Parking management method and computer program product

Abstract

The present application provides a parking management method and a computer program product, which relate to the field of parking management technology. The method includes: determining the target state data of a target vehicle in a parking lot; generating unique order information based on the target state data; and determining the management data of the target vehicle according to the order information stored in a non-tamperable area. By determining the target state data of the target vehicle in the parking lot, the current actual state of the target vehicle can be determined, so as to generate unique order information according to the target state data of the target vehicle, thereby distinguishing multiple orders between multiple vehicles and multiple orders for the same vehicle. In addition, in order to improve the reliability and traceability of the order information, the order information is stored in the non-tamperable area, so as to obtain the corresponding order information from the non-tamperable area according to the corresponding management requirements to determine the management data for managing the target vehicle, thereby effectively improving the accuracy and efficiency of vehicle management.

Description

Technical Field

[0001] The present application relates to the technical field of parking management, and in particular to a parking management method and a computer program product. Background Art

[0002] In order to alleviate the problem of parking difficulties in cities, at present, roadside parking spaces are usually set up in some scattered areas in the city to facilitate the parking of motor vehicles. For example, roadside parking spaces are set up on the roads in the city to facilitate the parking of motor vehicles. Considering that roadside parking spaces are relatively scattered, if parking management is done manually, it will bring about the problems of low parking management efficiency and high labor costs. Therefore, the existing technology introduces a parking management system to manage roadside parking spaces.

[0003] When managing parking spaces on the road, existing parking management systems usually record the process of a vehicle entering a parking space to determine the time when the vehicle enters the parking space, and record the process of a vehicle exiting a parking space to determine the time when the vehicle exits the parking space. Furthermore, the difference between the time of entering the parking space and the time of exiting the parking space is used to manage the parking situation of the vehicle.

[0004] However, due to the mobility of vehicles, the current parking management system has the problem of incomplete collection of vehicle parking information, resulting in problems such as miscalculation, omission, and wrong calculation of parking fees, which leads to low accuracy of parking management and adversely affects the user's parking experience. Summary of the invention

[0005] In view of this, an object of the embodiments of the present application is to provide a parking management method and a computer program product to improve the problem of low accuracy of parking management in the prior art.

[0006] In order to solve the above problems, in a first aspect, an embodiment of the present application provides a parking management method, the method comprising: determining target state data of a target vehicle in a parking lot;

[0007] Based on the target status data, generating unique order information;

[0008] The management data of the target vehicle is determined based on the order information stored in the tamper-proof area.

[0009] In the above implementation process, by determining the target state data of the target vehicle in the parking lot, the current actual state of the target vehicle can be analyzed and determined, so as to generate unique order information according to the target state data of the target vehicle, thereby distinguishing multiple orders between multiple vehicles and multiple orders of the same vehicle. In addition, considering the integrity and security of the data, in order to improve the reliability and traceability of the order information, the generated multiple order information is stored in a non-tamperable area. In the subsequent management process, the corresponding order information can be obtained from the non-tamperable area according to the corresponding management needs to determine the management data for various management processing of the target vehicle, which effectively improves the accuracy and efficiency of vehicle management, enhances the user's parking experience, is applicable to various types of parking scenarios, and meets a variety of different parking management needs.

[0010] Optionally, determining the management data of the target vehicle according to the order information stored in the non-tamperable area includes: extracting the order information stored in the non-tamperable area based on extraction requirements;

[0011] Determining the management data of the target vehicle according to the order information and preset management rules;

[0012] The management rules include at least one of charging rules, entry and exit rules, guidance rules and reservation rules.

[0013] In the above implementation process, when managing vehicles, the required order information can be extracted from the non-tampering area according to the extraction requirements of the target vehicle, so as to determine the management data for various management processes such as charging, restricting, releasing, guiding, and reserving the target vehicle according to the order information and the preset management rules. The ability to extract the corresponding data from the non-tampering area for management processing effectively reduces the risk of data tampering, improves the reliability, integrity and authenticity of the source of management data, and thus improves the accuracy and efficiency of parking management of vehicles.

[0014] Optionally, extracting the order information stored in the non-tamperable area based on the extraction demand includes: storing the order information in the non-tamperable area; wherein the non-tamperable area includes at least one of a blockchain, an immutable storage area, and a secure encrypted storage area;

[0015] If it is determined that the target vehicle has the extraction requirement, determining a query end of the extraction requirement of the target vehicle;

[0016] Authentication of the query end;

[0017] If the identity authentication of the query end is successful, generating unique key information based on the identity of the query end, and sending the key information to the query end;

[0018] If the key information is valid, the order information is extracted from the non-tamperable area based on the key information and the identity information of the target vehicle sent by the query end.

[0019] In the above implementation process, after obtaining multiple order information corresponding to multiple target vehicles, multiple order information can be stored in various types of non-tampering areas such as blockchain, immutable storage area, secure encryption storage area, etc. to ensure the security and non-tamperability of order information. When it is determined that the target vehicle has a corresponding extraction demand, the query end that initiates the extraction demand can be determined first, and its identity can be authenticated to determine whether the query end has the authority to query. If the query end has the query authority, in order to further reduce the adverse situation of order data leakage, unique key information can be generated according to the identity of the query end, and the key information can be sent to the query end for query. The key information is set with a corresponding validity period to improve the real-time and security of the query. Only when the key information is in the validity period and the key information verification is successful, can the corresponding order information be extracted in the non-tampering area according to the key information and the identity information of the target vehicle. The data extraction can be verified and managed through multiple verification methods of identity query, unique key information and key validity period, which effectively reduces the adverse situation of order information being leaked or tampered, and protects the privacy security of target vehicle related information during parking management.

[0020] Optionally, the method further comprises: performing abnormality detection on the management status of the target vehicle;

[0021] If it is determined that the management situation of the target vehicle is abnormal, then generating update order information based on the current target status data of the target vehicle;

[0022] Determining difference data between the order information and the updated order information;

[0023] Based on the analysis of the difference data, abnormal processing is performed on the management situation of the target vehicle.

[0024] In the above implementation process, the management situation of the target vehicle can be detected for abnormalities in real time. When it is determined that there is an abnormality in the management situation of the target vehicle, the corresponding updated order information can be generated based on the current target status data of the target vehicle, and the extracted order information and the updated order information can be compared to determine the difference data between the two, and the difference data can be parsed to handle the abnormality of the management situation of the target vehicle. In the case where the order information can be traced, by comparing the difference between two different order information to analyze the cause of the abnormal situation in the management process, the corresponding abnormal management method can be determined, which effectively improves the effectiveness and accuracy of vehicle management under abnormal circumstances.

[0025] Optionally, the parsing based on the difference data and performing abnormal processing on the management situation of the target vehicle includes: locating an abnormal area in the update order information based on the difference data;

[0026] Analyze the abnormal area to determine the abnormal behavior corresponding to the target vehicle;

[0027] The management status of the target vehicle is adjusted according to the difference data and the abnormal behavior.

[0028] In the above implementation process, when performing exception handling, the abnormal area in the order information that is different from the order information can be located and updated based on the abnormal data between the two order information, so as to perform exception analysis based on the order situation represented by the abnormal area, determine the abnormal behavior corresponding to the target vehicle, and analyze the cause of the abnormality by combining the difference data and the abnormal behavior, so as to adjust the management of the target vehicle accordingly, and realize the abnormal handling function of abnormal behavior. It is possible to locate and analyze the abnormal behavior corresponding to the target vehicle through the difference data, and analyze the cause of the abnormal behavior and the degree of abnormality of the abnormal behavior based on the abnormal behavior, so as to adjust the management of the target vehicle according to the abnormal behavior, effectively improving the pertinence and accuracy of abnormal management.

[0029] Optionally, the determining the target state data of the target vehicle in the parking lot includes: determining the posture information and trajectory information of the target vehicle in the parking lot;

[0030] The target state data is determined by combining the posture information and the trajectory information; wherein the target state data includes the parking behavior and parking duration of the target vehicle.

