Intelligent parking charging guiding method and system combined with parking space navigation

Abstract

The invention provides an intelligent parking charging guiding method and system combined with parking space navigation, and the method comprises the steps: obtaining the current vehicle position information of a user and a temporary or long-term parking demand type, calling a parking space state sensing module to obtain the real-time parking space occupation information in a parking lot, and carrying out the correlation matching to obtain the available parking space distribution information. Calling a corresponding charging calculation rule according to the parking demand type, and carrying out fusion analysis to obtain a parking space candidate set containing the parking space position and the charging standard; and planning a navigation path based on the parking space candidate set and generating path navigation information. And finally, integrating the path navigation information and a charging standard to generate an integrated parking charging guide instruction, and sending the integrated parking charging guide instruction to a user vehicle-mounted terminal. Accurate parking space navigation and differentiated charging information can be provided for the user, the parking time of the user is saved, and the parking space utilization rate and the parking lot management efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence, and more specifically, to a smart parking fee collection and guidance method and system that combines parking space navigation. Background Technology

[0002] In today's urban development, with the rapid increase in car ownership, the parking problem has become increasingly prominent. Most existing parking management systems are functionally limited, only providing basic parking space occupancy information. After entering a parking lot, users often have to blindly search for available spaces, wasting considerable time and energy and easily causing traffic congestion. Meanwhile, existing parking fee collection methods are also relatively simple, usually charging a uniform standard without differentiating based on varying parking needs and space location. For example, spaces near the entrance and exit have different levels of convenience than those further away, yet the fees are the same, which is detrimental to the rational use of parking spaces and efficient parking lot management. Furthermore, users cannot intuitively understand the fees for different parking spaces before parking, making it difficult to make the optimal parking choice. Therefore, there is an urgent need for a method that combines parking space navigation and intelligent parking fee guidance to solve these problems. Summary of the Invention

[0003] In view of the aforementioned problems, and in conjunction with the first aspect of the present invention, embodiments of the present invention provide a smart parking fee guidance method incorporating parking space navigation, the method comprising: Obtain the user's current vehicle location information and parking demand type, which can be either temporary parking demand or long-term parking demand. The system calls the parking space status perception module to obtain real-time parking space occupancy information in the parking lot, and associates and matches the user's current vehicle location information with the real-time parking space occupancy information to obtain available parking space distribution information. Based on the type of parking demand, the corresponding charging calculation rules are invoked, and the available parking space distribution information is integrated and analyzed with the charging calculation rules to obtain a candidate set of parking spaces that includes the location of the parking spaces and the corresponding charging standards. Based on the candidate parking space set, a navigation path from the user's current vehicle location to the target parking space is planned, and path navigation information is generated; By integrating route navigation information with the charging standards in the parking space candidate set, an integrated parking fee guidance instruction is generated and sent to the user's in-vehicle terminal.

[0004] In another aspect, embodiments of the present invention also provide a smart parking fee guidance system combined with parking space navigation, including a processor and a machine-readable storage medium connected to the processor. The machine-readable storage medium is used to store programs, instructions or code, and the processor is used to execute the programs, instructions or code in the machine-readable storage medium to implement the above-described method.

[0005] Based on the above, this embodiment of the invention, by acquiring the user's current vehicle location information and parking demand type, can accurately understand the user's parking intention. It calls the parking space status perception module to obtain real-time parking space occupancy information and performs correlation matching, quickly and accurately providing users with available parking space distribution information. This avoids users blindly searching in the parking lot, greatly saving time and energy and effectively alleviating traffic congestion. According to the parking demand type, it calls the corresponding charging calculation rules and integrates the available parking space distribution information with them for analysis, generating a candidate set of parking spaces containing parking space locations and corresponding charging standards. This achieves differentiated charging and improves the rational utilization rate of parking spaces. Based on the candidate set of parking spaces, it plans navigation routes and generates route navigation information, providing users with clear driving guidance. It integrates route navigation information and charging standards to generate an integrated parking charging guidance instruction and sends it to the user's in-vehicle terminal, allowing users to simultaneously obtain navigation and charging information during the parking process. This facilitates user decision-making, improves user experience, and also enhances the management efficiency and service quality of the parking lot. Attached Figure Description

[0006] Figure 1 This is a schematic diagram of the execution flow of the intelligent parking fee guidance method combined with parking space navigation provided in an embodiment of the present invention.

[0007] Figure 2 This is a schematic diagram of exemplary hardware and software components of the intelligent parking fee guidance system that combines parking space navigation, provided in an embodiment of the present invention. Detailed Implementation

[0008] The present invention will now be described in detail with reference to the accompanying drawings. Figure 1 This is a flowchart illustrating a smart parking fee guidance method combining parking space navigation according to an embodiment of the present invention. The following is a detailed description of this smart parking fee guidance method combining parking space navigation.

[0009] Step S110: Obtain the user's current vehicle location information and parking demand type, which is either temporary parking demand or long-term parking demand.

[0010] In this embodiment, when a user drives their vehicle into a large integrated parking lot, the system first needs to obtain the user's current vehicle location information and parking demand type. This process is the starting point of the entire smart parking fee guidance method, and its accuracy and timeliness directly affect the execution effect of all subsequent steps.

[0011] For example, in step S111: the positioning module in the user's vehicle terminal is called to obtain the vehicle's initial positioning information, which is generated based on the satellite positioning system.

[0012] In this embodiment, the user's vehicle-mounted terminal is equipped with a positioning module that supports a satellite positioning system. This module can receive signals from multiple satellites and calculate the vehicle's initial positioning information using a specific positioning algorithm. For example, the positioning module of the vehicle-mounted terminal can simultaneously receive signals from multiple satellite positioning systems such as GPS and BeiDou to improve the reliability and accuracy of positioning. The initial positioning information typically includes the vehicle's longitude and latitude coordinates. This coordinate data is stored in the vehicle-mounted terminal's cache in a specific format, awaiting retrieval by the system.

[0013] Step S112: Receive signals transmitted from positioning beacons deployed within the parking lot. These signals include beacon numbers and beacon location coordinates. In this embodiment, to improve indoor positioning accuracy, a large number of positioning beacons are deployed in various areas of the parking lot, such as on the ceiling and pillars. These positioning beacons are distributed according to a certain interval rule and can continuously transmit wireless signals to the surrounding area. When a user's vehicle enters the parking lot, the wireless receiving module of the vehicle terminal receives the signals transmitted by these positioning beacons. Each positioning beacon's signal carries its unique beacon number and its precise location coordinates within the parking lot's internal coordinate system. This information is crucial data for subsequent position calibration.

[0014] Step S113: Merge and calibrate the initial positioning information with the beacon position coordinates to correct the deviation in the initial positioning information and obtain the user's current vehicle position information.

[0015] In this embodiment, satellite positioning signals may be obstructed and reflected by building structures in indoor parking lots, leading to some deviation in the initial positioning information. Therefore, it is necessary to fuse and calibrate the initial positioning information with the received positioning beacon coordinates. The system first filters the received positioning beacon signals, selecting several beacons with strong signal strength and clear beacon numbers as reference points. Then, using a specific fusion algorithm, such as the Kalman filter algorithm, the initial positioning information is fused with these beacon coordinates. During the fusion process, the algorithm dynamically adjusts the weights of each data point based on factors such as the signal strength and distance of each beacon, as well as the error estimate of the initial positioning information, thereby calculating a more accurate current vehicle location information for the user. This location information includes not only longitude and latitude coordinates but is also converted to local coordinates used within the parking lot for subsequent unified processing with information such as parking space locations within the parking lot.

[0016] Step S114: Send a parking demand type selection request to the user's in-vehicle terminal. The request includes options for temporary or long-term parking. In this embodiment, after obtaining the user's current vehicle location information, the system sends a parking demand type selection request to the user's in-vehicle terminal via wireless communication. This request is presented to the user on the in-vehicle terminal's display screen or audio system in the form of a pop-up window or voice prompt. The request information clearly lists two options: temporary parking and long-term parking, and provides a brief explanation of each option. For example, temporary parking is suitable for short-term parking (e.g., a few hours), while long-term parking is suitable for longer-term parking (e.g., a few days or a month), allowing the user to choose according to their actual needs.

[0017] Step S115: Receive the selection signal fed back by the user through the vehicle terminal interface, and parse the demand identifier in the selection signal fed back by the user through the vehicle terminal interface.

[0018] In this embodiment, after seeing the parking demand type selection request on the in-vehicle terminal, the user selects their parking demand type by touching the display screen or operating the physical buttons on the in-vehicle terminal. Once the user makes a selection, the in-vehicle terminal generates a corresponding selection signal and sends it to the system via the wireless communication module. Upon receiving the selection signal, the system decodes and parses it. The selection signal contains a specific demand identifier, which is predefined and used to distinguish between temporary and long-term parking demands. For example, demand identifier "01" might represent a temporary parking demand, while demand identifier "02" might represent a long-term parking demand. By parsing this demand identifier, the system can determine the parking demand type selected by the user.

