A vehicle platoon energy-saving credit incentive system and method based on vehicle-road cooperation

Abstract

The application discloses a kind of vehicle platoon energy-saving credit incentive system and method based on vehicle-road cooperation, it is related to transaction reward technical field, in system, electronic toll gate gathers platoon identification, member vehicle unit identification and time stamp, speed information, trajectory sequence reconstruction unit is associated with multiple gantry data according to platoon identification and reconstructs platoon space-time trajectory sequence;Energy-saving credit evaluation unit compares trajectory sequence with road section reference energy consumption data, outputs emission reduction and energy-saving credit and generates credit voucher containing pre-link identification;Trustworthy credit account book stores evidence and records check information;When export transaction triggers, green credit cancellation unit is according to vehicle unit identification and entry time query and checks voucher, generates toll discount according to emission reduction-discount mapping and is incorporated into settlement with negative transaction record.It is realized that platoon energy-saving degree is measured and settlement linkage by the technical scheme of the application, forms trustworthy evidence, real-time cancellation closed loop, and improves incentive landing efficiency.

Description

Technical Field

[0001] This invention relates to the field of transaction reward technology, and in particular to a vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation and a vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation. Background Technology

[0002] With the widespread adoption of vehicle-to-infrastructure (V2I) communication and onboard units, platooning on highways is increasingly being used to improve traffic efficiency and reduce energy consumption and emissions. Placing vehicles in platoons, operating under relatively stable spacing and speed conditions, possesses significant potential for energy conservation and emission reduction. To promote the normalization of platooning operations, the industry has proposed converting energy conservation and emission reductions into credit benefits and providing incentives for toll settlement.

[0003] In existing technologies, electronic toll collection gantries and electronic toll collection settlement systems have the capabilities to collect vehicle identification information, record speed and timestamps, generate and settle transaction logs, etc. However, there is still a lack of a complete technical link for the generation and verification of "platoon energy-saving credits," mainly due to the following problems: First, the formation-related data is collected in a scattered manner at different gantries, and there is a lack of a mechanism for cross-gantry association based on formation identifiers. This makes it difficult to restore the discrete collection points into a continuous spatiotemporal trajectory sequence of formation, resulting in formation behavior being difficult to accurately characterize at the road segment scale.

[0004] Secondly, the quantitative assessment of energy-saving effects lacks a comparative calculation link with the benchmark energy consumption data of the same road section, making it difficult to form a unified standard for emission reduction and credit results that can be used for incentive settlement, thus resulting in unclear incentive basis and difficulty in large-scale implementation.

[0005] Third, energy-saving credit results are mostly stored in a centralized recording manner, lacking integrity verification information corresponding to the vouchers, which poses a risk of data tampering and difficulty in subsequent auditing and traceability.

[0006] Fourth, there is a lack of stable binding between energy-saving credits and export electronic fee transactions. Credits and transactions are separated between systems, which can easily lead to problems such as unclear ownership, duplicate verification, or illegal application, making it difficult to support real-time verification and settlement when export transactions are triggered.

[0007] Fifth, the existing settlement chain focuses on toll calculation and deduction, lacking a mechanism to convert emission reductions into incentives according to mapping rules and incorporate them into the settlement as negative transaction records, resulting in high incentive implementation costs and complex implementation. Summary of the Invention

[0008] To address the aforementioned issues, this invention provides a vehicle platooning energy-saving credit incentive system and method based on vehicle-road cooperation. By collecting platooning-related information at the electronic toll collection gantry and reconstructing the dispersed gantry data into a platooning spatiotemporal trajectory sequence according to platooning identifiers, platooning behavior can be continuously characterized at the road segment scale. This solves the problem of existing technologies struggling to reconstruct the platooning process across gantries. By comparing the platooning spatiotemporal trajectory sequence with baseline energy consumption data for the same road segment, energy-saving credit is output and an energy-saving credit certificate is generated, achieving a unified quantitative standard for emission reduction and credit. A trusted credit ledger stores and records integrity verification information for the energy-saving credit certificate, and a pre-linked identifier for binding with exit electronic toll transactions is introduced into the certificate, giving the energy-saving credit attributes of tamper-proof, traceability, and settlement binding. When an exit transaction is triggered, the system queries, verifies, and generates toll discounts according to a mapping table, incorporating negative transaction records into the settlement, forming a real-time incentive closed loop that can be implemented.

