CN117804473A - Map data acquisition method, apparatus, device and computer readable storage medium - Google Patents
Map data acquisition method, apparatus, device and computer readable storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
- G01C21/32—Structuring or formatting of map data
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
- G01C21/3804—Creation or updating of map data
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
- G01C21/3804—Creation or updating of map data
- G01C21/3807—Creation or updating of map data characterised by the type of data
- G01C21/3815—Road data
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Abstract
A map data acquisition method, apparatus, device and computer readable storage medium. The method comprises the following steps: determining the position of the vehicle according to a preset time interval; determining a target road segment based on the vehicle position for each determined vehicle position; acquiring first high-precision map data corresponding to a target road section; and updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area is used for being called by the intelligent driving module. According to the method and the device, the high-precision map data stored in the storage area are only relevant to the target road section corresponding to the vehicle position, so that the data size of the high-precision map data stored in the storage area is greatly reduced, and on the basis, when the intelligent driving module calls the high-precision map data, the data processing pressure is small, so that the consumption of computational resources is reduced.
Description
Technical Field
The present disclosure relates to the field of intelligent driving technologies, and in particular, to a map data acquisition method, apparatus, device, and computer readable storage medium.
Background
High-precision map data is an important data base on which intelligent driving algorithms depend when running. In the prior art, high-precision map data of all areas are stored in advance at a vehicle end so as to be called by an intelligent driving module.
Because the high-precision map data contains abundant information of various road elements, the data volume of the high-precision map data is large, so that the high-precision map data of all areas needs to occupy a large amount of storage space, and the intelligent driving module has higher calculation power resources when facing the high-precision map data with large data volume.
Disclosure of Invention
The application provides a map data acquisition method, a map data acquisition device, map data acquisition equipment and a map data acquisition computer readable storage medium, which can solve the technical problems that high-precision map data in an intelligent driving scene occupy a large amount of storage space and more computing power resources of an intelligent driving module are consumed in the prior art.
In a first aspect, an embodiment of the present application provides a map data acquisition method, including:
determining the position of the vehicle according to a preset time interval;
determining a target road segment based on the vehicle position for each determined vehicle position;
acquiring first high-precision map data corresponding to a target road section;
and updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area is used for being called by the intelligent driving module.
With reference to the first aspect, in one implementation manner, the target road segment is a road segment where a vehicle position is located.
With reference to the first aspect, in an implementation manner, the step of determining the target road section based on the vehicle position includes:
determining a first road section where the vehicle position is located;
detecting whether the distance between the vehicle position and the end point of the first road segment is smaller than a preset distance;
if the distance between the vehicle position and the end point of the first road section is smaller than the preset distance, the first road section and the road section adjacent to the first road section are taken as target road sections;
if the distance between the vehicle position and the end point of the first road section is not smaller than the preset distance, detecting whether a second road section with the distance between the starting point and the vehicle position smaller than the preset distance exists or not;
and if the second road section exists, taking the first road section and the second road section as target road sections.
With reference to the first aspect, in an implementation manner, the step of updating the second high-precision map data stored in the storage area based on the first high-precision map data includes:
deleting the second high-precision map data stored in the storage area;
the first high-precision map data is written into the storage area.
With reference to the first aspect, in an implementation manner, the step of updating the second high-precision map data stored in the storage area based on the first high-precision map data includes:
determining data to be newly added that exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area, and determining data to be deleted that exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data;
deleting the data to be deleted from the storage area, and writing the data to be newly added into the storage area.
With reference to the first aspect, in an implementation manner, the determining the data to be added that exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area, and the determining the data to be deleted that exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data includes:
comparing the road section identification information contained in the first high-precision map data with the road section identification information contained in the second high-precision map data stored in the storage area;
taking road section information corresponding to road section identification information which exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area as data to be newly added;
and taking the road section information corresponding to the road section identification information which exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data as the data to be deleted.
With reference to the first aspect, in an implementation manner, after the step of acquiring the first high-precision map data corresponding to the target road segment, the method further includes:
performing validity check on the first high-precision map data;
and if the validity check is passed, updating the second high-precision map data stored in the storage area based on the first high-precision map data.
