CN111435450A - Road data processing method and device - Google Patents
Road data processing method and device Download PDFInfo
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- CN111435450A CN111435450A CN201910026465.7A CN201910026465A CN111435450A CN 111435450 A CN111435450 A CN 111435450A CN 201910026465 A CN201910026465 A CN 201910026465A CN 111435450 A CN111435450 A CN 111435450A
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Abstract
The application discloses a road data processing method and a device thereof, wherein the method comprises the steps of determining a multi-source data fusion mode corresponding to a road, wherein the multi-source data fusion mode comprises information of a plurality of data sources for executing data fusion and a fusion method for executing the data fusion aiming at the data sources; acquiring multi-source road data corresponding to the plurality of data sources from road data corresponding to a road; and performing data fusion on the multi-source road data by using the fusion method to generate fusion data. By adopting the method and the device, the fusion data related to the road can be generated, the data related to the road are enriched, and the road analysis is conveniently executed by utilizing the fusion data in the follow-up process.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a road data processing method and apparatus.
Background
When urban traffic is described by using road data, if only a single data source is used, the complete urban traffic cannot be provided for a user, and the single data source has a risk of providing wrong information due to misoperation and the like. If it is desired to better construct the urban traffic system, a plurality of management departments and information systems thereof are usually involved, for example, information such as road data of various road surface facility systems of an industry management unit, and therefore, the data volume of the urban traffic data source is large and the data format is diversified. Therefore, a method for performing fusion processing on road data of a plurality of data sources is required.
Disclosure of Invention
One of the main objectives of the present application is to provide a method and an apparatus for processing road data, which are used to solve the above-mentioned technical problem of performing fusion processing on road data of multiple data sources.
An exemplary embodiment of the present application provides a road data processing method, the method including: determining a multi-source data fusion mode corresponding to a road, wherein the multi-source data fusion mode comprises information of a plurality of data sources for executing data fusion and a fusion method for executing the data fusion aiming at the data sources; acquiring multi-source road data corresponding to the plurality of data sources from road data corresponding to a road; and performing data fusion on the multi-source road data by using the fusion method to generate fusion data.
Another exemplary embodiment of the present application provides a computer-readable storage medium having stored thereon computer instructions, wherein the instructions, when executed, implement the above-described method.
Another exemplary embodiment of the present application provides a road data processing apparatus, including: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the steps of: determining a multi-source data fusion mode corresponding to a road, wherein the multi-source data fusion mode comprises information of a plurality of data sources for executing data fusion and a fusion method for executing the data fusion aiming at the data sources; acquiring multi-source road data corresponding to the plurality of data sources from road data corresponding to a road; and performing data fusion on the multi-source road data by using the fusion method to generate fusion data.
Another exemplary embodiment of the present application provides a road data processing apparatus, including: the system comprises a determining module, a data fusion module and a data fusion module, wherein the determining module is used for determining a multi-source data fusion mode corresponding to a road, and the multi-source data fusion mode comprises information of a plurality of data sources for executing data fusion and a fusion method for executing the data fusion aiming at the data sources; the acquisition module is used for acquiring multi-source road data corresponding to the data sources from the road data corresponding to the road; and the generating module is used for performing data fusion on the multi-source road data by using the fusion method to generate fusion data.
The above-mentioned at least one technical scheme that this application example embodiment adopted can reach following beneficial effect:
according to the road data processing method, the road data from different data sources related to the road can be obtained by the multi-source data fusion method, and the road data are subjected to fusion processing, so that the fusion data related to the road can be generated, the data related to the road are enriched, and the road analysis can be conveniently executed by using the fusion data subsequently.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a scene diagram of road data processing according to an exemplary embodiment of the present application;
FIG. 2 is a flowchart of a road data processing method according to an exemplary embodiment of the present application;
fig. 3 is a block diagram of a road data processing device according to an exemplary embodiment of the present application;
fig. 4 is a block diagram of a road data processing apparatus according to another exemplary embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Before describing exemplary embodiments of the present application, terms referred to in the present application will be explained first to facilitate better understanding of the present application by those skilled in the art.
