Vehicle parking credit authentication method, device, computer equipment and storage medium

Abstract

The present application relates to a vehicle parking credit authentication method, which includes: when a vehicle enters a parking lot, the vehicle credit rating is queried based on the vehicle identity information, and if the vehicle credit rating meets a first preset condition, the vehicle enters a first state; the vehicle credit rating is obtained based on the vehicle's historical parking data; the vehicle's historical parking data includes dishonest behavior data. The present application can achieve better supervision of vehicle parking by storing and querying the dishonest behavior of the vehicle, and calculating the credit rating based on the dishonest behavior; at the same time, setting access conditions for vehicle parking can reduce the dishonest behavior of the vehicle or prompt the user to correct his dishonest behavior. In addition, a vehicle parking credit authentication device, computer equipment and storage medium are also proposed.

Description

Technical Field

[0001] The present invention belongs to the field of blockchain technology, and in particular relates to a vehicle parking credit authentication method, device, computer equipment and storage medium. Background Art

[0002] Most of the existing parking fee charging methods are to identify the vehicle's identity information based on the license plate when entering the parking lot, and then charge the vehicle based on the parking time calculated based on the vehicle's identity information when the vehicle is about to leave the parking lot. After the charging is completed, the vehicle is released to leave.

[0003] The existing parking lot charging method does not verify the vehicle information when the vehicle enters the parking lot, so it is not possible to provide advance reminders, key supervision or other control measures on the parking lot side for vehicles with frequent evasion of fees and other vehicle dishonesty problems; in addition, when the vehicle leaves the parking lot, the vehicle can also evade fees by following other vehicles, and the existing charging method does not supervise the vehicle evasion. In addition, there are many charging systems in existing parking lots, which cannot record the evasion behavior well and it is not easy to share data between different parking lots, so the existing parking scene charging method cannot solve the problem of vehicle dishonesty such as evasion of fees. Summary of the invention

[0004] Based on this, it is necessary to provide a vehicle parking credit authentication method, device, computer equipment and storage medium for recording and statistically analyzing vehicle dishonest behaviors to address the above problems.

[0005] In a first aspect, an embodiment of the present invention provides a vehicle parking credit authentication method, the method comprising:

[0006] When a vehicle enters a parking lot, the vehicle credit rating is queried based on the vehicle identity information. If the vehicle credit rating meets a first preset condition, the vehicle enters a first state;

[0007] The vehicle credit rating is obtained based on the vehicle's historical parking data; the vehicle's historical parking data includes dishonest behavior data.

[0008] In one embodiment, the method further comprises the following steps:

[0009] After the vehicle enters the first state, whether there is any non-exit information is queried based on the vehicle identity information. If there is any non-exit information, it is determined whether the non-exit information constitutes a dishonest behavior. If the non-exit information constitutes a dishonest behavior, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating. The first state means that the vehicle meets the conditions for entering the parking lot.

[0010] In one of the embodiments, the method further includes a step of monitoring dishonest behavior: if dishonest behavior occurs during the time period from vehicle entry to vehicle exit, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating.

[0011] In one embodiment, the vehicle identity information includes a vehicle license plate number or a vehicle driver; the vehicle license plate number is identified based on image processing technology; and the vehicle driver is identified based on artificial intelligence technology.

[0012] In one embodiment, the vehicle identity information, vehicle credit rating and dishonest behavior are uploaded, queried and analyzed based on blockchain technology.

[0013] In one embodiment, each node of the blockchain includes unique identification information and public and private keys.

[0014] In one of the embodiments, the step of monitoring dishonest behavior is based on artificial intelligence technology for identification.

[0015] In a second aspect, an embodiment of the present invention provides a vehicle parking credit authentication device, the device comprising: a vehicle identity information collection module, a vehicle credit rating calculation module, a vehicle dishonest behavior collection module, and a vehicle parking credit query module;

[0016] The vehicle dishonest behavior collection module is used to collect the dishonest behavior of the vehicle;

[0017] The vehicle identity information collection module is used to collect vehicle identity information;

[0018] The vehicle credit rating calculation module is used to calculate the vehicle credit rating based on the vehicle's historical parking data; the vehicle's historical parking data includes the vehicle's dishonest behavior;

[0019] The vehicle parking credit query module is used to query the vehicle credit level according to the vehicle identity information when entering the parking lot. If the vehicle credit level meets the first preset condition, the vehicle enters the first state.