In a second aspect, an embodiment of the present application provides a map data acquisition apparatus, including:
the position determining module is used for determining the position of the vehicle according to a preset time interval;
a road segment determining module for determining a target road segment based on the vehicle position for each determined vehicle position;
the acquisition module is used for acquiring first high-precision map data corresponding to the target road section;
and the updating module is used for updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area are used for being called by the intelligent driving module.
In a third aspect, an embodiment of the present application provides a map data acquisition apparatus, including a processor, a memory, and a map data acquisition program stored on the memory and executable by the processor, wherein the map data acquisition program, when executed by the processor, implements the steps of the map data acquisition method according to the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having a map data acquisition program stored thereon, wherein the map data acquisition program, when executed by a processor, implements the steps of the map data acquisition method according to the first aspect.
The beneficial effects that technical scheme that this application embodiment provided include:
in the embodiment of the application, the position of the vehicle is determined according to a preset time interval; determining a target road segment based on the vehicle position for each determined vehicle position; acquiring first high-precision map data corresponding to a target road section; and updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area is used for being called by the intelligent driving module. According to the method and the device, the high-precision map data stored in the storage area are only related to the target road section corresponding to the vehicle position, so that the data size of the high-precision map data stored in the storage area is greatly reduced, and on the basis, when the intelligent driving module calls the high-precision map data, the data processing pressure is small, so that the consumption of computational resources is reduced.
Drawings
FIG. 1 is a flowchart of an embodiment of a map data acquisition method according to the present application;
FIG. 2 is a schematic view of a driving scenario in an embodiment of a map data acquiring method according to the present application;
FIG. 3 is a schematic view of a driving scenario in another embodiment of a map data obtaining method according to the present application;
FIG. 4 is a schematic functional block diagram of an embodiment of a map data acquiring apparatus according to the present application;
fig. 5 is a schematic hardware configuration diagram of a map data acquiring apparatus according to an embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will clearly and completely describe the technical solution in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
In a first aspect, an embodiment of the present application provides a map data acquisition method.
In an embodiment, referring to fig. 1, fig. 1 is a flowchart illustrating an embodiment of a map data obtaining method according to the present application. As shown in fig. 1, the map data acquisition method includes:
step S10, determining the position of the vehicle according to a preset time interval;
in this embodiment, the preset time interval is set according to actual needs, for example, set to 3 minutes, 5 minutes, or 10 minutes, etc.
Taking 5 minutes as an example of the preset time interval, considering that the high-precision map data is used for supporting the intelligent driving function, the vehicle position is acquired when the intelligent driving function is started, and then, the vehicle position is acquired every 5 minutes.
Wherein each time the vehicle position is determined, the vehicle position may be determined by any one of a fusion positioning technique, a combined navigation positioning technique, or an RTK positioning technique.
Further, the vehicle position may be determined by a fusion positioning technique preferentially, and when the vehicle cannot be positioned by the fusion positioning technique, the vehicle position is determined by an integrated navigation positioning technique, and when the vehicle cannot be positioned by the integrated navigation positioning technique, the vehicle position is determined by an RTK positioning technique.
The method for determining the vehicle position is not limited to the above method.
Step S20 of determining a target link based on the vehicle position for each determined vehicle position;
in the present embodiment, referring to the above description, a plurality of vehicle positions, for example, respectively designated as vehicle position 1, vehicle position 2, vehicle position 3, and so on, are sequentially acquired as time increases.
It is readily understood that the road segments where the vehicle is located and the road segments around the vehicle may change as the vehicle position changes, and only these road segments are or may be traversed by the vehicle, so that road segments on which the vehicle is traversing and/or is likely to be traversed may be determined based on the vehicle position and targeted.
Further, in an embodiment, the target road segment is a road segment where the vehicle position is located.
In this embodiment, it is easy to understand that the high-precision map data is used for vehicle navigation, and the vehicle navigation needs to be performed based on the road section on which the vehicle is traveling, so that the road section where the vehicle position is located can be directly used as the target road section, thereby obtaining the first high-precision map data corresponding to the target road section.
Further, in an embodiment, the step of determining the target road section based on the vehicle position includes:
determining a first road section where the vehicle position is located;
detecting whether the distance between the vehicle position and the end point of the first road segment is smaller than a preset distance;
if the distance between the vehicle position and the end point of the first road section is smaller than the preset distance, the first road section and the road section adjacent to the first road section are taken as target road sections;
if the distance between the vehicle position and the end point of the first road section is not smaller than the preset distance, detecting whether a second road section with the distance between the starting point and the vehicle position smaller than the preset distance exists or not;
and if the second road section exists, taking the first road section and the second road section as target road sections.
