Internet of vehicles resource transaction incentive method based on combined two-way auction

Abstract

The invention relates to the field of resource transaction in the Internet of Vehicles, in particular to an Internet of Vehicles resource transaction incentive method based on combined two-way auction, which comprises the following steps: constructing an Internet of Vehicles resource transaction incentive system consisting of a vehicle trust value block chain VBC, a local auxiliary road side unit L-RSU, a resource agent, a resource provider and a driver user, acquiring auction request auction packets, reputation values and other information of all participants participating in resource auction; the transaction participant submits an auction request auction packet to the L-RSU responsible for resource transaction in the VBC area within the time period; the L-RSU calculates a resource provider and a driver user who win the auction according to the auction packets submitted by all the transaction participants; determining a transaction sequence of two transaction parties; the two parties carry out resource allocation and pricing; and evaluating the auction result. According to the invention, the expandability and operation efficiency of the system can be improved while the resource allocation efficiency of the vehicle nodes is improved.

Description

Technical Field

[0001] The present invention relates to the field of resource trading in the Internet of Vehicles, and particularly to an incentive method for vehicle network resource trading based on combinatorial double auction. Background Art

[0002] Driven by the transformation of the global energy structure and the digital technology revolution, intelligent connected vehicles have broken through the scope of single transportation tools and evolved into a composite carrier of mobile intelligent terminals, distributed energy units, and data interaction nodes, gradually becoming an important direction for the transformation and upgrading of the automotive industry. With the rapid development of the Internet of Vehicles (IoV) technology, vehicle nodes achieve real-time data sharing, collaborative decision-making, and resource scheduling through vehicle-to-everything communication, bringing a revolutionary improvement to the intelligent transportation system.

[0003] Current research mainly focuses on directions such as game theory and blockchain. There are often many participants in IoV, and multiple participants work in a cooperative or independent manner. Game theory can help designers analyze and predict the interactions and decisions among various participants, so as to achieve the optimal allocation of resources and the balance of interests. Blockchain, due to its characteristics of decentralization, transparency, traceability, and immutability, is widely used in solving problems such as trust loss, low efficiency, and lack of fairness in traditional centralized incentive models. However, the collaboration efficiency and credibility management of distributed model participants are still core issues: firstly, private vehicles lack economic incentives to participate in data sharing or computing tasks, resulting in limited overall system performance; secondly, traditional centralized scheduling is difficult to adapt to dynamic network environments and is vulnerable to single-point failures; thirdly, malicious nodes may forge data or deny service, threatening system reliability and data authenticity.

[0004] Existing research mostly adopts unilateral pricing or centralized auction mechanisms, which have problems such as static pricing being unable to reflect dynamic supply and demand, ignoring trust factors, and poor scalability, and it is difficult to meet the core requirements of high dynamics, decentralization, and trusted collaboration in the Internet of Vehicles. Generally speaking, although existing research has achieved remarkable progress by using different technologies, the IoV incentive mechanism still faces many challenges when applied to specific trust management systems. Existing incentive mechanisms are often inefficient and lack consideration for the trust relationship of nodes. Therefore, it is necessary to design an incentive mechanism that is more suitable for the trust management system based on establishing the trust relationship between nodes, and improve the efficiency and cost of the incentive mechanism. Summary of the Invention

[0005] To solve the above problems, the present invention proposes an incentive method for vehicle network resource trading based on double auction, including the following steps:

[0006] S1. Construct an incentive system for vehicle network resource trading consisting of a Vehicle Trust Value Blockchain (VBC), a Local Auxiliary Road Side Unit (L-RSU), a resource broker, a resource provider, and a driver user, and obtain information such as auction request bidding packages and reputation values of all participants in the resource auction;

[0007] S2. The trading participants submit their auction request bidding packages to the L-RSU responsible for resource trading within the VBC area during this time period;

[0008] S3. The L-RSU calculates the winning resource providers and driver users in the auction based on the bidding packages submitted by all trading participants;

[0009] S4. Determine the trading order of the two parties;

[0010] S5. The two parties conduct resource allocation and pricing;

[0011] S6. Evaluate the auction results;

[0012] Among them, the Vehicle Trust Value Blockchain (VBC) serves as the lower-layer blockchain, recording local vehicle information in the current blockchain; the Local Auxiliary Road Side Unit (L-RSU) is responsible for collecting information related to reputation value evaluation, calculating the current reputation value of local vehicle nodes, and periodically updating the global reputation value of drivers; the driver user (DU) is the initiator who needs to request resource services in the system, that is, the "buyer" in the auction system; the resource provider (RP) is the resource provider in the system, that is, the "seller" in the auction system.

