CN116610832A - Auxiliary map verification data processing method and system for map, computer equipment and storage medium - Google Patents
Auxiliary map verification data processing method and system for map, computer equipment and storage medium Download PDFInfo
- Publication number
- CN116610832A CN116610832A CN202310636750.7A CN202310636750A CN116610832A CN 116610832 A CN116610832 A CN 116610832A CN 202310636750 A CN202310636750 A CN 202310636750A CN 116610832 A CN116610832 A CN 116610832A
- Authority
- CN
- China
- Prior art keywords
- track points
- map
- track
- points
- acquisition device
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012795 verification Methods 0.000 title claims abstract description 75
- 238000003672 processing method Methods 0.000 title claims abstract description 36
- 238000000034 method Methods 0.000 claims abstract description 30
- 238000007689 inspection Methods 0.000 claims abstract description 19
- 238000012545 processing Methods 0.000 claims description 22
- 230000004044 response Effects 0.000 abstract description 8
- 238000013524 data verification Methods 0.000 description 7
- 238000004590 computer program Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000012790 confirmation Methods 0.000 description 3
- 230000007774 longterm Effects 0.000 description 3
- 238000013507 mapping Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 230000004297 night vision Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/587—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/51—Indexing; Data structures therefor; Storage structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/55—Clustering; Classification
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Library & Information Science (AREA)
- Software Systems (AREA)
- Processing Or Creating Images (AREA)
Abstract
The invention relates to the technical field of automatic driving and unmanned driving, in particular to an auxiliary map verification data processing method and system for a map, computer equipment and a computer readable storage medium, and aims to solve the problem of low map verification efficiency in the prior art. For this purpose, the map-use auxiliary verification data processing method of the present invention comprises: acquiring a plurality of frames of images acquired by an acquisition device and track points of the acquisition device when the acquisition device acquires the images; checking the track points, and storing the track points as offline track points if the track points pass the checking; generating offline data according to the image and the offline track points; in response to the first request for the graph inspection operation, offline data is presented. By the method, the later map verification working efficiency of the map can be improved, the problem that workers frequently go to field verification is avoided, and therefore labor cost is reduced.
Description
Technical Field
The invention relates to the technical field of automatic driving and unmanned driving, and particularly provides an auxiliary map verification data processing method and system for a map, computer equipment and a computer readable storage medium.
Background
In an unmanned software system, the unmanned system mainly comprises a plurality of modules of perception, positioning, decision planning, control, map, prediction, simulation and the like, and a high-precision map is an important infrastructure and provides important priori knowledge for other modules. Such as: providing prejudgement information, such as lanes, roads and element information, for an automatic driving system, and even assisting high-precision positioning by dynamic traffic data so as to perform high-precision three-dimensional characterization on a road network; the auxiliary environment perception, such as traffic lights, speed limit signs, road markings and other semantic information, assists path planning and decision making.
After the high-precision map is manufactured, the high-precision map can be formally used after quality inspection, wherein the quality inspection comprises basic format verification, lane width and curvature verification, lane connection relation verification, simulation map inspection test, real vehicle map inspection test and the like, and the problems found in the map inspection process need to be manually modified.
In the conventional scheme, when the problems such as the fact that the center line or the boundary line of a lane is not matched with the actual position of a traffic light or a stop line is not matched with the actual position of the stop line are found in the process of checking the map, a person needs to frequently go to the field to check the map, the labor cost is high, and the map checking efficiency is low.
Accordingly, there is a need in the art for a new solution to the above-mentioned problems.
Disclosure of Invention
The present invention has been made to overcome the above-mentioned drawbacks, and provides a map-use auxiliary map verification data processing method, system, computer device, and computer-readable storage medium that solve or at least partially solve the technical problem of how to efficiently and inexpensively verify map data.
In a first aspect, the present invention provides a map-use auxiliary map verification data processing method, the method comprising:
acquiring a plurality of frames of images acquired by an acquisition device and track points of the acquisition device when acquiring the images;
checking the track points, and storing the track points as offline track points if the track points pass the checking;
generating offline data according to the image and the offline track points;
and responding to the first graph inspection operation request, and presenting the offline data.
