Intelligent parking lot access control system and method

Abstract

The invention relates to the technical field of automatic control, in particular to an intelligent parking lot access control system and method, and the system comprises a reservation information processing module, a vehicle entrance detection module, a parking space intelligent distribution module, a navigation path calculation module, an indicator light control module and a parking duration calculation module. According to the invention, through automatic identity verification and parking space matching, manual intervention is reduced, the efficiency and accuracy of the reservation process are optimized, the magnetic field inductor is used for identifying vehicle entrance and starting the image acquisition equipment, and vehicle information is identified and recorded, so that the calculation demand and equipment energy consumption of image analysis are reduced, and the vehicle entrance speed and safety are optimized; through parking space distribution and navigation path calculation, in combination with indication lamp control, an optimal navigation route is provided for a driver, a vehicle is guided to accurately arrive at a designated parking space, the time for finding the parking space by the vehicle is shortened, and through a mode of automatically calculating parking fees and controlling an exit barrier gate, payment and departure processes are optimized, and the convenience of the parking process is improved.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and in particular to an intelligent parking lot access control system and method. Background Art

[0002] The field of automated control technology focuses on using a variety of electronic and computing technologies to improve the operational efficiency, accuracy, and safety of equipment and systems, and to automatically perform complex and repetitive tasks by reducing reliance on manual operations, including monitoring and adjusting machine operations on production lines, controlling lighting and air-conditioning systems in buildings, optimizing traffic flow, and improving road safety. Control systems use sensors to monitor real-time data, actuators to perform physical operations, and controllers to process data and make decisions. Combined with artificial intelligence and machine learning technologies, intelligent and adaptive control is performed to enable the processing of complex tasks and improve operational flexibility and accuracy.

[0003] Among them, the intelligent parking lot access control system focuses on optimizing the management and operation of parking lots through automation technology, including automatic license plate recognition, automatic fee calculation, unattended entrance and exit control, and real-time monitoring. License plate recognition technology is used to identify vehicles and verify pre-stored vehicle data, simplifying the entry and exit processes. The automatic charging function automatically calculates fees based on parking time, reduces manual intervention and improves charging efficiency. Combined with mobile applications, it allows users to reserve parking spaces and pay parking fees through their mobile phones, improving the safety and efficiency of parking lots, and bringing convenience and economic benefits to managers and users.

[0004] Traditional parking lot access control technology relies on manual operation in handling parking lot management and operation, and relies on manual operation for vehicle entry management and fee calculation, which increases labor costs and calculation errors, affects the fairness of charging and the transparency of management, lacks dynamic management of parking spaces, and makes it impossible to make optimal use of parking space resources, resulting in vacant parking spaces and congestion. The vehicle navigation system and parking space indication are not smart enough, which causes drivers to spend a long time looking for parking spaces in the parking lot, increases driving pressure and traffic load in the parking lot, limits the operational efficiency and user experience of the parking lot, and affects the economic benefits and environmental friendliness of the parking lot. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent parking lot access control system and method.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, an intelligent parking lot access control system comprises: The reservation information processing module verifies the identity of the reservation user based on the parking reservation request information, matches the reserved parking space in combination with the real-time parking lot space information, sends notification information to the user, and generates reservation verification information; The vehicle entry detection module detects the vehicle entry in real time based on the reservation verification information using a magnetic field sensor, identifies the vehicle arrival and starts the image acquisition device, analyzes the vehicle license plate, records the vehicle size and type information, and generates vehicle identification information; The parking space intelligent allocation module matches parking spaces for vehicles that have not been reserved based on the vehicle identification information and the real-time parking space usage, and generates parking space allocation information; The navigation path calculation module calculates the optimal path between the parking lot entrance and the allocated parking space in real time based on the parking space allocation information and the current traffic flow data in the parking lot, and generates navigation route information; The indicator light control module controls the indicator lights in the parking lot in real time according to the navigation route information, adjusts the color and flashing mode to guide the vehicle to the target parking space, and generates a driving indication signal; The parking time calculation module monitors the parking time of multiple vehicles based on the driving indication signal, identifies the behavior of long-term occupation of parking spaces, calculates parking fees and controls the exit gate, and generates parking lot access control records.

[0007] As a further solution of the present invention, the reservation verification information includes user identity authentication status information, reserved parking space number, and reserved parking space location information; the vehicle identification information includes vehicle arrival status identification record, vehicle license plate recognition result, vehicle size and type data; the parking space allocation information includes parking space number allocation record, parking space location information, and vehicle matching status record; the navigation route information includes navigation path calculation results, estimated arrival time, and route turning point mark information; the driving indication signal includes indicator light position number information, light color control parameters, and flashing mode control parameters; the parking lot access control record includes parking time data, parking fee calculation results, and exit gate control parameters.