The Road Identification (RID) is identification information indicating a road, which may be a road between intersections, and a road between intersections. In the application, the road data and the road mark can be correspondingly stored, so that when the road data of different data sources represent the same road, the road data can be identified and stored by using the road mark.
The road profile information is information related to roads acquired in units of roads corresponding to the RID, and includes, for example, infrastructure information on roads, traffic route information on roads, and traffic event information on roads. In the present application, the generated road fusion data may be used to form road grade information for the road data.
Turning to the drawings, wherein like reference numerals refer to like elements, the principles of the present application are illustrated as being implemented in a suitable computing environment. The following description is based on illustrated embodiments of the application and should not be taken as limiting the application with regard to alternative embodiments that are not explicitly described herein. In order to more clearly describe the exemplary embodiments of the present application, the following explanation will be made in conjunction with the accompanying drawings.
Fig. 1 is a scene diagram illustrating road data processing applied to an exemplary embodiment of the present application. As shown in fig. 1, the road data processing system includes a server group 100 as a data provider and a server 200 that processes data provided by the server group 100. It should be noted that the road data processing system may also comprise other devices, such as a communication base station, but components not relevant to the inventive concept will be omitted here in order to avoid obscuring the present embodiment due to well-known methods, procedures, components and circuits.
Although the server group 100 shown in fig. 1 may include the server 101, the server 102, and the server 103, and the number of the servers 200 is one, it should be noted that the number of the servers is merely exemplary, and the user may increase the number of the servers according to a need in actual use.
The servers 101 to 103 may transmit the road data stored in the respective databases to the server 200, wherein the road data transmitted by different servers may have different formats due to different storage formats, and specifically, different traffic systems operating on different servers, and the formats of the road data stored in these systems are different, for example, the data storage formats in the navigation class application and the traffic police system are different for the same road event. Accordingly, the server 200 may perform conversion on road data in a data conversion manner corresponding to a data source after receiving the road data from a different server.
In this process, different roads may be identified by road identifiers, so that the road data of the same road may be mapped with the road to form road profile information of the road in the following. Subsequently, the server 200 performs a fusion process on the data by using the road profile information of the same road, that is, describes the same road by using the road data of different data sources, and specifically, the attribute information of the road can be described by using the address data of a single data source and can also be described by using the data of different data sources.
An exemplary road data processing method according to the present application will be described in detail below with reference to fig. 2. Before describing FIG. 2, it should be noted that the road data described in the present application may determine various attribute information on the road. Determining attribute information for the road using road data may include determining certain attributes on the road using data from a single data source, for example, a vehicle license plate on the road may be directly obtained using a traffic data source, which may be directly determined according to the prior art and will not be described in detail herein. When the road is described using data of a plurality of data sources, a road data processing method according to an exemplary embodiment of the present application as will be described below may be performed.
As shown in fig. 2, in step S210, a multi-source data fusion manner corresponding to a road is determined, where the multi-source data fusion manner includes information of a plurality of data sources performing data fusion and a fusion method performing data fusion for the plurality of data sources. According to an exemplary embodiment of the present application, data of different data sources may describe the same road, that is, different road data for the same road is included in different data sources.
Based on this, before performing step S210, the acquired data for the road from different data sources may be respectively converted into standard road data as road data corresponding to the road according to the data sources, wherein the road data may be data about the road acquired from different data sources, wherein the different data sources may include, but are not limited to, an internet data source, a video data source, and road data acquired by a traffic detector.
Specifically, a data source of the acquired road data may be determined, and then may be converted into standard road data according to a conversion method corresponding to the data source, wherein the standard road data represents data of each road in terms of road identification. Based on this, a road identification may be assigned to the road to be processed before the road data conversion is performed. That is, the standard road data includes identification information of the road. For example, when the acquired road data is passing data on a road with respect to RID1 from a video, the road data may be converted into (RID1, license plate number, vehicle type, passing time).
According to the exemplary embodiment of the present application, in the case that the data source includes, but is not limited to, an internet data source, a video data source, and a traffic data source, the data fusion manner may include a multi-source fusion manner of any two or more of the internet data source, the video data source, and the traffic data source. The traffic data source may be data acquired by a traffic police system, for example, the traffic data source may include data acquired by a gate camera and traffic light timing data of the road. The internet data source may be data obtained from various internet applications, such as vehicle positioning data obtained from navigation applications.
