Unmanned parking charging system and method

Abstract

The invention relates to the technical field of parking lot operation, in particular to an unmanned parking charging system and method, and the system comprises a license plate recognition module, a parking space distribution and navigation module, a vehicle in-place detection module, a vehicle behavior monitoring module, a service demand analysis module, and a fee calculation module. According to the invention, through the real-time image acquisition and license plate recognition technology, automatic recognition and recording of vehicle information are realized, the admission flow processing capability of the parking lot is improved, parking spaces are dynamically distributed according to the predetermined parking time of the target vehicle and the real-time parking space condition, the time for finding the parking spaces by the vehicle is shortened, the congestion is reduced, and the parking efficiency is improved. By means of real-time monitoring of vehicle behaviors and automatic recording of service use, the prediction capacity of parking demands and service demands is improved, dynamic adjustment of parking and service fees is achieved, flexibility of income management is enhanced, service quality is optimized and user experience is enhanced in combination with automatic bill information sending and monitoring, and user experience is improved. And the manpower demand and the operation cost are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of parking lot operation, and in particular to an unmanned parking charging system and method. Background Art

[0002] The parking lot operation technology field aims to use a variety of automation and information technologies to manage and optimize multiple aspects of parking facilities, including vehicle access control, parking space allocation, fee calculation and collection, customer service and vehicle safety management. It uses license plate recognition, RFID technology, mobile payment integration and real-time data analysis tools to improve the operational efficiency of parking lots, reduce manpower requirements and provide a safe, fast and user-friendly parking experience. It combines parking space reservation systems and dynamic pricing mechanisms to optimize space utilization and operating returns, realize automated and intelligent operation management, and meet the growing urban parking demand.

[0003] Among them, the unmanned parking billing system focuses on the design and implementation of automated management and billing of the parking process, enabling vehicles to automatically identify vehicles entering and leaving the parking lot without human intervention, calculate parking fees, and support automated payment processing. It aims to simplify the parking process, reduce human resource requirements in the parking lot, improve the operational efficiency of the parking lot, and optimize the accuracy and efficiency of charging. Through license plate recognition, time calculation, rate application and automatic payment, it manages the entry and exit of vehicles and ensures the transparency and fairness of the charging process. Combined with applications or self-service terminals, it provides user-friendly interaction methods and enhances customer experience.

[0004] Traditional unmanned parking and billing technology is not capable of handling vehicle flows and complex scenarios during peak hours. It lacks a sufficiently flexible mechanism for the dynamic allocation of parking spaces and real-time fee calculation to cope with rapidly changing demand and vehicle flows. It is also not capable of integrating real-time data processing and long-term operational data analysis, resulting in poor parking space utilization and prolonged service response times, affecting the operational efficiency of parking lots. In the absence of accurate prediction of parking space demand and adjustment of fee strategies, parking space resources may be wasted or excessively congested, affecting user experience and leading to revenue loss. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an unmanned parking charging system and method.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme, an unmanned parking charging system comprises: The license plate recognition module is based on real-time image acquisition equipment, which collects image information of vehicles entering the parking lot, recognizes vehicle information by analyzing the license plate image, and records the type and size of the vehicle to generate a vehicle entry record; The parking space allocation and navigation module allocates a parking space for the target vehicle based on the vehicle entry record, according to the vehicle size and scheduled parking time, taking into account the parking space usage status and charging pile usage requirements, and sends navigation information to the user to generate parking navigation instructions; The vehicle arrival detection module identifies the wrongly parked vehicle by analyzing the parking posture of the vehicle in the parking space based on the parking navigation instruction, sends a prompt message to the user, and generates a vehicle parking status record; The vehicle behavior monitoring module monitors the behavior of the vehicle in the parking lot in real time based on the vehicle parking status record, records the type and time information of the service, and generates a service usage record; The service demand analysis module performs time series analysis on the operation data of the parking lot based on the service usage record, predicts the parking space and service demand of the parking lot, adjusts the fees, and generates a pricing table adjustment record; The fee calculation module adjusts the records based on the pricing table, calculates the parking fee according to the vehicle behavior, sends the bill information to the user, and generates a parking billing information record.

[0007] As a further solution of the present invention, the vehicle entry record includes vehicle type identification information, vehicle volume and size information, and license plate number information; the vehicle parking navigation instruction includes parking space number allocation results, optimal driving path calculation results, and estimated arrival time point information at the parking space; the vehicle parking status record includes vehicle parking image information, parking posture analysis results, and incorrect parking prompt information; the service usage record includes charging service time record, car wash service usage information, and vehicle usage record information; the pricing table adjustment record includes predicted parking space occupancy rate, service demand trend prediction data, and fee adjustment record; the parking billing information record includes parking time calculation results, service fee calculation data, and bill payment status record.