[0020] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the following steps:

[0021] When a vehicle enters a parking lot, the vehicle credit rating is queried based on the vehicle identity information. If the vehicle credit rating meets a first preset condition, the vehicle enters a first state;

[0022] The vehicle credit rating is obtained based on historical parking data of the vehicle.

[0023] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the following steps:

[0024] When a vehicle enters a parking lot, the vehicle credit rating is queried based on the vehicle identity information. If the vehicle credit rating meets a first preset condition, the vehicle enters a first state;

[0025] The vehicle credit rating is obtained based on historical parking data of the vehicle.

[0026] The above-mentioned method, device, computer equipment and storage medium can achieve better supervision of vehicle parking by storing and querying the vehicle's dishonest behavior and calculating the credit level based on the dishonest behavior; at the same time, setting access conditions for vehicle parking can reduce the vehicle's dishonest behavior or encourage users to correct their dishonest behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0028] Figure 1 A flowchart of a vehicle parking credit authentication method in one embodiment;

[0029] Figure 2 is a structural block diagram of a vehicle parking credit authentication device in one embodiment;

[0030] Figure 3 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0032] like Figure 1 As shown, a vehicle parking credit authentication method is proposed, which specifically includes the following steps:

[0033] Step 101, when a vehicle enters a parking lot, the vehicle credit rating is queried according to the vehicle identity information. If the vehicle credit rating meets a first preset condition, the vehicle enters a first state;

[0034] The vehicle credit rating is obtained based on the vehicle's historical parking data; the vehicle's historical parking data includes dishonest behavior data.

[0035] Among them, the vehicle identity information includes information such as the vehicle license plate number or the information of the vehicle driver; if the shared car is a vehicle of a type with unfixed users, it is inaccurate if the vehicle identity information is queried using the vehicle license plate number. Therefore, for this type of vehicle, the vehicle driver's information can be used as the vehicle identity information. The vehicle credit rating is obtained based on the vehicle's historical parking data, and the vehicle's historical parking data includes dishonest behavior; the vehicle credit rating can be calculated based on the frequency of the vehicle's dishonest behavior and whether the dishonest behavior has been corrected. Common dishonest behaviors include vehicle evasion. Taking vehicle evasion as an example, the vehicle credit rating can be established based on the frequency of the vehicle's evasion and the supplementary payment or recovery behavior. If the vehicle's evasion behavior has been corrected and the corresponding supplementary payment or recovery has been made, the evasion behavior may not affect the vehicle's credit rating or reduce the weight of the impact of the evasion behavior on the vehicle's credit rating. For example, the credit rating of a vehicle is based on a percentage system. If a parking of a vehicle does not cause a dishonest behavior, the parking data of this parking is legal parking data; if the dishonest behavior has been corrected, the parking data of this parking is legally corrected parking data; the parking data of the dishonest behavior that has not been corrected is recorded as dishonest parking data; the credit rating of the vehicle is added or subtracted according to the legal parking data of the vehicle, the legally corrected parking data, and the frequency of dishonest parking data. For example, legal parking data can add points to the credit rating; legally corrected parking data can add points to the credit rating with a weight lower than the weight of legal parking data, or its weight is zero and does not affect the credit rating, or the absolute value is less than the absolute value of the weight of dishonest parking data. Dishonest parking data causes the credit rating to be subtracted. The first preset condition refers to that the vehicle credit rating is greater than the preset threshold, and the first state refers to that the vehicle meets the conditions for entering the parking lot, and the vehicle can enter the parking lot. Vehicles whose credit ratings do not meet the first preset condition cannot enter the parking lot, and can be reminded to correct the dishonest behavior to improve their credit rating, or allowed to enter the parking lot, but their parking this time is subject to special supervision to avoid new dishonest behavior.