Therefore, a multi-source data fusion mode for performing mutual fusion between different data sources may be preset, in other words, a data fusion mode for performing fusion on road data of different types of data sources may be preset according to the type of the data source, and after road data of a certain road about a plurality of data sources is acquired, the multi-source data fusion mode corresponding to the road may be directly determined according to the type of the data source in step S210. By using the method, after an event related to the road occurs, the road data related to the event can be extracted, the multi-source data fusion mode is determined according to the type of the data source of the road data related to the event, and the event is described in a standardized way. Further, the description data about the event may be different in different data sources, and after the multi-source data fusion mode is determined, the event may be described according to a unified standard, for example, a standardized description of the flow correction information may be obtained according to a fusion mode of an internet data source and a video data source. Further, various attribute information of the event, such as an intersection ID, a lane ID, a vehicle ID, and the like, may also be determined using the fusion data.
In step S220, multi-source road data corresponding to the plurality of data sources is acquired from road data corresponding to a road. Specifically, in the case where the multi-source data fusion manner corresponding to the road has been determined in step S210, the data source has been determined, and based on this, the multi-source road data from the determined data source corresponding to the determined data source may be acquired from the road data. It should be noted that the multi-source road data is road data including a plurality of data sources.
Finally, in step S230, data fusion is performed on the multi-source road data by using the fusion method, so as to generate fusion data. Specifically, data for a certain attribute is extracted from the multi-source road data by the fusion method, and then fusion is performed on the data by the fusion method, so as to obtain fused data for the attribute, that is, the fused data has a field of attribute information of the road.
For example, when the data fusion mode is a fusion mode of an internet data source and a video data source, fusion processing may be performed by using vehicle positioning data acquired in internet application and vehicle passing data of a gate in the video data source to generate fusion data. Optionally, flow correction information on the road may be determined from the fused data. That is, the vehicle positioning data is compared with the passing vehicle data information to determine the flow rate correction information. Specifically, vehicle positioning data and bayonet vehicle passing data in a fixed period for the same road are acquired, and then the ratio of the vehicle positioning data to the bayonet vehicle passing data is acquired and used as flow correction information. It should be noted that the longer the fixed period of time, the more reliable the data, and therefore, in practice, the vehicle positioning data and the bayonet passing data can be acquired monthly.
In addition, fusion processing can be performed by using traffic light timing data acquired by a traffic system and clock data in a video data source to generate fusion data, and optionally, a clock deviation value corresponding to the road can be determined according to the fusion data. Specifically, the clock information in the traffic light timing system and the clock information in the video data source may be biased due to lack of calibration, and a clock rectification operation may be performed on the clock information before it is determined, as follows: traversing each numerical value in [ -150,150] by a traffic light timing system, selecting any lane at a certain intersection by taking the numerical value as a clock deviation value and combining a traffic light timing scheme, and calculating a vector of the lane during (7: 00-9: 00) (7200 seconds is used as a vector, the green-yellow light value is 1, and the red light is 0); and vectors are made for the bayonet data in the video data in the same time period (a vehicle is 1, and no vehicle is 0). And performing inner product on the two vectors, so that the value with the maximum inner product is the clock deviation value.
Optionally, in order to obtain the vehicle track data on the road, the standard road data may be processed by using a track-related data fusion method. That is, after determining a data fusion method related to a trajectory, extracting road data corresponding to the data fusion method from road data according to the data fusion method, and finally, processing the part of road data by using the data fusion method, specifically, determining vehicle trajectory data corresponding to a vehicle trajectory passing through the road by using a traffic data source, and then supplementing the vehicle trajectory by using an internet data source, that is, splitting the vehicle trajectory according to a proportion by using travel time corresponding to the vehicle in the internet data, calculating time information of the vehicle passing through each intersection according to the split time, and inserting the time information into the vehicle trajectory, thereby forming complete vehicle trajectory data. It can be seen that the multi-source data fusion mode can describe events and/or attributes related to the same road by using data from different data sources, and a road archive taking the road as a unit is formed.
