CN116303866B - Data processing method, device, electronic equipment and storage medium - Google Patents

Data processing method, device, electronic equipment and storage medium Download PDF

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CN116303866B
CN116303866B CN202310563843.1A CN202310563843A CN116303866B CN 116303866 B CN116303866 B CN 116303866B CN 202310563843 A CN202310563843 A CN 202310563843A CN 116303866 B CN116303866 B CN 116303866B
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track
data
travel
specified
expansion
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CN116303866A (en
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李彬
何慧妍
张小玲
何晓航
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Beijing Mingli Surveying And Mapping Technology Co ltd
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Beijing Mingli Surveying And Mapping Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2477—Temporal data queries

Abstract

The embodiment of the disclosure provides a data processing method, a data processing device, electronic equipment and a storage medium. The method comprises the following steps: receiving a travel track data set; wherein the travel track data set includes travel track data for representing a travel track of at least one vehicle; generating a track expansion area according to a specified expansion rule by taking the running track as a reference; wherein the track extension region has an extension boundary extending along the travel track; designating an expansion rule for indicating a distance relation between an extension boundary of the track expansion region and the running track; and determining track fragments positioned in the track expansion area and track fragment data corresponding to the track fragments aiming at any track expansion area. By the implementation mode of the method, the device and the system, centralized processing of the driving track data corresponding to the driving track in the same track expansion area is achieved, and processing efficiency of the driving track data is improved.

Description

Data processing method, device, electronic equipment and storage medium
Technical Field
Embodiments of the present disclosure relate to the field of data processing, and in particular, to a data processing method, apparatus, electronic device, and storage medium.
Background
The navigation map provides assistance to the driving behavior of the driver during driving of the vehicle. At present, the data for making the navigation map is generally obtained by collecting the original data through a collecting vehicle and then processing the original data. However, the data types of the original data are more various, the data volume is more huge, and if all the collected original data are integrally processed, the calculation power requirement of the data processing equipment is higher.
Therefore, the original data is usually required to be split, and then the subsequent navigation map is manufactured according to the split data. The splitting of the original data is mainly realized by processing the running track data, the running track data is obtained according to the original data, and then the splitting of the original data is indicated by using the processing result of the running track data.
In the related art, the processing of the travel track data is usually performed manually, and in the case where the data amount of the travel track data is large, the efficiency of the manual processing is low.
Disclosure of Invention
Various embodiments in the present disclosure provide a data processing method, apparatus, electronic device, and storage medium, which can improve processing efficiency of driving track data.
One embodiment of the present disclosure provides a data processing method, including: receiving a travel track data set; wherein the travel track data set includes travel track data for representing at least one travel track; generating a track expansion area according to a specified expansion rule by taking the running track as a reference; wherein the track extension region has an extension boundary extending along the travel track; the specified extension rule is used for indicating the distance relation between the extension boundary of the track extension area and the running track; and determining track fragments positioned in the track expansion area and the data of the collected fragments corresponding to the track fragments aiming at any track expansion area.
One embodiment of the present disclosure provides a data processing apparatus, the apparatus including: the receiving module is used for receiving the driving track data set; wherein the travel track data set includes travel track data for representing at least one travel track; the generation module is used for generating a track expansion area according to a specified expansion rule by taking the running track as a reference; the track extension region has an extension boundary extending along the travel track; the specified extension rule is used for indicating the distance relation between the extending boundary of the track extension area and the running track; the determining module is used for determining track fragments positioned in the track expansion area and track fragment data corresponding to the track fragments aiming at any track expansion area.
One embodiment of the present disclosure provides an electronic device including a memory and a processor, the memory storing at least one computer program instruction that is loaded and executed by the processor to implement a data processing method as described above.
One embodiment of the present disclosure provides a computer-readable storage medium having stored therein at least one computer program instruction that when executed by a processor is capable of implementing a data processing method as described above.
According to the embodiments provided by the disclosure, the track expansion areas are generated according to the specified expansion rules by receiving the running track data set and taking the running track represented by the running track data included in the running track data set as a reference, and the track fragments and the corresponding track fragment data in any track expansion area are confirmed, so that the centralized processing of the running track data corresponding to the running track in the same track expansion area is realized, and the processing efficiency of the running track data is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a data processing method according to an embodiment of the present disclosure.
Fig. 2 (a) is a schematic diagram of a data processing method according to an embodiment of the present disclosure.
Fig. 2 (b) is a schematic diagram of a data processing method according to an embodiment of the present disclosure.
Fig. 3 is a schematic diagram of a processing result obtained by processing travel track data according to the data processing method provided in the embodiment of the present disclosure.
Fig. 4 is a flow chart of a data processing method according to an embodiment of the present disclosure.
Fig. 5 is a schematic block diagram of a data extraction device according to an embodiment of the present disclosure.
Fig. 6 is a schematic block diagram of an electronic device provided in one embodiment of the present disclosure.
Detailed Description
The following description of the embodiments of the present disclosure will be made clearly and fully with reference to the accompanying drawings in which it is evident that the described embodiments are only some, but not all embodiments. All other examples, which can be made by one of ordinary skill in the art without undue burden based on the embodiments provided in this disclosure, are within the scope of the present invention.
SUMMARY
The raw data collected by the collection vehicle generally includes various types of data capable of reflecting the road surface, the surrounding environment of the road, the running state of the vehicle on the road, and the like. For example, travel track data of a vehicle, road point cloud data, picture data or video data of the surrounding environment of a road, and the like. Raw data is collected mainly by the following procedure.