[0019] Step S116: Determine the parking demand type based on the demand identifier. If the demand identifier corresponds to the temporary parking demand option, the parking demand type is temporary parking demand; if the demand identifier corresponds to the long-term parking demand option, the parking demand type is long-term parking demand. In this embodiment, after parsing the demand identifier in the selection signal, the system compares the identifier with preset identifiers stored internally. The system internally stores preset identifiers corresponding to the temporary parking demand option and preset identifiers corresponding to the long-term parking demand option. When the parsed demand identifier matches the preset identifier of the temporary parking demand option, the system determines that the user's parking demand type is temporary parking demand; when the parsed demand identifier matches the preset identifier of the long-term parking demand option, the system determines that the user's parking demand type is long-term parking demand. For example, if the parsed demand identifier is "01", and the system presets "01" to correspond to the temporary parking demand option, then the parking demand type is determined to be temporary parking demand.

[0020] Step S117: Associate and store the determined current vehicle location information of the user with the parking demand type.

[0021] In this embodiment, after determining the user's parking need type, the system associates and stores the user's current vehicle location information with the corresponding parking need type. This association involves combining these two types of information according to a specific data structure, for example, forming a data record containing fields such as vehicle location coordinates and parking need type identifier. This data record is stored in the system's database, which can be a local database or a cloud database. A unique identifier is assigned to each data record during storage. Simultaneously, the system sets a storage validity period for the data to ensure that it does not occupy storage space indefinitely. If the data is not used again after the validity period expires, it will be automatically deleted.

[0022] Step S120: The parking space status perception module is invoked to obtain real-time parking space occupancy information within the parking lot. The user's current vehicle location information is then correlated and matched with the real-time parking space occupancy information to obtain available parking space distribution information. In this embodiment, after acquiring and storing the user's current vehicle location information and parking demand type, the system needs to invoke the parking space status perception module to obtain real-time parking space occupancy information within the parking lot and correlate and match it with the user's current vehicle location information to obtain available parking space distribution information. The core of this process is to accurately and promptly acquire parking space status and filter out available parking spaces that meet the user's location criteria.

[0023] Step S121: Perform position calibration processing on the user's current vehicle location information to obtain accurate vehicle location information. The position calibration processing is completed based on the preset positioning reference point in the parking lot.

[0024] In this embodiment, although the initial positioning information has been fused and calibrated in step S113, further position calibration is needed to improve the accuracy of the user's current vehicle location information and ensure the accuracy of subsequent matching with parking space locations. Multiple positioning reference points are pre-set in the parking lot; the coordinates of these reference points are precisely measured and stored in the system. During position calibration, the system first retrieves the coordinates of multiple positioning reference points within a certain range around the user's current vehicle location information from the database. Then, the system receives calibration signals from these positioning reference points via the vehicle terminal; these signals contain the reference point's identifier and precise coordinates. The system compares and calculates the user's current vehicle location information with the coordinates of these reference points, using methods such as triangulation to fine-tune the user's current vehicle location information, thereby obtaining accurate vehicle location information. For example, if the calculated distance between the user's current vehicle location information and a certain positioning reference point deviates from the actual preset distance, the system will comprehensively calculate a calibration value based on the deviations of multiple reference points and correct the user's current vehicle location information.

[0025] Step S122: Invoke the parking space camera acquisition unit in the parking space status perception module to obtain real-time image information corresponding to the parking space. The real-time image information includes the visual features of the vehicle parked in the parking space. In this embodiment, the parking space status perception module is an important component in the parking lot for monitoring the occupancy of parking spaces. The parking space camera acquisition unit is installed directly above or diagonally above each parking space, and can clearly capture the entire view of the parking space. The system calls the parking space camera acquisition unit through the network interface and sends an image acquisition command to it. After receiving the command, the parking space camera acquisition unit immediately starts the image sensor to capture images and obtain the real-time image information corresponding to the parking space. The real-time image information is stored in the form of digital images, and its resolution depends on the performance of the camera. It can usually clearly show whether there is a vehicle parked in the parking space and the approximate outline, color, and other visual features of the vehicle. For example, when there is a vehicle parked in the parking space, the real-time image will show the shape, color, and other features of the vehicle; when the parking space is empty, the image mainly shows the marking lines on the ground of the parking space.

[0026] Step S123: Perform vehicle presence recognition processing on the real-time image information to generate an occupancy status identifier for the parking space. The occupancy status identifier is either an occupied identifier or an unoccupied identifier. In this embodiment, after obtaining the real-time image information corresponding to the parking space, it is necessary to perform vehicle presence recognition processing to determine whether each parking space is occupied or unoccupied. This processing mainly relies on computer vision technology, which is achieved by analyzing and judging the visual features in the image.

[0027] Step S1231: Perform image preprocessing on the real-time image information to eliminate noise interference in the image and obtain denoised image information.

[0028] In this embodiment, the parking space camera acquisition unit may be affected by factors such as changes in light, camera noise, and external environmental interference during the shooting process, resulting in noise in the real-time image information. Therefore, image preprocessing is required to eliminate noise interference. Image preprocessing employs multiple techniques. First, grayscale conversion is performed, transforming the color real-time image into a grayscale image to reduce data volume and highlight the image's brightness characteristics. Then, a Gaussian filtering algorithm is used to smooth the grayscale image. This algorithm eliminates high-frequency noise by weighted averaging of the grayscale values ​​of each pixel and its neighboring pixels. Next, contrast enhancement is performed by adjusting the grayscale value range of the image to make the contrast between the target area (potential vehicles within the parking space) and the background area (parking space floor) more pronounced. After these preprocessing steps, a denoised image is obtained, where noise is effectively suppressed and image quality is improved.

[0029] Step S1232: Perform image segmentation on the denoised image information, dividing the image into parking space areas and non-parking space areas, with the parking space area being the image range corresponding to the parking space.

[0030] In this embodiment, the denoised image information includes parking space and surrounding environmental information. To accurately identify whether a vehicle is parked in the parking space, it is necessary to segment the parking space area and non-parking space area in the image. Image segmentation adopts a threshold-based segmentation method. First, the gray value distribution characteristics of the parking space area and non-parking space area in the denoised image information are analyzed. The parking space ground usually has a relatively uniform color and texture, and its gray value range is relatively fixed; while non-parking space areas, such as surrounding passages and walls, have significantly different gray values ​​from the parking space area. The system determines the approximate area range of the parking space in the image based on the preset parking space size and the camera installation position. Then, within this area, an appropriate threshold is calculated using an adaptive threshold algorithm. Pixels with gray values ​​greater than the threshold are classified as non-parking space areas, and pixels with gray values ​​less than or equal to the threshold are classified as parking space areas. In this way, the denoised image information is accurately segmented into parking space areas and non-parking space areas.

[0031] Step S1233: Perform edge detection on the parking space area and extract the boundary contour features of the parking space area. The boundary contour features include the four boundary lines of the parking space.

[0032] In this embodiment, after image segmentation to obtain the parking space area, edge detection needs to be performed on the parking space area to extract its boundary contour features. The boundary contour features of the parking space are crucial for determining whether a parking space is occupied by a vehicle, as parked vehicles partially obscure the boundary lines. The Canny edge detection algorithm is used. This algorithm first applies Gaussian filtering to the parking space image to further smooth the image and reduce the impact of noise on edge detection. Then, it calculates the gradient magnitude and direction of the image. The gradient magnitude reflects the rate of change of pixel grayscale values ​​in the image, while the gradient direction indicates the direction of grayscale value change. Next, non-maximum suppression is applied to the gradient magnitude, retaining the pixels with the largest grayscale value change along the gradient direction, thus obtaining refined edges. Finally, a double thresholding algorithm is used to determine the final edge pixels, and these edge pixels are connected to form the boundary contour features of the parking space area. The boundary contour features of the parking space area mainly include the four boundary lines of the parking space, which should be relatively regular straight line segments.

[0033] Step S1234: Analyze the pixel grayscale distribution characteristics within the parking space area, and calculate the mean and variance of the pixel grayscale. The mean and variance are used to reflect the parking situation of vehicles within the parking space area.

[0034] In this embodiment, the pixel grayscale distribution characteristics of the parking space area can effectively reflect whether a vehicle is parked in the parking space. When there is no vehicle in the parking space, the ground color and texture of the parking space area are relatively uniform, the distribution of pixel grayscale values ​​is relatively concentrated, and the mean and variance are relatively small. When there is a vehicle in the parking space, the color and texture of the vehicle differ from the ground, resulting in a more dispersed distribution of pixel grayscale values, and the mean and variance are relatively large. Therefore, the system needs to analyze the pixel grayscale distribution characteristics in the parking space area and calculate the mean and variance of the pixel grayscale values. When calculating the mean, the grayscale values ​​of all pixels in the parking space area are added together and then divided by the total number of pixels. When calculating the variance, the square of the difference between each pixel grayscale value and the mean is calculated first, and then these squared values ​​are added together and divided by the total number of pixels. The calculated mean and variance can quantitatively describe the grayscale distribution of the parking space area.

[0035] Step S1235: Compare the mean and variance of pixel grayscale with the preset vehicle presence determination threshold to generate threshold comparison results.

