CN114993329A

CN114993329A - Road data updating method and device

Info

Publication number: CN114993329A
Application number: CN202210720605.2A
Authority: CN
Inventors: 柯海帆; 刘延龙; 孙丰岩; 刘�东
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2022-06-23
Filing date: 2022-06-23
Publication date: 2022-09-02

Abstract

The application belongs to the technical field of computers, and particularly relates to a road data updating method and device. The embodiment of the application can be applied to the field of maps. The method comprises the following steps: acquiring road element data uploaded by a first terminal; comparing the road element data with pre-stored road element data corresponding to a preset road section; when the comparison results are different, acquiring road image data uploaded by the second terminal; and updating the pre-stored road image data according to the road image data uploaded by the second terminal. The technical scheme of the embodiment of the application can improve the transmission efficiency and save the transmission flow.

Description

Road data updating method and device

Technical Field

The application belongs to the technical field of computers, and particularly relates to a road data updating method and a road data updating device.

Background

With the rapid development of map identification technology, people have higher and higher requirements for map navigation scene information, so that various elements in a road scene need to be identified and marked, so that a user or a terminal can know the current driving state or scene state.

In the related art, when updating road data, a large amount of field data needs to be continuously collected so as to obtain the latest map elements in real time, thereby ensuring the timeliness of the map. However, since the data volume of the field data is large, it takes a large amount of traffic to complete the transmission of the field data, and the transmission efficiency is slow and the real-time performance is poor.

Therefore, how to improve the data transmission efficiency in the road data updating process is an urgent technical problem to be solved.

Disclosure of Invention

The present application aims to provide a road data updating method and apparatus, which at least to some extent solves the technical problem of how to improve the data transmission efficiency in the road data updating process in the related art.

Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.

According to an aspect of an embodiment of the present application, there is provided a road data updating method, including:

acquiring road element data uploaded by a first terminal; the road element data are data obtained by the first terminal performing image acquisition and element identification on a preset road section on a map;

comparing the road element data with pre-stored road element data corresponding to the preset road section; the pre-stored road element data is road element data obtained by carrying out element identification on pre-stored road image data;

when the comparison results are different, acquiring road image data uploaded by a second terminal, wherein the road image data is obtained by image acquisition of the preset road section; the second terminal is the same or different terminal equipment as the first terminal;

and updating the pre-stored road image data according to the road image data uploaded by the second terminal.

carrying out image acquisition and element identification on a preset road section on a map to obtain road element data;

uploading the road element data to a cloud, wherein the road element data is used for instructing the cloud to compare the road element data with prestored road element data corresponding to the preset road section; the pre-stored road element data is obtained by the cloud end performing element identification on pre-stored road image data;

and when the comparison results are different, acquiring the road image data corresponding to the preset road section, and transmitting the acquired road image data back to the cloud end to update the pre-stored road element data corresponding to the preset road section.

According to an aspect of embodiments of the present application, there is provided a road data updating apparatus, the apparatus including:

a road element acquisition module configured to acquire road element data uploaded by a first terminal; the road element data are data obtained by the first terminal performing image acquisition and element identification on a preset road section on a map;

a comparison module configured to compare the road element data with pre-stored road element data corresponding to the preset section; the pre-stored road element data is road element data obtained by carrying out element identification on pre-stored road image data;

the road image data acquisition module is configured to acquire road image data uploaded by a second terminal when the comparison results are different, wherein the road image data is obtained by acquiring images of the preset road section; the second terminal is the same or different terminal equipment as the first terminal;

and the road image data updating module is configured to update the pre-stored road image data according to the road image data uploaded by the second terminal.

In some embodiments of the present application, based on the above technical solutions, the road data updating apparatus further includes:

a track data acquisition unit configured to acquire track data of the first terminal, the track data being travel track data of the first terminal when acquiring the road image data;

the mapping relation establishing unit is configured to establish a mapping relation between the road element data and the track points according to the time stamps of the road image data corresponding to the road element data and the time stamps of the track points on the track data;

the preset road section determining unit is configured to determine a preset road section on the map corresponding to the road element data according to the mapping relation between the road element data and the track points;

a pre-stored road element acquisition unit configured to acquire pre-stored road element data corresponding to a preset link on the map.

In some embodiments of the present application, based on the above technical solutions, the comparison module includes:

a cache road element acquisition unit configured to acquire cache road element data; the cached road element data is road element data which is historically returned and cached by a third terminal and corresponds to the preset road section;

a target road element data determination unit configured to perform quantity statistics on the quantity of the road element data under each road element type according to the road element type of the road element data and the road element type of the cache road element data, and determine target road element data according to a statistical result;

a comparison unit configured to compare the target road element data with pre-stored road element data corresponding to the preset link.

In some embodiments of the present application, based on the above technical solutions, the comparison unit includes:

a confidence degree operator unit configured to calculate a confidence degree of the target road element according to the number of road element data in the road element type of the target road element data in the statistical result;

a second comparison subunit configured to compare the target road element data having the confidence level greater than a preset threshold value with pre-stored road element data corresponding to the preset road segment.

In some embodiments of the present application, based on the above technical solutions, the target road element data determination unit includes:

a track similarity calculation subunit configured to calculate track similarities of the road element data and the cache road element data according to the track points mapped by the road element data and the track points mapped by the cache road element data;

a statistical list determining subunit configured to add the cached road element data, of which the track similarity with the road element data is greater than a preset threshold, to a statistical list;

and the target road element data determining subunit performs quantity statistics on the quantity of the road element data under each road element type according to the road element type of the road element data and the road element type of the road element data in the statistical list, and determines the target road element data according to the statistical result.

a track matching unit configured to track-match the road element data with pre-stored road element data corresponding to the preset section;

a matching data determination unit configured to determine the road element data having a trajectory matching relationship with the pre-stored road element data as matching data;

a first operation unit configured to compare road element data in the matching data with pre-stored road element data when there is data having a track matching relationship with the road element data in the pre-stored road element data;

and a second operation unit configured to acquire road image data uploaded by the second terminal and update the pre-stored road image data according to the road image data uploaded by the second terminal when there is no data having a track matching relationship with the road element data in the pre-stored road element data.

and the third operation unit is configured to change the verification tag of the pre-stored road element data into the verified state when the comparison results are the same and the verification tag of the pre-stored road element data is in the to-be-verified state.