[0008] As a further solution of the present invention, the reservation information processing module includes: The identity authentication submodule identifies and analyzes the user's identity information based on the parking reservation request information, verifies the user's identity, and generates a user verification status; The reserved parking space matching submodule analyzes the real-time parking space information of the parking lot based on the user verification status, matches the reserved parking space for the reservation user, and generates a parking space matching result; The parking space information sending submodule sends parking space reservation notification information to the user based on the parking space matching result, including the parking space number and reservation time information, and generates reservation verification information.

[0009] As a further solution of the present invention, the vehicle entry detection module includes: The magnetic field monitoring submodule uses a magnetic field sensor to monitor the parking lot entrance in real time based on the reservation verification information, detects vehicle entry, and obtains magnetic field detection results; The license plate recognition submodule starts the image acquisition device based on the magnetic field detection result, collects the image information of the vehicle entering the venue, recognizes the vehicle number, and generates an image recognition result; The vehicle information recording submodule identifies the newly entered vehicle based on the image recognition result by comparing the registered vehicle license plate data, analyzes and records the size and type information of the new vehicle, and generates vehicle identification information.

[0010] As a further solution of the present invention, the parking space intelligent allocation module includes: The demand assessment submodule identifies unreserved vehicles based on the vehicle identification information and the reservation information, and assesses the type of parking space required by the target vehicle according to the size and type information of the vehicle, and generates a parking space demand analysis result; The vacant parking space analysis submodule matches a parking space for a target vehicle based on the parking space demand analysis result and generates a parking space matching result by analyzing the parking space usage status obtained in real time in the parking lot; The notification sending submodule sends the number and location information of the target parking space to the user based on the parking space matching result, and generates parking space allocation information.

[0011] As a further solution of the present invention, the navigation path calculation module includes: The parking lot traffic flow recognition submodule uses an image acquisition device to collect image information of multiple locations in the parking lot based on the parking space allocation information, analyzes the flow conditions of the entrance location and multiple lanes in real time, and generates real-time path flow data; The driving path analysis submodule calculates the optimal driving path between the parking lot entrance and the allocated parking space based on the real-time path flow data and generates a route calculation result; The navigation information sending submodule sends parking space navigation information, including driving instructions and estimated arrival time, to the user based on the route calculation result, and generates navigation route information.

[0012] As a further solution of the present invention, the indicator light control module includes: The route analysis submodule analyzes the position and sequence information of the indicator lights that need to be controlled based on the navigation route information, records the numbers of the indicator lights, and generates an indicator light demand analysis list; The lighting adjustment submodule adjusts the colors and flashing modes of the multiple indicator lights based on the indicator light demand analysis list and the real-time ambient light, optimizes the display effect, and generates a lighting parameter adjustment result; The signal output submodule controls the indicator light in real time according to the vehicle position based on the light parameter adjustment result, guides the driver to drive to the target parking space according to the planned path, and generates a driving instruction signal.

[0013] As a further solution of the present invention, the parking duration calculation module includes: The duration monitoring submodule monitors the parking duration of vehicles in multiple parking spaces in real time based on the driving indication signal, identifies vehicles that exceed a predetermined time, records the parking time of multiple vehicles, and generates a parking duration record; The vehicle charging submodule calculates the parking fee of the vehicle based on the parking time record, according to the parking time period, parking time, and vehicle type, and generates a fee calculation result; Based on the fee calculation result, the bill sending submodule matches the bill information for the vehicle and sends a payment notification to the vehicle owner, controls the parking lot exit gate, and generates a parking lot access control record.

[0014] As a further solution of the present invention, the specific formula for calculating the parking fee of the vehicle is: ; Where F represents the calculated parking fee, is the intercept of the model, indicating the basic parking fee, T indicates the parking time of the vehicle, is the coefficient of parking duration, reflecting the impact of duration on the cost. A numeric code indicating the vehicle type, is the coefficient of vehicle type, which indicates the difference in rates for different types of vehicles, S indicates whether parking is done during peak hours, is the peak hour coefficient, which indicates the impact of additional charges during peak hours.