[0036] In this embodiment, the system pre-stores vehicle presence determination thresholds, which include a mean threshold and a variance threshold, and are empirical values ​​obtained through analysis and statistics of a large number of sample images. The mean and variance of the pixel grayscale values ​​of the parking space area calculated in step S1234 are compared with the preset mean threshold and variance threshold, respectively. For example, if the calculated mean is less than the mean threshold and the variance is greater than the variance threshold, it indicates that the grayscale distribution in the parking space area is relatively dispersed, and a vehicle may be present; if the mean is greater than the mean threshold and the variance is less than the variance threshold, it indicates that the grayscale distribution in the parking space area is relatively concentrated, and the parking space may be empty. Through this comparison, a threshold comparison result is generated, which indicates whether a vehicle may be present in the parking space.

[0037] Step S1236: Generate an occupied status identifier based on the threshold comparison result. If the mean is less than the threshold and the variance is greater than the threshold, an occupied identifier is generated; if the mean is greater than the threshold and the variance is less than the threshold, an unoccupied identifier is generated.

[0038] In this embodiment, based on the threshold comparison result generated in step S1235, the system generates a corresponding occupancy status identifier. If the threshold comparison result shows that the mean value of the pixel grayscale in the parking space area is less than a preset mean threshold and the variance is greater than a preset variance threshold, the system determines that a vehicle exists in the parking space and generates an occupancy identifier, which can be a specific binary code, such as "1". If the threshold comparison result shows that the mean value is greater than the mean threshold and the variance is less than the variance threshold, the system determines that no vehicle exists in the parking space and generates an unoccupied identifier, which can be "0". The generation of the occupancy status identifier allows the occupancy status of the parking space to be represented and stored in a concise form.

[0039] Step S1237: Associate the occupancy status identifier of the parking space with the corresponding parking space number to generate a status association table containing the parking space number and the occupancy status identifier.

[0040] In this embodiment, each parking space has a unique parking space number, which is set and stored in the system when the parking space camera acquisition unit is installed. After generating the occupancy status identifier for each parking space, the system needs to associate the parking space number with the corresponding occupancy status identifier. The association process involves combining the parking space number and the occupancy status identifier into a record, for example, "parking space number 001, occupancy status identifier 1" indicates that parking space number 001 is occupied. Then, all such association records for parking spaces are arranged in a certain order, such as ascending or descending order of parking space numbers, to generate a status association table. The status association table can be stored in the system's memory or database in tabular form.

[0041] Step S124: Convert the precise vehicle location information into location coordinates in the parking lot's internal coordinate system to obtain the internal location coordinates.

[0042] In this embodiment, the precise vehicle location information of the user's current vehicle is obtained based on a satellite positioning system or other global coordinate system, while the parking space location information within the parking lot is typically described based on the parking lot's internal coordinate system. To facilitate distance calculation and matching between the user's current vehicle location and parking space locations, the precise vehicle location information needs to be converted into location coordinates within the parking lot's internal coordinate system. The parking lot's internal coordinate system is a coordinate system defined by the parking lot management for ease of management and navigation. It is typically established with a fixed point in the parking lot, such as the center point at the entrance, as the origin, with the horizontal direction as the X-axis and the vertical direction as the Y-axis. During the conversion process, the system first retrieves the conversion parameters between the parking lot's internal coordinate system and the global coordinate system from the database, such as translation, rotation, and scaling parameters. Then, these conversion parameters are used to perform mathematical transformation operations on the longitude and latitude coordinates in the precise vehicle location information, converting them into X-axis and Y-axis coordinates within the parking lot's internal coordinate system, i.e., the internal location coordinates. For example, if the coordinates of a point in the global coordinate system, after calculation using the conversion parameters, result in a certain X-coordinate and a certain Y-coordinate in the parking lot's internal coordinate system, then this combination of values ​​represents the internal location coordinates of that point.

[0043] Step S125: Perform distance correlation processing between the internal location coordinates and the parking space location coordinates, and filter out unoccupied parking spaces that are within a preset range from the user's current vehicle location by combining the occupancy status indicator.

[0044] In this embodiment, the system's database stores the position coordinates of all parking spaces within the parking lot's internal coordinate system. Each parking space's position coordinate corresponds to its center position or the position of a specific reference point. First, the system retrieves the position coordinates of all parking spaces from the database and, combined with the status association table generated in step S1237, obtains the occupancy status identifier for each parking space. Then, the system calculates the distance between the user's current vehicle's internal position coordinates and the position coordinates of each parking space. The distance calculation uses the Euclidean distance formula, where the distance between the user's current vehicle position coordinates (X1, Y1) and a parking space position coordinate (X2, Y2) is the square root of the sum of the squares of the differences between the two coordinate points along the X-axis and the Y-axis. After calculation, the system compares the distance value of each parking space with a preset range. This preset range is pre-set based on the actual layout of the parking lot and the user's convenience needs, for example, parking spaces within 50 meters of the user's current vehicle position. At the same time, based on the parking space occupancy status indicators, parking spaces that are within a preset range and whose occupancy status indicator is "unoccupied" are selected. These parking spaces are the unoccupied parking spaces that are within a preset range from the user's current vehicle location.

[0045] Step S126: Integrate the location information, parking space number, and occupancy status identifier of the selected unoccupied parking spaces to generate available parking space distribution information.

[0046] In this embodiment, after filtering in step S125, a list of unoccupied parking spaces within a preset range from the user's current vehicle location is obtained. Next, the information related to these unoccupied parking spaces needs to be integrated to generate available parking space distribution information. During the integration process, the system retrieves the location information (including X-axis and Y-axis coordinates in the parking lot's internal coordinate system), parking space number, and occupancy status indicator (unoccupied indicator) for each filtered unoccupied parking space from the database. Then, this information is organized according to a certain data format, for example, forming a structure array containing multiple fields, each structure corresponding to an unoccupied parking space, including fields such as parking space number, X-coordinate, Y-coordinate, and occupancy status indicator. Simultaneously, to facilitate use when generating the candidate parking space set later, additional information can be added to each unoccupied parking space, such as the size of the parking space (whether it is suitable for large vehicles), whether there are charging facilities, etc. In this embodiment, the available parking space distribution information mainly includes location information, parking space number, and occupancy status indicator. Finally, this integrated information is stored as available parking space distribution information, which can be stored and transmitted in data exchange formats such as JSON and XML for subsequent steps.

[0047] Step S130: Based on the parking demand type, the corresponding charging calculation rule is invoked, and the available parking space distribution information is fused and analyzed with the charging calculation rule to obtain a candidate set of parking spaces containing the location of the parking spaces and the corresponding charging standards. In this embodiment, after obtaining the available parking space distribution information, the system needs to invoke the corresponding charging calculation rule according to the user's parking demand type, and fuse and analyze the available parking space distribution information with these rules. The purpose of this step is to recommend parking spaces that meet the user's parking needs and willingness to pay, achieving accurate matching between parking spaces and charges.

[0048] Step S131: Analyze the parking demand type, distinguish between temporary parking demand and long-term parking demand, and retrieve the temporary charging rules corresponding to temporary parking demand and the long-term charging rules corresponding to long-term parking demand from the parking management system. The temporary charging rules are the rules for charging based on the parking duration, and the long-term charging rules are the rules for charging based on a fixed period.

[0049] In this embodiment, the parking demand type determined in step S116 is first parsed to clarify whether the user's parking demand is temporary or long-term. The system retrieves the corresponding charging rules from the database by accessing the parking management system's database interface. The parking management system pre-stores charging rules for different parking demand types. Temporary charging rules are mainly based on the duration of vehicle parking, such as charging a certain amount per hour, with different rates for different time periods (e.g., day and night). Long-term charging rules are based on fixed periods, such as charging a certain amount per month, with users paying for one or more periods at once. During the call process, the system sends a rule call request to the parking management system based on the parsed parking demand type, and the request includes an identifier for the parking demand type. The parking management system queries the database based on this identifier and returns the corresponding charging rule data. Temporary and long-term charging rules are stored in different data structures, including information such as billing unit, rate, and preferential policies.

[0050] Step S132: Extract the location coordinates of available parking spaces from the available parking space distribution information, and determine the parking lot functional area to which the available parking space belongs based on the location coordinates. The parking lot functional area is either the area near the entrance or the area far from the entrance.

[0051] In this embodiment, the available parking space distribution information includes the location coordinates (X-axis and Y-axis coordinates in the parking lot's internal coordinate system) of each available parking space. The system first extracts the location coordinates of each available parking space from the available parking space distribution information. Then, it determines the parking lot functional area to which each available parking space belongs based on these location coordinates. The division of parking lot functional areas is mainly based on the distance between the parking space and the parking lot entrance / exit, dividing the parking lot into areas close to the entrance / exit and areas far from the entrance / exit. The system's database stores the location coordinates of all parking lot entrances / exits in the parking lot's internal coordinate system. For each available parking space, the distance between its location coordinates and the location coordinates of each entrance / exit is calculated, and the minimum distance is taken as the distance from the parking space to the entrance / exit. Then, this minimum distance is compared with a preset area division distance threshold. If it is less than or equal to the threshold, the parking space belongs to the area close to the entrance / exit; if it is greater than the threshold, it belongs to the area far from the entrance / exit. For example, if the preset area division distance threshold is 30 meters, and the distance from an available parking space to the nearest entrance / exit is 20 meters, then that parking space belongs to the area close to the entrance / exit; if the distance from another available parking space to the nearest entrance / exit is 40 meters, then it belongs to the area far from the entrance / exit.