In this embodiment, referring to fig. 2, fig. 2 is a schematic view of a driving scene in an embodiment of a map data obtaining method of the present application. As shown in fig. 2, the first road section where the vehicle position (point a in fig. 2) is located is road section 1, which is shown in solid line in fig. 2; if the distance between the vehicle position and the end point (point B in fig. 2) of the road segment 1 is smaller than the preset distance, the road segment 1 and the road segment adjacent to the road segment 1 (i.e., the road segment 2, shown by a broken line in fig. 2) are taken as target road segments.
It is easy to understand that there may be a plurality of road segments adjacent to the road segment 1, and the road segment 1 and all the road segments adjacent to the road segment 1 are targeted.
The preset distance is set according to actual needs, for example, 200m, 500m, etc., which is not limited herein.
According to the embodiment, the first road section where the vehicle is located and the road section adjacent to the first road section are taken as target road sections, so that first high-precision map data corresponding to the target road sections are obtained, and the high-precision map data required by the vehicles in the converging and converging scenes are obtained.
Referring to fig. 3, fig. 3 is a schematic view of a driving scene in another embodiment of the map data obtaining method of the present application. As shown in fig. 3, the first road section where the vehicle position (point a in fig. 3) is located is road section 1, which is shown in solid line in fig. 3; if the distance between the vehicle position and the end point (point B in fig. 3) of the road segment 1 is not less than the preset distance and the distance between the start point (point C in fig. 3) of the road segment 2 (shown by the dotted line in fig. 3) and the vehicle position is less than the preset distance, the road segment 1 and the road segment 2 are taken as target road segments.
It is easy to understand that there may be a plurality of road segments whose distance between the starting point and the vehicle position is less than the preset distance, and the road segment 1 and the road segments whose distances between all the starting points and the vehicle position are less than the preset distance are taken as the target road segments.
The preset distance is set according to actual needs, for example, 200m, 500m, etc., which is not limited herein.
According to the embodiment, the first road section and the second road section are used as target road sections, so that first high-precision map data corresponding to the target road sections are obtained, and high-precision map data required by the vehicle when the vehicle is shunted and the scene is collected are obtained.
Step S30, obtaining first high-precision map data corresponding to a target road section;
in the prior art, the high-precision map data used by the intelligent driving module is often high-precision map data corresponding to the whole area, and contains relevant information of hundreds of road sections in the whole area. In this embodiment, only the first high-precision map data corresponding to the target road section determined based on the vehicle position is acquired, and the data size is reduced to a greater extent than the high-precision map data corresponding to the entire area.
And step S40, updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area is used for being called by the intelligent driving module.
In this embodiment, step S10 and subsequent steps are started with the intelligent driving function being turned on, when the intelligent driving function is turned on, the storage area is emptied, and when step S40 is executed, the first high-precision map data 1 is directly written into the storage area because the second high-precision map data stored in the storage area is empty for the first high-precision map data 1 acquired based on the first determined vehicle position; when step S40 is executed with respect to the first high-precision map data 2 acquired for the second determined vehicle position, the first high-precision map data 1, which is the second high-precision map data stored in the storage area at this time, is updated based on the first high-precision map data 2, and so on.
The updating method may be to newly add the first high-precision map data 2 to the storage area, or replace the first high-precision map data 1 with the first high-precision map data 2. And particularly, selecting an updating mode according to actual needs.
Further, in an embodiment, step S40 includes:
step S401, deleting the second high-precision map data stored in the storage area;
step S402, writing the first high-precision map data into the storage area.
In this embodiment, the second high-precision map data stored in the storage area is updated in an alternative manner, specifically, the second high-precision map data stored in the storage area is deleted first, and then the first high-precision map data is written into the storage area.
Further, in an embodiment, step S40 includes:
step S403 of determining new data to be added that exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area, and determining data to be deleted that exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data;
step S404, deleting the data to be deleted from the storage area, and writing the data to be newly added into the storage area.