In one technical scheme of the auxiliary map verification data processing method for a map, the step of storing the track point as an offline track point specifically includes:
judging whether the difference value between the generation time of the track point and the current time is larger than a first preset threshold value or not;
if yes, storing the track points as history track points;
if not, selectively storing the track points as recent track points or historical track points according to the image corresponding to the track points and the state information of the acquisition device when acquiring the image;
the offline trajectory points include the recent trajectory points and the historical trajectory points.
In one technical scheme of the auxiliary map verification data processing method for a map, the specific steps of selectively storing the track point as a recent track point or a historical track point according to an image corresponding to the track point and state information of the acquisition device when the image is acquired include:
segmenting a driving path formed by all track points, wherein the difference value between the generation time and the current time of all the track points is not greater than the first preset threshold value;
for each segment, acquiring the average speed of the acquisition device and the number of semantic tags contained in the image selected according to a preset rule;
for each segment, acquiring the average speed of the acquisition device and the number of semantic tags contained in the image selected according to a preset rule;
assigning a preset weight value to the average speed and the number of semantic tags in each segment and obtaining a confidence value;
sorting all the segments based on the confidence values, and storing track points contained in the segments of which the number is preset before based on the sorting result as recent track points;
judging whether the difference value between the generation time and the current time of the track points is larger than a second preset threshold value or not according to the track points corresponding to the unselected images, if so, storing the track points as history track points, and if not, storing the track points as recent track points, wherein the second preset threshold value is smaller than the first preset threshold value.
In one technical scheme of the auxiliary map verification data processing method for a map, the specific steps of selectively storing the track point as a recent track point or a historical track point according to an image corresponding to the track point and state information of the acquisition device when the image is acquired include:
segmenting a driving path formed by all track points, wherein the difference value between the generation time and the current time of all the track points is not greater than the first preset threshold value;
for each segment, acquiring the number of semantic tags contained in an image selected according to a preset rule, the average speed of the acquisition device and the number of times that the acquisition device is switched from an automatic die cutting mode to a manual mode;
assigning preset weight values to the number of semantic tags in each segment, the average speed and the switching times and obtaining confidence values;
sorting all the segments based on the confidence values, and storing track points contained in the segments of which the number is preset before based on the sorting result as recent track points;
judging whether the difference value between the generation time and the current time of the track points is larger than a second preset threshold value or not according to the track points corresponding to the unselected images, if so, storing the track points as history track points, and if not, storing the track points as recent track points, wherein the second preset threshold value is smaller than the first preset threshold value.
In one technical scheme of the auxiliary map verification data processing method for maps, the method further comprises the following steps:
storing the history trace point to HBase,
and/or the number of the groups of groups,
storing the recent track point to an elastic search.
In one technical scheme of the auxiliary map verification data processing method for maps, the method further comprises the following steps:
generating real-time data according to the image and the track point;
and responding to the second graph inspection operation request, and presenting the real-time data.
In a second aspect, the present invention provides an auxiliary map verification data processing system for a map, the system including an acquisition device, the system including:
the data acquisition module is used for acquiring a plurality of frames of images acquired by the acquisition device and track points of the acquisition device when acquiring the images;
the data processing module is used for checking the track points, and storing the track points as offline track points if the track points pass the checking; generating offline data according to the image and the offline track points;
and the data output module is used for responding to the first image verification operation request and presenting the offline data.
In one technical scheme of the auxiliary map verification data processing system for maps, the data processing module specifically comprises:
the first judging unit is used for judging whether the difference value between the generation time and the current time of the track point is larger than a first preset threshold value or not;
and the second judging unit is used for selectively storing the track points as recent track points or historical track points according to the image corresponding to the track points and the state information of the acquisition device when the acquisition device acquires the image if the difference value between the generation time and the current time of the track points is not larger than the first preset threshold value.
In a third aspect, a computer device is provided, which includes a processor and a storage device, where the storage device is adapted to store a plurality of program codes, where the program codes are adapted to be loaded and executed by the processor to perform the map-used auxiliary map-verification data processing method according to any one of the technical solutions of the map-used auxiliary map-verification data processing method.
In a fourth aspect, there is provided a computer-readable storage medium having stored therein a plurality of program codes adapted to be loaded and executed by a processor to perform the auxiliary map data processing method for a map as set forth in any one of the above-described auxiliary map data processing methods for a map.