The acquisition vehicle runs along the road, the surrounding environment of the road is shot through photographic equipment carried by the acquisition vehicle in the running process, the road point cloud data is acquired through a laser radar carried by the acquisition vehicle, and the coordinate data of the passing position of the acquisition vehicle in an earth coordinate system, such as the coordinate data acquired by a global positioning system and/or the inertial data acquired by an inertial measurement unit, are recorded. The above-mentioned types of data are stored in accordance with the time stamps, i.e., at the time indicated by the time stamp, all the data that already exist at that time are stored in the storage space marked with the corresponding time stamp. After the acquisition vehicle finishes a data acquisition task, carrying out data processing on all or part of original data acquired by the acquisition vehicle in the process of executing the task. The original data set acquired by the acquisition vehicle in the task can be obtained by extracting the same type of original data in the storage space and sequentially arranging the same type of original data according to the increasing sequence of the time stamps. The raw data set may include multiple types of raw data. For example, the travel track data in the original data set can be obtained by extracting the coordinate data in the storage space and sequentially arranging them in the order in which the time stamps are increased.
Because the data volume contained in the original data set is huge, the original data set needs to be split first, and then a navigation map is manufactured according to the split data. In general, splitting of an original data set is achieved through processing of running track data, that is, a running track data set is obtained according to a coordinate data set in the original data set, then the running track data in the running track data set is processed, and a specific splitting method of the original data set is indicated by adopting a processing result of the running track data. In the related art, the processing of the travel track data set is manually and empirically performed, which is inefficient.
Accordingly, it is necessary to provide a data processing method, apparatus, electronic device, and storage medium that can generate a trajectory extension region based on a travel trajectory represented by travel trajectory data, and that can improve the efficiency of travel trajectory data processing by performing centralized processing on travel trajectory data corresponding to a travel trajectory located within the same trajectory extension region.
Scene example
Vehicles described in embodiments of the present disclosure may include a collection vehicle carrying a data collection device. The collection vehicle can be a vehicle which is driven by a person and has an auxiliary driving function, and can also be an automatic intelligent driving vehicle. The collection vehicle can be a fuel oil vehicle, an electric vehicle or a hydrogen energy vehicle. The types of the collection vehicle can specifically comprise sedans, off-road vehicles, buses, trucks and the like. Embodiments of the present disclosure are not particularly limited to collection vehicles.
The roads described in the embodiments of the present disclosure may be urban roads or rural roads. The road types may include expressways, arterial roads, sub-arterial roads, branches, etc., and embodiments of the present disclosure do not specifically limit the road.
Please refer to fig. 1. One embodiment of the present disclosure provides an application scenario example of a data processing method. Taking a road as an urban trunk road as an example, the data processing device can obtain two running tracks a and b of the acquisition vehicle when two times of data acquisition tasks are executed according to the running track data after receiving the running track data set.
For example, the data processing device may compare the lengths of the travel tracks a, b first, determine the travel track b having a shorter length as the reference travel track, and may extract the travel track data corresponding to the travel track b from the travel track data set.
Then, the data processing device may compare the length of the travel track b with the first division length and the second division length, and if the length of the travel track b is greater than the first division length, compare the sum of the first division length and the second division length, and if the length of the travel track b is not less than the sum of the first division length and the second division length, identify that the travel track b meets the specified division rule.
In the case where the data processing apparatus recognizes that the travel locus b meets the specified division rule, the travel locus b may be divided according to the first division length from the start point of the travel locus b, that is, from the start point of the travel locus b, in the travel direction indicated by the travel locus b, that is, in the direction indicated by the arrow of fig. 1, and the travel locus having the length corresponding to the first division length may be taken as the first sub-locus of the travel locus b. And (3) putting back the driving track data corresponding to the driving tracks except the first sub-track in the driving track b into the driving track data set.
Subsequently, the data processing apparatus may expand the first sub-track by a specified width in a direction perpendicular to the traveling direction indicated by the traveling track with reference to the first sub-track to generate a track expansion region, that is, a gray region in fig. 1, whose upper and lower boundaries may be parallel to the first sub-track.
After the track extension area is generated, the data processing apparatus may determine track segments located in the area, that is, track segments located in gray areas in the traveling tracks a and b in fig. 1, and may determine track segment data corresponding to the track segments in the area.
And repeating the processes of length comparison, running track division, track expansion area generation and track fragment and corresponding track fragment data determination in the track expansion area until the running track data set is empty, thereby realizing the processing of the running track data.
Please refer to fig. 2 (a). Another embodiment of the present disclosure provides an application scenario example of a data processing method. Taking a road as an urban trunk road as an example, the data processing device can obtain two running tracks a and b of the acquisition vehicle when two times of data acquisition tasks are executed according to the running track data after receiving the running track data set.
For example, the data processing apparatus may first generate a track expansion region, i.e., a gray region in fig. 2 (a), by expanding the travel tracks a, b by a specified width in a direction perpendicular to the travel direction indicated by the travel tracks a, b, respectively, with reference to the travel tracks a, b.
After the track expansion area is generated, the data processing device may determine the travel track located in the area, and may determine the travel track data corresponding to the travel track in the area.
Subsequently, the data processing device can determine a plurality of reference positions on the travel tracks a, b at specified length intervals, establish a sampling region in a circular shape or a polygonal shape with any reference position as a center, and pre-divide the track expansion regions of the travel tracks a, b by the sampling region. Please refer to fig. 2 (b). The data processing device may set up a circular sampling area according to a specified radius with a reference position a on the running track a of a specified length interval as a center, and use a track expansion area overlapping with the circular sampling area as a pre-dividing area, that is, a gray area in fig. 2 (b).
After determining the pre-divided area, the data processing apparatus may determine whether the pre-divided area can be the target track expansion area according to whether the length of the travel track located within the area satisfies the specified division condition. In the case where the pre-divided region can be used as the target track extension region, the track segments and the corresponding track segment data located in the pre-divided region can be directly determined, and the track segment data can be taken out from the travel track data set.
The processes of generating the track expansion area, generating the sampling area, determining the pre-dividing area, determining the target track expansion area and determining the track fragments and the corresponding track fragment data in the target track expansion area are repeated until the running track data set is empty, so that the running track data is processed.
Please refer to fig. 3. The line segments of different thickness and different gray scale in fig. 3 may be the processing result obtained by processing the travel track data representing the travel track b in the above embodiment by the data processing method provided in the above embodiment.