[0015] An intelligent parking lot access control method, which is executed based on the above-mentioned intelligent parking lot access control system, comprises the following steps: S1: Based on the parking reservation request information, authenticate the reservation user and analyze the real-time parking space status of the parking lot, match the parking space and send notification information to the user, and generate a user identity authentication record; S2: Based on the user identity authentication record, the magnetic field sensor is used to monitor the vehicle entry in real time, and the image acquisition device is activated to identify the vehicle license plate, size and type, and generate a vehicle information identification record; S3: Based on the vehicle information identification record, the required parking space type is analyzed according to the size and type of the vehicle, the parking space is matched in combination with the real-time parking space usage in the parking lot, and the optimal path between the entrance location and the allocated parking space is calculated to generate parking space matching and navigation information; S4: Based on the parking space matching and navigation information, control the indicator lights in the parking lot in real time, adjust the light color and flashing mode to guide the vehicle to the assigned parking space, and generate light control parameters; S5: Based on the lighting control parameters, monitor the parking time of multiple vehicles in the parking space, identify the long-term occupation of the parking space, calculate the parking fee, send the fee bill to the user and control the exit gate, and generate the parking lot access control record.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, manual intervention is reduced through automated identity verification and parking space matching, the efficiency and accuracy of the reservation process are optimized, a magnetic field sensor is used to identify vehicle entry and start an image acquisition device to identify and record vehicle information, thereby reducing the computing requirements and equipment energy consumption of image analysis, and optimizing the speed and safety of vehicle entry. By allocating parking spaces and calculating navigation paths, combined with indicator light control, the driver is provided with the optimal navigation route and the vehicle is guided to arrive at the designated parking space accurately, shortening the time for finding a parking space. By automatically calculating parking fees and controlling exit barriers, the payment and departure processes are optimized, thereby improving the convenience of the parking process. 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 reservation information processing module of the present invention; Figure 4 The vehicle entry detection module flow chart of the present invention; Figure 5 This is a flow chart of the parking space intelligent allocation module of the present invention; Figure 6 This is a flowchart of the navigation path calculation module of the present invention; Figure 7 It is a flow chart of the indicator light control module of the present invention; Figure 8 This is a flow chart of the parking duration 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] See also Figure 1 to Figure 2 The present invention provides a technical solution, an intelligent parking lot access control system comprising: The reservation information processing module verifies the identity of the reservation user based on the parking reservation request information, matches the reserved parking space in combination with the real-time parking lot space information, sends notification information to the user, and generates reservation verification information; The vehicle entry detection module uses magnetic field sensors to detect vehicle entry in real time based on reservation verification information, recognize vehicle arrival and start image acquisition equipment, analyze vehicle license plates, record vehicle size and type information, and generate vehicle identification information; The parking space intelligent allocation module matches parking spaces for vehicles that have not been reserved based on vehicle identification information and real-time parking space usage, and generates parking space allocation information; The navigation path calculation module calculates the optimal path between the parking lot entrance and the allocated parking space in real time based on the parking space allocation information and the current traffic flow data in the parking lot, and generates navigation route information; The indicator light control module controls the indicator lights in the parking lot in real time according to the navigation route information, adjusts the color and flashing mode to guide the vehicle to the target parking space, and generates a driving instruction signal; The parking time calculation module monitors the parking time of multiple vehicles based on the driving indication signal, identifies the behavior of long-term occupation of parking spaces, calculates the parking fee and controls the exit gate, and generates parking lot access control records.

[0021] The reservation verification information includes user identity authentication status information, reserved parking space number, and reserved parking space location information; the vehicle identification information includes vehicle arrival status identification records, vehicle license plate recognition results, and vehicle size and type data; the parking space allocation information includes parking space number allocation records, parking space location information, and vehicle matching status records; the navigation route information includes navigation path calculation results, estimated arrival time, and route turning point marking information; the driving indication signal includes indicator light location number information, light color control parameters, and flashing mode control parameters; the parking lot access control record includes parking time data, parking fee calculation results, and exit gate control parameters.

[0022] See also Figure 2 and Figure 3 , the reservation information processing module includes: The identity authentication submodule identifies and analyzes the user's identity information based on the parking reservation request information, verifies the user's identity, and generates a user verification status; In the identity authentication submodule, the personal information in the parking reservation request is analyzed and the user identity is verified using deep learning-based facial recognition technology. The system extracts image data and personal information fields from the request, including the license plate number and driver's license number. The facial recognition model uses a pre-trained convolutional neural network. The verification steps include image preprocessing, such as standardization, resizing, and enhancement, to adapt to the model input requirements. After the feature extraction and comparison process, it is matched with the user information pre-stored in the database. When the match is successful, an encrypted verification status is generated and encrypted using the secure hash algorithm SHA-256 to ensure the security and integrity of data during network transmission, ensure that the user's identity authentication is accurate, and also strengthen the security of the system to prevent identity theft and data leakage.

[0023] The reserved parking space matching submodule analyzes the real-time parking space information of the parking lot based on the user verification status, matches the reserved parking space for the reservation user, and generates the parking space matching result; In the reserved parking space matching submodule, a rule-based decision tree algorithm is used to analyze parking space information and match reserved parking spaces. By collecting real-time parking space data, including the size, location, and availability status information of the parking space, the data is updated in real time through the sensor network and stored in the central database. The decision tree algorithm matches parking spaces based on the user's vehicle model, estimated arrival time, and personalized preference settings. The parameters set in the algorithm include the distance from the parking space to the entrance, the width of the parking space, and the type of parking space preferred by the user, including covered parking spaces and near-entrance parking spaces. When the user's request is verified, the system automatically selects a parking space based on the matching results of the decision tree, and optimizes the algorithm to ensure the shortest waiting time and the highest customer satisfaction, ensuring fair and efficient parking space allocation.