The technical scheme provided by the invention has at least one or more of the following beneficial effects:
in the technical scheme of the invention, a plurality of frames of images acquired by the acquisition device can be acquired and stored firstly, track points of the acquisition device when the images are acquired, and then real-time data are generated according to the images and the track points; and the method can also check the track points, store the track points as offline track points if the check is passed, and then generate offline data according to the images and the offline track points; and finally, in response to the image verification operation request, auxiliary image verification data are presented, wherein the auxiliary image verification data comprise real-time data or offline data. By the embodiment, the real-time data generated by the image and the track point can be obtained, and the data can be used for a graph inspection person to find problems in time when the acquisition device works; and when the acquisition device works, the track points after verification are stored, the image and offline data generated by the offline track points can be used for the image tester to trace back the history at any time, and when the map data is inconsistent with the actual road information, the image tester can call the pictures of the corresponding road sites at any time through inquiring the history data, so that frequent on-site verification of workers is avoided, the working efficiency of the image tester is improved, and the labor cost is reduced.
Further, the method sets a first preset threshold and a second preset threshold, and classifies and stores the track points by combining the number of semantic tags in the image and the state information of the acquisition device. Specifically, in this way, the track points with the existence time length longer than the first preset threshold value can be stored as history track points, the track points with the existence time length shorter than the second preset threshold value are stored as recent track points, the track points with the existence time length between the second preset threshold value and the first preset threshold value are stored as recent track points, the track points with the image containing more semantic tags, namely the track points with complex road conditions, are stored as recent track points, and the track points with the image containing fewer semantic tags, namely the track points with simple road conditions, are stored as history track points. The track points are classified and stored, so that a technician can conveniently perform proper processing operation on the track points of different categories.
Further, the method stores the history track points into the HBase database, stores the near-term track points into the elastic search engine, and in this way, considers the characteristics of lower later retrieval probability and frequency of the more long-term track points, namely the history track points, and puts the more long-term track points into the HBase database for long-term storage; considering that the track points with complex road conditions and the track points acquired recently may need to be frequently called for confirmation, the track points are stored in an elastic search engine so that the track points can be quickly read, and therefore the graph inspection efficiency is improved.
Drawings
The present disclosure will become more readily understood with reference to the accompanying drawings. As will be readily appreciated by those skilled in the art: the drawings are for illustrative purposes only and are not intended to limit the scope of the present invention. Moreover, like numerals in the figures are used to designate like parts, wherein:
FIG. 1 is a schematic illustration of an application scenario of the present invention;
FIG. 2 is a flow chart of main steps of an auxiliary map verification data processing method for a map according to an embodiment of the present invention;
FIG. 3 is a flow chart of the main steps of storing the trace points as offline trace points according to one embodiment of the invention;
FIG. 4 is a flow chart of an auxiliary map verification data processing method for a map according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a main frame of an auxiliary map verification data processing system for a map according to an embodiment of the present invention.
List of reference numerals：
100: the auxiliary map verification data processing system for the map; 110: a collection device; 120: a data acquisition module; 130: a data processing module; 140: and a data output module.
Detailed Description
Some embodiments of the invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
In the description of the present invention, a "module," "processor" may include hardware, software, or a combination of both. A module may comprise hardware circuitry, various suitable sensors, communication ports, memory, or software components, such as program code, or a combination of software and hardware. The processor may be a central processor, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and/or signal processing functions. The processor may be implemented in software, hardware, or a combination of both. Non-transitory computer readable storage media include any suitable medium that can store program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, and the like.
Referring to fig. 1, fig. 1 is a schematic diagram of an application scenario of the present invention. As shown in fig. 1, in a map data interface displayed in the application scene, continuously arranged points are track points of the acquisition device, wherein one track point corresponds to one frame of image, and in the application scene, a diagrammer checks the corresponding image by clicking different track points. When the problem feedback that the map data does not accord with the actual road is received, the image acquisition device can be checked by clicking the track points at the corresponding positions, for example, when the image acquisition device receives the problem feedback that the actual road is not communicated but the map data shows that the road is communicated, whether the road is newly added with a building such as an isolation belt or not can be preliminarily judged by checking the surrounding images through the track points, so that the problem that the image acquisition device needs to frequently go to the field for confirmation in the prior art is solved.
Referring to fig. 2, fig. 2 is a schematic flow chart of main steps of an auxiliary map verification data processing method for a map according to an embodiment of the present invention. As shown in fig. 2, the auxiliary map verification data processing method for a map according to the embodiment of the present invention mainly includes the following steps S101 to S104.