[0052] Step S133: Adjust the corresponding charging calculation rules according to the functional areas of the parking lot. The parking fee standard for areas near the entrance and exit is adjusted to a different standard than that for areas far from the entrance and exit by a preset ratio.

[0053] In this embodiment, parking spaces near the entrance / exit are more convenient to use, making parking and retrieving easier for users. Therefore, their fees are typically higher than those in areas farther from the entrance / exit. The system adjusts the charging calculation rules retrieved from the parking management system based on the parking lot functional area to which each available parking space belongs, as determined in step S132. First, a preset proportional adjustment coefficient is obtained from the system configuration file. This coefficient is pre-set based on the parking lot's operational strategy and market research results. For example, the charging standard for parking spaces near the entrance / exit can be 1.2 times that of parking spaces farther from the entrance / exit. For temporary charging rules, the hourly rate is adjusted; for long-term charging rules, the fee for each period is adjusted. For example, if the temporary base rate for parking spaces farther from the entrance / exit is A yuan per hour, then the temporary rate for parking spaces near the entrance / exit is A yuan multiplied by 1.2; if the long-term base rate for parking spaces farther from the entrance / exit is B yuan per month, then the long-term rate for parking spaces near the entrance / exit is B yuan multiplied by 1.2. This method of adjusting according to a preset proportion ensures that the charging standard for parking spaces near the entrance / exit differs from that for parking spaces farther from the entrance / exit.

[0054] Step S134: Associate the location information and parking space number of available parking spaces with the adjusted charging calculation rules to generate a parking space charging association table.

[0055] In this embodiment, after adjusting the charging calculation rules, it is necessary to associate the location information and parking space number of each available parking space with the adjusted charging calculation rules to clarify the charging standard for each parking space. First, the location information (internal location coordinates) and parking space number of each available parking space are obtained from the available parking space distribution information. Then, based on the parking lot functional area to which each parking space belongs, the corresponding adjusted charging calculation rule is determined. For example, for parking spaces near the entrance / exit area, the adjusted near-area charging rule is applied; for parking spaces far from the entrance / exit area, the adjusted far-area charging rule (i.e., the basic charging standard) is applied. Next, the parking space number and location information of each available parking space are associated with the charging standard (such as temporary rate, long-term fee, etc.) in the corresponding adjusted charging calculation rule to form an association record. Finally, all the association records of available parking spaces are arranged in a certain order (such as parking space number order or order from closest to farthest from the user's current vehicle location) to generate a parking space charging association table. The parking space fee association table can be a two-dimensional table structure, containing columns such as parking space number, location coordinates (X, Y), area, and fee standard. Each row corresponds to the association information of an available parking space.

[0056] Step S135: Sort the parking spaces in the parking space fee association table according to the sequence formed by the fee standard, and filter out the preset number of parking spaces at the top of the sort.

[0057] In this embodiment, the system creates a sequence of all parking spaces in the parking space fee association table according to their fee standards and sorts them. The sorting method varies depending on the type of parking demand. For temporary parking demand, it sorts by hourly rate from low to high; for long-term parking demand, it sorts by period fee from low to high. After sorting, the system selects a preset number of parking spaces from the sorted sequence. The preset number is pre-set based on the number of parking spaces in the parking lot and the user's selection needs. For example, the preset number is five, meaning the five parking spaces with the lowest fees are selected as candidate parking spaces. If the number of available parking spaces is less than the preset number, all available parking spaces are selected.

[0058] Step S136: Organize the location information, parking space number and corresponding fee standard of the selected parking spaces to generate a candidate set of parking spaces containing the location of the parking spaces and the corresponding fee standard.

[0059] In this embodiment, after filtering in step S135, a preset number of parking spaces with the highest ranking are obtained. Next, the relevant information of these parking spaces needs to be organized to generate a candidate parking space set. During the organization process, the location information (X-axis and Y-axis coordinates in the parking lot's internal coordinate system), parking space number, and corresponding charging standards (such as temporary hourly rates, long-term monthly fees, etc.) of these selected parking spaces are extracted from the parking space charging association table. Then, this information is organized according to a certain data format, similar to the available parking space distribution information, forming a structure array or other data structure, where each element contains fields such as parking space number, location coordinates, and charging standards. Simultaneously, some descriptive information can be added to the candidate parking space set, such as detailed descriptions of the charging standards for each parking space (such as the first hour rate for temporary parking, subsequent hourly rates, etc.), but... In this embodiment, the parking space candidate set mainly includes the parking space location, parking space number, and corresponding charging standard. Finally, the organized information is stored as a parking space candidate set, which will serve as the basic data for the next step of planning the navigation route.

[0060] Step S1331: Obtain the location coordinates of the parking lot entrance and exit, and use the location coordinates of the entrance and exit as the reference point for area division.

[0061] In this embodiment, step S133 mentions adjusting the charging calculation rules according to the functional areas of the parking lot. Determining the functional areas requires first dividing the area into zones, and the reference points for dividing the zones are the location coordinates of the parking lot entrances and exits. Therefore, it is first necessary to obtain the location coordinates of the parking lot entrances and exits. The system accesses the database of the parking management system to query and obtain the location coordinates of all parking lot entrances and exits in the parking lot's internal coordinate system. A parking lot may have multiple entrances and exits, such as main entrances and exits, secondary entrances and exits, etc., each with its unique identifier and corresponding location coordinates. These entrance and exit location coordinates are stored in a temporary data list as reference points for zone division. For example, a parking lot may have two entrances and exits with internal location coordinates (X01, Y01) and (X02, Y02) respectively; these two coordinate points are used as reference points for zone division.

[0062] Step S1332: Using the reference point as the center, divide the parking lot into areas close to the entrance and exit and areas far from the entrance and exit according to a preset distance range. Areas within the preset distance range from the reference point are areas close to the entrance and exit, and areas outside the preset distance range are areas far from the entrance and exit.

[0063] In this embodiment, after obtaining the location coordinates of the parking lot entrance and exit as reference points, the area needs to be divided according to a preset distance range. This preset distance range is pre-set by the parking lot management based on factors such as the size of the parking lot, parking space density, and operational strategies, and is stored in the system's configuration file. For each reference point (entrance / exit location coordinates), a circle is drawn with that point as the center and the preset distance range as the radius. The area within this circle represents the area near the entrance / exit, based on that specific entrance / exit. For a parking space within the parking lot, if its location coordinates are within the area near any entrance / exit, then that parking space belongs to the area near the entrance / exit; if its location coordinates are not within the area near any entrance / exit, then it belongs to the area far from the entrance / exit. For example, if the preset distance range is 30 meters, and the distance between the location coordinates of a parking space and the location coordinates of an entrance / exit is 25 meters (less than 30 meters), then that parking space belongs to the area near the entrance / exit; if the distance is 35 meters (greater than 30 meters), then it belongs to the area far from the entrance / exit. In this way, the entire parking lot is divided into areas near and far from the entrance / exit.

[0064] Step S1333: Retrieve the basic charging standard for parking spaces far from the entrance / exit area from the parking management system. The basic charging standard is the default charging standard for parking spaces far from the entrance / exit area.

[0065] In this embodiment, the parking fee standard for spaces far from the entrance / exit area serves as the base fee standard, acting as the benchmark for adjusting parking fee standards in other areas. The system sends a query request to the database through the parking management system's database interface, containing an instruction to query the base fee standard for parking spaces far from the entrance / exit area. The parking management system's database specifically stores base data for various fee standards, including the base fee standards for parking spaces far from the entrance / exit area under both temporary and long-term parking needs. Upon receiving the query request, the database queries and returns the corresponding base fee standard data based on the request conditions. For example, the base fee standard for temporary parking needs is A yuan per hour, with different rates for the first hour, such as A1 yuan for the first hour and A2 yuan for subsequent hours (A2 is less than A1); the base fee standard for long-term parking needs is B yuan per month, with possible discounts for quarterly or annual payments, but the base standard remains B yuan per month. This base fee standard data, once retrieved, is stored in the system's temporary variables.

[0066] Step S1334: Obtain the preset proportional adjustment coefficient, which is a fixed coefficient pre-stored in the parking management system.

[0067] In this embodiment, the preset proportional adjustment coefficient is a key parameter used to adjust the parking fee standard near the entrance / exit area. It is determined by the parking lot management based on factors such as market conditions, parking space supply and demand, and operating costs, and is pre-stored in the parking management system's configuration database. The system sends a request to the parking management system's configuration interface to retrieve the proportional adjustment coefficient. The configuration database queries and returns the preset proportional adjustment coefficient based on the request. This coefficient can be a value greater than 1, such as 1.2, representing that the parking fee standard near the entrance / exit area is 1.2 times the basic fee standard for parking spaces further away from the entrance / exit area. The proportional adjustment coefficient may vary depending on the type of parking demand; for example, the proportional adjustment coefficient for temporary parking is 1.2, while the proportional adjustment coefficient for long-term parking is 1.1. In this embodiment, it is assumed that the adjustment coefficients for temporary and long-term parking are the same, both being a fixed value. After obtaining the adjustment coefficients, they are stored in system variables.

[0068] Step S1335: Use the proportional adjustment coefficient to process the basic charging standard to obtain the charging standard for parking spaces near the entrance and exit.