System architecture
The data processing method provided by the embodiment of the disclosure is applied to the data processing equipment. The data processing device may be an electronic device with a certain arithmetic processing capability. In particular, for example, the data processing device may comprise a desktop computer, a tablet computer, a notebook computer, a smart phone, a server, or the like. The data processing device may have a network communication module, a processor, a memory, and the like.
Example method
Please refer to fig. 4. One embodiment of the present disclosure provides a data processing method. The data processing method may include the following steps.
S110: receiving a travel track data set; wherein the travel track data set includes travel track data for representing a travel track of at least one vehicle.
In the present embodiment, the travel track data set may be obtained from a coordinate data set in the original data set. Specifically, the coordinate data set may include coordinate data acquired by the acquisition vehicle when performing the data acquisition task multiple times. The coordinate data corresponding to each data acquisition task can have a unified identifier. For example, all coordinate data corresponding to a data collection task may have the same task name. The driving track data of the acquisition vehicle for executing each data acquisition task can be obtained according to the coordinate data corresponding to each data acquisition task. The travel track data set may include at least one piece of travel track data. Each travel track may also include an acquisition timestamp corresponding to each coordinate data.
In this embodiment, the travel track data corresponding to each data acquisition task may be obtained by sequentially arranging all the coordinate data corresponding to the data acquisition task once. Specifically, for example, the earth coordinate system may be used as a reference coordinate system, in the process of executing the data collection task by the collection vehicle, the storage space corresponding to each time stamp stores the coordinate data of the collection vehicle at the moment corresponding to each time stamp, and the coordinate data may be sequentially arranged according to the increasing or decreasing order of the time stamps to obtain the driving track data. The travel track indicated by the travel track data may be obtained by identifying the coordinate positions indicated by the coordinate data on the map, and sequentially connecting the coordinate positions in order of increasing or decreasing time stamps. In order to enable the travel track represented by the travel track data to more accurately show the actual travel track of the acquisition vehicle on the map, it is necessary to keep the coordinate data consistent with the reference coordinate system of the map. Embodiments of the present disclosure are not particularly limited with respect to the reference coordinate system used for the coordinate data.
It is noted that, the original data collected by each collection vehicle executing the data collection task each time may be stored separately, and in the process of executing one data collection task, each timestamp may correspond to the storage space one by one, that is, "task name+timestamp" may correspond to the unique storage space. Even if two collection vehicles collect data for the same road at the same time and the time stamps of the original data collected by the two vehicles are the same, the situation that the data collected by the two vehicles are mixed with each other can not occur due to the fact that the two vehicles execute different data collection tasks and the task names are different.
In this embodiment, the driving track data may be obtained by receiving the original data collected by the collection vehicle and sequentially arranging the coordinate data in the original data. In some embodiments, the driving track data obtained by sequentially arranging the coordinate data through other devices may also be directly received.
S120: generating a track expansion area according to a specified expansion rule by taking the running track as a reference; wherein the track extension region has an extension boundary extending along the travel track; the specified extension rule is used for indicating a distance relation between an extension boundary of the track extension region and the running track.
In the present embodiment, after receiving the travel track data, the track extension region may be generated with the travel track indicated by the travel track data as a reference.
The travel track may be any irregular curve. In the present embodiment, the track expansion region is generated according to the specified expansion rule by translating the travel track as the reference in the specified direction by the specified expansion width to obtain the extension boundary of the track expansion region, and then connecting the end points of the extension boundary to obtain the track expansion region. Specifically, the track expansion area has at least two extending boundaries, and can be obtained by translating the driving track along two specified directions. The specified direction may include a direction having an angle of 0 ° to 180 ° with the traveling direction of the traveling track, for example, a direction having an angle of 90 ° with the traveling direction of the traveling track.
In some embodiments, the track expansion area may be generated according to a specified expansion rule by generating a regular polygon with the travel track as a reference. Specifically, for example, the regular polygon is a rectangle, two opposite sides of the rectangle pass through the start point and the end point of the running track respectively, the other two opposite sides extend along the running direction of the running track, and the running track is located between the two sides extending along the running direction of the running track. Specifically, for example, the traveling direction of the traveling locus may be a tangential direction of any point on the traveling locus. The traveling direction of the traveling locus may be a connecting line direction between the start point and the end point of the traveling locus.
In the present embodiment, in the case where the extending boundary of the trajectory extension region is obtained by the travel trajectory translating in the specified direction, the specified extension rule may include a specified extension width of the travel trajectory translating as a reference. Specifically, the specified extension width may be a preset width value, and the preset width value may be a specific value or a value within a preset value range. The preset width value may be determined according to the road type and the corresponding lane attribute. Taking an urban eight-lane trunk as an example, in order to reduce the problem that the obtained data packet is difficult to reflect the actual condition of the road due to data division, a larger width can be preset in a reasonable range so as to reduce the influence of a specific lane on data division when the acquisition vehicle runs during the data acquisition task. For example, the preset width value may be 60m, or the preset width value may take a value in a range of 60m to 80 m.
In some embodiments, the specified extension width may also be a historical extension width, or may be a simulated extension width that results from training a machine learning algorithm model with the historical extension width. Embodiments of the present disclosure are not particularly limited to specifying an expanded width.
In some embodiments, in the case where the extending boundary of the trajectory extension region is a side of a regular polygon, the specified extension rule may include a distance range that any point on the extending boundary satisfies to the distance of the travel trajectory as a reference. Specifically, the distance range may be a preset range, for example, the distance range may be 60m to 80m. In some embodiments, the distance range may also be a historical range, or may be a simulation range that results from training a machine learning algorithm model with the historical range. Embodiments of the present disclosure do not specifically limit the distance range.
S130: and determining track fragments positioned in the track expansion area and track fragment data corresponding to the track fragments aiming at any track expansion area. Track segments are part or all of a running track, and track segment data are track data corresponding to the track segments.
In the present embodiment, a track segment located within the track expansion area and corresponding track segment data may be determined so that road sensing data for making a navigation map is further determined from the track segment data later.
