WO2022083487A1

WO2022083487A1 - Method and apparatus for generating high definition map and computer-readable storage medium

Info

Publication number: WO2022083487A1
Application number: PCT/CN2021/123613
Authority: WO
Inventors: 胡颖
Original assignee: 腾讯科技（深圳）有限公司
Priority date: 2020-10-22
Filing date: 2021-10-13
Publication date: 2022-04-28
Also published as: CN112163063A; CN112163063B

Abstract

A method and apparatus for generating a high definition map, and a computer-readable storage medium. The method comprises: acquiring map data of a target to be updated that is acquired by an acquisition device, wherein the acquisition device comprises a special map data acquisition vehicle and other mobile devices that have map data acquisition capabilities (S201); according to the map data of the target acquired by the acquisition device, the device weight value of the acquisition device and the property weight of the target, determining the update result of the target, wherein the device weight of the acquisition device represents the weight of the map data of the target acquired by the acquisition device, and the property weight of the target is determined according to requirements for the update frequency and accuracy of the target (S220); according to the update result for the target, generating an updated high definition map (S230).

Description

Method, apparatus and computer-readable storage medium for generating high-precision map

This application claims the priority of the Chinese Patent Application No. 202011138294.6 filed on October 22, 2020 and entitled "Method, Apparatus and Computer-readable Storage Medium for Generating High-precision Maps", the entire contents of which are incorporated by reference in this application.

technical field

The present invention relates to the field of map data collection, and more particularly, to a method, apparatus and computer-readable storage medium for generating a high-precision map.

Background technique

High Definition Map mainly relies on a dedicated collection vehicle for data collection, and is further generated by manual secondary verification. Since high-precision maps are updated more frequently than traditional maps, this mapping mode often leads to longer map production cycles and higher production costs.

SUMMARY OF THE INVENTION

The present application provides a method, a device and a computer-readable storage medium for generating a high-precision map, which can reduce the cost and cycle of drawing for generating a high-precision map.

In a first aspect, a method for generating a high-precision map is provided, including: acquiring map data of a target to be updated collected by a collection device, wherein the collection device includes a dedicated collection vehicle for map data and other devices with map data collection capability. A mobile device; according to the map data of the target to be updated collected by the collection device, the device weight of the collection device and the characteristic weight of the target to be updated, determine the update result of the target to be updated, wherein, The device weight of the collection device represents the weight of the map data of the target to be updated collected by the collection device, and the characteristic weight of the target to be updated is determined according to the update frequency and accuracy requirements of the target to be updated; The update result of the target to be updated generates an updated high-precision map.

In a second aspect, a method for generating a high-precision map is provided, including: a collection device collects map data of a target to be updated, the collection device is a movable device with map data collection capability, and the movable device is not a map A dedicated data collection vehicle; report the map data of the target to be updated to the high-precision map platform.

In a third aspect, a method for generating a high-precision map is provided, which includes: acquiring map data of a target to be verified collected by a collection device, wherein the collection device includes a dedicated map data collection vehicle and other devices with map data collection capabilities. A mobile device; according to the map data of the target to be verified collected by the said and other movable devices with a collection function, the device weight of the collection device and the characteristic weight of the target to be verified, determine the to-be-verified target The verification result of the target, wherein the device weight of the collection device represents the weight of the map data of the target to be verified collected by the collection device, and the characteristic weight of the target to be verified is updated according to the update of the target to be verified Frequency and accuracy requirements are determined; an updated high-precision map is generated according to the verification result of the target to be verified.

In a fourth aspect, a method for generating a high-precision map is provided, comprising: acquiring a candidate verification target issued by a high-precision map platform by a collection device, the collection device is a movable device with map data collection capability, and the movable The equipment is not a dedicated collection vehicle for map data; the target to be verified is determined among the candidate verification targets; the map data of the target to be verified is collected; the map data of the target to be verified is reported to the high-precision map platform.

In a fifth aspect, an apparatus for generating a high-precision map is provided, which is used to execute the method in the first aspect or the third aspect or the respective implementations thereof. Specifically, the apparatus includes functional modules for executing the methods in the first aspect or the third aspect or the respective implementation manners thereof.

In a sixth aspect, an apparatus for generating a high-precision map is provided, which is used to execute the method in the second aspect or the fourth aspect or the respective implementations thereof. Specifically, the apparatus includes functional modules for executing the methods in the second aspect or the fourth aspect or the respective implementation manners thereof.

In a seventh aspect, an apparatus for generating a high-precision map is provided, including a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the first aspect or the third aspect or each implementation manner thereof.

In an eighth aspect, an apparatus for generating a high-precision map is provided, including a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the second aspect or the fourth aspect or each of the implementations thereof.

In a ninth aspect, a system for generating a high-precision map is provided, including the device for generating a high-precision map in the fifth aspect and the device for generating a high-precision map in the sixth aspect.

A tenth aspect provides a system for generating a high-precision map, including the device for generating a high-precision map in the seventh aspect and the device for generating a high-precision map in the eighth aspect.

In an eleventh aspect, a computer-readable storage medium is provided for storing a computer program, the computer program causing a computer to execute the method in any one of the above-mentioned first to fourth aspects or each of its implementations.

A twelfth aspect provides a computer program product, the computer program product includes computer instructions, the computer instructions are stored in a computer-readable storage medium, and the processor reads and executes the computer instructions from the computer-readable storage medium, to A method in any one of the above-mentioned first to fourth aspects or implementations thereof is achieved.

Through the above technical solutions, map data is collected through vehicles or mobile devices with map data collection capabilities, so that the map data collection capabilities of existing equipment can be reasonably utilized to provide services for the generation of high-precision maps, which is conducive to reducing high-precision maps. The cartographic cost and cartographic cycle of the map.

Description of drawings

FIG. 1 is a block diagram of a system structure applicable to an embodiment of the present application.

FIG. 2 is a schematic diagram of a method for generating a high-precision map provided by an embodiment of the present application.

FIG. 3 is an overall flowchart of a method for generating a high-precision map according to the embodiment shown in FIG. 2 .

FIG. 4 is a schematic diagram of another method for generating a high-precision map provided by an embodiment of the present application.

FIG. 5 is an overall flow chart of the method for generating a high-precision map according to the embodiment shown in FIG. 4 .

FIG. 6 is a schematic diagram of yet another method for generating a high-precision map provided by an embodiment of the present application.

FIG. 7 is an overall flowchart of a method for generating a high-precision map according to the embodiment shown in FIG. 6 .

FIG. 8 is a schematic diagram of yet another method for generating a high-precision map provided by an embodiment of the present application.

FIG. 9 is an overall flowchart of a method for generating a high-precision map according to the embodiment shown in FIG. 8 .

FIG. 10 is a schematic structural diagram of an apparatus for generating a high-precision map provided by an embodiment of the present application.

FIG. 11 is a schematic structural diagram of an apparatus for generating a high-precision map provided by another embodiment of the present application.

FIG. 12 is a schematic structural diagram of an apparatus for generating a high-precision map provided by another embodiment of the present application.

FIG. 13 is a schematic structural diagram of an apparatus for generating a high-precision map provided by another embodiment of the present application.

FIG. 14 is a schematic structural diagram of an apparatus for generating a high-precision map provided by another embodiment of the present application.

FIG. 15 is a schematic structural diagram of an apparatus for generating a high-precision map provided by another embodiment of the present application.

FIG. 16 is a schematic structural diagram of a system for generating a high-precision map provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. With regard to the embodiments in the present application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

With the research and progress of artificial intelligence technology, artificial intelligence technology has been researched and applied in many fields, such as common smart homes, smart wearable devices, virtual assistants, smart speakers, smart marketing, unmanned driving, autonomous driving, drones It is believed that with the development of technology, artificial intelligence technology will be applied in more fields and play an increasingly important value.