[0031] In the above implementation process, in order to determine the current actual state of the target vehicle, the posture information and trajectory information of the target vehicle in the parking lot can be determined first, and the target state data representing the current parking state of the target vehicle can be determined by combining the posture information and trajectory information. The current actual parking state of the target vehicle in the parking lot can be analyzed and determined based on the posture and trajectory of the target vehicle, which effectively improves the real-time and effectiveness of the target state data.

[0032] Optionally, the determining the posture information and trajectory information of the target vehicle in the parking lot includes: determining the occupancy status of the parking space;

[0033] Detecting whether the target vehicle exists within the target range of the parking space, and determining detection information of the target vehicle; wherein the detection information includes: identity information of the target vehicle and parking time of the target vehicle within the target range;

[0034] Tracking the target vehicle to obtain vehicle feature data;

[0035] Determine the three-dimensional information of the target vehicle based on the vehicle characteristic data, and determine the motion data of the target vehicle based on the two-dimensional information in the parking space and the three-dimensional information;

[0036] Determining the posture information according to the occupancy condition, the detection information and the motion data; wherein the posture information includes the entry state, parking state and exit state of the target vehicle;

[0037] The movement trajectory of the target vehicle in the parking lot is tracked to obtain the trajectory information.

[0038] In the above implementation process, the actual occupancy situation in the parking space can be determined to determine the current working situation of the parking space. In addition, in order to determine the relationship between the parking space and the target vehicle, the target vehicle within the target range of the parking space can also be detected in real time to determine the identity of the target vehicle, the parking time and other detection information when there is vehicle information within the target range. In addition, in order to analyze the moving action of the target vehicle, the target vehicle can be tracked to obtain the corresponding vehicle feature data, thereby constructing the corresponding three-dimensional information based on the vehicle feature data, and combining the two-dimensional information in the parking space and the three-dimensional information of the vehicle for analysis to determine the vehicle's motion data. The occupancy situation, detection information and motion data can be combined with the working state of the parking space, the actual state of the target vehicle in the parking space and the motion trend of the target vehicle to determine the corresponding posture information of the target vehicle entering and exiting the parking space or parking situation. In addition, the motion trajectory of the target vehicle in the parking lot can also be tracked and monitored in real time to obtain the trajectory information representing the real-time position of the target vehicle. The real-time posture information and trajectory information of the target vehicle can be detected and calculated, which effectively improves the validity and accuracy of the target state data determined based on the posture information and trajectory information.

[0039] Optionally, generating unique order information based on the target state data includes: performing serialization processing based on the target state data to obtain target character data;

[0040] A hash calculation is performed based on the target character data to obtain the unique order information.

[0041] In the above implementation process, in order to generate unique order information for each order, the target state data can be serialized to obtain unique target character data. In addition, a bunch of target character data are processed by hash calculation to obtain the corresponding hash value as the corresponding order information. The original target state data can be processed by serialization and hash calculation, which effectively improves the security and non-tamperability of the order information.

[0042] Optionally, the method further comprises: dividing the parking lot into regions to obtain a plurality of sub-regions;

[0043] Analyze the plurality of target status data in each sub-area to determine the remaining parking spaces in each sub-area;

[0044] A guidance area for the newly added vehicle is determined according to the remaining conditions of the plurality of parking spaces and the entry position of the newly added vehicle.

[0045] In the above implementation process, considering that different parking lots have different area ranges, in a parking lot environment with a large area, in order to guide vehicles in an orderly manner, the parking lot can be divided into areas to divide the overall area of ​​the parking lot into multiple sub-areas. In order to improve the parking management efficiency of each of the multiple sub-areas, the target state data of multiple target vehicles in each sub-area can be analyzed to determine the remaining parking spaces in each sub-area, and according to the remaining parking spaces and the entry positions of the newly added vehicles entering the parking lot later, the guidance area suitable for the newly added vehicles to park is determined to guide the newly added vehicles. The parking lot can be divided and processed, and the newly added vehicles can be guided according to the actual parking spaces in the multiple sub-areas obtained by the division, so as to reasonably divert and guide the multiple vehicles entering the parking lot, effectively reduce the unfavorable conditions such as vehicle congestion in the parking lot, thereby improving the parking efficiency of users and improving the parking experience of users.

[0046] Optionally, the method further comprises: determining the vehicle type of the target vehicle by means of a detection device;

[0047] The locking device in the parking space is controlled to be opened / closed based on the vehicle type and the target type of the parking space.

[0048] In the above implementation process, considering that many parking scenarios also have corresponding charging services, in order to reduce the adverse situation that oil vehicles occupy parking spaces with charging services and cause new energy vehicles to be unable to charge normally, the vehicle type of the target vehicle can be determined according to the detection equipment, and the vehicle type is compared with the target type of the parking space to determine whether the vehicle type is consistent with the target type. When the vehicle type is consistent with the target type, the locking device in the parking space can be controlled to close to release the target vehicle for parking and other processing. When the vehicle type is inconsistent with the target type, the locking device in the parking space can be controlled to open to refuse the target vehicle from parking and other processing. It can determine whether to provide services for the target vehicle based on the type of vehicles that can be parked in the parking space and the actual type of the vehicle, which effectively improves the utilization rate of parking spaces with charging services and enhances the charging experience of users.

[0049] In a second aspect, an embodiment of the present application further provides a computer program product, which includes a computer program / instructions, and when the computer program / instructions are executed by a processor, the steps in any implementation of the above-mentioned parking management method are implemented.

[0050] In summary, the embodiments of the present application provide a parking management method and a computer program product, which can determine the current actual status of the target vehicle by determining the target status data of the target vehicle in the parking lot, so as to generate unique order information according to the target status data of the target vehicle, thereby distinguishing multiple orders between multiple vehicles and multiple orders of the same vehicle. In addition, in order to improve the reliability and traceability of the order information, the order information is stored in a non-tamperable area, so that according to the corresponding management requirements, the corresponding order information is obtained from the non-tamperable area to determine the management data for managing the target vehicle, which effectively improves the accuracy and efficiency of vehicle management. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 A block diagram of an electronic device provided in an embodiment of the present application;

[0053] Figure 2 A flowchart of a first parking management method provided in an embodiment of the present application;

[0054] Figure 3 A detailed flowchart of step S400 provided in an embodiment of the present application;

[0055] Figure 4 A detailed flowchart of step S410 provided in an embodiment of the present application;

[0056] Figure 5 A schematic diagram of a second parking management method provided in an embodiment of the present application;

[0057] Figure 6 A detailed flowchart of step S540 provided in an embodiment of the present application;

[0058] Figure 7 A detailed flow chart of step S200 provided in an embodiment of the present application;

[0059] Figure 8 A detailed flowchart of step S210 provided in an embodiment of the present application;

[0060] Fig. 9 A detailed flowchart of step S300 provided in an embodiment of the present application;

[0061] Fig.10 A schematic diagram of a flow chart of a third parking management method provided in an embodiment of the present application;

[0062] Fig.11 A flowchart of a fourth parking management method provided in an embodiment of the present application;

[0063] Fig.12 A schematic diagram of the structure of a parking management device provided in an embodiment of the present application.

[0064] Icons: 100 - electronic device; 111 - memory; 112 - storage controller; 113 - processor; 114 - peripheral interface; 115 - input and output unit; 116 - display unit; 800 - parking management device; 810 - status module; 820 - order module; 830 - management module. DETAILED DESCRIPTION

[0065] The technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments of the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the embodiments of the present application.

[0066] Due to the mobility of vehicles, the current parking management system has the problem of incomplete parking information collection. For example, a vehicle may drive around the parking lot without stopping and be charged when leaving. Alternatively, a vehicle may enter a parking space by mistake and non-parking vehicle information may be collected. Charges may be started before the vehicle stops completely. Data may be obscured during data collection, resulting in invalid data. Alternatively, parking order data of multiple vehicles may be tampered with or leaked, leading to miscalculation, omission, or wrong calculation of parking fees. This may result in low accuracy of parking management and adversely affect the user's parking experience.