In this embodiment, the track segments located in the track extension area may be one complete running track, may be multiple complete running tracks, may be a certain part of one complete running track, may be a certain part of each running track in multiple complete running tracks, and the number of track segments located in the track extension area in the embodiment of the present disclosure is not specifically limited.
In the present embodiment, when the track segment located in the track extension area is a complete travel track, that is, when only the travel track serving as a reference exists in the track extension area, the track segment located in the track extension area and the track segment data corresponding to the track segment may be determined by directly determining that the travel track serving as the reference is the track segment, and the corresponding travel track data is the track segment data. Specifically, the data identification of the coordinate data constituting the travel locus data may be determined from the travel locus data.
In this embodiment, when the track segment located in the track extension area is a plurality of complete running tracks, or is a certain portion of one complete running track, or is a certain portion of each of the plurality of complete running tracks, that is, when there is another running track or a certain portion of another running track in the track extension area in addition to the running track serving as a reference, track segment data located in the track extension area and track segment data corresponding to the track segment may be determined by first constructing a track line of the running track represented by the running track data in the running track data set, drawing the track extension area of the running track with the track corresponding to the running track as a reference, identifying the track line located in the track extension area, taking the track line located in the track extension area as a track segment, and taking the track line corresponding to the track line as track segment data. And data identification of the corresponding coordinate data.
In the embodiment of the disclosure, by receiving the running track data set, generating the track expansion area according to the appointed expansion rule by taking the running track represented by the running track data included in the running track data set as a reference, and determining the track fragments and the corresponding track fragment data in the track expansion area, the running track data in the same track expansion area are subjected to centralized processing, and the running track data processing efficiency is improved.
In some embodiments, the data processing method may further include: identifying first travel track data meeting specified screening conditions from the travel track data set; dividing sub-track data conforming to a specified extraction rule from the first driving track data; the sub-track represented by the sub-track data is used as a reference, and a track expansion area is generated according to a specified expansion rule. In addition, when the running track data set further includes running track data, the steps (that is, the first running track data meeting the specified screening condition is identified from the running track data set, and the sub-track data meeting the specified extraction rule is divided from the first running track data) may be repeatedly performed until all the running track data in the running track data set are extracted.
In order to improve the accuracy of the navigation map, multiple data acquisitions can be performed on the same road, so as to reduce errors or errors of the navigation map caused by errors or incompleteness of the acquired data. Thus, the original data reflecting the same road may include a plurality of travel tracks.
In this embodiment, specifying the screening condition may include: the length of the running track represented by the running track data is shortest; alternatively, the time when the travel track data is generated is the latest. Specifically, for the length of the travel track, when the travel track data set is formed, the length of the travel track indicated by the travel track data may be calculated, and the travel track data set may be formed together with the travel track data as the attribute of the travel track data. As for the time at which the travel track data is generated, a time stamp corresponding to the coordinate data indicating the end point of the travel track may be set as the time at which the travel track data is generated, among the coordinate data constituting the travel track data. In some embodiments, a time stamp corresponding to the coordinate data indicating the start point of the travel route may be generated as the travel route data, or a time stamp corresponding to the coordinate data indicating the midpoint of the travel route may be generated as the travel route data.
In this embodiment, the specified division rule may include a length relationship between the track length of the first travel track indicated by the first travel track data and the first division length, and a division method of dividing the sub-track data from the first travel track data. Specifically, in the case where the first travel track length is not less than the sum of the first division length and the second division length, the sub-track is divided from the start point or the end point of the first target travel track in accordance with the first division length.
In this embodiment, the first travel route data that meets the specified screening condition may be identified from the travel route data set, or the identification of the first travel route data that meets the specified screening condition may be identified from the travel route data set by extracting the first travel route data that meets the specified screening condition from the travel route data set.
By identifying the first travel track data from the travel track data set and dividing the sub-track data from the first travel track data set, the continuous division of the travel track data can be realized when the travel track data set only comprises the travel track data of one travel track, and the division of other travel track data in the travel track data set can be further realized when the travel track data set comprises a plurality of travel track data, so that the processing efficiency of the travel track data is improved.
In some embodiments, the step of generating the track expansion area according to the specified expansion rule based on the travel track may include: dividing the travel track into a plurality of sub-tracks according to a first division length in response to the travel track conforming to a specified division rule; wherein the length of the sub-track is not greater than the first division length; and respectively generating track expansion areas of the sub tracks according to the appointed expansion rules.
If the travel track represented by the travel track data is longer, the data volume of the original data corresponding to the travel track data is larger, the calculation power requirement on the data processing equipment is still higher, and if errors exist in the original data according to the drawing in the process of manufacturing the navigation map, the loss stopping cost is higher. In order to reduce the computational effort requirement on the data processing device and the damage stopping cost of errors in the drawing process, in the embodiment, the longer running track can be divided into a plurality of shorter sub-tracks first, so that the data size of corresponding original data is reduced.
In this embodiment, the value of the first dividing length may be a preset length value, and the preset length value may be a specific value or a value within a preset value range. The preset length value may be determined in combination with the road type, the topographical features of the region where the road is located, and the computational power consumption of the data processing device. Taking an urban main road as an example, if the terrain of the area where the road is located is flat, the water system distribution is concentrated, the situation that the difference between the road surface of the longer road and the surrounding environment is small may exist, and the longer length can be preset in a reasonable range, so that the drawing precision requirement is met, and meanwhile, the calculation power consumption of the data processing equipment is reduced. For example, the preset length value may be 3km, or the preset length value may take a value in a range of 3km to 5 km. If the terrain fluctuation of the area where the road is located is large, the water system distribution is scattered, and the situation that the difference between the road surface of the longer road and the surrounding environment is large may exist, the shorter length can be preset in a reasonable range so as to preferentially meet the drawing precision requirement. For example, the preset length value may be 2km, or the preset length value may take a value in a range of 1km to 2 km.