In this embodiment, assuming that the second high-precision map data is the high-precision map data corresponding to the road segments 1, 2 and 3, the first high-precision map data is the high-precision map data corresponding to the road segments 2, 3 and 4, the data to be newly added is the high-precision map data corresponding to the road segments 4, and the data to be deleted is the high-precision map data corresponding to the road segments 1. On this basis, it is only necessary to delete the high-precision map data corresponding to the link 1 from the storage area and write the high-precision map data corresponding to the link 4 into the storage area.
Further, in an embodiment, step S403 includes:
comparing the road section identification information contained in the first high-precision map data with the road section identification information contained in the second high-precision map data stored in the storage area;
taking road section information corresponding to road section identification information which exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area as data to be newly added;
and taking the road section information corresponding to the road section identification information which exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data as the data to be deleted.
In this embodiment, the high-precision map data includes road section information and road section identification information corresponding to the road section, and different road sections correspond to different road section identification information.
By comparing the road segment identification information contained in the first high-precision map data with the road segment identification information contained in the second high-precision map data, it is possible to determine which road segment information of the road segments exists in the first high-precision map data but does not exist in the second high-precision map data and which road segment information of the road segments exists in the second high-precision map data but does not exist in the first high-precision map data, thereby determining the data to be newly added and the data to be deleted.
Specifically, an array 1 and an array 2 may be set, where both array 1 and array 2 are initially empty. When the first high-precision map data 1 is acquired based on the first determined vehicle position, the road section identification information contained in the first high-precision map data 1 is put into an array 2, elements in the array 1 and the array 2 at the moment are compared, so that data to be added and data to be deleted are determined, then the elements in the array 2 are replaced with the elements in the array 1, and the array 2 is emptied; and when the first high-precision map data 2 is acquired based on the second determined vehicle position, the road section identification information contained in the first high-precision map data 2 is put into the array 2, the elements in the array 1 and the array 2 are compared at the moment, so that the data to be added and the data to be deleted are determined, then the elements in the array 2 are replaced with the elements in the array 1, the array 2 is emptied, and the like.
In the embodiment of the application, the position of the vehicle is determined according to a preset time interval; determining a target road segment based on the vehicle position for each determined vehicle position; acquiring first high-precision map data corresponding to a target road section; and updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area is used for being called by the intelligent driving module. According to the method and the device, the high-precision map data stored in the storage area are only related to the target road section corresponding to the vehicle position, so that the data size of the high-precision map data stored in the storage area is greatly reduced, and on the basis, when the intelligent driving module calls the high-precision map data, the data processing pressure is small, so that the consumption of computational resources is reduced.
Further, in an embodiment, after step S30, the method further includes:
performing validity check on the first high-precision map data;
and if the validity check is passed, updating the second high-precision map data stored in the storage area based on the first high-precision map data.
In this embodiment, after the first high-precision map data is acquired based on the vehicle position determined at any one time, the validity check is first performed on the first high-precision map data. The validity check comprises detecting whether complete road section information exists in the first high-precision map data and whether a time stamp of the road section information is valid; if the complete road section information exists and the time stamp of the road section information is valid, the validity check of the first high-precision map data is determined to pass, and on the basis, the step of updating the second high-precision map data stored in the storage area based on the first high-precision map data is performed.
The validity check of the first high-precision map data may be performed in other manners, which is not limited herein.
In a second aspect, embodiments of the present application further provide a map data obtaining apparatus.
In an embodiment, referring to fig. 4, fig. 4 is a schematic functional block diagram of an embodiment of a map data obtaining apparatus according to the present application. As shown in fig. 4, the map data acquisition apparatus includes:
a position determining module 10 for determining a vehicle position at preset time intervals;
a road segment determination module 20 for determining a target road segment based on the vehicle position for each determined vehicle position;
an obtaining module 30, configured to obtain first high-precision map data corresponding to a target road segment;
and an updating module 40 for updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area is used for being called by the intelligent driving module.
Further, in an embodiment, the target road segment is a road segment where the vehicle position is located.
Further, in an embodiment, the road segment determining module 20 is specifically configured to:
determining a first road section where the vehicle position is located;
detecting whether the distance between the vehicle position and the end point of the first road segment is smaller than a preset distance;
if the distance between the vehicle position and the end point of the first road section is smaller than the preset distance, the first road section and the road section adjacent to the first road section are taken as target road sections;
if the distance between the vehicle position and the end point of the first road section is not smaller than the preset distance, detecting whether a second road section with the distance between the starting point and the vehicle position smaller than the preset distance exists or not;
and if the second road section exists, taking the first road section and the second road section as target road sections.