[0067] In order to solve the above problems, an embodiment of the present application provides a parking management method, which is applied to electronic devices. The electronic device can be a server, a personal computer (PC), a tablet computer, a smart phone, a personal digital assistant (PDA), a smart parking lock, and other electronic devices with logical calculation functions. The method can determine the management data of multiple target vehicles in the parking lot, manage the parking lot according to the management data, or send the management data to a management terminal for the management terminal to manage the parking lot.

[0068] Optionally, see Figure 1 , Figure 1The block diagram of an electronic device provided in an embodiment of the present application. The electronic device 100 may include a memory 111, a storage controller 112, a processor 113, a peripheral interface 114, an input and output unit 115, and a display unit 116. A person skilled in the art may understand that Figure 1 The structure shown is only for illustration and does not limit the structure of the electronic device 100. For example, the electronic device 100 may further include Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0069] The memory 111, storage controller 112, processor 113, peripheral interface 114, input / output unit 115 and display unit 116 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines. The processor 113 is used to execute the executable module stored in the memory.

[0070] The memory 111 may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), etc. The memory 111 is used to store programs, and the processor 113 executes the program after receiving the execution instruction. The method executed by the electronic device 100 defined by the process disclosed in any embodiment of the present application can be applied to the processor 113, or implemented by the processor 113.

[0071] The processor 113 may be an integrated circuit chip with signal processing capability. The processor 113 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor or any conventional processor.

[0072] The peripheral interface 114 couples various input / output devices to the processor 113 and the memory 111. In some embodiments, the peripheral interface 114, the processor 113 and the memory controller 112 can be implemented in a single chip. In other embodiments, they can be implemented by separate chips.

[0073] The above-mentioned input and output unit 115 is used to provide input data to the user. The input and output unit 115 can be, but is not limited to, a mouse and a keyboard, etc. The above-mentioned display unit 116 provides an interactive interface (such as a user operation interface) between the electronic device 100 and the user or is used to display image data for the user's reference. In this embodiment, the display unit can be a liquid crystal display or a touch display. If it is a touch display, it can be a capacitive touch screen or a resistive touch screen that supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations generated simultaneously from one or more positions on the touch display, and the sensed touch operations are handed over to the processor for calculation and processing. In an embodiment of the present application, the display unit 116 can display various data such as the management data and status of each target vehicle, and the occupancy of the parking space.

[0074] The electronic device in this embodiment can be used to execute each step in each parking management method provided in the embodiment of the present application. The implementation process of the parking management method is described in detail below through several embodiments.

[0075] See also Figure 2 , Figure 2 A schematic flow chart of a first parking management method provided in an embodiment of the present application, the method may include steps S200-S400.

[0076] Step S200, determining target state data of the target vehicle in the parking lot.

[0077] Among them, by determining the target state data of the target vehicle in the parking lot, the current actual state of the target vehicle can be analyzed and determined.

[0078] Optionally, the target state data may include various types of data such as the current position information of the target vehicle, the relationship between the target vehicle and nearby parking spaces, and whether the target vehicle is currently in a parking state.

[0079] Optionally, the corresponding target state data can be obtained from various types of detection equipment installed in the parking lot. The detection equipment can include laser radar devices, cameras and other equipment installed in the parking lot and parking spaces, which can detect multiple vehicles in the parking lot in real time and collect images / videos to obtain or generate corresponding target state data based on the collected data. For example, in order to reduce the energy consumption required for detection by the detection equipment to effectively save the cost required for parking management, the laser radar device, camera and other equipment can be set as new energy driven equipment, such as solar-powered radar and camera.

[0080] Step S300, generating unique order information based on the target status data.

[0081] Among them, considering that there are multiple parking spaces and multiple vehicles in the parking lot, in order to manage different orders for each vehicle, unique order information can be generated according to the target state data of the target vehicle, so as to distinguish multiple orders between multiple vehicles and multiple orders for the same vehicle.

[0082] Optionally, the order information may be unique data such as a corresponding character string, table, QR code, barcode, etc., and the order information may be generated in combination with the identity information and target status data of the target vehicle.

[0083] Step S400, determining the management data of the target vehicle according to the order information stored in the non-tamperable area.

[0084] Among them, taking into account the integrity and security of the data, in order to improve the reliability and traceability of the order information, the generated multiple order information are stored in a non-tamperable area. In the subsequent management process, the corresponding order information can be obtained from the non-tamperable area according to the corresponding management needs to determine the management data for various management processing of the target vehicle.

[0085] It should be noted that the non-tamperable area is a storage area used to prevent data from being modified, deleted or tampered with without authorization, and can ensure the integrity, security and compliance of the stored data. Optionally, according to actual conditions and needs, multiple types of storage areas such as blockchain, immutable storage area, secure encrypted storage area, dedicated hardware security module and specific area in non-volatile memory can be selected to store order information.

[0086] exist Figure 2 In the illustrated embodiment, the accuracy and efficiency of vehicle management are effectively improved, the user's parking experience is enhanced, it is applicable to various types of parking scenarios, and meets a variety of different parking management needs.

[0087] Optionally, see Figure 3 , Figure 3 A detailed flowchart of step S400 is provided for an embodiment of the present application. Step S400 may include steps S410-S420.

[0088] Step S410: extracting order information stored in the non-tamperable area based on the extraction requirement.

[0089] Among them, when managing the vehicle, the required order information can be extracted from the non-tamperable area according to the extraction demand of the target vehicle. Optionally, the extraction demand can be a demand instruction generated by the query end or the management end when managing or querying the parking of the target vehicle. The query end can be a terminal device such as a mobile phone or a tablet computer used by the user on the target vehicle, and the management end can be a cloud server or a management gate in the parking lot.

[0090] Step S420, determining the management data of the target vehicle according to the order information and preset management rules.

[0091] Among them, the management rules may include: charging rules, entry and exit rules, guidance rules, reservation rules and other types of rules. According to the order information and the preset management rules, the management data for various management processes such as charging, restricting, releasing, guiding, and reserving the target vehicle can be determined. The management data may include charging data, restriction / release instructions, guidance information, reservation information and other types of data.

[0092] Optionally, various management rules can be pre-designed according to various actual factors such as the location, demand, and size of the parking lot. For example, charging rules may include: charging by time: charging according to the length of time the vehicle is parked, such as per hour, per day, or per month. For example, for open-air parking spaces, a service fee of 30 to 40 yuan per vehicle may be charged monthly; while indoor parking spaces dedicated to owners may charge a service fee of 50 to 60 yuan per vehicle per month. In addition, the fee for temporary parking (such as parking time of more than 1 hour and less than 12 hours) is usually 4 yuan per time. Pay per time: For some parking lots, a pay per time method may be adopted, that is, only a fixed fee is charged once regardless of the length of parking time. Free parking: Some parking lots or specific time periods may provide free parking services, such as parking spaces in front of public utilities, or free parking lots at specific times such as night and holidays. Entry and exit rules may include: Entrance management: When a vehicle enters a parking lot, it must comply with the instructions of traffic signs and signal lights and drive to the entrance at the specified lane and speed. Some parking lots may have access control systems that require users to show parking cards, license plate recognition or pay fees before entering. Exit management: When vehicles leave the parking lot, they must also abide by traffic rules and follow exit instructions. If parking fees are required, users must complete payment at the exit before leaving. Some parking lots also support convenient payment methods such as contactless payment. Height, width, and speed limits: To ensure the safety of vehicles and facilities in the parking lot, some parking lots will set up height, width, and speed limits. Users must strictly abide by the relevant regulations. Guidance rules may include: Signage guidance: Clear signs will be set up in the parking lot to guide users to vacant parking spaces. Signs usually indicate parking space numbers, directions, and other information. Ground markings: Parking space markings and lane markings will be drawn on the ground of the parking lot. Users must drive and park their vehicles according to the markings. Personnel guidance: Some large parking lots or special occasions (such as concerts, sports events, etc.) may arrange special personnel to provide vehicle guidance services to ensure that vehicles are parked in an orderly manner, as well as screen guidance, voice guidance, and other guidance rules. Reservation rules may include: users can make parking reservations through mobile phone apps, WeChat public accounts, official websites and other channels. Some parking lots also support telephone reservations and other methods. Users need to select the time period and parking space type (such as open-air, indoor, etc.) for parking reservations in advance. Some parking lots support instant reservations and reservations for parking spaces in the next few days. Cancellation and breach of contract: If users need to cancel the reservation after the reservation is successful, they must do so within the specified time. Failure to cancel the reservation within the specified time or failure to enter the parking lot at the scheduled time may be considered a breach of contract and incur corresponding fees or affect the qualification for subsequent reservations.