[0009] To achieve the above objectives, the present invention provides a vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation, including a roadside perception and communication unit, a trajectory sequence reconstruction unit, an energy-saving credit assessment unit, a trusted credit ledger, and a green credit verification unit; The roadside sensing and communication unit is installed at the electronic toll collection gantry of the highway and has a data interface for communicating with the vehicle's on-board unit. It is used to collect the platoon identifier, the on-board unit identifier of the platoon members, and the corresponding timestamp and speed information when vehicles pass in platoons. The trajectory sequence reconstruction unit is communicatively connected to the roadside perception and communication unit, and is used to associate the platoon data collected at different electronic toll collection gantries based on the platoon identifier, and reconstruct the discrete collection points into a platoon spatiotemporal trajectory sequence. The energy-saving credit assessment unit is communicatively connected to the trajectory sequence reconstruction unit and is used to compare and calculate the formation spatiotemporal trajectory sequence with the benchmark energy consumption data of the same road segment, output the energy-saving credit corresponding to the formation, and generate an energy-saving credit certificate containing formation identifier, timestamp, emission reduction and energy-saving credit result. The trusted credit ledger is communicatively connected to the energy-saving credit assessment unit and is used to store the energy-saving credit certificate and record the integrity verification information corresponding to the energy-saving credit certificate. The energy-saving credit certificate contains a pre-link identifier for binding the energy-saving credit certificate with the export electronic toll transaction. The green credit verification unit is connected to the electronic toll settlement system. When a vehicle triggers an exit electronic toll transaction, it queries the trusted credit ledger for a matching energy-saving credit certificate based on the vehicle's on-board unit identifier and entry time. After verifying the validity of the energy-saving credit certificate, it generates a toll discount according to a preset emission reduction and discount amount mapping table, and settles the toll discount together with the toll transaction as a negative transaction record.

[0010] In the above technical solution, preferably, the roadside sensing and communication unit is an enhanced electronic toll collection gantry, and the roadside sensing and communication unit includes a vehicle-to-infrastructure communication module and a video sensing module; The vehicle-to-infrastructure communication module is used to interact with the vehicle's onboard unit to confirm the formation status and to broadcast formation suggestions. The video perception module is used to acquire images of vehicles passing through the electronic toll gate and extract queue geometry information, including queue formation information and vehicle spacing information. The roadside perception and communication unit outputs the platoon identifier, the vehicle unit identifier of the platoon member, the timestamp, the speed information, and the queue geometry information based on the fusion result of the vehicle-to-infrastructure communication module and the video perception module.

[0011] In the above technical solution, preferably, the trajectory sequence reconstruction unit is used to associate and match the queuing data collected at different electronic toll collection gantries according to the queuing identifier, and sort them according to the timestamp to form a queuing spatiotemporal trajectory sequence containing multiple gantry collection points; The formation spatiotemporal trajectory sequence includes at least the vehicle unit identifier of the formation members, the gantry identifier sequence, the corresponding timestamp sequence, and the corresponding speed sequence, and includes travel time information between adjacent electronic toll collection gantries.

[0012] In the above technical solution, preferably, the energy-saving credit assessment unit includes an energy-saving assessment model, which adopts a spatiotemporal graph neural network architecture. The input feature map of the spatiotemporal graph neural network is constructed with vehicles as nodes and the spatiotemporal relationship between vehicles as edges. The node features include instantaneous speed, vehicle type, and travel time between two consecutive electronic toll gates. The weight of the edge is dynamically calculated based on the vehicle's position in the queue and the time difference. The energy-saving credit assessment unit inputs the formation spatiotemporal trajectory sequence, as well as the corresponding time period and road segment baseline traffic flow data, real-time weather data, and road alignment data, including slope and curvature. The energy-saving credit assessment unit is used to compare the actual energy consumption estimate of the formation with the benchmark energy consumption estimate, wherein the actual energy consumption estimate of the formation is obtained based on the aerodynamic formation drag reduction model, and outputs the energy-saving benefit coefficient and calculates the emission reduction based on the comparison results.

[0013] In the above technical solution, preferably, the trusted credit ledger is a central database with tamper-proof logs or a permissioned blockchain module; The trusted credit ledger is used to store each energy-saving credit certificate record. The energy-saving credit certificate record includes a unique hash value of the certificate, a queuing identifier, a timestamp, a snapshot of key input features of the energy-saving assessment, emission reduction calculation results, and information associated with the electronic toll transaction serial number corresponding to the pre-linked identifier. The pre-link identifier is an identifier pre-generated using an encryption algorithm and used to bind the energy-saving credit certificate to the export electronic toll transaction; The trusted credit ledger is used to encrypt and store the energy-saving credit certificate, and to record the integrity verification information corresponding to the energy-saving credit certificate.

[0014] This invention also proposes a vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation, applicable to the vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation disclosed in any of the above technical solutions, comprising: Collect platoon identification, platoon member onboard unit identification, and corresponding timestamp and speed information when vehicles pass in platoons at the electronic toll collection gantries on highways; Based on the formation identifier, the formation data collected at different electronic toll collection gantries are correlated, and the discrete collection points are reconstructed into a formation spatiotemporal trajectory sequence; The formation's spatiotemporal trajectory sequence is compared and calculated with the baseline energy consumption data of the same road segment. The energy-saving credit corresponding to the formation is output, and an energy-saving credit certificate containing the formation identifier, timestamp, emission reduction amount and energy-saving credit result is generated. The energy-saving credit certificate contains a pre-link identifier for binding the energy-saving credit certificate with the electronic toll collection transaction at the exit. Store the energy-saving credit certificate in a trusted credit ledger and record the integrity verification information corresponding to the energy-saving credit certificate; When a vehicle triggers an electronic toll collection transaction at the exit, the system queries the trusted credit ledger for a matching energy-saving credit certificate based on the vehicle's on-board unit identifier and entry time. After verifying the validity of the energy-saving credit certificate, the system generates a toll discount according to a preset mapping table of emission reduction and discount amount, and settles the toll discount together with the toll transaction as a negative transaction record.

