A method and system for real-time remediation and credit-based passage for failed ETC transactions based on road-vehicle cooperation.

Abstract

This invention provides a method and system for real-time remediation and credit-based passage of ETC transactions based on road-vehicle cooperation, relating to the field of intelligent transportation technology. The system includes the following steps: S1, real-time diagnosis of transaction failure; S2, multimodal identity collaborative verification; S3, dynamic remediation strategy generation; S4, augmented reality interactive guidance; S5, seamless payment execution; S6, credit-based passage decision-making and execution; S7, intelligent post-event recovery processing. The system includes: an edge perception layer; an edge computing layer; a cloud service layer; a roadside interaction layer; and an in-vehicle interaction layer. When a transaction fails, the intelligent roadside unit collects multi-faceted data in real time and combines it with historical records to intelligently diagnose the cause, changing the previous inefficient mode that was difficult to accurately locate and required manual intervention, shortening vehicle dwell time, improving lane traffic efficiency, and reducing labor costs.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to a method and system for real-time remediation of failed ETC transactions and credit-based passage based on road-vehicle cooperation. Background Technology

[0002] While electronic toll collection systems (ETCs) have been widely adopted and improved traffic efficiency in highway toll collection scenarios, some key technical issues still exist in their actual operation: Inefficient and rigid transaction failure handling: When a transaction fails, the existing ETC system struggles to pinpoint the cause in real time, such as communication interference, equipment malfunction, account anomalies, or incorrect vehicle information identification. This often necessitates manual intervention, prolonging vehicle dwell time, reducing lane efficiency, and increasing labor costs. Furthermore, remedial strategies lack flexibility, often relying on fixed patterns that fail to consider factors such as the cause of failure, user credit, and lane efficiency, making dynamic adjustments impossible and impacting remedial effectiveness and user experience.

[0003] Inadequate security and accuracy of identity verification: In the identity verification process after a transaction fails, existing systems mostly rely on a single method, such as license plate recognition or simple card verification. This method is susceptible to forgery, obscuring, and other factors, posing a risk of identity theft. It is difficult to ensure the authenticity and accuracy of vehicle and user identities, threatening transaction security and affecting subsequent processing procedures.

[0004] There are shortcomings in data security and credit management: transaction data is stored on a central server, which is at risk of data loss or tampering due to attacks or malfunctions; and when verifying the validity of payments, some transaction information often needs to be disclosed, making it impossible to balance user privacy and data authenticity; in addition, credit access decisions lack scientific basis, referencing only simple historical records without comprehensively considering real-time credit scores, the results of the current transaction, and other multi-dimensional information, making it difficult to provide accurate and differentiated access services. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies. This invention proposes a method and system for real-time remediation of failed ETC transactions and credit-based passage based on road-vehicle cooperation. Through innovative technical means, it effectively solves problems, improves system performance and user experience, and provides a better solution for highway toll management.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A method for real-time remediation and credit-based passage of ETC transactions based on road-vehicle cooperation includes the following steps: S1, real-time diagnosis of transaction failure: when a vehicle passes through a toll station, if the ETC transaction with the roadside unit fails, the intelligent roadside unit collects vehicle status, communication signals and environmental data in real time, and combines them with historical transaction records to intelligently diagnose the cause of the transaction failure. S2. Multimodal Identity Collaborative Verification: Based on the diagnostic results, activate an identity verification mechanism that includes at least two of the following methods: biometric recognition, accurate license plate recognition, and mobile terminal association verification, to cross-verify the identities of vehicles and users. S3. Dynamic remedial strategy generation: Based on the failure reason and the verified identity information, the dynamic risk assessment model is called to calculate the risk level, and an execution strategy containing multiple payment remedial methods is dynamically generated according to the preset weight parameters (α, β, γ). The weighting parameters are at least related to payment success rate, lane traffic efficiency, and transaction security level; S4. Augmented Reality Interactive Guidance: Through augmented reality display devices deployed on the roadside or vehicle-mounted terminals, the operation instructions of the remedial strategy are visually displayed to the driver in the form of augmented reality or holographic projection. S5. Seamless Payment Execution: Guide the driver or vehicle unit to complete the real-time payment of transaction fees through at least one seamless payment method; S6. Credit-based passage decision and execution: Based on the user's credit score and the results of this remedial action, dynamically decide whether to allow credit-based passage and match the corresponding level of passage lane to the vehicles that are allowed to pass. S7. Intelligent Post-Event Recovery Processing: For vehicles that fail to complete the payment on the spot, an intelligent recovery process will be initiated based on their identity information and credit records.