[0093] It should be noted that, based on the actual situation of the order information, it is possible to determine which rule or rules of the management rules are involved in the order of the target vehicle, and then perform corresponding charging, restriction, release, guidance, reservation and other management according to each rule. Moreover, when the order of the target vehicle involves multiple associated rules, it can also be managed in association according to multiple rules. For example, when the order information of the target vehicle indicates that the target vehicle is parked for 3 hours and needs to exit, it involves corresponding charging rules, guidance rules and entry and exit rules. The parking fee can be calculated according to the parking situation, and the target vehicle can be guided to exit based on its location, etc. Finally, the target vehicle can be charged and released at the exit according to the entry and exit rules.

[0094] exist Figure 3 In the illustrated embodiment, corresponding data can be extracted from the non-tamperable area for management processing, which effectively reduces the risk of data tampering, improves the reliability, integrity and authenticity of the management data source, and thus improves the accuracy and efficiency of vehicle parking management.

[0095] Optionally, see Figure 4 , Figure 4 A detailed flowchart of step S410 is provided for an embodiment of the present application. Step S410 may include steps S411-S415.

[0096] Step S411, storing the order information in a non-tamperable area.

[0097] Among them, after obtaining multiple order information corresponding to multiple target vehicles, the multiple order information can be stored in various types of non-tampering areas such as blockchain, immutable storage area, secure encrypted storage area, etc., to ensure the security and non-tamperability of the order information.

[0098] Optionally, the non-tamperable area may include multiple types of storage areas such as blockchain, immutable storage area, secure encrypted storage area, dedicated hardware security module, and specific area in non-volatile memory. Immutable storage is a storage protocol that protects stored data by preventing any changes or modifications. Based on the data security principle of write once read many times (WORM), these storage areas allow repeated access to stored data after creation, but prohibit editing, deletion, or rewriting until the end of a predetermined retention period. The secure encrypted storage area can encrypt the stored data using encryption technology to ensure that even if the data is stolen, it cannot be decrypted and tampered by unauthorized users. The dedicated hardware security module can be a hardware device set inside the parking lot, which can store and manage encryption keys, perform encryption and decryption operations, and provide secure data storage services. Blockchain technology provides extremely high security for data storage through the characteristics of decentralization, immutability, and transparency. Each block contains the hash value of the previous block, thus forming a chain structure, and any tampering with the data will cause the entire chain to break. Certain areas in non-volatile memory (such as NVRAM, Non-Volatile Random Access Memory, SSD, Solid State Drive) may be designed to be tamper-proof, so that the data stored in it remains intact and accessible when the system is attacked or fails. It is possible to prevent unauthorized access and tampering through a combination of hardware and software, thereby protecting the security and stability of data.

[0099] Step S412: If it is determined that the target vehicle has an extraction requirement, a query end for the extraction requirement of the target vehicle is determined.

[0100] Step S413: Authenticate the identity of the querying end.

[0101] When it is determined that the target vehicle has a corresponding extraction requirement, the query end that initiates the extraction requirement may be first determined and its identity verified to determine whether the query end has the authority to conduct the query.

[0102] Optionally, based on the set database, the identity of the query end can be verified in a variety of ways, for example, by using an account + password method. When the account entered at the query end belongs to the queryable range in the database and the password is correct, the verification is successful. Or by collecting the hardware and software information (such as IP address, MAC address, operating system, browser type, etc.) of the acquisition end for verification. When the hardware and software information belongs to the queryable range in the database, the verification is successful. Or by using a mobile phone verification code, fingerprint recognition, facial recognition, etc. for verification. When the mobile phone verification code is correct, or the fingerprint information and / or facial information belongs to the existing information in the database, the verification is successful. Or assign different permissions according to the role of the query end to ensure that users can only access resources within their scope of responsibility. Alternatively, the query end can also digitally sign the extraction requirements to ensure the authenticity and integrity of the request. The terminal device in the non-tampering area can confirm whether the request comes from an authorized device by verifying the signature to achieve identity authentication.

[0103] Step S414: If the identity authentication of the querying end is successful, unique key information is generated based on the identity of the querying end, and the key information is sent to the querying end.

[0104] Among them, if the query end has query authority, in order to further reduce the adverse situation of order data leakage, unique key information can be generated according to the identity of the query end, and the key information can be sent to the query end for query.

[0105] Optionally, random and unique key information can be generated based on unique data such as the identity number of the query end, combined with a high-quality random number generator (RNG). The key information can include corresponding public keys and private keys to ensure that the generated key information is highly random and unpredictable, thereby improving the security of the data extraction process. When generating key information, a suitable random number generator can be selected to generate a random key of sufficient length (such as a 2048-bit RSA key) in combination with the identity number of the query end, and the key is stored in a non-tamperable area. Alternatively, the password can be converted into key information through algorithms such as hash functions based on the password attached to the query end extraction requirements. Alternatively, a suitable key generation tool, such as GPG, OpenSSL, ssh-keygen, etc., can be selected to generate corresponding key information based on various data such as the user's identity number, IP address, request content, etc. Alternatively, a security key device can be used to generate corresponding key information in combination with the user's identity, such as a PIN code or biometric information. When transmitting key information, the key information can be transmitted through a secure channel (such as SSL / TLS protocol) to ensure the security of the key information during transmission and prevent the key information from being intercepted or tampered with during transmission.

[0106] Step S415: If the key information is valid, the order information is extracted in the non-tamperable area based on the key information and the identity information of the target vehicle sent by the query end.

[0107] Among them, in order to ensure the timeliness of data extraction, the key information can be set with a corresponding validity period, such as within 5 seconds, to improve the real-time and security of the query. Only when the key information is valid (for example, the key information uploaded by the query end is received within 3 seconds, etc.) and the key information verification is successful, can the corresponding order information be extracted in the non-tamperable area based on the key information and the identity information of the target vehicle.

[0108] Optionally, when verifying the private key in the key information uploaded by the query end, the public key stored in the non-tamperable area can be used for verification. For example, the private key is used to generate a signature, and the public key is used to verify the validity of the signature. The verification method may include: verifying whether the format of the private key is as expected, such as RSA private keys are usually stored in formats such as PKCS#1, PKCS#8, or PEM. By calculating the hash value (such as SHA-256) of the private key file and comparing it with the expected value or the stored hash value, ensure that the private key file has not been tampered with during transmission or storage. Sign a piece of data (such as a timestamp, a random number, or a specific message) with the private key, and then use the corresponding public key to verify the validity of the signature. If the signature verification passes, it means that the private key is valid and matches the public key. If the private key is associated with the digital certificate of the query end, the validity of the certificate chain can also be verified. This includes multiple verification methods such as verifying whether the certificate is issued by a trusted certificate authority (CA) and whether each certificate in the certificate chain is valid and has not been revoked.

[0109] Optionally, when sending order information to the query end, encryption protocols such as SSL / TLS can be used to encrypt the transmitted order information to ensure that the data is not stolen or tampered with during transmission.

[0110] exist Figure 4 In the illustrated embodiment, data extraction can be verified and managed through multiple verification methods including identity query, unique key information, and key validity period, thereby effectively reducing the adverse situation of order information being leaked or tampered with, and protecting the privacy security of target vehicle-related information during parking management.

[0111] Optionally, see Figure 5 , Figure 5 This is a flow chart of a second parking management method provided in an embodiment of the present application. The method may further include steps S510-S540.

[0112] Step S510, performing abnormality detection on the management status of the target vehicle.