[0013] Furthermore, step S1 obtains information such as auction request bidding packages and reputation values of all participants in the resource auction, including:

[0014] S11. In the contract initialization stage, create data and parameters related to the smart contract, such as a set B of auction bidding packages storing the quantity and price of the auctioned resources, a set storing the participant numbers, etc., and adjust the contract status parameter state to 1 to indicate that the trading status has been activated and trading can be carried out;

[0015] S12. In the trading preparation stage, obtain relevant information of all participants in the resource auction from the VBC, including the auction request bidding package B of trading participant j j , the node reputation value PR j and the node activity sleepy; to ensure that the system is not damaged by malicious nodes and to ensure the normal operation of the system during the auction, filter out nodes with a reputation threshold lower than 0.4 and nodes with a sleepy parameter of 2 (extremely inactive), and check whether the contract status parameter state is 1; finally, obtain the relevant information of the screened participants, including the auction request bidding package B of trading participant j j , the reputation value PRj 。

[0016] Furthermore, trading participant j submits a bidding package to the auction control center L-RSU, including:

[0017] S21. Trading participant j submits an auction request bidding package B to the L-RSU responsible for resource trading within this time period in the VBC area j =(b j , u j ), where b j =(b 1j ,..., b ij ,..., b nj ), b ij represents the quantity of the i-th type of resource in the bidding package B submitted by trading participant j j , u j =(u 1j ,..., u ij ,..., u nj ), u ij represents the price quoted by trading participant j for the i-th type of resource, where i ∈ {1,..., n}, j ∈ {1,..., m}, n is the total number of resource types, and m is the total number of trading participants;

[0018] S22. The contract collects the bidding information, checks whether all participant serial numbers and bidding packages exist in the participant set and the bidding package set. If not, add them to the corresponding sets, and check whether the trading status parameter state is 1.

[0019] Furthermore, in the vehicle networking resource trading market, there are multiple trading participants. The process of determining the auction winner is as follows:

[0020] S31. The bidding package B of trading participant j j =(b j , u j ). When trading participant j is a DU, b ij >0, u ij >0. When trading participant j is an RP, b ij <0, u ij <0;

[0021] S32. The winning result X=(x1,..., x n ) of the combinatorial double auction is obtained through a double auction model based on unit price. The double auction model is as follows:

[0022]

[0023]

[0024] Among them, the objective function Maximize market profits, constraints Ensure that the transaction is completed smoothly, that is, the resource supply can meet the resource demand, x j =1 means the bid is successful, x j =0 means the bidding failed;

[0025] Through the above double auction model based on unit price, the DU and RP that win the auction are obtained.

[0026] Furthermore, let there be j∈{1,...,m} transaction participants, and the DU serial number set be M p , the number of DUs is m p =|M p |; The RP sequence number set is set to M s , the number of RPs is m s =|M s The steps to determine the transaction sequence between the two parties are as follows:

[0027] S41. According to the current RP bid, according to the formula Calculate the current market reference price of the i-th resource for trading participant j

[0028] S42. According to the formula Calculate the price competitiveness evaluation parameter vs for the i-th type of resource of transaction participant j of type RP ij , according to the formula Calculate the normalized score of the price competitiveness evaluation parameter Similarly, according to the formula Calculate the price competitiveness evaluation parameter vp of transaction participant j of type DU for type i resources ij , according to the formula Calculate the normalized score of the price competitiveness evaluation parameter

[0029] S43. According to the formula Calculate the comprehensive competitiveness score R of transaction participant j of RP type for resource type i ij , where χ is the price weight, 1-χ is the trust weight, 0≤χ≤1;