According to an aspect of an embodiment of the present application, a road data updating method is provided. The method comprises the following steps:

uploading the road element data to a cloud, wherein the road element data is used for instructing the cloud to compare the road element data with prestored road element data corresponding to the preset road section; the pre-stored road element data is road element data obtained by performing element identification on pre-stored road image data by the cloud;

According to an aspect of an embodiment of the present application, there is provided a road data updating apparatus. The device comprises:

the road element data acquisition module is configured to acquire images and identify elements of a preset road section on a map to obtain road element data;

a road element data uploading module configured to upload the road element data to a cloud, the road element data being used to instruct the cloud to compare the road element data with pre-stored road element data corresponding to the preset road segment; the pre-stored road element data is obtained by the cloud end performing element identification on pre-stored road image data;

and the road image data updating module is configured to acquire the road image data corresponding to the preset road section when the comparison results are different, and return the acquired road image data to the cloud end to update the pre-stored road element data corresponding to the preset road section.

According to an aspect of an embodiment of the present application, there is provided a computer-readable medium on which a computer program is stored, the computer program, when executed by a processor, implementing a road data updating method as in the above technical solution.

According to an aspect of an embodiment of the present application, there is provided an electronic apparatus including: a processor; and a memory for storing executable instructions for the processor; wherein the processor is configured to execute the road data updating method as in the above technical solution via executing the executable instructions.

According to an aspect of an embodiment of the present application, there is provided a computer program product or a computer program, the computer program product or the computer program comprising computer instructions, the processor of the computer device executes the computer instructions, so that the computer device executes the road data updating method according to any one of the above technical solutions.

In the technical scheme provided by the embodiment of the application, the road element data uploaded by the first terminal is acquired, the road element data is compared with prestored road element data corresponding to a preset road section, when the comparison results are different, the road image data uploaded by the second terminal is acquired, and the prestored road image data is updated according to the road image data uploaded by the second terminal; so, can compare with prediction road element data through the road element data with terminal collection, when the contrast result is inequality, also when needing to update the high in the clouds data, upload the road image data that the terminal was gathered to the high in the clouds again. It can be understood that the data amount of the road element data is much smaller than the data amount of the corresponding road image data. Therefore, the defects of flow waste and low transmission efficiency caused by indiscriminate uploading of all collected road image data by the terminal can be avoided, the transmission efficiency can be improved, and the transmission flow is saved. ' Qiyi

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.

Fig. 1 schematically shows a block diagram of an exemplary device architecture to which the solution of the present application applies.

Fig. 2 schematically illustrates a flowchart of steps of a road data update method according to some embodiments of the present application.

Fig. 3 schematically shows a flowchart of steps before comparing road element data with pre-stored road element data corresponding to a preset road segment in an embodiment of the present application.

Fig. 4 schematically shows a detailed flowchart of road data update according to an embodiment of the present application.

Fig. 5 schematically shows a schematic diagram of inserting road element data into trajectory data.

Fig. 6 schematically shows a flowchart of steps for comparing road element data with pre-stored road element data corresponding to a preset road segment in an embodiment of the present application.

Fig. 7 schematically shows a flowchart of steps for comparing road element data with pre-stored road element data corresponding to a predetermined section in an embodiment of the present application.

Fig. 8 schematically shows a detailed flowchart of road data update according to an embodiment of the present application.

Fig. 9 schematically shows a flowchart of steps for comparing target road element data with pre-stored road element data corresponding to a preset road segment in an embodiment of the present application.

Fig. 10 is a flowchart schematically illustrating a procedure of performing quantity statistics on the quantity of road element data in each road element type according to the road element type of the road element data and the road element type of the cache road element data, and determining target road element data according to the statistical result in an embodiment of the present application.

Fig. 11 is a flow chart schematically illustrating steps of a road data updating method according to another embodiment of the present application.

Fig. 12 is a block diagram schematically illustrating a road data updating apparatus according to some embodiments of the present disclosure.

Fig. 13 is a block diagram schematically illustrating a road data updating apparatus according to another embodiment of the present application.

Fig. 14 schematically shows a structural block diagram of a computer system of an electronic device for implementing the embodiment of the present application.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the application.

The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.

The flowcharts shown in the figures are illustrative only and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

Before describing the technical solutions of the road data updating method and the road data updating apparatus provided in the embodiments of the present application in detail, the cloud technology related in some embodiments of the present application will be briefly described.

Cloud computing (cloud computing) is a computing model that distributes computing tasks over a pool of resources formed by a large number of computers, enabling various application systems to obtain computing power, storage space, and information services as needed. The network that provides the resources is referred to as the "cloud". Resources in the "cloud" appear to the user as being infinitely expandable and available at any time, available on demand, expandable at any time, and paid for on-demand.

As a basic capability provider of cloud computing, a cloud computing resource pool (cloud platform, generally referred to as IaaS a Service (Infrastructure as a Service) platform is established, and multiple types of virtual resources are deployed in the resource pool and are selectively used by external clients.

According to the logic function division, a PaaS (Platform as a Service) layer can be deployed on an IaaS (Infrastructure as a Service) layer, a SaaS (Software as a Service) layer is deployed on the PaaS layer, and the SaaS can be directly deployed on the IaaS. PaaS is a platform on which software runs, such as a database, a web container, etc. SaaS is a variety of business software, such as web portal, sms group sender, etc. Generally speaking, SaaS and PaaS are upper layers relative to IaaS.

The so-called artificial intelligence cloud Service is also generally called AIaaS (AI as a Service, chinese). The method is a service mode of an artificial intelligence platform, and particularly, the AIaaS platform splits several types of common AI services and provides independent or packaged services at a cloud. This service model is similar to the one opened in an AI theme mall: all developers can access one or more artificial intelligence services provided by the platform through an API (application programming interface), and part of the qualified developers can also use an AI framework and an AI infrastructure provided by the platform to deploy and operate and maintain the self-dedicated cloud artificial intelligence services.

The system related to the embodiment of the present application may be a distributed system formed by a client, a plurality of nodes (any form of computing devices in an access network, such as servers and terminal devices) connected through a network communication form.