[0113] Among them, real-time anomaly detection can be performed on the management situation of the target vehicle. The method of anomaly detection can include obtaining user feedback information from the user's terminal device. For example, the user has reported various information such as corresponding vehicle charging anomalies, the parking space is locked so that the vehicle cannot park or leave normally, the vehicle has paid but cannot pass through the gate, etc. The anomaly in the management situation of the target vehicle can be determined based on various types of feedback information.

[0114] Step S520: If it is determined that the management status of the target vehicle is abnormal, update order information is generated based on the current target status data of the target vehicle.

[0115] Wherein, when it is determined that the management situation of the target vehicle is abnormal, the corresponding update order information can be generated based on the current target state data of the target vehicle. Optionally, the data type of the current target state data is similar to the target state data, and the data type of the update order information is similar to the order information. The target state data determination method can be used to determine the corresponding current target state data, and the order information generation method can be used to generate the corresponding update order information based on the current target state data, which will not be described in detail.

[0116] Step S530, determining the difference data between the order information and the updated order information.

[0117] The extracted order information and the updated order information are compared to determine the difference data between the two.

[0118] Optionally, the difference data between the order information and the updated order information can be determined by string comparison, table comparison, QR code comparison or barcode comparison. The difference data can be various types of data such as different string data, table content, QR code area and barcode area between the two.

[0119] For example, when the order information and the updated order information are strings, you can start from the first character of the string and compare each character one by one until you find a different character or both strings are compared, and determine the different string data between the two. You can also build a two-dimensional matrix, compare each character of the two strings, and find the longest common subsequence (LCS). The length and position information of the LCS can characterize the similarities and differences between the two strings, and determine the different string data between the two. Alternatively, by dividing the string into smaller blocks or rows and calculating the hash value of each block, and then comparing the number and position of the same blocks in the two strings, and processing different blocks, determine the different string data between the two. Alternatively, by building a suffix tree of the two strings, the suffix tree is a special tree structure used to represent all suffixes of a string, and comparing the structures of the two trees, you can find the difference between the strings and determine the different string data between the two. You can also use a language such as Java to provide special string comparison methods, such as equals(), equalsIgnoreCase(), and compareTo(). Among them, the equals() method is used to check whether two strings are exactly the same (case sensitive), the equalsIgnoreCase() method is used to check whether two strings are the same but ignore case, and the compareTo() method compares the sizes of two strings in lexicographical order to determine the different string data between the two.

[0120] For example, when the order information and the updated order information are tables, the different table contents between the two tables can be determined by text recognition. When the order information and the updated order information are QR codes or bar codes, the different QR code areas or bar code areas between the two can be determined by image recognition, pixel value counting, etc.

[0121] Step S540, analyzing the difference data and handling the abnormality of the management status of the target vehicle.

[0122] The difference data may be analyzed to determine the cause of the abnormal management of the target vehicle, so as to handle the abnormal management of the target vehicle.

[0123] Optionally, the exception handling may include controlling gates, opening / closing parking locks, refunding overcharged fees, collecting uncollected fees, changing parking space status, and other types of processing methods.

[0124] exist Figure 5In the illustrated embodiment, when order information is traceable, the differences between two different order information are compared to analyze the causes of abnormal situations in the management process, thereby determining the corresponding abnormal management method, thereby effectively improving the effectiveness and accuracy of vehicle management under abnormal circumstances.

[0125] Optionally, see Figure 6 , Figure 6 A detailed flowchart of step S540 is provided for an embodiment of the present application. Step S540 may include steps S541-S543.

[0126] Step S541, based on the difference data, locate and update the abnormal area in the order information.

[0127] When performing exception handling, the abnormal area in the updated order information that is different from the order information can be located based on the abnormal data between the two order information. When the order information and the updated order information are strings, the abnormal area can be the location of different characters, when the order information and the updated order information are tables, the abnormal area can be the table location where different table contents are located, and when the order information and the updated order information are QR codes or bar codes, the abnormal area can be the location where different QR code areas or bar code areas are located.

[0128] Step S542, analyzing the abnormal area to determine the abnormal behavior corresponding to the target vehicle.

[0129] Among them, due to the difference in the meanings represented by the data in different areas of the order information, an abnormal analysis can be performed according to the order situation represented by the abnormal area to determine the abnormal behavior corresponding to the target vehicle. Optionally, when the order information and the updated order information are strings, the actual meanings represented by different characters can be determined according to the abnormal area to determine the abnormal behavior of the target vehicle. For example, if the characters representing the parking time in the abnormal area are different, the corresponding abnormal behavior is that there is an abnormality in the charge. When the order information and the updated order information are tables, the actual meanings represented by different table contents can be determined according to the abnormal area to determine the abnormal behavior of the target vehicle. For example, if the table contents representing the vehicle identity information in the abnormal area are different, the corresponding abnormal behavior is that there is an abnormality in the vehicle target. When the order information and the updated order information are QR codes or bar codes, the actual meanings represented by different QR code areas or bar code areas can be determined according to the abnormal area to determine the abnormal behavior of the target vehicle. For example, if the coding shapes representing whether the vehicle leaves the parking space in the abnormal area are different, the corresponding abnormal behavior is that there is an abnormality in the vehicle status.

[0130] Step S543, adjusting the management of the target vehicle according to the difference data and abnormal behavior.

[0131] Among them, the cause of the abnormality can be analyzed in combination with the difference data and abnormal behavior, so as to make corresponding adjustments to the management of the target vehicle and realize the abnormal behavior abnormality handling function.

[0132] Optionally, the degree of the difference between the two can be determined based on the difference data, and the specific processing method for adjusting the management of the target vehicle can be determined in combination with the abnormal behavior. For example, when the abnormal behavior is overcharging the user for parking fees, the value of the overcharged parking fees can be determined based on the different character string data in the difference data, and the excess parking fees can be refunded to the account paid by the user.

[0133] exist Figure 6 In the embodiment shown, it is possible to locate and analyze the abnormal behavior corresponding to the target vehicle through difference data, and based on the abnormal behavior, combined with the difference data, analyze the cause of the abnormal behavior, the degree of abnormality of the abnormal behavior, etc., so as to adjust the management of the target vehicle according to the abnormal behavior, effectively improving the pertinence and accuracy of abnormal management.

[0134] Optionally, see Figure 7 , Figure 7 A detailed flowchart of step S200 is provided for an embodiment of the present application. Step S200 may include steps S210-S220.

[0135] Step S210, determining the posture information and trajectory information of the target vehicle in the parking lot.

[0136] Among them, in order to determine the current actual status of the target vehicle, the posture information and trajectory information of the target vehicle in the parking lot can be determined first. The posture information is the current movement trend of the target vehicle in the parking lot, such as whether the vehicle is going in and out of the parking space, whether it is going in and out of the parking lot, whether it is going to park, etc. The trajectory information can be the movement trajectory of the target vehicle in the parking lot, and the corresponding posture information and trajectory information can be collected through various types of detection equipment set up in the parking lot or parking space.

[0137] Step S220, determining target state data by combining the posture information and the trajectory information.

[0138] The target state data representing the current parking state of the target vehicle can be determined by combining the posture information and the trajectory information. The target state data can include the parking behavior and parking duration of the target vehicle.

[0139] Optionally, the method for determining parking behavior may include: first detecting the objects in the parking space by means of a detection device, and obtaining a corresponding target signal when a change in the object is detected in the corresponding area. The target signal may be corresponding point cloud data, including a large number of laser points, each of which includes its position information in three-dimensional space (such as x, y, z coordinates) and possible additional information such as reflection intensity. The type of the detected object may be identified based on the target signal to determine whether there is an object in the parking space and whether the object in the parking space is a vehicle. When it is determined that there is a vehicle in the parking space, an analysis may be performed based on movement parameters related to vehicle movement and corresponding time conditions to determine whether the vehicle in the parking space has the corresponding parking behavior.