[0007] Furthermore, the intelligent roadside unit integrates an AI vision processing chip and supports redundant communication with vehicles and edge computing nodes through at least two of the following communication links: 5G, LTE-V2X, and Wi-Fi 6.

[0008] Furthermore, the method also includes a trusted transaction data storage step: deploying lightweight blockchain nodes at the edge computing layer and uploading key transaction information summaries to the blockchain for storage; for transactions that have been paid, using zero-knowledge proof technology to verify the validity of the payment to the roadside unit without disclosing the specific transaction amount.

[0009] Furthermore, the risk factors of the dynamic risk assessment model described in S3 include at least the vehicle's real-time driving speed, the user's historical fare evasion records, the current payment account activity level, and the environmental credibility score.

[0010] The credit access decision described in S6 specifically includes: Obtain real-time dynamic credit scores for vehicles or associated users; Based on the preset threshold range of the credit score, it is determined whether credit passage is allowed, and lanes with corresponding passage priorities are allocated to vehicles that are allowed to pass. Furthermore, the channel levels include at least an inspection-free channel, a rapid sampling channel, and a manual verification channel.

[0011] This invention also proposes a real-time remediation and credit-based passage system for ETC transaction failures based on road-vehicle cooperation to implement the above method. The system includes: The edge perception layer includes intelligent roadside units, high-precision license plate recognition units, and environmental perception modules installed at toll stations. These are used to collect vehicle characteristics and environmental data in real time and to perform preliminary diagnosis of transaction failures and collect identity information. The edge computing layer includes edge computing nodes deployed at the station. The nodes are equipped with a transaction failure intelligent diagnosis module, a dynamic risk assessment engine, and a blockchain evidence storage client, which are used to perform root cause analysis of failures, generate remedial strategies, and complete trusted evidence storage of transaction data. The cloud service layer includes the ETC credit big data platform and the intelligent collection and management platform, which are used to store and update user credit data, analyze payment behavior, and coordinate cross-regional collection and management tasks. The roadside interaction layer includes augmented reality prompting devices and voice interaction units, which are used to provide drivers with dynamic and visual operation guidance; The in-vehicle interaction layer, integrated into the vehicle's in-vehicle unit or user's mobile terminal, is used to receive instructions, verify identity, and perform contactless payment operations.

[0012] Furthermore, the augmented reality prompting device is a holographic projection device or AR glasses, and its displayed content can be adaptively adjusted according to the vehicle type, driver's posture, and ambient lighting conditions.

[0013] Furthermore, the in-vehicle interaction layer supports seamless payment through at least one of the following methods: in-vehicle mini-program, digital RMB hard wallet, or encrypted acoustic wave communication.

[0014] Furthermore, the intelligent debt collection management platform integrates an AI debt collection robot and an automatic legal document generation module; The AI ​​debt collection robot supports multilingual intelligent interaction, and the automatic legal document generation module integrates OCR recognition, natural language processing, and electronic signature services.

[0015] This invention proposes a method and system for real-time remediation of failed ETC transactions and credit-based passage based on road-vehicle cooperation, which has the following advantages compared with existing technologies: Efficient and flexible handling of transaction failures: When a transaction fails, the intelligent roadside unit collects multi-faceted data in real time and combines it with historical records to intelligently diagnose the cause. This changes the inefficient mode that was difficult to pinpoint and required manual intervention, shortens vehicle dwell time, improves lane traffic efficiency, and reduces labor costs. At the same time, based on the cause of failure and verified identity information, a dynamic risk assessment model is invoked. According to the weight parameters associated with payment success rate, lane traffic efficiency, and transaction security level, an execution strategy that includes multiple payment remediation methods is dynamically generated. The remediation strategy is more flexible, improving the remediation effect and user experience.

[0016] Secure and accurate identity verification: Based on the diagnostic results, an identity verification mechanism with at least two methods is activated for cross-verification. This changes the previous reliance on a single verification method, which is susceptible to forgery and obscuration, and poses a risk of identity theft. It ensures the authenticity and accuracy of vehicle and user identities, protects transaction security, and guarantees the smooth progress of subsequent processing.