[0015] In the above technical solution, preferably, the acquisition process specifically includes: The electronic toll gantry communicates with the vehicle's onboard unit to confirm platoon status and broadcast platoon suggestions. The queue geometry information is extracted by video capture, and the queue geometry information includes the queue formation information and the vehicle spacing information. It also outputs the formation data that corresponds to the queue geometry information, the timestamp, and the speed information.

[0016] In the above technical solution, preferably, the comparison calculation process specifically includes: A spatiotemporal graph neural network trained through multi-task learning is used to infer the spatiotemporal trajectory sequence of the formation. The main task of multi-task learning is single-vehicle energy consumption regression prediction, and the auxiliary task is classification prediction of whether the vehicles are in a formation state. The input feature map of the spatiotemporal graph neural network is constructed with vehicles as nodes and the spatiotemporal relationship between vehicles as edges. The node features include instantaneous speed, vehicle type and travel time between two consecutive electronic toll gates. The weight of the edge is dynamically calculated based on the vehicle's position in the queue and the time difference. The inference input simultaneously incorporates baseline traffic flow data, real-time weather data, and road alignment data, including slope and curvature. An aerodynamic drag reduction model is used to obtain an estimate of the actual energy consumption of the formation. The estimated actual energy consumption is then compared with a baseline energy consumption estimate to output an energy-saving benefit coefficient. Based on the energy-saving benefit coefficient, the baseline energy consumption data, and the carbon factor, the emission reduction is calculated.

[0017] In the above technical solution, preferably, the specific process of storing the energy-saving credit certificate in the trusted credit ledger includes: Generate a unique hash value for the energy-saving credit certificate, and store the unique hash value along with the fleet identifier, timestamp, snapshot of key input features of the energy-saving assessment, emission reduction calculation results, and integrity verification information. The pre-link identifier is pre-generated using an encryption algorithm and associated with the export electronic toll transaction serial number to achieve deterministic binding between the energy-saving credit certificate and the export electronic toll transaction; The evidence storage includes encrypting the energy-saving credit certificate and then writing it into the trusted credit ledger.

[0018] In the above technical solution, preferably, verifying the validity of the energy-saving credit certificate specifically includes verifying the consistency between the unique hash value of the certificate and the integrity verification information; The process of generating toll discounts includes calculating the discount amount based on the emission reduction and discount amount mapping table and generating a negative transaction record. The settlement process includes merging the negative transaction record with the toll transaction for settlement, and outputting the green platoon discount information corresponding to this passage.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) By collecting formation identifiers, vehicle unit identifiers of formation members, timestamps and speed information at the electronic toll collection gantry, and using the trajectory sequence reconstruction unit to associate the formation data at different gantries based on the formation identifiers, the discrete collection points are reconstructed into a formation spatiotemporal trajectory sequence, so that the formation driving process has a continuous and computable data foundation at the road segment scale, which solves the problem that the formation data is difficult to reconstruct across gantries in the prior art due to the dispersed collection of formation data.

[0020] (2) By comparing the formation spatiotemporal trajectory sequence with the baseline energy consumption data of the same road segment through the energy-saving credit assessment unit, the energy-saving credit corresponding to the formation is output, and an energy-saving credit certificate containing formation identifier, timestamp, emission reduction and energy-saving credit result is generated. This realizes the unified quantitative standard and certificate expression of energy-saving and emission-reduction effect, and supports large-scale and verifiable incentive basis.

[0021] (3) The energy-saving credit certificate is stored and the integrity verification information is recorded through a trusted credit ledger. A pre-linking identifier is set in the energy-saving credit certificate to bind it to the export electronic fee transaction, so that the credit result has the ability to prevent tampering, be traceable and be bound to the settlement transaction, thereby reducing the risk of credit tampering, unclear ownership and duplicate write-off.

[0022] (4) By linking the green credit verification unit with the electronic toll settlement system, when the electronic toll transaction at the exit is triggered, the system queries and matches the voucher based on the vehicle unit identifier and the entry time and completes the validity verification. The system generates toll discounts according to the emission reduction and discount amount mapping table, and settles them together with the negative transaction record and the toll transaction, forming a real-time incentive closed loop of generation, storage, verification and settlement, which improves the implementation efficiency and operational controllability. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of a unit module of a vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation, as disclosed in one embodiment of the present invention. Figure 2 This is a logical schematic diagram of a vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation disclosed in one embodiment of the present invention.