An application scenario in which an exemplary embodiment of the present application may be implemented will be described below, and when a user desires to view information of a certain road using a display screen of an electronic terminal (e.g., a mobile terminal), the request may be sent to a device that performs the method. After the device obtains the request, the device can obtain data of all data sources of the road, for example, first road data of a first data source, second road data of a second data source and third road data of a third data source, and then at least two road data of the first road data, the second road data and the third road data can be respectively subjected to fusion processing by using the method, so that a plurality of fusion data can be obtained, and finally different attribute information of the road can be obtained by using the fusion data. The apparatus may transmit these attribute information to the electronic terminal so that the user can visually check the condition of the road through the electronic terminal, for example, can check the complete vehicle trajectory of the vehicle running on the road.
In summary, according to the road data processing method of the exemplary embodiment of the present application, the multi-source data fusion mode may be used to perform fusion processing on data of multiple data sources, so as to describe the road more fully, and in the process of determining attribute information of the road by using multiple data sources, different fusion algorithms may be used to generate different attribute information, so as to mine deeper attribute information from multiple data sources, greatly enrich road files for the road, and facilitate subsequent road analysis. Furthermore, the flow correction information and the vehicle track information of the road can be obtained by utilizing a multi-source fusion mode of an internet data source and a video data source.
In order to more clearly understand the inventive concept of the exemplary embodiment of the present application, a block diagram of the apparatus to acquire a traffic flow of the exemplary embodiment of the present application will be described below with reference to fig. 3. Those of ordinary skill in the art will understand that: the apparatus in fig. 3 shows only components related to the present exemplary embodiment, and common components other than those shown in fig. 3 are also included in the apparatus.
Fig. 3 illustrates a road data processing apparatus according to an exemplary embodiment of the present application, and as described in fig. 3, the road data processing apparatus 300 includes a determination module 310, an acquisition module 320, and a generation module 330. The determining module 310 determines a multi-source data fusion mode corresponding to a road, where the multi-source data fusion mode includes information of a plurality of data sources performing data fusion and a fusion method performing data fusion for the plurality of data sources. The obtaining module 320 obtains multi-source road data corresponding to the plurality of data sources from road data corresponding to a road. The generating module 330 performs data fusion on the multi-source road data by using the fusion method to generate fusion data.
Optionally, the apparatus may further include an attribute determining module (not shown), and the attribute determining module may determine the attribute information of the road according to the fusion data.
Optionally, the apparatus may further include a conversion module (not shown) configured to convert the acquired data for the road from the different data sources into standard road data as road data corresponding to the road, respectively, according to the data sources.
Optionally, the apparatus may further comprise: a storage module (not shown) that stores the road data (the standard road data described above) in correspondence with the identification information of the road.
Optionally, the apparatus may further comprise: a conversion module (not shown) for converting the acquired data for the road from different data sources into standard road data as road data corresponding to the road according to the data sources, respectively.
Optionally, the multi-source data fusion mode includes a multi-source fusion mode of any two or more data sources of an internet data source, a video data source and a traffic data source.
Optionally, the determining module 310 may determine that the multi-source data fusion mode corresponding to the road is a multi-source fusion mode of an internet data source and a video data source. Subsequently, the obtaining module 320 may obtain, from the road data, vehicle positioning information corresponding to the internet data source and vehicle passing data at the gate corresponding to the video data source as multi-source road data. The generating module 330 may generate the fusion data of the road by using the vehicle positioning information and the bayonet vehicle passing data according to a multi-source fusion mode of the internet data source and the video data source. Optionally, the determine attributes module may determine flow correction information for the road using the fused data.
Optionally, the determining module 310 may determine that the multi-source data fusion mode corresponding to the road is a multi-source fusion mode of a traffic data source and a video data source. The obtaining module 320 may obtain, from the road data, vehicle trajectory data corresponding to vehicles passing through the road corresponding to the traffic data source and vehicle data of the vehicles corresponding to the video data source as multi-source road data. The generating module 330 may perform supplementary processing on the vehicle trajectory data using the vehicle data to generate fused data corresponding to the road. Optionally, the determine attributes module may determine vehicle trajectory information for the road using the fused data.