[0030] S44. Score the comprehensive competitiveness of the transaction participants of type RP as R ij Arrange in descending order and store the RP numbers in the list sl in this order i And store the available quantity of the i-th type of resources in the auction request bidding package submitted by all RPs in the list accordingly to obtain the list sal iArrange the price evaluation parameters of transaction participants of type DU in descending order, and store the numbers of DUs in this order into the list pl i , and store the request quantities for the i-th type of resource in the auction request bidding packages submitted by all DUs into the list accordingly to obtain the list pal i ;

[0031] S45. According to the formula θ p =1 - θ s Calculate the RP ratio parameter θ s , according to the formula Calculate the transaction unit price matrix of the i-th type of resource, where Tu i (p, s) represents the price when the DU ranked p in the pl i list and the RP ranked s in the sl i list trade the i-th type of resource, represents the average reputation of the overall DUs for the i-th type of resource, represents the reputation value of the RP ranked s in the list sl i .

[0032] Furthermore, let RA i and PA i store the transaction allocation result matrix and the transaction price result matrix of the i-th type of resource respectively. The resource allocation and pricing process is as follows:

[0033] S51. Initialize the parameters, i = 1, p = 1, s = 1;

[0034] S52. Process the requests for resource i in sequence according to the order in the pal i list. When there are unprocessed requests, go to step S53; otherwise, go to step S54;

[0035] S53. When pal i (p) ≤ -sal i (s), go to step S56; otherwise, go to step S57;

[0036] S54. Check whether all requests for the i-th type of resource in the pal i list are satisfied. If all requests for the i-th type of resource are satisfied, go to step S55; otherwise, perform the operation p = p + 1 and then go to step S52;

[0037] S55. Check whether all types of service resources are satisfied. If all service resources are satisfied, the process is completed and exited. Otherwise, perform the operations i = i + 1, p = 1, s = 1 and then go to step S52;

[0038] S56. Perform the following operations:

[0039] RA i (p, s) = RA i (p, s) + pal i (p);

[0040] PA i (p, s) = PA i (p, s) + pal i (p) · Tu i (p, s);

[0041] sal i (s) = sal i (s) + pal i (p);

[0042] pal i (p) = 0;

[0043] After performing the above operations, go to step S54;

[0044] S57. Perform the following operations:

[0045] RA i (p, s) = RA i (p, s) - sal i (s);

[0046] PA i (p, s) = PA i (p, s) - sal i (s) · Tu i (p, s);

[0047] pal i (p) = pal i (p) + sal i (s);

[0048] sal i (s) = 0;

[0049] s = s + 1;

[0050] After performing the above operations, go to step S52;

[0051] S58. Obtain the remaining funds and remaining resources of the participants after the auction, and adjust the transaction contract status parameter state to 0;

[0052] Furthermore, to evaluate auction results such as social surplus, the steps are as follows:

[0053] S61. Enter the contract end stage, receive the confirmation closing information sent by the trading participants after the transaction is completed. When the return value of the confirmation closing information is 1 and the transaction contract status parameter state is also 0, the contract ends;

[0054] S62. After all transactions are completed, according to the formula calculate the total income or expenditure costs of both trading parties respectively and For the auction winner, according to the formula calculate its utility, and according to the formula calculate the average utility, where b j ′ is the quantity of resources for which the transaction is completed in the presence of a transaction surplus;

[0055] S63. According to the formula calculate the social surplus SP, which represents the total sum of the total benefits jointly obtained by both trading parties in the trading system.

[0056] Advantages of the present invention:

[0057] The present invention considers constructing a system model with VBC, L-RSU, resource agents, RP, and DU; aiming at the problems in traditional methods, such as static pricing being unable to reflect dynamic supply and demand, ignoring trust factors, and poor scalability, a vehicle-to-everything (V2X) resource trading incentive method based on combinatorial double auction is proposed.