[0024] The correspondence between the components and the reference numerals in the diagram is as follows: 1. Roadside sensing and communication unit, 2. Trajectory sequence reconstruction unit, 3. Energy-saving credit assessment unit, 4. Trusted credit ledger, 5. Green credit verification unit. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] The present invention will now be described in further detail with reference to the accompanying drawings: like Figure 1 As shown, the vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation provided by the present invention is organized according to a closed-loop logic of monitoring-measuring-incentive. It is used to convert vehicle platooning behavior into verifiable energy-saving credits, which are then redeemed as toll discounts at the exit electronic toll transaction stage. The system includes a roadside perception and communication unit 1, a trajectory sequence reconstruction unit 2, an energy-saving credit assessment unit 3, a trusted credit ledger 4, and a green credit redemption unit 5.

[0027] The roadside sensing and communication unit 1 is deployed at the electronic toll collection gantry on the highway. Using the data interface that communicates with the vehicle's on-board unit, it collects the platoon identifier, the on-board unit identifier of the platoon members, and the corresponding timestamp and speed information when vehicles pass in platoons, as reliable data for subsequent calculations.

[0028] The trajectory sequence reconstruction unit 2 is connected to the roadside perception and communication unit 1. It is used to associate the platoon data collected at different electronic toll collection gantries based on the platoon identifier, restore and reconstruct the discrete collection points into the platoon spatiotemporal trajectory sequence, and transform the platoon behavior from point-like records to road segment-level process data.

[0029] The energy-saving credit assessment unit 3 is connected to the trajectory sequence reconstruction unit 2. Taking the formation spatiotemporal trajectory sequence as the core input, it is used to compare and calculate the formation spatiotemporal trajectory sequence with the benchmark energy consumption data of the same road segment, output the energy-saving credit corresponding to the formation, and generate an energy-saving credit certificate containing formation identifier, timestamp, emission reduction and energy-saving credit result, so that the energy-saving result has a unified quantitative standard and a certificate carrier.

[0030] The trusted credit ledger 4 is connected to the energy-saving credit assessment unit 3 for storing energy-saving credit certificates and recording the integrity verification information corresponding to the energy-saving credit certificates. At the same time, a pre-link identifier is written into the certificate to establish a deterministic binding relationship between the certificate and the export electronic toll transaction, reducing the risk of tampering, misuse and duplicate verification.

[0031] The green credit verification unit 5 is connected to the electronic toll settlement system. When a vehicle triggers an exit electronic toll transaction, it queries the trusted credit ledger 4 for a matching energy-saving credit certificate based on the vehicle's on-board unit identifier (OBU_ID) and entry time. After verifying the validity of the energy-saving credit certificate, it generates a toll discount according to a preset mapping table of emission reduction and discount amount. The toll discount is then settled together with the toll transaction as a negative transaction record, thus forming an automatically executable real-time incentive closed loop.

[0032] Specifically, the monitoring layer uses ETC gantries deployed on highways to monitor and identify the platooning status of autonomous vehicles in real time (such as platoon ID, vehicle members, formation, spacing, and passage time sequence).

[0033] The metric layer inputs the raw data acquired by the monitoring layer into an energy-saving assessment model specifically for autonomous vehicle platooning. This model integrates multi-source data and outputs a quantified energy-saving credit for that particular platooning behavior.

[0034] The incentive layer transmits the energy-saving credits generated by the measurement layer to the ETC toll settlement system in real time and securely, automatically calculates and applies the corresponding toll discounts, and completes the economic incentive for users.

[0035] In this implementation, gantry data, energy-saving measurements, and billing settlement are integrated to form a closed-loop logic that is measurable, verifiable, revocable, and settlementable, supporting the large-scale implementation and controllable operation of fleet energy-saving incentives.

[0036] In the above embodiments, preferably, the roadside sensing and communication unit 1 is an enhanced electronic toll collection gantry, and the roadside sensing and communication unit 1 includes a vehicle-to-infrastructure communication module and a video sensing module.

[0037] The vehicle-to-infrastructure communication module is used to interact with the vehicle's onboard unit to confirm the formation status information, enabling the gantry side to provide confirmation logic for the consistency between the formation identifier and the member identifier. At the same time, it broadcasts formation suggestions to the vehicles in the formation, expanding the formation operation from simple passive data collection to collaborative guidance.

[0038] The video perception module is used to acquire images of vehicles passing through the electronic toll gate and extract queue geometry information, including queue formation information and vehicle spacing information, so that the queue structure features have an independent source of perception.

[0039] The roadside perception and communication unit 1 is based on the fusion results of the vehicle-road communication module and the video perception module. The fusion processing uses the status confirmation information obtained by the vehicle-road communication as the identity anchor and the queue geometry information extracted from the video as the evidence of the formation structure. It outputs the association results of the formation identifier, the vehicle unit identifier of the formation member, the timestamp, the speed information and the queue geometry information.

[0040] In this implementation, the stability and consistency of formation identification are improved by using dual-channel acquisition and fusion of communication confirmation and video evidence, reducing misjudgments and data drift introduced by relying solely on a single acquisition link, and enhancing the credibility of subsequent energy-saving credit measurement.

