Urban parking prepayment revenue calculation method

Abstract

The application relates to a city parking prepayment income calculation method and system. The method comprises the following steps: establishing a parking prepayment basic data model, acquiring parking lot basic information, vehicle information and the like, acquiring vehicle parking order data through a parking information acquisition module, and generating a parking order; predicting parking fees by using a parking fee prediction module, calculating a prepayment amount by using a prepayment calculation module, and completing fund freezing; updating parking fees in real time during parking, completing final fee settlement after a vehicle leaves, statistically analyzing parking operation income, combining historical operation data to predict parking lot income trends, generating operation analysis results, and the system comprises a parking information acquisition module, a parking order management module, a prepayment calculation module, a dynamic fee updating module, a parking settlement module and an operation income prediction module. The application has the effects of improving parking fee accuracy, fund management efficiency and operation integrated management intelligent level.

Description

Technical Field

[0001] This application relates to the fields of smart parking, urban parking operation management, big data analysis and intelligent billing, and in particular to a method for calculating prepaid revenue for urban parking. Background Technology

[0002] With the rapid development of smart city construction and intelligent transportation systems, urban parking lots are gradually adopting information technologies such as automatic license plate recognition, mobile payment, and cloud platform management to realize intelligent parking fee collection and management. However, most parking lots still use a unified billing and settlement model after vehicles leave the parking lot. Although this can meet basic fee collection needs, it is easy to encounter problems such as long queues at the exit and long waiting times for payment during peak parking hours. This not only affects the efficiency of vehicle traffic but also reduces the overall operational efficiency of the parking lot.

[0003] On the other hand, existing prepaid parking methods typically involve prepaying a fixed amount or an amount chosen by the user. This lacks comprehensive analysis of factors such as parking duration, charging rules, historical parking behavior, and parking lot operations. This leads to significant discrepancies between prepaid amounts and actual parking costs. When the prepaid amount is insufficient, users are required to pay again, impacting departure efficiency. Conversely, excessively high prepaid amounts increase the refund process, affecting user experience and fund utilization efficiency. Furthermore, existing systems generally focus on parking fee collection, lacking real-time statistical analysis and operational revenue forecasting capabilities. This makes it difficult to promptly grasp the parking lot's operational status and provides effective data support for optimizing charging strategies, allocating parking space resources, and making operational decisions.

[0004] Regarding the aforementioned technologies, the inventors believe that a method and system for calculating urban parking prepaid revenue can be provided that combines parking fee prediction, intelligent calculation of prepaid amounts, dynamic updating of parking fees, automatic settlement, and statistical analysis of parking revenue with prediction of operating income. Summary of the Invention

[0005] To address the technical problems in existing technologies, such as inaccurate calculation of prepaid parking fees, inability to dynamically adjust parking costs based on actual parking processes, low efficiency of departure settlement, and insufficient statistical analysis and operational revenue forecasting capabilities, which lead to low efficiency in fund management, poor user experience, and difficulty in providing effective data support for parking lot operation decisions, this application provides a method for calculating prepaid parking revenue.

[0006] The technical solution for calculating prepaid parking revenue in this application is as follows: Firstly, a method for calculating prepaid parking revenue in cities includes the following steps: S1. Establish a basic data model for prepaid parking to obtain basic parking lot information, charging rules information, vehicle information, user account information, and historical parking information; S2. Obtain vehicle parking order data through the parking information collection module, and generate parking orders through the parking order management module; S3. Predict parking fees based on parking fee rules using the parking fee prediction module; S4. Calculate the prepayment amount based on the parking fee prediction results through the prepayment calculation module, and complete the fund freezing; S5. During the parking process, the parking fee is updated in real time through the dynamic fee update module; S6. After the vehicle leaves the parking lot, the final fee is calculated and automatically settled through the parking settlement module. S7. Calculate parking operation revenue through the revenue statistics and analysis module; S8. Analyze parking operation revenue trends and generate operation analysis results through the operation revenue forecasting module.