Autonomous driving technology usually includes high-precision maps, environmental perception, behavioral decision-making, path planning, motion control and other technologies. Autonomous driving technology has a wide range of application prospects.

In this embodiment of the present application, a high-precision map (or referred to as a high-precision map) is a high-resolution map format, which can be applied to, for example, but not limited to, the field of unmanned driving and the field of automatic driving.

Compared with traditional maps, high-resolution maps can be dynamically made into maps with multiple layers. Examples include, but are not limited to, lane-level road network layers, positioning layers, and dynamic layers.

1. Lane-level road network layer, which can be used for navigation planning.

This layer mainly describes the accurate (for example, centimeter-level accuracy) three-dimensional representation of the road network and stores it as structured data, which can be divided into two categories:

Road data: such as road geometry, lane line type (solid/dotted, single/double), lane color (white, yellow), and data attributes of each lane (slope, curvature, heading, elevation, etc.) ;

Fixed object information around the lane: such as traffic signs, traffic lights and other information, lane height limits, sewer crossings, obstacles, and other road details, including overhead objects, the number of guardrails, road edge types, roadside landmarks and other infrastructure information.

2. The positioning layer is used for vehicle positioning.

The elements contained in this layer are used to locate the vehicle by matching with the sensors of the self-driving car. The positioning solution of the self-driving car can include, but is not limited to, the localization solution based on visual feature matching, and the point cloud based on LiDAR. The positioning solution of feature matching is based on the fusion of visual features and lidar point cloud feature data.

Optionally, the positioning layer may also contain elements related to the application scenario of the autonomous vehicle. For example, different positioning layers of high-precision maps can be generated according to different scenarios and different sensors.

3. Dynamic layers for route planning that senses and considers current road and traffic conditions.

This dynamic layer mainly includes elements that update relatively frequently, such as real-time road conditions and traffic events. More specifically, for example, dynamic traffic information such as road congestion, construction, whether there is a traffic accident, traffic regulation, and weather. As the road network changes every day, such as renovations, road marking wear and repainting, traffic sign changes, etc. These changes need to be reflected on high-precision maps in time to ensure the safety of autonomous vehicles.

For a better understanding of the embodiments of the present application, the following describes a system architecture applicable to the embodiments of the present application.

Referring to FIG. 1 , FIG. 1 is a schematic diagram of a system architecture applicable to an embodiment of the present application. As shown in FIG. 1 , the system architecture 100 may include a high-precision map platform 101 and a plurality of movable devices with map data collection capabilities, for example, a map data collection vehicle 102 and other movable devices with map data collection capabilities (or Common vehicles) 103, such as private cars with radar or camera equipment, or other movable equipment with radar or camera equipment.

Optionally, the map data acquisition vehicle 102 may include various sensors for map data acquisition, such as but not limited to lidar, camera, inertial measurement unit (Inertial measurement unit, IMU), global satellite navigation system (Global Navigation Satellite System, GNSS), high-precision wheel speed meter, etc.

In this embodiment of the present application, a movable device with map data collection capability can communicate with the high-precision map platform 101 . Communication takes place, for example, through wired, wireless communication links, or fiber optic cables.

The high-precision map platform 101 can be a server that provides various services, for example, can acquire road data, fixed object data around the road, traffic conditions, and the like. Further, the above data can be used in the field of autonomous driving, or the analysis results based on the above data can be displayed on any platform or product of real-time traffic conditions, such as digital large screens, map service applications, taxi software, logistics scheduling systems, etc. etc., or can also dynamically display real-time road conditions on the user's terminal (such as a vehicle-mounted computer) in a timely manner to facilitate the user to plan a route.

The user can use the terminal to interact with the high-precision map platform 101 to receive or send messages and the like. For example, the terminal can install and run a related client (Client). The client (for example, a high-precision map service client, etc.) refers to a program corresponding to the high-precision map platform 101 and providing services to users.

Clients include, but are not limited to, applications running locally, functions running on web browsers (also known as Web App), applets embedded in emails, and applets embedded in instant messaging client software. programs, as well as functions embedded in other applications (such as application accounts applied by developers or merchants based on public platforms), etc. For the client, the high-precision map platform 101 needs to run on the high-precision map platform 101, including but not limited to any operating system corresponding to the operating system that enriches the functions of the mobile device by providing various mobile applications. Server-side programs to provide corresponding services, such as database services, data computing , decision-making, etc.

The terminal in this embodiment of the present application may include, but is not limited to, any vehicle-mounted or handheld electronic product based on an intelligent operating system, which can communicate with the user through input devices such as keyboards, virtual keyboards, touchpads, touchscreens, and voice control devices. computer interaction, such as smartphones, tablets, personal computers, etc. Among them, intelligent operating systems, such as Android (Android), IOS, Windows Phone, etc.

FIG. 2 is a schematic flowchart of a method 200 for generating a high-precision map provided by an embodiment of the present application, and the method 200 may be based on the system architecture shown in FIG. 1 . Hereinafter, the method 200 is described from the perspective of a high-resolution map platform (or, in other words, a server). As shown in FIG. 2, the method 200 includes at least some of the following steps:

S210, acquiring the map data of the target to be updated collected by the collection device, wherein the collection device includes a dedicated map data collection vehicle and other movable devices with map data collection capability;

S220: Determine the update result of the target to be updated according to the map data of the target to be updated collected by the collection device, the device weight of the collection device and the characteristic weight of the target to be updated, wherein the device weight of the collection device represents the data collected by the collection device. The weight of the map data of the target to be updated, and the characteristic weight of the target to be updated is determined according to the update frequency and accuracy requirements of the target to be updated;

S230: Generate an updated high-precision map according to the update result of the target to be updated.

The collection device in the embodiment of the present application may be any movable device registered with the high-precision map platform, more specifically, a movable device with map data collection capability, for example, may include but not limited to a dedicated collection vehicle for map data, a user private vehicles, etc.

In this embodiment of the present application, the map update task is sent to the mobile devices registered on the high-precision map platform, and map data is collected through these devices, so that the map data collection capability of the existing devices can be reasonably utilized, and a high-precision map is created. It provides services for the generation of high-precision maps, which is conducive to reducing the mapping cost and mapping cycle of high-precision maps.

In some embodiments of the present application, the map data of the target to be updated may include, but is not limited to, road data, data of fixed objects around the road, road condition data, and the like, for example.

In some embodiments of the present application, which objects to be updated are collected by the collection device for map data may be determined by the collection device according to its own device capabilities, or may also be based on the update task issued by the high-precision map platform to the collection device definite. The update task issued by the high-precision map platform may also be determined according to the device capability of the collection device. For example, the update task may include which targets to collect map data for.

In some embodiments of the present application, the device capability of the collection device may include whether a specific sensor for map data collection is installed on the collection device, or the included sensor accuracy, for example, whether a radar is installed, radar accuracy, whether a camera is installed, camera accuracy, etc.

In some embodiments of the present application, the collection device may collect map data according to a predetermined route or a driving route. The collection device may choose a map data collection mode by itself, or may use a specific mode to collect map data based on the configuration of the high-precision map platform, which is not limited in this application. For example, a dedicated vehicle for collecting map data can collect map data based on a predetermined route, and a private car can collect map data along the driving route.

In some embodiments of the present application, the device weight of the collection device, that is, the weight of the map data of the target to be updated collected by the collection device, may be determined according to the device capability of the collection device and the characteristics of the target to be updated.

For example, for a target to be updated that requires high radar accuracy, if the radar accuracy of the acquisition device is high, a larger device weight can be configured for the acquisition device to represent the map data of the target to be updated collected by the acquisition device. or, if the radar accuracy of the acquisition device is low, a smaller device weight can be configured for the acquisition device, indicating that the reliability of the map data of the target to be updated collected by the acquisition device is relatively high. Low.

For another example, if the target to be updated (such as a road name) only needs to have a camera function, the device weights of the collection devices can be configured to have little difference, which indicates the reliability of the map data of the target to be updated collected by different collection devices. minor difference.