The following describes a road data updating method, a corresponding device, and the like provided by the present application in detail with reference to specific embodiments.

Fig. 1 schematically shows a block diagram of an exemplary device architecture to which the technical solution of the present application is applied.

As shown in fig. 1, the apparatus architecture 100 may include a terminal device 110, a network 120, and a server 130. The terminal device 110 may include various electronic devices such as a smart phone, a tablet computer, a notebook computer, and a desktop computer. The server 130 may be an independent physical server, a server cluster or a distributed device configured by a plurality of physical servers, or a cloud server providing cloud computing services. Network 120 may be a communication medium of various connection types capable of providing a communication link between terminal device 110 and server 130, such as a wired communication link or a wireless communication link.

The device architecture in the embodiments of the present application may have any number of terminal devices, networks, and servers, according to implementation needs. For example, the server 130 may be a server group composed of a plurality of server devices. In addition, the technical solution provided in the embodiment of the present application may be applied to the terminal device 110, or may be applied to the server 130, or may be implemented by both the terminal device 110 and the server 130, which is not particularly limited in this application.

For example, the server 130 may execute the road data updating method provided by the present application, obtain the road element data uploaded by the first terminal, compare the road element data with the pre-stored road element data corresponding to the preset road segment, obtain the road image data uploaded by the second terminal when the comparison result is different, and update the pre-stored road image data according to the road image data uploaded by the second terminal; so, can compare with prediction road element data through the road element data with terminal collection, when the contrast result is inequality, also when needing to update the high in the clouds data, upload the road image data that the terminal was gathered to the high in the clouds again. It can be understood that the data amount of the road element data is much smaller than the data amount of the corresponding road image data. Therefore, the defects of traffic waste and low transmission efficiency caused by indiscriminate uploading of all acquired road image data by the terminal can be avoided, the updating flow of road data can be optimized, the transmission efficiency is improved, and the transmission traffic is saved. In addition, the cloud server does not need to identify and process mass road image data indiscriminately, so that computing resources of the cloud server can be saved, and computing processing resources of the terminal can be fully utilized.

Or the terminal device may execute the road data updating method provided by the application to perform image acquisition and element identification on a preset road section on the map to obtain road element data; uploading the road element data to a cloud end, wherein the road element data is used for instructing the cloud end to compare the road element data with prestored road element data corresponding to a preset road section; and when the comparison results are different, acquiring the road image data corresponding to the preset road section, and returning the acquired road image data to the cloud end to update the pre-stored road element data corresponding to the preset road section. Therefore, the defects of flow waste and low transmission efficiency caused by indiscriminate uploading of all collected road image data by the terminal can be avoided, the updating flow of road data can be optimized, the transmission efficiency is improved, and the transmission flow is saved.

The following describes the road data updating method provided by the present application in detail with reference to specific embodiments.

Fig. 2 schematically illustrates a flowchart of steps of a road data update method according to some embodiments of the present application. The execution main body of the road data updating method can be a server or a service cloud, a cloud end and the like, and the method is not limited in the application. The embodiment of the invention can be applied to various scenes, including but not limited to map recognition, road network data production, cloud technology, artificial intelligence, intelligent traffic, driving assistance and the like.

It is understood that in the specific implementation of the present application, when the related data of the user is used, when the above embodiments of the present application are applied to specific products or technologies, the related user permission or consent needs to be obtained, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.

As shown in fig. 2, the road data updating method may mainly include the following steps S210 to S240.

S210, acquiring road element data uploaded by a first terminal; the road element data is data obtained by the first terminal performing image acquisition and element identification on a preset road section on the map.

Specifically, the first terminal includes, but is not limited to, a mobile phone, a computer, an intelligent voice interaction device, an intelligent appliance, a vehicle-mounted terminal, an aircraft, and the like. In a specific embodiment, the first terminal may be a vehicle event data recorder.

The first terminal can acquire the road image data by carrying out image acquisition on the preset road section on the map through the shooting equipment. The road image data is data obtained by image acquisition of a preset road section. Then, the first terminal may perform element recognition on the road image data through the processor to obtain road element data. In some embodiments, the processor may be pre-configured with a pre-trained road element recognition model. The road image data is input to a pre-trained road element recognition model, and road element data corresponding to the road image data can be obtained, wherein the road element data may include a road element type of the road element data and a confidence level of the road element type. In some embodiments, the road element data may be vector data.

In some embodiments, the vehicle-mounted terminal may acquire an image of a preset road segment on a map to obtain road video data, and then perform frame-cutting processing on the video data to obtain road image data with a timestamp. In some embodiments, the vehicle-mounted terminal may perform image acquisition on a preset road segment on a map at preset intervals to obtain road image data with a timestamp.

In some embodiments, the vehicle-mounted terminal may detect its own driving track data on the map, and obtain track data including a plurality of time-stamped track points.

Specifically, the road element type of the road element data and the confidence of the road element type may be represented by the following fields:

score 90.0, # confidence

1001, type, highest limit speed 30

Here, the field "label" is 1001 indicating that the road element type of the road element data is the signpost of the "highest speed limit 30", and the field "score" indicates that the confidence of the signpost of the road element type of the road element data is 90% of the signpost of the "highest speed limit 30".

The road element identification model may further comprise an adjustable confidence threshold R by which data below the confidence threshold R in the road element data output by the road element identification model can be culled and only road element data with a confidence level above the confidence threshold R is output. In a specific embodiment, the value adjustment of the confidence threshold R may be adjusted correspondingly by the number of calls to the road element recognition model.

Specifically, the road element identification model may be created based on a machine learning model such as an Fcos (full volumetric One-Stage Object Detection) model, a Fast R-CNN model, or a Mask R-CNN model, and the pre-training of the road element identification model is implemented by using a calibration result of an image historically acquired on the vehicle-mounted device as a training set.

In some embodiments, a lightweight SDK (Software Development Kit) of a road element recognition model trained by using an Fcos first-order full convolution detection algorithm may be implanted into a mainstream Android version system, a Linux system, and various other small systems through adaptation of an end-side system version, so as to conveniently implement implantation of an element recognition function in a terminal device.