Step S101: and acquiring a plurality of frames of images acquired by the acquisition device and track points of the acquisition device when the images are acquired.
In this embodiment, the acquisition device acquires a plurality of frame images and acquires a track of the frame images, and preferably, each frame image is attached with a unique identifier.
In one embodiment, the frequency of the image collected by the collecting device can be set according to the actual situation, and the image can be a special map collecting vehicle or a common civil vehicle authorized by a user, and can include a color image or an achromatic image taken by a night vision device, which is not limited herein. The position of the acquisition device may be acquired by a global positioning system (Global Positioning System, GPS) or by a beidou satellite navigation system (BeiDou Navigation Statellite System, BDS), without limitation. In this embodiment, the acquired images of each frame need to be stored, and the images may be stored in cloud by using an object storage service (Object Storage Service, OSS) proposed by the ali cloud, an object storage service (Object Storage Service, OBS) proposed by the hua-to-cloud, or an object storage service (Cloud Object Storage, COS) proposed by the Tencent cloud, which is not limited herein. The unique identifier may be a file name with time information or a specific code in the image data, which is used to provide basis for matching future images and track points, so the specific form of the unique identifier is not limited herein.
Step S102: and checking the track points, and if the track points pass the checking, storing the track points as offline track points.
In this embodiment, before storing the track points, the track points need to be checked first, and the track points passing the check are stored as offline track points.
In one embodiment, the trace point is uploaded to the Apache Kafka system by using websocket, then trace point data is extracted from the Apache Kafka system by using a flink service and pushed to a verification system for verification, and specific verification steps comprise data verification and specification verification, wherein the data verification is to verify the basic format and correctness of the data, including but not limited to data field integrity verification, content format such as time and/or digital correctness verification, field sequence positive determination verification and the like. In one embodiment, a data error file is generated if the data verification fails; the specification verification is to verify the uploading process of the track points, namely the specification verification process occurs in the process of uploading the track points with successful data verification to the cloud database. The specification verification process mainly comprises the step of comparing the consistency of the uploaded track points before and after uploading, and if the consistency of the uploaded track points before and after uploading is the same, the specification verification is successful, and whether the working state of the cloud database is normal can be reflected laterally. In one embodiment, a specification error file is generated if the specification verification fails.
In another embodiment, real-time data may also be generated from the image and the trace points, it being understood that the process of generating real-time data does not affect the storage of trace points and the generation of offline data.
Step S103: and generating offline data according to the image and the offline track points.
In this embodiment, when the acquisition device is in an off-line state, for example, the acquisition is stopped or all the data is uploaded, the map auxiliary map inspection data are all from off-line data.
Step S104: in response to the first request for the graph inspection operation, offline data is presented.
In one embodiment, the real-time data generated in one embodiment of step S102 may also be presented in response to the second map inspection operation request.
In this embodiment, offline data is presented in response to a first mapping operation request by a mapping personnel. In combination with an application scenario diagram of the present invention shown in fig. 1, a diagramming person may click on different track points on a data presentation page to view an image of the corresponding track point.
Based on the method described in the above steps S101 to S104, a plurality of frames of images acquired by the acquisition device may be acquired and stored, and track points of the acquisition device when acquiring the images may be acquired, and then real-time data may be generated according to the images and the track points; and the method can also check the track points, store the track points as offline track points if the check is passed, and then generate offline data according to the images and the offline track points; and finally, in response to the image verification operation request, auxiliary image verification data are presented, wherein the auxiliary image verification data comprise real-time data or offline data. By the embodiment, the real-time data generated by the image and the track point can be obtained, and the data can be used for a graph inspection person to find problems in time when the acquisition device works; and when the acquisition device works, the track points after verification are stored, the image and offline data generated by the offline track points can be used for the image tester to trace back the history at any time, and when the map data is inconsistent with the actual road information, the image tester can call the pictures of the corresponding road sites at any time through inquiring the history data, so that frequent on-site verification of workers is avoided, the working efficiency of the image tester is improved, and the labor cost is reduced.
Based on the embodiment shown in fig. 2 and referring to fig. 3, in some implementations of step S102, the method of storing the track points as offline track points may be implemented through the following steps S1021 to S1022.