[0069] In this embodiment, after obtaining the basic fee standard and preset proportional adjustment coefficient for parking spaces far from the entrance / exit area, the fee standard for parking spaces near the entrance / exit area can be calculated. For temporary fee standards, the hourly rate in the basic fee standard is multiplied by the proportional adjustment coefficient. For example, if the temporary basic fee rate for the area far from the entrance / exit is A yuan per hour and the proportional adjustment coefficient is 1.2, then the temporary fee rate for the area near the entrance / exit is A yuan multiplied by 1.2, resulting in A × 1.2 yuan per hour. If the temporary fee standard has a first hour and subsequent hours, the rates for the first hour and subsequent hours are adjusted separately. For example, if the basic fee rate for the first hour is A1 yuan, the adjusted rate is A1 × 1.2 yuan; if the basic fee rate for subsequent hours is A2 yuan, the adjusted rate is A2 × 1.2 yuan. For long-term fee standards, the periodic fee in the basic fee standard is multiplied by the proportional adjustment coefficient. For example, if the long-term basic fee for the area far from the entrance / exit is B yuan per month, the adjusted rate is B × 1.2 yuan, i.e., B × 1.2 yuan per month. Through this multiplication operation, the fee standard for parking spaces near the entrance / exit area is obtained, which is higher than the basic fee standard for the area far from the entrance / exit.

[0070] Step S1336: Associate the available parking spaces in the area near the entrance / exit with the processing fee standards for parking spaces in the area near the entrance / exit, and associate the available parking spaces in the area far from the entrance / exit with the basic fee standards to generate an area fee correspondence table.

[0071] In this embodiment, after determining the charging standards for parking spaces near and far from the entrance / exit areas, it is necessary to associate the available parking spaces in the available parking space distribution information with their corresponding charging standards to generate a regional charging correspondence table. First, each available parking space in the available parking space distribution information is traversed, and the corresponding charging standard is matched according to the parking lot functional area (near or far from the entrance / exit area) to which each parking space belongs, as determined in step S132. For available parking spaces near the entrance / exit area, they are associated with the charging standards of parking spaces in the area near the entrance / exit obtained in step S1335; for available parking spaces far from the entrance / exit area, they are associated with the basic charging standards retrieved in step S1333. During the association process, a record is created for each available parking space, containing fields such as parking space number, area identifier (near or far), and charging standard. Then, all these records are arranged in order of parking space number to generate a regional charging correspondence table. The regional charging correspondence table can be stored in the system's memory for quick querying of the charging standard for each parking space when generating the parking space charging correspondence table in step S134.

[0072] Step S1337: Verify the area identifier, available parking space information and corresponding charging standards in the area charging correspondence table to ensure the accuracy of the association between the area and the charging standards.

[0073] In this embodiment, after generating the area fee correspondence table, verification is required to ensure the accuracy of the relationships between area identifiers, available parking space information, and corresponding fee standards. The verification process employs multiple methods. First, a data integrity check is performed, examining whether there are any missing fields in the area fee correspondence table, such as parking space number, area identifier, or whether the fee standard is empty. Then, a logical consistency check is performed. For each available parking space, its area identifier is recalculated based on its location coordinates and compared with the area identifier recorded in the table. If they do not match, an error exists. Simultaneously, it is checked whether the fee standard matches the area identifier; that is, whether the fee standard for parking spaces near the entrance / exit area is the adjusted standard, and whether the fee standard for parking spaces far from the entrance / exit area is the basic standard. Furthermore, sampling verification can be performed, randomly selecting some available parking spaces and manually verifying their area and fee standard for accuracy. If errors are found during the verification process, the system will automatically issue an alarm and prompt relevant management personnel to handle the issue. Only after all relationships are accurate will the area fee correspondence table be officially used for generating subsequent parking space fee association tables.

[0074] Step S140: Based on the parking space candidate set, plan a navigation path from the user's current vehicle location to the target parking space and generate path navigation information. In this embodiment, after obtaining the parking space candidate set, the system needs to plan a navigation path from the user's current vehicle location to the target parking space based on this set and generate path navigation information. The target parking space can be a specific parking space in the parking space candidate set. In this embodiment, it is assumed that the target parking space is the first-ranked parking space in the candidate set, meaning it has the lowest fee and is also advantageous in terms of distance and other conditions. Route navigation information will guide the user to drive their vehicle smoothly to the target parking space, which is a crucial step in realizing intelligent parking guidance.

[0075] Step S141: Extract the location coordinates of the target parking space from the candidate parking space set, use the location coordinates of the target parking space as the endpoint coordinates of the path planning, and use the user's current vehicle location information as the starting coordinates of the path planning.

[0076] In this embodiment, the starting and ending points of the path planning need to be clearly defined first. The starting coordinates are the position coordinates of the user's current vehicle's precise location information obtained in step S121 within the parking lot's internal coordinate system, i.e., the internal position coordinates (Xs, Ys). The ending coordinates are the position coordinates of the target parking space in the parking space candidate set. The position coordinates (Xe, Ye) of the target parking space are extracted from the parking space candidate set, which are also the X-axis and Y-axis coordinates within the parking lot's internal coordinate system. When determining the target parking space, if there are many parking spaces in the candidate set, the system can determine the target parking space based on the user's further selection or default rules (such as lowest price, closest distance, etc.). In this embodiment, the parking space ranked first is selected as the target parking space by default. The starting and ending coordinates are stored in the variables of the path planning module as input parameters for path search.

[0077] Step S142: Call the map building unit in the path planning module to obtain the channel layout data in the parking lot. The channel layout data includes the channel direction, channel connection relationship and traffic restriction information in the channel.

[0078] In this embodiment, the path planning module is the core module responsible for calculating navigation paths in the system, while the map building unit is used to build and maintain digital map data for the parking lot. The system calls the map building unit within the path planning module through an internal interface, sending a request to obtain lane layout data. Upon receiving the request, the map building unit retrieves the latest lane layout data for the parking lot from its database. Lane layout data describes the network structure of lanes within the parking lot, including the direction of the lanes (e.g., east-west, north-south, turning directions); lane connections (i.e., which lanes are interconnected, forming nodes and edges in the lane network); and lane restrictions (e.g., one-way traffic, no left turns, lane width restrictions, height restrictions, etc.). This data is stored in a specific format, such as a graph data structure, where nodes represent lane intersections or endpoints, edges represent lanes, and edge attributes include lane direction, length, and traffic restrictions. After obtaining the lane layout data, it is loaded into the memory of the path planning module.

[0079] Step S143: Construct an internal path map of the parking lot based on the channel layout data, and mark the starting point coordinates and the ending point coordinates in the path map.

[0080] In this embodiment, the path map is an abstract model representing the parking lot access network, transforming access layout data into a data structure usable by the path search algorithm. During construction, the access connection relationships in the access layout data are first parsed, and the intersections or endpoints of the access routes are used as nodes in the path map. Each node has a unique identifier and its position coordinates within the parking lot's internal coordinate system. Then, the access routes connecting the nodes are used as edges in the path map. Each edge has attributes such as direction (determined based on the route and traffic restrictions), length (the actual length of the access route), and traffic restrictions. For example, if an access route is unidirectional, the corresponding edge is a directed edge, pointing only from one node to another. After the path map is constructed, the starting and ending coordinates determined in step S141 are marked on the map, i.e., the locations of the nodes or edges containing the starting and ending coordinates are found and marked in the path map so that the path search algorithm can clearly identify the starting and target locations for the search.

[0081] Step S144: Use a path search algorithm to search for a path from the starting point coordinates to the ending point coordinates in the path map, and generate multiple candidate navigation paths. The candidate navigation paths include the channel numbers passed through, the path length, and the estimated travel time.

[0082] In this embodiment, the path search algorithm is the core algorithm of path planning. Commonly used algorithms include Dijkstra's algorithm and A* algorithm. This embodiment uses the A* algorithm for path search because it has high search efficiency and optimal solution guarantee in static road networks. During the search process, the A* algorithm comprehensively considers the actual cost from the starting point to the current node (e.g., path length) and the estimated cost from the current node to the destination (e.g., straight-line distance), guiding the search direction through a heuristic function. In the path map, starting from the node corresponding to the starting point coordinates, the search nodes are gradually expanded according to the channel connection relationship, and the cost of each possible path is calculated. During the search process, multiple possible paths from the starting point to the destination are generated, i.e., candidate navigation paths. For each candidate navigation path, the sequence of channel numbers it passes through, the total length of the path (the sum of the lengths of each channel segment), and the estimated travel time are recorded. The estimated travel time is calculated based on the path length and the preset average travel speed of the channels. For example, if the average travel speed of the channels is 15 kilometers per hour and the path length is a certain value, the length unit is converted to kilometers, the time unit is converted to hours, and the two are divided to obtain the estimated travel time, which is then converted to minutes or seconds.

[0083] Step S145: Perform feasibility processing on candidate navigation paths, exclude candidate navigation paths with traffic restrictions, and retain feasible candidate navigation paths.