Further, in one embodiment, the updating module 40 is specifically configured to:
deleting the second high-precision map data stored in the storage area;
the first high-precision map data is written into the storage area.
Further, in one embodiment, the updating module 40 is specifically configured to:
determining data to be newly added that exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area, and determining data to be deleted that exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data;
deleting the data to be deleted from the storage area, and writing the data to be newly added into the storage area.
Further, in one embodiment, the updating module 40 is specifically configured to:
comparing the road section identification information contained in the first high-precision map data with the road section identification information contained in the second high-precision map data stored in the storage area;
taking road section information corresponding to road section identification information which exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area as data to be newly added;
and taking the road section information corresponding to the road section identification information which exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data as the data to be deleted.
Further, in an embodiment, the map data obtaining apparatus further includes a verification module, configured to:
performing validity check on the first high-precision map data;
the updating module 40 is further configured to update the second high-precision map data stored in the storage area based on the first high-precision map data if the validity check is passed.
The function implementation of each module in the map data obtaining device corresponds to each step in the map data obtaining method embodiment, and the function and implementation process thereof are not described herein in detail.
In a third aspect, embodiments of the present application provide a map data acquisition apparatus, which may be a personal computer (personal computer, PC), a notebook computer, a server, or the like, having a data processing function.
Referring to fig. 5, fig. 5 is a schematic diagram of a hardware structure of a map data acquiring apparatus according to an embodiment of the present application. In the embodiment of the application, the map data acquisition device may include a processor, a memory, a communication interface, and a communication bus.
The communication bus may be of any type for implementing the processor, memory, and communication interface interconnections.
The communication interfaces include input/output (I/O) interfaces, physical interfaces, logical interfaces, and the like for realizing interconnection of devices inside the map data acquisition apparatus, and interfaces for realizing interconnection of the map data acquisition apparatus with other apparatuses (e.g., other computing apparatuses or user apparatuses). The physical interface may be an ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device may be a Display, a Keyboard (Keyboard), or the like.
The memory may be various types of storage media such as random access memory (randomaccess memory, RAM), read-only memory (ROM), nonvolatile RAM (non-volatileRAM, NVRAM), flash memory, optical memory, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (electrically erasable PROM, EEPROM), and the like.
The processor may be a general-purpose processor, and the general-purpose processor may call a map data acquisition program stored in the memory and execute the map data acquisition method provided in the embodiment of the present application. For example, the general purpose processor may be a central processing unit (central processing unit, CPU). The method executed when the map data obtaining program is called may refer to various embodiments of the map data obtaining method of the present application, and will not be described herein.
Those skilled in the art will appreciate that the hardware configuration shown in fig. 5 is not limiting of the application and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium.
The present application provides a map data acquisition program stored on a computer-readable storage medium, wherein the map data acquisition program, when executed by a processor, implements the steps of the map data acquisition method described above.
The method implemented when the map data obtaining program is executed may refer to various embodiments of the map data obtaining method of the present application, and will not be described herein.
It should be noted that, the foregoing embodiment numbers are merely for describing the embodiments, and do not represent the advantages and disadvantages of the embodiments.
The terms "comprising" and "having" and any variations thereof in the description and claims of the present application and in the foregoing drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus. The terms "first," "second," and "third," etc. are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order, and are not limited to the fact that "first," "second," and "third" are not identical.
In the description of embodiments of the present application, "exemplary," "such as," or "for example," etc., are used to indicate an example, instance, or illustration. Any embodiment or design described herein as "exemplary," "such as" or "for example" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "such as" or "for example," etc., is intended to present related concepts in a concrete fashion.
In the description of the embodiments of the present application, unless otherwise indicated, "/" means or, for example, a/B may represent a or B; the text "and/or" is merely an association relation describing the associated object, and indicates that three relations may exist, for example, a and/or B may indicate: the three cases where a exists alone, a and B exist together, and B exists alone, and in addition, in the description of the embodiments of the present application, "plural" means two or more than two.