[0036] The vehicle parking credit authentication method described in this embodiment determines the vehicle credit rating calculated based on the vehicle's historical parking data before entering the parking lot, and allows vehicles that meet the credit rating requirements to enter the parking lot. By storing and querying the vehicle's dishonest behavior and calculating the credit rating based on the dishonest behavior, better supervision of vehicle parking can be achieved; at the same time, setting access conditions for vehicle parking can reduce the vehicle's dishonest behavior or encourage users to correct their dishonest behavior.

[0037] In one embodiment, the method further comprises the following steps:

[0038] Step 102, after the vehicle enters the first state, it is inquired whether there is any non-exit information based on the vehicle identity information. If there is non-exit information, it is determined whether the non-exit information is a dishonest behavior: if the non-exit information is a dishonest behavior, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating; the first state means that the vehicle meets the conditions for entering the parking lot.

[0039] In this embodiment, if the vehicle credit rating meets the first preset condition, the vehicle is controlled and allowed to enter the parking lot. At this time, if the vehicle has not exited the parking lot, the information of not exiting the parking lot is judged to identify whether the information of not exiting the parking lot is a dishonest behavior such as evading fees, so as to handle the situation of not exiting the parking lot and update the historical parking data of the vehicle and the credit rating of the vehicle. For example, the situation of the parking lot of the not exiting the parking lot can be queried. If the parking lot has not updated the information in time due to information collection and updating, so that the not exiting information exists, it is judged that the not exiting the parking lot does not belong to a dishonest situation such as evading fees, and the not exiting information is updated; if the not exiting the parking lot is judged to belong to a dishonest behavior, the dishonest behavior is uploaded to update the historical parking data of the vehicle and the credit rating of the vehicle.

[0040] In one embodiment, the method further includes a dishonest behavior monitoring step:

[0041] Step 103, if any dishonest behavior occurs during the period from vehicle entry to vehicle exit, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating.

[0042] The dishonest behaviors include, but are not limited to, evading fees and irregular parking. For example, irregular parking includes not parking in a designated area (such as parking in a fire lane) or not parking within a designated parking space (such as occupying multiple parking spaces). For the above dishonest situations, after identifying and judging the specific dishonest behaviors, the dishonest behavior data will be uploaded to update the vehicle's historical parking data and vehicle credit rating.

[0043] In one embodiment, the vehicle identity information includes a vehicle license plate number or a vehicle driver; the vehicle license plate number is identified based on image processing technology; and the vehicle driver is identified based on artificial intelligence technology.

[0044] The vehicle identity information includes information such as the vehicle license plate number or the information of the vehicle driver; if the vehicle identity information is queried using the vehicle license plate number for a shared car, which is a type of vehicle with a non-fixed user, it will be inaccurate. Therefore, for this type of vehicle, the vehicle driver's information can be used as the vehicle identity information. For example, information can be interacted with the shared car usage platform to obtain the driver information of the shared car with the current license plate number. The identification of the vehicle identity information can be done manually or by other means, but the degree of automation is low and the efficiency is not high. Therefore, the license plate number can be identified by image recognition or by artificial intelligence technologies such as face recognition.

[0045] In one embodiment, the vehicle identity information, vehicle credit rating and dishonest behavior are uploaded, queried and analyzed based on blockchain technology.

[0046] The data upload, query and analysis based on blockchain technology includes the following steps:

[0047] Data upload:

[0048] The blockchain includes a collection node and an authentication node; the collection node collects vehicle identity information and vehicle historical parking data, and publishes and uploads the data based on the blockchain; wherein the vehicle historical parking data includes dishonest behavior data, such as vehicle evasion and supplementary payment or recovery records.

[0049] The authentication node performs statistical analysis based on the vehicle identity information uploaded by the collection node and the vehicle historical parking data, obtains the credit level corresponding to each vehicle identity information, and publishes and uploads the credit level based on the blockchain.

[0050] Data query:

[0051] The acquisition node queries the credit rating uploaded by the authentication node corresponding to the vehicle identity based on the blockchain. Among them, the vehicle parking credit query module can perform corresponding control based on the credit rating queried by the acquisition node.

[0052] Data Analysis:

[0053] The authentication node performs statistical analysis on the vehicle identity information and vehicle historical parking data uploaded by the download collection node based on the blockchain.