Step S1021: and judging whether the difference value between the generation time of the track point and the current time is larger than a first preset threshold value.
Step S1022: if yes, storing the track points as history track points; if not, selectively storing the track points as recent track points or historical track points according to the state information of the image and the acquisition device.
In the present embodiment, it is considered that the track points having the difference value larger than the first preset threshold value exist for a longer time, so that they are stored as history track points; for the track points with the difference value not larger than the first preset threshold value, the track points are further selectively stored as recent track points or historical track points according to the state information of the image and the acquisition device, and the specific modes include, but are not limited to, judging the road condition complexity according to the number of semantic tags in the image, the brightness degree in the image, the running speed of the acquisition device, the braking or deceleration frequency of the acquisition device and the like, further storing the track points with the complex road condition as recent track points and storing the track points with the simple road condition as historical track points.
In one embodiment, the driving path formed by all track points is segmented, wherein the difference value between the generation time and the current time of all track points is not greater than a first preset threshold value; for each segment, acquiring the average speed of the acquisition device and the number of semantic tags contained in the image selected according to a preset rule; for each segment, acquiring the average speed of the acquisition device and the number of semantic tags contained in the image selected according to a preset rule; assigning a preset weight value to the average speed and the number of semantic tags in each segment and obtaining a confidence value; sorting all the segments based on the confidence values, and storing track points contained in the segments of which the number is preset before based on the sorting result as recent track points; and judging whether the difference value between the generation time and the current time of the track points is larger than a second preset threshold value according to the track points corresponding to the unselected images, if so, storing the track points as history track points, and if not, storing the track points as recent track points, wherein the second preset threshold value is smaller than the first preset threshold value. In this embodiment, the selection of the image according to the preset rule may specifically be a random selection of a frame of image, or may be a frame of image corresponding to the track point at the middle position of the segment, or may be all the images in the segment.
In another embodiment, the driving path formed by all the track points is segmented, wherein the difference value between the generation time and the current time of all the track points is not greater than a first preset threshold value; for each segment, acquiring the number of semantic tags contained in an image selected according to a preset rule, the average speed of the acquisition device and the number of times that the acquisition device is switched from an automatic die cutting mode to a manual mode; assigning preset weight values to the number of semantic tags, the average speed and the switching times in each segment and obtaining confidence values; sorting all the segments based on the confidence values, and storing track points contained in the segments of which the number is preset before based on the sorting result as recent track points; and judging whether the difference value between the generation time and the current time of the track points is larger than a second preset threshold value according to the track points corresponding to the unselected images, if so, storing the track points as history track points, and if not, storing the track points as recent track points, wherein the second preset threshold value is smaller than the first preset threshold value. In this embodiment, the selection of the image according to the preset rule may specifically be a random selection of a frame of image, or may be a frame of image corresponding to the track point at the middle position of the segment, or may be all the images in the segment.
In one embodiment, the historical track points are stored to HBase and the late track points are stored to elastesearch.
Based on the method described in the above steps S1021 to S1022, the track points are classified and stored by setting a first preset threshold and a second preset threshold and combining the number of semantic tags in the image and the state information of the acquisition device. Specifically, in this way, the track points with the existence time length longer than the first preset threshold value can be stored as history track points, the track points with the existence time length shorter than the second preset threshold value are stored as recent track points, the track points with the existence time length between the second preset threshold value and the first preset threshold value are stored as recent track points, the track points with the image containing more semantic tags, namely the track points with complex road conditions, are stored as recent track points, and the track points with the image containing fewer semantic tags, namely the track points with simple road conditions, are stored as history track points. The track points are classified and stored, so that a person skilled in the art can conveniently select a proper display mode for different types of data, for example, a primary interface is set for displaying recent data, a secondary interface is set for displaying historical data, and a proper later management mode for different types of data can be selected, for example, the recent data is locally stored, and the historical data is stored in a cloud.
Further, the history track points are stored in the HBase database, the near-term track points are stored in the elastic search engine, and in this way, the characteristics of lower later retrieval probability and frequency of the longer track points, namely the history track points, are considered, and the longer track points are stored in the HBase database for a long time; considering that the track points with complex road conditions and the track points acquired recently may need to be frequently called for confirmation, the track points are stored in an elastic search engine so that the track points can be quickly read, and therefore the graph inspection efficiency is improved.