In some of the processes described in the embodiments of the present application, a plurality of operations or steps occurring in a particular order are included, but it should be understood that these operations or steps may be performed out of the order in which they occur in the embodiments of the present application or in parallel, the sequence numbers of the operations merely serve to distinguish between the various operations, and the sequence numbers themselves do not represent any order of execution. In addition, the processes may include more or fewer operations, and the operations or steps may be performed in sequence or in parallel, and the operations or steps may be combined.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising several instructions for causing a terminal device to perform the method described in the various embodiments of the present application.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the claims, and all equivalent structures or equivalent processes using the descriptions and drawings of the present application, or direct or indirect application in other related technical fields are included in the scope of the claims of the present application.
Claims (10)
1. A map data acquisition method, characterized in that the map data acquisition method comprises:
determining the position of the vehicle according to a preset time interval;
determining a target road segment based on the vehicle position for each determined vehicle position;
acquiring first high-precision map data corresponding to a target road section;
and updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area is used for being called by the intelligent driving module.
2. The map data acquisition method according to claim 1, wherein the target link is a link in which a vehicle position is located.
3. The map data acquisition method according to claim 1, wherein the step of determining the target link based on the vehicle position includes:
determining a first road section where the vehicle position is located;
detecting whether the distance between the vehicle position and the end point of the first road segment is smaller than a preset distance;
if the distance between the vehicle position and the end point of the first road section is smaller than the preset distance, the first road section and the road section adjacent to the first road section are taken as target road sections;
if the distance between the vehicle position and the end point of the first road section is not smaller than the preset distance, detecting whether a second road section with the distance between the starting point and the vehicle position smaller than the preset distance exists or not;
and if the second road section exists, taking the first road section and the second road section as target road sections.
4. The map data obtaining method according to claim 1, wherein the step of updating the second high-definition map data stored in the storage area based on the first high-definition map data includes:
deleting the second high-precision map data stored in the storage area;
the first high-precision map data is written into the storage area.
5. The map data obtaining method according to claim 1, wherein the step of updating the second high-definition map data stored in the storage area based on the first high-definition map data includes:
determining data to be newly added that exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area, and determining data to be deleted that exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data;
deleting the data to be deleted from the storage area, and writing the data to be newly added into the storage area.
6. The map data acquisition method according to claim 5, wherein the step of determining newly added data that exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area, and determining to delete data that exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data, includes:
comparing the road section identification information contained in the first high-precision map data with the road section identification information contained in the second high-precision map data stored in the storage area;
taking road section information corresponding to road section identification information which exists in the first high-precision map data but does not exist in the second high-precision map data stored in the storage area as data to be newly added;
and taking the road section information corresponding to the road section identification information which exists in the second high-precision map data stored in the storage area but does not exist in the first high-precision map data as the data to be deleted.
7. The map data acquisition method according to any one of claims 1 to 6, characterized by further comprising, after the step of acquiring the first high-precision map data corresponding to the target link:
performing validity check on the first high-precision map data;
and if the validity check is passed, updating the second high-precision map data stored in the storage area based on the first high-precision map data.
8. A map data acquisition apparatus, characterized in that the map data acquisition apparatus comprises:
the position determining module is used for determining the position of the vehicle according to a preset time interval;
a road segment determining module for determining a target road segment based on the vehicle position for each determined vehicle position;
the acquisition module is used for acquiring first high-precision map data corresponding to the target road section;
and the updating module is used for updating the second high-precision map data stored in the storage area based on the first high-precision map data, wherein the high-precision map data stored in the storage area are used for being called by the intelligent driving module.
9. A map data acquisition apparatus comprising a processor, a memory, and a map data acquisition program stored on the memory and executable by the processor, wherein the map data acquisition program, when executed by the processor, implements the steps of the map data acquisition method according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a map data acquisition program is stored, wherein the map data acquisition program, when executed by a processor, implements the steps of the map data acquisition method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311863760.0A CN117804473A (en) | 2023-12-28 | 2023-12-28 | Map data acquisition method, apparatus, device and computer readable storage medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311863760.0A CN117804473A (en) | 2023-12-28 | 2023-12-28 | Map data acquisition method, apparatus, device and computer readable storage medium |
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| CN117804473A true CN117804473A (en) | 2024-04-02 |
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| CN202311863760.0A Pending CN117804473A (en) | 2023-12-28 | 2023-12-28 | Map data acquisition method, apparatus, device and computer readable storage medium |
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| Country | Link |
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| CN (1) | CN117804473A (en) |
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- 2023-12-28 CN CN202311863760.0A patent/CN117804473A/en active Pending
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