[0054] In this embodiment, a decentralized vehicle parking credit authentication is established by using blockchain, and the vehicle identity information and the vehicle historical parking data are distributedly stored. The credit score of each vehicle identity information on the chain is obtained through the authentication node, and the credit rating is also stored on the chain. When the vehicle historical parking data is updated, the credit rating is updated in real time. Blockchain is a decentralized database that contains a list called blocks, which has continuously growing and neatly arranged records. Each block contains a timestamp and a link to the previous block: the blockchain is designed so that the data cannot be tampered with - once recorded, the data in a block will be irreversible. Blockchain technology is a new distributed infrastructure and computing that uses block chain data structures to verify and store data, uses distributed node consensus algorithms to generate and update data, uses cryptography to ensure the security of data transmission and access, and uses smart contracts composed of automated script codes to program and operate data. Using the method described in this embodiment, different parking lots can query related records and credit ratings based on vehicle identity information and conduct corresponding supervision.

[0055] In one embodiment, each node of the blockchain includes unique identification information and public and private keys. Each node has its own public key and private key, and can only query data within its authority, which is convenient for information protection. The blockchain provides permission control information query. Each node can only query its own uploaded information without authorization. For information not uploaded by itself, corresponding authorization is required before querying.

[0056] In one embodiment, the step of monitoring dishonest behavior is identified based on artificial intelligence technology. This embodiment uses license plate recognition and other methods such as neural networks to identify whether a vehicle has dishonest behaviors such as following a vehicle to evade fees, and uses image recognition and other technologies to identify whether a vehicle has dishonest behaviors such as not parking in a designated area or not parking within a designated parking space. Compared with manual identification, monitoring and identifying dishonest behaviors based on artificial intelligence technology can improve efficiency.

[0057] like Figure 2 As shown, an embodiment of the present invention provides a vehicle parking credit authentication device, the device comprising: a vehicle identity information collection module 201, a vehicle credit rating calculation module 203, a vehicle dishonest behavior collection module 204 and a vehicle parking credit query module 202;

[0058] The vehicle dishonest behavior collection module 204 is used to collect dishonest behaviors of vehicles;

[0059] The vehicle identity information collection module 201 is used to collect vehicle identity information;

[0060] The vehicle credit rating calculation module 203 is used to calculate the vehicle credit rating based on the vehicle's historical parking data; the vehicle's historical parking data includes the vehicle's dishonest behavior;

[0061] The vehicle parking credit query module 202 is used to query the vehicle credit level according to the vehicle identity information when entering the parking lot. If the vehicle credit level meets the first preset condition, the vehicle enters the first state.

[0062] In one embodiment, the vehicle parking credit query module 202 is further used to implement the following steps:

[0063] After the vehicle enters the first state, whether there is any non-exit information is queried based on the vehicle identity information. If there is any non-exit information, it is determined whether the non-exit information constitutes a dishonest behavior. If the non-exit information constitutes a dishonest behavior, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating. The first state means that the vehicle meets the conditions for entering the parking lot.

[0064] In one embodiment, a dishonest behavior monitoring module 205 is also included, which is used to upload the dishonest behavior to update the vehicle's historical parking data and vehicle credit rating if a dishonest behavior occurs during the period from vehicle entry to vehicle exit.

[0065] In one embodiment, the vehicle identity information includes a vehicle license plate number or a vehicle driver; the vehicle license plate number is identified based on image processing technology; and the vehicle driver is identified based on artificial intelligence technology.

[0066] In one embodiment, the vehicle identity information, vehicle credit rating and dishonest behavior are uploaded, queried and analyzed based on blockchain technology.

[0067] In one embodiment, each node of the blockchain includes unique identification information and public and private keys.

[0068] In one embodiment, the step of monitoring dishonest behavior is based on artificial intelligence technology for identification.