[0017] Data security while ensuring privacy and authenticity: Lightweight blockchain nodes are deployed at the edge computing layer to upload key transaction information summaries to the blockchain for evidence storage, avoiding the risk of data loss or tampering; zero-knowledge proof technology is used to verify the validity of payments without disclosing the specific transaction amount, thus ensuring both user privacy and data authenticity.

[0018] Credit-based access decision-making: Based on the user's credit score and the results of the current remedial action, the system dynamically decides whether to grant credit access and matches the corresponding access level. This changes the previous decision-making method that only referred to simple historical records. It integrates multi-dimensional information to provide accurate and differentiated access services.

[0019] Reliable intelligent post-event recovery: For vehicles that fail to complete the payment on the spot, an intelligent recovery process is initiated based on their identity information and credit file. The intelligent recovery management platform integrates an AI collection robot and an automatic legal document generation module. The AI ​​collection robot supports multilingual intelligent interaction, and the automatic legal document generation module integrates multiple services to ensure the effective implementation of recovery work. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a method for real-time remediation and credit-based passage for ETC transactions based on road-vehicle cooperation, according to the present invention.

[0021] Figure 2 This is a system block diagram of an ETC transaction failure real-time recovery and credit passage system based on road-vehicle cooperation according to the present invention. Detailed Implementation

[0022] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0023] This invention proposes a method for real-time remediation of failed ETC transactions and credit-based passage based on road-vehicle cooperation, such as... Figure 1 As shown, the steps are as follows: S1 Real-time Diagnosis of Transaction Failure: When the intelligent roadside unit collects vehicle status, communication signals, and environmental data in real time, the vehicle status data not only covers the vehicle's basic physical parameters, such as vehicle height, width, and number of axles, but also includes the vehicle's driving status information, such as vehicle acceleration and steering angle; the communication signal data records in detail the signal strength, signal interference, and signal transmission delay between the vehicle and the roadside unit; the environmental data includes not only conventional weather conditions (such as sunny, rainy, and foggy days) and light intensity, but also traffic flow around the toll station, such as the queue length of vehicles in adjacent lanes and vehicle speed.

[0024] When performing intelligent diagnostics based on historical transaction records, the system will conduct in-depth analysis of the distribution of failure reasons in similar scenarios in historical transactions. For example, if past transaction failures were mostly related to unstable communication signals under specific weather conditions, then communication signal problems will be given higher diagnostic weight under the same current weather conditions. At the same time, the system will also consider factors such as the vehicle's historical transaction frequency and transaction amount range to comprehensively judge the possible reasons for the current transaction failure, such as whether it was caused by insufficient account balance, card malfunction, or temporary system failure.

[0025] S2 Multimodal Identity Collaborative Verification: Biometric recognition methods include, but are not limited to, facial recognition, fingerprint recognition, and iris recognition; advanced liveness detection technology is used during biometric recognition to prevent identity impersonation using photos, models, or other forgery methods; accurate license plate recognition uses high-precision image recognition algorithms, combined with license plate images captured by multi-angle cameras, to ensure accurate identification of license plate numbers under various lighting conditions and shooting angles; mobile terminal association verification uses mobile devices such as smartphones associated with the vehicle for identity verification, such as connecting the phone to the roadside unit via Bluetooth to verify the phone's unique identification information and related information about the phone being bound to the vehicle.

[0026] When performing cross-validation, different weights are assigned to each validation method. For example, biometric recognition may have a relatively high weight because it has high accuracy and uniqueness; license plate recognition has a lower weight; and the weight of mobile terminal association verification is dynamically adjusted according to the specific situation. Only when the combined verification results of multiple validation methods reach the preset threshold is the vehicle and user identity verification considered successful.

[0027] S3 Dynamic Remedial Strategy Generation: When calculating risk levels, the dynamic risk assessment model considers not only risk factors such as vehicle real-time speed, user's historical toll evasion records, current payment account activity, and environmental credibility score, but also vehicle trajectory information. For example, if a vehicle frequently appears in areas with high toll evasion rates, its risk level will increase accordingly. Simultaneously, different weight parameters (α, β, γ) are set according to different risk levels; for example, for high-risk levels, the weight α for payment success rate will be appropriately reduced, while the weight γ for transaction security level will be increased to ensure that transaction security is prioritized in high-risk situations.

[0028] The generated execution strategy includes various payment remedies, including common bank card payments and third-party payment platform payments, as well as emerging payment methods such as blockchain-based digital currency payments. Furthermore, it prioritizes each payment method based on its risk level and characteristics; for example, for low-risk levels, convenient third-party payment platforms are prioritized, while for high-risk levels, more secure bank card payments or blockchain-based digital currency payments are prioritized.

