclosure, which includes the following steps S601-S604, as shown in fig. 6:

in step S601, the updating device obtains geographic data of a target area, and extracts a map element vector to be updated in the target area based on the geographic data;

in step S602, after the target area is matched and aligned with a corresponding area in a pre-stored high-precision map, the updating device performs element difference between the map element vector to be updated and an existing map element vector in the corresponding area to determine whether a map element in the target area changes;

if the map elements in the target area change, executing the following step S603;

in step S603, the map element vector to be updated of the changed element is sent to the server;

in step S604, the server performs map data update processing based on the map element vector to be updated of the change element.

For example, a map data update scenario of the present disclosure may be as follows: the update device on the crowdsourcing vehicle may collect raw data of the target area during normal driving of the crowdsourcing vehicle, the raw data including raw point cloud data, image data, and real-time trajectory height; the updating device can filter useless points (far away from road points and dynamic object points) in the original point cloud data based on the real-time track height to obtain geographic point cloud data, then extracts a map element vector to be updated in the target area based on the geographic point cloud data and image data, matches and aligns the target area with a corresponding area in a pre-stored high-precision map, and then performs element difference on the map element vector to be updated and an existing map element vector in the corresponding area to determine whether the map element in the target area changes; when the map elements in the target area are changed, determining the change confidence coefficient of the changed elements; when the change confidence coefficient is greater than a preset threshold value, sending a to-be-updated map element vector corresponding to the changed element to a server, so that the server performs map updating based on the to-be-updated map element vector corresponding to the changed element, and when the change confidence coefficient is less than or equal to the preset threshold value, sending the to-be-updated map element vector and geographic data corresponding to the changed element to the server, displaying the to-be-updated map element vector and the original data corresponding to the changed element by the server, and then performing map updating based on an updating instruction in response to receiving an updating instruction input by a user, wherein the updating instruction is used for indicating map updating based on the to-be-updated map element vector corresponding to the changed element or map updating based on the changed element vector input by the user. In such a scenario, the server may also send the latest high-precision map and the updated image segmentation algorithm to the updating device, and may also obtain log information returned by the updating device.

In other possible embodiments, another map data update scenario of the present disclosure may be as follows: the update device on the crowdsourcing vehicle may collect raw data of the target area during normal driving of the crowdsourcing vehicle, the raw data including raw point cloud data, image data, and real-time trajectory height; the updating device can filter useless points (far away from road points and dynamic object points) in the original point cloud data based on the real-time track height to obtain geographic point cloud data, then sends the geographic point cloud data and corresponding image data to a server, the server can extract a map element vector to be updated in the target area based on the geographic point cloud data and the image data, after the target area is matched and aligned with a corresponding area in a pre-stored high-precision map, element difference is carried out on the map element vector to be updated and an existing map element vector in the corresponding area, and whether the map element in the target area changes or not is determined; when the map elements in the target area are changed, determining the change confidence coefficient of the changed elements; when the change confidence coefficient is larger than a preset threshold value, performing map updating based on the to-be-updated map element vector corresponding to the change element, when the change confidence coefficient is smaller than or equal to the preset threshold value, displaying the to-be-updated map element vector corresponding to the change element and original data, and then responding to an updating instruction input by a user, and performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the to-be-updated map element vector corresponding to the change element or map updating based on the change element vector input by the user.

The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.

Fig. 7 shows a block diagram of a map data update apparatus according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 7, the map data update apparatus includes:

a first obtaining module 701 configured to obtain geographic data of a target area, the geographic data including geographic point cloud data;

an extracting module 702 configured to extract a map element vector to be updated within the target region based on the geographic data;

a difference module 703, configured to match and align the target area with a corresponding area in a pre-stored high-precision map, and then perform element difference between the map element vector to be updated and an existing map element vector in the corresponding area to determine whether a map element in the target area changes;

a first updating module 704 configured to perform map data updating processing if the map elements in the target area are changed.

In a possible implementation manner, the apparatus is applied to an update device, and the first update module 704 is configured to:

In a possible implementation, the apparatus is applied to a server, and the first updating module 704 is configured to:

if the change confidence coefficient is less than or equal to a preset threshold value, outputting a map element vector to be updated and geographic data corresponding to the changed element; and in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

In a possible implementation, the first obtaining module 701 is configured to:

acquiring original point cloud data of a target area;

In a possible implementation, the raw data further includes a real-time track height, and the filtering in the first obtaining module 701 is configured to filter the far road point and the dynamic object point in the raw point cloud data to obtain a portion of the geographical point cloud data:

and filtering out dynamic object points with the height exceeding the third preset distance of the ground elevation in the non-ground points.

In a possible implementation, the geographic data further includes image data, and the extraction module 702 is configured to:

In a possible implementation, the extraction module 702 performs map element extraction based on the geographic point cloud data, and a portion of the map element vector in the target area is configured to:

In a possible implementation, the extraction module 702 performs map element extraction based on the geographic point cloud data and the image data, and the portion of the second map element vector in the target area is configured to:

In a possible implementation manner, the merging, in the extracting module 702, the first map element vector and the second map element vector to obtain the map element vector to be updated is configured to:

In a possible implementation, the part of the first updating module 704 that determines the confidence of the change of the changed element is configured to:

Technical terms and technical features related to the technical terms and technical features shown in fig. 7 and related embodiments are the same as or similar to those of the technical terms and technical features shown in fig. 1 to 5 and related embodiments, and for the explanation and description of the technical terms and technical features related to the technical terms and technical features shown in fig. 7 and related embodiments, the above explanation of the technical terms and technical features shown in fig. 1 to 5 and related embodiments can be referred to, and are not repeated herein.