Therefore, the first terminal has the capacity of element identification, so that for a road needing to acquire road data, the first terminal can perform element identification to obtain road element data, vector information of the road element data can be uploaded to the cloud, so that the road element data can be compared with pre-stored road element data of a preset road section in the cloud mother library at the cloud, if the map information of the preset road section is determined to have changed and the image data is required to be subjected to subsequent processing, an image data return command is issued, the first terminal or other vehicle-mounted terminals acquire and return image data and track information of the preset road section, and only return image data before and after the changed map information position, namely image data located in the preset road section, so that accurate acquisition of a map information element change point is realized, and the flow cost can be reduced to the greatest extent, and the updating efficiency of the map elements is improved.

In some embodiments, the cloud may generate a road data acquisition task for a preset road segment that needs to be subjected to road data acquisition, and set an acquisition cycle requirement and an acquisition coverage requirement for the road data acquisition task. Specifically, the acquisition cycle requires that for a preset road section, at least one road data acquisition is required every preset cycle. The covering times requirement is that at least the preset times are required to be collected at all for a preset road section, and the cloud-end mother database on-line can be carried out on the relevant results obtained according to the collected road data.

Specifically, a road section ID can be set for each road section on the mother base map of the cloud, so that identification management of each road section is realized. Specifically, still can be for in the road element data of prestoring of mother's storehouse, the road element data of prestoring on each highway section sets up the best identification point that corresponds on the highway section to and the offset that this best identification point corresponds on the highway section, thereby can realize issuing data acquisition instruction so that the terminal carries out data acquisition and passback in accurate place, and then can save the transmission flow, promote data transmission efficiency, realize the accurate update of high in the clouds data.

In some embodiments, the road element data may further include information such as a driving direction angle of the vehicle in which the vehicle-mounted terminal is located, and may assist in determining the optimal recognition point corresponding to the road element data.

In some embodiments, the identification ID of the vehicle is generated by the vehicle-mounted terminal, and the vehicle is bound and then uploaded to the cloud for use, so that data collected by the subsequent vehicle is bound with the identification ID, and management of the terminal is achieved. Thus, privacy confidentiality of the vehicle and the user can be improved.

S220, comparing the road element data with pre-stored road element data corresponding to a preset road section; the pre-stored road element data is road element data obtained by performing element recognition on pre-stored road image data.

Before comparing the road element data with the pre-stored road element data corresponding to the preset section at step S220, the following steps may be further included:

and judging the usability of the road element data according to the integrity and the continuity of the track data corresponding to the road element data.

That is, after it is determined that the road element data is available, the step of comparing the road element data with the pre-stored road element data corresponding to the preset link of step S220 is performed.

Specifically, the determining the availability of the road element data according to the integrity and continuity of the track data corresponding to the road element data may include the following steps:

when the track data corresponding to the road element data is complete and continuous, judging that the road element data is available;

when the track data corresponding to the road element data has more than a preset number of missing points, judging that the road element data is unavailable;

and when the track data corresponding to the road element data has more than the preset number of jumping points, judging that the road element data is unavailable.

Therefore, after the availability of the track of the road element data is determined, the step of comparing the road element data with the pre-stored road element data corresponding to the preset road section in the step S220 is executed, so that the accuracy of updating the road data can be improved, and the pollution of the interference data to the mother database of the road data in the cloud can be avoided.

Fig. 3 schematically shows a flowchart of steps before comparing road element data with pre-stored road element data corresponding to a preset road segment in an embodiment of the present application. As shown in fig. 3, on the basis of the above embodiment, the following steps S310 to S340 may be further included before comparing the road element data with the pre-stored road element data corresponding to the preset link at step S220.

S310, acquiring track data of the first terminal, wherein the track data is driving track data of the first terminal when the first terminal collects road image data;

s320, establishing a mapping relation between the road element data and the track points according to the time stamps of the road image data corresponding to the road element data and the time stamps of the track points on the track data;

s330, determining a preset road section on a map corresponding to the road element data according to the mapping relation between the road element data and the track points;

and S340, acquiring prestored road element data corresponding to a preset road section on the map.

Therefore, mapping matching of the road element data and the track points can be achieved, and data corresponding to the road element data uploaded by the first terminal can be found conveniently in the cache road element data and the pre-stored road element data.

Fig. 4 schematically illustrates a detailed flowchart of road data update according to an embodiment of the present application. As shown in fig. 4, after the device side uploads the road element data obtained by element recognition of the road image data and the track data of the device when the road image data corresponding to the road element data is collected to the cloud side, the cloud side determines the preset road segment on the map corresponding to the road element data according to the track point mapped by the road element data. Then, the acquisition task service unit of the cloud end confirms that the preset road section is in the range of the current preset acquisition task of the cloud end, so that the road element data in the cloud end mother library is inquired according to the preset road section, and the pre-stored road element data corresponding to the preset road section on the map is obtained. And comparing the pre-stored road element data with the road element data uploaded by the terminal to obtain a comparison result and outputting the comparison result to the acquisition task service unit. When the comparison results are different, the acquisition task service unit determines that image acquisition is required, and then issues a command to a terminal (the terminal can be the same as or different from the terminal which originally uploads the road element data) so that the terminal acquires images of a preset road section and uploads the acquired road image data and track data of equipment during acquisition of the road image data. And finally, the cloud end stores the acquired road image data into the mother library in an information storage mode, and updates the pre-stored road image data in the mother library according to the acquired road image data.

The collection task that the high in clouds was predetermine can be artifical predetermine, predetermine or the risk degree of road element predetermines according to the disappearance of the road element of high in clouds, and this application does not do special restriction to this.

In a specific implementation manner, the road element data can be inserted into the track data according to the mapping relationship between the road element data and the track points to obtain the comprehensive data, and the comprehensive data is uploaded to the cloud. For the road element data uploaded by the first terminal, the road element type with the largest quantity of road element data in the track data of the preset road section is the road element identification result of the preset road section, and the road element identification result is the road element type of the road element data uploaded by the first terminal.

In some embodiments, the road element data may be inserted between two track points adjacent to the time stamp of the road element data according to the chronological order of the time stamp of the road element data and the time stamp of the track point on the track data. As shown in fig. 5, fig. 5 schematically shows a schematic diagram of inserting road element data into track data, and the road element data is inserted into the middle of the track points corresponding to two timestamps "22" and "25" adjacent to the timestamp "23" of the road element data according to the precedence order of the timestamp "23" of the road element data and the timestamps of the track points on the track data.

