Cloud control service and roadside equipment data quality online authentication system
By using end-to-end authentication through cloud and roadside data services, combined with offline and online verification, a unique electronic tag is generated, which solves the problems of insufficient real-time performance and coverage of data quality verification in existing technologies, and improves the trustworthiness of cloud control services and the reliability of authentication results.
Patent Information
- Application Number
- CN202511421882.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-30
- Publication Date
- 2025-12-16
AI Technical Summary
In existing technologies, the single-point sampling inspection commonly used in vehicle-road-cloud systems is insufficient in terms of real-time performance and coverage, cannot adapt to diverse data quality requirements, and the verification results cannot reach end users, resulting in low trust in cloud control services.
The system employs a cloud service authentication module, a roadside service authentication module, and an electronic tag generation module. Data verification is performed through 4G/5G and LTE-V2X networks. By combining offline and online verification, a unique electronic tag is generated, achieving full-link coverage and hierarchical authentication, and ensuring that authentication results reach end users in real time.
It achieves data quality certification covering all scenarios, enhances the trustworthiness of cloud control services, meets diverse needs, forms a closed-loop process of certification-feedback-trust, and ensures the timeliness and reliability of certification results.
Smart Images
Figure CN121151889A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of vehicle-road-cloud data service technology, specifically to a cloud control service and an online authentication system for roadside equipment data quality. Background Technology
[0002] Currently, a new round of technological revolution and industrial transformation is developing in depth, and the integration of automotive, transportation, and information and communication technologies is accelerating, driving the rapid evolution of vehicle-road-cloud collaborative autonomous driving systems. This system relies on technologies such as roadside perception, edge computing, cloud-to-ground fusion, and C-V2X / 4G / 5G communication to achieve multi-dimensional collaboration between vehicles, roads, and the cloud. Its aim is to improve the performance of autonomous vehicles in terms of safety, efficiency, energy saving, and comfort, and to promote overall traffic optimization.
[0003] Against this backdrop, cloud control services provide critical data support from the cloud and roadside to intelligent connected vehicles via wireless communication, and their reliability has become the core foundation for the construction of the entire vehicle-road-cloud ecosystem. However, the current requirements of vehicle-side service data quality are becoming increasingly stringent with the increasing penetration rate of connected vehicles and the increased participation of automakers, and are showing diversified and divergent characteristics. The data quality indicator requirements of different intelligent driving functions are even mutually exclusive.
[0004] The single-point sampling inspection commonly used in existing technologies has significant shortcomings in terms of real-time performance and coverage, and the single evaluation index is difficult to adapt to diverse needs. More importantly, the verification results cannot reach the intelligent connected vehicles that are the end users of cloud control services, resulting in the inspection process failing to form a business loop and no longer meeting the actual needs of vehicle-road-cloud integrated construction. Summary of the Invention
[0005] The present invention aims to provide an online authentication system for cloud control services and roadside equipment data quality, in order to solve the problems of low trust in cloud control services and inability to reach end users in the prior art.
[0006] To achieve the above objectives, the present invention adopts the following technical solution: an online authentication system for cloud control services and roadside equipment data quality, comprising a cloud service authentication module, a roadside service authentication module, and an electronic tag generation module; The cloud service authentication module communicates with a third-party cloud control platform via a 4G / 5G network to perform online stability verification and data content verification of cloud data services. The roadside service authentication module communicates with roadside devices through the LTE-V2X network and performs static and dynamic information verification on roadside V2X messages by combining offline and online verification methods. The electronic tag generation module generates an electronic tag containing a unique code based on the verification results of the cloud service authentication module and the roadside service authentication module. The electronic tag is used to identify the data service quality level and supports online query by end users.
[0007] The principle behind this solution is: This solution employs end-to-end coverage of cloud and roadside data services, authenticating data security, message protocols, and data quality to achieve full-scenario coverage of cloud and roadside messaging services. Simultaneously, a layered verification mechanism is adopted. Cloud services monitor and verify service stability and data content in real time, while roadside services perform separate verification of static and dynamic information. This combination of offline verification and online automatic monitoring ensures the timeliness and reliability of authentication results. Furthermore, a multi-factor data quality authentication system is constructed, designing tiered authentication and electronic tags. A unique electronic tag is generated for each service, enabling authentication results to reach end users in real time.