[0084] In this embodiment, the generated multiple candidate navigation paths may include some paths with traffic restrictions, such as those passing through temporarily closed passages, passages with obstacles, or paths that conflict with passageway traffic direction restrictions. These paths are not feasible and need to be eliminated through traffic feasibility processing. Traffic feasibility processing is an important step to ensure that the navigation path can actually be traveled. It combines real-time traffic status information within the parking lot to filter candidate navigation paths.

[0085] Step S146: Sort the feasible candidate navigation paths according to the sequence formed by the estimated travel time, and select the feasible candidate navigation path ranked first as the optimal navigation path.

[0086] In this embodiment, the optimal navigation path needs to be selected from these feasible paths. There can be various criteria for selecting the optimal path, such as shortest path length, least estimated travel time, and fewest turns. In this embodiment, the shortest estimated travel time is chosen as the criterion for sorting. Feasible candidate navigation paths are sorted in ascending order of their estimated travel time, forming a sequence. Then, the first-ranked feasible candidate navigation path, i.e., the path with the shortest estimated travel time, is selected as the optimal navigation path. If multiple paths have the same estimated travel time, other factors such as path length or number of turns can be further compared to select the path that best combines all these factors.

[0087] Step S147: Parse the path information of the optimal navigation path and generate path navigation information including turning prompts, distance prompts and channel number prompts.

[0088] In this embodiment, during the parsing process, the sequence of channel numbers traversed by the optimal navigation path is first extracted, for example, channel numbers are C01, C03, C05, etc. Then, based on the connection relationship and direction of the channels, the turning operation required at the exit of each channel is determined, such as going straight, turning left, turning right, or making a U-turn, forming a turning prompt. Simultaneously, the distance from each turning point to the current vehicle position is calculated, forming a distance prompt, such as "Turn left 50 meters ahead to enter channel C03." Furthermore, the channel number is also included as part of the prompt information, informing the user of the currently traveling channel and the channel number to be entered, such as "Currently traveling in channel C01, turn left ahead to enter channel C03." These turning prompts, distance prompts, and channel number prompts are organized according to the vehicle's travel sequence to form structured path navigation information.

[0089] Step S1451: Call the traffic status monitoring module in the parking lot to obtain real-time lane access restriction information. The lane access restriction information includes temporary lane closure signs, the location of obstacles in the lane, and lane traffic direction restrictions.

[0090] In this embodiment, the traffic status monitoring module monitors the traffic status of the parking lot lanes in real time using various sensors installed within the lanes, such as infrared sensors, cameras, and inductive loops. The system calls this module via a network interface to obtain real-time lane access restriction information. This information is a comprehensive dataset containing temporary lane closure identifiers (a list of lane numbers currently closed due to maintenance, accidents, etc.); obstacle locations within the lanes (the coordinates of obstacles such as construction materials and disabled vehicles within the parking lot's internal coordinate system); and lane direction restrictions (which lanes are one-way and their permitted directions, e.g., lane C02 only allows east-to-west travel). This information is stored in the traffic status monitoring module's database in real-time and, after being retrieved by the system, is stored in a local cache for use in determining the feasibility of candidate navigation paths.

[0091] Step S1452: Extract the channel numbers traversed by the candidate navigation path, compare the channel numbers with the temporary closed channel identifiers in the real-time channel access restriction information, and generate the first comparison result.

[0092] In this embodiment, all channel numbers traversed by each candidate navigation path are extracted from its path information to form a channel number list. For example, for a candidate navigation path, the channel number list is [C01, C02, C04]. Then, a list of temporary closed channel identifiers is extracted from real-time channel access restriction information, such as [C02, C07]. The channel number list of the candidate navigation path is compared with the list of temporary closed channel identifiers to check whether the channel number list of the candidate navigation path contains any channel number from the list of temporary closed channel identifiers. The comparison can be achieved through set operations, such as calculating the intersection of the two lists. If the intersection is not empty, it means that the candidate navigation path traverses a temporary closed channel; if the intersection is empty, it means that it does not. The generated first comparison result is a Boolean value. For each candidate navigation path, if it traverses a temporary closed channel, the first comparison result is true; otherwise, it is false.

[0093] Step S1453: Filter candidate navigation paths based on the first comparison result. If the channel number traversed by the candidate navigation path is included in the temporary closed channel identifier, then exclude the candidate navigation path.

[0094] In this embodiment, for each candidate navigation path, if the first comparison result is true, meaning the channel number it traverses is included in the temporary closed channel identifier, it indicates that the path traverses a temporarily closed channel and is therefore impassable, and thus it is excluded. If the first comparison result is false, meaning none of the channels traversed by the candidate navigation path are temporarily closed, then the candidate navigation path is retained and proceeds to the next feasibility check. Through this step, paths that are infeasible due to channel closures can be initially eliminated.

[0095] Step S1454: If the channel number passed by the candidate navigation path is not included in the temporary closed channel identifier, further extract the obstacle location information in the channel, extract the path coordinates of the candidate navigation path and compare them with the obstacle positions to generate a coordinate comparison result.

[0096] In this embodiment, firstly, detailed path coordinates within each channel are extracted from the path information of the candidate navigation paths. These coordinates are the position coordinates of a series of continuous points on the path, describing the vehicle's trajectory within the channel. Then, obstacle position information within these channels is extracted from real-time channel access restriction information, i.e., the position coordinates of the obstacles in the parking lot's internal coordinate system. For each channel, the path coordinates of the candidate navigation paths within that channel are compared with the obstacle position coordinates. The coordinate comparison uses a distance judgment method, calculating the distance between each point in the path coordinates and the obstacle position coordinates. If the distance between any path point and the obstacle position is less than a preset safe distance threshold, it indicates a conflict between the path and the obstacle; otherwise, there is no conflict. The preset safe distance threshold is determined based on the channel width and vehicle size, for example, 1.5 meters. The generated coordinate comparison result is a Boolean value. For each candidate navigation path, if the distance between its path coordinates and the obstacle position in any channel is less than the safe distance threshold, the coordinate comparison result is true; otherwise, it is false.

[0097] Step S1455: Filter candidate navigation paths based on coordinate comparison results. If the path coordinates overlap with the obstacle position, exclude the candidate navigation path.

[0098] In this embodiment, for each candidate navigation path, if the coordinate comparison result is true (meaning the path coordinates overlap with the location of an obstacle within the channel (the distance is less than the safe distance threshold), it indicates that the vehicle would collide with the obstacle if it follows the path, and therefore the path is excluded. If the coordinate comparison result is false (meaning the path does not overlap with the obstacle), the candidate navigation path is retained and proceeds to the next feasibility check. This step eliminates paths that are infeasible due to obstacles within the channel.

[0099] Step S1456: If the path coordinates do not overlap with the obstacle position, extract the channel travel direction restriction, extract the driving direction of the candidate navigation path and compare it with the channel travel direction restriction to generate the direction comparison result.

[0100] In this embodiment, firstly, the traffic direction restriction for each channel is extracted from real-time channel traffic restriction information. For example, the traffic direction restriction for channel C03 is that it only allows travel from node N05 to node N06 (i.e., one-way traffic). Then, the travel direction within each channel is extracted from the path information of the candidate navigation path, i.e., the node where the vehicle enters the channel and the node where it leaves the channel, thereby determining the travel direction. For example, if the candidate navigation path in channel C03 travels from node N05 to node N06, then the travel direction is consistent with the traffic direction restriction of channel C03; if it travels from node N06 to node N05, then the travel direction is opposite to the traffic direction restriction. The travel direction of the candidate navigation path in each channel is compared with the traffic direction restriction of that channel to generate a direction comparison result. The direction comparison result is a Boolean value. For each candidate navigation path, if its driving direction in all channels is consistent with the channel's travel direction restriction, the direction comparison result is true; if there is any channel where the driving direction is inconsistent with the channel's travel direction restriction, the direction comparison result is false.

[0101] Step S1457: Filter candidate navigation paths based on the direction comparison results. If the driving direction is consistent with the passage direction restriction, the candidate navigation path is retained; if the driving direction is inconsistent with the passage direction restriction, the candidate navigation path is excluded.

[0102] In this embodiment, for each candidate navigation path, if the direction comparison result is true, meaning that its driving direction in all channels conforms to the channel's travel direction restriction, then the candidate navigation path is feasible and is retained as a feasible candidate navigation path. If the direction comparison result is false, meaning that there is at least one channel where the driving direction is inconsistent with the travel direction restriction, then the candidate navigation path violates the traffic rules and cannot be passed, and is excluded. Through this series of screening steps, the final feasible candidate navigation paths are those that can be passed safely and legally.

[0103] Step S150: Integrate the route navigation information with the charging standards in the parking space candidate set to generate an integrated parking fee guidance instruction, and send the parking fee guidance instruction to the user's in-vehicle terminal. In this embodiment, after generating the route navigation information and the parking space candidate set, these two types of information need to be integrated to generate an integrated parking fee guidance instruction, which is then sent to the user's in-vehicle terminal.

[0104] Step S151: Extract the turning prompts, distance prompts, and channel number prompts from the route navigation information, and organize the turning prompts, distance prompts, and channel number prompts into structured navigation text according to the driving sequence.