Fig. 6 schematically shows a flowchart of steps for comparing road element data with pre-stored road element data corresponding to a preset road segment in an embodiment of the present application. As shown in fig. 6, on the basis of the above embodiment, comparing the road element data with the pre-stored road element data corresponding to the preset link at step S220 may further include the following steps S610 to S640.

S610, carrying out track matching on the road element data and prestored road element data corresponding to a preset road section;

s620, determining the road element data with the track matching relationship and prestored road element data as matching data;

s630, when data with a track matching relationship with the road element data exists in the pre-stored road element data, comparing the road element data in the matching data with the pre-stored road element data;

and S640, when the data which has a track matching relationship with the road element data does not exist in the pre-stored road element data, acquiring the road image data uploaded by the second terminal, and updating the pre-stored road image data according to the road image data uploaded by the second terminal.

Therefore, when data with a track matching relationship with the road element data does not exist in the pre-stored road element data, namely when it is stated that part of the road elements possibly lack in the cloud terminal mother bank, the road image data uploaded by the second terminal is obtained, and the pre-stored road image data is updated according to the road image data uploaded by the second terminal, so that completion of the road element data and the road image data which lack in the cloud terminal mother bank can be achieved, and accurate updating of the road data of the cloud terminal is achieved. Specifically, the road data of the cloud includes pre-stored road element data and pre-stored road image data of the cloud.

In some embodiments, after comparing the road element data with the pre-stored road element data corresponding to the preset road segment in step S220 based on the above example, the following steps may be further included:

and when the comparison results are the same and the verification tag of the pre-stored road element data is in the to-be-verified state, changing the verification tag of the pre-stored road element data into the verified state.

In some embodiments, when the collection period requirement or the coverage number requirement of the pre-stored road element data is not met or has a related data defect, the pre-stored road element data may be set to a to-be-verified state. And when the comparison result is determined to be the same and the verification tag of the pre-stored road element data is in the to-be-verified state in the road data acquisition and updating process, the verification tag of the pre-stored road element data is changed into the verified state. Therefore, continuous verification and updating of the cloud road data can be achieved, and the accuracy of the cloud road data can be improved.

In some embodiments, for the pre-stored road element data and the pre-stored road image data of the high-risk road section such as a sharp turn, a high-speed entrance, an intersection, and the like, when the comparison result between the road element data and the pre-stored road element data corresponding to the preset road section is different, the road image data uploaded by the second terminal is acquired, that is, the image data is acquired and verified through the device side. From this, can realize the risk management and control to the high risk highway section, avoid the condition of the road element disappearance or the mistake of high risk highway section, can promote the degree of accuracy of high in the clouds road data.

S230, when the comparison results are different, acquiring road image data uploaded by a second terminal, wherein the road image data is data obtained by image acquisition of a preset road section; the second terminal is the same or different terminal device as the first terminal.

In some embodiments, the second terminal may be a first terminal, and the first terminal uploads road image data obtained by image acquisition on a preset road segment on the map, that is, road image data corresponding to the road element data, to the cloud.

In some embodiments, the second terminal is different from the first terminal, that is, the cloud terminal issues the data acquisition command, and after receiving the data acquisition command, the second terminal performs image acquisition on a preset road segment on the map to obtain road image data, and uploads the acquired road image data to the cloud terminal.

Compared with road element data, the road image data has more detailed road data, but the data volume of the road image data is much larger than that of the road element data, so that the uploading road image data has a large demand for transmission flow. According to the method and the device, only when the comparison result is different, the road image data uploaded by the second terminal is obtained, the transmission flow can be saved, and the transmission efficiency is improved.

In a specific implementation manner, when the comparison results are different, the cloud generates an image frame-capturing order of the device side, the order is issued to a second terminal running in a pre-order section of the preset road section, and when the second terminal passes through the preset road section, the second terminal finishes image acquisition of the preset road section and returns the image to the cloud.

And S240, updating the pre-stored road image data according to the road image data uploaded by the second terminal.

Specifically, the pre-stored road image data is updated according to the road image data uploaded by the second terminal, or the latest road image data is obtained by performing fusion processing according to the road image data uploaded by the second terminal and the pre-stored road image data, and the latest road image data is uploaded to the cloud mother bank as the latest version of the pre-stored road image data. In some embodiments, other ways may also be adopted to update the pre-stored road image data according to the road image data uploaded by the second terminal, which is not particularly limited in this application.

In the related art, the full amount of tracks and image data of the device can be returned for the road requiring data collection, however, actually, most of the uploaded image data is invalidated by the automatic processing and filtering and the manual processing because the map information on the road is not changed, which results in high traffic cost required for data return, high server cost required for automatic processing, and high labor cost.

According to the method and the device, the road element data are obtained by carrying out influence collection and element identification on the road image data, the road element data are compared with the prestored road element data of the preset road section in the cloud parent bank, when the comparison result of the road element data and the prestored road element data corresponding to the preset road section is different, the road image data uploaded by the second terminal are obtained, namely when the comparison result of the road element data which are returned are determined to be changed compared with the parent bank data, a new data collection mode of the road image data return is carried out. Therefore, accurate collection of map information element change points can be achieved, flow cost can be reduced to the greatest extent, map element updating efficiency is improved, and resource consumption of a cloud server is reduced.

It can be understood that if all the collected image data are returned to the cloud end without difference, a large amount of transmission flow and a large amount of transmission bandwidth are caused, meanwhile, the image processing calculation amount of the cloud end is also very large, and as the cloud scale is continuously enlarged, the cloud end calculation resources which are possibly very large are needed, and the bottleneck of the cloud end calculation processing capacity is easily met.

On the image processing demand that this application embodiment will concentrate high in the clouds processing dispersed the mobile unit, after the road key element data passback contrast of equipment, just confirm when the contrast result is inequality and carry out the collection of road image data to when can greatly reduced transmission flow, can save high in the clouds computational resource. Therefore, in practical case application, the total consumption of data acquisition flow is only 30% of the total consumption of all acquired image data returned to the cloud end in the related technology without difference, and the consumption of cloud end resources is only 25% of the total consumption of all acquired image data returned to the cloud end in the related technology without difference.