[0008] The advantages of applying this solution are as follows: 1. This solution integrates online automatic verification and offline authentication, covering cloud and roadside data services across all scenarios, ensuring the comprehensiveness and real-time nature of authentication, and solving the problems of insufficient real-time performance and coverage of traditional single-point sampling; 2. By using electronic tags to deliver authentication results to end users, a closed-loop process of authentication-feedback-trust is formed, enhancing the vehicle's trust in cloud control services; 3. Construct a demand space and hierarchical evaluation scale based on scenario elements, and achieve dynamic and precise adjustment of quality level through data instance deviation analysis to meet diverse and divergent data quality needs. Attached Figure Description
[0009] Figure 1 This is a schematic diagram of the structure of a cloud control service and roadside equipment data quality online authentication system according to the present invention; Figure 2 This is a flowchart illustrating the cloud control service and roadside equipment data quality online authentication system of the present invention. Detailed Implementation
[0010] The following detailed description illustrates the specific implementation method: Example 1 This embodiment presents an online authentication system for cloud control services and roadside equipment data quality, which integrates online automatic verification and offline authentication to ensure the timeliness and reliability of authentication results and improve the trust of intelligent connected vehicles in cloud control services.
[0011] In this embodiment, as shown in the appendix Figure 1 and attached Figure 2As shown, an online authentication system is first built, including a front-end web page, a back-end data service, and a data storage architecture. The data storage architecture adopts a distributed storage design, supporting parallel authentication of roadside devices in multiple areas and historical data tracing and querying. Furthermore, this authentication system supports both HTTP synchronous communication and MQTT asynchronous communication modes, enabling it to simulate data terminals sending requests and rate services based on the response results.
[0012] In this embodiment, the online authentication system includes a cloud service authentication module, a roadside service authentication module, and an electronic tag generation module. These modules are all communicatively connected.
[0013] It also includes an authentication process management module, which manages the authentication process and inputs relevant information. For example, for the cloud service authentication module, the authentication process management module manages the cloud service authentication process, registers the third-party cloud control platform, and inputs the data service information provided by it to the vehicle, including the access address, data service acquisition method, request parameters, etc., and sets the data service verification frequency and data verification rules for each field. The system creates a unique authentication electronic tag based on the access address. The online authentication system automatically accesses the data service of the registered third-party cloud control platform at regular intervals. It verifies the service data content according to the set rules. If it meets the verification rules, the electronic tag indicates that the data service is qualified; if it does not meet the rules, it indicates that the data service is abnormal.
[0014] For the roadside service authentication module, the authentication process for roadside message services is managed through the authentication process management module. This includes registering networked intersection information and entering intersection coordinates, the type of message service provided, and other relevant details. The system creates a unique electronic authentication tag for each type of service message at the intersection. If the service message quality and data quality meet the standard conditions, the corresponding electronic tag indicates that the message service is qualified; otherwise, the message service is marked as abnormal.
[0015] In this embodiment, the cloud service authentication module communicates with a third-party cloud control platform via a 4G / 5G network to obtain various data services from the cloud platform, such as differential signals, path planning, and traffic light information. In this embodiment, the communication method primarily uses HTTP synchronous communication or MQTT asynchronous message communication. This is used for online stability verification and data content verification of the cloud data services.
[0016] Specifically, the cloud service authentication module includes a service stability verification unit and a data content verification unit.
[0017] The service stability verification unit is used to monitor the status of cloud services in real time through online listening. The authentication system simulates the data terminal and requests cloud services. The service stability verification unit counts the service online rate to verify stability and counts the average request response latency.
[0018] The data content verification unit is used to verify the legality and logical consistency of data through preset rules, which include data legality rules and self-consistency logic checking algorithms.
[0019] In this embodiment, the data validity rules include verification rules such as protocol consistency checks, field non-empty checks, data format checks, numerical range checks, and status type checks. The self-consistency logic check algorithm includes verifying whether the data logic is contradictory and whether the information conforms to common sense. Verification rules and parameters are configured through the authentication system, and requests are periodically sent to the service under test. The service quality is rated based on the request results.
[0020] The roadside service authentication module communicates with roadside devices through the LTE-V2X network and performs static and dynamic information verification on roadside V2X messages by combining offline and online verification methods.
[0021] In this embodiment, roadside messages are broadcast by the Roadside Communicator Unit (RSU), and the message types are MAP, SPAT, RSI, and RSM. In this embodiment, MAP map data and traffic signs in RSI are set as static information, traffic events in RSI are set as semi-static information, and SPAT and RSM messages are dynamic messages.