It should be understood that the device weight of the collection device is for the target to be updated, and for different targets to be updated, the device weight corresponding to the same collection device may be different.

Since the sensors configured by different collection devices are different, and different targets to be updated also have different accuracy requirements, the embodiment of the present application configures the collection devices with different device capabilities with corresponding device weights, which is beneficial to Ensure the accuracy of the update data of the target to be updated.

In some embodiments of the present application, the characteristic of the target to be updated has a specific corresponding weight, and the weight of the characteristic of the target to be updated may be determined according to the update frequency and accuracy requirements of the target to be updated.

For example, if the update frequency of the to-be-updated target is relatively low, or the accuracy requirements are relatively high, for example, the to-be-updated target is road width, it may be determined that the to-be-updated target has a relatively small characteristic weight.

For another example, if the update frequency of the to-be-updated target is relatively high, or the accuracy requirements are not high, for example, the to-be-updated target is the degree of road congestion, it can be determined that the to-be-updated target has a relatively large characteristic weight.

In some embodiments, the update completion degree of the map data of the target to be updated is the sum of the update results of the target to be updated by multiple collection devices, wherein the multiple collection devices are collection devices that collect map data of the target to be updated, and the collection The update result of the target to be updated by the device is the product of the device weight of the acquisition device, the characteristic weight of the target to be updated, and the update flag corresponding to the acquisition device, where the update flag corresponding to the acquisition device represents the update flag of the target to be updated collected by the acquisition device. The map data determines whether the map data of the target to be updated in the high-precision map needs to be updated.

In this embodiment of the present application, the update flag corresponding to the collection device may indicate whether updating is required. For example, 1 may be used to indicate that updating is required, -1 (or 0) may be used to indicate that updating is not required, or 1 may be used to indicate that updating is not required, and- 1 (or 0) indicates that it needs to be updated, and the specific representation method is not limited in this application.

In some embodiments, when 1 is used to indicate that an update is required and -1 is used to indicate that an update is not required, if the calculated update completion degree is a negative value, it means that the update is not required, or if the calculated update completion degree is a positive value , it indicates that an update is required. In other embodiments, when -1 is used to indicate that an update is required and 1 is used to indicate that an update is not required, if the calculated update completion degree is a negative value, it means that an update is required, or if the calculated update completion degree is a positive value , it means that no update is required.

Specifically, the target to be updated is the road width, the current road width in the high-precision map is 10m, the characteristic weight of the target to be updated is 1, the equipment weight of vehicle A is 1, and the equipment weight of vehicle B is 0.5. The width of the road collected by vehicle A is 10m, and the width of the road collected by vehicle B is 9.9m. An update flag of 1 indicates that no update is required, and an update flag of -1 indicates that an update is required. The update result of vehicle A to the update target is: 1*1*1, the update result of vehicle B to the update target is: 0.5*1*(-1), and the update result of the road width at this time is: the update completion degree is 1* 1*1+0.5*1*(-1)=0.5, no update is required.

For another example, the target to be updated is the road congestion degree, the current road congestion degree in the high-precision map is no congestion, the characteristic weight of the target to be updated is 50, the equipment weight of vehicle A is 1, and the equipment weight of vehicle B is 1. is 1. The road congestion degree determined by vehicle A is relatively high, and the road congestion degree determined by vehicle B is relatively high. If the update flag is 1, it means that it needs to be updated, and if the update flag is -1, it means that it does not need to be updated. Then the update result of vehicle A to the update target is: 1*50*1, and the update result of vehicle A to the update target is: 1*50*1 . Then, the update result of the road congestion degree is: the update completion degree is 1*50*1+1*50*1=100, which needs to be updated.

In some embodiments of the present application, when the update completion degree of the map data of the target to be updated reaches a preset value, the information of the target to be updated in the high-precision map is updated.

In some embodiments, the preset value may be, for example, 100, or may be other values, and the present application is not limited thereto. The following description takes the default value of 100 as an example, but the present application is not limited to this.

It should be understood that, in this embodiment of the present application, the update completion rate of the target to be updated can also be used to indicate the update completion status of the target to be updated. In this case, when the update completion rate reaches 100%, it can be considered that the update is completed, and the present application is not limited to this. .

In this embodiment of the present application, a target configuration to be updated with a low update frequency or a high precision requirement is assigned a smaller characteristic weight, and a target configuration to be updated with a high update frequency or a low precision requirement is assigned a larger characteristic weight. In this way, for targets to be updated with low update frequency or high accuracy requirements, map data of more devices is required to complete the update, and for targets to be updated with high update frequency or low accuracy requirements, less map data is required. The device's map data is updated. By performing differentiated update configuration for different types of targets to be updated, it is possible to take into account the data accuracy and mapping efficiency of the targets to be updated.

Optionally, in this embodiment of the present application, before the collection device performs the collection of map data, the registration or authentication process of the collection device needs to be performed. This application does not specifically limit the registration or authentication method of the collection device.

As an implementation manner, an account number and a password may be used for registration and authentication.

As another implementation manner, the user's biometric feature may also be used for registration and authentication, and the biometric feature may be, for example, a face, a voiceprint, or a fingerprint. The following describes an overall flow chart of a method for generating a high-precision map with reference to FIG. 3 , taking the collection device as a vehicle as an example. As shown in Figure 3, at least some of the following steps may be included:

S301, the vehicle is authenticated.

For example, authentication may be performed according to the account number and password input by the user or authentication may be performed according to the biometric information input by the user.

S302, acquiring the map update mode. The map update mode can be selected by the vehicle, or can also be configured by the high-precision map platform.

The map update mode may include, for example, but is not limited to, a specific road segment update mode, that is, driving according to a predetermined route to collect map data of the target to be updated on the predetermined route, and a driving update mode, that is, collecting map data of the target to be updated according to the driving route.

For a specific road segment update mode, the specific update steps may include:

S311, acquiring the selected road range. That is, the map data of which road section is selected to be collected.

S312, obtain the device capability of the vehicle.

S313: Determine the device weight of the vehicle according to the device capability required by the target to be updated on the selected road and the device capability of the vehicle. For the specific implementation, refer to the relevant descriptions of the foregoing embodiments, which are not repeated here for brevity.

S314, the map updating step of the currently selected road is customized for different vehicles.

For example, the map updating step may include the driving route, the collection sequence of the objects to be updated on the road, the equipment capability of the vehicle to be used, and the like.

S315, instructing the vehicle to collect map data based on the map update step.

The specific instruction mode is, for example, but not limited to, the voice mode.

S316: Obtain the map data of the target to be updated collected by the vehicle, and determine the update result of the target to be updated according to the map data of the target to be updated collected by the vehicle, the equipment weight of the vehicle, and the characteristic weight of the target to be updated. For the specific implementation, refer to the relevant descriptions of the foregoing embodiments, which are not repeated here for brevity.

It should be understood that S313 may be performed before acquiring the map data collected by the vehicle, or may also be performed after acquiring the map data collected by the vehicle, which is not limited in this application.

For the update mode while driving, the specific update steps can include:

S321 , acquiring the device capability of the vehicle.

S322, according to the current positioning of the vehicle, determine the target to be updated on the road where the vehicle is currently located.

S323 , prompting the device capability to be used by the vehicle according to the device capability required by the target to be updated.

S324: Determine the device weight of the vehicle according to the device capability required by the target to be updated on the road and the device capability of the vehicle. For the specific implementation, refer to the relevant descriptions of the foregoing embodiments, which are not repeated here for brevity.

S325: Obtain the map data of the target to be updated collected by the vehicle, and determine the update result of the target to be updated according to the map data of the target to be updated collected by the vehicle, the equipment weight of the vehicle, and the characteristic weight of the target to be updated. For the specific implementation, refer to the relevant descriptions of the foregoing embodiments, which are not repeated here for brevity.