Referring to fig. 4, fig. 4 is a flow chart of an auxiliary map verification data processing method for map according to an embodiment of the invention, in this embodiment, the auxiliary map verification data processing method for map may be described as follows:
the acquisition device acquires the track information of the acquisition device while acquiring the image; the captured photograph falls into OSS (Object Storage Service, object store service); on the one hand, the photos in the OSS and the tracks through websocket service are combined to generate real-time data; on the other hand, the track sequentially passes the kafka and the flink service and then starts to carry out a verification process, wherein the specific verification process comprises data verification, if the data verification is not passed, an error file is generated, and if the data verification is passed, specification verification is carried out; if the specification check is not passed, generating a failure_handler file, and if the specification check is passed, putting the track point into an elastic search engine. And screening the track points in the elastic search engine according to a preset rule, and transferring the corresponding track points to the HBase. The drop disc is stored as an offline combination of the offline trace points and the images in the OSS to generate offline data. In response to a technician's request for a mapping operation, offline data and/or real-time data is presented.
It should be noted that, although the foregoing embodiments describe the steps in a specific order, it will be understood by those skilled in the art that, in order to achieve the effects of the present invention, the steps are not necessarily performed in such an order, and may be performed simultaneously (in parallel) or in other orders, and these variations are within the scope of the present invention.
The invention further provides an auxiliary map verification data processing system for the map.
Referring to fig. 5, fig. 5 is a schematic diagram of a main frame of an auxiliary map verification data processing system according to an embodiment of the present invention. As shown in fig. 5, the auxiliary map verification data processing system for map in the embodiment of the present invention mainly includes an acquisition device 110, a data acquisition module 120, a data processing module 130, and a data output module 140. In some embodiments, the acquisition device 110, the data acquisition module 120, the data processing module 130, and the data output module 140 may be combined together into one module. In some embodiments: the acquisition device 110 may be configured to acquire images and trajectories; the data acquisition module 120 may be configured to acquire a number of frames of images acquired by the acquisition device 110, and to acquire a trace point of the acquisition device 110 when acquiring the images; the data processing module 130 may be configured to verify the track points, and if the verification passes, store the track points as offline track points; generating offline data according to the image and the offline track points; the data output module 140 may be configured to present offline data in response to the first map inspection operation request. Description of specific implementation functions may be described with reference to steps S101 to S104.
Based on the embodiment shown in fig. 5, the data processing module 130 specifically includes a first judging unit and a second judging unit. In some embodiments: the first judging unit may be configured to judge whether a difference between the generation time of the trace point and the current time is greater than a first preset threshold; the second judging unit may be configured to selectively store the track point as a recent track point or a history track point according to the image corresponding to the track point and the state information of the acquisition device when the image is acquired if the difference between the generation time of the track point and the current time is not greater than the first preset threshold.
The technical principles of the above auxiliary map verification data processing system for map and the embodiments of the auxiliary map verification data processing method for map shown in fig. 2 to 4, the technical problems to be solved and the technical effects to be produced are similar, and those skilled in the art can clearly understand that, for convenience and brevity of description, the specific working process and related description of the auxiliary map verification data processing system for map can refer to the description of the embodiments of the auxiliary map verification data processing method for map, which is not repeated herein.
It will be appreciated by those skilled in the art that the present invention may implement all or part of the above-described methods according to the above-described embodiments, or may be implemented by means of a computer program for instructing relevant hardware, where the computer program may be stored in a computer readable storage medium, and where the computer program may implement the steps of the above-described embodiments of the method when executed by a processor. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable storage medium may include: any entity or device, medium, usb disk, removable hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier wave signals, telecommunications signals, software distribution media, and the like capable of carrying the computer program code. It should be noted that the computer readable storage medium may include content that is subject to appropriate increases and decreases as required by jurisdictions and by jurisdictions in which such computer readable storage medium does not include electrical carrier signals and telecommunications signals.
Further, the invention also provides computer equipment. In one embodiment of the computer apparatus according to the present invention, the computer apparatus includes a processor and a storage device, the storage device may be configured to store a program for executing the auxiliary map data processing method for a map of the above-described method embodiment, and the processor may be configured to execute the program in the storage device, including, but not limited to, the program for executing the auxiliary map data processing method for a map of the above-described method embodiment. For convenience of explanation, only those portions of the embodiments of the present invention that are relevant to the embodiments of the present invention are shown, and specific technical details are not disclosed, please refer to the method portions of the embodiments of the present invention. The computer device may be a computer device formed from a variety of electronic devices.
