CN114490910A - Map generation method and device, electronic equipment and storage medium - Google Patents
Map generation method and device, electronic equipment and storage medium Download PDFInfo
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- CN114490910A CN114490910A CN202210096016.1A CN202210096016A CN114490910A CN 114490910 A CN114490910 A CN 114490910A CN 202210096016 A CN202210096016 A CN 202210096016A CN 114490910 A CN114490910 A CN 114490910A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/20—Drawing from basic elements, e.g. lines or circles
- G06T11/206—Drawing of charts or graphs
Abstract
The invention discloses a map generation method, a map generation device, electronic equipment and a storage medium, wherein the map generation method is applied to a mapping platform and comprises the following steps: acquiring vehicle-end acquisition data acquired by a target automatic driving vehicle; according to the target hardware equipment information of the target automatic driving vehicle, carrying out standardization processing on the vehicle end collected data to obtain standardized collected data which can be identified by a drawing platform; and generating an operation map according to the standardized acquisition data. By the technical scheme, the problem of high cost caused by the fact that data acquisition can only be carried out through a vehicle exclusive for the mapping platform in the prior art can be solved, the mapping platform and the acquired vehicle are decoupled, the data acquisition cost is reduced, the timeliness of map generation is improved, development of automatic driving demonstration operation work is supported, and a new thought is provided for generation of high-precision maps.
Description
Technical Field
The embodiment of the invention relates to the technical field of automatic driving, in particular to a map generation method and device, electronic equipment and a storage medium.
Background
With the automation and intellectualization of automobiles, the automatic driving technology is continuously advanced, and host factories and science and technology companies launch the automatic driving vehicles of the city scene level L4.
It is common to operate demonstration in a small range in a demonstration area, and the road distance is basically from several kilometers to tens of kilometers, and generally not more than tens of kilometers. Because map data need customize and develop, can only rely on the exclusive vehicle of drawing platform to carry out data acquisition, and high-accuracy map timeliness is stronger, and road environment changes often, and the qualification map merchant is uninteresting such small-range, costly drawing task, can't generate high-accuracy operation map, leads to the automatic driving operation work to be unable to expand, needs urgent solution.
Disclosure of Invention
The invention provides a map generation method, a map generation device, electronic equipment and a storage medium, which can generate an operation map for a small-range demonstration area so as to support the development of automatic driving operation work.
In a first aspect, an embodiment of the present invention provides a method for generating a map, which is applied to a mapping platform, and the method includes:
acquiring vehicle-end acquisition data acquired by a target automatic driving vehicle;
according to the target hardware equipment information of the target automatic driving vehicle, carrying out standardization processing on the vehicle end collected data to obtain standardized collected data which can be identified by a drawing platform;
and generating an operation map according to the standardized acquisition data.
In a second aspect, an embodiment of the present invention further provides a map generation apparatus, which is applied to a mapping platform, where the apparatus includes:
the acquisition data acquisition module is used for acquiring vehicle-end acquisition data acquired by the target automatic driving vehicle;
the data standardization module is used for carrying out standardization processing on the vehicle end collected data according to the target hardware equipment information of the target automatic driving vehicle to obtain standardized collected data which can be identified by the drawing platform;
and the map generation module is used for generating an operation map according to the standardized acquisition data.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the map generation method according to any embodiment of the present invention.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the map generating method according to any embodiment of the present invention.
According to the map generation method and device, the electronic equipment and the storage medium, vehicle-end acquisition data acquired by the target automatic driving vehicle are acquired; according to the target hardware equipment information of the target automatic driving vehicle, carrying out standardization processing on the vehicle end collected data to obtain standardized collected data which can be identified by a drawing platform; according to the standardized collected data, an operation map is generated, the problem that in the prior art, data collection can only be carried out through a vehicle special for a drawing platform, so that the cost is high is solved, the drawing platform and the collected vehicle are decoupled, the data collection cost is reduced, the timeliness of map generation is improved, the development of automatic driving demonstration operation work is supported, and a new thought is provided for the generation of a high-precision map.