In some embodiments, the first partition length may also take a historical partition length value, or may take a simulated partition length value that is derived from training a machine learning algorithm model with the historical partition length. The embodiment of the present disclosure does not particularly limit the value of the first division length.
In the present embodiment, the travel track is divided into a plurality of sub-tracks according to the first division length, and the travel track having the first division length may be regarded as a sub-track each time the length of the travel track reaches the first division length by accumulating the length of the travel track from the start point or the end point of the travel track. Specifically, the travel track may be formed by connecting coordinate positions represented by the coordinate data in order of increasing time stamps, and therefore, the coordinate position represented by the coordinate data stored in the storage space corresponding to the minimum time stamp may be used as the start point of the travel track, and the coordinate position represented by the coordinate data stored in the storage space corresponding to the maximum time stamp may be used as the end point of the travel track. Taking the example that the first division length is 2km from the starting point of the running track, marking the coordinate positions represented by the coordinate data on a map, connecting a plurality of coordinate positions in the order of increasing time stamps, accumulating the distances between the adjacent coordinate positions to be used as the length of the running track, and taking the corresponding running track as a first sub-track when the length of the running track reaches 2 km.
In this embodiment, the driving track dividing process may be performed first, that is, after the driving track is divided into a plurality of sub-tracks after the dividing process is completed, the track expansion region generating process may be performed, that is, the corresponding track expansion regions may be generated according to the plurality of sub-tracks, respectively. In some embodiments, the driving track dividing process and the track expansion region generating process may be performed alternately, that is, after dividing the sub-track according to the driving track each time, the corresponding sub-track expansion region may be generated according to the sub-track.
And generating a corresponding track expansion region according to the shorter sub-track, and determining the track fragments and the corresponding track fragment data according to the sub-track expansion region, so that the data volume of the original data is reduced, and the power requirement on the data processing equipment and the damage stopping cost of errors in the drawing process are reduced.
In some embodiments, the indicating the partitioning rule may include: the length of the running track is not less than the sum of the first specified dividing length and the second specified dividing length; wherein the second specified partition length is less than the first specified partition length.
In the case where the length of the travel track is greater than the first division length, the travel track may be divided, and the second division length may be introduced to limit the length of the sub-track. The second dividing length is smaller than the first dividing length, and when the length of the running track is not smaller than the sum of the first dividing length and the second dividing length, the length of the sub track obtained by dividing the running track is not smaller than the second dividing length, so that the computational power resource consumed by the data processing equipment is reduced.
In this embodiment, the second dividing length may be a minimum dividing length, and the value of the second dividing length may be a preset length value, and the preset wide length value may be a specific value, or may be a value within a preset value range. For example, the preset length value may be 1km, or the preset length value may take a value in a range of 0.5km to 1 km. In some embodiments, the second partition length may also take a historical partition length value, or may take a simulated partition length value that is derived from training a machine learning algorithm model with the historical partition length. The embodiment of the present disclosure does not particularly limit the value of the second division length.
In some embodiments, the specified extension rule includes a specified extension width in a lateral direction with respect to a traveling direction of the traveling track represented by the traveling track data as a longitudinal direction; the step of generating a track expansion area according to a specified expansion rule with the travel track as a reference may include: and expanding the running track along the transverse direction by the specified expansion width by taking the running track as a reference to generate the track expansion area.
In the present embodiment, the traveling direction of the traveling locus may be a tangential direction of any point on the traveling locus, and the traveling direction may be a normal direction of any point on the traveling locus with respect to the traveling direction.
In some embodiments, the traveling direction of the traveling track may also be a connecting line direction of the start point and the end point of the traveling track. With the traveling direction as the longitudinal direction, the lateral direction with respect to the traveling direction may be a direction perpendicular to a line direction connecting the start point and the end point of the traveling locus.
In the present embodiment, when the traveling direction of the traveling track is a tangential direction of any point on the traveling track, the traveling track is extended in the lateral direction by the predetermined extension width to generate the track extension region based on the traveling track, and the plurality of coordinate positions constituting the traveling track may be moved to both sides by the predetermined extension width along the normal direction of each coordinate position, and the moved coordinate positions may be sequentially connected to form two extension boundaries of the track extension region. And connecting the end points of the two extension boundaries by two line segments respectively passing through the start point and the end point of the running track to form a track extension area. The values of the appointed expansion widths at the two sides can be the same or different.
In some embodiments, when the traveling direction of the traveling track is a direction connecting the start point and the end point of the traveling track, the traveling track is extended by the specified extension width in the lateral direction based on the traveling track to generate the track extended region, and the track extended region may be generated by translating the traveling track by the specified extension width in a direction perpendicular to the direction connecting the start point and the end point of the traveling track. The values of the appointed expansion widths at the two sides can be the same or different.
In some embodiments, the running track is extended by the designated extension width along the transverse direction to generate the track extension area by taking the running track as a reference, or the central line of the running track is determined first, and then the central line of the running track is translated by the designated extension width along the transverse direction to generate the track extension area. The values of the appointed expansion widths at the two sides can be the same or different. Specifically, the center line of the travel track may be determined by a wired method, an average method, or a median method. Specifically, a line connecting the start point and the end point of the travel track may be used as a center line of the travel track. The line connecting the start point and the end point of the travel track may be used as a reference line, an average value of distances from any point on the travel track to the reference line may be calculated, and a line obtained by translating the reference line by the average value distance in a direction perpendicular to the reference line may be used as a center line of the travel track. The median of the distance from any point on the travel track to the reference line may be calculated, and a line obtained by translating the reference line by the median distance in a direction perpendicular to the reference line may be used as a center line of the travel track.
And the running track is used as a reference, the running track is transversely expanded to generate a track expansion area, the association between the track expansion area and the running track is realized, and a basis is provided for determining track fragments and corresponding track fragment data.
In some embodiments, for any track extension area, the step of determining a track segment located in the track extension area and track segment data corresponding to the track segment may include: identifying, in the travel track data set, second travel track data in which the represented travel track is located in the track expansion area; wherein the second travel track data is used as the track segment data.