[0140] It should be noted that parking behavior may include the behavior of a vehicle entering or leaving a parking space. In order to identify whether a vehicle has the action of entering or leaving a parking space, a variety of vehicle movement parameters may be obtained. The movement parameters may include the vehicle's movement trajectory, speed change data, and the distance parameters between the vehicle and the restriction line in the parking space, and other parameters related to the movement and position of the vehicle. The movement purpose and trend of the speed change data vehicle can be determined based on the movement trajectory. The restriction line in the parking space can be the marking line when the parking space is divided. The relative position relationship between the vehicle and the parking space marking line can be determined based on the distance parameter. The time condition may include a set time period, and data collection is performed only within a specific time period to avoid invalid operations during non-peak hours.

[0141] exist Figure 7 In the illustrated embodiment, the actual current parking state of the target vehicle in the parking lot can be analyzed and determined according to the posture and trajectory of the target vehicle, thereby effectively improving the real-time performance and validity of the target state data.

[0142] Optionally, see Figure 8 , Figure 8 A detailed flowchart of step S210 is provided for an embodiment of the present application. Step S210 may include steps S211-S216.

[0143] Step S211, determining the occupancy status of the parking space.

[0144] Among them, the actual occupancy situation in the parking space can be determined to determine the current working situation of the parking space.

[0145] Optionally, the occupancy status of the parking space may be determined by target detection or the like.

[0146] Step S212, detecting whether there is a target vehicle within the target range of the parking space, and determining detection information of the target vehicle.

[0147] Among them, the detection information may include: the identity information of the target vehicle and the parking time of the target vehicle within the target range. In order to determine the relationship between the parking space and the target vehicle, the target vehicle within the target range of the parking space can also be detected in real time to determine the identity information, parking time and other detection information of the target vehicle when there is vehicle information within the target range. Optionally, the identity information of the target vehicle may include the license plate information obtained by photographing the license plate of the target vehicle by a detection device such as a camera. The camera can photograph and obtain the corresponding initial data. In order to improve the quality of the data, the initial data can be image recognized to evaluate the quality of the image data in the initial data to obtain the target license plate data whose image quality meets the preset conditions. Considering the complexity and diversity of the license plate characters, the target license plate data can also be feature extracted to obtain the corresponding character data. The license plate color + character can be deep convolved to extract the feature vector, combined with the license plate distortion calibration technology, the neural network algorithm and the feature recognition algorithm to perform feature extraction and recognition, to achieve overall integrated recognition without character segmentation, with strong generalization ability and high recognition accuracy, and obtain character data with high effectiveness as the license plate information. Optionally, the stop time may be the time during which the target vehicle is completely within the target range, and the timing may start when the target vehicle enters the target range and stop when the target vehicle leaves the target range.

[0148] Step S213, tracking the target vehicle to obtain vehicle feature data.

[0149] Among them, in order to analyze the moving action of the target vehicle, the target vehicle can be tracked to obtain the corresponding vehicle feature data. Optionally, a multi-target tracking algorithm can be used, such as using Kalman filter + state transfer matrix to track the number of multiple targets and their motion state or motion track, and can also be combined with ReID (Person Re-identification) network to extract multiple features such as the vehicle's roof, windows, rearview mirrors, etc. for matching to obtain multiple vehicle feature data corresponding to the roof, windows, rearview mirrors, etc.

[0150] For example, a convolutional neural network (CNN) can be used to extract global features from a vehicle image. These global features can capture the overall appearance information of the vehicle, such as the vehicle model, color, etc. By designing a specific ROI (Region of Interest) area, focus on extracting the features of the roof. The features of the roof often include color, shape, decoration, etc. The ROI area can also be set to extract the features of the window part. The features of the window may include the shape, size, decoration, and whether it is open. The ROI area can also be set to extract the features of the rearview mirror, which usually include shape, color, and whether it has decoration. The extracted global features and multiple types of local features are fused to fully utilize the complementarity of the two. The fusion method may include splicing, weighted summation, etc. The metric learning technology can be used to map the extracted features to a new feature space, in which the distance between vehicle features of the same category should be closer, and the distance between vehicle features of different categories should be farther. A suitable loss function can be selected to optimize the model. For example, the loss function may include contrastive loss and triplet loss. The corresponding model can also be trained for feature extraction, and the image of the target vehicle can be input into the model to output multiple features through feature matching, etc. In a multi-camera monitoring system, ReID technology can also be used to track vehicles across cameras. By extracting the features of the vehicle under different cameras and calculating the distance between the features, continuous tracking and identification of the vehicle can be achieved.

[0151] Step S214, determining the three-dimensional information of the target vehicle based on the vehicle feature data, and determining the motion data of the target vehicle based on the two-dimensional information and the three-dimensional information in the parking space.

[0152] Among them, the corresponding three-dimensional information can be constructed based on the vehicle feature data, and the two-dimensional information in the parking space and the three-dimensional information of the vehicle can be analyzed to determine the vehicle's motion data.

[0153] Optionally, corresponding three-dimensional information can be constructed based on vehicle feature data, and combined with the two-dimensional information in the parking space and the three-dimensional information of the vehicle for analysis to determine the vehicle's motion data. Optionally, based on the initial data collected by the camera, a method based on multi-feature fusion can be used to detect the lane lines in the parking space and delineate the lane line area, so as to manually mark the 2D parking line according to the restriction line on the ground of the parking space, thereby determining the two-dimensional information of the vehicle, and regressing the landing point of the vehicle tires and the ground using the 3D chassis information in the vehicle's three-dimensional information, and regressing to obtain the mapping of the 3D coordinates on the 2D image, and calculating the target vehicle's driving trajectory, driving direction and fusion parking matching algorithm model through a multi-target algorithm model, judging the vehicle's entry or exit action process, and obtaining the corresponding action data. This allows complex scenes to still accurately match parking spaces, and finely manage parking spaces, supporting multiple scenarios such as parallel front lighting, oblique lighting, vertical parking, and oblique non-parking.

[0154] For example, a multi-target tracking algorithm can accurately locate and track multiple targets from continuous image frames or video sequences while maintaining the identity consistency of the targets. The multi-target tracking algorithm can include various types of feature extraction algorithms, classifiers, and filters, such as Kalman filters, particle filters, maximum a posteriori probability estimation, etc. It can also include algorithms that directly learn the appearance features and motion information of targets by using deep models such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), thereby achieving more accurate and robust target tracking, such as discriminant correlation filters (DCFs), using Siamese networks to calculate the similarity between targets in different frames, thereby achieving target association and tracking, using target detection algorithms (such as Faster R-CNN, YOLO, etc.) to detect the position and bounding box of the target in each frame, and then using data association methods to associate the detection results of the current frame with the tracked objects in the past frames, and finally obtain the target motion trajectory, and by training the RNN model, the position of the target in the future frame can be predicted, thereby achieving tracking, etc.

[0155] Step S215, determining posture information according to the occupancy status, detection information and motion data.

[0156] Among them, the posture information of the target vehicle entering or exiting the parking space or parking situation corresponding to the target vehicle can be determined by combining the occupancy situation, detection information and motion data, the working state of the parking space, the actual state of the target vehicle in the parking space and the motion trend of the target vehicle. The posture information may include the entry state, parking state and exit state of the target vehicle.

[0157] Step S216, tracking the movement trajectory of the target vehicle in the parking lot to obtain trajectory information.

[0158] Among them, the movement trajectory of the target vehicle in the parking lot can also be tracked and monitored in real time based on the image information or video information collected by the set camera or camera, so as to obtain trajectory information representing the real-time position of the target vehicle.

[0159] exist Figure 8 In the illustrated embodiment, the real-time posture information and trajectory information of the target vehicle can be detected and calculated, which effectively improves the validity and accuracy of the target state data determined based on the posture information and trajectory information.

[0160] Optionally, see Fig. 9 , Fig. 9 A detailed flowchart of step S300 is provided for an embodiment of the present application. Step S300 may include steps S310-S320.

[0161] Step S310, performing serialization processing based on the target state data to obtain target character data.

[0162] In order to generate unique order information for each order, the target state data may be serialized to obtain unique target character data.