In some embodiments, the pre-stored road image data is updated according to the road image data uploaded by the second terminal in S240, and the road element recognition may be performed again at the cloud end according to the updated pre-stored road image data, so as to obtain the updated road element data.

Fig. 7 schematically shows a flowchart of steps for comparing road element data with pre-stored road element data corresponding to a preset road segment in an embodiment of the present application. As shown in fig. 7, on the basis of the above embodiment, comparing the road element data with the pre-stored road element data corresponding to the preset link at step S220 may further include the following steps S710 to S730.

S710, obtaining cache road element data; the cached road element data is road element data which is historically returned and cached by the third terminal and corresponds to a preset road section;

s720, according to the road element types of the road element data and the road element types of the cache road element data, carrying out quantity statistics on the quantity of the road element data under each road element type, and determining target road element data according to the statistical result;

and S730, comparing the target road element data with pre-stored road element data corresponding to a preset road section.

In some embodiments, when the cached road element data in the cloud does not have the road element data corresponding to the preset road segment, the road element data uploaded by the first terminal is cached in the cloud as the cached road element data, so that when the subsequent road element data uploaded by other terminals is prepared, the cached road element data uploaded by the first terminal and other cached road element data are matched and retrieved to determine the target road element data.

In some embodiments, when the number of the road element data corresponding to the preset road section in the cloud is less than the preset number, the road element data uploaded by the first terminal is cached in the cloud as cached road element data, so that when other subsequent terminals upload the road element data and the number of the road element data corresponding to the preset road section reaches the preset number, the cached road element data uploaded by the first terminal and other cached road element data are matched and retrieved to determine the target road element data.

Therefore, the target road element data are determined through the road element data uploaded by the plurality of terminal devices, the road element data uploaded by the plurality of terminal devices can be fused and counted, the accuracy of the road element data is determined, and then the pre-stored road element data corresponding to the preset road section are compared according to the target road element data, so that the difference comparison between the pre-stored data and the current data is realized, and the accurate updating of the road data at the cloud end is realized.

It can be understood that the reference of an equipment acquisition result is weaker, and the identification result of multiple equipment has extremely strong reliability, so that the above embodiment carries out quantity statistics after the cache road element data of the preset road section cached at the cloud end is accumulated to a certain amount through the characteristic of crowdsourcing acquisition, and the accurate and reliable identification of the road elements is realized.

Fig. 8 schematically shows a detailed flowchart of road data update according to an embodiment of the present application. As shown in fig. 8, after the terminal side generates the identification ID, the identification ID is uploaded to the cloud, so that verification and management of data returned by the terminal are realized through the identification ID. After the terminal reports the track data to the cloud, the cloud performs road network matching on a map according to the track data to obtain a preset road section of the track data uploaded by the terminal. And the terminal uploads the track data and simultaneously uploads a real-time identification result of the road element, namely the road element data to the cloud. The cloud end obtains corresponding cache road element data according to a preset road section, performs quantity statistics on the quantity of the road element data under each road element type according to the road element type of the road element data and the road element type of the cache road element data, and determines target road element data according to a statistical result. And then, the cloud determines pre-stored road element data corresponding to the preset road section according to the preset road section, and compares the target road element data with the pre-stored road element data. And when the comparison result is different, issuing a video frame-cutting order to the terminal (here, the terminal may be the same as or different from the terminal which originally uploads the road element data). After the terminal receives the video frame-cutting order, the frame-cutting processing can be performed on the video of the road image data corresponding to the preset road section, which is collected by the terminal, or the packing processing can be performed on the image of the road image data corresponding to the preset road section, which is collected by the terminal, so that the road image data can be obtained. After the obtained road image data are uploaded to the cloud end by the terminal, the cloud end carries out data storage on the road image data and updates the prestored road image data according to the road image data, so that the cloud end road data are updated.

Fig. 9 is a flowchart schematically illustrating a step of comparing target road element data with pre-stored road element data corresponding to a predetermined section in an embodiment of the present application. As shown in fig. 9, on the basis of the above embodiment, comparing the target road element data of step S730 with the pre-stored road element data corresponding to the preset link may further include the following steps S910 to S920.

S910, calculating the confidence coefficient of the target road element according to the quantity of the road element data under the road element type of the target road element data in the statistical result;

and S920, comparing the target road element data with the confidence coefficient greater than a preset threshold value with pre-stored road element data corresponding to a preset road section.

It can be understood that the actual road is complex, so that the quality of the road elements obtained by actual influence acquisition and element identification is high or low, the target road element data with the confidence coefficient smaller than the preset threshold value indicates that the data accuracy meets the end, the target road element data with the confidence coefficient larger than the preset threshold value is compared with the pre-stored road element data corresponding to the preset road section, the confidence coefficient of the target road data can be screened, and the condition that the database data is polluted by inaccurate road element data can be prevented.

Fig. 10 is a flowchart schematically illustrating a procedure of performing quantity statistics on the quantity of road element data in each road element type according to the road element type of the road element data and the road element type of the cache road element data, and determining target road element data according to the statistical result in an embodiment of the present application. As shown in fig. 10, on the basis of the above embodiment, the step S720 of performing quantity statistics on the quantity of the road element data in each road element type according to the road element type of the road element data and the road element type of the cache road element data, and determining the target road element data according to the statistical result may further include the following steps S1010 to S1030.

S1010, calculating the track similarity of the road element data and the cache road element data according to the track points mapped by the road element data and the track points mapped by the cache road element data;

s1020, adding the cached road element data with the track similarity larger than a preset threshold value to a statistical list;

and S1030, carrying out quantity statistics on the quantity of the road element data under each road element type according to the road element type of the road element data and the road element type of the road element data in the statistical list, and determining the target road element data according to the statistical result.

Therefore, track points mapped by the road element data of the vehicle-mounted terminal are gathered into a line, and the track similarity is calculated, so that the cache road element data which is positioned in the preset road section and accurately corresponds to the road element data uploaded by the first terminal can be accurately identified from the cache road element data cached at the cloud end, and accurate element data comparison is realized.