Fig. 8 is a block diagram illustrating a structure of a map data update apparatus according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 8, the map data updating apparatus includes:

a second obtaining module 801 configured to obtain map information of a changed element sent by an updating device, where the map information includes a map element vector to be updated;

a second updating module 802, configured to update a map based on the to-be-updated map element vector corresponding to the changed element if the map information includes the to-be-updated map element vector; if the map information comprises a map element vector to be updated, geographical point cloud data and image data, displaying the map element vector to be updated, the geographical point cloud data and the image data; and in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

Technical terms and technical features related to the technical terms and technical features shown in fig. 8 and related embodiments are the same as or similar to those of the technical terms and technical features shown in fig. 1 to 5 and related embodiments, and for explanation and explanation of the technical terms and technical features related to the technical terms and technical features shown in fig. 8 and related embodiments, reference may be made to the explanation of the above explanation of the technical terms and technical features shown in fig. 1 to 5 and related embodiments, and no further description is provided here.

The embodiment of the disclosure also discloses a navigation service, wherein the positioning of the carrier is determined based on the carrier positioning method, and the navigation guidance service of the corresponding scene is provided for the carrier based on the positioning of the carrier. Wherein, the corresponding scene is one or a combination of more of AR navigation, overhead navigation or main and auxiliary road navigation.

The embodiment of the disclosure also discloses a navigation method, wherein a navigation route calculated at least based on a starting point, an end point and a road condition is obtained based on an electronic map, the carrier is guided based on the navigation route and the positioning of the carrier, and the positioning of the carrier is realized by the carrier positioning method.

The present disclosure also discloses an electronic device, fig. 9 shows a block diagram of an electronic device according to an embodiment of the present disclosure, and as shown in fig. 9, the electronic device 900 includes a memory 901 and a processor 902; wherein the content of the first and second substances,

the memory 901 is used to store one or more computer instructions, which are executed by the processor 902 to implement the above-described method steps.

FIG. 10 is a schematic block diagram of a computer system suitable for use in implementing methods according to embodiments of the present disclosure.

As shown in fig. 10, the computer system 1000 includes a processing unit 1001 that can execute various processes in the above-described embodiments according to a program stored in a Read Only Memory (ROM)1002 or a program loaded from a storage section 1008 into a Random Access Memory (RAM) 1003. In the RAM1003, various programs and data necessary for the operation of the system 1000 are also stored. The processing unit 1001, the ROM1002, and the RAM1003 are connected to each other by a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.

The following components are connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a network interface card such as a LAN card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary. The processing unit 1001 may be implemented as a CPU, a GPU, a TPU, an FPGA, an NPU, or other processing units.

In particular, the above described methods may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the method described above. In such embodiments, the computer program may be downloaded and installed from a network through the communication section 1009 and/or installed from the removable medium 1011.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.

As another aspect, the disclosed embodiment also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the embodiments of the present disclosure.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept. For example, the above features and (but not limited to) the features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.

Claims

1. A map data updating method, comprising:

2. The method according to claim 1, wherein the method is applied to an updating device, and the map data updating process performed if the map elements in the target area are changed comprises the following steps:

3. The method according to claim 1, wherein the method is applied to a server, and the updating the map data if the map elements in the target area are changed comprises:

if the map elements in the target area change, determining the change confidence coefficient of the changed elements;

4. The method of claim 1, wherein the obtaining geographic data for a target area comprises:

acquiring original point cloud data of a target area;

and filtering the road points and the dynamic object points far away from the original point cloud data to obtain the geographical point cloud data of the target area.

5. The method of claim 4, wherein the raw data further comprises real-time trajectory height, and the filtering of far road points and dynamic object points in the raw point cloud data to obtain geo-point cloud data comprises:

6. The method of claim 1 or 5, wherein the geographic data further comprises image data, said extracting a map element vector to be updated within the target region based on the geographic data comprising:

7. The method of claim 6, wherein the performing map element extraction based on the geographic point cloud data to obtain a first map element vector within the target area comprises:

8. The method of claim 6 or 7, wherein the map element extraction based on the geographic point cloud data and the image data to obtain a second map element vector within the target region comprises:

9. The method of claim 8, wherein the fusing the first map element vector and the second map element vector to obtain the map element vector to be updated comprises:

10. The method of claim 2 or 3, wherein said determining a change confidence for said changed element comprises:

11. A map data updating method, comprising:

obtaining map information of the changed elements sent by the updating equipment;

if the map information comprises a map element vector to be updated, geographical point cloud data and image data, displaying the map element vector to be updated, the geographical point cloud data and the image data; in response to receiving an input updating instruction, performing map updating based on the updating instruction, wherein the updating instruction is used for indicating map updating based on the map element vector to be updated corresponding to the changed element or map updating based on the changed element vector input by a user.

12. A map data updating method, comprising:

13. An electronic device comprising a memory and a processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the processor to implement the method steps of any of claims 1 to 12.

14. A navigation method, wherein a navigation route calculated at least based on a starting point, an end point and a road condition is obtained based on an electronic map, and the carrier is guided based on the navigation route, and the electronic map is implemented based on any one of the methods of claims 1 to 12.