[0008] As a further solution of the present invention, the license plate recognition module includes: The image information acquisition submodule is based on real-time image acquisition equipment to collect image data of vehicles entering the parking lot in real time, identify and record the vehicle's license plate number, and generate number information recognition records; The vehicle size analysis submodule identifies the type and size of the target vehicle based on the number information recognition record and generates vehicle identification data by analyzing the vehicle image; The time information recording submodule analyzes the parking space type required by the vehicle based on the vehicle identification data, records the vehicle's entry time, and generates a vehicle entry record.

[0009] As a further solution of the present invention, the parking space allocation and navigation module includes: The position calculation submodule allocates a parking space for the target vehicle based on the vehicle entry record, according to the vehicle size information and the scheduled parking time, taking into account the real-time parking space usage and charging requirements, and generates a parking space allocation result; The path planning submodule calculates the optimal driving path between the parking lot entrance and the target parking space based on the parking space allocation result and takes into account path congestion, and generates navigation path calculation information; The navigation information sending submodule sends navigation instructions to the user's mobile device and vehicle system based on the navigation path calculation information, including direction prompts and estimated arrival time of the turning point, and generates vehicle parking navigation instructions.

[0010] As a further solution of the present invention, the vehicle arrival detection module includes: The posture analysis submodule generates parking image information by collecting images of the vehicle in the target parking space in real time based on the vehicle parking navigation instruction and analyzing the parking angle and position of the vehicle; The error detection submodule, based on the parking image information, determines whether the vehicle exceeds the parking space line by evaluating the position of the vehicle relative to the parking space boundary, detects whether the target vehicle meets the parking regulations, records the wrongly parked vehicles, and generates the wrong parking detection result; The status recording submodule sends a wrong parking prompt message to the target user based on the wrong parking detection result, records the parking status of the vehicle, calculates the parking time, and generates a vehicle parking status record.

[0011] As a further solution of the present invention, the vehicle behavior monitoring module includes: The vehicle activity recording submodule monitors the vehicle activities in the parking lot in real time based on the vehicle parking status record, records the vehicle information of using the charging pile and entering the car wash area, and generates a service activity identification result; The vehicle behavior recording submodule records the types and times of the services used by multiple vehicles based on the service activity identification results, including the charging usage time and the car wash service type, and generates a service behavior recording result; The data statistics analysis submodule calculates the usage frequency and average usage duration of various services based on the service behavior record results, analyzes the usage frequency and type of services by various vehicles, evaluates the preferences of various vehicles for service types, and generates service usage records.

[0012] As a further solution of the present invention, the service demand analysis module includes: The operation data collection submodule collects and records the operation data of the parking lot, including parking space and service usage data, based on the service usage record, and generates an operation data collection record; The demand fluctuation assessment submodule predicts the demand fluctuation of parking spaces and services, including the demand changes of charging and car washing services, and generates demand forecast results by performing time series analysis on the operation data based on the operation data collection records; The charging standard adjustment submodule adjusts the fees for parking spaces and various services based on the demand forecast results, according to the demand forecast data, taking into account market conditions and consumer sensitivity, and generates a pricing table adjustment record.

[0013] As a further solution of the present invention, the fee calculation module includes: The parking fee analysis submodule calculates parking fees for multiple users based on the adjustment records of the pricing table, according to the parking time and parking status of the vehicle, combined with the type of service used and the difference in fees for multiple time periods, and generates a parking fee calculation result; The bill content generation submodule matches bill information for multiple users based on the parking fee calculation result, including service fees, parking fees and overdue fees, and generates a bill content matching record; The bill status monitoring submodule sends bill information to the user based on the bill content matching record, monitors the payment status of the bill in real time, records the bill completion information, and generates parking billing information records.

[0014] As a further solution of the present invention, the specific formula for calculating parking fees for multiple users is: ; Among them, C represents the calculated parking fee, which is determined according to the parking time, service usage, parking status and time period. T represents the length of time the vehicle is parked, in hours, which is the basic part affecting the fee. CS represents the use of charging service, reflecting whether the charging service is used and the impact on the fee. WS represents the use of car wash service, reflecting whether the car wash service is used and the impact on the fee. P represents the parking status adjustment coefficient of the vehicle, considering whether the parking posture of the vehicle is standardized and whether it is parked in the designated area. D represents the time period of day or night, reflecting the difference in rates in different time periods. is the intercept of the model, representing the base parking fee, the starting fee without any additional factors. is the coefficient of the time variable, is the rate coefficient of the charging service, which shows the increase in the total cost due to the use of the charging service. is the rate factor of the car wash service, which shows the increase in total cost caused by using the car wash service. is the adjustment factor for parking status, which measures the impact of irregular parking on fees. It is the time period coefficient, which indicates the impact of different time periods on the fee. The formula reflects the impact of different service usage and parking behaviors on parking fees, and provides a flexible billing method.