[0022] The roadside service authentication module includes a static information verification unit and a dynamic information verification unit. The static information verification unit includes offline static verification and offline sampling semi-static verification. Static verification is used to verify the accuracy of MAP map data and the consistency of RSI traffic sign information. Semi-static verification is used to verify the accuracy of traffic event messages in the RSI.
[0023] The dynamic information verification unit is used to detect the data quality of SPAT messages and RSM messages by combining offline and online automatic monitoring. The specific verification methods are shown in Table 1 below.
[0024] Table 1
[0025] As shown in Table 1 above, in this embodiment, SPAT message detection includes message performance indicator verification, light status delay verification, and traffic light data driving direction control consistency verification (lane permitted driving direction mapping relationship). Among them, light status delay verification is performed by comparing the delay between the light status switching time broadcast by the roadside equipment and the actual traffic signal light status switching time offline, calculating the light status switching delay time, and triggering an early warning mechanism when the delay exceeds 100ms.
[0026] The automated verification of traffic light data consistency in driving direction control is achieved through a combination of offline and online methods. This involves detecting whether the traffic light phases controlling the permitted driving directions of each lane via roadside SPAT messages match the actual situation. In this embodiment, driving data uploaded by intelligent connected vehicles to the cloud platform is aggregated. Electronic fences are established at each connected intersection and road segment. Based on the order in which vehicles pass through the electronic fences at each intersection, the method of vehicle passage through the signal-controlled connected intersection (including straight, left turn, and right turn) is analyzed, and the corresponding traffic light phases controlling the driving direction are matched. The proportion of red-light violations and phase configurations are analyzed. When an anomaly is detected, an electronic tag is triggered for identification. In this embodiment, if the proportion of corresponding traffic lights being red during the vehicle passage period is ≥80%, it is considered that a connected vehicle has violated a red light. If the proportion of red-light violations is >10% among all passage samples through the intersection, it is considered that the traffic light phase configuration may be abnormal, and the corresponding certified electronic tag indicates an anomaly in the intersection's SPAT message service.
[0027] In this embodiment, when the traffic light configuration scheme changes, the mapping relationship between the lane's permitted driving direction and phase will become mismatched. The authentication system accesses SPAT messages and intelligent connected vehicle driving trajectory data from the cloud control platform, compares the consistency between the connected vehicle's driving trajectory at the signalized intersection and the SPAT message's permission to allow passage, and automatically monitors for any mismatch in the mapping relationship.
[0028] In this embodiment, the RSM message originates from the perception results of the roadside sensing system. Its data quality is affected by the installation condition of the sensing equipment, such as pole deformation or foliage obstruction, which degrades the accuracy of the data results. The authentication system accesses the RSM message and the driving trajectory data of the intelligent connected vehicle from the cloud control platform. It selects connected vehicles as data probes from the perception results, compares position and speed deviations, and dynamically monitors the accuracy of the perception results. In this embodiment, the accuracy indicators of the fused perception target data include position deviation, speed deviation, and heading angle deviation.
[0029] The system aggregates real-time kinematic information collected by connected vehicles when they pass through intersections, including GPS position, speed, and heading angle. The collected data is then converted, matched, and calculated to obtain position deviation, speed deviation, and heading angle deviation. Based on preset thresholds, the system determines whether the device's perception capability is abnormal and updates the electronic tag status.
[0030] Specifically, RSM message detection includes perception detection latency, perception accuracy detection, and perception precision detection. Perception accuracy detection combines offline and online methods, employing the IOU (Intersection over Union) area matching algorithm to match the perceived target of the connected vehicle from the RSM (Road Side Message), ensuring a one-to-one correspondence between the acquired data and the target object. The deviation values of position, speed, and heading angle between the GPS-collected data and the RSM message are calculated; when the deviation consistently exceeds a threshold, an abnormal state is identified and the electronic tag status is updated.
[0031] The position deviation is calculated as follows: GPS coordinates are uniformly converted to UTM (Universal Transverse Mercator) coordinates for calculation in a planar coordinate system. The distance deviation between the actual position and the perceived position is calculated to eliminate the influence of direction. The average position deviation of all samples is calculated as the evaluation index of position error, expressed as... ; In the formula, To sense location; This refers to the actual location.
[0032] The speed deviation is calculated as follows: The speed of the connected vehicle is matched with the speed in the corresponding RSM message; the absolute value of the speed deviation is calculated; and the average speed deviation of all samples is calculated as the evaluation index of the speed error, expressed as: ; In the formula, To perceive speed; This refers to the actual speed.