[0024] The parking space information sending submodule sends parking space reservation notification information to the user based on the parking space matching result, including the parking space number and reservation time information, and generates reservation verification information; In the parking space information sending submodule, based on the parking space matching results, the parking space information is sent directly to the user's smart device using the push notification service, and notification information including the parking space number and reserved time is generated. The information is pushed and notifications are sent to the user's device, including constructing message content, setting push rules, and sending messages. The message content includes the location of the parking space, reserved time, and a navigation link to the parking space, ensuring a smooth user experience, allowing users to easily obtain reserved parking space information and arrive at the designated location on time according to the provided navigation.

[0025] See also Figure 2 and Figure 4 , the vehicle entry detection module includes: The magnetic field monitoring submodule uses a magnetic field sensor to monitor the parking lot entrance in real time based on the reservation verification information, detects vehicle entry, and obtains magnetic field detection results; In the above content, the magnetic field sensor is used to monitor the parking lot entrance in real time to detect vehicle entry. According to the formula , calculate the magnetic field detection results; In the formula, represents the change in magnetic field, Indicates the magnetic field strength when a vehicle is present, Indicates the baseline magnetic field strength when there is no vehicle; Detailed explanation of the formula and the process of formula calculation and derivation: Assuming baseline magnetic field strength The magnetic field strength is 400mT. When the vehicle enters the monitoring area, the magnetic field strength rises to 450mT. The change in magnetic field is calculated as: ; result It shows that when a vehicle passes through the monitoring area, a 50mT magnetic field change is caused. The numerical results reflect the magnetic field interference caused by the vehicle, which is of key significance for judging the entry of the vehicle. It is used to adjust the sensitivity parameters of vehicle detection and optimize the response effect.

[0026] Based on the magnetic field detection results, the license plate recognition submodule starts the image acquisition device, collects the image information of the vehicles entering the venue, recognizes the vehicle number, and generates the image recognition results; In the license plate recognition submodule, after detecting the change in the magnetic field, the image acquisition device is started to capture the image of the entering vehicle. Optical character recognition is used, combined with the Tesseract OCR engine optimized for license plate recognition, to pre-process the image captured by the camera, including grayscale conversion, noise filtering and edge enhancement, to improve recognition accuracy. The OCR software analyzes the processed image and extracts text information from it. The system sets license plate format matching rules to ensure that only valid license plate numbers are recognized and recorded, and applies machine learning algorithms to optimize recognition accuracy, so that the system matches differentiated license plate fonts and styles, optimizes recognition algorithms and improves image processing quality.

[0027] The vehicle information recording submodule identifies the newly entered vehicle based on the image recognition results by comparing the registered vehicle license plate data, analyzes and records the size and type information of the new vehicle, and generates vehicle identification information; In the vehicle information recording submodule, the identified license plate number is analyzed, and data matching and vehicle type recognition are used to confirm whether the vehicle is a new entry through database comparison. The parameter types involved include license plate number and vehicle size. SQL database query is used to check whether the license plate number already exists in the registration database. For new vehicles, a vehicle recognition model based on image deep learning is used to estimate the size and type of the vehicle, including sedans, trucks, and SUVs. The vehicle identification information generated by the system includes vehicle type, size, and entry time. The data is stored for parking management and statistical analysis to ensure that accurate vehicle usage data can be provided to users and parking lot operators.

[0028] See also Figure 2 and Figure 5 , the parking space intelligent allocation module includes: The demand assessment submodule identifies unreserved vehicles based on vehicle identification information and reservation information, and evaluates the type of parking space required by the target vehicle based on the size and type information of the vehicle, generating a parking space demand analysis result; In the demand assessment submodule, vehicle identification information and reservation data are used to perform screening of unreserved vehicles and parking demand assessment. Conditional query technology is used to extract vehicle size and type data from the vehicle identification database, and compared with the reservation information database to identify vehicles that have not been reserved. After confirming that the vehicle is not reserved, the decision support system is used to evaluate the required parking space type based on the size and type of the vehicle. For example, SUVs or trucks require larger parking spaces, and sedans can fit into standard parking spaces. Through data extraction, condition matching and parking space demand decisions, combined with vehicle height and length thresholds, the parking space demand analysis results are analyzed and generated, including vehicle type, recommended parking space type and urgency index. This information is crucial to the subsequent parking space matching process.