[0105] In this embodiment, turning prompts include "turn left," "go straight," and "turn right"; distance prompts include "50 meters later" and "100 meters later"; and lane number prompts include "enter lane C03" and "driving in lane C05." After extracting this information, it is organized according to the vehicle's driving sequence to form structured navigation text. The structured navigation text adopts a paragraph-based text structure, with each paragraph corresponding to a driving step, including distance prompts, turning prompts, and lane number prompts for that step. For example, "Turn left 50 meters ahead to enter lane C03; drive 100 meters along lane C03 and then turn right to enter lane C05;...". This method of organizing by driving sequence allows the structured navigation text to clearly and coherently guide the user's driving.

[0106] Step S152: Extract the charging standards associated with the target parking space from the candidate parking space set, break down the charging standards into billing cycle, unit cost and estimated total cost, and organize them into a structured charging text.

[0107] In this embodiment, for temporary parking needs, the charging standard typically includes a billing cycle (e.g., per hour), a unit fee (the hourly rate), and an estimated total cost based on the user's likely parking duration (unit fee multiplied by the estimated parking duration). For example, if the temporary charging standard is A × 1.2 yuan per hour, and the user estimates parking for three hours, the estimated total cost is A × 1.2 × 3. For long-term parking needs, the charging standard includes a billing cycle (e.g., per month), a unit fee (the monthly fee), and the estimated total cost can be the cost for one cycle or the total cost for multiple cycles selected by the user. After breaking down this information into billing cycles, unit fees, and estimated total costs, it is described and organized into structured charging text using natural language, such as "Temporary parking charging standard: A × 1.2 yuan per hour, estimated parking for three hours, total cost approximately A × 1.2 × 3 yuan;" or "Long-term parking charging standard: B × 1.2 yuan per month, estimated parking for one month, total cost B × 1.2 yuan." Step S153: Merge the structured navigation text and the structured toll text to match the presentation order of the navigation information and toll information with the vehicle's driving process, and generate merged text information.

[0108] In this embodiment, during fusion, structured charging text is inserted at appropriate positions within the structured navigation text, following the sequence of the vehicle's driving process. Typically, charging information is placed at the beginning or end of the navigation information so that users can understand the charges before starting their journey or gradually learn about them through voice prompts or other methods during the journey. For example, the fused text information could be: "The charging standard for the target parking space you selected is: temporary parking at A × 1.2 yuan per hour. Estimated parking time is three hours, with a total cost of approximately A × 1.2 × 3 yuan. Navigation route: Turn left 50 meters ahead into lane C03; drive 100 meters along lane C03 and then turn right into lane C05;...". This matching of presentation order ensures that users can clearly understand the parking fees while receiving navigation guidance, achieving integration of navigation and charging information.

[0109] Step S154: Perform language optimization on the merged text information, add guiding statements to adapt the merged text information to the user's reading style, and obtain preliminary guiding content.

[0110] In this embodiment, language optimization includes adding guiding statements, such as "Dear user, the following is your parking fee and navigation guidance information:"; adjusting the word order and expression to make the text smoother and more natural; and using concise and clear vocabulary, avoiding technical jargon or ambiguous expressions. For example, "The estimated total cost is A × 1.2 × 3 yuan" is optimized to "The estimated total cost for your three-hour parking is approximately A × 1.2 × 3 yuan." Through these optimizations, the integrated text information becomes more user-friendly and easier to understand, resulting in preliminary guidance content.

[0111] Step S155: Call the instruction generation module to encapsulate the initial guidance content in a format, add instruction identifier, instruction length and verification information, and generate parking fee guidance instructions.

[0112] In this embodiment, the initial guidance content is in text format, which needs to be encapsulated into a parking fee guidance instruction conforming to the format received by the user's in-vehicle terminal for transmission and parsing. The instruction generation module is responsible for completing this format encapsulation process, adding necessary instruction header and footer information such as instruction identifier, instruction length, and verification information.

[0113] Step S156: Invoke the wireless communication module to establish a communication connection with the user's vehicle terminal and send the parking fee guidance instruction to the user's vehicle terminal.

[0114] In this embodiment, the system invokes a wireless communication module that supports various wireless communication methods such as Bluetooth, Wi-Fi, and cellular networks. First, the wireless communication module scans for nearby connectable user vehicle terminals, identifying and establishing a communication connection with the target user's vehicle terminal using its unique identifier (such as Bluetooth MAC address, device number, etc.). Once the connection is successfully established, the wireless communication module sends parking fee guidance instructions to the vehicle terminal in the form of data packets. During transmission, data verification and retransmission mechanisms are implemented to ensure accurate transmission of the instructions. Upon receiving the parking fee guidance instructions, the vehicle terminal parses them and presents the guidance information to the user through display screen and voice announcement.

[0115] Step S1551: Call the format definition unit in the instruction generation module to obtain the instruction format specifications supported by the user's vehicle terminal. The instruction format specifications include the structural requirements of the instruction header, instruction body and instruction tail.

[0116] In this embodiment, the system calls the format definition unit in the instruction generation module. This unit stores various common vehicle terminal instruction format specifications, or can dynamically obtain supported format specifications by querying the vehicle terminal's configuration information. The instruction format specification defines the instruction structure in detail, including the composition and requirements of the instruction header, instruction body, and instruction tail. The instruction header typically includes an instruction identifier, version number, sender identifier, etc.; the instruction body is the text data of the initial guiding content; and the instruction tail includes verification information, instruction length, etc.

[0117] Step S1552: According to the instruction format specification, add an instruction identifier to the header of the preliminary guidance content. The instruction identifier is used to identify that the instruction corresponding to the instruction identifier is a parking fee guidance instruction.

[0118] In this embodiment, based on the obtained instruction format specification, an instruction identifier corresponding to the parking fee guidance instruction is selected from the system's preset instruction identifier list, such as "PARKING_GUIDE_CMD". This instruction identifier is added to the header of the initial guidance content as the starting part of the instruction header. The length and encoding method of the instruction identifier conform to the requirements of the instruction format specification, for example, using hexadecimal encoding with a length of two bytes.

[0119] Step S1553: Calculate the character length of the initial guidance content, convert the character length into a numerical value in a preset format, and add it as the instruction length after the instruction identifier.

[0120] In this embodiment, firstly, the character length of the initial boot content is calculated, that is, the number of characters contained in the initial boot content (excluding the characters in the instruction header and footer). Then, according to the requirements of the instruction format specification, the character length is converted into a numerical value in a preset format, such as an unsigned integer, stored in big-endian or little-endian byte order. The converted instruction length value is appended after the instruction identifier as part of the instruction header. For example, if the character length of the initial boot content is 120 characters, after being converted to a numerical value in the preset format, it is appended after the instruction identifier "PARKING_GUIDE_CMD".

[0121] Step S1554: Perform verification calculation on the initial guidance content, and generate a verification code using a preset verification algorithm. The verification algorithm includes a cyclic redundancy check algorithm.

[0122] In this embodiment, the preset verification algorithm can be a Cyclic Redundancy Check (CRC32), MD5, SHA, etc., and this embodiment uses a Cyclic Redundancy Check (CRC). The CRC algorithm performs a polynomial division operation on the binary data of the initial boot content, and the remainder is the checksum. Specifically, the initial boot content is converted into a binary data stream, a preset generator polynomial (such as the generator polynomial of CRC32) is selected, and the binary data stream is divided using this polynomial; the remainder is the checksum. The generated checksum has a fixed length; for example, the CRC32 checksum is four bytes.

[0123] Step S1555: Add the verification code to the end of the initial guidance content to form a complete instruction structure including the instruction header, instruction body and instruction tail. This complete instruction structure is the structure of the parking fee guidance instruction.

[0124] In this embodiment, the instruction header includes an instruction identifier and instruction length, the instruction body is the initial guidance content, and the instruction tail is the checksum. The instruction header added in step S1552, the initial guidance content (instruction body), and the checksum generated in step S1554 (instruction tail) are combined sequentially to form a complete instruction structure. For example, the instruction structure is: [Instruction Identifier][Instruction Length][Initial Guidance Content][Checksum]. This structure conforms to the requirements of the instruction format specification and can be correctly parsed by the user's vehicle terminal.

[0125] Step S1556: Encode the complete instruction structure, convert it into binary data format, and generate parking fee guidance instructions.

[0126] In this embodiment, the complete instruction structure currently consists of a character or byte sequence comprising an instruction identifier, instruction length, preliminary boot content, and a checksum. This needs to be encoded to convert it into a binary data format suitable for wireless transmission. The encoding process uses a character encoding method agreed upon with the user's vehicle terminal, such as UTF-8 or ASCII, to convert the text characters in the instruction structure into corresponding binary byte streams.

[0127] Figure 2 The illustration shows exemplary hardware and software components of a smart parking fee guidance system 100 incorporating parking space navigation, which can implement the ideas of this application, according to some embodiments of this application. For example, a processor 120 can be used in the smart parking fee guidance system 100 incorporating parking space navigation and to perform the functions described in this application.

[0128] The intelligent parking fee collection and guidance system 100 integrating parking space navigation can be a general-purpose server or a special-purpose server; both can be used to implement the intelligent parking fee collection and guidance method integrating parking space navigation of this application. Although only one server is shown in this application, for convenience, the functions described in this application can be implemented in a distributed manner on multiple similar platforms to balance the load.