Drawings
FIG. 1 is a flowchart of a method for generating a map according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for generating a map according to a second embodiment of the present invention;
FIG. 3 is a flowchart of a map generation method according to a third embodiment of the present invention;
fig. 4 is a block diagram of a map generation apparatus according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a map generation method according to an embodiment of the present invention, and this embodiment is applicable to a map generation situation in which a mapping platform generates a map according to vehicle-side collected data collected by an autonomous vehicle, and is particularly applicable to generation of a map for a small-range operation, for example, generation of a high-precision map for a small-range autonomous driving demonstration operation city market view in an autonomous driving demonstration area. The method can be executed by a map generation device provided by the embodiment of the invention, and the device can be realized in a software and/or hardware manner and can be integrated on an electronic device.
Specifically, as shown in fig. 1, the method for generating a map provided in the embodiment of the present invention may include the following steps:
and S110, acquiring vehicle-end acquisition data acquired by the target automatic driving vehicle.
Wherein the target autonomous vehicle is an autonomous vehicle for collecting raw data from a vehicle end. In this embodiment, the target driving vehicle may be an L4 autonomous driving vehicle, and raw data collection is performed through an L4 autonomous driving vehicle and a sensing device thereon, specifically, the collection device may include a laser radar, a forward-looking camera, and a combined inertial navigation system.
Furthermore, the acquisition software in the target driving vehicle can be developed by a mapping platform side and deployed in an industrial personal computer or a controller of the automatic driving vehicle. The acquisition software is decoupled from the real vehicle and can be applied to other vehicle types after being adapted and calibrated by the sensor. The adaptation process of the acquisition software comprises drive installation, sensor data synchronization (hard synchronization is considered preferentially), parameter calibration and the like. In this way, data acquisition can be carried out on any one or the automatic driving vehicles with different system schemes through the adaptation of acquisition software. The vehicle host factory can change the acquisition software interface according to the scheme adaptation of the actual automatic driving vehicle so as to realize the purpose that any trolley can acquire data.
In the running process of the target automatic driving vehicle, point cloud data are collected through a laser radar, image data are collected through a forward-looking camera, track position data are collected through combined inertial navigation, and vehicle-end collected data including the point cloud data, the image data and the track position data are packaged, encrypted and stored. The method has no special requirements on the flows of data acquisition, data storage, data delivery and the like, and can be carried out according to the relevant specified requirements.
Preferably, the data transmission module on the target automatic driving vehicle can be used for uploading the vehicle-end collected data to a server of the mapping platform, and the mapping platform acquires the vehicle-end collected data collected by the target automatic driving vehicle and is used for subsequently generating the operation map.
And S120, according to the target hardware equipment information of the target automatic driving vehicle, carrying out standardized processing on the vehicle end collected data to obtain standardized collected data which can be identified by the drawing platform.
The target hardware equipment information is hardware information of acquisition equipment of the target automatic driving vehicle, such as sensor parameters, driving parameters and the like. The specifications of the collected raw data may also vary depending on the parameters of the collection equipment.
The format of data collected by a vehicle end is not matched with the standard format of a mapping platform, for example, if a data packet collected in an automatic driving Ubuntu ROS system is a rossbag generally and contains various self-defined sensor messages (msg files), and the msg files in the rossbag cannot be directly identified in the high-precision map making process, analysis and format conversion are required.
Before the vehicle-end collected data enter a preprocessing link of the drawing platform, the vehicle-end collected data are subjected to standardized processing through a preprocessing middleware. The core of the preprocessing middleware is the analysis and conversion of data acquired by the vehicle end, the format conversion middleware of different sensor schemes and the mapping platform is linked, and the data acquired by the different sensor schemes is analyzed into standard specifications which can be identified and processed in the subsequent high-precision mapping link, namely the specifications available for the mapping platform.
In this embodiment, the preprocessing middleware associated with the target hardware device information may be determined according to the target hardware device information of the target autonomous vehicle; through the preprocessing middleware, the vehicle-end collected data is converted into the collected data in a standard format, namely the standardized collected data, and the data is used for subsequent drawing.
For example, when parsing is performed by preprocessing middleware, the point cloud can be parsed into las or pcd format, the image can be parsed into png format, and the track can be parsed into pos text.
And S130, generating an operation map according to the standardized acquisition data.
The operation map is a high-precision map for the small-range operation demonstration of the automatic driving vehicle in the demonstration area.
After the operation map is generated according to the standardized collected data, the drawing platform can deliver the operation map to a host factory, and the host factory develops an interface API based on the customized data specification and is applied to automatic driving demonstration operation vehicle models.