[0029] S4 Augmented Reality Interactive Guidance: When augmented reality or holographic projection is performed through roadside augmented reality display devices or vehicle-mounted terminals, the displayed content will be customized according to different remedial strategies and vehicle conditions. For example, for remedial strategies that require bank card payments, the displayed content will show in detail the location of the bank card insertion, the payment operation process, and the prompt information after successful payment. At the same time, the displayed content will also include auxiliary information such as dynamic arrow indicators and voice prompts to help drivers complete the operation more accurately.

[0030] During the demonstration, the displayed content will be adjusted in real time according to the driver's line of sight and operation progress; for example, when the driver looks at a certain operation area, the displayed content in that area will be enlarged; when the driver completes a certain operation step, the displayed content will automatically jump to the prompt information for the next step.

[0031] S5 Seamless Payment Execution: When guiding drivers or in-vehicle units to complete real-time payment of transaction fees through seamless payment methods, corresponding operation guidance and safety prompts will be provided for different seamless payment methods. For example, for in-vehicle mini-program payment, the driver will be prompted to open the corresponding in-vehicle mini-program and operate according to the prompts on the mini-program; for digital RMB hard wallet payment, the driver will be prompted to bring the hard wallet close to the designated payment device for payment; for encrypted sound wave communication payment, the driver will be prompted to ensure that the vehicle's audio equipment is working properly and complete the payment operation according to the voice prompts.

[0032] Meanwhile, the payment status will be monitored in real time during the payment process. If any abnormalities occur, such as payment timeout or payment failure, the driver will be notified in a timely manner and a corresponding solution will be provided, such as re-payment or changing the payment method.

[0033] S6 Credit-Based Access Decision-Making and Execution: When obtaining real-time dynamic credit scores for vehicles or associated users, the credit score comprehensively considers multiple dimensions of factors, including but not limited to the user's historical transaction records, toll evasion records, complaint records, and credit consumption records. Simultaneously, the credit score is dynamically adjusted according to different time periods and traffic scenarios. For example, during peak traffic hours, vehicles with higher credit scores are given higher passage priority; during special events, the credit score standards are temporarily adjusted according to the relevant requirements of the event.

[0034] When determining whether to allow passage based on a preset threshold range for a credit score, multiple threshold ranges are set, each corresponding to a different passage strategy. For example, vehicles with a credit score of 90 or above are allowed to pass through the inspection-free lane without any inspection; vehicles with a credit score between 70 and 90 are allowed to pass through the fast-track inspection lane for simple random checks; and vehicles with a credit score below 70 need to go through the manual review lane for detailed inspection and verification.

[0035] S7 Intelligent Post-Payment Recovery Processing: For vehicles that fail to complete payment on the spot, when the intelligent recovery process is initiated based on their identity information and credit file, the intelligent recovery process will be tiered according to factors such as the amount owed, the duration of the overdue payment, and the credit score. For example, for vehicles with small overdue amounts and high credit scores, gentle reminders will be sent via SMS and email first; for vehicles with large overdue amounts and low credit scores, an AI collection robot will be activated to conduct multilingual intelligent interactive collection and generate legal documents for formal recovery.

[0036] During the collection process, the vehicle's outstanding fees and credit file will be updated in real time, and the collection results will be fed back to the ETC credit big data platform so that the user's credit score can be dynamically adjusted. At the same time, information will be shared with traffic management departments and financial institutions in other regions to achieve coordination and processing of cross-regional collection tasks.

[0037] The method also includes: a trusted notarization process for transaction data. When deploying lightweight blockchain nodes at the edge computing layer, blockchain technologies suitable for the edge computing environment are selected to ensure the efficient operation of the blockchain nodes and the security of the data. When uploading key transaction information summaries to the blockchain for notarization, the key transaction information is encrypted to ensure the confidentiality and integrity of the information. At the same time, a unique identifier is generated for each transaction so that it can be queried and verified on the blockchain.

[0038] For transactions that have been paid, when using zero-knowledge proof technology to verify the validity of the payment to the roadside unit, the zero-knowledge proof algorithm will ensure that the payment has been successfully completed without revealing the specific transaction amount. For example, by designing specific mathematical proofs, the roadside unit can verify that the payer does have sufficient funds to complete the payment and that the payment has been effectively confirmed, even without knowing the transaction amount.