[0058] The vehicle-to-everything (V2X) resource trading incentive mechanism based on combinatorial double auction of the present invention, compared with the existing incentive mechanisms based on unilateral pricing or centralized auction mechanisms, can achieve optimal allocation of resources through dynamic market equilibrium, has enhanced scalability, higher operating efficiency, and ensures the fairness and transparency of the mechanism by deploying the algorithm on the smart contract platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is the vehicle-to-everything (V2X) resource trading incentive system model in the embodiment of the present invention;

[0060] Figure 2 is the flowchart of the vehicle-to-everything (V2X) resource trading incentive method based on combinatorial double auction of the present invention;

[0061] Figure 3 is the flowchart of the vehicle-to-everything (V2X) resource trading incentive system in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0063] This paper proposes a combinatorial double auction-based method for incentivizing IoV resource trading. This method constructs an IoV resource trading incentive system. By using a reputation-based combinatorial double auction algorithm and maximizing social surplus, it improves the efficiency of resource allocation among vehicle nodes. Furthermore, a competitiveness evaluation model based on reputation and bidding is proposed, achieving a positive cycle of "reputation appreciation, increased opportunities, and increasing returns."

[0064] In one embodiment, considering the problem of insufficient node enthusiasm in the Internet of Vehicles system, the following is formulated: Figure 1 The Internet of Vehicles resource transaction incentive system shown in FIG.

[0065] RAs, or resource agents, can be divided into vehicle agents (VAs) and facility agents (SAs). RAs exist in the system in different forms depending on the type of participant. Generally speaking, the RA of the user initiating the request is the VA. When the driver logs into the vehicle system, the VA submits the user's request information and coordinates the operation of system mechanisms, including resource discovery, user bidding, and result recording. SAs generally act as agents for resource providers, often fixed facilities such as gas stations and charging stations. These facilities are more reliable than individual providers and are a highly competitive type of resource provider. Individual providers, on the other hand, have geographical or price advantages when vehicle users require urgent charging or when the power network is experiencing peak traffic.

[0066] Driver users (DUs) are the initiators of resource requests in the system, i.e., the “buyers” in the auction system. When a DU needs a resource service, it first submits a bid to the RA, which then processes the request.

[0067] RPs are the providers of system resources, or "sellers" in the auction system. RPs themselves have competitiveness, influenced by their bids and reputation. If other RPs also need resource services, they may be converted into DUs.

[0068] VBC is jointly maintained by VA, SA, and L-RSU. The combined double auction algorithm is implemented in VBC through smart contracts. Smart contracts automatically execute pre-defined rules to complete the pre-allocation of resources and improve system operation efficiency.

[0069] The L-RSU is a facility with relatively strong computing performance and high reliability in the VBC node. This system allows vehicles to unload tasks to a certain L-RSU within the VBC area in turn for real-time processing, and the randomness of the L-RSU responsible for completing the tasks increases the cost of malicious behavior of intruders.

[0070] As Figure 2 shown, an embodiment of the present invention provides an incentive method for vehicle-to-everything (V2X) resource trading based on combinatorial double auction, which specifically includes the following steps:

[0071] S1. Construct a V2X resource trading incentive system composed of a vehicle trust value blockchain (VBC), a local assisted roadside unit (L-RSU), a resource agent, a resource provider, and a driver user, and obtain information such as auction request bidding packages and reputation values of all participants in the resource auction.

[0072] Specifically, step S1 of obtaining information such as auction request bidding packages and reputation values of all participants in the resource auction includes:

[0073] S11. In the contract initialization stage, create data and parameters related to the smart contract, such as a set B of auction bid packages storing the quantity and price of auctioned resources, a set storing participant serial numbers, etc., and adjust the contract state parameter state to 1 to indicate that the trading state has been activated and trading can be carried out;

[0074] S12. In the trading preparation stage, obtain relevant information of all participants in the resource auction from the VBC, including the auction request bidding package B j of trading participant j, the node reputation value PR j and the node activity sleepy; to ensure that the system is not damaged by malicious nodes and to ensure the normal operation of the system during the auction process, filter out nodes with a reputation threshold lower than 0.4 and nodes with a sleepy parameter of 2 (extremely inactive), and check whether the contract state parameter state is 1; finally, obtain relevant information of the screened participants, including the auction request bidding package B j of trading participant j, the reputation value PR j .

[0075] S2. The trading participant submits an auction request bidding package to the L-RSU responsible for resource trading in the VBC area during this time period.