In some embodiments, the trajectory similarity calculation may be implemented by DTW (Dynamic Time Warping, Dynamic Time Warping algorithm); in some embodiments, the track similarity calculation may also be implemented by other algorithms, which is not limited in this application.

In some embodiments, the cloud end can perform key acquisition on a region with a demand based on the missing condition of the road elements, namely, perform acquisition tasks with higher frequency and more coverage times, reduce acquisition frequency for a region with a low demand, avoid the continuous cost investment of an invalid road section, and improve the improvement efficiency of the road data of the cloud end.

In some embodiments, as in the above technical solutions, the step of comparing the road element data with the pre-stored road element data corresponding to the preset road segment in step S220 may be performed at a terminal in addition to the cloud.

When the step of comparing the road element data with the pre-stored road element data corresponding to the preset road section in step S220 is performed at the cloud, the data transmission flow can be saved, and the data transmission efficiency can be improved. When the step of comparing the road element data with the pre-stored road element data corresponding to the preset road section in step S220 is performed at the terminal, the cloud computing power can be saved, and the utilization rate of the computing power of the terminal can be improved.

In some embodiments, as in the above technical solution, the steps from step S710 to step S730 may be performed in a cloud, or may be performed in a terminal.

When the steps from step S710 to step S730 are performed in the cloud, the data transmission traffic can be saved, and the data transmission efficiency can be improved. When the steps from step S710 to step S730 are performed in the terminal, the computing power at the cloud can be saved, and the utilization rate of the computing power of the terminal can be improved.

Fig. 11 is a flow chart schematically illustrating steps of a road data updating method according to another embodiment of the present application. The execution main body of the road data updating method can be a vehicle-mounted terminal, a mobile terminal, a handheld terminal and the like, and the method is not limited in the application. The terminal includes, but is not limited to, a mobile phone, a computer, an intelligent voice interaction device, an intelligent household appliance, a vehicle-mounted terminal, an aircraft, and the like. The embodiment of the invention can be applied to various scenes, including but not limited to map recognition, road network data production, cloud technology, artificial intelligence, intelligent traffic, driving assistance and the like.

As shown in fig. 11, the road data updating method may mainly include the following steps S1110 to S1130.

S1110, carrying out image acquisition and element identification on a preset road section on a map to obtain road element data;

s1120, uploading the road element data to a cloud end, wherein the road element data are used for instructing the cloud end to compare the road element data with prestored road element data corresponding to a preset road section; the pre-stored road element data is road element data obtained by performing element identification on pre-stored road image data by a cloud;

and S1130, when the comparison results are different, acquiring the road image data corresponding to the preset road section, and transmitting the acquired road image data back to the cloud end to update the pre-stored road element data corresponding to the preset road section.

It should be noted that, a specific technical scheme of the road data updating method in which the execution main body is the terminal side such as the vehicle-mounted terminal, the mobile terminal, and the handheld terminal is similar to the above specific technical scheme of the road data updating method in which the execution main body is the server, the service cloud, or the cloud, etc., which is only different in explanation angle, and the description is not repeated here.

It should be noted that although the various steps of the methods in this application are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the shown steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

The following describes embodiments of the apparatus of the present application, which may be used to perform corresponding road data updating methods in the above-described embodiments of the present application.

Fig. 12 is a block diagram schematically illustrating a road data updating apparatus according to some embodiments of the present disclosure. As shown in fig. 12, the road data updating device 1200 includes:

a road element acquisition module 1210 configured to acquire road element data uploaded by a first terminal; the road element data is data obtained by the first terminal performing image acquisition and element identification on a preset road section on the map;

a comparison module 1220 configured to compare the road element data with pre-stored road element data corresponding to a preset section; the pre-stored road element data is road element data obtained by carrying out element identification on pre-stored road image data;

the road image data acquisition module 1230 is configured to acquire road image data uploaded by the second terminal when the comparison results are different, where the road image data is data obtained by performing image acquisition on a preset road segment; the second terminal is the same or different terminal equipment as the first terminal;

the road image data updating module 1240 is configured to update the pre-stored road image data according to the road image data uploaded by the second terminal.

a track data acquisition unit configured to acquire track data of the first terminal, the track data being travel track data of the first terminal when acquiring road image data;

the preset road section determining unit is configured to determine a preset road section on a map corresponding to the road element data according to the mapping relation between the road element data and the track points;

a pre-stored road element acquisition unit configured to acquire pre-stored road element data corresponding to a pre-set link on a map.

a cache road element acquisition unit configured to acquire cache road element data; the cached road element data is road element data which is historically returned and cached by the third terminal and corresponds to a preset road section;

a target road element data determination unit configured to perform quantity statistics on the quantity of the road element data under each road element type according to the road element type of the road element data and the road element type of the cache road element data, and determine the target road element data according to the statistical result;

a comparison unit configured to compare the target road element data with pre-stored road element data corresponding to a preset section.

a confidence degree operator unit configured to calculate the confidence degree of the target road element according to the number of the road element data of the road element type of the target road element data in the statistical result;

and a second comparison subunit configured to compare the target road element data with the confidence level greater than the preset threshold value with pre-stored road element data corresponding to a preset road segment.

the track similarity calculation operator unit is configured to calculate the track similarity of the road element data and the cache road element data according to the track points mapped by the road element data and the track points mapped by the cache road element data;

a statistical list determining subunit configured to add the cached road element data, of which the trajectory similarity with the road element data is greater than a preset threshold, to a statistical list;

the target road element data determining subunit performs quantity statistics on the quantity of the road element data under each road element type according to the road element type of the road element data and the road element type of the road element data in the statistical list, and determines the target road element data according to the statistical result.

a track matching unit configured to track-match the road element data with pre-stored road element data corresponding to a preset section;

a matching data determination unit configured to determine road element data having a trajectory matching relationship with pre-stored road element data as matching data;

and a second operation unit configured to acquire the road image data uploaded by the second terminal when there is no data having a track matching relationship with the road element data in the pre-stored road element data, and update the pre-stored road image data according to the road image data uploaded by the second terminal.

and a third operation unit configured to change the verification tag of the pre-stored road element data to the verified state when the comparison results are the same and the verification tag of the pre-stored road element data is in the to-be-verified state.

uploading the road element data to a cloud end, wherein the road element data is used for instructing the cloud end to compare the road element data with prestored road element data corresponding to a preset road section; the pre-stored road element data is road element data obtained by performing element identification on pre-stored road image data by a cloud;

and when the comparison results are different, acquiring the road image data corresponding to the preset road section, and returning the acquired road image data to the cloud end to update the pre-stored road element data corresponding to the preset road section.