[0029] The vacant parking space analysis submodule matches parking spaces for target vehicles based on the parking space demand analysis results and generates parking space matching results by real-time analysis of the parking space usage status obtained in the parking lot; In the vacant parking space analysis submodule, parking space matching is performed based on the parking space demand analysis results. A real-time parking space monitoring system is used to monitor the usage status of each parking space by integrating sensor data and database information. The location and status of each parking space are displayed in real time through the geographic information system. The parking space matching process includes real-time data acquisition, parking space status analysis, and matching algorithm application. A greedy algorithm is used to consider the adaptability of parking space size, vehicle priority, and entry time, and priority is given to matching empty parking spaces near the entrance and that meet vehicle needs, minimizing vehicle driving distance and meeting parking space needs, ensuring efficient and fair allocation of parking spaces.

[0030] The notification sending submodule sends the number and location information of the target parking space to the user based on the parking space matching result, and generates parking space allocation information; In the notification sending submodule, the parking space matching results are received, and the parking space information is sent to the user through electronic communication. The message queue service is used to ensure the instant delivery of information and the high reliability of the system, including information formatting, message queue configuration and sending notifications. During the information formatting stage, the system adjusts the message content according to the user's preferences, including the parking space number and location description. During the message queue configuration stage, the priority and retry mechanism are set to ensure that the message can be resent when the network fluctuates or the user's device is offline. The mobile push service is used to send customized parking space information to users to ensure that users receive parking space allocation notifications.

[0031] See also Figure 2 and Figure 6 , the navigation path calculation module includes: The parking lot traffic flow recognition submodule uses image acquisition equipment to collect image information of multiple locations in the parking lot based on parking space allocation information, analyzes the flow conditions of the entrance location and multiple lanes in real time, and generates real-time path flow data; In the parking lot vehicle flow recognition submodule, image acquisition equipment is used to capture image data from key locations in the parking lot, including entrances and lanes. Image processing and machine vision techniques are used, and the OpenCV library is used to implement vehicle detection and vehicle flow analysis, including setting camera angles to cover a wide area, collecting continuous video streams, and using background subtraction and vehicle recognition algorithms to monitor vehicle flow in real time. The system regularly updates the background model to adapt to different environmental conditions to ensure detection accuracy. The inter-frame difference method is used to identify moving vehicles by comparing the differences between consecutive frames, and vehicles are separated from complex backgrounds. The real-time path flow data generated includes vehicle counts and traffic speeds. The data is transmitted to the central processing unit in real time for analysis and is used to evaluate the flow status of the parking lot.

[0032] The driving path analysis submodule calculates the optimal driving path between the parking lot entrance and the allocated parking space based on the real-time path flow data and generates the route calculation result; In the above content, in the driving path analysis submodule, the optimal driving path between the parking lot entrance and the allocated parking space is calculated based on the real-time path flow data, and the formula is applied Calculate estimated travel time; In the formula, T represents the total driving time, represents the distance of the i-th path, represents the average speed of the i-th path, n is the total number of all paths, and i is the index of the multi-segment path; Detailed explanation of the formula and the process of formula calculation and derivation: Assume that there are three paths from the parking lot entrance to the assigned parking space, with distances of 100 meters, 150 meters, and 200 meters, and the corresponding average speeds are 10m / s, 5m / s, and 8m / s, respectively. Calculate T: ; The result 65 seconds shows that according to the current traffic conditions and speed limits of each section, the estimated driving time for users from the entrance to the parking space is 65 seconds. The optimal driving path based on real-time traffic data is determined to help users reach the designated parking space quickly and efficiently, optimizing the traffic flow in the parking lot.

[0033] The navigation information sending submodule sends parking navigation information to the user based on the route calculation result, including driving instructions and estimated arrival time, and generates navigation route information; In the navigation information sending submodule, the route calculation results are used to send parking navigation information to users through mobile applications or vehicle systems, and push technology is used to generate visual representations of navigation routes and driving instructions, including receiving route calculation results, converting the results into navigation instructions, such as turning points, road names and distances of each section of the journey, calculating the estimated arrival time from the current location to the destination, considering real-time traffic conditions, and formatting the information before sending it through the user's smart device or vehicle system to ensure that the user can receive real-time and accurate driving guidance. The accuracy and timely update of navigation information are the key to providing a high-quality user experience, helping users navigate to the reserved parking space efficiently.

[0034] See also Figure 2 and Figure 7 , the indicator light control module includes: The route analysis submodule analyzes the location and sequence information of the indicator lights that need to be controlled based on the navigation route information, records the numbers of the indicator lights, and generates an indicator light demand analysis list; In the route analysis submodule, the navigation route information is received, the position and sequence of the indicator lights that need to be controlled are analyzed and determined, the path parsing algorithm is applied, and the breadth-first search is used to analyze the indicator lights required in the route planning. By receiving the navigation route data, the navigation data is parsed to determine the key turning points and straight-ahead areas along the predetermined route, the indicator light device is matched for each key point, and the number is recorded, and the distance from each indicator light to the next one and the signal sequence that should be displayed are calculated to ensure that the driver follows the navigation instructions. The generated indicator light requirement analysis list includes the position, number and order of each light in the driver's route.