According to the technical scheme of the embodiment, vehicle end acquisition data acquired by a target automatic driving vehicle is acquired; according to the target hardware equipment information of the target automatic driving vehicle, carrying out standardized processing on vehicle end collected data to obtain standardized collected data which can be identified by a drawing platform; according to the standardized data collection, the operation map is generated, the problem that in the prior art, data collection can only be carried out through exclusive vehicles of the mapping platform, so that the cost is high is solved, the mapping platform and the collected vehicles are decoupled, the data collection cost is reduced, the timeliness of map generation is improved, the development of automatic driving demonstration operation work is supported, and a new thought is provided for generating the high-precision map.
Example two
Fig. 2 is a flowchart of a map generation method according to a second embodiment of the present invention, which is further optimized based on the second embodiment, and provides a specific description of how to standardize vehicle-side collected data, where the standardized collected data that can be recognized by the mapping platform is optimized to determine a target middleware associated with target hardware device information according to the target hardware device information of the target autonomous driving vehicle and an association relationship between the candidate device information and the candidate middleware; and calling a target middleware to carry out standardized processing on the vehicle-end collected data to obtain standardized collected data which can be identified by the drawing platform.
Specifically, as shown in fig. 2, the method includes:
and S210, acquiring vehicle-end acquisition data acquired by the target automatic driving vehicle.
S220, determining the target middleware associated with the target hardware equipment information according to the target hardware equipment information of the target automatic driving vehicle and the association relation between the candidate equipment information and the candidate middleware.
It will be appreciated that the parameters of the acquisition equipment vary, as will the specifications of the raw data acquired. In order to unify the format of the data collected by the vehicle end and facilitate subsequent charting, the target middleware associated with the target hardware equipment information can be determined according to the target hardware equipment information of the target automatic driving vehicle and the association relationship between the candidate equipment information and the candidate middleware. And the target middleware is used for converting vehicle-end acquired data acquired by the target automatic driving vehicle into standard specifications which can be identified and processed in a subsequent high-precision map making link.
The association relationship between the candidate device information and the candidate middleware may be preset. The data format collected by the candidate equipment can be determined according to the candidate equipment information, and the data collected by the candidate equipment can be converted into a standard specification which can be identified and processed in a subsequent high-precision map making link through the middleware associated with the candidate equipment information.
And S230, calling a target middleware to carry out standardized processing on the vehicle-end collected data to obtain standardized collected data which can be identified by the drawing platform.
After the target middleware associated with the target hardware equipment information is determined, the target middleware can be called to carry out standardized processing on the vehicle-end acquired data. The standardized processing can be understood as resolving data collected by different sensor schemes into standard specifications which can be identified and processed in the subsequent high-precision map making link, namely the specifications available for the mapping platform.
And S240, generating an operation map according to the standardized acquisition data.
According to the technical scheme, specific situation introduction of standardized processing of vehicle-end collected data is provided, the target middleware associated with the target hardware equipment information is determined through the target hardware equipment information of the target automatic driving vehicle and the association relation between the candidate equipment information and the candidate middleware, the target middleware is called to carry out standardized processing on the vehicle-end collected data, and standardized collected data which can be identified by a mapping platform is obtained.
EXAMPLE III
Fig. 3 is a flowchart of a map generation method provided in a third embodiment of the present invention, which is further optimized based on the above embodiment, and provides a specific description of how to update a map.
Specifically, as shown in fig. 3, the method includes:
and S310, acquiring perception difference data acquired by the target automatic driving vehicle under the condition that the initial operation map exists.
The initial operation map is also a map drawn by the drawing platform, and the drawing platform generates the operation map according to the standardized collected data and sends the operation map to the target automatic driving vehicle. The perception difference data is determined by the target automatic driving vehicle according to the original acquisition data and the initial operation map of the target automatic driving vehicle, and is not determined by the mapping platform, but can be determined off-line.
Preferably, the perceptual difference data is determined by the target autonomous vehicle in particular according to the following: identifying the original collected data through a deep learning algorithm to obtain a classification identification result; matching the classification recognition result with an initial operation map, and marking the part which cannot be matched as a difference point; and acquiring the position coordinates of the difference points, and generating perception difference data including the position coordinates of the difference points.
