Information synchronization method, device and system of road auxiliary equipment, equipment and medium

Abstract

The embodiment of the invention provides an information synchronization method, device and system of road auxiliary equipment, equipment and a medium. The invention belongs to the technical field of computers. The method comprises the following steps: receiving to-be-written information of each electronic tag constructed by front-end equipment according to a preset format; issuing a writing instruction of the to-be-written information to the base station, so that the base station completes writing operation according to the label identity information; the method comprises the following steps: acquiring reported data and reported data signal strength of each electronic tag through a base station, and determining whether the reported data is valid based on the reported data signal strength; and if yes, synchronizing the position information of the road auxiliary equipment in the reported data to the map data. According to the technical scheme, the tag management platform is adopted to perform information writing and management on the electronic tag of the road auxiliary equipment, and the technical effects of reducing deployment, operation and maintenance cost, expanding an effective identification distance, improving information synchronization timeliness and information identification stability, and improving road traffic information real-time performance and safety can be achieved.

Description

Technical Field

[0001] This application belongs to the field of computer technology, and in particular relates to a method, apparatus, system, equipment and medium for information synchronization of road auxiliary equipment. Background Technology

[0002] With the development of intelligent transportation and autonomous driving technologies, scenarios such as road construction and traffic control place higher demands on the timeliness, warning distance, and reliability of traffic assistance facilities. Existing technologies mostly employ solutions involving installing readers on vehicles and laying passive tags on roads or infrastructure, such as roadside equipment. Vehicle positioning, route guidance, and collision warnings are achieved by reading tag information through onboard devices. To avoid deploying roadside equipment separately, some solutions embed RFID (Radio Frequency Identification) tags into road markings or tunnel walls, combining this with onboard readers to address issues such as visual recognition failure and GPS (Global Positioning System) signal blockage, thus providing decision-making support for autonomous driving.

[0003] However, current deployment methods not only suffer from high deployment and maintenance costs, requiring large-scale modifications to road infrastructure and the installation of specialized equipment on vehicles, but also suffer from easily damaged tags and difficult maintenance. Furthermore, the limited recognition distance—vehicle-mounted readers can only read tags within a 10-meter line-of-sight range—fails to provide beyond-line-of-sight warnings, posing a serious driving safety hazard. This offers minimal assistance in rainy or foggy weather, and the limited communication distance leads to significant errors in tag reading at high speeds, making it difficult to accurately determine whether tag displacement is normal and prone to misjudgment. These problems severely impact the effectiveness of the deployment and pose road safety hazards, representing a pressing technical challenge that needs to be addressed by those skilled in the art. Summary of the Invention

[0004] This application provides a method, apparatus, system, device, and medium for synchronizing information on road auxiliary equipment. The purpose of this application is to address the problems of high deployment and maintenance costs, limited identification distance, information lag, and poor stability in existing road auxiliary equipment information synchronization technologies. This solution uses a tag management platform to write and manage information on the electronic tags of road auxiliary equipment via base stations. This achieves the technical effects of reducing deployment and maintenance costs, extending the effective identification distance, improving the timeliness of information synchronization and the stability of information identification, and enhancing the real-time nature and security of road traffic information.

[0005] In a first aspect, embodiments of this application provide an information synchronization method for road auxiliary equipment, the method being executed by a tag management platform; the road auxiliary equipment is equipped with an electronic tag, the electronic tag communicating with a base station, and the tag management platform communicating with the base station and simultaneously with a front-end device; the method includes: The system receives information to be written from each electronic tag constructed by the front-end device according to a preset format; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; Send a write instruction to the base station for writing the information to be written, so that the base station can complete the write operation based on the tag identity information; The base station collects the reported data and signal strength of each electronic tag, and determines whether the reported data is valid based on the signal strength of the reported data. If valid, the location information of the road auxiliary equipment in the reported data will be synchronized to the map data.

[0006] In one feasible implementation, determining whether the reported data is valid based on the signal strength of the reported data includes: Calculate the signal strength change information of the reported data signal strength of the electronic tag in the time dimension, and identify whether the signal strength change information meets the preset removal characteristics; If the preset demolition characteristics are not met, the reported data is deemed valid. If the preset demolition characteristics are met, then the reported data is determined to be invalid.

[0007] In one feasible implementation, the signal strength change information of the reported data signal strength of the electronic tag over time is calculated, and it is identified whether the signal strength change information meets the preset removal characteristics, including: Based on the time series of the reported data signal strength of a single electronic tag, information on intensity changes is obtained; For electronic tags whose intensity change information exceeds a set threshold, a graph neural network is constructed; wherein, the graph neural network consists of nodes and edges between nodes; the edges between nodes include the signal strength correlation coefficients of the two electronic tags that construct the current edge; Identify whether the edges of the graph neural network satisfy the preset removal characteristics.

[0008] In one feasible implementation, identifying whether the edges of the graph neural network satisfy a preset teardown characteristic includes: If some edges of the graph neural network exhibit changes in signal strength correlation coefficient, then the preset demolition characteristics are not met. If all edges of the graph neural network exhibit changes in signal strength correlation coefficients, then the preset demolition characteristics are satisfied.

[0009] In one feasible implementation, the information to be written also includes group information of electronic tags set by the road auxiliary equipment; Before obtaining intensity change information based on the time series of reported data signal strength from a single electronic tag, the method further includes: Identify group information from electronic tags; Filter out electronic tags that are not in the same group and get electronic tags that are in the same group.

[0010] In one feasible implementation, after obtaining the electronic tags of the same group, the method further includes: Identify the serial number and activation time of electronic tags within the same group; Electronic tags whose activation time interval is outside the preset time interval range are filtered out.

[0011] In one feasible implementation, the information to be written further includes the type information of the road auxiliary equipment; Accordingly, the location information in the reported data is synchronized to the map data, including: Based on the location information of the road auxiliary equipment in the reported data, the synchronization location is determined; Based on the type information of road auxiliary equipment in the reported data, a virtual model is constructed to display the virtual model of the road auxiliary equipment at the synchronization location.

[0012] In one feasible implementation, the system receives the information to be written from each electronic tag constructed by the front-end device according to a preset format, including: The front-end device scans the identification code of the electronic tag on the road auxiliary equipment to obtain the tag identity information; Location information is obtained by acquiring the positioning data from the front-end device; Based on the identity information and the location information, the information to be written to the electronic tag is encoded according to a preset encoding rule.

[0013] Secondly, embodiments of this application provide an information synchronization device for road auxiliary equipment, the device being configured to run on a tag management platform; the road auxiliary equipment is equipped with an electronic tag, the electronic tag communicating with a base station, the tag management platform communicating with the base station and simultaneously communicating with a front-end device; the device includes: The information to be written module is used to receive the information to be written from each electronic tag constructed by the front-end device according to a preset format; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; The writing module is used to send a writing instruction to the base station for the information to be written, so that the base station can complete the writing operation according to the tag identity information. The reported data validity identification module is used to collect the reported data and the reported data signal strength of each electronic tag through the base station, and determine whether the reported data is valid based on the reported data signal strength; The road auxiliary equipment synchronization module is used to synchronize the location information of the road auxiliary equipment in the reported data to the map data if the data is identified as valid.