[0163] Optionally, the target state data can be serialized in a variety of data formats, for example, the target state data can be serialized into a JSON string or an XML format string. A built-in serialization library or method can also be provided to directly convert data objects into character data (such as strings or byte streams). For example, by implementing the Serializable interface in Java, ObjectOutputStream can be used to serialize data objects into byte streams, and then ObjectInputStream can be used to deserialize them. Python's json module provides a dumps function that can serialize Python data structures (such as dictionaries, lists, etc.) into JSON strings. JavaScript's JSON.stringify() method can serialize JavaScript objects into JSON strings, etc. You can also customize the serialization method to serialize the target state data according to specific business needs. According to the actual protocol situation and needs, the corresponding data format can be selected to serialize the target state data, which can convert multiple target state data into character data in a unified data format and effectively reduce the storage amount of character data, thereby reducing the storage pressure of the non-tampering area.

[0164] Step S320, performing hash calculation based on the target character data to obtain unique order information.

[0165] Among them, a bunch of target character data are processed by hash calculation to obtain the corresponding hash value as the corresponding order information. It should be noted that the characteristic of the hash algorithm is that its output (i.e., hash value) is of fixed length, and any slight data change will result in a completely different hash value output to verify the integrity and uniqueness of the data according to the change of the hash value. Optionally, different hash functions can be selected for hash calculation according to actual scenarios and needs, such as MD5, SHA-1, SHA-256, etc. Before the target character data is input into the hash function, considering that some hash functions usually have specific requirements for the format and length of the input data, some preprocessing operations can be performed on the target character data, such as encoding conversion, padding or grouping, etc. For example, the SHA-256 algorithm requires the input data to be grouped by 512 bits (64 bytes), and the insufficient part needs to be filled with 0. The processed target character data is input into the hash function for calculation to obtain a fixed-length hash value as the corresponding order information.

[0166] Optionally, a larger hash value length can be selected to reduce the possibility of collision. Double hashing or multi-hash technology can also be used to calculate the same input target character data using two different hash functions to obtain two or more hash values. Only when these hash values ​​are the same, the input data is considered to be the same to improve the uniqueness of the hash value. In some hash algorithms, prime numbers are required as parameters to ensure the uniqueness of the hash value. Choosing a suitable prime number can reduce the probability of collision.

[0167] exist Fig. 9 In the illustrated embodiment, the original target state data can be processed by serialization and hash calculation, which effectively improves the security and non-tamperability of the order information.

[0168] Optionally, see Fig.10 , Fig.10 This is a flow chart of a third parking management method provided in an embodiment of the present application. The method may further include steps S610-S630.

[0169] Step S610, dividing the parking lot into regions to obtain a plurality of sub-regions.

[0170] Considering that different parking lots have different area ranges, in a parking lot environment with a large area, in order to guide vehicles in an orderly manner, the parking lot can be divided into areas so as to divide the overall area of ​​the parking lot into multiple sub-areas.

[0171] Optionally, the parking lot may be divided based on various factors such as regional characteristics and floors. When providing prompts, the parking lot may be divided into several independent grids through several guide screens, each grid representing a corresponding sub-area.

[0172] Step S620: Analyze the multiple target status data in each sub-area to determine the remaining parking spaces in each sub-area.

[0173] In order to improve the parking management efficiency of each of the multiple sub-areas, the target state data of multiple target vehicles in each sub-area may be analyzed to determine the remaining parking spaces in each sub-area.

[0174] Optionally, the target status data of all vehicles in each sub-area can be analyzed to determine the occupancy of each parking space in the sub-area, thereby determining the overall remaining parking spaces in the sub-area. Optionally, in each sub-area, the vehicle license plate can be automatically identified by the detection equipment set on the parking space, and the parking space occupancy status can be transmitted to the in-field guidance screen through the network controller. The guidance screen will calculate the collected in-field remaining space data to obtain the remaining parking space situation, and publish the remaining parking space situation in real time on the in-field guidance screen or upload it to the server synchronously.

[0175] Step S630, determining a guidance area for the newly added vehicle according to the remaining conditions of the plurality of parking spaces and the entry position of the newly added vehicle.

[0176] Among them, the guidance area suitable for parking the new vehicles can be determined according to the remaining parking spaces and the entry positions of the new vehicles that will enter the parking lot later, so as to guide the new vehicles.

[0177] Optionally, a sub-area with remaining parking spaces and closest to the entrance position of the newly added vehicle can be selected as the guidance area for the newly added vehicle, and parking guidance can be provided to the newly added vehicle through voice, guidance screen, etc.

[0178] It should be noted that when the newly added vehicle is a new energy vehicle, the guidance area for the newly added vehicle may also be determined based on whether the remaining parking spaces in the sub-area are rechargeable parking spaces.

[0179] exist Fig.10 In the illustrated embodiment, the parking lot can be divided, and newly added vehicles can be guided according to the actual parking space conditions in the multiple sub-areas obtained by the division, so as to reasonably divert and guide the multiple vehicles entering the parking lot, effectively reduce adverse conditions such as vehicle congestion in the parking lot, thereby improving the user's parking efficiency and enhancing the user's parking experience.

[0180] Optionally, see Fig.11 , Fig.11 This is a flow chart of a fourth parking management method provided in an embodiment of the present application. The method may further include steps S710-S720.

[0181] Step S710, determining the vehicle type of the target vehicle through a detection device.

[0182] Among them, considering that many parking scenarios also have corresponding charging services, in order to reduce the adverse situation that oil vehicles occupy parking spaces with charging services and cause new energy vehicles to be unable to charge normally, the vehicle type of the target vehicle can be determined according to the detection equipment. Optionally, the vehicle type of the target vehicle can be determined by identifying the color of the collected license plate information. For example, in general, a blue license plate is an oil vehicle and a green license plate is a new energy vehicle, or the vehicle type of the target vehicle can be determined by identifying the characters in the license plate information, or by detecting the contour features of the vehicle.

[0183] Step S720: Controlling the opening / closing of the locking device in the parking space based on the vehicle type and the target type of the parking space.

[0184] Among them, the locking device in the parking space, such as the parking lock, can be connected to the new energy camera, or set in the same device, so that the parking lock can be controlled by the new energy camera. The vehicle type can be compared with the target type of the parking space to determine whether the vehicle type is consistent with the target type. When the vehicle type is consistent with the target type, the new energy camera can control the locking device in the parking space to close to allow the target vehicle to park, etc. When the vehicle type is inconsistent with the target type, the new energy camera can control the locking device in the parking space to open to refuse the target vehicle to park, etc.

[0185] Optionally, the locking device can be a parking lock or other device that can be set in the parking space and can rise and fall to restrict the entry and exit of vehicles. When the vehicle type is inconsistent with the target type, for example, when the target vehicle is a fuel truck, when the vehicle approaches, the parking lock is controlled to rise to prevent the vehicle from entering the parking space. The new energy camera or the sound and light device set in the parking lock can make a sound and light alarm to drive away the fuel truck and improve the utilization rate of the new energy parking space. Alternatively, when the target parking space is a non-motor vehicle, the new energy camera recognizes that the non-motor vehicle is parked in the new energy parking space, and the sound and light device set in the new energy camera or the parking lock gives a sound and light alarm, and reports the abnormal occupation event to the management platform for processing. Alternatively, when the target vehicle is a new energy vehicle, the new energy camera on the parking space recognizes that the vehicle is parked across the space, and the sound and light device set in the new energy camera or the parking lock gives a sound and light alarm, and reports the abnormal occupation event to the management platform for processing.

[0186] Optionally, the control method of the locking device and the reservation rules can be combined to effectively reserve the new energy parking space.

[0187] exist Fig.11 In the illustrated embodiment, it is possible to determine whether to provide service for a target vehicle based on the type of vehicle that can be parked in the parking space and the actual type of the vehicle, thereby effectively improving the utilization rate of parking spaces with charging services and enhancing the user's charging experience.

[0188] See also Fig.12 , Fig.12 A schematic diagram of the structure of a parking management device provided in an embodiment of the present application, the parking management device 800 may include: a status module 810, an order module 820 and a management module 830.