[0033] The heading angle deviation is calculated as follows: The heading angle of the connected vehicle is matched with the heading angle in the corresponding RSM message; the absolute value of the heading angle deviation is calculated; and the average value of the heading angle deviations for all samples is calculated as the evaluation index for the heading angle deviation, expressed as: ; In the formula, To sense the heading angle; This is the actual heading angle.
[0034] Based on preset standard thresholds, it is determined whether the position error, speed error, and heading angle deviation consistently exceed the threshold. If the error consistently exceeds the standard threshold, the device's sensing capability is considered to be in an abnormal state, and the electronic tag is marked as abnormal accordingly. In this embodiment, the standard threshold is designed to be 5 degrees.
[0035] In this embodiment, the electronic tag generation module generates an electronic tag containing a unique code based on the verification results of the cloud service authentication module and the roadside service authentication module. The electronic tag is used to identify the data service quality level and supports online query by end users.
[0036] In this embodiment, the electronic tag generation module includes a hierarchical authentication indicator unit and an encoding generation unit.
[0037] The tiered certification indicator unit is used to construct a multi-element data quality certification system, which includes perception data quality levels SQ1 and SQ2. SQ1 is used to provide real-time road information to drivers, while SQ2 is used to provide real-time road information to autonomous driving systems.
[0038] In this embodiment, the data quality requirements of vehicle-road-cloud integrated systems for different intelligent connected vehicles and intelligent connected scenarios are investigated. Based on the investigation, a data quality certification system map including multiple elements such as attributes, types, and functions is constructed. A method for constructing the data quality requirement space is designed based on the map. By calculating and analyzing the deviation relationship between data instances and the requirement space, a rule-based data quality grading and evaluation scale for vehicle-road-cloud integrated systems is established.
[0039] To address the needs of constructing an integrated vehicle-road-cloud data quality certification system, this paper standardizes scene elements through continuous scene element normalization and discrete scene element one-hot normalization methods. It reduces spatial dimensionality through correlation analysis and principal component analysis, selects key scene elements, and constructs a road scene data domain. Sample sets are aggregated based on different levels of intelligent connected vehicles or vehicle-side application functions. The paper quantifies the demand of samples for each scene element, calculates the demand space and demand center point, and performs annealing on sampling points within the localized edge of the demand space to reduce the disturbance of critical region sampling points on the scoring results.
[0040] In this embodiment, the authentication rating is divided into perceived data quality levels SQ1 and SQ2 based on the service recipient.
[0041] Among them, the perception data quality level SQ1 is: the perception data quality meets the requirements of driver assistance applications for perception data quality, and the perception data can be used to provide drivers with real-time road information to assist drivers in making on-site decisions.
[0042] The perception data quality level SQ2 is: the perception data quality meets the requirements of autonomous driving applications, and the perception data can be used to provide valuable real-time road information to the autonomous driving system to support the autonomous driving system in making decisions.
[0043] The encoding generation unit generates unique codes based on the cloud service combination and the roadside device message type. In this embodiment, the authentication system provides a unique data quality authentication identifier for each cloud control service. Specifically, for cloud service authentication, the encoding generation unit combines the service resource request address, communication method, URL address, or message name to form a unique code, which serves as the electronic authentication label for the service. For roadside service authentication, the encoding generation unit combines the device code and message type to form a unique code, which serves as the electronic authentication label for the service.
[0044] In this embodiment, online query services for intelligent connected vehicles are also supported, providing certification and evaluation results, as well as detailed information. After obtaining the rating results, the intelligent connected vehicle responds based on its actual condition.
[0045] In this embodiment, cloud service authentication and roadside service authentication modules cover the quality authentication of cloud and roadside data services. The authentication content includes data security, message protocols, and data quality. Simultaneously, various data service electronic tags are designed to enable online verification, ensuring that quality inspection results reach end-users and improving the trust of intelligent connected vehicles in cloud control services. The online authentication system consists of cloud services and roadside message services. Cloud services are obtained through 4G / 5G networks, while roadside message services are obtained through LTE-V2X networks, i.e., V2X messages broadcast by roadside communication units (RSUs). By integrating online automatic verification and offline authentication mechanisms, the timeliness and reliability of authentication results are effectively guaranteed. This system comprehensively covers the quality authentication of cloud and roadside data services, including multiple dimensions such as data security, message protocols, and data quality. It also innovatively designs various data service electronic tags to achieve online verification, ensuring that quality results reach end-users, thereby significantly improving the trust of intelligent connected vehicles in cloud control services.
[0046] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific technical solutions and / or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.