[0076] Specifically, trading participant j submits an auction request bidding package to the auction control center L-RSU, including:

[0077] S21. Trading participant j submits an auction request bidding package B j = (b j , uj ), where b j = (b 1j ,..., b ij ,..., b nj ), b ij represents the quantity of the i-th type of resource in the bidding package B j submitted by the trading participant j, u j = (u 1j ,..., u ij ,..., u nj ), u ij represents the bid price of the trading participant j for the i-th type of resource, where i ∈ {1,..., n}, j ∈ {1,..., m}, n is the number of resource types, and m is the total number of trading participants;

[0078] S22. The contract collects the bidding information, checks whether the participant serial number and the bidding package exist in the participant set and the bidding package set. If not, add them to the corresponding sets, and check whether the transaction status parameter state is 1.

[0079] S3. The L-RSU calculates the winning resource providers and driver users in the auction based on the bidding packages submitted by all trading participants.

[0080] Specifically, in the vehicle-to-everything (V2X) resource trading market, there are multiple trading participants. The process of determining the auction winner is as follows:

[0081] S31. The bidding package B j = (b j , u j ) of the trading participant j. When the trading participant j is a DU, b ij > 0, u ij > 0. When the trading participant j is an RP, b ij < 0, u ij < 0;

[0082] S32. The winning result X = (x1,..., x n ) of the combinatorial double auction is obtained through the double auction model based on the unit price. The double auction model is as follows:

[0083]

[0084] Among them, the objective function realizes the maximization of market profit, and the constraint condition ensures the smooth completion of the transaction, that is, the resource supply can meet the resource demand. x j = 1 indicates a successful bid, and x j = 0 indicates a failed bid;

[0085] Through the above double auction model based on unit price, the DU and RP that win the auction are obtained.

[0086] S4. Determine the transaction order between the two parties.

[0087] Specifically, suppose there are j∈{1,...,m} transaction participants, and the DU sequence number set is M p , the number of DUs is m p =|M p |; The RP sequence number set is set to M s , the number of RPs is m s =|M s The steps to determine the transaction sequence between the two parties are as follows:

[0088] S41. According to the current RP bid, according to the formula Calculate the current market reference price for resource type i by participant j

[0089] S42. According to the formula Calculate the price competitiveness evaluation parameter vs of transaction participant j for resource i of type RP ij , according to the formula Calculate the normalized score of the price competitiveness evaluation parameter Similarly, according to the formula Calculate the price competitiveness evaluation parameter vp of transaction participant j for resource i of type DU ij , according to the formula Calculate the normalized score of the price competitiveness evaluation parameter

[0090] S43. According to the formula Calculate the comprehensive competitiveness score of transaction participant j for resource type i, where χ is the price weight, 1-χ is the trust weight, and 0≤χ≤1;

[0091] S44. Score the comprehensive competitiveness of the transaction participants of type RP as R ij Arrange in descending order and store the RP numbers in the list sl in this order i And store the available quantity of the i-th type of resources in the auction request bidding package submitted by all RPs in the list accordingly to obtain the list sal i ; Arrange the price evaluation parameters of the trading participants of type DU in descending order, and store the DU numbers in the list pl in this order i And store the number of requests for the i-th type of resources in the auction request packages submitted by all DUs in the list accordingly to obtain the list pal i ;

[0092] S45. Calculate the RP ratio parameter θ according to the formula θ p = 1 - θ s and calculate the transaction unit price matrix of the i-th type of resource according to the formula s , where, according to the formula calculate the transaction unit price matrix of the i-th type of resource, where Tu i (p, s) represents the price when the DU ranked p in the pl i list trades the i-th type of resource with the RP ranked s in the sl i list, represents the average reputation of the overall DUs for the i-th type of resource, represents the sl i list, and the reputation value of the RP ranked s in it.

[0093] In one embodiment, it should be noted that when the bid of the DU is higher than that of the RP, the higher the average reputation of the overall DUs , the closer θ s is to 1, and the closer Tu i (p, s) is to , that is, the transaction price will be lower, which will improve the utility of high-reputation DUs. On the contrary, the reputation ratio will make the transaction price higher, which will improve the utility of high-reputation RPs. Correspondingly, when the bid of the RP is higher than that of the DU, the higher the reputation value of the RP ranked s , the closer θ s is to 1, and the closer Tu i (p, s) is to , that is, the transaction price will be higher, which will improve the utility of high-reputation RPs. On the contrary, the reputation ratio will make the transaction price lower, which will improve the utility of high-reputation DUs.