[0015] An unmanned parking charging method is implemented based on the unmanned parking charging system, and comprises the following steps: S1: Use real-time image acquisition equipment to collect image information of vehicles entering the parking lot, identify license plate numbers, record vehicle models and sizes, and generate vehicle identification information; S2: Based on the vehicle identification information, taking into account the vehicle size and the scheduled parking time, by analyzing the parking space usage and the vehicle charging demand, allocating the parking position, calculating the path between the entrance and the target parking space and sending navigation information to the user, and generating parking space allocation information; S3: Using the parking space allocation information, detecting the parking posture of the vehicle in the parking space in real time, sending an incorrect parking prompt message to the user, and generating parking status verification information; S4: Based on the parking status verification information, real-time monitoring of vehicle activities in the parking lot, including use of charging piles and car wash services, recording service types and usage durations, and generating service behavior analysis results; S5: Based on the service behavior analysis results, by performing time series analysis on the parking lot's operational information, the fluctuations in parking space and service demand are predicted, and pricing standards are adjusted to calculate parking fees for multiple vehicles, and bills are sent to vehicle owners to generate parking billing information records.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, through real-time image acquisition and license plate recognition technology, automatic recognition and recording of vehicle information are realized, the parking lot's entrance flow processing capacity is improved, parking spaces are dynamically allocated according to the target vehicle's scheduled parking time and real-time parking space status, the time and congestion of vehicles searching for parking spaces are reduced, and the real-time monitoring of vehicle behavior and automated recording of service usage are utilized to improve the ability to predict parking demand and service demand, realize dynamic adjustment of parking and service fees, enhance the flexibility of revenue management, and combine automated bill information sending and monitoring to optimize service quality and enhance user experience, thereby reducing manpower requirements and operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a system flow chart of the present invention; Figure 2 It is a schematic diagram of the system framework of the present invention; Figure 3 It is a flow chart of the license plate recognition module of the present invention; Figure 4This is a flow chart of the parking space allocation and navigation module of the present invention; Figure 5 This is a flow chart of the vehicle arrival detection module of the present invention; Figure 6 The vehicle behavior monitoring module flow chart of the present invention; Figure 7 It is a flow chart of the service demand analysis module of the present invention; Figure 8 It is a flow chart of the cost calculation module of the present invention; Fig. 9 It is a schematic diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0020] Embodiment 1 See also Figure 1 to Figure 2 The present invention provides a technical solution, an unmanned parking charging system comprising: The license plate recognition module is based on real-time image acquisition equipment, which collects image information of vehicles entering the parking lot, recognizes vehicle information by analyzing the license plate image, and records the type and size of the vehicle to generate a vehicle entry record; The parking space allocation and navigation module allocates parking spaces for target vehicles based on vehicle entry records, vehicle size, scheduled parking time, parking space usage, and charging pile usage requirements, and sends navigation information to users to generate parking navigation instructions. The vehicle arrival detection module analyzes the parking posture of the vehicle in the parking space based on the parking navigation instructions, identifies the wrongly parked vehicle, sends a prompt message to the user, and generates a vehicle parking status record; The vehicle behavior monitoring module monitors the behavior of vehicles in the parking lot in real time based on the vehicle parking status records, records the type and time information of the service, and generates service usage records; The service demand analysis module conducts time series analysis on the parking lot’s operational data based on service usage records, predicts parking lot space and service demand, adjusts fees, and generates pricing table adjustment records; The fee calculation module adjusts the records based on the pricing table, calculates the parking fee according to the vehicle behavior, sends the bill information to the user, and generates the parking billing information record.

[0021] Vehicle entry records include vehicle type identification information, vehicle volume and size information, and license plate number information. Vehicle parking navigation instructions include parking space number allocation results, optimal driving path calculation results, and estimated arrival time information at the parking space. Vehicle parking status records include vehicle parking image information, parking posture analysis results, and incorrect parking prompt information. Service usage records include charging service time records, car wash service usage information, and vehicle usage record information. Pricing table adjustment records include predicted parking space occupancy rate, service demand trend forecast data, and fee adjustment records. Parking billing information records include parking time calculation results, service fee calculation data, and bill payment status records.

[0022] See also Figure 2 and Figure 3 , the license plate recognition module includes: The image information acquisition submodule is based on real-time image acquisition equipment to collect image data of vehicles entering the parking lot in real time, identify and record the vehicle's license plate number, and generate number information recognition records; In the image information acquisition submodule, real-time image acquisition equipment is used to continuously monitor and collect images of vehicles entering the parking lot. Image processing technology is used to screen the original image data and filter out low-quality images affected by light and weather factors to ensure that the processed images are clear and usable. After the image is cleaned, the license plate recognition algorithm is used to identify the license plate in the image. The license plate position is located using edge detection technology. Optical character recognition technology is used to adjust the accuracy parameters of character segmentation and extract the text on the license plate. The license plate number is stored in the database after identification to generate a number information recognition record.