[0189] The state module 810 is used to determine the target state data of the target vehicle in the parking lot;

[0190] The order module 820 is used to generate unique order information based on the target status data;

[0191] The management module 830 is used to determine the management data of the target vehicle based on the order information stored in the non-tamperable area.

[0192] In an optional embodiment, the management module 830 is specifically used to: extract order information stored in the non-tamperable area based on extraction requirements; determine the management data of the target vehicle according to the order information and preset management rules; wherein the management rules include: at least one of charging rules, entry and exit rules, guidance rules and reservation rules.

[0193] In an optional embodiment, the management module 830 is specifically used to: store the order information in a non-tamperable area; wherein the non-tamperable area includes at least one of a blockchain, an immutable storage area, and a secure encrypted storage area; if it is determined that the target vehicle has a withdrawal requirement, then determine the query end of the withdrawal requirement of the target vehicle; authenticate the query end; if the identity authentication of the query end is successful, then generate unique key information based on the identity of the query end, and send the key information to the query end; if the key information is valid, extract the order information in the non-tamperable area based on the key information and the identity information of the target vehicle sent by the query end.

[0194] In an optional embodiment, the parking management device 800 may also include: an abnormality module, which is used to detect abnormalities in the management situation of the target vehicle; if it is determined that there is an abnormality in the management situation of the target vehicle, generating update order information based on the current target status data of the target vehicle; determining the difference data between the order information and the updated order information; and performing analysis based on the difference data to handle the abnormality of the management situation of the target vehicle.

[0195] In an optional implementation, the exception module is specifically used to: locate and update abnormal areas in order information based on difference data; analyze the abnormal areas to determine abnormal behaviors corresponding to the target vehicles; and adjust the management of the target vehicles based on the difference data and abnormal behaviors.

[0196] In an optional embodiment, the state module 810 is specifically used to: determine the posture information and trajectory information of the target vehicle in the parking lot; determine the target state data in combination with the posture information and trajectory information; wherein the target state data includes the parking behavior and parking duration of the target vehicle.

[0197] In an optional embodiment, the status module 810 is specifically used to: determine the occupancy status of the parking space; detect whether there is a target vehicle within the target range of the parking space, and determine the detection information of the target vehicle; wherein the detection information includes: the identity information of the target vehicle and the parking time of the target vehicle within the target range; track the target vehicle to obtain vehicle characteristic data; determine the three-dimensional information of the target vehicle based on the vehicle characteristic data, and determine the motion data of the target vehicle based on the two-dimensional information and three-dimensional information in the parking space; determine the posture information according to the occupancy status, detection information and motion data; wherein the posture information includes the entry status, parking status and exit status of the target vehicle; track the movement trajectory of the target vehicle in the parking lot to obtain trajectory information.

[0198] In an optional implementation, the order module 820 is specifically used to: perform serialization processing based on the target state data to obtain target character data; and perform hash calculation based on the target character data to obtain unique order information.

[0199] In an optional embodiment, the parking management device 800 may also include: a guidance module, which is used to divide the parking lot into multiple sub-areas; determine the remaining parking spaces in each sub-area based on multiple target status data in each sub-area; and determine the guidance area for the newly added vehicle based on the remaining parking spaces and the entry position of the newly added vehicle.

[0200] In an optional embodiment, the parking management device 800 may further include: a locking module, which is used to determine the vehicle type of the target vehicle through a detection device; and control the opening / closing of the locking device in the parking space based on the vehicle type and the target type of the parking space.

[0201] Since the principle of solving the problem by the parking management device 800 in the embodiment of the present application is similar to that of the embodiment of the aforementioned parking management method, the implementation of the parking management device 800 in this embodiment can refer to the description in the embodiment of the aforementioned parking management method, and the repeated parts will not be repeated.

[0202] An embodiment of the present application also provides a computer program product, which includes a computer program / instructions. When the computer program / instructions are executed by a processor, the steps in any implementation of the above-mentioned parking management method are implemented.

[0203] In several embodiments provided in the present application, it should be understood that the disclosed device can also be implemented in other ways. The device embodiments described above are merely schematic, for example, the block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices according to the multiple embodiments of the present application. In this regard, each box in the block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram, and the combination of the block diagrams, can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0204] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0205] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0206] The above description is only an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0207] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

[0208] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

Claims

1. A parking management method, characterized in that: The method comprises: Determine target state data of the target vehicle in the parking lot; Based on the target status data, generating unique order information; Determining the management data of the target vehicle based on the order information stored in the non-tamperable area; The method further includes: performing abnormality detection on the management of the target vehicle; if it is determined that the management of the target vehicle is abnormal, generating updated order information based on the current target state data of the target vehicle; determining the difference data between the order information and the updated order information; parsing based on the difference data, performing abnormality processing on the management of the target vehicle; wherein the order information and the updated order information include character strings; the abnormality processing includes: controlling the gate machine, the parking space lock to open / close, refunding the overcharged fees, collecting the uncollected fees or changing the parking space status; The method of parsing the difference data and performing abnormal processing on the management situation of the target vehicle includes: locating an abnormal area in the update order information based on the difference data; analyzing the abnormal area to determine the abnormal behavior corresponding to the target vehicle; adjusting the management situation of the target vehicle based on the difference data and the abnormal behavior; wherein the abnormal area includes: the positions of different characters in the character string.

2. The method according to claim 1, characterized in that The step of determining the management data of the target vehicle according to the order information stored in the non-tamperable area includes: Based on the extraction requirement, extract the order information stored in the non-tamperable area; Determining the management data of the target vehicle according to the order information and preset management rules; The management rules include at least one of charging rules, entry and exit rules, guidance rules and reservation rules.

3. The method according to claim 2, characterized in that The extracting the order information stored in the non-tamperable area based on the extraction requirement includes: The order information is stored in the non-tamperable area; wherein the non-tamperable area includes at least one of a blockchain, an immutable storage area, and a secure encrypted storage area; If it is determined that the target vehicle has the extraction requirement, determining a query end of the extraction requirement of the target vehicle; Authentication of the query end; If the identity authentication of the query end is successful, generating unique key information based on the identity of the query end, and sending the key information to the query end; If the key information is valid, the order information is extracted from the non-tamperable area based on the key information and the identity information of the target vehicle sent by the query end.

4. The method according to any one of claims 1 to 3, characterized in that: The step of determining target state data of the target vehicle in the parking lot includes: Determining the posture information and trajectory information of the target vehicle in the parking lot; The target state data is determined by combining the posture information and the trajectory information; wherein the target state data includes the parking behavior and parking duration of the target vehicle.

5. The method according to claim 4, characterized in that The determining of the posture information and trajectory information of the target vehicle in the parking lot includes: Determine the occupancy status of the parking space; Detecting whether the target vehicle exists within the target range of the parking space, and determining detection information of the target vehicle; wherein the detection information includes: identity information of the target vehicle and parking time of the target vehicle within the target range; Tracking the target vehicle to obtain vehicle feature data; Determine the three-dimensional information of the target vehicle based on the vehicle characteristic data, and determine the motion data of the target vehicle based on the two-dimensional information in the parking space and the three-dimensional information; Determining the posture information according to the occupancy condition, the detection information and the motion data; wherein the posture information includes the entry state, parking state and exit state of the target vehicle; The movement trajectory of the target vehicle in the parking lot is tracked to obtain the trajectory information.

6. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: Dividing the parking lot into multiple sub-areas; Analyze the plurality of target status data in each sub-area to determine the remaining parking spaces in each sub-area; A guidance area for the newly added vehicle is determined according to the remaining conditions of the plurality of parking spaces and the entry position of the newly added vehicle.

7. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: Determining the vehicle type of the target vehicle by means of a detection device; The locking device in the parking space is controlled to be opened / closed based on the vehicle type and the target type of the parking space.

8. A computer program product, characterized in that The computer program product comprises a computer program / instruction, and when the computer program / instruction is executed by a processor, the steps in the method according to any one of claims 1 to 7 are implemented.

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