[0007] By adopting the above technical solutions, intelligent management of urban parking fees has been achieved throughout the entire process, from data collection, fee prediction, prepayment calculation, dynamic updates, automatic settlement to operational analysis. Establishing a basic data model for prepaid parking improves the accuracy of parking fee calculations; dynamic fee updates and automatic settlement mechanisms enhance collection efficiency; and combined with revenue statistics and profit prediction functions, data support is provided for parking operation management, thereby improving the level of intelligent parking management.

[0008] Optionally, the parking information collection module includes a vehicle identification unit, a parking space status collection unit, an entry information collection unit, and a departure information collection unit; The vehicle identification unit is used to identify vehicle identity information; The parking space status acquisition unit is used to obtain the parking space occupancy status; The entry information collection unit is used to acquire vehicle entry time and entry lane information; The departure information collection unit is used to obtain the vehicle departure time and departure information.

[0009] By adopting the above technical solutions, the entire process of collecting vehicle identity, parking location, entry and exit time, and parking status can be achieved, improving the accuracy and completeness of parking order data acquisition; at the same time, it provides a reliable data foundation for parking fee prediction, prepayment calculation, and automatic settlement upon departure, thereby improving the automation level of urban parking management and the efficiency of fee processing.

[0010] Optionally, the parking order management module includes an order generation unit, an order status management unit, and an order storage unit; The order generation unit is used to create parking orders based on vehicle entry information; The order status management unit is used to update the parking order status; The order storage unit is used to store parking order data.

[0011] By adopting the above technical solutions, automatic order creation, status updates, and data storage management of vehicle parking information can be achieved. This enables real-time tracking of order status throughout the entire process of vehicle entry, parking, and departure, improving the accuracy and continuity of parking order management. At the same time, it facilitates subsequent cost prediction, dynamic billing, automatic settlement, and operational data statistical analysis, thereby improving the efficiency of parking business processing.

[0012] Optionally, the parking fee prediction module includes a charging rule acquisition unit, a parking duration calculation unit, and a fee prediction unit; The charging rule acquisition unit is used to acquire parking charging rules; The parking duration calculation unit is used to calculate the parking duration of the vehicle; The cost prediction unit is used to predict parking costs based on the charging rules and parking duration.

[0013] By adopting the above technical solution, intelligent calculation of fees based on parking fee rules, estimated parking duration, and vehicle parking status can be achieved. This enables the prediction of potential parking fees at the initial stage of vehicle parking, improving the accuracy of prepayment calculation. At the same time, it reduces errors in manual estimation, providing a reliable basis for subsequent fund freezing, dynamic fee adjustment, and automatic settlement.

[0014] Optionally, the prepaid calculation module includes a prepaid amount calculation unit, a funds freezing unit, and a payment management unit; The prepayment calculation unit is used to calculate the prepayment amount for parking. The funds freezing unit is used to freeze the corresponding prepayment amount; The payment management unit is used to complete the prepayment payment and payment status management.

[0015] By adopting the above technical solutions, intelligent linkage management between parking fee prediction results and user payment accounts is achieved; the prepayment calculation unit accurately generates prepayment fees, the fund freezing unit ensures the validity of parking fee payments, and the payment management unit enables real-time management of fund status, thereby improving the automation and security of the parking fee collection process, avoiding congestion problems at the exit payment point, and providing reliable financial security for subsequent dynamic billing and automatic settlement.

[0016] Optionally, the dynamic cost update module includes a parking status monitoring unit, a cost dynamic correction unit, and an additional pre-authorization unit; The parking status monitoring unit is used to acquire parking status change information in real time; The dynamic fee correction unit is used to update the parking fee according to changes in parking status. The additional pre-authorization unit is used to execute additional pre-authorization when the parking fee exceeds the prepaid amount.

[0017] By adopting the above technical solution, the dynamic fee update module realizes real-time tracking and dynamic adjustment of fees during the parking process. It can automatically correct parking fees based on the actual parking time, changes in parking status, and changes in charging rules. When the actual fee exceeds the prepaid amount, the fee is supplemented by adding a pre-authorization unit, which improves the accuracy of billing and the continuity of payment, and avoids settlement abnormalities due to insufficient prepayment.

[0018] Optionally, the parking settlement module includes a final fee calculation unit, an automatic deduction unit, a refund processing unit, and a supplementary payment processing unit; The final cost calculation unit is used to calculate the final parking cost of the vehicle. The automatic deduction unit is used to automatically deduct parking fees. The refund processing unit is used to refund the remaining prepaid amount; The supplementary payment processing unit is used to pay any outstanding parking fees.

[0019] By adopting the above technical solutions, the parking settlement module realizes the functions of automatic calculation, automatic deduction and fund abnormality handling of parking fees. It can accurately calculate the final parking amount based on the actual parking time and fee changes of the vehicle. The automatic deduction unit improves the efficiency of departure payment, and the refund processing unit and supplementary payment processing unit realize the refund of overpayment and the supplementary payment of underpayment, ensuring the accuracy, flexibility and fund settlement security of the parking fee collection process.

[0020] Optionally, the revenue statistics and analysis module includes a revenue statistics unit, a payment channel statistics unit, and a report generation unit; The revenue statistics unit is used to calculate parking fee revenue; The payment channel statistics unit is used to compile revenue data for each payment channel; The report generation unit is used to generate parking revenue statistics reports.

[0021] By adopting the above technical solutions, the revenue statistics and analysis module realizes the automatic collection, classification, statistics and visualization analysis of parking operation revenue data; it obtains the total parking fee revenue through the revenue statistics unit, analyzes the revenue ratio of different payment methods through the payment channel statistics unit, and generates operation reports through the report generation unit, providing accurate data support for parking lot operation management, revenue analysis and operation strategy adjustment.

[0022] Optionally, the operating revenue forecasting module includes a historical data analysis unit, a revenue forecasting unit, and a risk warning unit; The historical data analysis unit is used to analyze historical parking operation data; The revenue forecasting unit is used to forecast parking operation revenue; The risk warning unit is used to generate parking operation risk warning information.

[0023] By adopting the above technical solutions, the operation revenue forecasting module enables in-depth analysis of historical parking operation data, prediction of future revenue trends, and early warning of operational risks. It utilizes the historical data analysis unit to uncover patterns in parking traffic and revenue, generates future operation revenue assessment results through the revenue forecasting unit, and promptly identifies potential operational risks through the risk warning unit. This provides data support for parking lot managers to formulate operational strategies, optimize resource allocation, and improve operating revenue.

[0024] Secondly, an urban parking prepaid revenue calculation system includes a parking information collection module, a parking order management module, a parking fee prediction module, a prepaid calculation module, a dynamic fee update module, a parking settlement module, a revenue statistical analysis module, an operating revenue prediction module, a user terminal, a parking lot management platform, a database, a payment platform, and a communication network. The parking information collection module is connected to the parking order management module and the parking fee prediction module, respectively. The parking order management module is connected to the prepaid calculation module, the dynamic fee update module, and the parking settlement module, respectively. The revenue statistics and analysis module is connected to the operating revenue forecasting module; The database is connected to the parking order management module, parking fee prediction module, prepayment calculation module, dynamic fee update module, parking settlement module, revenue statistics and analysis module, and operating revenue prediction module, respectively, and is used to store parking order data, charging data, and statistical analysis data. The payment platform is connected to the prepaid calculation module and the parking settlement module, and is used to complete parking fee freezing, deduction, refund and supplementary payment; The parking management platform and user terminals are connected to various functional modules via a communication network to display parking order information, payment information, revenue statistics, and operational analysis results. By adopting the above technical solutions, an intelligent parking prepaid revenue calculation system was constructed, integrating parking information collection, order management, cost prediction, prepayment calculation, dynamic billing, automatic settlement, and revenue analysis. Through data interaction between various functional modules, the system achieves digital management of the entire parking business process; it utilizes a database to uniformly store parking orders, fees, and operational data; and it completes fund freezing, deduction, refunds, and supplementary payments through a payment platform, improving the efficiency of fee processing; and it combines a parking lot management platform and user terminals to achieve information display and remote management, providing accurate data support for parking operation decisions.

[0025] In summary, this application includes at least one of the following beneficial technical effects: By establishing a basic data model for prepaid parking and combining it with parking information collection, parking order management, and parking fee prediction modules, comprehensive management of parking lot basic information, vehicle information, charging rules, and parking status data can be achieved, improving the accuracy of parking fee prediction and providing a reliable data foundation for prepaid calculation.

[0026] By setting up a prepaid calculation module, the prepaid amount is automatically calculated based on the predicted parking fee. The prepaid funds are managed using a fund freezing unit and a payment management unit, avoiding the queuing problem caused by traditional parking lot exit payment, thus improving parking fee collection efficiency and user parking experience.

[0027] By setting up a dynamic fee update module, the system can obtain real-time information on changes in parking status during vehicle parking and dynamically adjust parking fees based on actual parking duration and charging rules. At the same time, an additional pre-authorization mechanism ensures the continuity of fee payment, thereby improving the real-time performance and accuracy of parking billing.

[0028] By setting up a parking settlement module, the final cost after a vehicle leaves can be automatically calculated, automatically deducted, refunded, and supplemented if insufficient, making the parking fee collection process more intelligent, reducing the cost of manual fee collection and management, and improving parking operation efficiency.

[0029] By setting up a revenue statistics and analysis module, parking fee revenue, payment channel data, and operation reports can be automatically statistically analyzed to achieve digital management of parking operation revenue and provide accurate data for the analysis of parking lot operation.

[0030] By setting up an operational revenue forecasting module, historical parking operation data can be used to analyze parking flow and revenue trends, and operational risk warning information can be generated. This enables managers to anticipate operational risks, optimize parking resource allocation, and improve parking lot operational revenue.

[0031] By setting up a database, payment platform, parking management platform, and user terminals, and utilizing communication networks to achieve data interaction between various functional modules, an integrated closed-loop system for parking information collection, fee calculation, fund management, and operation analysis is formed, thereby improving the intelligence level and operational reliability of urban parking management. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating an overall method for calculating prepaid parking revenue according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the overall structure of an urban parking prepaid revenue calculation system according to an embodiment of the present invention.

[0033] Figure 3 This is a schematic diagram of a parking fee prediction and prepayment calculation process according to an embodiment of the present invention.

[0034] Figure 4 This is a schematic diagram of a dynamic fee update and departure settlement process according to an embodiment of the present invention.

[0035] Figure 5 This is a schematic diagram of a revenue statistical analysis and operating income forecasting process according to an embodiment of the present invention.

[0036] Figure labeling: 1. Urban Parking Prepaid Revenue Calculation System; 2. Parking Information Collection Module; 21. Vehicle Identification Unit; 22. Parking Space Status Collection Unit; 23. Entry Information Collection Unit; 24. Exit Information Collection Unit; 3. Parking Order Management Module; 31. Order Generation Unit; 32. Order Status Management Unit; 33. Order Storage Unit; 4. Parking Fee Prediction Module; 41. Fee Rule Acquisition Unit; 42. Parking Duration Calculation Unit; 43. Fee Prediction Unit; 5. Prepaid Calculation Module; 51. Prepaid Amount Calculation Unit; 52. Funds Freezing Unit; 53. Payment Management Unit; 6. Dynamic Fee Update Modules: 61. Parking Status Monitoring Unit; 62. Dynamic Fee Correction Unit; 63. Additional Pre-authorization Unit; 7. Parking Settlement Module; 71. Final Fee Calculation Unit; 72. Automatic Deduction Unit; 73. Refund Processing Unit; 74. Supplementary Payment Processing Unit; 8. Revenue Statistics and Analysis Module; 81. Revenue Statistics Unit; 82. Payment Channel Statistics Unit; 83. Report Generation Unit; 9. Operating Revenue Forecasting Module; 91. Historical Data Analysis Unit; 92. Revenue Forecasting Unit; 93. Risk Warning Unit; 10. User Terminal; 11. Parking Management Platform; 12. Database; 13. Payment Platform; 14. Communication Network. Detailed Implementation

[0037] The following is in conjunction with the appendix Figure 1-5 This application will be described in further detail.

[0038] This application discloses a method for calculating prepaid revenue from urban parking.

[0039] like Figures 1 to 5 As shown, this application provides a method and system for calculating prepaid parking revenue in urban parking scenarios. It is used to intelligently manage parking fee estimation, prepayment calculation, dynamic fee update, parking settlement, operating revenue statistics, and revenue trend prediction in urban parking scenarios. This is to solve the problems of inaccurate fee estimation, unreasonable prepayment setting, low efficiency of parking revenue statistics, and insufficient operating revenue analysis capabilities in the existing parking fee collection process. The urban parking prepaid revenue calculation system 1 includes a parking information collection module 2, a parking order management module 3, a parking fee prediction module 4, a prepayment calculation module 5, a dynamic fee update module 6, a parking settlement module 7, a revenue statistics and analysis module 8, an operating revenue prediction module 9, a user terminal 10, a parking lot management platform (11), a database 12, a payment platform 13, and a communication network 14. Among them, the parking information collection module 2, parking order management module 3, parking fee prediction module 4, prepayment calculation module 5, dynamic fee update module 6, parking settlement module 7, revenue statistics and analysis module 8, and operation revenue prediction module 9 establish data connections through the communication network 14, and realize unified storage and retrieval of parking data, order data, fee data, and operation analysis data through the database 12.

[0040] like Figure 1 As shown in the figure, the method for calculating prepaid parking revenue in cities provided in this application includes the following steps: S1. Establish a basic data model for prepaid parking. First, a basic data model for prepaid parking is established through the parking management platform 11 to obtain basic parking information, charging rules, vehicle information, user account information, and historical parking information. The basic parking information includes parking lot number, parking area, number of parking spaces, parking lot location, and operation and management information. The charging rules information includes charging standards for different time periods, free parking time, tiered charging rules, and discount rules. The vehicle information includes vehicle identification information, vehicle type, and user binding information. The user account information includes user identity information, payment account information, and historical consumption records. This prepaid parking data model provides a data foundation for subsequent parking fee prediction, prepaid amount calculation, and operational revenue analysis.

[0041] S2. Obtain parking order data and generate parking orders. After a vehicle enters the parking lot, its parking information is collected through the parking information collection module 2, such as... Figure 2As shown, the parking information collection module 2 includes a vehicle identification unit 21, a parking space status collection unit 22, an entry information collection unit 23, and an exit information collection unit 24. The vehicle identification unit 21 obtains vehicle identity information through a license plate recognition device. The parking space status collection unit 22 obtains the current parking space occupancy status through a parking space detection device. The entry information collection unit 23 is used to collect the time when the vehicle enters the parking lot, the entrance location, and lane information. The exit information collection unit 24 is used to collect the time information when the vehicle leaves the parking lot. After the collection is completed, the parking information is sent to the parking order management module 3. The parking order management module 3 includes an order generation unit 31, an order status management unit 32, and an order storage unit 33. The order generation unit 31 creates a corresponding parking order based on the vehicle entry information, the order status management unit 32 updates the order status in real time, and the order storage unit 33 stores the parking order information in the database 12.

[0042] Parking fee prediction and prepayment calculation process as follows Figure 3 As shown, the parking fee prediction module 4 is used to predict the parking fee of a vehicle according to the parking fee rules. The parking fee prediction module 4 includes a fee rule acquisition unit 41, a parking duration calculation unit 42, and a fee prediction unit 43. The fee rule acquisition unit 41 calls the corresponding parking lot fee rules from the database 12. The parking duration calculation unit 42 calculates the parking duration based on the vehicle's entry time and estimated exit time. The fee prediction unit 43 calculates the estimated parking fee of the vehicle by combining the fee rules and parking duration information. When a user enters the parking lot, the system predicts the parking fee that the user may incur based on the current time, historical parking duration data, and parking fee rules. After the prediction is completed, the prediction result is sent to the prepaid calculation module 5. The prepaid calculation module 5 includes a prepaid amount calculation unit 51, a fund freezing unit 52, and a payment management unit 53. The prepaid amount calculation unit 51 generates the user's prepaid amount based on the predicted parking fee. The fund freezing unit 52 calls the payment platform 13 to freeze the corresponding amount in the user's account. The payment management unit 53 records the prepaid payment status. Through the above methods, prepaid management after the vehicle enters the parking lot is realized, avoiding the problem of long waiting time for payment upon leaving the parking lot in traditional parking fees.

[0043] Dynamic fee updates during parking, such as Figure 4As shown, during vehicle parking, the parking fee is adjusted in real time through the dynamic fee update module 6. The dynamic fee update module 6 includes a parking status monitoring unit 61, a fee dynamic correction unit 62, and an additional pre-authorization unit 63. The parking status monitoring unit 61 continuously acquires the vehicle parking status, including parking duration, changes in parking area, and changes in charging rules. The fee dynamic correction unit 62 recalculates the current parking fee based on the real-time parking status. The additional pre-authorization unit 63 is used to perform additional pre-authorization on the user's payment account when the actual parking fee exceeds the prepaid amount. When the vehicle exceeds the originally estimated parking time, the system automatically increases the pre-authorization amount based on the increased parking duration, so that the parking fee calculation process remains continuous.

[0044] The automatic settlement process for vehicle departure is as follows: When a vehicle leaves the parking lot, the departure information collection unit 24 obtains the vehicle departure information and sends it to the parking settlement module 7. The parking settlement module 7 includes a final fee calculation unit 71, an automatic deduction unit 72, a refund processing unit 73, and a supplementary payment processing unit 74. The final fee calculation unit 71 calculates the final parking fee based on the vehicle's actual entry time, departure time, and charging rules. The automatic deduction unit 72 automatically deducts the corresponding parking fee through the payment platform 13. When the actual parking fee is less than the prepaid amount, the refund processing unit 73 refunds the remaining amount to the user's account. When the actual parking fee exceeds the prepaid amount, the supplementary payment processing unit 74 performs the supplementary payment operation. Through the above structure, automatic calculation and settlement of parking fees are achieved, improving parking fee collection efficiency.

[0045] The process of statistical analysis of parking revenue is as follows: Figure 5 As shown, the revenue statistics and analysis module 8 is used to perform statistical analysis on parking operation revenue. The revenue statistics and analysis module 8 includes a revenue statistics unit 81, a payment channel statistics unit 82, and a report generation unit 83. The revenue statistics unit 81 counts parking fee revenue based on parking order data in the database 12. The payment channel statistics unit 82 classifies and counts the revenue data generated by different payment methods. The report generation unit 83 generates parking revenue analysis reports based on the statistical results. Managers can view the real-time revenue of the parking lot through the parking lot management platform 11, thereby improving the efficiency of parking operation management.

[0046] The operational revenue forecasting module 9 is used to predict future revenue trends based on historical parking operation data. The operational revenue forecasting module 9 includes a historical data analysis unit 91, a revenue forecasting unit 92, and a risk warning unit 93. The historical data analysis unit 91 calls historical parking orders, revenue data, and vehicle flow data from the database 12. The revenue forecasting unit 92 analyzes future parking revenue trends based on historical operating patterns. The risk warning unit 93 generates operational risk warning information based on the revenue forecast results. When the predicted parking revenue continues to decline or the parking utilization rate drops abnormally, the system sends risk warning information to the parking lot management platform 11 so that managers can adjust their operational strategies in a timely manner.

[0047] In this embodiment, the parking information collection module 2 acquires vehicle parking information in real time, the parking order management module 3 establishes parking orders, the parking fee prediction module 4 predicts parking fees, the prepayment calculation module 5 freezes funds, the dynamic fee update module 6 adjusts fees in real time, the parking settlement module 7 completes the final collection, the revenue statistics and analysis module 8 performs operating revenue statistics, and the operating revenue prediction module 9 performs revenue trend analysis. The various functional modules interact with each other through the database 12 and the communication network 14, forming an intelligent closed-loop management process of: parking information collection → parking fee prediction → prepayment calculation → dynamic fee update → automatic settlement → revenue statistics → revenue prediction.

[0048] Through the above implementation methods, this application can achieve accurate prediction of urban parking fees, intelligent calculation of prepayment amounts, dynamic billing during parking, automatic settlement upon departure, and intelligent analysis of operating revenue. It solves the problems of low efficiency in fee calculation, difficulty in revenue statistics, and insufficient operational forecasting capabilities in existing parking management systems, thereby improving the level of intelligence and economic benefits of urban parking operation management.

[0049] The implementation principle of the urban parking prepaid revenue calculation method in this application embodiment is as follows: After a vehicle enters the parking lot, the vehicle identification information, parking space status information, entry time information and parking status information are first collected by the parking information collection module 2, and the collected data is transmitted to the parking order management module 3. The order generation unit 31 establishes the corresponding parking order, and the parking order status is updated in real time by the order status management unit 32. Subsequently, the parking fee prediction module 4 calls the corresponding parking fee rule according to the fee rule acquisition unit 41, and calculates the estimated parking duration in conjunction with the parking duration calculation unit 42, and generates the estimated parking fee through the fee prediction unit 43. The prepayment calculation module 5 calculates the user's prepayment amount through the prepayment amount calculation unit 51 based on the fee prediction result, and completes the prepayment fund freezing through the payment platform 13 using the fund freezing unit 52. During vehicle parking, the dynamic fee update module 6 continuously acquires information on changes in vehicle parking status through the parking status monitoring unit 61, and the dynamic fee correction unit 62 adjusts the parking fee in real time based on the actual parking duration and changes in the charging rules. When the actual fee exceeds the prepaid amount, the additional pre-authorization unit 63 executes an additional payment authorization to ensure the continuity of parking fee payment. When the vehicle leaves, the parking settlement module 7 calculates the actual parking fee through the final fee calculation unit 71 based on the vehicle departure data acquired by the departure information collection unit 24), and completes the fee deduction using the automatic deduction unit 72. In addition, when there is a surplus in the prepaid amount, the refund processing unit 73 completes the balance refund; when the prepaid amount is insufficient, the supplementary payment processing unit 74 completes the difference payment. At the same time, the revenue statistics and analysis module 8 performs statistical analysis on parking order data, charging data, and payment channel data, and generates a parking operation revenue report through the report generation unit 83; the operation revenue prediction module 9 further analyzes historical parking operation data based on the historical data analysis unit 91, predicts future operation revenue trends through the revenue prediction unit 92, and generates operation risk warning information using the risk warning unit 93; Through the above process, this application realizes intelligent management of the entire process of parking fee prediction, prepayment fund management, dynamic fee adjustment, automatic settlement and operation revenue analysis, forming a data closed loop from parking data collection and fee calculation to operation decision analysis, thereby improving the efficiency of urban parking fee management, the accuracy of fee calculation and the level of intelligent parking operation.

[0050] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for calculating prepaid revenue from urban parking, characterized in that, Includes the following steps: S1. Establish a basic data model for prepaid parking to obtain basic parking lot information, charging rules information, vehicle information, user account information, and historical parking information; S2. Obtain vehicle parking order data through the parking information collection module (2), and generate parking orders through the parking order management module (3); S3. Predict parking fees according to parking fee rules using the parking fee prediction module (4); S4. Calculate the prepayment amount based on the parking fee prediction results through the prepayment calculation module (5) and complete the fund freeze; S5. During the parking process, the parking fee is updated in real time through the dynamic fee update module (6); S6. After the vehicle leaves the parking lot, the final cost calculation and automatic settlement are completed through the parking settlement module (7); S7. Calculate parking operation revenue through the revenue statistics and analysis module (8); S8. Analyze the parking operation revenue trend through the operation revenue prediction module (9) and generate operation analysis results.

2. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The parking information collection module (2) includes a vehicle identification unit (21), a parking space status collection unit (22), an entry information collection unit (23), and a departure information collection unit (24). The vehicle identification unit (21) is used to identify vehicle identity information; The parking space status acquisition unit (22) is used to acquire the parking space occupancy status; The entry information collection unit (23) is used to acquire vehicle entry time and entry lane information; The departure information acquisition unit (24) is used to acquire the vehicle departure time and departure information.

3. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The parking order management module (3) includes an order generation unit (31), an order status management unit (32), and an order storage unit (33). The order generation unit (31) is used to create a parking order based on the vehicle entry information; The order status management unit (32) is used to update the parking order status; The order storage unit (33) is used to store parking order data.

4. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The parking fee prediction module (4) includes a charging rule acquisition unit (41), a parking duration calculation unit (42), and a fee prediction unit (43). The charging rule acquisition unit (41) is used to acquire parking charging rules; The parking duration calculation unit (42) is used to calculate the parking duration of the vehicle; The cost prediction unit (43) is used to predict parking costs based on the charging rules and parking duration.

5. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The prepaid calculation module (5) includes a prepaid amount calculation unit (51), a fund freezing unit (52), and a payment management unit (53). The prepayment calculation unit (51) is used to calculate the parking prepayment amount; The fund freezing unit (52) is used to freeze the corresponding prepayment amount; The payment management unit (53) is used to complete the prepayment and payment status management.

6. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The dynamic cost update module (6) includes a parking status monitoring unit (61), a cost dynamic correction unit (62), and an additional pre-authorization unit (63). The parking status monitoring unit (61) is used to acquire parking status change information in real time; The fee dynamic correction unit (62) is used to update the parking fee according to changes in parking status; The additional pre-authorization unit (63) is used to perform additional pre-authorization when the parking fee exceeds the prepaid amount.

7. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The parking settlement module (7) includes a final fee calculation unit (71), an automatic deduction unit (72), a refund processing unit (73), and a supplementary payment processing unit (74). The final cost calculation unit (71) is used to calculate the final parking cost of the vehicle; The automatic deduction unit (72) is used to automatically deduct parking fees; The refund processing unit (73) is used to refund the remaining prepaid amount; The supplementary payment processing unit (74) is used to pay the shortfall in parking fees.

8. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The revenue statistics and analysis module (8) includes a revenue statistics unit (81), a payment channel statistics unit (82), and a report generation unit (83). The revenue statistics unit (81) is used to count parking fee revenue; The payment channel statistics unit (82) is used to collect revenue data for each payment channel; The report generation unit (83) is used to generate parking revenue statistics reports.

9. The method for calculating prepaid revenue for urban parking according to claim 1, characterized in that: The operating revenue forecasting module (9) includes a historical data analysis unit (91), a revenue forecasting unit (92), and a risk warning unit (93). The historical data analysis unit (91) is used to analyze historical parking operation data; The revenue forecasting unit (92) is used to forecast parking operation revenue; The risk warning unit (93) is used to generate parking operation risk warning information.

10. A system for calculating prepaid parking revenue in urban areas, characterized in that, It includes a parking information collection module (2), a parking order management module (3), a parking fee prediction module (4), a prepayment calculation module (5), a dynamic fee update module (6), a parking settlement module (7), a revenue statistics and analysis module (8), an operating revenue prediction module (9), a user terminal (10), a parking lot management platform (11), a database (12), a payment platform (13), and a communication network (14). The parking information collection module (2) is connected to the parking order management module (3) and the parking fee prediction module (4) respectively; The parking order management module (3) is connected to the prepaid calculation module (5), the dynamic fee update module (6), and the parking settlement module (7), respectively. The revenue statistics and analysis module (8) is connected to the operating revenue forecast module (9); The database (12) is connected to the parking order management module (3), parking fee prediction module (4), prepaid calculation module (5), dynamic fee update module (6), parking settlement module (7), revenue statistical analysis module (8) and operating revenue prediction module (9) respectively, and is used to store parking order data, charging data and statistical analysis data; The payment platform (13) is connected to the prepaid calculation module (5) and the parking settlement module (7) to complete the freezing, deduction, refund and supplementary payment of parking fees; The parking management platform (11) and user terminal (10) are connected to each functional module through a communication network (14) to display parking order information, charging information, revenue statistics results and operation analysis results.

Images