Further, after obtaining the update result of the target to be updated, in S330, it may be determined whether the update of the target to be updated is completed according to the update result of the target to be updated. That is, whether the update completion degree reaches the preset value.

If the update is completed, S340 is executed, and an updated high-precision map is generated according to the updated information of the target to be updated. Further, the updated high-precision map can be sent to the user of the map.

If the update is not completed, continue to perform the operations before S330 to obtain more map data collected by the vehicle for updating the map data.

The method for generating a high-precision map according to an embodiment of the present application is described in detail from the perspective of a high-precision map platform in conjunction with FIGS. 2 to 3 . A method for generating a high-precision map according to another embodiment of the application is claimed. It should be understood that the description on the side of the high-precision map platform corresponds to the description on the side of the collection device, and similar descriptions can be found in the above, which will not be repeated here to avoid repetition.

FIG. 4 is a schematic flowchart of a method 400 for generating a high-precision map provided by an embodiment of the present application, and the method 400 may be based on the system architecture shown in FIG. 1 . In the following, the method 400 is described from the perspective of a collection device. As shown in FIG. 4 , the method 400 includes at least some of the following steps:

S410, the collection device collects map data of the target to be updated, the collection device is a movable device with map data collection capability, and the collection device is not a dedicated collection vehicle for map data;

S420, report the map data of the target to be updated to the high-precision map platform.

Optionally, in some embodiments, the method 400 further includes:

The prompt information sent by the high-precision map platform is received, and the prompt information is used to prompt the device capability of the acquisition device used to collect the map data of the target to be updated.

Optionally, in some embodiments, the method 400 further includes:

Report the device capability of the acquisition device to the high-precision map platform.

The following describes an overall flow chart of the method for generating a high-precision map according to an embodiment of the present application, taking the collection device as a vehicle as an example with reference to FIG. 5 . As shown in Figure 5, at least some of the following steps may be included:

S501, the vehicle is registered to the high-precision map platform or authenticated based on the registered information.

For example, an account number and password can be used for registration or authentication, or biometric information can be used for registration or authentication.

S502, select a map update mode. The map update mode may include, but is not limited to, a specific road segment update mode, that is, collecting map data of the target to be updated on the predetermined route according to a predetermined route, and a driving update mode, that is, collecting map data of the target to be updated according to the driving route.

For a specific road segment update mode, the specific update steps may include:

S511, select a road range for map update. That is, the map data of which road section is selected to be collected.

S512 , report the device capability of the vehicle to the high-precision map platform.

S513, obtaining a map update step customized for the vehicle by the high-precision map platform based on the road selected by the vehicle.

S514, collecting map data based on the map updating step.

S515, upload the collected map data to the high-precision map platform.

For the update mode while driving, the specific update steps can include:

S521 , report the equipment capability of the vehicle to the high-precision map platform.

S522: Obtain the target to be updated on the current road issued by the high-precision map platform.

The target to be updated may be determined according to the target to be updated on the current road and the device capability of the vehicle.

In other embodiments, the vehicle can also obtain the target to be updated on the current road by itself according to the current positioning, and further collect the map data.

S523: Receive prompt information sent by the high-precision map platform, where the prompt information is used to prompt the device capability to be used by the vehicle during driving. For example, turn on the radar, camera, read the vehicle's location, mileage, etc.

S524, upload the map data collected by the vehicle to the high-precision map platform.

Hereinafter, the specific execution process will be described with reference to specific embodiments.

Assume that both vehicle A and vehicle B update the map of road S, vehicle A is a dedicated collection vehicle for map data, the vehicle A adopts the update mode of a specific road section, and vehicle B is an ordinary private car. Drive in to perform a map update mission.

First, vehicle A and vehicle B perform user login operations on the high-precision map platform.

The high-precision map platform authenticates the authority of vehicle A and vehicle B respectively. If the authentication is successful, the vehicle A and vehicle B are allowed to perform map update tasks.

Further, vehicle A selects the update mode for road S, and vehicle B selects the update mode with driving.

The high-precision map platform obtains the equipment capabilities of vehicle A and vehicle B. For example, vehicle A can perform functions such as point cloud data collection, ranging, and photographing, while vehicle B can perform functions such as ranging and photographing.

The potential update targets on the road S include: road name, road width, road marker X for localization, and road congestion degree.

Then, the high-precision map platform issues to vehicle A a predetermined route for updating all the targets, and prompts the vehicle to travel according to the predetermined route and execute the update steps. The high-precision map platform prompts vehicle B to use the vehicle's ranging and photographing capabilities during the vehicle's driving.

Further, the vehicle A and the vehicle B respectively drive through the road S, collect map data, and upload the collected map data.

The high-precision map platform receives the map data collected by vehicle A, and determines the update result of vehicle A for each target to be updated according to the map data collected by vehicle A: road name N, no need to update; road width 10m, no need to update; road sign The point cloud data of object X; the current congestion degree of road S is relatively high.

The high-precision map platform receives the map data collected by vehicle B, and determines the update result of vehicle B for each target to be updated according to the map data collected by vehicle B: road name N, no need to update; road width 9.9m, which needs to be updated from 10m is 9.9m; the current congestion level of road S is relatively high.

The high-precision map platform can determine the equipment weight of the vehicle according to the equipment capability of the vehicle and the characteristics of the target to be updated. The feature weight of the target to be updated may also be determined according to the characteristics of the target to be updated (eg, update frequency, accuracy requirements, etc.).

Further, according to the map data of the target to be updated collected by the vehicle, the equipment weight of the vehicle and the characteristic weight of the target to be updated, the update result of the target to be updated is determined. For example, whether there has been a change, the degree of completion of the update, etc.

For example, for the road name, the characteristic weight of the target can be set to 1, and the equipment weights collected by vehicle A and vehicle B are both 1. Therefore, the update result of the road name is: no update required, and the update completion degree is 1*1 *1+1*1*1=2.

For road width, the feature weight of the target can be set to 1, the equipment weight of vehicle A is 1, and the equipment weight of vehicle B is 0.5. Then, the update result of the road width is: no update is required, and the update completion degree is 1*1*1+(-1)*1*0.5=0.5.

For road marker X, the characteristic weight of the target can be set to 0.5, the equipment weight of vehicle A is 1, and the data returned by vehicle A is different from the data on the high-precision map platform, the update result of the road width is: need For update, the update completion degree is 1*0.5*1=0.5.

For the road congestion degree, the characteristic weight of the target can be set to 50, the equipment weight of vehicle A is 1, and the equipment weight of vehicle B is 1, then the update result of the road congestion degree is: need to be updated, the road congestion degree is Higher, the update completion degree is 1*50*1+1*50*1=100.

Further, when the update completion degree of the target to be updated reaches a preset value, such as 100, update the information of the target to be updated in the high-precision map, for example, the update completion degree of the road congestion degree reaches 100, then update the high-precision map. information on the road congestion level, and further distribute the updated map to the user.

FIG. 6 is a schematic flowchart of a method 600 for generating a high-precision map provided by an embodiment of the present application, and the method 600 may be based on the system architecture shown in FIG. 1 . Hereinafter, the method 600 is described from the perspective of a high-resolution map platform (or, in other words, a server). As shown in FIG. 6, the method 600 includes at least some of the following steps:

S610, acquiring map data of the target to be verified collected by a collection device, where the collection device includes a dedicated map data collection vehicle and other movable devices with a map collection function;

S620: Determine the verification result of the target to be verified according to the map data of the target to be verified collected by the acquisition device, the device weight of the acquisition device, and the characteristic weight of the target to be verified, wherein the device weight of the acquisition device represents the data collected by the acquisition device. The weight of the map data of the target to be verified, the characteristic weight of the target to be verified is determined according to the update frequency and accuracy requirements of the target to be verified;

S630: Generate an updated high-precision map according to the verification result of the target to be verified.