In summary, the road data processing apparatus according to the exemplary embodiment of the present application may perform the fusion processing on the data of multiple data sources by using a multi-source data fusion manner, so as to describe the road more fully, and in the process of determining the attribute information of the road by using multiple data sources, different fusion algorithms may be used to generate different attribute information, so as to mine deeper attribute information from multiple data sources, greatly enrich the road profile for the road, and facilitate the subsequent road analysis. Furthermore, the traffic correction information of the road can be obtained by utilizing a multi-source fusion mode of a traffic data source and a video data source, and the vehicle track information can be obtained by utilizing the multi-source fusion mode of the traffic data source and the video data source.
Fig. 4 is a block diagram of a road data processing apparatus according to another exemplary embodiment of the present application. Referring to fig. 4, the apparatus includes, at a hardware level, a processor, an internal bus, and a computer-readable storage medium, wherein the computer-readable storage medium includes volatile memory and non-volatile memory. The processor reads the corresponding computer program from the non-volatile memory and then runs it. Of course, besides the software implementation, the present application does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or logic devices.
Specifically, the processor performs the following operations: determining a multi-source data fusion mode corresponding to a road, wherein the multi-source data fusion mode comprises information of a plurality of data sources for executing data fusion and a fusion method for executing the data fusion aiming at the data sources; acquiring multi-source road data corresponding to the plurality of data sources from road data corresponding to a road; and performing data fusion on the multi-source road data by using the fusion method to generate fusion data.
Optionally, the processor further includes, after the executing step uses the fusion method to perform data fusion on the multi-source road data to generate fused data: and determining the attribute information of the road according to the fusion data.
Optionally, before the step of obtaining the multi-source road data corresponding to the plurality of data sources from the road data corresponding to the road, the processor further includes: and respectively converting the acquired data aiming at the road from different data sources into standard road data as road data corresponding to the road according to the data sources.
Optionally, the processor further performs storing the road data in correspondence with identification information of the road.
Optionally, the multi-source data fusion mode includes a multi-source fusion mode of any two or more data sources of an internet data source, a video data source and a traffic data source.
Optionally, the determining, by the processor in the executing step, a multi-source data fusion mode corresponding to the road includes: and determining that the multi-source data fusion mode corresponding to the road is the multi-source fusion mode of the internet data source and the video data source.
Optionally, the processor, in the implementing step, acquiring multi-source road data corresponding to the plurality of data sources from road data corresponding to a road includes: and acquiring vehicle positioning information corresponding to the internet data source and vehicle passing data corresponding to the video data source from the road data to serve as multi-source road data.
Optionally, the processor, in the implementation step, performing data fusion on the multi-source road data by using the fusion method to generate fusion data includes: and generating the fusion data of the road by utilizing the vehicle positioning information and the bayonet vehicle passing data according to the multi-source fusion mode of the internet data source and the video data source.
Optionally, the processor, after the step of generating the fused data of the road by using the vehicle positioning information and the bayonet vehicle passing data, further includes: and determining flow correction information of the road by using the fusion data.
Optionally, the determining, by the processor in the implementation step, a multi-source data fusion mode corresponding to the road includes: and determining that the multi-source data fusion mode corresponding to the road is a multi-source fusion mode of a traffic data source and a video data source.
Optionally, the processor, in the implementing step, acquiring multi-source road data corresponding to the plurality of data sources from road data corresponding to a road includes: and acquiring vehicle track data corresponding to vehicles passing through the road corresponding to the traffic data source and vehicle data of the vehicles corresponding to the video data source from the road data as multi-source road data.
Optionally, the processor, in the implementation step, performing data fusion on the multi-source road data by using the fusion method to generate fusion data includes: and performing supplementary processing on the vehicle track data by using the vehicle data to generate fused data corresponding to the road.
Optionally, after the step of generating the fused data corresponding to the road, the processor further includes: and determining vehicle track information of the road by using the fusion data.
In summary, the road data processing apparatus according to the exemplary embodiment of the present application may perform the fusion processing on the data of multiple data sources by using a multi-source data fusion manner, so as to describe the road more fully, and in the process of determining the attribute information of the road by using multiple data sources, different fusion algorithms may be used to generate different attribute information, so as to mine deeper attribute information from multiple data sources, greatly enrich the road profile for the road, and facilitate the subsequent road analysis. Furthermore, the traffic correction information of the road can be obtained by utilizing a multi-source fusion mode of an internet data source and a video data source, and the vehicle track information can be obtained by utilizing a multi-source fusion mode of a traffic data source and a video data source.