In the present embodiment, in the travel locus data set, the second travel locus data identifying that the indicated travel locus is located in the locus expansion area may include the following.
In the case where the travel locus data set includes travel locus data of one travel locus, the second travel locus data is the travel locus data itself.
In the case where the travel locus data set includes a plurality of travel locus data, in the case where the travel locus as the reference generation locus expansion region does not conform to the specified division rule, the second travel locus data may include the travel locus data itself corresponding to the travel locus as the reference generation locus expansion region and locus piece data corresponding to a locus piece located in the locus expansion region in the other travel locus.
In the case where the travel track as the reference generation track extension region meets the specified division rule, the second travel track data may include sub-track data corresponding to the sub-track as the reference generation track extension region and track fragment data corresponding to track fragments located within the track extension region of the other travel track.
And determining the track segment and the corresponding track segment data according to the second running track data in the track expansion area, so that the running track data reflecting the same road condition can be subjected to centralized processing, and the running track data processing efficiency is improved. Meanwhile, when the navigation map is manufactured according to the original data corresponding to the track fragment data, as the data according to the drawing can come from multiple acquisition tasks aiming at the same road, the possibility of error of the navigation map caused by data errors or incompleteness is reduced, and the accuracy of the navigation map is improved.
In some embodiments, in the travel track data set, the step of identifying second travel track data in which the represented travel track is located within the track extension area may include: constructing a track line of a running track represented by at least one piece of running track data in the running track data set; drawing a track expansion area of the running track by taking a track line corresponding to the running track as a reference; and identifying a track line which has an overlapping relation with the expansion area diagram, and taking the running track data corresponding to the track line as the second running track data.
By constructing the track line and the track expansion area, the visualization of the running track and the track expansion area is realized, and the identification of the running track data in the track expansion area can be realized through an image processing technology.
In some embodiments, for any track extension region, the step of determining track segments located within the track extension region and the track segment data may include: dividing the generated track expansion area into a plurality of target track expansion areas; track segment data located in each target track expansion area and track segment data corresponding to the track segments are respectively determined.
In the present embodiment, when the travel track data set includes only one travel track data of one-way travel, the track expansion region is generated from the travel track. When the travel track data set includes travel track data representing a plurality of incompletely overlapping travel tracks or the travel track data set includes travel track data representing a single travel track that travels back and forth on the same road, the track expansion regions may be generated based on the plurality of travel tracks or the single travel track, respectively, and then the track expansion regions corresponding to the plurality of travel tracks or the single travel track may be combined, and the combined track expansion regions may be used as the track expansion regions generated based on the travel track data set. Specifically, the track extension regions having the overlapping relationship may be merged.
In some embodiments, the step of dividing the generated track extension region into a plurality of target track extension regions may include: generating a sampling area at a designated position; taking the track expansion area overlapped with the sampling area as a pre-dividing area; determining the pre-divided region meeting a specified dividing condition as the target track expansion region; wherein the specified dividing condition includes a track segment located within the pre-dividing region and a length condition of a track segment located outside the pre-dividing region.
In the present embodiment, there may be a plurality of designated positions, and the sampling region may be generated at each designated position starting from the start point of the travel track. In the case where there is an overlap of the sampling region and the track extension region, the track extension region of the overlapping portion may be regarded as the pre-divided region. And judging whether the pre-divided area meets the specified dividing condition or not, and determining the pre-divided area meeting the specified dividing condition as a target track expansion area. Specifically, the specified division condition may be a length condition of a travel track located within the pre-divided area and a travel track located outside the pre-divided area. For example, if the length of both the travel locus located in the pre-divided area and the travel locus located outside the pre-divided area is greater than the third divided length, it may be determined that the pre-divided area satisfies the specified division condition. If any one of the travel tracks located in the pre-divided area and the travel tracks located outside the pre-divided area has a length smaller than the third divided length, it may be determined that the pre-divided area does not satisfy the specified division condition.
In this embodiment, the third division length may be a preset value, or may take a value within a preset data range. For example, the third division length may be 50m, or may take a value within a range of 50m to 60 m. In some embodiments, the third partition length may also be a historical partition length, or may be a simulated partition length that is derived from training a machine learning algorithm model with the historical partition length. Embodiments of the present disclosure do not specifically limit the third division length.
In case there is no overlap of the sampling area and the track extension area, the track extension area may not be pre-divided.
The generated track extension area may be divided into a plurality of target track extension areas by traversing a plurality of designated positions.
In some embodiments, the sampling area is generated at a specified position, and the sampling area may be generated by determining reference data according to a specified reference determination rule in the travel track data, and then using a position represented by the reference data as a reference according to a specified generation rule. Specifically, the position represented by the reference data may be a specified position. The specified reference determination rule may be used to indicate a specified length interval on the travel track indicated by the travel track data. For example, the specification reference determination rule may include determining a specified position every interval of a specified length from a start point or an end point of the travel track, and coordinate data corresponding to the specified position may be reference data. The specified length interval may be a preset value or may take a value within a preset data range. For example, the specified length interval may be 50m, or may take a value within a range of 50m to 60 m.
In some embodiments, the specified length interval may also be a historical length interval, or may be a simulated length interval resulting from training a machine learning algorithm model with the historical length interval. Embodiments of the present disclosure are not particularly limited to the specified length interval.
In the present embodiment, the specified generation rule includes: and establishing a sampling area with a specified shape by taking the specified position as a center. The specified shape includes a circle or a polygon. Specifically, for example, the designated shape is a circle, and the sampling area of the circle can be established according to the designated radius with the designated position as the center of the circle. The specified radius may be a preset value or may be a value within a preset data range. For example, the specified radius may be 500m, or may be a value in the range of 500m to 600 m.
In some embodiments, the specified radius may also be a historical radius, or may be a simulated radius that results from training a machine learning algorithm model with the historical radius. Embodiments of the present disclosure are not particularly limited to a specified radius.