[0035] The lighting adjustment submodule is based on the indicator light requirement analysis list and adjusts the color and flashing mode of multiple indicator lights according to the real-time ambient light, optimizes the display effect, and generates the lighting parameter adjustment results; In the above content, in the lighting adjustment submodule, the influence of ambient light changes on the brightness of the indicator light is considered, according to the formula , calculate the light brightness that needs to be adjusted; In the formula, Represents the light brightness that needs to be adjusted. Represents the target ambient light intensity, Represents the current ambient light intensity. It is the adjustment sensitivity coefficient, which describes the responsiveness of the ambient light intensity change to the light brightness adjustment; Detailed explanation of the formula and the process of formula calculation and derivation: Set target ambient light intensity The current ambient light intensity is 600lux. To 500lux, adjust the sensitivity coefficient ,calculate : ; The result of 10lux shows that when the current ambient light intensity changes from 500lux to 600lux, the brightness of the light needs to be increased by 10lux to maintain the effectiveness of visual guidance and the comfort of the driver, to ensure that the indicator light can provide sufficient brightness under different ambient light conditions, and to avoid affecting the navigation effect due to excessively bright or dark ambient light.

[0036] The signal output submodule controls the indicator lights in real time according to the vehicle position based on the lighting parameter adjustment results, guides the driver to the target parking space according to the planned path, and generates a driving instruction signal; In the signal output submodule, based on the light parameter adjustment results, the indicator lights are controlled in real time to ensure that the driver drives to the target parking space safely and efficiently according to the planned path. Wireless signal transmission and location-based dynamic control system are used to receive the light adjustment parameters and use the vehicle positioning system to determine the real-time position of the vehicle. According to the vehicle position, the indicator lights along the path are dynamically adjusted. The specified light mode is activated through wireless control signals, including that when the vehicle approaches a turning point, the indicator light in front will flash in advance to guide the driver to turn. The working mode of the indicator light is automatically adjusted according to the traffic density and traffic congestion to ensure smooth traffic. The generated driving indication signal is designed to provide continuous, easy-to-follow navigation prompts to help drivers find the assigned parking space.

[0037] See also Figure 2 and Figure 8 , the parking time calculation module includes: The duration monitoring submodule monitors the parking duration of vehicles in multiple parking spaces in real time based on the driving indication signal, identifies vehicles that exceed the scheduled time, records the parking time of multiple vehicles, and generates parking duration records; In the duration monitoring submodule, sensors and positioning systems are used to monitor the parking time of vehicles in the parking lot in real time. Geomagnetic parking space sensors are used to detect whether there are vehicles in the parking space and record the parking time of the vehicle. Real-time data collection is used by sensors and transmitted to the central processing unit through a wireless network. The parking time of each vehicle is calculated based on the timestamps of the vehicle's arrival and departure. The module identifies vehicles that exceed the scheduled parking time through a set predetermined time threshold. The data of overtime vehicles will be recorded and marked for additional charges or reminders to the owner. The generated parking time record includes vehicle identification, parking time, arrival time and departure time. The data provides necessary input information for vehicle billing.

[0038] The vehicle billing submodule calculates the parking fee of the vehicle based on the parking time record, according to the parking time period, parking time, and vehicle type, and generates the fee calculation result; The specific formula for calculating the parking fee for a vehicle is: ; Where F represents the calculated parking fee, is the intercept of the model, indicating the basic parking fee, T indicates the parking time of the vehicle, is the coefficient of parking duration, reflecting the impact of duration on the cost. A numeric code indicating the vehicle type, is the coefficient of vehicle type, which indicates the difference in rates for different types of vehicles, S indicates whether parking is done during peak hours, is the peak hour coefficient, which indicates the impact of additional charges during peak hours.

[0039] formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: The formula is used to calculate the parking fee of vehicles in the parking lot according to the basic rate, parking time, vehicle type and parking period, so that the fee calculation is accurate and reasonable, and the fee result is used to generate bill information.

[0040] Parameter meaning and setting value: Assume the basic fee is 2.50 yuan; is the time coefficient, which means the cost per hour, assuming it is 1.50 yuan / hour; T is the parking time, which is assumed to be 3 hours, reflecting that the target vehicle has been parked in the parking lot for 3 hours; is the vehicle type coefficient. Assume that the sedan is set to 0.00 yuan, indicating that there is no additional charge for the standard model, and the truck is set to 0.50 yuan, indicating that the larger model requires additional charges. is the vehicle type indicator, assuming , indicating that the target vehicle is a truck, ; is the peak period coefficient, assumed to be 0.30 yuan, reflecting the increased cost during peak periods due to high demand; S is the peak period indicator, assuming S = 1, indicating the peak parking period; Substitute the parameters into the formula for calculation:

[0041] The calculation result F=7.80 yuan shows that the parking fee is calculated based on the vehicle type, parking duration and time period, which effectively responds to the parking needs of different times and different types of vehicles, ensures fair charging and flexibly adjusts the fees according to actual conditions.