[0069] Figure 3 FIG. 1 shows an internal structure diagram of a computer device in an embodiment. The computer device may be a terminal. Figure 3As shown, the computer device includes a processor, a memory and a network interface connected via a system bus. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor may implement a vehicle parking credit authentication method. The internal memory may also store a computer program. When the computer program is executed by the processor, the processor may implement a vehicle parking credit authentication method. The network interface is used to communicate with the outside world. Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0070] In one embodiment, the vehicle parking credit authentication provided by the present application can be implemented in the form of a computer program, which can be used in Figure 3 The computer device shown in the figure is run. The memory of the computer device can store various program templates that constitute the vehicle parking credit authentication device. For example, a vehicle identity information collection module, a vehicle credit rating calculation module, a vehicle dishonest behavior collection module, and a vehicle parking credit query module.

[0071] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the following steps:

[0072] When a vehicle enters a parking lot, the vehicle credit rating is queried based on the vehicle identity information. If the vehicle credit rating meets a first preset condition, the vehicle enters a first state;

[0073] The vehicle credit rating is obtained based on the vehicle's historical parking data; the vehicle's historical parking data includes dishonest behavior data.

[0074] In one embodiment, the processor further performs the following steps:

[0075] After the vehicle enters the first state, whether there is any non-exit information is queried based on the vehicle identity information. If there is any non-exit information, it is determined whether the non-exit information constitutes a dishonest behavior. If the non-exit information constitutes a dishonest behavior, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating. The first state means that the vehicle meets the conditions for entering the parking lot.

[0076] In one embodiment, the processor further executes a dishonest behavior monitoring step: if dishonest behavior occurs during the time period from vehicle entry to vehicle exit, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating.

[0077] In one embodiment, the vehicle identity information includes a vehicle license plate number or a vehicle driver; the vehicle license plate number is identified based on image processing technology; and the vehicle driver is identified based on artificial intelligence technology.

[0078] In one embodiment, the vehicle identity information, vehicle credit rating and dishonest behavior are uploaded, queried and analyzed based on blockchain technology.

[0079] In one embodiment, each node of the blockchain includes unique identification information and public and private keys.

[0080] In one embodiment, the step of monitoring dishonest behavior is based on artificial intelligence technology for identification.

[0081] A computer-readable storage medium stores a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0082] When a vehicle enters a parking lot, the vehicle credit rating is queried based on the vehicle identity information. If the vehicle credit rating meets a first preset condition, the vehicle enters a first state;

[0083] The vehicle credit rating is obtained based on the vehicle's historical parking data; the vehicle's historical parking data includes dishonest behavior data.

[0084] In one embodiment, the processor further performs the following steps:

[0085] After the vehicle enters the first state, whether there is any non-exit information is queried based on the vehicle identity information. If there is any non-exit information, it is determined whether the non-exit information constitutes a dishonest behavior. If the non-exit information constitutes a dishonest behavior, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating. The first state means that the vehicle meets the conditions for entering the parking lot.

[0086] In one embodiment, the processor further executes a dishonest behavior monitoring step: if dishonest behavior occurs during the time period from vehicle entry to vehicle exit, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating.

[0087] In one embodiment, the vehicle identity information includes a vehicle license plate number or a vehicle driver; the vehicle license plate number is identified based on image processing technology; and the vehicle driver is identified based on artificial intelligence technology.

[0088] In one embodiment, the vehicle identity information, vehicle credit rating and dishonest behavior are uploaded, queried and analyzed based on blockchain technology.

[0089] In one embodiment, each node of the blockchain includes unique identification information and public and private keys.

[0090] In one embodiment, the step of monitoring dishonest behavior is based on artificial intelligence technology for identification.