[0094] S5. The two parties perform resource allocation and pricing.

[0095] Specifically, let RA i and PA i store the transaction allocation result matrix and the transaction price result matrix of the i-th type of resource respectively. The resource allocation and pricing process is as follows:

[0096] S51. Initialize the parameters, i = 1, p = 1, s = 1;

[0097] S52. Process the resource i requests in sequence according to the order in the pal i list. When there are unprocessed requests, go to step S53; otherwise, go to step S54;

[0098] S53. When pal i (p) ≤ -sal i (s), go to step S56; otherwise, go to step S57;

[0099] S54. Check pal i Check whether all requests for the i-th type of resource in the list are satisfied. If all requests for the i-th type of resource are satisfied, go to step S55; otherwise, after performing the operation p = p + 1, go to step S52;

[0100] S55. Check whether all types of service resources are satisfied. If all service resources are satisfied, the execution is completed and exit. Otherwise, after performing the operations i = i + 1, p = 1, and s = 1, go to step S52;

[0101] S56. Perform the following operations:

[0102] RA i (p, s) = RA i (p, s) + pal i (p);

[0103] PA i (p, s) = PA i (p, s) + pal i (p) · Tu i (p, s);

[0104] sal i (s) = sal i (s) + pal i (p);

[0105] pal i (p) = 0;

[0106] After performing the above operations, go to step S54;

[0107] S57. Perform the following operations:

[0108] RA i (p, s) = RA i (p, s) - sal i (s);

[0109] PA i (p, s) = PA i (p, s) - sal i (s) · Tu i (p, s);

[0110] pal i (p) = pal i (p) + sal i (s);

[0111] sal i (s) = 0;

[0112] s=s+1;

[0113] After completing the above operations, proceed to step S52;

[0114] S58. Obtain the remaining funds and resources of the participants after the auction, and adjust the transaction contract state parameter state to 0;

[0115] In step S56, the prerequisite is pal i (p)≤-sal i (s), represents the list pl i The number of resources of category i in DU ranked p is less than or equal to the list sl i The number of resources of type i of RP ranked s in the RA, at which point the resource provider can satisfy the request of the resource requester; i (p,s) and PA i (p,s) represent the list pl i The pth DU and list sl i The transaction quantity and transaction price of the s-th RP for the i-th type of resources, where sal i (s)=sal i (s)+pal i (p) indicates the remaining amount of resources after the resource provider has provided resources to the requester; pal i (p)=0 indicates that the request of the DU ranked p for the i-type resource has been satisfied.

[0116] In step S57, the prerequisite is pal i (p)>-sal i (s), represents the list pl i The number of resources of category i in DU ranked p is greater than that in list sl i The number of type i resources of the RP ranked s in the RP. At this time, the resource provider cannot meet the request of the requester, and the number of resources that can be provided is sal i (s);pal i (p) = pal i (p)+sal i (s) represents the list pl i The new demand for DU ranked p after the completion of this transaction; i (s)=0 indicates that the resource provider has provided all resources to the requester; after executing s=s+1, the process goes to step S52, indicating that the transaction between the pth DU and the s+1th RP begins.

[0117] In step S5, the resource i is classified and the DU sorting list pl is sorted.i allocate and price resources in the order, and the RP satisfies the DU demands in the order of sl i . Note that only when the demands of all DUs in the list pl storing resource i are satisfied, will the RP group allocate and price for the next resource, that is, perform the resource allocation for the next pl i , until all resource demands of the DU group are satisfied. i

[0118] S6. Evaluate the auction results.

[0119] Specifically, to evaluate auction results such as social surplus, the steps are as follows:

[0120] S61. Enter the contract end stage, receive the confirmation closing information sent by the trading participants after the transaction is completed. When the return value of the confirmation closing information is 1 and the transaction contract status parameter state is also 0, the contract ends;

[0121] S62. After all transactions are completed, calculate the total income or expenditure costs of both parties to the transaction according to the formula respectively. And For the auction winner, calculate its utility according to the formula , calculate the average utility according to the formula , where b j ′ is the number of resources for which the transaction is completed in the case of transaction surplus;

[0122] S63. Calculate the social surplus SP according to the formula , which represents the total sum of the total benefits jointly obtained by both parties to the transaction in the trading system.