[0042] The bill sending submodule matches the bill information for the vehicle based on the fee calculation results and sends a payment notification to the owner, controls the parking lot exit gate, and generates parking lot access control records; In the bill sending submodule, based on the fee calculation results, a payment notification is sent to the car owner, and the exit gate of the parking lot is controlled. The electronic payment system and automatic access control technology are used, including receiving the fee data transmitted by the billing module, generating an electronic bill, and pushing the payment notification to the car owner via SMS or mobile application. The payment system supports multiple payment methods, such as credit cards and mobile payments. By monitoring the completion status of the bill in real time, the billing system identifies the payment completion and sends a signal to the control system of the exit gate to allow the vehicle to leave. The generated parking lot access control record includes the payment status, bill details and gate opening time of each vehicle, ensuring the financial and physical security management of the parking lot.

[0043] See also Fig. 9 , an intelligent parking lot access control method, the intelligent parking lot access control method is executed based on the above-mentioned intelligent parking lot access control system, and includes the following steps: S1: Based on the parking reservation request information, authenticate the reservation user and analyze the real-time parking space status of the parking lot, match the parking space and send notification information to the user, and generate a user identity authentication record; S2: Based on the user identity verification record, the magnetic field sensor is used to monitor the vehicle entry in real time, and the image acquisition device is activated to identify the vehicle's license plate, size and type, and generate a vehicle information identification record; S3: Based on the vehicle information recognition record, the required parking space type is analyzed according to the size and type of the vehicle, the parking space is matched according to the real-time parking space usage in the parking lot, and the optimal path between the entrance location and the allocated parking space is calculated to generate parking space matching and navigation information; S4: Based on parking space matching and navigation information, control the indicator lights in the parking lot in real time, adjust the light color and flashing mode to guide vehicles to the assigned parking spaces, and generate light control parameters; S5: Based on the lighting control parameters, monitor the parking time of multiple vehicles in the parking space, identify the long-term occupation of parking spaces, calculate the parking fee, send the fee bill to the user and control the exit gate to generate the parking lot access control record.

[0044] 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 intelligent parking lot access control system, characterized in that: The system comprises: The reservation information processing module verifies the identity of the reservation user based on the parking reservation request information, matches the reserved parking space in combination with the real-time parking lot space information, sends notification information to the user, and generates reservation verification information; The vehicle entry detection module detects the vehicle entry in real time based on the reservation verification information using a magnetic field sensor, identifies the vehicle arrival and starts the image acquisition device, analyzes the vehicle license plate, records the vehicle size and type information, and generates vehicle identification information; The parking space intelligent allocation module matches parking spaces for vehicles that have not been reserved based on the vehicle identification information and the real-time parking space usage, and generates parking space allocation information; The navigation path calculation module calculates the optimal path between the parking lot entrance and the allocated parking space in real time based on the parking space allocation information and the current traffic flow data in the parking lot, and generates navigation route information; The indicator light control module controls the indicator lights in the parking lot in real time according to the navigation route information, adjusts the color and flashing mode to guide the vehicle to the target parking space, and generates a driving indication signal; The parking time calculation module monitors the parking time of multiple vehicles based on the driving indication signal, identifies the behavior of long-term occupation of parking spaces, calculates parking fees and controls the exit gate, and generates parking lot access control records.

2. The intelligent parking lot access control system according to claim 1 is characterized in that: The reservation verification information includes user identity authentication status information, reserved parking space number, and reserved parking space location information; the vehicle identification information includes vehicle arrival status identification record, vehicle license plate identification result, and vehicle size and type data; the parking space allocation information includes parking space number allocation record, parking space location information, and vehicle matching status record; the navigation route information includes navigation path calculation results, estimated arrival time, and route turning point mark information; the driving indication signal includes indicator light position number information, light color control parameters, and flashing mode control parameters; the parking lot access control record includes parking duration data, parking fee calculation results, and exit gate control parameters.

3. The intelligent parking lot access control system according to claim 1 is characterized in that: The reservation information processing module includes: The identity authentication submodule identifies and analyzes the user's identity information based on the parking reservation request information, verifies the user's identity, and generates a user verification status; The reserved parking space matching submodule analyzes the real-time parking space information of the parking lot based on the user verification status, matches the reserved parking space for the reservation user, and generates a parking space matching result; The parking space information sending submodule sends parking space reservation notification information to the user based on the parking space matching result, including the parking space number and reservation time information, and generates reservation verification information.