It should be noted that the execution subjects of the steps of the method provided in embodiment 1 may be the same device, or different devices may be used as the execution subjects of the method. For example, the execution subject of steps 21 and 22 may be device 1, and the execution subject of step 23 may be device 2; for another example, the execution subject of step 21 may be device 1, and the execution subjects of steps 22 and 23 may be device 2; and so on.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (16)
1. A method of road data processing, comprising:
determining a multi-source data fusion mode corresponding to a road, wherein the multi-source data fusion mode comprises information of a plurality of data sources for executing data fusion and a fusion method for executing the data fusion aiming at the data sources;
acquiring multi-source road data corresponding to the plurality of data sources from road data corresponding to a road;
and performing data fusion on the multi-source road data by using the fusion method to generate fusion data.
2. The method of claim 1, wherein generating fused data by performing data fusion on the multi-source road data using the fusion method further comprises:
and determining the attribute information of the road according to the fusion data.
3. The method of claim 1, further comprising, prior to obtaining multi-source road data corresponding to the plurality of data sources from road data corresponding to a road:
and respectively converting the acquired data aiming at the road from different data sources into standard road data according to the data sources, and taking the standard road data as the road data corresponding to the road.
4. The method of claim 1, further comprising:
and the road data and the identification information of the road are correspondingly stored.
5. The method of claim 1, wherein the multi-source data fusion mode comprises a multi-source data fusion mode of any two or more of an internet data source, a video data source, and a traffic data source.
6. The method of claim 1, wherein determining a multi-source data fusion mode corresponding to a road comprises:
and determining that the multi-source data fusion mode corresponding to the road is the multi-source data fusion mode of an internet data source and a video data source.
7. The method of claim 6, wherein obtaining multi-source road data corresponding to the plurality of data sources from road data corresponding to a road comprises:
and acquiring vehicle positioning data corresponding to the internet data source and vehicle passing data corresponding to the video data source from the road data to serve as multi-source road data.
8. The method of claim 7, wherein performing data fusion on the multi-source road data using the fusion method to generate fused data comprises:
and generating the fusion data of the road by utilizing the vehicle positioning information and the bayonet vehicle passing data according to the multi-source fusion mode of the internet data source and the video data source.
9. The method of claim 8, wherein generating fused data for the roadway using vehicle positioning information and bayonet pass data further comprises:
and determining flow correction information of the road by using the fusion data.
10. The method of claim 1, wherein determining a multi-source data fusion mode corresponding to a road comprises:
and determining that the multi-source data fusion mode corresponding to the road is a multi-source data fusion mode of a traffic data source and a video data source.
11. The method of claim 10, wherein obtaining multi-source road data corresponding to the plurality of data sources from road data corresponding to a road comprises:
and acquiring vehicle track data corresponding to vehicles passing through the road corresponding to the traffic data source and vehicle data of the vehicles corresponding to the video data source from the road data as multi-source road data.
12. The method of claim 11, wherein performing data fusion on the multi-source road data using the fusion method to generate fused data comprises:
and performing supplementary processing on the vehicle track data by using the vehicle data to generate fused data corresponding to the road.
13. The method of claim 12, wherein generating fused data corresponding to the link further comprises:
and determining vehicle track information of the road by using the fusion data.
14. A computer readable storage medium having computer instructions stored thereon that, when executed, implement the method of any of claims 1 to 13.
15. A road data processing apparatus, comprising:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method of any of claims 1 to 13.
16. A road data processing apparatus, comprising:
the system comprises a determining module, a data fusion module and a data fusion module, wherein the determining module is used for determining a multi-source data fusion mode corresponding to a road, and the multi-source data fusion mode comprises information of a plurality of data sources for executing data fusion and a fusion method for executing the data fusion aiming at the data sources;
the acquisition module is used for acquiring multi-source road data corresponding to the data sources from the road data corresponding to the road;
and the generating module is used for performing data fusion on the multi-source road data by using the fusion method to generate fusion data.
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