The acquisition device in this embodiment of the present application may be any movable device registered with the high-precision map platform, and more specifically, a device with map data acquisition capability, such as but not limited to the private map of the high-precision map platform. Data collection vehicle, user's private vehicle.

In the embodiment of the present application, by sending the map verification task to the mobile devices registered to the high-precision map platform, collecting map data through these devices, and further verifying based on the collected map data, the existing equipment can be used reasonably. The map collection capability provides services for the generation of high-precision maps, which is conducive to reducing the mapping cost and mapping cycle of high-precision maps.

In some embodiments of the present application, the map data of the target to be verified may include, but is not limited to, road data, data of fixed objects around the road, road condition data, and the like, for example.

In some embodiments of the present application, which objects to be verified are collected by the collection device for map data may be determined by the collection device according to the information of candidate verification targets sent by the high-precision map platform to the collection device, and the high-precision map platform sends The information of the candidate verification target may be determined according to the device capability of the acquisition device.

In some embodiments of the present application, the device capabilities of the collection device may include whether the collection device includes sensors for map data collection, or the included sensor accuracy, for example, whether to include radar, radar accuracy, whether to include cameras, camera accuracy Wait.

In some embodiments of the present application, the device weight of the acquisition device, that is, the weight of the map data of the to-be-verified target collected by the acquisition device, may be determined according to the device capability of the acquisition device and the characteristics of the target to be verified.

For example, for a target to be verified that requires high radar accuracy, if the radar accuracy of the acquisition device is high, a larger device weight can be configured for the acquisition device to represent the map data of the target to be verified collected by the acquisition device. or, if the radar accuracy of the acquisition device is low, a smaller device weight can be configured for the acquisition device, indicating that the reliability of the map data of the target to be verified collected by the acquisition device is relatively high. Low.

For another example, if the target to be verified (such as a road name) only needs to have a camera function, the device weights of the acquisition devices can be configured to have little difference, indicating the reliability of the map data of the target to be verified collected by different acquisition devices. minor difference.

It should be understood that the device weight of the collection device is for the target to be verified, and for different targets to be verified, the device weight corresponding to the same collection device may be different.

Since the sensors configured by different collection devices are different, and the requirements for data accuracy of different targets to be verified are also different, the embodiment of the present application configures the map data collected by the collection devices with different device capabilities to correspond to The weights are beneficial to ensure the accuracy of the verification data of the target to be verified.

In some embodiments of the present application, the characteristic of the object to be verified corresponds to a corresponding weight, and the weight of the characteristic of the object to be verified may be determined according to the update frequency and accuracy requirements of the object to be verified.

For example, if the update frequency of the object to be verified is relatively low, or the accuracy requirements are high, such as road width, it may be determined that the characteristic weight of the object to be verified is low. For another example, if the update frequency of the object to be verified is relatively high, or the accuracy requirements are not high, such as the degree of road congestion, it can be determined that the characteristic weight of the object to be verified is relatively large.

In some embodiments, the verification completion degree of the map data of the target to be verified is the sum of the verification results of the target to be verified by multiple collection devices, wherein the multiple collection devices are collection devices that collect map data of the target to be verified, and the collection device The verification result of the target to be verified is the product of the device weight of the acquisition device, the characteristic weight of the target to be verified, and the verification mark corresponding to the acquisition device, wherein the verification mark corresponding to the acquisition device represents the map of the target to be verified collected according to the acquisition device The data determines whether the map data of the target to be verified in the high-resolution map is correct.

In this embodiment of the present application, the verification flag corresponding to the collection device may indicate whether the verification result is correct, for example, 1 may be used to indicate correctness, -1 may be used to indicate incorrectness, or 1 may be used to indicate incorrectness, and -1 may be used to indicate correctness. Mode This application does not limit this.

In some embodiments, when 1 is used to indicate correctness and -1 is used to indicate incorrectness, if the calculated verification completion degree is a negative value, it means that it is incorrect, or if the calculated verification completion degree is a positive value, it means that correct. In other embodiments, when -1 is used to indicate correctness and 1 is used to indicate incorrectness, if the calculated verification completion degree is a negative value, it means correct, or if the calculated verification completion degree is a positive value, it means that Incorrect.

For example, the target to be verified is the road width, the road width in the high-precision map is 10m, the characteristic weight of the target to be verified is 1, the equipment weight of vehicle A is 1, and the equipment weight of vehicle B is 0.5. The width of the road collected by vehicle A is 10m, and the width of the road collected by vehicle B is 9.9m. If the verification flag is 1, the data is correct, and if the verification result flag is -1, the data is incorrect. At this time, the verification result of the road width is: the verification completion degree is 1*1*1+0.5*1*(-1)=0.5, and the current The map data is correct.

In some embodiments of the present application, when the verification completion degree of the map data of the target to be verified reaches a preset value, the information of the target to be verified in the high-precision map is updated according to the verified information.

In some embodiments of the present application, the preset value may be, for example, 100, or may be other values, but the present application is not limited thereto. The following description takes the default value of 100 as an example, but the present application is not limited to this.

It should be understood that, in this embodiment of the present application, the verification completion rate of the target to be verified may also be used to indicate the verification completion status of the target to be verified. In this case, when the verification completion rate reaches 100%, it can be considered that the verification is completed, and the present application is not limited to this. .

In this embodiment of the present application, a target configuration to be verified with a low update frequency or a high accuracy requirement is assigned a smaller characteristic weight, and a target configuration to be verified with a high update frequency or a low accuracy requirement is assigned a larger characteristic weight. In this way, for the targets to be verified with low update frequency or high precision requirements, more map data of the acquisition device is required to complete the verification, and for the targets to be verified with high update frequency or low precision requirements, less need for verification The map data of the collection device can be verified. By performing differentiated verification configurations for different types of targets to be verified, the accuracy of the data of the targets to be verified and the mapping efficiency can be taken into account.

The following describes an overall flow chart of the method for generating a high-precision map with reference to FIG. 7 , taking the collection device as a vehicle as an example. As shown in Figure 3, at least some of the following steps may be included:

S701, the vehicle is authenticated.

S702, according to the road range selected by the user, determine the verification target within the road range.

Further optionally, the verification target within the road range may be issued to the user.

In some embodiments, the high-resolution map platform can obtain the device capabilities of the vehicle.

Then in some embodiments, in S703, the high-precision map platform determines a candidate verification target that the vehicle can execute according to the device capability of the vehicle and the verification target on the road. Further optionally, the information of the candidate verification target may be delivered to the user.

S704, the high-precision map platform obtains the verification target selected by the vehicle.

The verification target selected by the vehicle may be selected by the verification target in S702, or may also be selected by the candidate verification target in S703.

S705, according to the characteristics of the verification target of the vehicle and the equipment capability of the vehicle, determine the equipment weight of the vehicle. For the specific implementation, refer to the relevant descriptions of the foregoing embodiments, which are not repeated here for brevity.

S706: Determine the required verification steps according to the verification target selected by each vehicle.

For example, the verification step may include the driving route for performing verification, the verification sequence of the objects to be verified on the road, the equipment capability of the vehicle to be used, and the like.

S707, the verification step is sent to the vehicle, and the vehicle is guided to verify the map data based on the verification step.

S708: Obtain the map data of the target to be verified collected by the vehicle, and determine the verification result of the target to be verified according to the map data of the target to be verified collected by the vehicle, the equipment weight of the vehicle, and the characteristic weight of the target to be verified. For the specific implementation, refer to the relevant descriptions of the foregoing embodiments, which are not repeated here for brevity.

It should be understood that S705 may be performed before the map data collected by the vehicle is acquired, or may be performed after the map data collected by the vehicle is acquired, which is not limited in this application.

Further, after obtaining the verification result of the target to be verified, in S709, it may be determined whether the verification of the target to be verified is completed according to the verification result of the target to be verified. That is, verify whether the completion degree reaches the preset value.