4. The intelligent parking lot access control system according to claim 1 is characterized in that: The vehicle entry detection module comprises: The magnetic field monitoring submodule uses a magnetic field sensor to monitor the parking lot entrance in real time based on the reservation verification information, detects vehicle entry, and obtains magnetic field detection results; The license plate recognition submodule starts the image acquisition device based on the magnetic field detection result, collects the image information of the vehicle entering the venue, recognizes the vehicle number, and generates an image recognition result; The vehicle information recording submodule identifies the newly entered vehicle based on the image recognition result by comparing the registered vehicle license plate data, analyzes and records the size and type information of the new vehicle, and generates vehicle identification information.

5. The intelligent parking lot access control system according to claim 1 is characterized in that: The parking space intelligent allocation module includes: The demand assessment submodule identifies unreserved vehicles based on the vehicle identification information and the reservation information, and assesses the type of parking space required by the target vehicle according to the size and type information of the vehicle, and generates a parking space demand analysis result; The vacant parking space analysis submodule matches a parking space for a target vehicle based on the parking space demand analysis result and generates a parking space matching result by analyzing the parking space usage status obtained in real time in the parking lot; The notification sending submodule sends the number and location information of the target parking space to the user based on the parking space matching result, and generates parking space allocation information.

6. The intelligent parking lot access control system according to claim 1 is characterized in that: The navigation path calculation module includes: The parking lot traffic flow recognition submodule uses an image acquisition device to collect image information of multiple locations in the parking lot based on the parking space allocation information, analyzes the flow conditions of the entrance location and multiple lanes in real time, and generates real-time path flow data; The driving path analysis submodule calculates the optimal driving path between the parking lot entrance and the allocated parking space based on the real-time path flow data and generates a route calculation result; The navigation information sending submodule sends parking space navigation information, including driving instructions and estimated arrival time, to the user based on the route calculation result, and generates navigation route information.

7. The intelligent parking lot access control system according to claim 1 is characterized in that: The indicator light control module comprises: The route analysis submodule analyzes the position and sequence information of the indicator lights that need to be controlled based on the navigation route information, records the numbers of the indicator lights, and generates an indicator light demand analysis list; The lighting adjustment submodule adjusts the colors and flashing modes of the multiple indicator lights based on the indicator light demand analysis list and the real-time ambient light, optimizes the display effect, and generates a lighting parameter adjustment result; The signal output submodule controls the indicator light in real time according to the vehicle position based on the light parameter adjustment result, guides the driver to drive to the target parking space according to the planned path, and generates a driving instruction signal.

8. The intelligent parking lot access control system according to claim 1 is characterized in that: The parking time calculation module includes: The duration monitoring submodule monitors the parking duration of vehicles in multiple parking spaces in real time based on the driving indication signal, identifies vehicles that exceed a predetermined time, records the parking time of multiple vehicles, and generates a parking duration record; The vehicle charging submodule calculates the parking fee of the vehicle based on the parking time record, according to the parking time period, parking time, and vehicle type, and generates a fee calculation result; Based on the fee calculation result, the bill sending submodule matches the bill information for the vehicle and sends a payment notification to the vehicle owner, controls the parking lot exit gate, and generates a parking lot access control record.

9. The intelligent parking lot access control system according to claim 8 is characterized in that: The specific formula for calculating the parking fee of the vehicle is: ； Where F represents the calculated parking fee, is the intercept of the model, indicating the basic parking fee, T indicates the parking time of the vehicle, is the coefficient of parking duration, reflecting the impact of duration on the cost. A numeric code indicating the vehicle type, is the coefficient of vehicle type, which indicates the difference in rates for different types of vehicles, S indicates whether parking is done during peak hours, is the peak hour coefficient, which indicates the impact of additional charges during peak hours.

10. An intelligent parking lot access control method, characterized in that: The intelligent parking lot access control system according to any one of claims 1 to 9 comprises the following steps: Based on the parking reservation request information, authenticate the reservation user and analyze the real-time parking space status of the parking lot, match the parking space and send notification information to the user, and generate a user identity authentication record; Based on the user identity verification record, the magnetic field sensor is used to monitor the vehicle entry in real time, and the image acquisition device is activated to identify the vehicle license plate, size and type, and generate a vehicle information identification record; Based on the vehicle information identification record, the required parking space type is analyzed according to the size and type of the vehicle, the parking space is matched in combination with the real-time parking space usage in the parking lot, and the optimal path between the entrance location and the allocated parking space is calculated to generate parking space matching and navigation information; Based on the parking space matching and navigation information, the indicator lights in the parking lot are controlled in real time, the light color and flashing mode are adjusted to guide the vehicle to the assigned parking space, and the light control parameters are generated; Based on the lighting control parameters, the parking time of multiple vehicles in the parking space is monitored, the long-term occupation of the parking space is identified, the parking fee is calculated, the fee bill is sent to the user, the exit gate is controlled, and the parking lot access control record is generated.

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