The target automatic driving vehicle carries out recognition detection on the acquired image data through a deep learning algorithm, and specifically comprises image classification segmentation and image recognition modeling. The main elements identified include: lane lines, arrows, bars, tiles, ground, curbs, and the like. After the recognition detection is performed, vectorization modeling may be performed on the recognized object.
Furthermore, the recognition output result can be matched with the existing vector map in a semantic matching mode, and updating detection is carried out. In the matching process, the matching optimal solution is calculated, and the parts which cannot be matched are marked to obtain difference points. Preferably, the positions of the difference points are acquired, the positions of the difference points are recorded, and the category elements of the difference points are recorded in a correlated manner to serve as the perception difference data.
After the target automatic driving vehicle determines the perception difference data, the perception difference data are uploaded to the drawing platform through the vehicle-mounted data uploading module, so that the drawing platform can update the operation map according to the perception difference data.
And S320, carrying out standardization processing on the perception difference data according to the target hardware equipment information of the target automatic driving vehicle to obtain standardized difference data which can be identified by the drawing platform.
Normalizing the perceptual difference data may include: analysis of the Rosbag data, format conversion, data settlement, data de-noising and cleaning, data clipping and the like.
And S330, updating the initial operation map by adopting the perception difference data of the target automatic driving vehicle.
The essence of updating the initial operation map is data storage updating, namely, adding, deleting and modifying the existing data. Preferably, the difference points can be determined according to the perception difference data, the original updated difference point part in the initial operation map is marked and deleted, the new difference points are embedded into the initial operation map according to the distance and the position, and then the initial operation map is updated.
According to the technical scheme, the initial operation map is updated through the perception difference data of the target automatic driving vehicle under the condition that the initial operation map exists, and the effect of improving the timeliness of map generation is achieved.
Example four
Fig. 4 is a schematic structural diagram of a map generation apparatus according to a fourth embodiment of the present invention, which is adapted to execute the map generation method according to the fourth embodiment of the present invention, and can generate an operation map for a small-scale demonstration area to support development of automatic driving operation work. As shown in fig. 4, the apparatus includes an acquisition data acquisition module 410, a data normalization module 420, and a map generation module 430.
The acquired data acquiring module 410 is used for acquiring vehicle-end acquired data acquired by the target automatic driving vehicle;
the data standardization module 420 is used for carrying out standardization processing on vehicle-end collected data according to target hardware equipment information of a target automatic driving vehicle to obtain standardized collected data which can be identified by a drawing platform;
and the map generation module 430 is configured to generate an operation map according to the standardized collected data.
According to the technical scheme of the embodiment, vehicle end acquisition data acquired by a target automatic driving vehicle is acquired; according to the target hardware equipment information of the target automatic driving vehicle, carrying out standardized processing on vehicle end collected data to obtain standardized collected data which can be identified by a drawing platform; according to the standardized data collection, the operation map is generated, the problem that in the prior art, data collection can only be carried out through exclusive vehicles of the mapping platform, so that the cost is high is solved, the mapping platform and the collected vehicles are decoupled, the data collection cost is reduced, the timeliness of map generation is improved, the development of automatic driving demonstration operation work is supported, and a new thought is provided for generating the high-precision map.
Preferably, the data normalization module 420 specifically includes: a middleware determination unit and a data normalization unit. Wherein the content of the first and second substances,
the middleware determining unit is used for determining target middleware associated with the target hardware equipment information according to the target hardware equipment information of the target automatic driving vehicle and the association relation between the candidate equipment information and the candidate middleware;
and the data standardization unit is used for calling the target middleware to carry out standardization processing on the vehicle-end collected data to obtain standardized collected data which can be identified by the drawing platform.
Preferably, under the condition that the initial operation map exists, the data collected by the vehicle end is perception difference data; the perception difference data is determined according to the original collected data of the target autonomous vehicle and the initial operation map.
Preferably, the apparatus further comprises: the difference data determining module is used for identifying the original collected data through a deep learning algorithm to obtain a classification identification result; matching the classification recognition result with an initial operation map, and marking the part which cannot be matched as a difference point; and acquiring the position coordinates of the difference points, and generating perception difference data including the position coordinates of the difference points.
Preferably, the map generating module 430 is further specifically configured to update the initial operation map by using the perceived difference data of the target autonomous vehicle.
The map generation device provided by the embodiment of the invention can execute the map generation method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
Fig. 5 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention. FIG. 5 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 5 is only an example and should not bring any limitation to the function and the scope of use of the embodiment of the present invention.
As shown in FIG. 5, electronic device 12 is embodied in the form of a general purpose computing device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and/or any device (e.g., network card, modem, etc.) that enables the electronic device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by running a program stored in the system memory 28, for example, implementing a map generation method provided by an embodiment of the present invention.
EXAMPLE six
The sixth embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the map generating method provided in any embodiment of the present invention.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A map generation method is applied to a mapping platform, and comprises the following steps:
acquiring vehicle-end acquisition data acquired by a target automatic driving vehicle;
according to the target hardware equipment information of the target automatic driving vehicle, carrying out standardization processing on the vehicle end collected data to obtain standardized collected data which can be identified by a drawing platform;
and generating an operation map according to the standardized acquisition data.
2. The method of claim 1, wherein the step of standardizing the vehicle-end collected data according to the target hardware equipment information of the target automatic driving vehicle to obtain standardized collected data recognizable by a mapping platform comprises the following steps:
determining a target middleware associated with the target hardware equipment information according to the target hardware equipment information of the target automatic driving vehicle and the association relationship between the candidate equipment information and the candidate middleware;
and calling the target middleware to carry out standardized processing on the vehicle end collected data to obtain standardized collected data which can be identified by a drawing platform.
3. The method of claim 1, wherein the vehicle-side collected data is perceived difference data in the presence of an initial operational map; the perception difference data is determined according to the original collected data of the target automatic driving vehicle and an initial operation map.
4. The method according to claim 3, wherein the perceptual difference data is determined in particular according to:
identifying the original collected data through a deep learning algorithm to obtain a classification identification result;
matching the classification recognition result with the initial operation map, and marking the part which cannot be matched as a difference point;
and acquiring the position coordinates of the difference points, and generating perception difference data including the position coordinates of the difference points.
5. The method of claim 3, wherein generating an operational map from the standardized acquisition data comprises:
and updating the initial operation map by adopting the perception difference data of the target automatic driving vehicle.
6. A map generation device is applied to a mapping platform, and comprises:
the acquisition data acquisition module is used for acquiring vehicle-end acquisition data acquired by the target automatic driving vehicle;
the data standardization module is used for carrying out standardization processing on the vehicle end collected data according to the target hardware equipment information of the target automatic driving vehicle to obtain standardized collected data which can be identified by the drawing platform;
and the map generation module is used for generating an operation map according to the standardized acquisition data.
7. The apparatus of claim 6, wherein the data normalization module comprises:
the middleware determining unit is used for determining target middleware associated with the target hardware equipment information according to the target hardware equipment information of the target automatic driving vehicle and the association relation between the candidate equipment information and the candidate middleware;
and the data standardization unit is used for calling the target middleware to carry out standardization processing on the vehicle end collected data to obtain standardized collected data which can be identified by the drawing platform.
8. The apparatus of claim 6, wherein the vehicle-side collected data is perceived difference data in the presence of an initial operational map; the perception difference data is determined according to the original collected data of the target automatic driving vehicle and an initial operation map.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method of generating a map as claimed in any one of claims 1-5.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method of generating a map according to any one of claims 1 to 5.
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| CN202210096016.1A CN114490910A (en) | 2022-01-26 | 2022-01-26 | Map generation method and device, electronic equipment and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115002196A (en) * | 2022-05-25 | 2022-09-02 | 国汽智图(北京)科技有限公司 | Data processing method and device and vehicle-end acquisition equipment |
| CN115793993A (en) * | 2023-01-28 | 2023-03-14 | 禾多科技（北京）有限公司 | Data processing method and device, storage medium and electronic device |
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2022
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115002196A (en) * | 2022-05-25 | 2022-09-02 | 国汽智图(北京)科技有限公司 | Data processing method and device and vehicle-end acquisition equipment |
| CN115002196B (en) * | 2022-05-25 | 2024-01-26 | 国汽智图(北京)科技有限公司 | Data processing method and device and vehicle end acquisition equipment |
| CN115793993A (en) * | 2023-01-28 | 2023-03-14 | 禾多科技（北京）有限公司 | Data processing method and device, storage medium and electronic device |
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