Fig. 13 is a block diagram schematically illustrating a road data updating apparatus according to another embodiment of the present application. As shown in fig. 13, the road data updating apparatus 1300 includes:

a road element data acquiring module 1310 configured to perform image acquisition and element identification on a preset road segment on a map to obtain road element data;

a road element data uploading module 1320 configured to upload road element data to a cloud, the road element data being used to instruct the cloud to compare the road element data with pre-stored road element data corresponding to a preset road segment; the pre-stored road element data is road element data obtained by performing element identification on pre-stored road image data by a cloud;

the road image data updating module 1330 is configured to, when the comparison result is different, obtain the road image data corresponding to the predetermined road segment, and return the obtained road image data to the cloud end to update the pre-stored road element data corresponding to the predetermined road segment.

The specific details of the road data updating device provided in each embodiment of the present application have been described in detail in the corresponding related method embodiment, and are not repeated herein.

It should be noted that the computer system 1400 of the electronic device shown in fig. 14 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.

As shown in fig. 14, the computer system 1400 includes a Central Processing Unit (CPU) 1401 which can perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 1402 or a program loaded from a storage portion 1408 into a Random Access Memory (RAM) 1403. In the random access memory 1403, various programs and data necessary for system operation are also stored. The central processor 1401, the read only memory 1402 and the random access memory 1403 are connected to each other via a bus 1404. An Input/Output interface 1405(Input/Output interface, i.e., I/O interface) is also connected to the bus 1404.

The following components are connected to the input/output interface 1405: an input portion 1406 including a keyboard, a mouse, and the like; an output portion 1407 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage portion 1408 including a hard disk and the like; and a communication section 1409 including a network interface card such as a local area network card, a modem, or the like. The communication section 1409 performs communication processing via a network such as the internet. The driver 1410 is also connected to the input/output interface 1405 as necessary. A removable medium 1411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1410 as necessary, so that a computer program read out therefrom is installed into the storage section 1408 as necessary.

In particular, the processes described in the various method flowcharts may be implemented as computer software programs, according to embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 1409 and/or installed from the removable medium 1411. When executed by the central processing unit 1401, the computer program performs various functions defined in the system of the present application.

It should be noted that the computer readable media shown in the embodiments of the present application may be computer readable signal media or computer readable storage media or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.

It will be understood that the present application is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. A road data update method, the method comprising:

2. The method according to claim 1, wherein before comparing the road element data with pre-stored road element data corresponding to the preset road segment, the method further comprises:

acquiring track data of the first terminal, wherein the track data is driving track data of the first terminal when the first terminal collects the road image data;

according to the time stamp of the road image data corresponding to the road element data and the time stamp of the track points on the track data, establishing a mapping relation between the road element data and the track points;

determining a preset road section on the map corresponding to the road element data according to the mapping relation between the road element data and the track points;

pre-stored road element data corresponding to a preset road segment on the map is acquired.

3. The method of claim 2, wherein comparing the road element data with pre-stored road element data corresponding to the preset road segment comprises:

acquiring cache road element data; the cached road element data is road element data which is historically returned and cached by a third terminal and corresponds to the preset road section;

according to the road element types of the road element data and the road element types of the cache road element data, carrying out quantity statistics on the quantity of the road element data under each road element type, and determining target road element data according to a statistical result;

and comparing the target road element data with pre-stored road element data corresponding to the preset road section.

4. The method of claim 3, wherein comparing the target road element data with pre-stored road element data corresponding to the preset road segment comprises:

calculating the confidence coefficient of the target road element according to the quantity of the road element data under the road element type of the target road element data in the statistical result;

and comparing the target road element data with the confidence coefficient greater than a preset threshold value with pre-stored road element data corresponding to the preset road section.

5. The method of claim 3, wherein performing a quantity statistic of the number of the road element data in each road element type according to the road element type of the road element data and the road element type of the cache road element data, and determining the target road element data according to the statistic result comprises:

calculating the track similarity of the road element data and the cache road element data according to the track points mapped by the road element data and the track points mapped by the cache road element data;

adding the cached road element data with the track similarity larger than a preset threshold value with the road element data into a statistical list;

and carrying out quantity statistics on the quantity of the road element data under each road element type according to the road element type of the road element data and the road element type of the road element data in the statistical list, and determining target road element data according to the statistical result.

6. The method of claim 1, wherein comparing the road element data with pre-stored road element data corresponding to the preset road segment comprises:

matching the track of the road element data with the track of prestored road element data corresponding to the preset road section;

determining the road element data with the track matching relationship and the prestored road element data as matching data;

when data with a track matching relationship with the road element data exists in the pre-stored road element data, comparing the road element data in the matching data with the pre-stored road element data;

and when data having a track matching relationship with the road element data does not exist in the prestored road element data, acquiring the road image data uploaded by the second terminal, and updating the prestored road image data according to the road image data uploaded by the second terminal.

7. The method according to claim 1, wherein after comparing the road element data with pre-stored road element data corresponding to the preset section, the method further comprises:

and when the comparison results are the same and the verification tag of the pre-stored road element data is in a to-be-verified state, changing the verification tag of the pre-stored road element data into a verified state.

8. A road data update method, the method comprising:

9. A road data update apparatus, comprising:

the road image data acquisition module is configured to acquire road image data uploaded by a second terminal when the comparison results are different, wherein the road image data is data obtained by image acquisition of the preset road section; the second terminal is the same or different terminal equipment as the first terminal;

10. A road data update apparatus, comprising:

a road element data uploading module configured to upload the road element data to a cloud, the road element data being used to instruct the cloud to compare the road element data with pre-stored road element data corresponding to the preset road section; the pre-stored road element data is road element data obtained by performing element identification on pre-stored road image data by the cloud;