[0023] The vehicle size analysis submodule identifies the type and size of the target vehicle based on the number information recognition record, and generates vehicle identification data by analyzing the vehicle image; In the vehicle size analysis submodule, the record is identified according to the received number information, and the size analysis is performed on the vehicle image in the record. The analysis determines the outline of the vehicle by applying the image segmentation algorithm, performs grayscale conversion on the image, and extracts the vehicle outline using a threshold-based segmentation method. After analyzing the vehicle outline, the length, width and height of the vehicle are measured using geometric parameter calculation technology. The type of vehicle, including sedan, SUV or truck, is determined by geometric dimensions combined with a preset vehicle type and size database. The type and size information of the vehicle is used to generate vehicle identification data. The data records the specific model and volume category of each vehicle, providing basic data for subsequent parking space allocation and vehicle management.

[0024] The time information recording submodule analyzes the parking space type required by the vehicle based on the vehicle identification data, records the vehicle's entry time, and generates a vehicle entry record; In the time information recording submodule, vehicle identification data is used to analyze and determine the parking space type suitable for each vehicle. The parking space size is selected according to the type and volume of the vehicle, including small parking spaces or large parking spaces. The parking space allocation algorithm dynamically adjusts the parking space allocation strategy according to the vehicle size and predicted parking demand. When a vehicle enters the parking lot, the vehicle's entry time is recorded, and the vehicle entry record is generated in combination with the vehicle's license plate number and parking space type. The record includes the time point of the vehicle's entry and the allocated parking space, providing necessary data support for optimizing vehicle flow and space management in the parking lot, ensuring the effective use of parking resources, and realizing efficient operation of the parking lot.

[0025] See also Figure 2 and Figure 4 , the parking space allocation and navigation module includes: The position calculation submodule allocates parking spaces to target vehicles based on vehicle entry records, according to vehicle size information and scheduled parking time, taking into account real-time parking space usage and charging requirements, and generates parking space allocation results; In the position calculation submodule, the vehicle entry record is received, which includes the vehicle's size information and scheduled parking time, and the real-time parking space usage is checked. The current occupancy status of each parking space is obtained through the parking space status monitoring system. A dynamic allocation algorithm is used to match the vehicle with a parking space based on the vehicle size and charging requirements. The algorithm includes the matching degree between the vehicle's length, width, and height information and the parking space size, the conflict check between the scheduled time and the current occupancy time of the parking space, and the compatibility of the vehicle's charging type with the parking space charging facilities. The parking space allocation algorithm adopts priority arrangement, giving priority to vehicles with charging requirements and vehicles with long-term reservations. After the allocation is completed, the parking space allocation result is generated, including the allocated parking space number and the estimated idle time.

[0026] The path planning submodule calculates the optimal driving path between the parking lot entrance and the target parking space based on the parking space allocation results and takes into account path congestion, and generates navigation path calculation information; In the path planning submodule, based on the received parking space allocation results, a graph search algorithm is used to calculate the optimal driving path from the parking lot entrance to the target parking space. Taking into account the path congestion in the parking lot, real-time traffic flow data is introduced, and the Dijkstra algorithm is used to search for the shortest path. The algorithm considers the current traffic flow of each channel and the predicted short-term traffic flow changes to avoid high congestion areas. During the calculation process, the driving time of each section is dynamically adjusted according to the traffic density to ensure the real-time optimality of the path. After the path calculation is completed, the navigation path calculation information is generated, including the route map of the selected path and the estimated driving time of each section. The information is used to send navigation information.

[0027] The navigation information sending submodule sends navigation instructions to the user's mobile device and vehicle system based on the navigation path calculation information, including direction prompts and estimated arrival time of the turning point, and generates vehicle parking navigation instructions; In the above content, the estimated arrival time is calculated according to the formula , calculate the arrival time; In the formula, t represents the estimated arrival time, d represents the distance from the parking lot entrance to the target parking space, v represents the average speed of the vehicle, and c represents the congestion factor; Detailed explanation of the formula and the process of formula calculation and derivation: Considering the actual driving conditions in the parking lot, assuming that the distance d from the parking lot entrance to the target parking space is 300 meters, the average speed v of the vehicle is 2.78 meters per second, and the congestion factor c is 0.1, the calculation is as follows: ; The result t = 118.7 seconds indicates that under conditions of slight congestion, the driver is expected to reach the target parking space within 119 seconds.

[0028] See also Figure 2 and Figure 5 , the vehicle arrival detection module includes: The posture analysis submodule generates parking image information by collecting images of the vehicle in the target parking space in real time based on the vehicle parking navigation instructions and analyzing the parking angle and position of the vehicle; In the posture analysis submodule, according to the vehicle parking navigation instructions, the system collects image data of the vehicle in the target parking space in real time through the high-resolution camera in the parking lot. Using the deep learning image processing algorithm, the submodule analyzes the parking angle and position of the vehicle relative to the parking space. The algorithm pre-processes the collected images, including noise reduction and brightness adjustment, to improve the image quality, and uses the edge detection technology based on the convolutional neural network to determine the outer contour of the vehicle. The relative position and angle of the vehicle and the parking space are calculated through geometric analysis, including the sensitivity of edge recognition and the accuracy of angle calculation. After the analysis is completed, the parking image information is generated. The information records the position and angle data of the vehicle for use by the subsequent error detection submodule.

[0029] The error detection submodule is based on the parking image information. It evaluates the position of the vehicle relative to the parking space boundary, determines whether it exceeds the parking space line, detects whether the target vehicle meets the parking regulations, records the wrongly parked vehicles, and generates the wrong parking detection results. In the above content, the position of the vehicle relative to the parking space boundary is evaluated according to the formula , calculate the distance the vehicle deviates from the center; In the formula, e represents the distance the vehicle deviates from the center, and represents the coordinates of the center point of the vehicle, and Represents the coordinates of the center point of the parking space boundary; Detailed explanation of the formula and the process of formula calculation and derivation: Assume that the coordinates of the center point of the vehicle are (2,3) meters, and the coordinates of the center point of the parking space boundary are (2.5,3.5) meters. The calculation is as follows: ; The result e = 0.71 meters indicates that the distance between the center of the vehicle and the center of the parking space boundary is 0.71 meters. The distance is used to determine whether the vehicle exceeds the parking space line and meets the parking regulations.

[0030] The status recording submodule sends a wrong parking reminder message to the target user based on the wrong parking detection result, records the parking status of the vehicle, calculates the parking time, and generates a vehicle parking status record; In the status recording submodule, based on the wrong parking detection results, the contact information of the vehicle and the owner to which the reminder needs to be sent is determined, and the reminder information of the wrong parking is sent to the target user, including the details of the parking error and the message of correction suggestions. The parking status of the vehicle is recorded, including the parking time, location and any violation records. The parking time is calculated based on the timestamps of the vehicle entering and leaving the parking space. The data is recorded in the vehicle parking status record for management and statistical analysis.

[0031] See also Figure 2 and Figure 6, the vehicle behavior monitoring module includes: The vehicle activity record submodule monitors the activities of vehicles in the parking lot in real time based on the vehicle parking status record, records the information of vehicles using charging piles and entering the car wash area, and generates service activity recognition results; In the vehicle activity recording submodule, the system monitors the activities of vehicles in the parking lot in real time, including identifying vehicles using charging piles and entering the car wash area. It collects data through sensors and cameras installed at charging piles and car wash areas, identifies service activities, and uses event detection algorithms to identify the time points when vehicles enter and leave the service location. It also matches the vehicle's license plate number through the vehicle identification system. The algorithm accurately records the start and end time of each vehicle using a specific service and generates service activity identification results. The results illustrate the specific service usage of each vehicle in the parking lot, providing a basis for subsequent behavior records.

[0032] The vehicle behavior record submodule records the types and times of multiple vehicle service usage based on the service activity recognition results, including charging usage time and car wash service types, and generates service behavior record results; In the vehicle behavior record submodule, based on the service activity identification results, the types and times of different services used by the vehicle are recorded in detail. Database query technology is used to process and store various service activity data, including the vehicle's stay time at the charging station and the type of charging used, and the type of service in the car wash area, such as standard car wash or deep cleaning. The frequency and periodicity of service use are analyzed through time series analysis methods to generate service behavior record results, which include the specific usage time of the service, the order of service use and the time distribution.

[0033] The data statistics analysis submodule calculates the usage frequency and average usage duration of various services based on the service behavior record results, analyzes the usage frequency and types of services by various vehicles, evaluates the preferences of various vehicles for service types, and generates service usage records; In the above content, the usage frequency and average usage time of various services are calculated according to the formula and , calculate the service usage frequency and average usage duration respectively; In the formula, f represents the frequency of service use, N represents the number of times the target service is used, and T represents the total monitoring time; Represents the average usage time, Represents the total usage time of all services; Detailed explanation of the formula and the process of formula calculation and derivation: Assume that in one month, the charging service is used 150 times, the total monitoring time T is 720 hours, and the total usage time of all charging services is 450 hours. Calculate the service usage frequency: ; Calculate the average usage time: ; The result is f = 0.208 and =3 indicates that the frequency of use of the charging service is 0.208 times per hour, and the average usage time is 3 hours. The data helps evaluate service efficiency and customer preferences, and provides basic information for service optimization and adjustment.

[0034] See also Figure 2 and Figure 7 , the service demand analysis module includes: The operation data collection submodule collects and records the operation data of the parking lot, including parking space and service usage data, based on the service usage records, and generates operation data collection records; In the operational data collection submodule, the system centrally collects the operational data of the parking lot based on the service usage records, and uses the database management system to record the usage of each parking space and the frequency and duration of use of various services, including the use of charging piles and car wash services. By setting up data collection points, including parking space sensors and service area cameras, the parking space occupancy and service area activities are monitored in real time. During the data collection process, batch processing technology is used to regularly extract data from the monitoring system to ensure timely updating and accuracy of information. The generated operational data collection records show the usage status and service fluidity of the parking lot. The information provides a data basis for optimizing operational strategies and improving user satisfaction.

[0035] The demand fluctuation assessment submodule is based on the operation data collection records. By performing time series analysis on the operation data, it predicts the demand fluctuations of parking spaces and services, including the demand changes of charging and car washing services, and generates demand forecast results. In the demand fluctuation assessment submodule, time series analysis technology is applied to predict the demand fluctuations of parking spaces and services based on the operational data collection records. The autoregressive moving average model is used to analyze historical data to predict the changes in demand for charging and car washing services in a specific period in the future. The impact of seasonal factors and changes in economic indicators on demand is considered to ensure the accuracy and practicality of the forecast results, and generate demand forecast results. The results reveal the potential growth or decline trend of various service demands in the future, providing decision support for parking lot management.

[0036] The charging standard adjustment submodule adjusts the fees for parking spaces and various services based on the demand forecast results, taking into account market conditions and consumer sensitivity, and generates pricing table adjustment records; In the above content, the charging standards are adjusted according to the demand forecast data, according to the formula , generate pricing table adjustment records; Where P represents the adjusted price, represents the base price, k represents the price sensitivity coefficient, Represents the change in demand; Detailed explanation of the formula and the process of formula calculation and derivation: Setting base parking fees The forecasted increase in demand is 10 yuan. is 20%, and the price sensitivity coefficient k is 0.5, which is calculated as follows: P = 10 + 0.5 × (20% × 10) = 10 + 1 = 11 yuan; The result P=11 yuan indicates that according to the predicted increase in demand, the adjusted parking service fee is 11 yuan per time. This pricing strategy is designed to respond to changes in market demand while taking into account consumers' price sensitivity in order to maintain the competitiveness and market share of the service.

[0037] See also Figure 2 and Figure 8 , the cost calculation module includes: The parking fee analysis submodule calculates parking fees for multiple users based on the adjustment records of the pricing table, according to the parking time and parking status of the vehicle, combined with the type of service used and the difference in fees for multiple time periods, and generates parking fee calculation results; The specific formula for calculating parking fees for multiple users is: ; Among them, C represents the calculated parking fee, which is determined according to the parking time, service usage, parking status and time period. T represents the length of time the vehicle is parked, in hours, which is the basic part affecting the fee. CS represents the use of charging service, reflecting whether the charging service is used and the impact on the fee. WS represents the use of car wash service, reflecting whether the car wash service is used and the impact on the fee. P represents the parking status adjustment coefficient of the vehicle, considering whether the parking posture of the vehicle is standardized and whether it is parked in the designated area. D represents the time period of day or night, reflecting the difference in rates in different time periods. is the intercept of the model, representing the base parking fee, the starting fee without any additional factors. is the coefficient of the time variable, is the rate coefficient of the charging service, which shows the increase in the total cost due to the use of the charging service. is the rate factor of the car wash service, which shows the increase in total cost caused by using the car wash service. is the adjustment factor for parking status, which measures the impact of irregular parking on fees. It is the time period coefficient, which indicates the impact of different time periods on the fee. The formula reflects the impact of different service usage and parking behaviors on parking fees, and provides a flexible billing method.

[0038] formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: The formula uses information about the vehicle’s parking time, service type, parking status, and time period to calculate parking fees; Parameter meaning and setting value: It is the basic fee, assumed to be 5.00 yuan, indicating the starting price when there are no other influencing factors.

[0039] is the time coefficient, assuming it is 2.00 yuan / hour, reflecting the increase in fees for each additional hour of parking time. is the charging service coefficient, which is assumed to be 15.00 yuan, reflecting the additional cost of using the charging service. is the car wash service coefficient, which is assumed to be 10.00 yuan, reflecting the additional cost of using the car wash service. is the parking status adjustment factor, which is assumed to be -1.00 yuan, reflecting the fee reduction brought by correct parking. is the time period coefficient, assuming it is -3.00 yuan, reflecting the reduction of parking fees at night. T is the parking time length. Assume that T=3, which means the target vehicle is parked for 3 hours. CS is the use of charging service. Assume that CS=1, which means the use of charging service. WS is the use of car wash service. Assume WS=0, which means that the car wash service is not used. is the parking state adjustment coefficient of the vehicle, assuming P=1, which means it is parked correctly. D is the parking time period, assuming D=1, which means nighttime parking; Substitute the parameters into the formula for calculation: ; The result C=22 yuan means that the customer needs to pay 22 yuan for parking. The calculation takes into account the parking duration, the use of charging services and the additional discount for night parking, ensuring the fairness and adaptability of the fees, and enhancing the customer experience by adjusting the billing according to the services used and the parking duration.

[0040] The bill content generation submodule matches bill information for multiple users based on the parking fee calculation results, including service fees, parking fees, and overdue fees, and generates bill content matching records; In the bill content generation submodule, bill information is generated for multiple users based on the parking fee calculation results. An automated billing system is used to extract each user's service fee, parking fee and overdue fee from the fee calculation results. The accuracy of the bill information is ensured by matching and integrating the user's license plate number, service details and fee data. The generated bill content matching record lists the fee and total fee for each service, making it easier for users to understand and verify the accuracy of their bills. The bills are provided in electronic and paper formats to meet the needs of different users.

[0041] The bill status monitoring submodule sends bill information to users based on bill content matching records, monitors bill payment status in real time, records bill completion information, and generates parking billing information records; In the bill status monitoring submodule, based on the bill content matching records, it is responsible for sending bill information to users and monitoring the payment status of bills. It uses email and mobile application notification systems to send bill information to users, including payment deadlines and payment methods. The module monitors the payment status of bills in real time and tracks and confirms the status of each transaction by connecting to the payment gateway and bank system. For bills that are not paid on time, the module automatically sends reminder notifications to prompt users to handle them in time. The bill completion information is recorded in the parking billing information record. The record helps the parking management team monitor revenue flow and customer payment behavior to ensure the accuracy and completeness of financial data.

[0042] See also Fig. 9 , an unmanned parking charging method, the unmanned parking charging method is executed based on the unmanned parking charging system, comprising the following steps: S1: Use real-time image acquisition equipment to collect image information of vehicles entering the parking lot, identify license plate numbers, record vehicle models and sizes, and generate vehicle identification information; S2: Based on the vehicle identification information, taking into account the vehicle size and the scheduled parking time, the parking location is allocated by analyzing the parking space usage and the vehicle charging demand, the path between the entrance and the target parking space is calculated, and the navigation information is sent to the user to generate the parking space allocation information; S3: Using the parking space allocation information, the parking posture of the vehicle in the parking space is detected in real time, and an incorrect parking prompt message is sent to the user to generate parking status verification information; S4: Based on the parking status verification information, real-time monitoring of vehicle activities in the parking lot, including the use of charging piles and car wash services, recording the type and duration of services, and generating service behavior analysis results; S5: Based on the service behavior analysis results, by conducting time series analysis on the parking lot’s operational information, the fluctuations in parking space and service demand are predicted, and pricing standards are adjusted. The parking fees for multiple vehicles are calculated, and bills are sent to the car owners to generate parking billing information records.

[0043] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An unmanned parking fee charging system, characterized in that: The system comprises: The license plate recognition module is based on real-time image acquisition equipment, which collects image information of vehicles entering the parking lot, identifies vehicle information by analyzing the license plate image, and records the type and size of the vehicle to generate a vehicle entry record; The parking space allocation and navigation module allocates a parking space for the target vehicle based on the vehicle entry record, according to the vehicle size and scheduled parking time, taking into account the parking space usage status and charging pile usage requirements, and sends navigation information to the user to generate parking navigation instructions; The vehicle arrival detection module identifies the wrongly parked vehicle by analyzing the parking posture of the vehicle in the parking space based on the parking navigation instruction, sends a prompt message to the user, and generates a vehicle parking status record; The vehicle behavior monitoring module monitors the behavior of the vehicle in the parking lot in real time based on the vehicle parking status record, records the type and time information of the service, and generates a service usage record; The service demand analysis module performs time series analysis on the operation data of the parking lot based on the service usage record, predicts the parking space and service demand of the parking lot, adjusts the fees, and generates a pricing table adjustment record; The fee calculation module adjusts the records based on the pricing table, calculates the parking fee according to the vehicle behavior, sends the bill information to the user, and generates a parking billing information record.

2. The unmanned parking fee charging system according to claim 1, characterized in that: The vehicle entry record includes vehicle type identification information, vehicle volume and size information, and license plate number information; the vehicle parking navigation instruction includes parking space number allocation results, optimal driving path calculation results, and estimated arrival time information at the parking space; the vehicle parking status record includes vehicle parking image information, parking posture analysis results, and incorrect parking prompt information; the service usage record includes charging service time records, car wash service usage information, and vehicle usage record information; the pricing table adjustment record includes predicted parking space occupancy rate, service demand trend prediction data, and fee adjustment records; the parking billing information record includes parking time calculation results, service fee calculation data, and bill payment status records.

3. The unmanned parking fee charging system according to claim 1, characterized in that: The license plate recognition module comprises: The image information acquisition submodule is based on real-time image acquisition equipment to collect image data of vehicles entering the parking lot in real time, identify and record the vehicle's license plate number, and generate number information recognition records; The vehicle size analysis submodule identifies the type and size of the target vehicle based on the number information recognition record and generates vehicle identification data by analyzing the vehicle image; The time information recording submodule analyzes the parking space type required by the vehicle based on the vehicle identification data, records the vehicle's entry time, and generates a vehicle entry record.

4. The unmanned parking fee charging system according to claim 1, characterized in that: The parking space allocation and navigation module includes: The position calculation submodule allocates a parking space for the target vehicle based on the vehicle entry record, according to the vehicle size information and the scheduled parking time, taking into account the real-time parking space usage and charging requirements, and generates a parking space allocation result; The path planning submodule calculates the optimal driving path between the parking lot entrance and the target parking space based on the parking space allocation result and takes into account path congestion, and generates navigation path calculation information; The navigation information sending submodule sends navigation instructions to the user's mobile device and vehicle system based on the navigation path calculation information, including direction prompts and estimated arrival time of the turning point, and generates vehicle parking navigation instructions.

5. The unmanned parking fee charging system according to claim 1, characterized in that: The vehicle arrival detection module comprises: The posture analysis submodule generates parking image information by collecting images of the vehicle in the target parking space in real time based on the vehicle parking navigation instruction and analyzing the parking angle and position of the vehicle; The error detection submodule, based on the parking image information, determines whether the vehicle exceeds the parking space line by evaluating the position of the vehicle relative to the parking space boundary, detects whether the target vehicle meets the parking regulations, records the wrongly parked vehicles, and generates the wrong parking detection result; The status recording submodule sends a wrong parking prompt message to the target user based on the wrong parking detection result, records the parking status of the vehicle, calculates the parking time, and generates a vehicle parking status record.

6. The unmanned parking fee charging system according to claim 1, characterized in that: The vehicle behavior monitoring module comprises: The vehicle activity recording submodule monitors the vehicle activities in the parking lot in real time based on the vehicle parking status record, records the vehicle information of using the charging pile and entering the car wash area, and generates service activity identification results; The vehicle behavior recording submodule records the types and times of the services used by multiple vehicles based on the service activity identification results, including the charging usage time and the car wash service type, and generates a service behavior recording result; The data statistics analysis submodule calculates the usage frequency and average usage duration of various services based on the service behavior record results, analyzes the usage frequency and type of services by various vehicles, evaluates the preferences of various vehicles for service types, and generates service usage records.

7. The unmanned parking fee charging system according to claim 1, characterized in that: The service demand analysis module includes: The operation data collection submodule collects and records the operation data of the parking lot, including parking space and service usage data, based on the service usage record, and generates an operation data collection record; The demand fluctuation assessment submodule predicts the demand fluctuation of parking spaces and services, including the demand changes of charging and car washing services, and generates demand forecast results by performing time series analysis on the operation data based on the operation data collection records; The charging standard adjustment submodule adjusts the fees for parking spaces and various services based on the demand forecast results, according to the demand forecast data, taking into account market conditions and consumer sensitivity, and generates a pricing table adjustment record.

8. The unmanned parking fee charging system according to claim 1, characterized in that: The cost calculation module includes: The parking fee analysis submodule calculates parking fees for multiple users based on the adjustment records of the pricing table, according to the parking time and parking status of the vehicle, combined with the type of service used and the difference in fees for multiple time periods, and generates a parking fee calculation result; The bill content generation submodule matches bill information for multiple users based on the parking fee calculation result, including service fees, parking fees and overdue fees, and generates a bill content matching record; The bill status monitoring submodule sends bill information to the user based on the bill content matching record, monitors the payment status of the bill in real time, records the bill completion information, and generates parking billing information records.

9. The unmanned parking fee charging system according to claim 8, characterized in that: The specific formula for calculating parking fees for multiple users is: ; Among them, C represents the calculated parking fee, which is determined according to the parking time, service usage, parking status and time period. T represents the length of time the vehicle is parked, in hours, which is the basic part affecting the fee. CS represents the use of charging service, reflecting whether the charging service is used and the impact on the fee. WS represents the use of car wash service, reflecting whether the car wash service is used and the impact on the fee. P represents the parking status adjustment coefficient of the vehicle, considering whether the parking posture of the vehicle is standardized and whether it is parked in the designated area. D represents the time period of day or night, reflecting the difference in rates in different time periods. is the intercept of the model, representing the base parking fee, the starting fee without any additional factors. is the coefficient of the time variable, is the rate coefficient of the charging service, which shows the increase in the total cost due to the use of the charging service. is the rate factor of the car wash service, which shows the increase in total cost caused by using the car wash service. is the adjustment factor for parking status, which measures the impact of irregular parking on fees. It is the time period coefficient, which indicates the impact of different time periods on the fee. The formula reflects the impact of different service usage and parking behaviors on parking fees, and provides a flexible billing method.

10. An unmanned parking fee charging method, characterized in that: The unmanned parking charging system according to any one of claims 1 to 9 comprises the following steps: Use real-time image acquisition equipment to collect image information of vehicles entering the parking lot, identify license plate numbers, record vehicle models and sizes, and generate vehicle identification information; Based on the vehicle identification information, taking into account the size of the vehicle and the scheduled parking time, by analyzing the parking space usage and the vehicle charging needs, allocating the parking position, calculating the path between the entrance and the target parking space and sending navigation information to the user, and generating parking space allocation information; Using the parking space allocation information, the parking posture of the vehicle in the parking space is detected in real time, and an incorrect parking prompt message is sent to the user to generate parking status verification information; Based on the parking status verification information, real-time monitoring of vehicle activities in the parking lot, including use of charging piles and car wash services, recording the type and duration of service, and generating service behavior analysis results; According to the service behavior analysis results, by performing time series analysis on the parking lot's operational information, the fluctuations in parking space and service demand are predicted, and pricing standards are adjusted. The parking fees for multiple vehicles are calculated, and bills are sent to vehicle owners to generate parking billing information records.

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