In some embodiments, the data processing method further comprises: receiving a road sensing dataset corresponding to the travel track dataset; the road sensing data set comprises sensing data acquired in the process that a vehicle forms the running track; and extracting road sensing segment data corresponding to the track segment data under the condition that the track segment and the track segment data corresponding to the track segment are determined.
After the track segments and the corresponding track segment data in the same track expansion area are determined, road sensing data corresponding to the track segment data can be extracted so as to be used for manufacturing a navigation map with high requirements on precision and accuracy. The track segments in the same track expansion area can be a track segment of one running track, a multi-segment track segment of one running track, or different track segments of different running tracks, and if the coordinate positions are in the track expansion area, the track segments belong to the track expansion area, so that the track segments in the track expansion area can be collectively referred to as a track segment set.
In this embodiment, the road sensing data may include point cloud data, video data, picture data, etc. collected by the sensing device during formation of the driving track by the collection vehicle. Specifically, for example, during the running process of the acquisition vehicle, the road pavement and the surrounding environment can be scanned by the vehicle-mounted laser radar, and the road point cloud data is acquired; the road surrounding environment can be shot at the moment corresponding to each time stamp through the vehicle-mounted camera, and the road picture data are acquired.
In the present embodiment, a point cloud data set, a video data set, a picture data set, and the like may be taken out from the original data set, and the road sensing data set is composed of these data sets together. The data type and the data amount included in the road sensing data set are not particularly limited in the embodiments of the present disclosure.
In this embodiment, the road sensing segment data may include sensing data acquired by the acquisition vehicle in the process of forming the track segment corresponding to the track segment data.
The corresponding road sensing segment data is extracted according to the determined track segment data, and the road sensing segment data is extracted, so that the road sensing data is divided according to the driving track data, and the data amount required to be processed for executing one data processing task on the road sensing data according to the drawing is reduced when the navigation map with higher requirements on precision and accuracy is manufactured.
In addition, knowing the association relationship between each driving track and the corresponding road sensing data, the present disclosure may also generate an identifier of each track expansion region, and store the association relationship between the identifier of the track expansion region and all track segments in the track expansion region, then determine the road sensing data corresponding to all track segments in the track expansion region according to the identifier of the track expansion region, and generate the road map in the track expansion region according to the determined road sensing data. In addition, the present disclosure may further store the collected road sensing data by using the track extension area as a storage unit, and record an association relationship between the identifier of the track extension unit and the storage address of the road sensing data corresponding to the track extension unit, so that the corresponding road sensing data may be directly obtained according to the selected one or more track extension areas to generate the map of the corresponding area.
Example apparatus, electronic device, storage Medium, and software
Please refer to fig. 5. One embodiment of the present disclosure also provides a data processing apparatus, which may include: a receiving module 21 for receiving a travel track data set; wherein the travel track data set includes travel track data for representing a travel track of at least one vehicle. A generation module 22, configured to generate a track expansion area according to a specified expansion rule based on the travel track; wherein the track extension region has an extension boundary extending along the travel track; the specified extension rule is used for indicating a distance relation between an extension boundary of the track extension region and the running track. The determining module 23 is configured to determine, for any track extension area, a track segment located in the track extension area and track segment data corresponding to the track segment.
The specific functions and effects achieved by the apparatus may be explained in reference to other embodiments of the present disclosure, and are not described herein. The various modules in the data processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in hardware or independent of a processor in the computer equipment, and can also be stored in a memory in the computer equipment in a software mode, so that the processor can call and execute the operations corresponding to the modules.
Please refer to fig. 6. The disclosed embodiments also provide an electronic device, including a memory storing at least one computer program instruction and a processor implementing the data processing method of any of the above embodiments when the processor executes the at least one computer program instruction.
The electronic device may include a processor, a non-volatile storage medium, an internal memory, a communication interface, a display device, and an input device connected by a system bus. The non-volatile storage medium may store an operating system and associated computer program instructions.
The disclosed embodiments also provide a computer-readable storage medium having stored thereon computer program instructions which, when executed by a computer, cause the computer to perform the data processing method of any of the above embodiments.
It will be appreciated that the specific examples herein are intended only to assist those skilled in the art in better understanding the disclosed embodiments and are not intended to limit the scope of the invention.
It will be understood that, in various embodiments of the present disclosure, the sequence number of each process does not mean the order of execution, and the order of execution of each process should be determined by its functions and internal logic, and should not constitute any limitation on the implementation of the embodiments of the present disclosure.
It is to be understood that the various embodiments described in this disclosure may be implemented either alone or in combination, and that the disclosed embodiments are not limited in this regard.
Unless defined otherwise, all technical and scientific terms used in the embodiments of the present disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure pertains. The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present disclosure. The term "and/or" as used in this disclosure includes any and all combinations of one or more of the associated listed items. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It will be appreciated that the processor of embodiments of the present disclosure may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be implemented by integrated logic circuits of hardware in a processor or instructions in software form. The processor may be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (ApplicationSpecific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps and logic blocks of the disclosure in the embodiments of the disclosure may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present disclosure may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.
It will be appreciated that the memory in the embodiments of the disclosure may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (programmableROM, PROM), an erasable programmable read-only memory (erasablePROM, EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory, among others. The volatile memory may be Random Access Memory (RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system, apparatus and unit may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the present disclosure may be embodied in essence or a part contributing to the prior art or a part of the technical solutions, or in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present disclosure. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a read-only memory (ROM), a random-access memory (RAM), a magnetic disk, or an optical disk, etc.