If the verification is completed, S710 is executed, and an updated high-precision map is generated according to the verified information of the target to be verified. Further, the updated high-precision map can be sent to the user of the map.

If the verification is not completed, continue to perform the operations before S709 to obtain more map data collected by the vehicle for verification.

The method for generating a high-precision map according to another embodiment of the present application is described in detail from the perspective of a high-precision map platform in conjunction with FIGS. 6 to 7 . A method for generating a high-precision map according to another embodiment of the present application. It should be understood that the description on the side of the high-precision map platform corresponds to the description on the side of the collection device, and similar descriptions can be found in the above, which will not be repeated here to avoid repetition.

FIG. 8 is a schematic flowchart of a method 800 for generating a high-precision map provided by an embodiment of the present application, and the method 800 may be based on the system architecture shown in FIG. 1 . In the following, the method 800 is described from the perspective of a collection device. As shown in FIG. 8, the method 800 includes at least some of the following steps:

S810, the acquisition device acquires the candidate verification target issued by the high-precision map platform, the acquisition device is a movable device with map data acquisition capability, and the acquisition device is not a dedicated map data acquisition vehicle;

S820, determining the target to be verified among the candidate verification targets;

S830, collect map data of the target to be verified;

S840, report the map data of the target to be verified to the high-precision map platform.

Optionally, in some embodiments, the method 800 further includes:

The device capability of sending the acquisition device to the high-precision map platform.

With reference to FIG. 9 , the overall flow chart of the method for generating a high-precision map is described by taking the collection device as a vehicle as an example. As shown in Figure 9, at least some of the following steps may be included:

S901, the vehicle is registered to the high-precision map platform or authenticated based on the registered information.

S902, select a road range for verification. That is, the map data of which road segment is selected to be verified.

S903: Obtain candidate verification targets issued by the high-precision map platform.

S904, a target to be verified is determined from the candidate verification targets.

The to-be-verified target may include all candidate verification targets, or may only include some candidate verification targets, for example, the vehicle may select the to-be-verified target from the candidate verification targets for verification according to its own device capability.

S905, obtaining the verification steps issued by the high-precision map platform.

S906, collecting map data based on the verification step to verify the map data.

The specific execution process is described with reference to specific embodiments.

Assume that both vehicle A and vehicle B verify the road S, vehicle A is a dedicated collection vehicle for map data, and vehicle B is an ordinary private car.

The high-precision map platform authenticates the authority of vehicle A and vehicle B respectively. If the authentication is successful, the vehicle A and vehicle B are allowed to perform the map verification task.

Further, vehicle A and vehicle B choose to perform map verification on road S.

The high-precision map platform obtains the equipment capabilities of vehicle A and vehicle B. For example, both vehicle A and vehicle B can perform functions such as point cloud data collection, ranging, and photographing.

The high-precision map platform determines the candidate verification targets on the road S based on the device capabilities, and further sends the candidate verification targets to vehicle A and vehicle B. For example, road name, road width, road marker X for positioning.

Further, vehicle A chooses to verify road names, road widths, and road markers, and vehicle B chooses to verify road names and road widths.

According to the verification targets selected by vehicle A and vehicle B, the high-precision map platform formulates the driving route of the vehicle and sends it to vehicle A and vehicle B respectively.

Vehicle A and vehicle B drive through road S respectively according to the prompts of the high-precision map platform, collect map data during the driving process, and upload the collected data.

The high-precision map platform receives the map data of vehicle A, and determines the verification result of vehicle A for each target to be verified according to the map data collected by vehicle A: the road name N, which is consistent with the current map data; the road width is 10m, which is consistent with the current map data. The point cloud data of road marker X is consistent with the current map data.

The high-precision map platform receives the map data of vehicle B, and determines the verification result of vehicle B for each target to be verified according to the map data collected by vehicle B: the road name N, which is consistent with the current map data; the road width is 9.9m, which is consistent with the current map data. The current map data does not match.

The high-precision map platform can determine the equipment weight of the vehicle according to the equipment capability of the vehicle and the characteristics of the target to be verified. The feature weight of the object to be verified can also be determined according to the characteristics of the object to be verified (eg update frequency, accuracy requirements, etc.).

Further, the verification result of the target to be verified is determined according to the map data of the target to be verified collected by the vehicle, the equipment weight of the vehicle and the characteristic weight of the target to be verified. For example, whether it is correct, verification completion, etc.

For the road name, its characteristic weight is 1, and the equipment weights of vehicle A and vehicle B are both 1, so the verification result of the road name is: the current map data is correct, and the verification completion degree is 1*1*1+1*1 *1=2.

For road width, its feature weight is 1, the equipment weight of vehicle A is 1, and the equipment weight of vehicle B is 1. At this time, the verification result of the road width is: the current map data is correct, and the verification completion degree is 1*1*1+(-1)*1*1=0.

For road marker X, its characteristic weight is 0.5, and the equipment weight of vehicle A is 1. At this time, the verification result of the road width is: the current map data is correct, and the verification completion degree is 1*0.5*1=0.5.

The method embodiments of the present application are described in detail above with reference to FIGS. 2 to 9 , and the device embodiments of the present application are described in detail below with reference to FIGS. 10 to 16 . It should be understood that the device embodiments and the method embodiments correspond to each other, and are similar to For the description, refer to the method embodiment.

FIG. 10 is a schematic structural diagram of an apparatus for generating a high-precision map according to an embodiment of the present application. As shown in FIG. 10 , the apparatus 1000 may include:

An acquiring unit 1001 is configured to acquire map data of a target to be updated collected by a collection device, wherein the collection device includes a dedicated collection vehicle for map data and other movable devices with map data collection capability;

The determining unit 1002 is configured to determine the update result of the target to be updated according to the map data of the target to be updated collected by the acquisition device, the device weight of the acquisition device and the characteristic weight of the target to be updated, wherein the device weight of the acquisition device represents The weight of the map data of the target to be updated collected by the acquisition device, and the characteristic weight of the target to be updated is determined according to the update frequency and accuracy requirements of the target to be updated;

The generating unit 1003 is configured to generate an updated high-precision map according to the update result of the target to be updated.

Optionally, in some embodiments, the device weight of the collection device is determined according to the device capability of the collection device and the characteristics of the target to be updated collected by the collection device, wherein the characteristics of the target to be updated include the update frequency of the target to be updated. and precision requirements.

Optionally, in some embodiments, the update result of the target to be updated includes whether the map data of the target to be updated has changed and the update completion degree of the map data of the target to be updated.

Optionally, in some embodiments, the update completion degree of the map data of the target to be updated is the sum of the update results of the target to be updated by a plurality of collection devices, wherein the plurality of collection devices are the ones that collected the map data of the target to be updated. The acquisition device, the update result of the target to be updated by the acquisition device is the product of the device weight of the acquisition device, the characteristic weight of the target to be updated, and the update flag corresponding to the acquisition device, where the update flag corresponding to the acquisition device represents the data collected by the acquisition device. The map data of the target to be updated determines whether the map data of the target to be updated in the high-precision map needs to be updated.

Optionally, in some embodiments, the generating unit 1003 is further configured to:

When the update completion degree of the map data of the target to be updated reaches a preset value, the information of the target to be updated in the high-precision map is updated.

Optionally, in some embodiments, the apparatus 1000 further includes:

The sending unit is configured to send prompt information to the acquisition device according to the device capability required to collect the map data of the target to be updated, where the prompt information is used to prompt the device capability of the acquisition device to be used.

Optionally, in some embodiments, the obtaining unit 1001 is further configured to:

Get the device capability of the acquisition device.

The determining unit 1002 is further configured to: determine the target to be updated according to the device capability of the collecting device.

It should be noted that, the functions of the units in the apparatus 1000 in the embodiments of the present application may refer to the specific implementation manners of any of the embodiments in FIG. 2 to FIG. 3 in the foregoing method embodiments, which will not be repeated here. The apparatus 1000 can be, for example, a server, including but not limited to a computer and the like.