[0091] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0092] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0093] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle parking credit authentication method, characterized in that: The method comprises: When a vehicle enters a parking lot, the vehicle credit rating is queried based on the vehicle identity information. If the vehicle credit rating meets a first preset condition, the vehicle enters a first state. If the vehicle is a shared car, information is interacted with the shared car user platform to obtain the driver information of the shared car with the current license plate number as the vehicle identity information. The vehicle credit rating is obtained based on the vehicle's historical parking data; the vehicle's historical parking data includes dishonest behavior data; the vehicle credit rating is calculated based on the frequency of the vehicle's dishonest behavior and whether the dishonest behavior has been corrected, wherein if the dishonest behavior has been corrected, the weight of the impact of this dishonest behavior on the vehicle credit rating is reduced; The method further includes: after the vehicle enters the first state, querying whether there is any non-exit information based on the vehicle identity information; if there is any non-exit information, querying the parking lot of the non-exit information to determine whether the non-exit information is a dishonest behavior; if the non-exit information is a dishonest behavior, uploading the dishonest behavior to update the vehicle's historical parking data and the vehicle's credit rating; the first state means that the vehicle meets the conditions for entering the parking lot; The vehicle identity information, vehicle credit rating and dishonest behavior are uploaded, queried and analyzed based on blockchain technology, including: The collection node collects vehicle identity information and vehicle historical parking data, and publishes and uploads the vehicle identity information and vehicle historical parking data based on the blockchain; the authentication node performs statistical analysis based on the vehicle identity information and vehicle historical parking data uploaded by the collection node, obtains the credit level corresponding to each vehicle identity information, and publishes and uploads the credit level based on the blockchain; wherein the blockchain includes a collection node and an authentication node; The collection node queries the credit rating uploaded by the authentication node corresponding to the vehicle identity based on the blockchain; The authentication node downloads the vehicle identity information and vehicle historical parking data uploaded by the collection node based on the blockchain for statistical analysis.

2. The method according to claim 1, characterized in that It also includes a step of monitoring dishonest behavior: if dishonest behavior occurs during the time period from vehicle entry to vehicle exit, the dishonest behavior is uploaded to update the vehicle's historical parking data and vehicle credit rating.

3. The method according to claim 1, characterized in that The vehicle identity information includes the vehicle license plate number or the vehicle driver; the vehicle license plate number is identified based on image processing technology; the vehicle driver is identified based on artificial intelligence technology.

4. The method according to claim 1, characterized in that: Each node of the blockchain includes unique identification information and public and private keys.

5. The method according to claim 2, characterized in that: The step of monitoring dishonest behavior is based on artificial intelligence technology for identification.

6. A vehicle parking credit authentication device, characterized in that: The device comprises: a vehicle identity information collection module, a vehicle credit rating calculation module, a vehicle dishonest behavior collection module and a vehicle parking credit query module; The vehicle dishonest behavior collection module is used to collect the dishonest behavior of the vehicle; The vehicle identity information collection module is used to collect vehicle identity information; The vehicle credit rating calculation module is used to calculate the vehicle credit rating based on the vehicle's historical parking data; the vehicle's historical parking data includes the vehicle's dishonest behavior; The vehicle parking credit query module is used to query the vehicle credit rating according to the vehicle identity information when entering the parking lot. If the vehicle credit rating meets the first preset condition, the vehicle enters the first state; if the vehicle is a shared car, information is exchanged with the shared car usage platform to obtain the driver information of the shared car with the current license plate number as the vehicle identity information; the vehicle credit rating is calculated according to the frequency of the vehicle's dishonest behavior and whether the dishonest behavior has been corrected. If the dishonest behavior has been corrected, the weight of the impact of this dishonest behavior on the vehicle credit rating is reduced; The vehicle parking credit query module is further used to: after the vehicle enters the first state, query whether there is any non-exit information based on the vehicle identity information; if there is any non-exit information, query the parking lot of the non-exit information to determine whether the non-exit information is a dishonest behavior; if the non-exit information is a dishonest behavior, upload the dishonest behavior to update the vehicle's historical parking data and the vehicle credit level; the first state means that the vehicle meets the conditions for entering the parking lot; Among them, the vehicle identity information, vehicle credit rating and dishonest behavior are uploaded, queried and analyzed based on blockchain technology, including: the collection node collects vehicle identity information and vehicle historical parking data, and publishes and uploads the vehicle identity information and vehicle historical parking data based on the blockchain; the authentication node performs statistical analysis based on the vehicle identity information and vehicle historical parking data uploaded by the collection node, obtains the credit rating corresponding to each vehicle identity information, and publishes and uploads the credit rating based on the blockchain; wherein the blockchain includes a collection node and an authentication node; the collection node queries the credit rating uploaded by the authentication node corresponding to the vehicle identity based on the blockchain; the authentication node downloads the vehicle identity information and vehicle historical parking data uploaded by the collection node based on the blockchain for statistical analysis.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 5.

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