[0039] This invention also proposes a real-time remediation and credit-based passage system for ETC transaction failures based on road-vehicle cooperation to implement the above method, such as... Figure 2 As shown, it includes: 1) Edge Perception Layer: In addition to integrating an AI vision processing chip and supporting redundant communication with vehicles and edge computing nodes via at least two of the following communication links: 5G, LTE-V2X, and Wi-Fi 6, the intelligent roadside unit is also equipped with a high-precision positioning module, such as a Beidou positioning module, to accurately obtain vehicle location information; the high-precision license plate recognition unit adopts multispectral imaging technology, which can accurately identify license plate color and characters under various lighting conditions, and also has a license plate anti-counterfeiting function, which can effectively identify counterfeit license plates; in addition to collecting conventional environmental data, the environmental perception module is also equipped with air quality sensors, noise sensors, etc., to gain a more comprehensive understanding of the environmental conditions around the toll station.

[0040] 2) Edge Computing Layer: During analysis, the intelligent diagnostic module for transaction failures uses machine learning algorithms to train and model large amounts of historical transaction data and real-time collected data to improve the accuracy and efficiency of diagnosis; the dynamic risk assessment engine calculates the risk level of vehicles in real time based on different risk factors and weight parameters, and provides a basis for generating remedial strategies; the blockchain evidence storage client works in collaboration with other modules on the edge computing node to ensure that key transaction information can be uploaded to the blockchain for evidence storage in a timely and accurate manner; at the same time, the blockchain evidence storage client also has data backup and recovery functions to prevent data loss.

[0041] 3) Cloud Service Layer: The ETC Credit Big Data Platform will use big data analytics to deeply mine and analyze user credit data, providing support for the calculation and dynamic adjustment of user credit scores. Simultaneously, the ETC Credit Big Data Platform will share and interact with other relevant platforms, such as credit platforms of financial institutions and violation information platforms of traffic management departments, to obtain more comprehensive user credit information. The intelligent collection management platform, in addition to integrating AI collection robots and automatic legal document generation modules, will also be equipped with an intelligent dispatch system to rationally allocate collection resources based on the location of the overdue vehicle and the priority of collection tasks, thereby improving collection efficiency.

[0042] 4) Roadside Interaction Layer: When the augmented reality prompting device is a holographic projection device or AR glasses, the holographic projection device will use advanced laser projection technology to project clear and realistic 3D images into the air; the AR glasses will have a high-resolution display and accurate positioning tracking function, and can adjust the displayed content in real time according to the driver's head movement; the voice interaction unit will use natural language processing technology to understand the driver's natural language commands and provide accurate voice feedback; at the same time, the voice interaction unit will support multiple languages ​​to meet the needs of drivers in different regions.

[0043] 5) In-vehicle Interaction Layer: When the in-vehicle interaction layer is integrated into the vehicle's onboard unit or user mobile terminal, the onboard unit will have powerful computing and communication capabilities, enabling real-time communication with roadside units and the cloud service layer; the user mobile terminal will connect to the system through a dedicated application to achieve identity verification and contactless payment; the in-vehicle mini-program will provide a simple and convenient interface for drivers to perform payment operations; the digital RMB hard wallet will have secure and reliable storage and payment functions to ensure the safety of users' funds; and encrypted acoustic communication will use advanced encryption algorithms to ensure the security of the communication process.

[0044] 6) Intelligent Collection Management Platform: When the AI ​​collection robot supports multilingual intelligent interaction, it will have speech recognition, speech synthesis, and natural language understanding capabilities, and can automatically switch to the appropriate language for communication based on the driver's language type; when the automatic legal document generation module integrates OCR recognition, natural language processing, and electronic signature services, OCR recognition technology can accurately recognize text information in various documents; natural language processing technology can organize and analyze the recognized text information to generate document content that complies with legal norms; electronic signature services can ensure the authenticity and validity of legal documents and facilitate remote signing by users.