FIG. 11 is a schematic structural diagram of another apparatus for generating a high-precision map according to an embodiment of the present application. The apparatus 1100 is set on a movable device with map data collection capability, and the collection device is not a dedicated collection vehicle for map data. , as shown in FIG. 11 , the apparatus 1100 may include:

The collection unit 1101 is configured to collect map data of the target to be updated.

The sending unit 1102 is configured to report the map data of the target to be updated to the high-precision map platform.

Optionally, in some embodiments, the apparatus 1100 further includes:

The receiving unit is configured to receive prompt information sent by the high-precision map platform, where the prompt information is used to prompt the device capability of the movable device used to collect the map data of the target to be updated.

Optionally, in some embodiments, the sending unit 1102 is further configured to:

Report the device capability of the removable device to the high-resolution map platform.

It should be noted that, the functions of the units in the apparatus 1100 in the embodiments of the present application may refer to the specific implementation manners of any of the embodiments in FIG. 4 to FIG. 5 in the foregoing method embodiments, which will not be repeated here. The apparatus 1100 may be, for example, a vehicle-mounted terminal or a handheld terminal.

FIG. 12 is a schematic structural diagram of another apparatus for generating a high-precision map according to an embodiment of the present application. As shown in FIG. 12 , the apparatus 1200 may include:

The acquiring unit 1201 is configured to acquire map data of the target to be verified collected by a collection device, wherein the collection device includes a dedicated map data collection vehicle and other movable devices with map data collection capability.

The determining unit 1202 is configured to determine the verification result of the target to be verified according to the map data of the target to be verified collected by the acquisition device, the device weight of the acquisition device and the characteristic weight of the target to be verified, wherein the device weight of the acquisition device represents The weight of the map data of the target to be verified collected by the acquisition device, and the characteristic weight of the target to be verified is determined according to the update frequency and accuracy requirements of the target to be verified.

The generating unit 1203 is configured to generate an updated high-precision map according to the verification result of the target to be verified.

Optionally, in some embodiments, the device weight of the collection device is determined according to the device capability of the collection device and the characteristics of the target to be verified collected by the vehicle, wherein the characteristics of the target to be updated include the update frequency of the target to be updated and precision requirements.

Optionally, in some embodiments, the verification result of the target to be verified includes whether the map data of the target to be verified is correct and the degree of completion of verification of the map data of the target to be verified.

Optionally, in some embodiments, the verification completion degree of the map data of the target to be verified is the sum of the verification results of the target to be verified by multiple collection devices, wherein the multiple collection devices are the collection of map data of the target to be verified. The verification result of the target to be verified by the acquisition device is the product of the device weight of the acquisition device, the characteristic weight of the target to be verified, and the verification flag corresponding to the acquisition device, where the verification flag corresponding to the acquisition device represents the The map data of the verification target determines whether the map data of the target to be verified in the high-precision map is correct.

Optionally, in some embodiments, the generating unit 1203 is further configured to:

When the verification completion degree of the map data of the target to be verified reaches a preset value, an updated high-precision map is generated.

Optionally, in some embodiments, the obtaining unit 1201 is further configured to: obtain the device capability of the collecting device.

Optionally, in some embodiments, the determining unit 1202 is further configured to: determine the target to be verified according to the device capability of the collecting device.

It should be noted that, the functions of the units in the apparatus 1200 in the embodiments of the present application may refer to the specific implementation manners of any of the embodiments in FIG. 6 to FIG. 7 in the foregoing method embodiments, which will not be repeated here. The apparatus 1200 may be, for example, a server, including but not limited to a computer and the like.

FIG. 13 is a schematic structural diagram of another apparatus for generating a high-precision map according to an embodiment of the present application. The apparatus 1300 is set on a movable device with map data collection capability, and the movable device is not dedicated for map data collection. Vehicle, as shown in FIG. 13, the apparatus 1300 may include:

Obtaining unit 1301, configured to obtain candidate verification targets issued by the high-precision map platform;

a determining unit 1302, configured to determine a target to be verified among the candidate verification targets;

The collection unit 1303 is used to collect the map data of the target to be verified;

The sending unit 1304 is configured to report the map data of the target to be verified to the high-precision map platform.

Optionally, in some embodiments, the sending unit 1304 is further configured to:

It should be noted that, the functions of the units in the apparatus 1100 in the embodiments of the present application may refer to the specific implementation manners of any of the embodiments in FIG. 8 to FIG. 9 in the foregoing method embodiments, which will not be repeated here. The apparatus 1300 may be, for example, a vehicle-mounted terminal or a handheld terminal.

FIG. 14 is another schematic structural diagram of an apparatus for generating a high-precision map provided by an embodiment of the present application. As shown in FIG. The communication interface 1401 , the memory 1402 , and the processor 1403 communicate with each other through the communication bus 1404 . The communication interface 1401 is used for the apparatus 1400 to perform data communication with external devices. The memory 1402 can be used to store software programs and modules, and the processor 1403 executes the software programs and modules stored in the memory 1402, such as software programs for corresponding operations in the method embodiments shown in FIG. 2 to FIG. 3, or FIG. 6 to FIG. 7 . Software routines for corresponding operations in the illustrated method embodiments.

As an embodiment, the processor 1403 may call software programs and modules stored in the memory 1402 to perform the following operations: acquire map data of the target to be updated collected by a collection device, wherein the collection device includes a dedicated collection vehicle for map data and other Movable devices with map data collection capabilities;

According to the map data of the target to be updated collected by the acquisition device, the device weight of the acquisition device and the characteristic weight of the target to be updated, the update result of the target to be updated is determined, wherein the device weight of the acquisition device represents the data to be updated collected by the acquisition device The weight of the map data of the target, the characteristic weight of the target to be updated is determined according to the update frequency and accuracy requirements of the target to be updated;

According to the update result of the target to be updated, an updated high-precision map is generated.

As another embodiment, the processor 1403 can call software programs and modules stored in the memory 1402 to perform the following operations:

Obtain the map data of the target to be verified collected by the collection equipment, wherein the collection equipment includes a special collection vehicle for map data and other movable equipment with a map data collection function;

The verification result of the target to be verified is determined according to the map data of the target to be verified collected by the acquisition device, the device weight of the acquisition device and the characteristic weight of the target to be verified. The weight of the map data of the target, and the characteristic weight of the target to be verified is determined according to the update frequency and accuracy requirements of the target to be verified;

According to the verification result of the target to be verified, an updated high-precision map is generated.

FIG. 15 is another schematic structural diagram of an apparatus for generating a high-precision map provided by an embodiment of the present application. As shown in FIG. The communication interface 1501 , the memory 1502 , and the processor 1503 communicate with each other through the communication bus 1504 . The communication interface 1501 is used for the apparatus 1500 to perform data communication with external devices. The memory 1502 can be used to store software programs and modules, and the processor 1503 executes the software programs and modules stored in the memory 1502, such as software programs for corresponding operations in the method embodiments shown in FIG. 4 to FIG. 5, or FIG. 8 to FIG. 9. Software routines for corresponding operations in the illustrated method embodiments.

As an embodiment, the processor 1503 can call software programs and modules stored in the memory 1502, and control the communication interface 1501 to perform the following operations: collect map data of the target to be updated; report the map data of the target to be updated to the high-precision map platform .

As another embodiment, the processor 1503 can call the software programs and modules stored in the memory 1502, and control the communication interface 1501 to perform the following operations: acquire candidate verification targets issued by the high-precision map platform, and the acquisition device is a map data acquisition device. Capable mobile equipment, and the collection equipment is not a dedicated collection vehicle for map data; determine the target to be verified among the candidate verification targets; collect the map data of the target to be verified; report the map data of the target to be verified to the high-precision map platform.