Further, the invention also provides a computer readable storage medium. In one embodiment of the computer-readable storage medium according to the present invention, the computer-readable storage medium may be configured to store a program for executing the auxiliary map verification data processing method for a map of the above-described method embodiment, the program being loadable and executable by a processor to implement the auxiliary map verification data processing method for a map as described above. For convenience of explanation, only those portions of the embodiments of the present invention that are relevant to the embodiments of the present invention are shown, and specific technical details are not disclosed, please refer to the method portions of the embodiments of the present invention. The computer readable storage medium may be a storage device including various electronic devices, and optionally, the computer readable storage medium in the embodiments of the present invention is a non-transitory computer readable storage medium.
Further, it should be understood that, since the respective modules are merely set to illustrate the functional units of the apparatus of the present invention, the physical devices corresponding to the modules may be the processor itself, or a part of software in the processor, a part of hardware, or a part of a combination of software and hardware. Accordingly, the number of individual modules in the figures is merely illustrative.
Those skilled in the art will appreciate that the various modules in the apparatus may be adaptively split or combined. Such splitting or combining of specific modules does not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solution after splitting or combining falls within the protection scope of the present invention.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will fall within the scope of the present invention.
Claims (10)
1. An auxiliary map verification data processing method for a map, which is characterized by comprising the following steps:
acquiring a plurality of frames of images acquired by an acquisition device and track points of the acquisition device when acquiring the images;
checking the track points, and storing the track points as offline track points if the track points pass the checking;
generating offline data according to the image and the offline track points;
and responding to the first graph inspection operation request, and presenting the offline data.
2. The map-assisted verification data processing method according to claim 1, wherein the step of storing the trajectory points as offline trajectory points specifically includes:
judging whether the difference value between the generation time of the track point and the current time is larger than a first preset threshold value or not;
if yes, storing the track points as history track points;
if not, selectively storing the track points as recent track points or historical track points according to the image corresponding to the track points and the state information of the acquisition device when acquiring the image;
the offline trajectory points include the recent trajectory points and the historical trajectory points.
3. The map-use auxiliary map verification data processing method according to claim 2, wherein the specific step of selectively storing the trajectory point as a recent trajectory point or a history trajectory point according to an image corresponding to the trajectory point and state information of the acquisition device at the time of acquiring the image includes:
segmenting a driving path formed by all track points, wherein the difference value between the generation time and the current time of all the track points is not greater than the first preset threshold value;
for each segment, acquiring the average speed of the acquisition device and the number of semantic tags contained in the image selected according to a preset rule;
assigning a preset weight value to the average speed and the number of semantic tags in each segment and obtaining a confidence value;
sorting all the segments based on the confidence values, and storing track points contained in the segments of which the number is preset before based on the sorting result as recent track points;
judging whether the difference value between the generation time and the current time of the track points is larger than a second preset threshold value or not according to the track points corresponding to the unselected images, if so, storing the track points as history track points, and if not, storing the track points as recent track points, wherein the second preset threshold value is smaller than the first preset threshold value.
4. The map-assisted verification data processing method according to claim 2, wherein the specific step of selectively storing the trajectory point as a recent trajectory point or a history trajectory point according to an image corresponding to the trajectory point and state information of the acquisition device at the time of acquiring the image includes:
segmenting a driving path formed by all track points, wherein the difference value between the generation time and the current time of all the track points is not greater than the first preset threshold value;
for each segment, acquiring the number of semantic tags contained in an image selected according to a preset rule, the average speed of the acquisition device and the number of times that the acquisition device is switched from an automatic die cutting mode to a manual mode;
assigning preset weight values to the number of semantic tags in each segment, the average speed and the switching times and obtaining confidence values;
sorting all the segments based on the confidence values, and storing track points contained in the segments of which the number is preset before based on the sorting result as recent track points;
judging whether the difference value between the generation time and the current time of the track points is larger than a second preset threshold value or not according to the track points corresponding to the unselected images, if so, storing the track points as history track points, and if not, storing the track points as recent track points, wherein the second preset threshold value is smaller than the first preset threshold value.