[0014] Thirdly, embodiments of this application provide an information synchronization system for road auxiliary equipment, the system comprising: The front-end device communicates with the tag management platform to send the information to be written for each electronic tag, constructed according to a preset format, to the tag management platform; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; The tag management platform communicates with the base station and is used to send the information to be written to each electronic tag to the base station; The base station communicates with each electronic tag and is used to complete the writing operation of the information to be written based on the tag's identity information. The base station is also used to collect the reported data and signal strength of each electronic tag and upload them to the tag management platform. The tag management platform is also used to determine whether the reported data is valid based on the signal strength of the reported data; if valid, the location information of the road auxiliary equipment in the reported data is synchronized to the map data.

[0015] Fourthly, embodiments of this application provide an information synchronization device for road auxiliary equipment, the device comprising: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the information synchronization method for road auxiliary equipment as described above.

[0016] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the information synchronization method for road auxiliary equipment as described above.

[0017] Sixthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the information synchronization method for road auxiliary equipment as described above.

[0018] The information synchronization method, apparatus, system, equipment, and medium for road auxiliary equipment in this application embodiment achieve synchronous updates of road auxiliary equipment on the server side through the interaction between base stations and passive tags. This eliminates the need for vehicle modifications, significantly reducing deployment costs. By combining signal strength analysis to determine data validity, information accuracy is improved. Real-time location synchronization to the map enables beyond-line-of-sight warnings, solving the problem of delays in traditional manual updates and providing assurance for road safety management. Through data validity judgment, such as time-dimensional signal change analysis, graph neural network construction, and edge attribute difference identification, the system accurately distinguishes between individual tag anomalies and the complete removal of facilities, avoiding misjudgments that lead to map data errors and further ensuring information accuracy. Group information filtering and activation time screening eliminate tags from different scenarios and anomalous tags, ensuring consistency of analysis objects and improving the accuracy of subsequent data processing. By introducing equipment type information to construct a virtual model, facilities are visualized, helping users quickly identify scenarios and respond, optimizing the navigation experience. By constructing a simple and easy-to-operate information generation process, automated collection and encoding reduce human error, improving information collection efficiency and standardization. This technical solution comprehensively improves the efficiency of road auxiliary equipment information synchronization, the accuracy of identification, and the practicality of the solution. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating an information synchronization method for road auxiliary equipment provided in an embodiment of this application; Figure 2 This is a schematic diagram of the passive Internet of Things (IoT) network architecture provided in the embodiments of this application; Figure 3 This is a schematic diagram of the construction process of the triangular pyramid provided in the embodiments of this application; Figure 4 This is a schematic diagram of the encoding information provided in the embodiments of this application; Figure 5 This is a schematic diagram of the virtual facility imaging process provided in the embodiments of this application; Figure 6 This is a schematic diagram of the preprocessing procedure provided in the embodiments of this application; Figure 7This is a schematic diagram illustrating the process of constructing and using a graph neural network as provided in an embodiment of this application; Figure 8 This is a schematic diagram of the fitting process provided in the embodiments of this application; Figure 9 This is a schematic diagram illustrating the map data synchronization effect provided in an embodiment of this application; Figure 10 This is a schematic diagram of the construction completion process provided in the embodiments of this application; Figure 11 This is a schematic diagram of the structure of an information synchronization device for road auxiliary equipment provided in an embodiment of this application; Figure 12 This is a schematic diagram of the structure of an information synchronization system for road auxiliary equipment provided in an embodiment of this application; Figure 13 This is a schematic diagram of the structure of an information synchronization device for road auxiliary equipment provided in an embodiment of this application. Detailed Implementation

[0021] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0022] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0023] To address the problems in existing technologies, this application provides a method, apparatus, system, device, and medium for synchronizing information on road auxiliary equipment. The technical solution provided by this application can resolve issues such as high deployment and maintenance costs, limited identification distance, information lag, and poor stability in existing road auxiliary equipment information synchronization technologies. This solution employs a tag management platform to write and manage information on electronic tags of road auxiliary equipment via base stations, achieving the technical effects of reducing deployment and maintenance costs, extending the effective identification distance, improving the timeliness of information synchronization and the stability of information identification, and enhancing the real-time nature and security of road traffic information.

[0024] The information synchronization method for road auxiliary equipment provided in the embodiments of this application will be introduced first below.

[0025] Figure 1 This is a flowchart illustrating a method for synchronizing information on road auxiliary equipment provided in an embodiment of this application. In this embodiment, the method for synchronizing information on road auxiliary equipment can be executed by a tag management platform and can be widely applied to scenarios such as highway construction and detours, urban road traffic control, and routine highway maintenance. Through the collaborative interaction of electronic tags, 5G-A base stations, front-end equipment, and the tag management platform, real-time and accurate synchronization of road auxiliary equipment information with map data is achieved, solving problems such as delayed facility information updates and insufficient beyond-line-of-sight warnings in traditional traffic scenarios. Figure 1 As shown, the method may include the following steps: S101, receive the information to be written from each electronic tag constructed by the front-end device according to a preset format; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; Among them, front-end equipment can refer to terminal equipment operated by construction personnel on the road site, such as smartphones pre-installed with a dedicated management APP (Application), handheld terminals with high-precision positioning functions, etc. Its core function is to collect basic information of electronic tags, obtain equipment deployment location data, and generate information to be written in a standardized format.

[0026] Preset format can refer to the data structure specification predefined by the tag management platform, which is used to unify the storage logic and field arrangement of the information to be written. For example, the 32-bit length encoding format designed in the disclosure document clearly defines the length and position of fields such as version number, group ID, and location information, ensuring that the data format is consistent when the base station writes and the platform parses the data.

[0027] Electronic tags refer to passive electronic tags attached to road auxiliary equipment. They do not require built-in batteries and can transmit data back by reflecting and demodulating 5G-A (5G-Advanced) base station signals. The tag has a user area inside for storing information to be written.

[0028] The information to be written can refer to the core data set that needs to be stored in the electronic tag. It is the basic data for subsequent base station writing and platform parsing. It includes at least tag identity information and location information, and can also be expanded to include information such as construction unit and operation time as needed. For example, it includes tag coding data such as group ID, latitude and longitude coordinates and facility type.

[0029] Tag identification information can refer to information used to uniquely identify a single electronic tag, ensuring that each electronic tag can be accurately identified and avoiding data confusion. For example, the EPCID (Electronic Product Code Identifier) ​​of an electronic tag is the basis for subsequent base station to locate a specific tag and complete the writing operation.

[0030] Near-field interaction can be a way for front-end devices to obtain information from electronic tags through short-range communication technology, such as scanning the QR code on the electronic tag or sensing the tag through NFC (Near Field Communication). A specific scenario is that construction workers use front-end devices to scan the QR code on the electronic tag on the triangular cone to directly obtain the EPCID of the tag.

[0031] In this solution, the front-end device can integrate the collected tag identity information and its own location information into structured data to be written, according to a preset format. For example, after obtaining the EPCID and its own location coordinates, the front-end device fills the two types of information into the corresponding fields according to the 32-bit encoding rule, forming complete data to be written. When the tag management platform receives the data to be written uploaded by the front-end device, it can perform preliminary verification on the received data, such as whether the format conforms to the preset specifications, to ensure that the data can be used for subsequent command issuance.