[0045] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0046] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for real-time remediation and credit-based passage for failed ETC transactions based on road-vehicle cooperation, characterized in that, Includes the following steps: S1. Real-time diagnosis of transaction failure: When a vehicle passes through a toll station, if the ETC transaction with the roadside unit fails, the intelligent roadside unit will collect the vehicle status, communication signals and environmental data in real time, and combine them with historical transaction records to intelligently diagnose the reason for the transaction failure. S2. Multimodal Identity Collaborative Verification: Based on the diagnostic results, activate an identity verification mechanism that includes at least two of the following methods: biometric recognition, accurate license plate recognition, and mobile terminal association verification, to cross-verify the identities of vehicles and users. S3. Dynamic remedial strategy generation: Based on the failure reason and the verified identity information, the dynamic risk assessment model is called to calculate the risk level, and an execution strategy containing multiple payment remedial methods is dynamically generated according to the preset weight parameters (α, β, γ). The weighting parameters are at least related to payment success rate, lane traffic efficiency, and transaction security level; S4. Augmented Reality Interactive Guidance: Through augmented reality display devices deployed on the roadside or vehicle-mounted terminals, the operation instructions of the remedial strategy are visually displayed to the driver in the form of augmented reality or holographic projection. S5. Seamless Payment Execution: Guide the driver or vehicle unit to complete the real-time payment of transaction fees through at least one seamless payment method; S6. Credit-based passage decision and execution: Based on the user's credit score and the results of this remedial action, dynamically decide whether to allow credit-based passage and match the corresponding level of passage lane to the vehicles that are allowed to pass. S7. Intelligent Post-Event Recovery Processing: For vehicles that fail to complete the payment on the spot, an intelligent recovery process will be initiated based on their identity information and credit records.

2. The method according to claim 1, characterized in that, The intelligent roadside unit integrates an AI vision processing chip and supports redundant communication with vehicles and edge computing nodes through at least two of the following communication links: 5G, LTE-V2X, and Wi-Fi 6.

3. The method according to claim 1 or 2, characterized in that, The method also includes a trusted transaction data storage step: deploying lightweight blockchain nodes at the edge computing layer and uploading key transaction information summaries to the blockchain for storage; for transactions that have been paid, using zero-knowledge proof technology to verify the validity of the payment to the roadside unit without disclosing the specific transaction amount.

4. The method according to claim 1, characterized in that, The risk factors in the dynamic risk assessment model described in S3 include at least the vehicle's real-time speed, the user's historical fare evasion records, the current activity level of the payment account, and the environmental credibility score.

5. The method according to claim 1, characterized in that, The credit access decision described in S6 specifically includes: Obtain real-time dynamic credit scores for vehicles or associated users; Based on the preset threshold range of the credit score, it is determined whether credit passage is allowed, and lanes with corresponding passage priorities are allocated to vehicles that are allowed to pass. The channel levels include at least the inspection-free channel, the fast sampling channel, and the manual review channel.

6. A real-time remediation and credit-based passage system for ETC transaction failure based on road-vehicle cooperation for implementing the method of any one of claims 1-5, characterized in that, include: The edge perception layer includes intelligent roadside units, high-precision license plate recognition units, and environmental perception modules installed at toll stations. These are used to collect vehicle characteristics and environmental data in real time and to perform preliminary diagnosis of transaction failures and collect identity information. The edge computing layer includes edge computing nodes deployed at the station. The nodes are equipped with a transaction failure intelligent diagnosis module, a dynamic risk assessment engine, and a blockchain evidence storage client, which are used to perform root cause analysis of failures, generate remedial strategies, and complete trusted evidence storage of transaction data. The cloud service layer includes the ETC credit big data platform and the intelligent collection and management platform, which are used to store and update user credit data, analyze payment behavior, and coordinate cross-regional collection and management tasks. The roadside interaction layer includes augmented reality prompting devices and voice interaction units, which are used to provide drivers with dynamic and visual operation guidance; The in-vehicle interaction layer, integrated into the vehicle's in-vehicle unit or user's mobile terminal, is used to receive instructions, verify identity, and perform contactless payment operations.

7. The system according to claim 6, characterized in that, The augmented reality prompting device is a holographic projection device or AR glasses, and its displayed content can be adaptively adjusted according to vehicle type, driver's posture and ambient lighting conditions.

8. The system according to claim 6, characterized in that, The in-vehicle interaction layer supports seamless payment through at least one of the following methods: in-vehicle mini-program, digital RMB hard wallet, or encrypted acoustic wave communication.

9. The system according to claim 6, characterized in that, The intelligent debt collection management platform integrates an AI debt collection robot and an automatic legal document generation module. The AI ​​debt collection robot supports multilingual intelligent interaction, and the automatic legal document generation module integrates OCR recognition, natural language processing, and electronic signature services.

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