FIG. 16 is a schematic structural diagram of a system 1600 for generating a high-precision map provided by an embodiment of the present application. Referring to FIG. 16 , the system 1600 may include: a device 1610 and a device 1620 for generating a high-precision map, where the device 1610 may be the one shown in FIG. 10 . The apparatus 1000 in FIG. 12 , or the apparatus 1200 in FIG. 12 or the apparatus 1400 in FIG. 14 , the apparatus 1620 may be the apparatus 1100 in FIG. 11 , or the apparatus 1300 in FIG. 13 or the apparatus 1500 in FIG. 15 . For specific implementation, reference may be made to the relevant descriptions in the foregoing, which will not be repeated here.

Embodiments of the present application further provide a computer-readable storage medium for storing a computer program. The computer-readable storage medium can be applied to a computer device, and the computer program enables the computer device to execute the corresponding process in the method for generating a high-precision map in the embodiment of the present application, which is not repeated here for brevity.

It should be understood that the processor in this embodiment of the present application may be an integrated circuit chip, which has a signal processing capability. In the implementation process, each step of the above method embodiments may be completed by a hardware integrated logic circuit in a processor or an instruction in the form of software. The above-mentioned processor can be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA) or other available Programming logic devices, discrete gate or transistor logic devices, discrete hardware components. The methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other storage media mature in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware.

It can be understood that the memory in this embodiment of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. Wherein, the non-volatile memory may be a read-only memory (Read-Only Memory, ROM), a programmable read-only memory (Programmable ROM, PROM), an erasable programmable read-only memory (Erasable PROM, EPROM), an electrically programmable read-only memory (Erasable PROM, EPROM). Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory. Volatile memory may be Random Access Memory (RAM), which acts as an external cache. By way of illustration and not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (Synchlink DRAM, SLDRAM) ) and direct memory bus random access memory (Direct Rambus RAM, DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but not be limited to, these and any other suitable types of memory.

It should be understood that the above memory is an example but not a limitative description, for example, the memory in the embodiment of the present application may also be a static random access memory (static RAM, SRAM), a dynamic random access memory (dynamic RAM, DRAM), Synchronous dynamic random access memory (synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (double data rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM), synchronous connection Dynamic random access memory (synch link DRAM, SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM) and so on. That is, the memory in the embodiments of the present application is intended to include but not limited to these and any other suitable types of memory.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk and other mediums that can store program codes.

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited to this. should be covered within the scope of protection of this application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

A method of generating a high-precision map, the method comprising:

Acquiring map data of the target to be updated collected by a collection device, wherein the collection device includes a dedicated map data collection vehicle and other movable devices with map data collection capabilities;

According to the map data of the target to be updated collected by the collection device, the device weight of the collection device and the characteristic weight of the target to be updated, the update result of the target to be updated is determined, wherein the collection The device weight of the device represents the weight of the map data of the to-be-updated target collected by the collection device, and the characteristic weight of the to-be-updated target is determined according to the update frequency and accuracy requirements of the to-be-updated target;

According to the update result of the target to be updated, an updated high-precision map is generated.
The method according to claim 1, wherein the device weight of the collection device is determined according to the device capability of the collection device and the characteristics of the target to be updated, wherein the characteristics of the target to be updated include all Describe the update frequency and accuracy requirements of the target to be updated.
The method according to claim 1, wherein the update result of the target to be updated includes whether the map data of the target to be updated has changed and the update completion degree of the map data of the target to be updated.
The method according to claim 3, wherein the update completion degree of the map data of the target to be updated is the sum of the update results of the target to be updated by a plurality of collection devices, wherein the plurality of collection devices are collected A device for collecting map data of the target to be updated, the update result of the target to be updated by the collecting device is the device weight of the collecting device, the characteristic weight of the target to be updated and the corresponding value of the collecting device The product of the update flags of , where the update flag corresponding to the collection device indicates whether the map data of the target to be updated in the high-precision map needs to be determined according to the map data of the target to be updated collected by the collection device renew.
The method of any one of claims 1-4, wherein the method further comprises:

According to the device capabilities required to collect the map data of the target to be updated, prompt information is sent to the acquisition device, where the prompt information is used to prompt the device capabilities of the acquisition device to be used.
The method of any one of claims 1-4, wherein the method further comprises:

The device capability of the collection device reported by the collection device is received.
A method of generating a high-precision map, the method comprising:

Obtaining map data of the target to be verified collected by a collection device, wherein the collection device includes a dedicated map data collection vehicle and other movable devices with map data collection function;

The verification result of the target to be verified is determined according to the map data of the target to be verified collected by the collection device, the device weight of the collection device and the characteristic weight of the target to be verified, wherein the collection The device weight of the device represents the weight of the map data of the to-be-verified target collected by the collection device, and the characteristic weight of the to-be-verified target is determined according to the update frequency and accuracy requirements of the to-be-verified target;

According to the verification result of the target to be verified, an updated high-precision map is generated.
The method according to claim 7, wherein the device weight of the collection device is determined according to the device capability of the collection device and the characteristics of the target to be verified, wherein the characteristics of the target to be updated include all the characteristics of the target to be updated. Describe the update frequency and accuracy requirements of the target to be updated.
The method according to claim 7, wherein the verification result of the object to be verified includes whether the map data of the object to be verified is correct and the degree of completion of verification of the map data of the object to be verified.
The method according to claim 9, wherein the verification completion degree of the map data of the target to be verified is the sum of the verification results of the target to be verified by a plurality of collection devices, wherein the plurality of collection devices are collected A device for collecting map data of the target to be verified, and the verification result of the target to be verified by the collecting device is the device weight of the collecting device, the characteristic weight of the target to be verified and the corresponding value of the collecting device The product of the verification marks, wherein the verification mark corresponding to the collection device indicates whether the map data of the target to be verified in the high-precision map is correct according to the map data of the target to be verified collected by the collection device. .
The method according to any one of claims 7-10, wherein the method further comprises: receiving the device capability of the collection device reported by the collection device.
A device for generating a high-precision map, the device comprising:

an acquisition unit, configured to acquire map data of the target to be updated collected by a collection device, wherein the collection device includes a dedicated map data collection vehicle and other movable devices with map data collection capabilities;

a determining unit, configured to determine the update result of the target to be updated according to the map data of the target to be updated collected by the acquisition device, the device weight of the acquisition device and the characteristic weight of the target to be updated, The device weight of the collection device represents the weight of the map data of the target to be updated collected by the collection device, and the characteristic weight of the target to be updated is determined according to the update frequency and accuracy requirements of the target to be updated ;

A generating unit, configured to generate an updated high-precision map according to the update result of the target to be updated.
A device for generating a high-precision map, the device comprising:

an acquisition unit, configured to acquire map data of the target to be verified collected by a collection device, wherein the collection device includes a dedicated map data collection vehicle and other movable devices with map data collection capabilities;

a determining unit, configured to determine the verification result of the target to be verified according to the map data of the target to be verified collected by the acquisition device, the device weight of the acquisition device and the characteristic weight of the target to be verified, The device weight of the collection device represents the weight of the map data of the target to be verified collected by the collection device, and the characteristic weight of the target to be verified is determined according to the update frequency and accuracy requirements of the target to be verified ;

The generating unit is configured to generate an updated high-precision map according to the verification result of the target to be verified.
An apparatus for generating a high-precision map, the apparatus comprising: a communication bus, a processor, a communication interface and a memory, the processor, the communication interface and the memory are connected to each other through the communication bus, wherein the a memory for storing program code, the processor being configured to invoke the program code to perform a method as claimed in any one of claims 1 to 6, or as claimed in any one of claims 7 to 11 method.
A computer-readable storage medium for storing a computer program that causes a computer to perform the method as claimed in any one of claims 1 to 6, or the method as claimed in any one of claims 7 to 11 method.
A computer program product comprising computer instructions stored in a computer-readable storage medium, from which a processor reads and executes the computer instructions to implement such as The method of any one of claims 1 to 6, or the method of any one of claims 7 to 11.