[0123] In the embodiment of the present invention, a combined two-way auction algorithm CICDA based on a vehicle trust mechanism is designed. Aiming at the scalability bottleneck problem in the blockchain IoV deployment, an incentive mechanism is innovatively deployed in an adaptive smart contract architecture. The smart contract designed in the solution is shown in Table 1, which includes storing the set of participant serial numbers ParList, the set of auction winner serial numbers WinnersList, the set of changes in transaction amounts totalBalance, the set of changes in transaction quantities totalAmount, each participant Par j , the remaining funds balance + totalBalance j , the remaining resource quantity amount + totalAmount j , the confirmation closing message Closure j . In the embodiment of the present invention, the algorithm CICDA is deployed on a smart contract platform, and the transaction process flow chart is as Figure 3 shown.

[0124] Table 1 Smart Contract

[0125]

[0126]

[0127] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art will appreciate that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A vehicle networking resource trading incentive method based on combinatorial double auction, characterized in that It includes the following steps: S1. Construct an incentive system for vehicle network resource trading composed of a vehicle trust value blockchain VBC, a local auxiliary roadside unit L-RSU, a resource broker, a resource provider, and a driver user, and obtain information such as auction request bidding packages and reputation values of all participants in the resource auction; S2. The trading participants submit the auction request bidding packages to the L-RSU responsible for resource trading within the VBC area during this time period; S3. The L-RSU calculates the winning resource providers and driver users in the auction based on the bidding packages submitted by all trading participants; S4. Determine the trading order of both parties; S5. Both parties conduct resource allocation and pricing; S6. Evaluate the auction results; Among them, the vehicle trust value blockchain VBC is used as the underlying blockchain to record the local vehicle information in the current blockchain; The local auxiliary roadside unit L-RSU is responsible for collecting information related to reputation value evaluation, calculating the current reputation value of local vehicle nodes, and regularly updating the global reputation value of drivers; the driver user DU is the initiator who needs to request resource services in the system, that is, the "buyer" in the auction system; the resource provider RP is the resource provider in the system, that is, the "seller" in the auction system. The RP itself has a competitiveness attribute, which is affected by two factors: the bid price and the reputation value. If some RPs also need resource services, these RPs may also be converted into DUs.

2. The incentive method for vehicle - to - everything (V2X) resource trading based on combinatorial double - auction according to claim 1, characterized in that, Step S1 obtains information such as auction request bidding packages and reputation values of all participants in the resource auction, including: S11. In the contract initialization stage, create data and parameters related to the smart contract, such as the bidding package set B that stores the quantity and price of the auctioned resources, the set that stores the participant numbers, etc., and adjust the contract status parameter state to 1 to indicate that the trading status has been activated and trading can be carried out; S12. In the transaction preparation stage, obtain and process the relevant information of all participants in the resource auction from the VBC, including the auction request bidding package B of transaction participant j j , credit value PR j and node activity sleepy.

3. A method for incentivizing vehicle - to - everything (V2X) resource trading based on combinatorial double - auction according to claim 1, characterized in that, The trading participant j submits a bidding package to the auction control center L-RSU, including: S21. Trading participant j submits an auction request bidding package B to the L-RSU responsible for resource trading in the VBC area during this time period j =(b j , u j ), where b j =(b 1j ,..., b ij ,..., b nj ), b ij represents the quantity of the i-th type of resource in the bidding package submitted by trading participant j, u j =(u 1j ,..., u ij ,..., u nj ), u ij represents the bid price of trading participant j for the i-th type of resource, where i ∈ {1,..., n}, j ∈ {1,..., m}, n is the total number of resource types, and m is the total number of trading participants; S22. The contract collects bidding information, checks whether all participant numbers and bidding packages exist in the participant set and the bidding package set. If not, add them to the corresponding sets, and check whether the trading status parameter state is 1.