[0041] In the above embodiments, preferably, the trajectory sequence reconstruction unit 2 is deployed on a cloud service or a central computing node, maintaining a data link with the roadside perception and communication units 1 of multiple electronic toll collection gantries. The trajectory sequence reconstruction unit 2 correlates and matches the platooning data collected at different electronic toll collection gantries according to the platooning identifier, and sorts them by timestamp to form a platooning spatiotemporal trajectory sequence containing multiple gantry collection points.

[0042] The formation spatiotemporal trajectory sequence includes at least the vehicle unit identifier of the formation members, the gantry identifier sequence, the corresponding timestamp sequence, and the corresponding speed sequence. Furthermore, the travel time information between adjacent gantries is calculated, thereby organizing the discrete observations across gantry into process data with temporal continuity and spatial order.

[0043] In this implementation, the formation behavior is continuously characterized at the road segment scale, providing a stable input for subsequent energy-saving assessments and avoiding the problem of coarse assessments caused by discrete gantry points not being able to directly reflect the formation process.

[0044] In the above embodiments, preferably, the energy-saving credit assessment unit 3 includes an energy-saving assessment model. The energy-saving assessment model adopts a spatiotemporal graph neural network (ST-GNN) architecture. The input feature map of the spatiotemporal graph neural network is constructed with vehicles as nodes and the spatiotemporal relationship between vehicles as edges.

[0045] Node features are extracted from the gantry acquisition and sequence reconstruction results, including instantaneous speed, vehicle type, and travel time between two consecutive electronic toll collection gantries. The edge weights are dynamically calculated based on the vehicle's position in the queue and the time difference to reflect the strength of mutual influence between vehicles in the queue.

[0046] In addition to inputting the formation spatiotemporal trajectory sequence, the energy-saving credit assessment unit 3 also inputs the baseline traffic flow data, real-time weather data, and road alignment data for the corresponding time period and road segment. The road alignment data includes slope and curvature, so that the energy consumption estimation is consistent with the road conditions and environmental conditions.

[0047] Energy-saving credit assessment unit 3 is used to compare the actual energy consumption estimate of the formation with the benchmark energy consumption estimate. The actual energy consumption estimate of the formation is obtained based on the aerodynamic formation drag reduction model and is used to reflect the impact of formation spacing and formation on drag and energy consumption. After the comparison is completed, the energy-saving benefit coefficient is output and the emission reduction (such as CO2 grams) is calculated to form a quantitative result for incentive settlement.

[0048] In this implementation, the formation structure, driving status and external operating conditions are incorporated into a unified evaluation framework, enabling a more refined and verifiable measurement of energy-saving benefits, reducing evaluation bias and improving the fairness of incentive criteria.

[0049] In the above embodiments, preferably, the trusted credit ledger 4 is a central database with tamper-proof logs or a permissioned blockchain module, which forms an energy-saving credit certificate record for each formation credit generation.

[0050] The Trusted Credit Ledger 4 is used to store each energy-saving credit certificate record. The energy-saving credit certificate record includes the certificate's unique hash value, formation identifier, timestamp, snapshot of key input features of the energy-saving assessment, emission reduction calculation results, and information associated with the electronic toll transaction serial number corresponding to the pre-linked identifier.

[0051] The pre-link identifier is generated in advance using an encryption algorithm and is used to establish a deterministic binding relationship between energy-saving credit certificates and export electronic toll transactions, making the ownership and verification of certificates clear.

[0052] Trusted Credit Ledger 4 is used to encrypt and store energy-saving credit vouchers, and record the integrity verification information corresponding to the energy-saving credit vouchers, so that the ledger has anti-tampering and auditable traceability capabilities; when the reconciliation side initiates a query, the ledger returns the matching voucher and the information required for verification to support validity verification.

[0053] In this implementation, a trusted link is formed by hashing, encrypted storage, integrity verification, and transaction association, which reduces the risk of voucher tampering, forgery, and duplicate resale, and improves the compliance and auditability of incentive settlement.

[0054] The vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation provided by this invention, for the first time, deeply couples the ETC monitoring system, AI model evaluation system, and toll settlement system, constructing a fully automated closed-loop technical framework of "perception-measurement-incentive" for vehicle platooning behavior. It proposes a quantitative method for "platooning energy-saving credit" based on ETC spatiotemporal trajectory sequences and baseline comparison, solving the technical challenge of directly measuring energy-saving effects in open road environments while ensuring fair evaluation. This transforms "green incentives" from a concept into an automatically executable technical protocol. Through the technical carrier of "credit certificates," it opens up a technical path from environmental behavior to economic feedback while ensuring safety and fairness, overcoming a core obstacle to the promotion of autonomous driving platooning technology. It is expected to significantly increase the proportion of platooning within the highway network, enabling road network managers to proactively guide and improve the energy efficiency of the entire transportation system in a measurable and verifiable manner. The carbon reduction effect is clear and auditable, and encouraging platooning behavior objectively promotes the coordination and orderliness of vehicle groups, helping to smooth traffic flow and improve road capacity and safety.

[0055] like Figure 2 As shown, the present invention also proposes a vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation, applied to the vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation disclosed in any of the above embodiments, comprising: At the electronic toll collection gantries on highways, the platoon identification, on-board unit identification of platoon members, and corresponding timestamps and speed information are collected when vehicles pass in platoons to form a traceable platoon passage record.

[0056] By associating platoon data collected at different electronic toll collection gantries based on platoon identifiers, discrete collection points are reconstructed into a platoon spatiotemporal trajectory sequence, expanding the evaluation object from a single point to a road segment process.

[0057] The formation's spatiotemporal trajectory sequence is compared and calculated with the baseline energy consumption data of the same road segment. The energy-saving credit corresponding to the formation is output, and an energy-saving credit certificate containing the formation identifier, timestamp, emission reduction, and energy-saving credit result is generated. The energy-saving credit certificate contains a pre-link identifier for binding the energy-saving credit certificate with the electronic toll collection transaction at the exit.

[0058] Store the energy-saving credit certificate in the trusted credit ledger 4 and record the integrity verification information corresponding to the energy-saving credit certificate to complete the trusted storage.

[0059] When a vehicle triggers an electronic toll collection transaction at the exit, the system queries the trusted credit ledger 4 for a matching energy-saving credit certificate based on the vehicle's on-board unit identifier and entry time. After verifying the validity of the energy-saving credit certificate, the system generates a toll discount based on the preset emission reduction and discount amount mapping table, and settles the toll discount together with the toll transaction as a negative transaction record.

[0060] In this implementation, monitoring, measurement, and incentives are formalized into automated execution paths through standardized procedures, reducing the costs of manual intervention and cross-system integration, and supporting the implementation of real-time incentives.

[0061] In the above embodiments, preferably, the acquisition process employs a collaborative acquisition link combining gantry communication interaction and video assistance, specifically including: The electronic toll collection gantry communicates with the vehicle's onboard unit to confirm the formation status information, which is used to confirm the correspondence between formation identifiers and member identifiers, and simultaneously broadcasts formation suggestions to form formation coordination guidance.

[0062] The geometric information of the queue is extracted by video capture. The queue geometric information includes the formation information and the distance between vehicles. It is then correlated with the timestamp and speed information to form structured queue data output.

[0063] In this implementation, the accuracy and robustness of formation recognition are improved by jointly collecting state confirmation and geometric information, providing a more stable data foundation for subsequent trajectory reconstruction and energy-saving assessment.

[0064] In the above embodiments, preferably, the comparison calculation process specifically includes: A spatiotemporal graph neural network trained through multi-task learning is used to infer the spatiotemporal trajectory sequence of platooning. The main task of multi-task learning is the regression prediction of single-vehicle energy consumption, while the auxiliary task is the classification prediction of whether vehicles are in platooning. This allows the model to share representations for both energy consumption inference and platooning identification, improving generalization consistency. The training data comes from a fusion dataset of ETC toll data and real fuel consumption data provided by a commercial truck vehicle networking platform, and is aligned by associating vehicle license plates with toll times.

[0065] The input feature map of the spatiotemporal graph neural network is constructed with vehicles as nodes and the spatiotemporal relationships between vehicles as edges. The node features include instantaneous speed, vehicle type, and travel time between two consecutive electronic toll gates. The edge weights are dynamically calculated based on the vehicle's position in the queue and the time difference to reflect the mutual influence within the queue.

[0066] The inference input simultaneously incorporates baseline traffic flow data, real-time weather data, and road alignment data, including slope and curvature, so that the baseline comparison and the actual estimate are under the same external operating condition constraints.

[0067] An aerodynamic-based formation drag reduction model is used to estimate the actual energy consumption of the formation. This estimate is then compared with a baseline energy consumption estimate to output an energy-saving efficiency coefficient K (0 < K ≤ 1), representing the energy consumption ratio of formation driving compared to single-vehicle driving. Based on the energy-saving efficiency coefficient, baseline energy consumption data, and carbon factor, the emission reduction (credit) is calculated. The specific calculation formula is as follows: Credit=(1-K)×Baseline_Consumption×Carbon_Factor; Among them, Baseline_Consumption is the historical average energy consumption of this vehicle type on the same road segment, and Carbon_Factor is the adjustment coefficient for different vehicle types (pure electric, pure fuel, hybrid, hydrogen, electrified, etc.).

[0068] In this implementation, the stability of energy consumption inference is improved by multi-task learning and graph structure modeling. At the same time, the fairness of comparative evaluation is improved by combining drag reduction mechanism and multi-source operating condition input, making the emission reduction results more consistent with the actual operating conditions of open roads.

[0069] In the above embodiments, preferably, the trusted credit ledger 4 is essentially a central database with tamper-proof logs or a permissioned blockchain module. The specific process of storing energy-saving credit certificates in the trusted credit ledger 4 includes four key operations: hash solidification, element snapshot, association binding, and encrypted writing, specifically including: A unique hash value is generated for the energy-saving credit certificate, and the unique hash value is stored together with the fleet identifier, timestamp, snapshot of key input features of energy-saving assessment, emission reduction calculation results and integrity verification information, so that the content boundary and generation logic of the certificate have audit anchors.

[0070] The pre-link identifier is generated in advance using an encryption algorithm and associated with the export electronic toll transaction serial number to achieve deterministic binding between the energy-saving credit certificate and the export electronic toll transaction.

[0071] After the energy-saving credit certificate is encrypted, it is written into the trusted credit ledger 4, so that the evidence data can maintain security and tamper-proofness during the transmission and storage stages.

[0072] In this implementation, deterministic binding and encrypted storage reduce the risk of vouchers being replaced, reused, or misappropriated across transactions, thereby improving the verifiability and compliance of the reconciliation process.

[0073] In the above embodiments, preferably, verifying the validity of the energy-saving credit certificate specifically includes verifying the consistency between the unique hash value of the certificate and the integrity verification information, so that the cancellation is only performed on genuine and untampered certificates.

[0074] When generating toll discounts, the discount amount is calculated based on the mapping table between emission reduction and discount amount, and a corresponding negative transaction record is generated so that the discount is settled in the form of transaction elements.

[0075] During the settlement phase, negative transaction records and toll transactions are merged and settled, and the green formation discount information corresponding to this passage is output, that is, the discount enjoyed by this passage due to the green formation, so that the incentive results are visible to users and consistent with the transaction records.

[0076] In this implementation, the discount calculation is solidified into a verifiable transaction record and settled together with the original transaction, reducing the risk of clearing and reconciliation caused by system fragmentation and realizing real-time write-off and traceable settlement.

[0077] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation, characterized in that, It includes a roadside sensing and communication unit, a trajectory sequence reconstruction unit, an energy-saving credit assessment unit, a trusted credit ledger, and a green credit verification unit; The roadside sensing and communication unit is installed at the electronic toll collection gantry of the highway and has a data interface for communicating with the vehicle's on-board unit. It is used to collect the platoon identifier, the on-board unit identifier of the platoon members, and the corresponding timestamp and speed information when vehicles pass in platoons. The trajectory sequence reconstruction unit is communicatively connected to the roadside perception and communication unit, and is used to associate the platoon data collected at different electronic toll collection gantries based on the platoon identifier, and reconstruct the discrete collection points into a platoon spatiotemporal trajectory sequence. The energy-saving credit assessment unit is communicatively connected to the trajectory sequence reconstruction unit and is used to compare and calculate the formation spatiotemporal trajectory sequence with the benchmark energy consumption data of the same road segment, output the energy-saving credit corresponding to the formation, and generate an energy-saving credit certificate containing formation identifier, timestamp, emission reduction and energy-saving credit result. The trusted credit ledger is communicatively connected to the energy-saving credit assessment unit and is used to store the energy-saving credit certificate and record the integrity verification information corresponding to the energy-saving credit certificate. The energy-saving credit certificate contains a pre-link identifier for binding the energy-saving credit certificate with the export electronic toll transaction. The green credit verification unit is connected to the electronic toll settlement system. When a vehicle triggers an exit electronic toll transaction, it queries the trusted credit ledger for a matching energy-saving credit certificate based on the vehicle's on-board unit identifier and entry time. After verifying the validity of the energy-saving credit certificate, it generates a toll discount according to a preset emission reduction and discount amount mapping table, and settles the toll discount together with the toll transaction as a negative transaction record.

2. The vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation according to claim 1, characterized in that, The roadside sensing and communication unit is an enhanced electronic toll collection gantry, which includes a vehicle-to-infrastructure communication module and a video sensing module. The vehicle-to-infrastructure communication module is used to interact with the vehicle's onboard unit to confirm the formation status and to broadcast formation suggestions. The video perception module is used to acquire images of vehicles passing through the electronic toll gate and extract queue geometry information, including queue formation information and vehicle spacing information. The roadside perception and communication unit outputs the platoon identifier, the vehicle unit identifier of the platoon member, the timestamp, the speed information, and the queue geometry information based on the fusion result of the vehicle-to-infrastructure communication module and the video perception module.

3. The vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation according to claim 1, characterized in that, The trajectory sequence reconstruction unit is used to associate and match the platoon data collected at different electronic toll collection gantries according to the platoon identifier, and sort them by timestamp to form a platoon spatiotemporal trajectory sequence containing multiple gantry collection points; The formation spatiotemporal trajectory sequence includes at least the vehicle unit identifier of the formation members, the gantry identifier sequence, the corresponding timestamp sequence, and the corresponding speed sequence, and includes travel time information between adjacent electronic toll collection gantries.

4. The vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation according to claim 1, characterized in that, The energy-saving credit assessment unit includes an energy-saving assessment model, which adopts a spatiotemporal graph neural network architecture. The input feature map of the spatiotemporal graph neural network is constructed with vehicles as nodes and the spatiotemporal relationships between vehicles as edges. The node features include instantaneous speed, vehicle type, and travel time between two consecutive electronic toll gates. The weight of the edge is dynamically calculated based on the vehicle's position in the queue and the time difference. The energy-saving credit assessment unit inputs the formation spatiotemporal trajectory sequence, as well as the corresponding time period and road segment baseline traffic flow data, real-time weather data, and road alignment data, including slope and curvature. The energy-saving credit assessment unit is used to compare the actual energy consumption estimate of the formation with the benchmark energy consumption estimate, wherein the actual energy consumption estimate of the formation is obtained based on the aerodynamic formation drag reduction model, and outputs the energy-saving benefit coefficient and calculates the emission reduction based on the comparison results.