Claims
1. A cloud-based control service and roadside equipment data quality online authentication system, characterized in that: This includes a cloud service authentication module, a roadside service authentication module, and an electronic tag generation module; The cloud service authentication module communicates with a third-party cloud control platform via a 4G / 5G network to perform online stability verification and data content verification of cloud data services. The roadside service authentication module communicates with roadside devices through the LTE-V2X network and performs static and dynamic information verification on roadside V2X messages by combining offline and online verification methods. The electronic tag generation module generates an electronic tag containing a unique code based on the verification results of the cloud service authentication module and the roadside service authentication module. The electronic tag is used to identify the data service quality level and supports online query by end users.
2. The cloud control service and roadside equipment data quality online authentication system according to claim 1, characterized in that: The cloud service authentication module includes a service stability verification unit and a data content verification unit; The service stability verification unit is used to monitor the cloud service status in real time and to count the service online rate and the average request response latency. The data content verification unit is used to verify the legality and logical consistency of data through preset rules, which include data legality rules and self-consistency logic checking algorithms.
3. The cloud control service and roadside equipment data quality online authentication system according to claim 1, characterized in that: The roadside service authentication module includes a static information verification unit and a dynamic information verification unit; the static information verification unit includes offline static verification and offline sampling semi-static verification; the static verification is used to verify the accuracy of MAP map data and the consistency of RSI traffic sign information; the semi-static verification is used to verify the accuracy of traffic events in RSI; the dynamic information verification unit is used to detect the data quality of SPAT messages and RSM messages by combining offline and online methods.
4. The cloud control service and roadside equipment data quality online authentication system according to claim 1, characterized in that: The electronic tag generation module includes a hierarchical authentication index unit and a coding generation unit; the hierarchical authentication index unit is used to construct a multi-element data quality authentication system, which includes perceived data quality levels SQ1 and SQ2; SQ1 is used to provide real-time road information to drivers, and SQ2 is used to provide real-time road information to autonomous driving systems; the coding generation unit is used to generate unique codes based on cloud service combinations and roadside device message types.
5. The cloud control service and roadside equipment data quality online authentication system according to claim 3, characterized in that: The SPAT message detection includes message performance indicator verification, light status delay verification, and traffic light data driving direction control consistency verification. The light status delay verification involves comparing the delay between the light status switching time broadcast by the roadside equipment and the actual traffic signal light status switching time offline, calculating the light status switching delay time, and triggering an early warning mechanism when the delay exceeds 100ms.
6. The cloud control service and roadside equipment data quality online authentication system according to claim 3, characterized in that: The consistency verification of traffic light data driving direction control is carried out by combining offline and online methods. Electronic fences are established at each intersection to analyze the way vehicles pass through the intersection and match the corresponding traffic light phases that control the driving direction. The proportion of red light violations and the phase configuration are analyzed. When an anomaly is detected, an electronic tag is triggered for identification.
7. The cloud control service and roadside equipment data quality online authentication system according to claim 3, characterized in that: The RSM message detection includes perception detection delay, perception accuracy detection, and perception precision detection. The perception accuracy detection combines offline and online methods and uses the IOU area matching algorithm to calculate the deviation values of position, speed, and heading angle in the GPS data and RSM messages. When the deviation is consistently higher than the threshold, an abnormal state is identified and the electronic tag status is updated.
8. The cloud control service and roadside equipment data quality online authentication system according to claim 7, characterized in that, The position deviation is calculated as follows: GPS coordinates are uniformly converted to UTM coordinates, the difference between the actual position and the perceived position is calculated, and the average position deviation of all samples is calculated as the evaluation index of position error, expressed as follows: ； In the formula, To sense location; This refers to the actual location.
9. The cloud control service and roadside equipment data quality online authentication system according to claim 7, characterized in that, The speed deviation is calculated as follows: The speed of the connected vehicle is matched with the speed in the corresponding RSM message; the absolute value of the speed deviation is calculated; and the average speed deviation of all samples is calculated as the evaluation index of the speed error, expressed as: ； In the formula, To perceive speed; This refers to the actual speed.
10. The cloud control service and roadside equipment data quality online authentication system according to claim 7, characterized in that, The heading angle deviation is calculated as follows: The heading angle of the connected vehicle is matched with the heading angle in the corresponding RSM message; the absolute value of the heading angle deviation is calculated; and the average value of the heading angle deviations for all samples is calculated as the evaluation index of the heading angle deviation, expressed as: ； In the formula, To sense the heading angle; This is the actual heading angle.