[0032] S102, send a write instruction for the information to be written to the base station, so that the base station can complete the write operation according to the tag identity information; A base station, which can refer to a 5G-A base station, has the functions of transmitting excitation signals to electronic tags, receiving tag response data, and executing write commands. Its signal coverage range can reach 300-500 meters, which can meet the communication needs of electronic tags in road scenarios.

[0033] The write command can be a control signal generated by the tag management platform, which contains the information to be written and operation instructions. This command can inform the base station of the specific data to be written and the object to be operated.

[0034] The write operation is the process by which the base station stores the information to be written into a designated area of ​​the electronic tag. For example, the platform sends a write command to the base station to write the encoded information into the user area of ​​the tag.

[0035] In this solution, the tag management platform can transmit write commands to the target base station via a communication link composed of the core network and edge nodes. Specifically, based on the deployment location of the electronic tag, the platform can select a 5G-A base station covering the area to issue the command, ensuring that the command is accurately delivered to the corresponding base station. After receiving the write command, the base station first locates the corresponding electronic tag based on the tag's identity information, and then writes the information to be written into the user area of ​​the electronic tag by transmitting an excitation signal at a specific frequency. For example, after the base station finds the electronic tag on a triangular pyramid based on the EPCID, it writes the latitude and longitude coordinates, facility type, and other data of the triangular pyramid into the tag.

[0036] S103, the base station collects the reported data and the signal strength of the reported data from each electronic tag, and determines whether the reported data is valid based on the signal strength of the reported data; The reported data can be the data transmitted back to the base station by the electronic tag after receiving the base station's excitation signal. This data can include information to be written stored in the electronic tag, such as tag identity information, location information, facility type, etc.

[0037] The reported data signal strength, or RSSI (Received Signal Strength Indicator), is the strength value of the signal received by the base station from the electronic tag. Its magnitude can reflect the communication quality and distance between the electronic tag and the base station, and can also be used to determine whether the tag has been displaced.

[0038] Validity refers to whether the reported data can truly and accurately reflect the current status of the road auxiliary equipment. If the data is valid, it can be used for subsequent map synchronization; if it is invalid, such as when the data deviates due to label displacement or signal interference, it needs to be filtered to avoid synchronizing erroneous information into the map data.

[0039] In this scheme, the base station can continuously transmit excitation signals to the electronic tags within its coverage area, receive the reported data transmitted back by the tags, and simultaneously record the signal strength corresponding to the reported data of each electronic tag. Then, it sends the reported data and signal strength to the tag management platform. The tag management platform analyzes the signal strength of the reported data collected by the base station to determine whether the reported data is valid. For example, the platform presets a signal strength threshold. If the RSSI of an electronic tag is higher than the threshold, the reported data of that tag is considered valid; if the RSSI is lower than the threshold, or the signal strength fluctuates abnormally, the data is considered invalid. Alternatively, it can determine whether tags have been removed in batches. If they have been removed in batches, the tag data is determined to be invalid, and the road information can be displayed normally, avoiding interference to drivers due to untimely synchronization and affecting road traffic safety.

[0040] S104, if valid, then synchronize the location information of the road auxiliary equipment in the reported data to the map data.

[0041] Road auxiliary equipment can be facilities used for road construction warnings and traffic order maintenance, such as traffic cones, warning posts, guardrails, and triangular frames. Their location information reflects the current state of the road, such as whether there is construction or whether the route is diverted.

[0042] Location information can be the geographic coordinate data of the deployment location of road auxiliary equipment, which usually includes longitude, latitude and altitude. It is collected by the high-precision positioning module of the front-end equipment, such as GPS and Beidou positioning, and stored in electronic tags.

[0043] Map data can be a database that stores road geographic information and traffic dynamic information, such as the backend database of some map software or a road information database dedicated to traffic management departments. It can support the display of real-time road status after the driver opens the navigation.

[0044] In this solution, the tag management platform can transmit the location information from the effectively reported data to the map data and update the map display content. Specifically, it can convert the location information into identifiable coordinate points to ensure that the map can accurately display the location of road auxiliary equipment. For example, the latitude and longitude coordinates of the triangular cones can be synchronized to the navigation map. Note that the height data can be ignored here, so that the distribution of triangular cones in the construction area can be displayed on the map in real time.

[0045] The technical solution provided in this embodiment achieves automated and precise synchronization of road auxiliary equipment information. Compared to traditional methods of installing readers on vehicles or laying identification tags on roads, this solution requires no modification to roads or vehicles. Basic data collection is achieved through information interaction between 5G-A base stations and passive tags, significantly reducing deployment costs. Simultaneously, the validity of data collected by base stations and signal strength is assessed, avoiding data reading errors in high-speed moving scenarios and improving information accuracy. Furthermore, real-time synchronization of road auxiliary equipment location information to maps allows drivers to obtain the distribution of road auxiliary equipment in advance through navigation, such as the location of traffic cones in construction areas, enabling beyond-line-of-sight warnings and effectively reducing the probability of traffic accidents. Especially in highway construction scenarios, drivers can use navigation to know about road sections enclosed by traffic cones 500 meters or even further in advance, allowing them to slow down and change lanes in advance, improving road traffic safety.

[0046] In one feasible embodiment, determining whether the reported data is valid based on the reported data signal strength includes: Calculate the signal strength change information of the reported data signal strength of the electronic tag in the time dimension, and identify whether the signal strength change information meets the preset removal characteristics; If the preset demolition characteristics are not met, the reported data is deemed valid. If the preset demolition characteristics are met, then the reported data is determined to be invalid.

[0047] The time dimension can be the time range in which the signal strength (RSSI) of the electronic tag is continuously collected, with time as the axis. For example, the RSSI of a triangular pyramid electronic tag is collected every 10 seconds to form 6 sets of RSSI data within 1 minute, which are used to observe the change of signal strength over time.

[0048] Signal strength change information can be the trend or fluctuation of the RSSI of the electronic tag over time. For example, if the RSSI remains stable at around -60dBm, the change range is small. If the RSSI drops rapidly from -60dBm to -90dBm, the change range is large. It can be seen that RSSI can reflect whether the electronic tag has been displaced. For example, when the traffic cone is removed, the distance between the tag and the base station increases, and the RSSI drops. Or, individual traffic cones attached to electronic tags may roll to a greater distance due to crosswinds.

[0049] The preset removal characteristics can be used by the tag management platform to identify the signal strength change patterns when road auxiliary equipment is removed. For example, if the RSSI of a certain electronic tag drops continuously within 1 minute and the drop exceeds 20dBm, or if the RSSI of the same group of tags drops significantly at the same time, comparative analysis can show that the latter is caused by the batch removal of road auxiliary equipment. This batch removal operation is exactly what this solution needs to focus on. It can quickly synchronize the removal on the map data to avoid causing confusion to drivers or causing them to misjudge, thus creating road traffic safety hazards.

[0050] In this solution, the tag management platform processes multiple sets of continuously collected RSSI data to obtain signal strength change information. For example, it determines the magnitude of signal strength change by calculating the difference in RSSI between adjacent time points, or it determines whether the signal strength is increasing, decreasing, or stable by calculating the slope of the RSSI change trend using the least squares method. Furthermore, the calculated signal strength change information is compared with preset removal characteristics to determine if they match. Based on the identification results, if the preset removal characteristics are not met, it indicates that the road auxiliary equipment is still in place; if the preset removal characteristics are met, it indicates that the equipment may have been removed, and the reported data cannot reflect the current road condition, therefore the data is invalid.

[0051] The technical solution provided in this embodiment enables dynamic judgment of the validity of reported data. Compared with the method of judging solely by a single signal strength threshold, it can more accurately identify whether road auxiliary equipment has been removed, avoiding invalid data from being synchronized to the map. For example, when the traffic cone is removed after construction, the RSSI of the electronic tag will drop significantly with increasing distance. If the platform recognizes that this change meets the preset removal characteristics, it can determine that the reported data is invalid and will no longer synchronize the location information of the traffic cone to the map, preventing the map from displaying the removed facilities and ensuring the real-time performance and accuracy of the map data. However, if the RSSI fluctuates slightly due to only brief signal interference, it does not meet the preset removal characteristics, and the platform still determines that the data is valid, avoiding the misfiltering of normal facility information and ensuring the continuity of navigation prompts.

[0052] In one feasible embodiment, the signal strength change information of the reported data signal strength of the electronic tag over time is calculated, and it is identified whether the signal strength change information meets the preset removal characteristics, including: Based on the time series of the reported data signal strength of a single electronic tag, information on intensity changes is obtained; For electronic tags whose intensity change information exceeds a set threshold, a graph neural network is constructed; wherein, the graph neural network consists of nodes and edges between nodes; the edges between nodes include the signal strength correlation coefficients of the two electronic tags that construct the current edge; Identify whether the edges of the graph neural network satisfy the preset removal characteristics.

[0053] The time series can be a set of RSSI data of a single electronic tag arranged in chronological order. For example, the RSSI of a certain electronic tag at three time points of 10:00:10, 10:00:20 and 10:00:30 are -60dBm, -61dBm and -62dBm respectively. These three sets of data form the RSSI time series of the tag in chronological order, which is the basic data for analyzing the intensity change of a single tag.

[0054] Setting a threshold can be a standard for the intensity change of electronic tags that may be displaced, which can be pre-set by the tag management platform. For example, if the absolute value of the difference between RSSI values ​​at adjacent time points exceeds 5dBm, and if the RSSI of a tag changes from -60dBm to -66dBm (a difference of 6dBm), then its intensity change information is greater than the set threshold, and further analysis is needed to determine whether it was caused by removal.

[0055] A Graph Neural Network (GNN) is a neural network model used to process graph-structured data. It consists of nodes and edges and can be used to represent the relationships between multiple electronic tags. By analyzing changes in the edges in the graph, the overall state of a tag group can be determined.

[0056] A node can be the basic unit representing a single electronic tag in a graph neural network. Each node stores the core information of the electronic tag, such as tag identity information, intensity change information, facility type, etc. For example, a node contains information such as (GroupId, TagIndex, FaType, RssiTrend, Status).

[0057] An edge can be a line segment connecting two nodes in a graph neural network, used to characterize the association between two electronic tags. Here, the edge includes the signal strength correlation coefficient, which can reflect whether the RSSI changes of the two tags are synchronized, corresponding to the edge definition of "Edge[Nodei,Nodej,RssiCorr(i,j)]" in the disclosure.

[0058] The signal strength correlation coefficient, also known as RssiCorr (Rssi Correlation Coefficient), refers to the degree of correlation between the RSSI time series of two electronic tags. Its value ranges from -1 to 1. The closer the coefficient is to 1, the more synchronous the RSSI changes of the two tags. The closer the coefficient is to 0 or a negative number, the more asynchronous the changes.

[0059] The tag management platform processes the RSSI time series of individual electronic tags to extract intensity change information. For example, it calculates the difference between the maximum and minimum RSSI values ​​in the time series to obtain the intensity change amplitude, or it uses linear fitting to obtain the trend of the time series and thus the direction of intensity change. For electronic tags with intensity change information exceeding a set threshold, the platform establishes a graph neural network. Specifically, each eligible electronic tag is treated as a node, its information is filled in, and the correlation coefficient between the signal strength of any two nodes is calculated. This coefficient is then used as the attribute of an edge, connecting the corresponding two nodes to form a complete graph neural network. A preset removal characteristic is that the correlation coefficient of the signal strength of each edge synchronously drops below 0.3. Then, all edges in the graph are traversed to check if the correlation coefficients all meet this condition. If they do, it indicates that the road auxiliary equipment has been removed in batches.

[0060] This embodiment enables accurate judgment of whether a facility has been dismantled based on the status of a single tag and the status of a tag group, avoiding misjudgment of facility dismantling due to occasional signal fluctuations of a single tag. For example, if there are 10 triangular cones in a construction area, and the RSSI of only one tag drops significantly due to signal interference, the platform, after building a graph neural network, will find that the correlation coefficient of the signal strength of this tag with the other 9 tags is close to 0, while the correlation coefficient between the other tags is still close to 1. Therefore, it can be determined that only a single tag is abnormal, not that the facility has been dismantled. Conversely, if the RSSI of all 10 tags drops significantly, and the correlation coefficient of all edges drops to below 0.3 simultaneously, it can be accurately identified as the overall dismantling of the facility. This further improves the accuracy of the status perception of road auxiliary equipment. After being synchronized with map data, it can provide accurate information for vehicle drivers, avoiding misjudgments by vehicle drivers.

[0061] In one feasible embodiment, identifying whether the edges of the graph neural network satisfy a preset teardown characteristic includes: If some edges of the graph neural network exhibit changes in signal strength correlation coefficient, then the preset demolition characteristics are not met. If all edges of the graph neural network exhibit changes in signal strength correlation coefficients, then the preset demolition characteristics are satisfied.

[0062] In this context, "partial edges" can refer to a portion of the edges in a graph neural network, representing only a certain proportion or number of edges. For example, in a graph with 10 edges, 3 of them are partial edges. "All edges" can refer to all edges connecting any two nodes in a graph neural network.

[0063] The phenomenon of changes in the correlation coefficient of signal strength can refer to the significant decrease, increase, or fluctuation of the correlation coefficient of the edges in a graph neural network compared to the initial state. Here, it specifically refers to changes related to the removal of road auxiliary equipment, such as a significant decrease in the correlation coefficient.

[0064] The tag management platform can compare the current signal strength correlation coefficient of edges in a graph neural network with the initial correlation coefficient to detect changes in the coefficients of some or all edges that indicate a potential removal requirement. For example, if the initial correlation coefficient of an edge is 0.9 and it drops to 0.2, it indicates a change in the signal strength correlation coefficient of that edge. The platform can then determine whether the preset removal characteristics are met based on whether changes occur in some or all edges.

[0065] The technical solution provided in this embodiment further improves the accuracy of identifying preset demolition characteristics and avoids map data errors caused by misjudgments. For example, in a highway construction scenario, if a traffic cone is accidentally knocked away by a passing vehicle, only the correlation coefficient between the edge of that label and other labels in the graph neural network decreases, while other edges remain unchanged. The platform determines that the preset demolition characteristics are not met and still synchronizes the position information of other traffic cones to the map, ensuring the continuity of warnings in the construction area. If all traffic cones are removed after construction, the correlation coefficient of all edges in the graph neural network decreases synchronously. The platform determines that the preset demolition characteristics are met and no longer synchronizes the position information to the map data, avoiding the map displaying facilities that no longer exist and ensuring that navigation information is updated in a timely manner.

[0066] In one feasible embodiment, the information to be written also includes group information of electronic tags set by the road assist device; Before obtaining intensity change information based on the time series of reported data signal strength from a single electronic tag, the method further includes: Identify the group information of electronic tags; filter electronic tags that are not in the same group to obtain electronic tags in the same group.

[0067] Among them, group information can be used to identify the group to which the electronic tag belongs, ensuring that electronic tags in the same road scenario are grouped into one group, and avoiding confusion of tag data in different scenarios.

[0068] The same group can be a set of electronic tags with the same group information, such as the same GroupId. The road auxiliary equipment corresponding to these tags is usually located in the same area, such as the traffic cones in the same construction area.

[0069] The tag management platform can remove electronic tags that are not in the same group, and only retain tags in the same group, ensuring the consistency of subsequent analysis objects.

[0070] The tag management platform parses the 32-bit code in the reported data from the electronic tags, and reads the GroupId from specific fields, such as the 2nd to 5th bits, to determine the group information of the tag.

[0071] This technical solution, by introducing group information and group filtering, ensures that subsequent data processing, such as intensity change information analysis and graph neural network construction, is only applied to electronic tags within the same scene, avoiding cross-interference between tag data from different scenes and improving the accuracy of data processing. It also ensures the accuracy of map synchronization across different scenes.

[0072] In one feasible embodiment, after obtaining the electronic tags of the same group, the method further includes: Identify the serial number and activation time of electronic tags within the same group; Electronic tags whose activation time interval is outside the preset time interval range are filtered out.

[0073] The serial number information can be a serial number used to identify a single electronic tag within the same group, ensuring that each tag within the same group can be distinguished. The TagIndex in the 32-bit encoding, for example, if there are 10 tags in the same group, the TagIndex will be 1, 2, ..., 10, which can clearly identify the unique identity of each tag within the group.

[0074] The activation time can be the time when the electronic tag is written with the information to be written, that is, the time when it changes from the pending activation state to the activated state, that is, the time when the tag begins to work effectively. For example, the Time in the 32-bit code in the briefing, in the format of MM-DDHH:MM:SS, can reflect when the tag starts recording road auxiliary equipment information.

[0075] The preset time interval range can be a reasonable range of differences in the activation times of electronic tags within the same group, pre-set by the tag management platform. For example, the activation times should differ by no more than 5 minutes, and this range is set based on the actual construction scenario. For instance, triangular cones in the same construction area typically complete deployment and activation within 5 minutes.

[0076] The tag management platform extracts serial number information and activation time from the reported data of electronic tags in the same group, and identifies tags whose activation time interval exceeds the preset range, thus completing tag filtering.

[0077] This technical solution, by activating time filtering, removes abnormal tags that were deployed out of the same time within the same group, ensuring that the tags analyzed subsequently are all tags that were deployed normally at the same time, thereby further improving the accuracy of data validity judgment.

[0078] In one feasible embodiment, the information to be written further includes the type information of the road auxiliary equipment; Accordingly, the location information in the reported data is synchronized to the map data, including: Based on the location information of the road auxiliary equipment in the reported data, the synchronization location is determined; Based on the type information of road auxiliary equipment in the reported data, a virtual model is constructed to display the virtual model of the road auxiliary equipment at the synchronization location.

[0079] Type information can be used to identify the specific category of road auxiliary equipment, ensuring that the map can distinguish facilities with different functions. For example, FaType in the 32-bit code in the briefing defines 0 as traffic cone; 1 as water-filled barrier; 2 as warning post; 3 as guardrail; and 4 as tripod. It can clearly identify the facility type corresponding to the electronic tag.

[0080] Synchronized location can be the specific coordinate point in the map data determined by the tag management platform based on the location information in the reported data, used to display road auxiliary equipment. It is the placement position of the virtual model on the map.

[0081] A virtual model can be a digital graphic generated on a map that resembles the physical form of a road auxiliary device, based on the type information of the road auxiliary device. For example, a virtual graphic of a triangular pyramid can be generated based on FaType=0.

[0082] The tag management platform can convert the location information in the reported data into a coordinate format recognizable by the map data, thus synchronizing the location and ensuring its accuracy on the map. Furthermore, based on the type information of the road auxiliary equipment, it can call a preset model library. For example, if the type information is FaType=0, it can retrieve a 3D or 2D graphic template of a triangular cone from the model library to generate a virtual model of the triangular cone. After updating the map data, drivers can intuitively see the distribution of road auxiliary equipment in the navigation interface, and drivers can clearly see the arrangement of triangular cones in the construction area through the navigation app.

[0083] The technical solution provided in this embodiment enables the visual display of road auxiliary equipment on a map. Compared to simply synchronizing location coordinates, it allows for more intuitive and rapid acquisition of road status information, improving the navigation experience and road safety. It also prevents users from confusing the functions of the facilities, further reducing the probability of traffic accidents.

[0084] In one feasible embodiment, the information to be written to each electronic tag constructed by the front-end device according to a preset format is received, including: The front-end device scans the identification code of the electronic tag on the road auxiliary equipment to obtain the tag identity information; Location information is obtained by acquiring the positioning data from the front-end device; Based on the identity information and the location information, the information to be written to the electronic tag is encoded according to a preset encoding rule.

[0085] An identification code is an identifier on an electronic tag used to quickly identify the tag's identity. It is usually physically printed on the tag surface in the form of a QR code, barcode, etc. It is the physical carrier for front-end devices to obtain the tag's identity information and contains the tag's EPCID information.

[0086] Location data can be the geographic coordinates of the current location of the front-end device, collected by the front-end device through its built-in positioning module. Since the front-end device and the road auxiliary equipment are in the same location, this location data can be directly used as the location information of the road auxiliary equipment.

[0087] Pre-defined encoding rules can be encoding specifications predefined by the tag management platform to convert tag identity information and location information into information to be written. These rules specify field divisions, field lengths, data formats, etc. For example, the 32-bit encoding rule in the briefing assigns fixed-length fields to tag identity information (EPCID), location information, etc., to ensure that the encoded data can be correctly parsed by the base station and the platform.

[0088] Construction workers operate the front-end equipment, aligning it with the identification code on the electronic tag. By reading the information contained in the code, they obtain the tag's identity information. Simultaneously, the front-end equipment can automatically collect location data generated by its own positioning module. For example, while scanning the identification code, the front-end equipment automatically activates GPS positioning to obtain the latitude and longitude coordinates of the current location, using these coordinates as the location information for the road auxiliary equipment. Following preset encoding rules, the front-end equipment fills the scanned tag identity information and the obtained location information into the corresponding fields, generating structured information to be written.

[0089] This technical solution automates and standardizes the generation of information to be written, significantly improving the accuracy and efficiency of information collection compared to manual input. For example, when construction workers deploy traffic cones, they only need to scan the tag's QR code with a front-end device. The device can automatically obtain the tag's identity information and location data, and generate the information to be written according to preset rules. The entire process requires no manual input, improving the overall operability of the solution.

[0090] To enable those skilled in the art to better understand this solution, this application also provides a preferred embodiment.

[0091] This proposal puts forward a passive Internet of Things network architecture based on 5G-A technology, constructing a star-shaped network structure of tags, terminals, base stations, edge nodes, platforms, and vehicles. It realizes the function of fitting real-world traffic facilities as virtual graphics in a map, solving the problem that traditional traffic auxiliary facilities can only provide warnings within the line of sight. It can effectively reduce the probability of traffic accidents caused by traffic construction. The system's capabilities can also improve the active safety of intelligent vehicles.

[0092] Figure 2 This is a schematic diagram of the passive Internet of Things (IoT) network architecture provided in an embodiment of this application. For example... Figure 2 As shown, the passive tag group ① is installed on the road auxiliary equipment and does not require an internal power supply. The front-end device ② can scan the passive tags to encode data. The 5G-A base station ③ is responsible for transmitting excitation signals to the passive tag group ①, receiving the reported data and signal strength, and transmitting the data to the edge node ④. After preliminary processing of the data, the edge node ④ uploads it to the passive IoT platform ⑤ through the 5G core network. The passive IoT platform ⑤ sends a write command to the 5G-A base station ③, and the 5G-A base station ③ completes the data write operation; at the same time, it judges the validity of the data based on the signal strength of the reported data. If valid, the location information of the road auxiliary equipment is synchronized to the map data for vehicle terminals ⑥, such as navigation software or vehicle navigation devices, to achieve real-time updates of road auxiliary equipment information on the map, providing drivers with services such as beyond-line-of-sight warnings and ensuring the efficiency of road safety management.

[0093] Step 1: Construction of the triangular pyramid Figure 3 This is a schematic diagram of the construction process of a triangular pyramid provided in an embodiment of this application. Figure 3 As shown in the figure, the process is as follows: S301, Place the triangular pyramid; S302, Scan the QR code on the cone label with the APP; S303, Obtain key information such as label input facilities; S304, facility type, tag grouping, terminal coordinates, etc., the APP completes the information encoding; S305 sends a write command to the base station.

[0094] Specifically, when deploying traffic cones (each cone has a label attached, initially set to invalid), on-site construction workers scan the QR code on the label of each cone using a handheld terminal. This solution employs a 32-bit encoding rule to label information related to the current construction work. Figure 4 This is a schematic diagram of the encoding information provided in an embodiment of this application. For example... Figure 4 As shown, the encoding information includes encoding version number, group ID, group index number, operator ID, construction unit, operation time, tag status, latitude and longitude coordinates, altitude, virtual facility category, etc.

[0095] The key fields are described in Table 1 below: Table 1 The terminal comes with a high-precision positioning module. During construction, on-site construction personnel scan the QR code using the terminal's built-in app, read the tag's EPICE, and simultaneously enter the current construction information (triangular cone). The app automatically associates this construction information (time, coordinates, EPICE, etc.) and uploads it to the passive IoT platform, which is essentially the platform for the app. The platform sends a writing command to the base station to write the tag, and writes the encoded information into the tag's user area through the cellular base station.

[0096] At this point, the labels inside each completed cone contain key information needed for the construction, including: facility type (triangular cone), label group, construction time, and precise construction location.

[0097] Step 2: Virtual Facility Imaging Edge nodes process tag data collected by base stations, parse and calculate the location information of the tags, then determine the rationality of the location, fit tag groups, create virtual images, and upload them to the platform for map synchronization.

[0098] Figure 5 This is a schematic diagram of the virtual facility imaging process provided in an embodiment of this application. Figure 5 As shown, it specifically includes: S501, Data Acquisition: The base station transmits an excitation signal to the passive tag and receives the tag response EPC[i]. The base station then sends the received information to the edge node.

[0099] S502, Data Preprocessing: The edge node receives tag data and signal strength from at least one base station, and filters out tag data that does not meet the conditions through data preprocessing.

[0100] Figure 6 This is a schematic diagram of the preprocessing procedure provided in an embodiment of this application. For example... Figure 6 As shown, it specifically includes: S601, Data Acquisition: S602, Grouping: Labels from edge nodes that belong to the same group are grouped together. For the Fatype type, the label of the i-th group is represented as: ; Where i represents the i-th group; j represents the j-th label; and jk represents the k-th base station of the j-th label.

[0101] S603, Timing Detection: For different labels within the same group i, determine the temporal continuity to prevent the inclusion of incorrect labels. This is done by calculating the time difference between two adjacent labels within the same group and comparing it to a preset threshold. If the difference exceeds the threshold, the label is considered abnormal. The determination formula is as follows: Formula 1: Formula 1, ; S604, Discrete point determination: In the physical world, there are two scenarios for the movement of a triangular pyramid: In a normal evacuation scenario, where the entire group moves according to a set of rules, virtual facilities need to be removed simultaneously. Abnormal movement occurred, with some of the cones moving away from their construction positions, and the entire group exhibiting irregular movement. In this scenario, simultaneous removal of the virtual facilities is not required.

[0102] S605, Proceed to the next step; S606, filtration.

[0103] By constructing a graph neural network model for grouped labels, and utilizing changes in the topological relationships of label groups, the model determines the location of the labels in the physical world, thus ensuring the accuracy of virtual imaging. As shown below: Signal strength sequence of tag i: ; Signal intensity sequence of tag j: ; The trend of label i over the most recent T times is calculated using the least squares method to determine the slope of the signal strength change trend, as shown in Formula 2 below: Formula 2, ; Where RssiCorr(i,j) is the Pearson correlation coefficient of the most recent T Rssi signal sequences of labels i and j, representing the intensity of Rssi synchronization fluctuations, and is expressed by the following formula 3: Formula 3, ; The stronger the fluctuation intensity, the more the label deviates from its original position.

[0104] Figure 7 This is a schematic diagram illustrating the construction and use process of a graph neural network provided in an embodiment of this application. For example... Figure 7 As shown, it specifically includes: S701, Construct the graph neural network model in the initial state; When the target tag group is in the correct position (typically at the end of facility deployment), the tags in the group are inventoried every 10 seconds.

[0105] The initial node is denoted as: [ ], where Node (GroupId, TagIndex, FaType, RssiTrend, Status).

[0106] The initial edge is denoted as: [ ], where Edge[Nodei,Nodej,RssiCorr(i,j)]; S702, the node that constructs the graph neural network model of the current state; The current node is denoted as: [ ]; S703, Construct the edges of the graph neural network model for the current state; The current edge is recorded as: [ ]; S704, Displacement determination; Calculate the changes in the correlation of the node signal sequence and compare the RssiCorr values ​​of the associated edges in the current state with those in the initial state.

[0107] S705, the RssiCorr of some adjacent edges of the label decreases, which is identified as partial displacement; S706 showed no significant change and was identified as having no displacement. S707, all edges RssiCorr decrease synchronously, which is identified as a global displacement; S708, For cases of partial displacement and no displacement, retain the label.

[0108] After the above preprocessing, several sets of tag information that have not been displaced are obtained.

[0109] S503, Graphical Fitting: Perform graphic fitting on labels of the same group to obtain the necessary data for virtual map imaging. Figure 8 This is a schematic diagram of the fitting process provided in an embodiment of this application. For example... Figure 8 As shown, the fitting process is as follows: S801, Read Tag Data: Read and parse the tag data. Since the coordinates of the same group are usually at the same height, for the sake of simplicity, only the coordinates in the longitude and latitude planes are fitted here. S802, Grouping Processing: Grouping tag data according to GroupId; S803, Facility Modeling: Select different virtual models based on FaType, combine them with the latitude and longitude coordinates of the labels, first perform piecewise linear interpolation, then perform smoothing filtering, and finally form a virtual curve. S804, map rendering.

[0110] Piecewise linear interpolation is a method that approximates a function by connecting adjacent data points to form a polyline. Given a set of discrete label coordinates... Connecting two adjacent points with a straight line forms a broken line. This can be represented by Formula 4: Formula 4, ; The pseudocode implementation method is as follows: # Define a two-dimensional array coords to represent the filtered coordinates; Coords = array[x(t), y(t)]; # Interpolate longitude and latitude using interpolation functions respectively; interp_lon = interp(loc_new, loc, coords[:, 0]); interp_lat = interp(loc_new, loc, coords[:, 1]); Using the Savitzky-Golay filter to select coordinate points within the window Smoothing filtering. The implementation method is as follows: Smooth_lon = savgol_filter(points[:, 0], window_size, 2); Smooth_lat = savgol_filter(points[:, 1], window_size, 2); Obtain smooth latitude and longitude coordinates.

[0111] Convert smoothed coordinate points to GeoJson format; S504, map synchronization.

[0112] Figure 9 This is a schematic diagram illustrating the map data synchronization effect provided in an embodiment of this application. For example... Figure 9 As shown, key information such as coordinates and facility types are synchronized to the map server, and virtual facilities on the driving route are updated in real time through the navigation system, enabling users to navigate traffic conditions beyond the line of sight and reducing the occurrence of traffic accidents.

[0113] Step 3: After construction is completed, remove the traffic auxiliary facilities. Figure 10 This is a schematic diagram of the construction completion process provided in an embodiment of this application. For example... Figure 10 As shown, S1001, Removal of Triangular Cones: On-site construction personnel removed the previously deployed triangular cones one by one from their original positions, causing the group of triangular cones to shift as a whole. S1002, The base station reads the tag EPC information; S1003, Algorithm determines that the group as a whole has shifted: Edge nodes use an algorithm (detailed below) to determine that the group labels as a whole have shifted; S1004, Platform updates virtual facility information: The platform removes generated virtual transportation facilities; S1005, Send a command to the base station to write the tag status as pending activation: The platform writes the tag status as pending activation through the base station.

[0114] The technical solution provided in this embodiment is a virtual traffic facility system architecture based on 5G-A cellular passive technology. This system architecture combines the capabilities of tags, base stations, edge nodes, core network, and map platform. Based on the information in the tag encoding, it virtualizes traffic facilities and updates them to the map platform in real time, enabling functions such as beyond-line-of-sight traffic warnings.

[0115] A method for generating virtual traffic assistance facilities using passive tags and a method for fitting images using passive tags are proposed. Images are fitted using pre-defined facility types on passive tags and tag group information collected in real time by cellular base stations, and then presented through a map platform. Coordinate points are generated through interpolation and smoothing filtering, and can be directly synchronized to the map for use.

[0116] A collaborative displacement detection method for passive IoT tag groups based on graph neural networks is proposed. When a passive tag moves physically, a graph neural network model is constructed by combining tag group information, and a tag displacement judgment method is designed to verify the tag's validity.

[0117] Existing technologies involve installing readers and communication devices on vehicles, laying passive tags on roads, and using algorithms to achieve functions such as vehicle location positioning and inter-vehicle communication.

[0118] This proposal has the following advantages: Low deployment cost: Replacing base stations with traditional methods requires installing reader / writer devices and communication equipment in vehicles, keeping the overall vehicle production cost unchanged. Furthermore, tag deployment is on-demand, keeping costs under control. During on-site installation, contractors use pre-installed apps on mobile devices to write the encoded information into the tag's user area before installing it on the traffic aids.

[0119] High accuracy: Unlike traditional high-speed mobile readers, base stations read tag information more accurately. The tag information contains high-precision positioning coordinates of the current location, which, after edge node fitting, can accurately express the location and shape of auxiliary facilities.

[0120] Strong anti-interference capability: Unlike traditional tags that can only be deployed in fixed locations, these tags can be deployed on movable facilities, such as traffic cones. When the facility moves, the construction team only needs to rewrite the new coordinate information, and the edge nodes will refit the new virtual traffic facility. If the movement occurs unexpectedly, the base station can also use algorithms to determine the validity of the current facility and prevent misidentification.

[0121] Real-time map updates: After receiving information on virtual traffic facilities or abnormal vehicles reported by base stations, the platform updates the map in real time to make the map more accurate.

[0122] High encoding efficiency: Designed with 32-byte encoding rules, it adapts to most types of tags and enables the management of tag groups and location information.

[0123] Wide range of applications: This solution can be applied to various scenarios such as highway detours, highway closures, and urban road traffic control.

[0124] Figure 11 This is a schematic diagram of the structure of an information synchronization device for road auxiliary equipment provided in an embodiment of this application. Figure 11 As shown, the device is configured to operate within a tag management platform; the road auxiliary equipment is equipped with electronic tags, which communicate with a base station; the tag management platform communicates with the base station and simultaneously with the front-end device; the device includes: The information to be written module 1110 is used to receive the information to be written from each electronic tag constructed by the front-end device according to a preset format; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; The writing module 1120 is used to send a writing instruction to the base station for the information to be written, so that the base station can complete the writing operation according to the tag identity information. The reporting data validity identification module 1130 is used to collect the reporting data and the reporting data signal strength of each electronic tag through the base station, and determine whether the reporting data is valid based on the reporting data signal strength; The road auxiliary equipment synchronization module 1140 is used to synchronize the location information of the road auxiliary equipment in the reported data to the map data if the identification is valid.

[0125] The information synchronization device for road auxiliary equipment provided in this embodiment has the same functional modules and beneficial effects as the information synchronization method for road auxiliary equipment described above. To avoid repetition, it will not be described in detail here.

[0126] Figure 12 This is a schematic diagram of the structure of an information synchronization system for road auxiliary equipment provided in an embodiment of this application. Figure 12 As shown, the system includes: The front-end device 1210 communicates with the tag management platform 1220 to send the information to be written to each electronic tag 1230 constructed according to a preset format to the tag management platform 1220; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; The tag management platform 1220 communicates with the base station 1240 and is used to send the information to be written from each electronic tag 1230 to the base station 1240. The base station 1240 communicates with each electronic tag 1230 and is used to complete the writing operation of the information to be written according to the tag identity information. The base station 1240 is also used to collect the reported data and the signal strength of the reported data from each electronic tag 1230 and upload them to the tag management platform 1220; The tag management platform 1220 is also used to determine whether the reported data is valid based on the signal strength of the reported data; if valid, the location information of the road auxiliary equipment in the reported data is synchronized to the map data.

[0127] The information synchronization system for road auxiliary equipment provided in this embodiment has the same execution process and beneficial effects as the information synchronization method for road auxiliary equipment described above. To avoid repetition, it will not be described in detail here.

[0128] Figure 13 This is a schematic diagram of the structure of an information synchronization device for road auxiliary equipment provided in an embodiment of this application. Figure 13 As shown, the information synchronization device for road auxiliary equipment may include a processor 1301 and a memory 1302 storing computer program instructions.

[0129] Specifically, the processor 1301 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0130] Memory 1302 may include mass storage for data or instructions. For example, and not limitingly, memory 1302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 1302 may include removable or non-removable (or fixed) media, or memory 1302 may be non-volatile solid-state memory. Memory 1302 may be internal or external to the integrated gateway disaster recovery device.

[0131] In one instance, memory 1302 may be read-only memory (ROM). In one instance, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0132] Memory 1302 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0133] The processor 1301 implements the information synchronization method for road auxiliary equipment in the above embodiments by reading and executing computer program instructions stored in the memory 1302.

[0134] In one example, the information synchronization device for road auxiliary equipment may further include a communication interface 1303 and a bus 1304. For example, Figure 13 As shown, the processor 1301, memory 1302, and communication interface 1303 are connected through bus 1304 and complete communication with each other.

[0135] The communication interface 1303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0136] Bus 1304 includes hardware, software, or both, that couples components of a road assist device information synchronization device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 1304 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0137] The information synchronization device for road auxiliary equipment can execute the information synchronization method for road auxiliary equipment in the embodiments of this application, thereby realizing the information synchronization method for road auxiliary equipment described in the above embodiments.

[0138] Furthermore, in conjunction with the information synchronization method for road auxiliary equipment in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the information synchronization methods for road auxiliary equipment in the above embodiments.

[0139] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the information synchronization device method for any of the road auxiliary devices described in the above embodiments.

[0140] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0141] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0142] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0143] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0144] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for synchronizing information of road auxiliary equipment, characterized in that, The method is executed by a tag management platform; the road auxiliary equipment is equipped with electronic tags, which communicate with a base station; the tag management platform communicates with the base station and simultaneously with the front-end equipment; the method includes: The system receives information to be written from each electronic tag constructed by the front-end device according to a preset format; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; Send a write instruction to the base station for writing the information to be written, so that the base station can complete the write operation based on the tag identity information; The base station collects the reported data and signal strength of each electronic tag, and determines whether the reported data is valid based on the signal strength of the reported data. If valid, the location information of the road auxiliary equipment in the reported data will be synchronized to the map data.

2. The information synchronization method for road auxiliary equipment according to claim 1, characterized in that, Determining the validity of the reported data based on the signal strength of the reported data includes: Calculate the signal strength change information of the reported data signal strength of the electronic tag in the time dimension, and identify whether the signal strength change information meets the preset removal characteristics; If the preset demolition characteristics are not met, the reported data is deemed valid. If the preset demolition characteristics are met, then the reported data is determined to be invalid.

3. The information synchronization method for road auxiliary equipment according to claim 2, characterized in that, Calculate the signal strength change information of the reported data signal strength of the electronic tag over time, and identify whether the signal strength change information meets the preset removal characteristics, including: Based on the time series of the reported data signal strength of a single electronic tag, information on intensity changes is obtained; For electronic tags whose intensity change information exceeds a set threshold, a graph neural network is constructed; wherein, the graph neural network consists of nodes and edges between nodes; the edges between nodes include the signal strength correlation coefficients of the two electronic tags that construct the current edge; Identify whether the edges of the graph neural network satisfy the preset removal characteristics.

4. The information synchronization method for road auxiliary equipment according to claim 3, characterized in that, Identifying whether the edges of the graph neural network satisfy a preset teardown characteristic includes: If some edges of the graph neural network exhibit changes in signal strength correlation coefficient, then the preset demolition characteristics are not met. If all edges of the graph neural network exhibit changes in signal strength correlation coefficients, then the preset demolition characteristics are satisfied.

5. The information synchronization method for road auxiliary equipment according to claim 3, characterized in that, The information to be written also includes group information of the electronic tags set up by the road auxiliary equipment; Before obtaining intensity change information based on the time series of reported data signal strength from a single electronic tag, the method further includes: Identify group information from electronic tags; Filter out electronic tags that are not in the same group and get electronic tags that are in the same group.

6. The information synchronization method for road auxiliary equipment according to claim 5, characterized in that, After obtaining the electronic tags of the same group, the method further includes: Identify the serial number and activation time of electronic tags within the same group; Electronic tags whose activation time interval is outside the preset time interval range are filtered out.

7. The information synchronization method for road auxiliary equipment according to claim 1, characterized in that, The information to be written also includes the type information of the road auxiliary equipment; Accordingly, the location information in the reported data is synchronized to the map data, including: Based on the location information of the road auxiliary equipment in the reported data, the synchronization location is determined; Based on the type information of road auxiliary equipment in the reported data, a virtual model is constructed to display the virtual model of the road auxiliary equipment at the synchronization location.

8. The information synchronization method for road auxiliary equipment according to claim 1, characterized in that, Receive the information to be written from each electronic tag constructed by the front-end device according to a preset format, including: The front-end device scans the identification code of the electronic tag on the road auxiliary equipment to obtain the tag identity information; Location information is obtained by acquiring the positioning data from the front-end device; Based on the identity information and the location information, the information to be written to the electronic tag is encoded according to a preset encoding rule.

9. An information synchronization device for road auxiliary equipment, characterized in that, The device is configured to operate within a tag management platform; the road auxiliary equipment is equipped with electronic tags, which communicate with a base station; the tag management platform communicates with the base station and also with the front-end equipment; the device includes: The information to be written module is used to receive the information to be written from each electronic tag constructed by the front-end device according to a preset format; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; The writing module is used to send a writing instruction to the base station for the information to be written, so that the base station can complete the writing operation according to the tag identity information. The reported data validity identification module is used to collect the reported data and the reported data signal strength of each electronic tag through the base station, and determine whether the reported data is valid based on the reported data signal strength; The road auxiliary equipment synchronization module is used to synchronize the location information of the road auxiliary equipment in the reported data to the map data if the data is identified as valid.

10. An information synchronization system for road auxiliary equipment, characterized in that, The system includes: The front-end device communicates with the tag management platform to send the information to be written for each electronic tag, constructed according to a preset format, to the tag management platform; wherein, the information to be written includes tag identity information and location information, and the tag identity information is obtained based on close-range interaction; The tag management platform communicates with the base station and is used to send the information to be written to each electronic tag to the base station; The base station communicates with each electronic tag and is used to complete the writing operation of the information to be written based on the tag's identity information. The base station is also used to collect the reported data and signal strength of each electronic tag and upload them to the tag management platform. The tag management platform is also used to determine whether the reported data is valid based on the signal strength of the reported data; if valid, the location information of the road auxiliary equipment in the reported data is synchronized to the map data.

11. An information synchronization device for road auxiliary equipment, characterized in that, The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the information synchronization method for road auxiliary equipment as described in any one of claims 1-8.

12. A computer-readable storage medium, characterized in that, The computer storage medium stores computer program instructions, which, when executed by a processor, implement the information synchronization method for road auxiliary equipment as described in any one of claims 1-8.

13. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the information synchronization method for road auxiliary equipment as described in any one of claims 1-8.

Images