The foregoing is merely specific embodiments of the disclosure, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the disclosure, and it is intended to cover the protection scope of the disclosure. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (16)

1. A method of data processing, comprising:
receiving a travel track data set; wherein the travel track data set includes travel track data for representing at least one travel track;
generating a track expansion area according to a specified expansion rule by taking the running track as a reference; wherein the track extension region has an extension boundary extending along the travel track; the specified extension rule is used for indicating the distance relation between the extension boundary of the track extension area and the running track;
for any track expansion area, determining track segments in the track expansion area and track segment data corresponding to the track segments, including:
determining a plurality of specified positions from the running track according to specified length intervals;
dividing the track expansion area into a plurality of target track expansion areas by traversing the plurality of designated positions;
track segments in each target track expansion area and road sensing data corresponding to the track segments are respectively determined, so that a map of a corresponding area is generated according to the road sensing data corresponding to each target track expansion area;
Wherein dividing the track extension region into a plurality of target track extension regions includes:
for each specified location, generating a sampling region at the specified location;
taking the track expansion area overlapped with the sampling area as a pre-dividing area;
determining the pre-divided region meeting a specified dividing condition as the target track expansion region; wherein the specified dividing condition includes a track segment located within the pre-dividing region and a length condition of a track segment located outside the pre-dividing region.
2. The method according to claim 1, wherein the method further comprises:
identifying first travel track data meeting specified screening conditions from the travel track data set;
dividing sub-track data conforming to a specified division rule from the first driving track data; the sub-track represented by the sub-track data is used as a reference, and a track expansion area is generated according to a specified expansion rule.
3. The method of claim 2, wherein the specified screening conditions include:
the length of the running track represented by the running track data is shortest; or alternatively, the process may be performed,
the time when the travel track data is generated is latest.
4. The method according to claim 2, wherein the step of generating a track expansion area based on the specified expansion rule with reference to the travel track, comprises:
dividing the travel track into a plurality of sub-tracks according to a first division length in response to the travel track conforming to a specified division rule; wherein the length of the sub-track is not greater than the first division length;
and respectively generating track expansion areas of the sub tracks according to the appointed expansion rules.
5. The method of claim 4, wherein the specified partitioning rule comprises:
the length of the running track is not less than the sum of the first dividing length and the second dividing length; wherein the second division length is smaller than the first division length.
6. The method according to claim 1, wherein the specified extension rule includes a specified extension width in a lateral direction with respect to a traveling direction of the traveling track indicated by the traveling track data as a longitudinal direction; the step of generating a track expansion area according to a specified expansion rule by taking the running track as a reference comprises the following steps:
and expanding the running track along the transverse direction by the specified expansion width by taking the running track as a reference to generate the track expansion area.
7. The method of claim 6, wherein the step of determining track segments located within the track extension area and track segment data corresponding to the track segments for any track extension area comprises:
identifying, in the travel track data set, second travel track data in which the represented travel track is located in the track expansion area; wherein the second travel track data is used as the track segment data.
8. The method of claim 7, wherein the step of identifying, in the travel track data set, second travel track data representing a travel track that is located within the track expansion area, comprises:
constructing a track line of a running track represented by at least one piece of running track data in the running track data set;
drawing a track expansion area of the running track by taking a track line corresponding to the running track as a reference;
and identifying a track line positioned in the track expansion area, and taking the running track data corresponding to the track line as the second running track data.
9. The method as recited in claim 2, further comprising:
And repeatedly executing the steps of identifying the first travel track data which accords with the specified screening condition from the travel track data set and dividing the sub-track data which accords with the specified extraction rule from the first travel track data until the travel track data in the travel track data set are completely divided under the condition that the travel track data still exist in the travel track data set.
10. The method of claim 1, wherein traversing the plurality of specified locations starts from a start point or an end point of the travel track and traverses the plurality of specified locations in a time-stamped order, and wherein the specified partitioning condition includes a length of the travel track within the pre-partitioned area and a length of the travel track outside the pre-partitioned area being greater than a third partitioned length.
11. The method of claim 10, wherein the step of generating the sampling area at the designated location comprises:
determining reference data in the travel track data according to a specified reference determination rule; wherein the position represented by the reference data is used as the specified position; the specified reference determination rule is used for indicating a specified length interval on a running track represented by the running track data;
And generating the sampling area by taking the position represented by the reference data as a reference according to a specified generation rule.
12. The method of claim 11, wherein the specified generation rule comprises: generating a sampling area with a specified shape by taking the specified position as a center; wherein the specified shape includes: circular or polygonal.
13. The method according to claim 1, wherein the method further comprises:
receiving a road sensing dataset corresponding to the travel track dataset; the road sensing data set comprises sensing data acquired in the process that a vehicle forms the running track;
and extracting road sensing segment data corresponding to the track segment data under the condition that the track segment and the track segment data corresponding to the track segment are determined.
14. A data processing apparatus, comprising:
the receiving module is used for receiving the driving track data set; wherein the travel track data set includes travel track data for representing at least one travel track;
the generation module is used for generating a track expansion area according to a specified expansion rule by taking the running track as a reference; the track extension region has an extension boundary extending along the travel track; the specified extension rule is used for indicating the distance relation between the extending boundary of the track extension area and the running track;
The determining module is used for determining track fragments positioned in the track expansion area and track fragment data corresponding to the track fragments aiming at any track expansion area;
the determination module is further to:
determining a plurality of specified positions from the running track according to specified length intervals;
dividing the track expansion area into a plurality of target track expansion areas by traversing the plurality of designated positions;
track segments in each target track expansion area and road sensing data corresponding to the track segments are respectively determined, so that a map in the corresponding target track expansion area is generated according to the road sensing data;
wherein dividing the track extension region into a plurality of target track extension regions includes:
for each specified location, generating a sampling region at the specified location;
taking the track expansion area overlapped with the sampling area as a pre-dividing area;
determining the pre-divided region meeting a specified dividing condition as the target track expansion region; wherein the specified dividing condition includes a track segment located within the pre-dividing region and a length condition of a track segment located outside the pre-dividing region.
15. An electronic device comprising a memory and a processor, wherein the memory stores at least one computer program instruction that is loaded and executed by the processor to implement the data processing method of any of claims 1 to 13.
16. A computer-readable storage medium comprising,
the computer readable storage medium having stored therein at least one computer program instruction which, when executed by a processor, is capable of implementing a data processing method according to any of claims 1 to 13.
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