5. The vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation according to claim 1, characterized in that, The trusted credit ledger is a central database with tamper-proof logs or a permissioned blockchain module; The trusted credit ledger is used to store each energy-saving credit certificate record. The energy-saving credit certificate record includes a unique hash value of the certificate, a queuing identifier, a timestamp, a snapshot of key input features of the energy-saving assessment, emission reduction calculation results, and information associated with the electronic toll transaction serial number corresponding to the pre-linked identifier. The pre-link identifier is an identifier pre-generated using an encryption algorithm and used to bind the energy-saving credit certificate to the export electronic toll transaction; The trusted credit ledger is used to encrypt and store the energy-saving credit certificate, and to record the integrity verification information corresponding to the energy-saving credit certificate.

6. A vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation, characterized in that, The vehicle platooning energy-saving credit incentive system based on vehicle-road cooperation as described in any one of claims 1 to 5 includes: Collect platoon identification, platoon member onboard unit identification, and corresponding timestamp and speed information when vehicles pass in platoons at the electronic toll collection gantries on highways; Based on the formation identifier, the formation data collected at different electronic toll collection gantries are correlated, and the discrete collection points are reconstructed into a formation spatiotemporal trajectory sequence; The formation's spatiotemporal trajectory sequence is compared and calculated with the baseline energy consumption data of the same road segment. The energy-saving credit corresponding to the formation is output, and an energy-saving credit certificate containing the formation identifier, timestamp, emission reduction amount and energy-saving credit result is generated. The energy-saving credit certificate contains a pre-link identifier for binding the energy-saving credit certificate with the electronic toll collection transaction at the exit. Store the energy-saving credit certificate in a trusted credit ledger and record the integrity verification information corresponding to the energy-saving credit certificate; When a vehicle triggers an electronic toll collection transaction at the exit, the system queries the trusted credit ledger for a matching energy-saving credit certificate based on the vehicle's on-board unit identifier and entry time. After verifying the validity of the energy-saving credit certificate, the system generates a toll discount according to a preset mapping table of emission reduction and discount amount, and settles the toll discount together with the toll transaction as a negative transaction record.

7. The vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation according to claim 6, characterized in that, The data acquisition process specifically includes: The electronic toll gantry communicates with the vehicle's onboard unit to confirm platoon status and broadcast platoon suggestions. The queue geometry information is extracted by video capture, and the queue geometry information includes the queue formation information and the vehicle spacing information. It also outputs the formation data that corresponds to the queue geometry information, the timestamp, and the speed information.

8. The vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation according to claim 6, characterized in that, The comparison calculation process specifically includes: A spatiotemporal graph neural network trained through multi-task learning is used to infer the spatiotemporal trajectory sequence of the formation. The main task of multi-task learning is single-vehicle energy consumption regression prediction, and the auxiliary task is classification prediction of whether the vehicles are in a formation state. The input feature map of the spatiotemporal graph neural network is constructed with vehicles as nodes and the spatiotemporal relationship between vehicles as edges. The node features include instantaneous speed, vehicle type and travel time between two consecutive electronic toll gates. The weight of the edge is dynamically calculated based on the vehicle's position in the queue and the time difference. The inference input simultaneously incorporates baseline traffic flow data, real-time weather data, and road alignment data, including slope and curvature. An aerodynamic drag reduction model is used to obtain an estimate of the actual energy consumption of the formation. The estimated actual energy consumption is then compared with a baseline energy consumption estimate to output an energy-saving benefit coefficient. Based on the energy-saving benefit coefficient, the baseline energy consumption data, and the carbon factor, the emission reduction is calculated.

9. The vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation according to claim 6, characterized in that, The specific process of depositing the energy-saving credit certificate into the trusted credit ledger includes: Generate a unique hash value for the energy-saving credit certificate, and store the unique hash value along with the fleet identifier, timestamp, snapshot of key input features of the energy-saving assessment, emission reduction calculation results, and integrity verification information. The pre-link identifier is pre-generated using an encryption algorithm and associated with the export electronic toll transaction serial number to achieve deterministic binding between the energy-saving credit certificate and the export electronic toll transaction; The evidence storage includes encrypting the energy-saving credit certificate and then writing it into the trusted credit ledger.

10. The vehicle platooning energy-saving credit incentive method based on vehicle-road cooperation according to claim 6, characterized in that, The verification of the validity of the energy-saving credit certificate specifically includes verifying the consistency between the unique hash value of the certificate and the integrity verification information; The process of generating toll discounts includes calculating the discount amount based on the emission reduction and discount amount mapping table and generating a negative transaction record. The settlement process includes merging the negative transaction record with the toll transaction for settlement, and outputting the green platoon discount information corresponding to this passage.

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