4. A vehicle networking resource trading incentive method based on combined double auction according to claim 1, characterized in that, In the vehicle network resource trading market, there are multiple trading participants. The process of determining the auction winner is as follows: The bidding package B of trading participant j j =(b j , u j ), when trading participant j is DU, b ij >0, u ij >0, when trading participant j is RP, b ij <0, u ij <0; S32. Through a two-way auction model based on unit price, obtain the winning DUs and RPs in the auction.

5. A vehicle networking resource trading incentive method based on combined double auction according to claim 1, characterized in that The steps for step S4 to determine the trading order of both parties are as follows: S41. Calculate the current market reference price of the i-th type of resource for trading participant j according to the bid of the current RP S42. Calculate the price competitiveness evaluation parameter vs of the transaction participant j of type RP for the i-th type of resource ij and the normalized score of the price competitiveness evaluation parameter; Similarly, calculate the price competitiveness evaluation parameter vp of the transaction participant j of type DU for the i-th type of resource ij and the normalized score of the price competitiveness evaluation parameter S43. Calculate the comprehensive competitiveness score R of transaction participant j of calculation type RP for the i-th type of resource ij ; S44. Sort the comprehensive competitiveness scores R of transaction participants of type RP ij in descending order, and store the numbers of RPs in the list sl in this order i , and store the available quantities of the i-th type of resources in the auction request bidding packages submitted by all RPs in the list accordingly to obtain the list sal i ; Sort the price evaluation parameters of transaction participants of type DU in descending order, and store the numbers of DUs in the list pl in this order i , and store the requested quantities of the i-th type of resources in the auction request bidding packages submitted by all DUs in the list accordingly to obtain the list pal i ; S45. Calculate the RP ratio parameter θ s , according to the formula Calculate the transaction unit price matrix of resources, where Tu i (p, s) represents the DU ranked p in the pl i list and the RP ranked s in the sl i list when trading the i-th type of resource, and θ p = 1 - θ s .

6. The incentive method for vehicle networking resource trading based on combined double auction according to claim 1, wherein it is assumed that RA i and PA i respectively store the transaction allocation result matrix and the transaction price result matrix of the i-th type of resource. The resource allocation and pricing processes are as follows: S51. Initialize the parameters, i = 1, p = 1, s = 1; S52. Process the resource i requests in the order in the pal i List. When there are unprocessed requests, go to step S53; otherwise, go to step S54. S53. When pal i (p) ≤ -sal i (s), proceed to step S56; otherwise, proceed to step S57; S54. Check pal i Check whether all requests for resources of type i in the list are satisfied. If all requests for resources of type i are satisfied, proceed to step S55; otherwise, after performing the operation p = p + 1, proceed to step S52. S55. Check whether all types of service resources are satisfied. If all service resources are satisfied, the execution is completed and exited; otherwise, after performing the operations i = i + 1, p = 1, s = 1, enter step S52; S56. Perform the following operations: RA i (p, s) = RA i (p, s) + pal i (p); PA i (p, s) = PA i (p, s) + pal i (p)·Tu i (p, s); sal i (s) = sal i (s) + pal i (p); pal i (p) = 0; After performing the above operations, enter step S54; S57. Perform the following operations: RA i (p, s) = RA i (p, s) - sal i (s); PA i (p, s) = PA i (p, s) - sal i (s)·Tu i (p, s); pal i (p) = pal i (p) + sal i (s); sal i (s) = 0; s = s + 1; After performing the above operations, enter step S52; S58. Obtain the remaining funds and remaining resources of the trading participants after the auction, and adjust the trading contract status parameter state to 0.

7. A method for incentivizing vehicle - to - everything (V2X) resource trading based on combinatorial double - auction according to claim 1, characterized in that, To evaluate auction results such as social surplus, the steps are as follows: S61. Enter the contract end stage, receive the confirmation closing information sent by the trading participant after the transaction is completed. When the return value of the confirmation closing information is 1 and the trading contract status parameter state is also 0, the contract ends. S62. After all transactions are completed, calculate the total income and expenditure costs of both parties to the transaction and For the auction winner j, calculate its utility U j and the average utility AU j ; S63. Obtain the social surplus SP by adding the utilities of the two types of trading participants, DU and RP, which represents the total sum of the total benefits jointly obtained by both parties in the trading system.

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