5. The map assist map inspection data processing method according to any one of claims 2 to 4, characterized in that the method further comprises:
storing the history trace point to HBase,
and/or the number of the groups of groups,
storing the recent track point to an elastic search.
6. The map-use auxiliary map verification data processing method according to claim 1, characterized in that the method further comprises:
generating real-time data according to the image and the track point;
and responding to the second graph inspection operation request, and presenting the real-time data.
7. An auxiliary map verification data processing system for a map, comprising a collection device, characterized in that the system comprises:
the data acquisition module is used for acquiring a plurality of frames of images acquired by the acquisition device and track points of the acquisition device when acquiring the images;
the data processing module is used for checking the track points, and storing the track points as offline track points if the track points pass the checking; generating offline data according to the image and the offline track points;
and the data output module is used for responding to the first image verification operation request and presenting the offline data.
8. The map-aided illustration data processing system of claim 7, wherein said data processing module specifically comprises:
the first judging unit is used for judging whether the difference value between the generation time and the current time of the track point is larger than a first preset threshold value or not;
and the second judging unit is used for selectively storing the track points as recent track points or historical track points according to the image corresponding to the track points and the state information of the acquisition device when the acquisition device acquires the image if the difference value between the generation time and the current time of the track points is not larger than the first preset threshold value.
9. A computer device comprising a processor and storage means, said storage means being adapted to store a plurality of program code, characterized in that said program code is adapted to be loaded and executed by said processor to perform the auxiliary map verification data processing method for a map as claimed in any one of claims 1 to 6.
10. A computer readable storage medium having stored therein a plurality of program codes, wherein the program codes are adapted to be loaded and executed by a processor to perform the auxiliary map verification data processing method for a map as set forth in any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310636750.7A CN116610832A (en) | 2023-05-31 | 2023-05-31 | Auxiliary map verification data processing method and system for map, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310636750.7A CN116610832A (en) | 2023-05-31 | 2023-05-31 | Auxiliary map verification data processing method and system for map, computer equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116610832A true CN116610832A (en) | 2023-08-18 |
Family
ID=87674471
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310636750.7A Pending CN116610832A (en) | 2023-05-31 | 2023-05-31 | Auxiliary map verification data processing method and system for map, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116610832A (en) |
-
2023
- 2023-05-31 CN CN202310636750.7A patent/CN116610832A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108318043B (en) | Method, apparatus, and computer-readable storage medium for updating electronic map | |
| CN110782120B (en) | Method, system, equipment and medium for evaluating traffic flow model | |
| CN106023622B (en) | A kind of method and apparatus of determining traffic lights identifying system recognition performance | |
| CN110335484B (en) | Method and device for controlling vehicle to run | |
| CN111081017B (en) | Vehicle information management system, method, computer device, and storage medium | |
| CN110969719A (en) | Automatic inspection method, system, terminal equipment and storage medium | |
| CN109190674B (en) | Training data generation method and device | |
| CN111258974A (en) | Vehicle offline scene data processing method and system | |
| KR20200001206A (en) | Apparatus and method for learning facilities using video file | |
| CN115294544A (en) | Driving scene classification method, device, equipment and storage medium | |
| CN113129596A (en) | Travel data processing method, travel data processing device, travel data processing apparatus, storage medium, and program product | |
| CN113553304A (en) | Data storage system for automatic driving | |
| CN116580271A (en) | Evaluation method, device, equipment and storage medium for perception fusion algorithm | |
| WO2023129224A1 (en) | Systems and methods for updating maps and evaluating map accuracy based on collected image data | |
| US11816543B2 (en) | System and method for using knowledge gathered by a vehicle | |
| CN114821247A (en) | Model training method and device, storage medium and electronic device | |
| CN110646002A (en) | Method and apparatus for processing information | |
| CN110967036B (en) | Test method and device for navigation product | |
| CN116610832A (en) | Auxiliary map verification data processing method and system for map, computer equipment and storage medium | |
| CN114550129B (en) | Machine learning model processing method and system based on data set | |
| CN108882145A (en) | Sight spot recognition methods and device | |
| CN113048988B (en) | Method and device for detecting change elements of scene corresponding to navigation map | |
| CN114677843A (en) | Road condition information processing method, device and system and electronic equipment | |
| CN114252087A (en) | Map data processing method and device, vehicle and storage medium | |
| CN114612876A (en) | Method for acquiring traffic incident and navigation terminal |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |