Data processing method for vehicle-infrastructure cooperative system, system, device and readable medium

Abstract

The present disclosure belongs to the technical field of communications. Provided are a data processing method for a vehicle-infrastructure cooperative system, a system, a device and a readable medium. The method comprises: receiving a traffic monitoring message, wherein the traffic monitoring message carries traffic monitoring data, and the traffic monitoring data comprises data source information and environmental condition information; according to the environmental condition information and the data source information, determining quality evaluation information corresponding to the traffic monitoring data; and adding the quality evaluation information into the corresponding traffic monitoring message and storing same. The method is used for improving the data processing efficiency of vehicle-infrastructure cooperative systems.

Description

Data processing method, system, device and readable medium for vehicle-road cooperative system

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Chinese patent application No. 202311554456.8 filed on November 20, 2023, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0003] The present disclosure relates to the field of communication technology, and in particular to a data processing method, system, device and readable medium for a vehicle-road cooperative system. Background Art

[0004] With the development of fifth-generation mobile communications (5G) technology, cooperative vehicle-infrastructure (CVIS) technology, based on 5G and cellular vehicle-to-everything (C-V2X), has emerged. CVIS aims to improve the efficiency, safety, and sustainability of traffic management through real-time data exchange between vehicles, road infrastructure, and traffic management systems.

[0005] At present, vehicle-road cooperative technology has made significant progress in intelligent traffic management, but the data processing efficiency of the vehicle-road cooperative system still needs to be further improved.

[0006] Summary of the Invention

[0007] The embodiments of the present disclosure provide a data processing method, system, device, and readable medium for a vehicle-road cooperative system.

[0008] A first aspect of an embodiment of the present disclosure provides a data processing method for a vehicle-road cooperative system, comprising: receiving a traffic monitoring message, wherein the traffic monitoring message carries traffic monitoring data, and the traffic monitoring data includes data source information and environmental condition information; determining quality evaluation information corresponding to the traffic monitoring data based on the environmental condition information and the data source information; and adding the quality evaluation information to the corresponding traffic monitoring message and saving it.

[0009] A second aspect of an embodiment of the present disclosure provides a vehicle-road cooperative system, including: a communication module, used to obtain traffic monitoring data, generate traffic monitoring messages and report them to a cloud control platform via a communication network, wherein the traffic monitoring messages carry the traffic monitoring data, and the traffic monitoring data include data source information and environmental condition information; and a cloud control platform, used to receive the traffic monitoring messages; determine quality evaluation information corresponding to the traffic monitoring data based on the environmental condition information and the data source information; and add the quality evaluation information to the corresponding traffic monitoring messages and save them.

[0010] A third aspect of an embodiment of the present disclosure provides an electronic device, comprising: at least one processor; a memory on which at least one program is stored, wherein when the at least one program is executed by the at least one processor, the at least one processor implements the method according to the first aspect; and at least one I / O interface connected between the processor and the memory, and configured to implement information interaction between the processor and the memory.

[0011] A fourth aspect of the embodiments of the present disclosure provides a computer-readable medium having a computer program stored thereon, which implements the method described in the first aspect when the program is executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] FIG1 is a schematic diagram of an application environment of a vehicle collaborative data processing method provided in an embodiment of the present disclosure;

[0013] FIG2 is a flow chart of a data processing method for a vehicle-road cooperative system provided in an embodiment of the present disclosure;

[0014] FIG3 is a schematic diagram of a message format standardization process provided in an embodiment of the present disclosure;

[0015] FIG4a is a schematic diagram of a comprehensive quality score calculation standard formulation process provided in an embodiment of the present disclosure;

[0016] FIG4 b is a schematic diagram of a process for formulating a communication protocol provided in an embodiment of the present disclosure;

[0017] FIG5 is a schematic diagram of a data processing device for a vehicle-road cooperative system provided in an embodiment of the present disclosure;

[0018] FIG6 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0019] The following describes the specific embodiments of the present disclosure in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present disclosure and are not intended to limit the present disclosure.

[0020] As used in this disclosure, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0021] The terms used in the present disclosure are only used to describe specific embodiments and are not intended to limit the present disclosure.As used in the present disclosure, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0022] When the terms “comprising” and / or “made of…” are used in the present disclosure, it specifies the existence of the stated features, integers, steps, operations, elements and / or components, but does not preclude the existence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0023] Unless otherwise defined, all terms (including technical and scientific terms) used in this disclosure have the same meanings as those commonly understood by those skilled in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and this disclosure, and will not be interpreted as having an idealized or overly formal meaning unless expressly defined in this disclosure.

[0024] Figure 1 shows the application environment of the vehicle-road cooperative system data processing method provided by the embodiment of the present disclosure. As shown in Figure 1, the vehicle-road cooperative system involved in this application environment mainly includes: vehicles, communication networks, cloud control platforms, traffic management centers and security layers.

[0025] Vehicles are the source of data, and they generate and send vehicle-related data by carrying IoT devices (such as on-board communication modules). These data include location, speed, traffic conditions, etc.

[0026] The on-board communication module is a hardware device installed on the vehicle, responsible for collecting vehicle data and sending it to the cloud control platform. The module usually includes a GPS receiver, sensors, data processing unit, etc., and can communicate directly with the 5G / C-V2X network.

[0027] The communication network, which connects vehicles to the cloud-based control platform, can be a 5G network or a C-V2X network, providing high-speed, low-latency 5G network connectivity in the application environment. The communication network supports real-time communication between vehicles (V2V), vehicles and infrastructure (V2I), and vehicles and the cloud (V2C), transmitting vehicle and road information and ensuring high-speed data transmission.

[0028] The cloud control platform, also known as a cloud computing platform, is used to store, process, and analyze large amounts of vehicle and road data. It includes distributed computing resources and data centers to handle the massive amounts of data required. The data center is a key component of the cloud control platform, ensuring secure data storage and management. The application environment features a highly reliable data center infrastructure, including data backup, fault tolerance, and data security. The cloud control platform serves as the data processing and management hub, receiving data from vehicles and processing, storing, and analyzing it.

[0029] The cloud control platform may include the following components:

[0030] a data receiving and processing module configured to receive a data stream from a vehicle and parse the data into a standardized message format;

[0031] a standardization processing module configured to perform data processing procedures, including message format standardization, dynamic data quality control, data encryption and digital signature, and communication protocol development;

[0032] a data storage and management module configured to store the processed data in a database and provide data query and retrieval functions;

[0033] A data analysis and application module is configured to analyze vehicle data to support intelligent traffic management applications, such as real-time traffic condition monitoring, route optimization, etc.

[0034] The traffic management center is a user of the cloud control platform, responsible for monitoring and managing the traffic system, and accessing standardized vehicle data through the cloud control platform to support traffic management decisions.

[0035] The security layer implements data encryption and digital signatures to ensure the confidentiality and integrity of data during transmission and storage. This layer may include: a data encryption module that encrypts data using algorithms such as the Advanced Encryption Standard (AES); and a digital signature module that signs and verifies data using algorithms such as RSA and the Elliptic Curve Digital Signature Algorithm (ECDSA).

[0036] The vehicle-road cooperative system covers the data processing and management from vehicle-generated data to the cloud control platform, as well as the data application for traffic management. The system provides a basis for the standardized processing of vehicle-road cooperative data and a powerful tool for traffic management. The various parts work together to ensure the reliability, security and efficiency of the data.

[0037] The present disclosure provides a data processing method for a vehicle-road cooperative system, which can be applied to a cloud control platform of the vehicle-road cooperative system. FIG2 is a flow chart of the data processing method for the vehicle-road cooperative system, which mainly includes the following steps 201 to 203.

[0038] In step 201, a traffic monitoring message is received; wherein the traffic monitoring message carries traffic monitoring data, and the traffic monitoring data includes data source information and environmental condition information.

[0039] In some embodiments, environmental condition information refers to external factors and situations during the operation of the vehicle-road cooperative system, which may affect the quality and credibility of the data.

[0040] The environmental condition information includes at least one of the following environmental condition parameters: weather conditions, for example, bad weather such as rainy days, snowy days, foggy days, etc. may reduce the credibility of sensor data; traffic density, high traffic density may cause instability of vehicle sensor data; road conditions, the state of the road, such as wet, slippery, potholes, etc., may affect the accuracy of vehicle sensors; lighting conditions, low light conditions may affect the quality of traffic camera data.

[0041] In some embodiments, the data source information reflects the credibility of the data source. The data sources of the vehicle-road cooperative system include vehicle sensors, traffic cameras, traffic management centers, etc.

[0042] For example, sensors installed on vehicles can provide information such as location, speed, and acceleration. This data is generally highly reliable because it comes directly from the vehicle itself and is typically a sensor specifically designed for vehicle control and monitoring. Traffic cameras can capture images and videos of the road. These data sources are generally highly reliable but are affected by environmental conditions (such as weather and lighting). Traffic management centers can provide traffic flow data and road condition information, which are generally highly reliable.

[0043] In some embodiments, traffic monitoring data also includes traffic-related data, including vehicle data, road data, and other data. Vehicle data includes data related to vehicle operation, such as vehicle location and speed. Road data includes data related to the road on which the vehicle operates, such as road congestion.

[0044] In step 202, quality evaluation information corresponding to the traffic monitoring data is determined based on the environmental condition information and the data source information.

[0045] In some embodiments, the quality evaluation information is determined based on at least one of the following quality standards of the traffic monitoring data: data accuracy, that is, how close the data value is to the actual situation; data integrity, that is, whether the data contains all the required information; data timeliness, that is, whether the data is updated in a timely manner; data consistency, that is, whether data from different sources are consistent; data credibility, that is, whether the data is credible and the degree to which it can be trusted.

[0046] Among them, the setting of quality standards is related to the credibility of the corresponding environmental condition information and data source information. The adjustment of quality standards is usually based on environmental conditions and the credibility of the data source. Quality standards include but are not limited to: data quality metrics, data cleaning, and error repair mechanisms. When environmental conditions are not conducive to data quality (for example, bad weather), higher requirements may be required for data quality standards to ensure the credibility of the data; when the credibility of the data source is low (for example, data from low-precision sensors or smartphones), higher requirements may be required for data quality standards, including more error repair and interpolation operations.

[0047] In some embodiments, the environmental condition information includes information of at least one environmental condition parameter.

[0048] Determining the quality evaluation information corresponding to the traffic monitoring data based on the environmental condition information and the data source information includes: performing the following processing for at least one quality standard: determining a first part of the quality evaluation value corresponding to the quality standard based on the information of each environmental condition parameter included in the environmental condition information; determining a second part of the quality evaluation value corresponding to the quality standard based on the data source information; and determining the quality evaluation information corresponding to the traffic monitoring data based on the first part of the quality evaluation value and the second part of the quality evaluation value.

[0049] Illustratively, the environmental condition parameters included in the environmental condition information include at least one of weather conditions, traffic density, road conditions, and lighting conditions. Each quality standard is configured with a corresponding quality evaluation method corresponding to the environmental condition information, and a first partial quality evaluation value corresponding to the quality standard is obtained based on the quality evaluation method corresponding to the quality standard.

[0050] The data source information in the traffic monitoring data is configured with corresponding quality evaluation methods corresponding to different quality standards. For example, for the same data source, the quality evaluation method for the timeliness of the data is different from the evaluation method for the accuracy of the data.

[0051] The first part of the quality evaluation value corresponding to the quality standard is used to reflect the impact of environmental condition information on the quality of traffic monitoring data, and the second part of the quality evaluation value corresponding to the quality standard is used to reflect the impact of data source information on the quality of traffic monitoring data.

[0052] In some embodiments, determining the first part of the quality evaluation value corresponding to the quality standard based on the information of each environmental condition parameter included in the environmental condition information includes: obtaining the weight value of each environmental condition parameter in the environmental condition information corresponding to the quality standard; determining the quality score of the quality standard corresponding to the indication value of each environmental condition parameter; and determining the first part of the quality evaluation value corresponding to the quality standard based on the weight value and quality score of each environmental condition parameter corresponding to the quality standard.

[0053] In some embodiments, determining the quality score of the quality standard corresponding to the indication value of each environmental condition parameter includes: determining the quality score of the quality standard corresponding to the indication value of the environmental condition parameter based on a mapping relationship among the indication value of the preset environmental condition parameter, the quality grade of the quality standard, and the quality score.

[0054] In some embodiments, determining the quality score of the quality standard corresponding to the indication value of the environmental condition parameter based on the mapping relationship among the indication value of the preset environmental condition parameter, the quality grade of the quality standard, and the quality score includes: determining the target quality grade of the quality standard corresponding to the indication value of the environmental condition parameter based on the mapping relationship among the indication value of the preset environmental condition parameter, the quality grade of the quality standard, and the quality score, and determining the quality score corresponding to the target quality grade as the quality score of the quality standard corresponding to the indication value of the environmental condition parameter.

[0055] In some embodiments, determining the first part of the quality evaluation value corresponding to the quality standard based on the weight value and quality score of each of the environmental condition parameters corresponding to the quality standard includes: determining the target quality evaluation value of each of the environmental condition parameters corresponding to the quality standard based on the weight value of each of the environmental condition parameters corresponding to the quality standard and the product of the quality score of the quality standard; and determining the first part of the quality evaluation value of the environmental condition information corresponding to the quality standard based on the sum of each of the target quality evaluation values.

[0056] In some embodiments, determining the second part of the quality evaluation value corresponding to the quality standard based on the data source information includes: obtaining the weight value of the data source information corresponding to the quality standard; obtaining the quality score of the data source information corresponding to the quality standard; and determining the second part of the quality evaluation value of the data source information corresponding to the quality standard based on the product of the weight value of the data source information corresponding to the quality standard and the quality score corresponding to the quality standard.

[0057] In some embodiments, determining the quality evaluation information corresponding to the traffic monitoring data based on the first part quality evaluation value and the second part quality evaluation value includes: determining the quality evaluation information of the traffic monitoring data corresponding to the quality standard based on the sum of the first part quality evaluation value and the second part quality evaluation value.

[0058] For example, different indicator values ​​are set for different environmental condition parameters and data source information, that is, specific value ranges are defined to adjust the quality evaluation information, for example:

[0059] Weather condition rating range:

[0060] Good weather: score range 0.7-1.0;

[0061] Sunny day: score range 0.6-0.79;

[0062] Cloudy: score range 0.5-0.69;

[0063] Rainy day: score range 0.4-0.59;

[0064] Snowy days: score range 0.3-0.49;

[0065] Foggy day: score range 0.0-0.29;

[0066] Traffic density score range:

[0067] Low traffic density: score range 0.7-1.0;

[0068] Medium traffic density: score range 0.5-0.69;

[0069] High traffic density: score range 0.0-0.49;

[0070] Road condition rating range:

[0071] Excellent road conditions: score range 0.8-1.0;

[0072] Good road conditions: score range 0.6-0.79;

[0073] Moderate road conditions: score range 0.4-0.59;

[0074] Poor road conditions: score range 0.0-0.39;

[0075] Lighting condition rating range:

[0076] Bright light conditions: score range 0.7-1.0;

[0077] Medium light conditions: score range 0.5-0.69;

[0078] Low light conditions: score range 0.0-0.49;

[0079] The credibility score range corresponding to the data source information is:

[0080] High-credibility data source: score range 0.8-1.0;

[0081] Moderately reliable data sources: score range 0.6-0.79;

[0082] Low-credibility data source: score range 0.0-0.59.

[0083] Exemplarily, the mapping relationship between the indicated value of the environmental condition parameter and the quality grade of the quality standard is expressed as follows:

[0084] Weather conditions: rated as "good" (score range 0.7-1.0);

[0085] Traffic density: Rated as "medium" (score range 0.5-0.69);

[0086] Road conditions: Rated "Excellent" (score range 0.8-1.0);

[0087] Lighting conditions: rated as "poor" (score range 0.0-0.49);

[0088] Data source credibility: Rated as "excellent" (score range 0.8-1.0);

[0089] According to the weight distribution (the weight of each factor has been defined), the quality score of each factor is calculated, and then the comprehensive quality score is calculated as follows:

[0090] Weather condition score: 0.85;

[0091] Traffic density score: 0.59;

[0092] Road condition score: 0.9;

[0093] Lighting condition score: 0.2;

[0094] Data source credibility score: 0.9.

[0095] Comprehensive quality score calculation:

[0096] Comprehensive quality score = (0.85*0.2)+(0.59*0.2)+(0.9*0.2)+(0.2*0.1)+(0.9*0.3)=0.67.

[0097] Based on the range of the overall quality score, the data is considered high quality (0.67 is within the range of 0.6-0.79), and therefore can be used directly. Different processing strategies will be adopted for different overall quality score ranges to ensure that the data can be appropriately used in various scenarios.

[0098] In some embodiments, the data source information includes a sender identifier, a receiver identifier, a timestamp, and a version number. Each received traffic monitoring message uses the same standard message format, and the traffic monitoring message includes a message header and a message body. The message header includes the message type, sender identifier, receiver identifier, timestamp, and version number. The message body includes traffic monitoring data, such as the vehicle's operating information, which includes the vehicle's location information, speed information, and traffic condition information.

[0099] The standard message format is predefined and includes a message header and a message body. The message header includes metadata such as the message type, sender ID, receiver ID, timestamp, and version number. The message body contains specific data fields. For example, the standard message format is represented as follows:

[0100] In some embodiments, the data field includes traffic monitoring data, such as vehicle location information, speed information, and traffic condition information. The following are some possible field examples:

[0101] In some embodiments, the data field supports multimedia data, such as images, videos, and sounds. This data can be stored in a linked or encoded format, and metadata can be provided to describe the multimedia data. For example, a data field that includes an image representing traffic conditions via a link is represented as follows:

[0102] In the disclosed embodiments, the consistency and interpretability of data in the VIS are ensured by standardizing the message format. For example, the message format standardization process is shown in FIG3 .

[0103] In step 203, the quality evaluation information is added to the corresponding traffic monitoring message and saved.

[0104] In some embodiments, the adjustment of quality standards may affect the data processing process. For example, when a data source with low credibility needs to be updated for data cleaning and error repair, the data content may change to meet higher quality standards. Changes in data content include correction of data values, data interpolation to fill missing values, etc.

[0105] In some embodiments, the quality evaluation information in the traffic monitoring message is very important for subsequent data analysis and processing. For example, the system can automatically filter or mark low-quality data based on the quality evaluation information to ensure that analysis and decision-making are based on high-quality data.

[0106] In some embodiments, the data processing method also includes performing data processing based on the traffic monitoring message, and the processing may include: screening and filtering out low-quality messages from each of the traffic monitoring messages according to the quality evaluation information in each of the traffic monitoring messages, wherein the quality evaluation value indicated by the quality evaluation information of the low-quality message is lower than a preset low-quality threshold value.

[0107] It should be noted that, when there is quality evaluation information corresponding to multiple quality standards, data processing is performed on the traffic monitoring message for the quality evaluation information of each quality standard respectively, wherein the process of data processing the traffic monitoring message for the quality evaluation information corresponding to any quality standard includes: according to the quality evaluation information corresponding to the quality standard in each traffic monitoring message, low-quality messages corresponding to the quality standard are screened and filtered out from each traffic monitoring message, wherein the quality evaluation value indicated by the quality evaluation information of the low-quality message corresponding to the quality standard is lower than the preset low-quality threshold value corresponding to the quality standard.

[0108] In some embodiments, the data processing method further includes: determining a preprocessing method corresponding to the traffic monitoring message based on the quality evaluation information in the traffic monitoring message, and preprocessing the traffic monitoring message using the preprocessing method.

[0109] In an exemplary embodiment, a preprocessing level corresponding to the traffic monitoring message is determined based on the quality evaluation information corresponding to at least one quality standard in the traffic monitoring message; and the traffic monitoring message is preprocessed using a preprocessing method corresponding to the preprocessing level.

[0110] In some embodiments, the quality evaluation information in the traffic monitoring message can also be used to generate a data quality report to help users understand the credibility level of the data, so as to better use the data to make decisions.

[0111] In some embodiments, the performing data processing based on the traffic monitoring message includes: generating a data quality report based on the traffic monitoring message.

[0112] Exemplarily, the data quality report includes at least one of the following:

[0113] Detailed description of the quality evaluation information corresponding to the quality standard, for example, detailed information on data quality indicators such as accuracy, completeness, timeliness, consistency and credibility, such as the score and weight of each indicator;

[0114] The environmental condition information includes changes in data quality under different environmental conditions, such as data quality performance under different weather conditions, traffic density, road conditions, and lighting conditions, and these changes may be presented in charts or graphs;

[0115] The data source credibility indicated by the data source information, i.e., the credibility level of different data sources, may be highlighted in the quality report. This may be achieved by labeling, scoring, or color coding different data sources so that users can quickly identify and understand the credibility of the data;

[0116] Historical traffic monitoring data received within a set time period, and a data quality change trend of the historical traffic monitoring data over time, wherein the data quality change trend is determined based on quality evaluation information corresponding to the quality standard for each of the historical traffic monitoring data; historical data and trend icons can enhance the information value of the report, so that users can understand changes in data quality over time;

[0117] Abnormal data and alarm information, wherein the abnormal data is determined based on the quality evaluation information of the quality standard, and the alarm information is used to indicate abnormal data, for example, the report highlights any data quality anomalies or issues exceeding thresholds and provides alarm information so that users can take corrective measures in a timely manner;

[0118] Visualizing data generated based on the traffic monitoring messages, for example, using data visualization tools such as graphs, charts, and heat maps to represent data to enhance the readability and comprehensibility of the report. Appropriate data visualization can make complex data quality information clearer;

[0119] Based on the human-computer interaction data generated by the traffic monitoring messages, the report is designed to be interactive, allowing users to deeply explore the data quality information according to their needs and concerns. For example, users can view specific data quality aspects by clicking on a chart or selecting different filter conditions;

[0120] A summary and recommendations of the analysis results of the traffic monitoring information. For example, the end of the report should include a concise summary that summarizes the overall status of data quality and provides relevant recommendations or decision support, which helps users quickly understand the core issues and solutions of data quality;

[0121] Customized content generated according to customized requirements. Considering that different users may have different concerns, the reports have a certain degree of customizability so that users can customize the data quality information and visualization methods they need; and

[0122] Marking information for key content, for example, using colors, symbols, or other identification methods to highlight important data quality information and indicators to guide users to focus on key aspects.

[0123] By comprehensively considering these factors, or at least some of them, a clear, easy-to-understand, and highly visible quality report can be created, which improves the visibility and information integrity of the report, helps users better understand the quality status and credibility of the data, and supports better decision-making.

[0124] In some embodiments, an error recovery mechanism is performed on traffic monitoring messages in the following manner:

[0125] Process for identifying data errors:

[0126] 1. Outlier Detection: Identify potential errors by analyzing abnormal values ​​or outliers in the data. For example, if the vehicle speed suddenly increases from 60 km / h to 600 km / h, this may be an outlier.

[0127] 2. Data consistency check: Check whether the data is inconsistent with other related data or environmental conditions. For example, if the vehicle position data shows that the car is flying in the air, this is obviously inconsistent.

[0128] 3. Historical data comparison: Compare the newly collected data with the historical data to see if there are any unreasonable changes or differences.

[0129] 4. Sensor self-diagnosis: Some sensors have self-diagnosis functions and can detect their own faults or abnormalities.

[0130] Data error repair process:

[0131] 1. Interpolation: For missing data points, interpolation methods can be used to estimate the missing values. Common interpolation methods include linear interpolation and polynomial interpolation.

[0132] 2. Filters: Use filters to smooth data and remove noise and outliers. Common filters include mean filtering and median filtering.

[0133] 3. Data correction: Correct inaccurate data based on known accurate data sources. For example, vehicle sensor data can be corrected by comparing it with data from a traffic management center.

[0134] The repaired data should be re-labeled with quality assessment information based on its quality standards to reflect the impact of the repair operation on the data. The repaired data can be used for further processing, analysis, and decision-making in the system. At the same time, the repair operation and the repaired data should be recorded and reported for subsequent review and analysis. This can help ensure the quality and credibility of the data. For example, the repaired data is as follows:

[0135] In an exemplary embodiment, a calculation standard for quality evaluation information is pre-established to comprehensively evaluate the quality of traffic monitoring data under different environmental conditions and data sources. As shown in Figure 4a, the formulation process includes the following key steps:

[0136] 1. Define environmental conditions and data source information, taking into account key factors such as weather conditions, traffic density, road conditions, lighting conditions, and the credibility of the data source;

[0137] 2. Assign weights to each factor based on its importance to data quality, ensuring the overall score is between 0 and 1;

[0138] 3. Define quality levels for each factor, such as excellent, good, medium, and poor;

[0139] 4. Assign a score range to each factor and a score range to each quality grade. These ranges will be used to calculate the quality score for each factor.

[0140] 5. Calculate the quality score of each factor. Map the rating of each factor to the corresponding score range based on the actual situation and calculate the quality score;

[0141] 6. Calculate the comprehensive quality score. Use the weights to sum the quality scores of each factor to obtain the comprehensive quality score. This comprehensive quality score is the quality evaluation information.

[0142] 7. Determine data quality and process it, deciding how to handle the data based on the range of the overall quality score to ensure that data quality is appropriately managed in all situations.

[0143] In some embodiments, a data encryption and digital signature mechanism is introduced to encrypt and digitally sign traffic monitoring messages to ensure the confidentiality and integrity of the data. Standard encryption algorithms and signature methods, such as RSA or ECDSA, can be used.

[0144] In one exemplary embodiment, as shown in Figure 4b, the process of developing a communication protocol includes defining a data transmission protocol, which includes data packaging, compression, and transmission methods. The protocol design takes into account the low latency characteristics of 5G to achieve efficient data transmission. This protocol ensures reliable message delivery and correct interpretation by the recipient.

[0145] Data packaging may include:

[0146] 1. Message format definition: Define the structure of the message, usually using structured data formats such as JSON or XML to ensure the parsability and consistency of the message.

[0147] 2. Message header: The message header should include metadata information such as message type, sender, receiver, timestamp, and version number. This information helps the receiver to correctly parse and process the message.

[0148] 3. Message: The message body should contain specific data fields, such as location, speed, traffic conditions, etc. Ensure that the data fields in the message body are arranged according to the specifications so that the receiver can correctly parse them.

[0149] 4. Data encoding: Data fields should be encoded in a unified way to ensure interoperability between different platforms. Typically, UTF-8 is used to encode text data, and a standard numerical representation is used.

[0150] Data compression can include:

[0151] 1. Select a compression algorithm: Select the Brotli data compression algorithm, which maintains a high compression ratio while having low latency, making it suitable for use in vehicle-road cooperative systems.

[0152] 2. Pre-compression processing: Before compression, data can be pre-processed, such as removing unnecessary spaces and line breaks, to improve compression efficiency.

[0153] 3. Decompression: The data is decompressed using the same compression algorithm at the receiving end to restore the original message.

[0154] Data transmission method:

[0155] Data transmission uses V2V communication. V2V communication utilizes direct connections between vehicles without going through a central server, which can achieve low-latency and high-reliability data transmission. In addition, the support of 5G technology further improves the performance of V2V communication.

[0156] Through the above methods, data packaging, compression and transmission can be realized in an efficient and reliable manner in the vehicle-road cooperative system to meet the needs of real-time monitoring and traffic management.

[0157] In an embodiment of the present disclosure, when receiving a traffic monitoring message, a quality evaluation is performed on the traffic monitoring data based on the data source information and environmental condition information of the traffic monitoring data carried in the traffic monitoring message, and the (or corresponding) quality evaluation information of the traffic monitoring data is obtained. The quality evaluation information is carried in the traffic monitoring message, so that subsequent data processing can execute different processing rules based on the quality evaluation information, thereby improving the processing efficiency of the vehicle-road cooperative system, ensuring the accuracy, security and sustainability of the data, and providing the possibility of improving the efficiency, safety and sustainability of traffic management.

[0158] In addition, in the embodiments of the present disclosure, by formulating a standard message format in the vehicle-road cooperative system, the traffic monitoring data interacting in the vehicle-road cooperative system are all transmitted in the standard message format, quality evaluation is performed according to at least one quality standard, quality evaluation information corresponding to at least one quality standard is obtained, and the quality evaluation information is carried in the standardized traffic monitoring message, so that traffic monitoring messages in the standard message format are exchanged between the devices in the vehicle-road cooperative system, eliminating the differences in the traffic monitoring message formats from different devices, and laying the foundation for improving data processing efficiency; and, by adding quality evaluation information of the data to the standardized message, subsequent data processing can execute different processing rules based on the quality evaluation information, ensuring the accuracy, security and sustainability of the data, and providing the possibility of improving the efficiency, security and sustainability of traffic management.

[0159] In the disclosed embodiments, the standardization of message formats is introduced, making it easier for different vehicles and systems to exchange and understand data, thereby reducing the technical complexity in terms of integration and interoperability.

[0160] In this disclosed embodiment, a dynamic data quality control mechanism is introduced, adjusting data quality standards in real time based on the credibility of the data source and environmental conditions. This means that traffic management systems can more reliably utilize vehicle data, improve decision-making accuracy, and ensure the accuracy and reliability of vehicle-infrastructure collaborative data in different scenarios.

[0161] In the disclosed embodiments, by supporting multimedia data, such as images, videos, and sounds, these data can be seamlessly integrated into a standardized message format, enabling a traffic management center to have a more comprehensive understanding of traffic conditions and thus better respond to incidents and problems without the need for a separate multimedia processing system.

[0162] In the disclosed embodiment, data encryption and digital signatures are introduced to ensure the confidentiality and integrity of vehicle data, provide a higher level of data security protection, and ensure the confidentiality and integrity of data during transmission and storage, which helps prevent data leakage and tampering and improves the security of the entire system.

[0163] In the disclosed embodiments, the advantages of advanced communication technologies such as 5G and C-V2X are fully utilized to achieve low-latency, high-bandwidth data transmission, making vehicle-road collaboration more responsive.

[0164] In the disclosed embodiments, due to the standardization and quality control of data, the traffic management center can more accurately monitor traffic conditions, predict congestion, and perform intelligent route optimization, thereby improving urban traffic mobility.

[0165] In summary, the improvements in data standardization, quality control, multimedia data support, data security enhancement, and intelligent traffic management made by the embodiments of the present disclosure will help improve the efficiency, safety, and sustainability of the transportation system.

[0166] Possible applications of the embodiments of the present disclosure include but are not limited to the following aspects:

[0167] 1. Intelligent Traffic Management: This technology can be applied to intelligent traffic management systems to monitor vehicle location, speed, traffic conditions, and multimedia data in real time to support traffic light optimization, optimize traffic flow, provide early warning of traffic incidents, and improve traffic safety.

[0168] 2. Traffic decision support: Traffic management centers can use standardized data to support traffic decision-making, including route optimization, traffic congestion management, incident response, and traffic signal control.

[0169] 3. Autonomous driving and vehicle connectivity: Autonomous driving vehicles and vehicle connectivity communications require accurate and real-time data. The disclosed embodiments provide standardized processing of this data to support the development of autonomous driving systems and communication between connected vehicles.

[0170] 4. Urban Planning and Smart Cities: Urban planners can use vehicle data to improve urban planning, including the design of transportation infrastructure and the optimization of public transportation systems, thereby creating smarter and more sustainable cities.

[0171] 5. Vehicle safety: The data standardization and dynamic data quality control of the disclosed embodiments help improve vehicle safety. Traffic management centers can more accurately monitor traffic conditions, warn drivers, and take measures to avoid accidents.

[0172] 6. Emergency response and rescue: The multimedia data support of the embodiments of the present disclosure can be used for rapid response to accidents and rescue operations in emergency situations, and rescue personnel can better understand the situation through video and sound data.

[0173] 7. Environmental Monitoring: The data standardization and multimedia support of the disclosed embodiments can also be used for environmental monitoring, such as monitoring pollution or environmental changes caused by traffic.

[0174] 8. Road safety monitoring: The application environment can be used for road safety monitoring, including pedestrian detection, traffic sign recognition and traffic accident detection.

[0175] 9. Traffic flow optimization: The embodiments of the present disclosure can be used to optimize traffic flow, reduce traffic congestion, and improve road utilization efficiency.

[0176] 10. Personalized transportation services: The application environment can provide personalized transportation suggestions and route planning based on the user's travel habits and preferences.

[0177] The disclosed embodiments may have many other potential uses, depending on specific market needs and innovative applications. The application areas can be continuously expanded based on market demand and technological development. The disclosed embodiments can be applied in multiple intelligent transportation fields, aiming to improve road safety, traffic efficiency, and user experience.

[0178] The application environment of the embodiments of the present disclosure can incorporate the following technologies to improve intelligence, stability, security, and processing efficiency:

[0179] 1. Machine Learning and Deep Learning: Use machine learning and deep learning technologies for data classification and analysis to improve the efficiency of standardization processes. The application environment includes the hardware and software infrastructure that supports these technologies, including high-performance graphics processing units (GPUs) and machine learning frameworks such as TensorFlow and PyTorch.

[0180] 2. Data standardization tools: To achieve data standardization, the application environment has data format conversion tools and standardization libraries to ensure that data collected by different devices can be converted into a unified format.

[0181] 3. Distributed computing technology: To efficiently process large-scale data, the application environment supports distributed computing technologies such as Apache Spark and Hadoop to achieve parallel processing and analysis of data.

[0182] 4. Data security and privacy protection: Since sensitive traffic data is involved, the application environment needs to adopt enhanced data security and privacy protection measures, including data encryption, access control, and authentication.

[0183] 5. Real-time data stream processing: Data streams need to be monitored and analyzed in real time, and the application environment needs to have real-time data processing technology to support real-time traffic monitoring, predictive analysis, and decision support.

[0184] The steps of the various methods above are divided only for clarity of description. During implementation, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this disclosure. Adding insignificant modifications or introducing insignificant designs to the algorithm or process without changing the core design of the algorithm and process are all within the scope of protection of this disclosure.

[0185] The present disclosure provides a data processing device for a vehicle-road cooperative system. The specific implementation of the device can be found in the relevant description of the method embodiment and will not be repeated here. FIG5 shows a schematic diagram of the structure of the device, which mainly includes: an acquisition module 501, a standardization module 502, and a processing module 503.

[0186] The acquisition module 501 is configured to receive a traffic monitoring message; wherein the traffic monitoring message carries traffic monitoring data, and the traffic monitoring data includes data source information and environmental condition information.

[0187] The standardization module 502 is configured to determine the quality evaluation information corresponding to the traffic monitoring data according to the environmental condition information and the data source information.

[0188] The processing module 503 is configured to add the quality evaluation information to the corresponding traffic monitoring message and save it.

[0189] The functions or modules included in the apparatus provided in the embodiments of the present disclosure can be used to execute the method described in the method embodiments. The specific implementation and technical effects thereof can be referred to the description of the above method embodiments, and will not be repeated here for the sake of brevity.

[0190] It should be noted that all modules involved in this embodiment are logical modules. In actual applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, to highlight the innovations of this disclosure, this embodiment does not include units that are not closely related to solving the technical problems proposed by this disclosure. However, this does not mean that other units do not exist in this embodiment.

[0191] The embodiment of the present disclosure also provides a vehicle-road cooperative system, including: a communication module and a cloud control platform.

[0192] a communication module configured to obtain traffic monitoring data, generate a traffic monitoring message, and report it to the cloud control platform via a communication network, wherein the traffic monitoring message carries the traffic monitoring data, and the traffic monitoring data includes data source information and environmental condition information;

[0193] The cloud control platform is configured to receive the traffic monitoring message; determine the quality evaluation information corresponding to the traffic monitoring data based on the environmental condition information and the data source information; and add the quality evaluation information to the corresponding traffic monitoring message and save it.

[0194] The communication module includes on-board communication modules, roadside units and other communication devices that can obtain vehicle-road monitoring data and transmit it to the central control platform.

[0195] 6 , an embodiment of the present disclosure provides an electronic device, comprising: at least one processor 601; a memory 602 on which at least one program is stored, and when the at least one program is executed by the at least one processor, the at least one processor implements the above method; and at least one I / O interface 603, connected between the processor and the memory, and configured to implement information interaction between the processor and the memory.

[0196] Among them, the processor 601 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 602 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read-write interface) 603 is connected between the processor 601 and the memory 602, and can realize information interaction between the processor 601 and the memory 602, including but not limited to a data bus (Bus), etc.

[0197] In some embodiments, the processor 601 , the memory 602 , and the I / O interface 603 are connected to each other via a bus, and further connected to other components of the computing device.

[0198] This embodiment further provides a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the method provided in this embodiment is implemented. To avoid repeated description, the specific steps of the method are not repeated here.

[0199] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods applied for above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As is well known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable, and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those skilled in the art that communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0200] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0201] Those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features from different embodiments is meant to be within the scope of the present embodiment and to form different embodiments.

[0202] It is understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present disclosure, and the present disclosure is not limited thereto. Those skilled in the art may make various modifications and improvements without departing from the spirit and substance of the present disclosure, and such modifications and improvements are also considered to be within the scope of protection of the present disclosure.

Claims

1. A data processing method for a vehicle-road cooperative system, comprising: Receiving a traffic monitoring message, wherein the traffic monitoring message carries traffic monitoring data, and the traffic monitoring data includes data source information and environmental condition information; Determining quality evaluation information corresponding to the traffic monitoring data according to the environmental condition information and the data source information; and The quality evaluation information is added to the corresponding traffic monitoring message and saved.

2. The method according to claim 1, wherein: The quality evaluation information is determined based on at least one of the following quality criteria: The accuracy of the data; Data integrity; Timeliness of data; Data consistency; Credibility of data.

3. The method according to claim 2, wherein: Determining the quality evaluation information corresponding to the traffic monitoring data according to the environmental condition information and the data source information includes performing the following processing for at least one of the quality standards: Determine a first part of the quality evaluation value corresponding to the quality standard according to the information of each environmental condition parameter included in the environmental condition information; Determining, according to the data source information, a second part of the quality evaluation value corresponding to the quality standard; Quality evaluation information corresponding to the traffic monitoring data is determined according to the first part of the quality evaluation value and the second part of the quality evaluation value.

4. The method according to claim 3, wherein: The determining, according to information of each environmental condition parameter included in the environmental condition information, a first part of the quality evaluation value corresponding to the quality standard comprises: Obtaining a weight value of each environmental condition parameter in the environmental condition information corresponding to the quality standard; Determine the mass fraction of the indicated value of each of the environmental condition parameters corresponding to the quality standard; According to the weight value and quality score of each of the environmental condition parameters corresponding to the quality standard, a first part of the quality evaluation value corresponding to the quality standard is determined.

5. The method according to claim 4, wherein: The step of determining the quality score of the quality standard corresponding to the indication value of each of the environmental condition parameters includes: According to the mapping relationship among the indication value of the preset environmental condition parameter, the quality grade of the quality standard and the quality score, it is determined that the indication value of the environmental condition parameter corresponds to the quality score of the quality standard.

6. The method according to claim 5, wherein: The step of determining the quality score of the quality standard corresponding to the indication value of the environmental condition parameter according to a mapping relationship among the indication value of the preset environmental condition parameter, the quality grade of the quality standard, and the quality score comprises: According to the mapping relationship among the indication value of the preset environmental condition parameter, the quality grade of the quality standard and the quality score, determine that the indication value of the environmental condition parameter corresponds to the target quality grade of the quality standard, and determine the quality score corresponding to the target quality grade as the quality score of the quality standard corresponding to the indication value of the environmental condition parameter.

7. The method according to claim 4, wherein: Determining the first part of the quality evaluation value corresponding to the quality standard according to the weight value and the quality score of each of the environmental condition parameters corresponding to the quality standard includes: Determine the target quality evaluation value of each environmental condition parameter corresponding to the quality standard according to the product of the weight value of each environmental condition parameter corresponding to the quality standard and the quality score corresponding to the quality standard; A first part of the quality evaluation value of the environmental condition information corresponding to the quality standard is determined according to the sum of the target quality evaluation values.

8. The method according to claim 3, wherein: Determining the second part of the quality evaluation value corresponding to the quality standard according to the data source information includes: Obtaining a weight value of the data source information corresponding to the quality standard; Obtaining the quality score of the data source information corresponding to the quality standard; The second part of the quality evaluation value of the data source information corresponding to the quality standard is determined according to the product of the weight value of the data source information corresponding to the quality standard and the quality score corresponding to the quality standard.

9. The method according to claim 3, wherein: The determining, according to the first part of the quality evaluation value and the second part of the quality evaluation value, the quality evaluation information corresponding to the traffic monitoring data includes: The quality evaluation information of the traffic monitoring data corresponding to the quality standard is determined according to the sum of the first part quality evaluation value and the second part quality evaluation value.

10. The method according to claim 1, wherein: The environmental condition information includes at least one of the following environmental condition parameters: Weather conditions; Traffic density; Road conditions; Lighting conditions.

11. The method according to claim 1, further comprising: According to the quality evaluation information in each of the traffic monitoring messages, low-quality messages are screened and filtered out from each of the traffic monitoring messages, wherein the quality evaluation value indicated by the quality evaluation information of the low-quality message is lower than a preset low-quality threshold value.

12. The method according to claim 1, further comprising: According to the quality evaluation information in the traffic monitoring message, a preprocessing method corresponding to the traffic monitoring message is determined, and the traffic monitoring message is preprocessed using the preprocessing method.

13. The method according to claim 1, wherein: The method further comprises: A data quality report is generated based on the traffic monitoring message.

14. A vehicle-road cooperative system, comprising: a communication module, configured to obtain traffic monitoring data, generate a traffic monitoring message, and report it to the cloud control platform through a communication network, wherein the traffic monitoring message carries the traffic monitoring data, and the traffic monitoring data includes data source information and environmental condition information; and The cloud control platform is configured to receive the traffic monitoring message; determine the quality evaluation information corresponding to the traffic monitoring data according to the environmental condition information and the data source information; and add the quality evaluation information to the corresponding traffic monitoring message and save it.

15. An electronic device, comprising: at least one processor; A memory having at least one program stored thereon, wherein when the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 13; as well as At least one I / O interface is connected between the processor and the memory and is configured to implement information interaction between the processor and the memory.

16. A computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method according to any one of claims 1 to 13.

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