[0129] For example, a smart parking fee guidance system 100 incorporating parking space navigation may include a network port 110 connected to a network, one or more processors 120 for executing program instructions, a communication bus 130, and various forms of storage media 140, such as a disk, ROM, or RAM, or any combination thereof. Exemplarily, the smart parking fee guidance system 100 incorporating parking space navigation may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The methods of this application can be implemented according to these program instructions. The smart parking fee guidance system 100 incorporating parking space navigation also includes an I / O interface 150 between the computer and other input / output devices.

[0130] For ease of explanation, only one processor is described in the smart parking fee guidance system 100 with parking space navigation. However, it should be noted that the smart parking fee guidance system 100 with parking space navigation in this application may also include multiple processors. Therefore, the steps performed by one processor described in this application may also be performed jointly or individually by multiple processors. For example, if the processor of the smart parking fee guidance system 100 with parking space navigation performs steps A and B, it should be understood that steps A and B may also be performed jointly by two different processors or individually by one processor. For example, the first processor performs step A, the second processor performs step B, or the first processor and the second processor jointly perform steps A and B.

[0131] Furthermore, this embodiment of the invention also provides a readable storage medium, wherein computer-executable instructions are preset in the readable storage medium, and when the processor executes the computer-executable instructions, the above-mentioned intelligent parking fee guidance method combined with parking space navigation is implemented.

[0132] It should be noted that, in order to simplify the description of the present invention and thus help to understand one or more embodiments of the invention, multiple features may sometimes be grouped into one embodiment, drawing or description thereof in the foregoing description of the embodiments of the present invention.

Claims

1. A smart parking fee guidance method combined with parking space navigation, characterized in that, The method comprises: acquiring user current vehicle position information and parking demand type, the parking demand type being temporary parking demand or long-term parking demand; calling a parking space state perception module to acquire real-time parking space occupancy information, correlating and matching the user current vehicle position information with the real-time parking space occupancy information, and obtaining available parking space distribution information; calling corresponding charging calculation rules according to the parking demand type, fusing and analyzing the available parking space distribution information and the charging calculation rules, and obtaining a parking space candidate set containing parking space positions and corresponding charging standards; planning a navigation path from the user current vehicle position to a target parking space based on the parking space candidate set, and generating path navigation information; fusing the path navigation information and the charging standards in the parking space candidate set, generating integrated parking charging guidance instructions, and sending the parking charging guidance instructions to a user vehicle terminal. 2.The intelligent parking fee guidance method with parking space navigation of claim 1, wherein, The method comprises: performing position calibration processing on the user current vehicle position information to obtain accurate vehicle position information, the position calibration processing being completed based on preset positioning reference points in the parking lot; calling a parking space camera acquisition unit in the parking space state perception module to acquire real-time image information corresponding to the parking space, the real-time image information containing visual features of a vehicle parked in the parking space; performing vehicle existence identification processing on the real-time image information to generate an occupancy state identifier of the parking space, the occupancy state identifier being an occupied identifier or an unoccupied identifier; converting the accurate vehicle position information into a position coordinate in an internal coordinate system of the parking lot to obtain an internal position coordinate; performing distance correlation processing on the internal position coordinate and a position coordinate of the parking space, and screening out unoccupied parking spaces within a preset range from the user current vehicle position in combination with the occupancy state identifier; integrating the position information, the parking space number, and the occupancy state identifier of the screened unoccupied parking spaces to generate the available parking space distribution information. 3.The intelligent parking fee guidance method combined with parking space navigation according to claim 1, wherein, The method comprises: analyzing the parking demand type to distinguish between temporary parking demand and long-term parking demand, calling temporary charging rules corresponding to the temporary parking demand and long-term charging rules corresponding to the long-term parking demand from a parking lot management system, the temporary charging rules being rules for charging according to parking time length, and the long-term charging rules being rules for charging according to a fixed period; extracting position coordinates of available parking spaces in the available parking space distribution information, and determining parking lot functional areas to which the available parking spaces belong according to the position coordinates, the parking lot functional areas being areas close to entrances or areas far from the entrances; adjusting the corresponding charging calculation rules according to the parking lot functional areas, and adjusting the parking space charging standards in the areas close to the entrances by a preset proportion to be different from the parking space charging standards in the areas far from the entrances; correspondingly associating the position information and the parking space number of the available parking spaces with the adjusted charging calculation rules to generate a parking space charging association table; and Sort the sequence of parking spaces in the parking fee association table according to the charging standards, and screen out a preset number of parking spaces with the highest ranking; Sort the sequence of parking spaces in the parking fee association table according to the charging standards, and screen out a preset number of parking spaces with the highest ranking; 4.The intelligent parking fee guidance method with parking space navigation of claim 3, wherein, The parking fee standard of the parking space in the area close to the entrance is adjusted by a preset proportion to be different from the parking fee standard of the parking space in the area far from the entrance, including: Obtain the position coordinates of the entrance of the parking lot, and take the entrance position coordinates as the reference point for area division; Divide the parking lot into an area close to the entrance and an area far from the entrance according to a preset distance range with the reference point as the center, the area within the preset distance range from the reference point is the area close to the entrance, and the area beyond the preset distance range is the area far from the entrance; Retrieve the basic charging standard of the parking space in the area far from the entrance from the parking lot management system, and the basic charging standard is the default charging standard of the parking space in the area far from the entrance; Obtain a preset proportion adjustment coefficient, and the proportion adjustment coefficient is a fixed coefficient stored in the parking lot management system in advance; Process the basic charging standard using the proportion adjustment coefficient to obtain the charging standard of the parking space in the area close to the entrance; Associate the available parking spaces in the area close to the entrance with the charging standard obtained by processing, and associate the available parking spaces in the area far from the entrance with the basic charging standard to generate a regional charging correspondence table; Verify the area identifier, available parking space information and corresponding charging standard in the regional charging correspondence table to ensure the accuracy of the association relationship between the area and the charging standard. 5.The intelligent parking fee guidance method with parking space navigation of claim 1, wherein, The navigation path from the current vehicle position of the user to the target parking space is planned based on the parking space candidate set to generate path navigation information, including: Extract the position coordinates of the target parking space in the parking space candidate set, take the position coordinates of the target parking space as the end point coordinates of path planning, and take the current vehicle position information of the user as the start point coordinates of path planning; Call the map construction unit in the path planning module to obtain the channel layout data in the parking lot, and the channel layout data includes channel direction, channel connection relationship and channel passing limit information; Construct the internal path map of the parking lot based on the channel layout data, and mark the start point coordinates and the end point coordinates in the path map; Use a path search algorithm to search for a path from the start point coordinates to the end point coordinates in the path map to generate a plurality of candidate navigation paths, and the candidate navigation paths include the channel number, path length and estimated passing time of the path; Process the passing feasibility of the candidate navigation paths, exclude the candidate navigation paths with passing limit, and retain the feasible candidate navigation paths; Sort the sequence of the feasible candidate navigation paths according to the estimated passing time to select the first feasible candidate navigation path as the optimal navigation path; Analyze the path information of the optimal navigation path to generate path navigation information including turning prompt, distance prompt and channel number prompt. 6.The intelligent parking fee guidance method with parking space navigation of claim 5, wherein, The passing feasibility of the candidate navigation paths is processed, the candidate navigation paths with passing limit are excluded, and the feasible candidate navigation paths are retained, including: Call the passage state monitoring module in the parking lot to obtain real-time passage traffic restriction information, which includes temporary closed passage identifier, passage obstacle position and passage traffic direction restriction; Extract the passage number of the candidate navigation path, compare the passage number with the temporary closed passage identifier in the real-time passage traffic restriction information, and generate a first comparison result; According to the first comparison result, the candidate navigation path is screened, and if the passage number of the candidate navigation path is included in the temporary closed passage identifier, the candidate navigation path is excluded; If the passage number of the candidate navigation path is not included in the temporary closed passage identifier, further extract the obstacle position information in the passage, and perform coordinate comparison between the path coordinates of the candidate navigation path and the obstacle position to generate a coordinate comparison result; According to the coordinate comparison result, the candidate navigation path is screened, and if the path coordinates overlap with the obstacle position, the candidate navigation path is excluded; If the path coordinates do not overlap with the obstacle position, further extract the passage traffic direction restriction, and perform direction comparison between the driving direction of the candidate navigation path and the passage traffic direction restriction to generate a direction comparison result; According to the direction comparison result, the candidate navigation path is screened, and if the driving direction is consistent with the passage traffic direction restriction, the candidate navigation path is retained; if the driving direction is inconsistent with the passage traffic direction restriction, the candidate navigation path is excluded. 7.The intelligent parking fee guidance method with parking space navigation of claim 1, wherein, The fusion path navigation information and the parking fee standard in the parking space candidate set are generated into an integrated parking fee guidance instruction, and the parking fee guidance instruction is sent to the user's vehicle terminal, including: Extract the turning prompt, distance prompt and passage number prompt in the path navigation information, and arrange the turning prompt, distance prompt and passage number prompt into a structured navigation text according to the driving order; Extract the charging standard associated with the target parking space in the parking space candidate set, split the charging standard into charging period, unit cost and estimated total cost, and arrange it into a structured charging text; Fuse the structured navigation text and the structured charging text to match the vehicle driving process in the presentation order of the navigation information and the charging information, and generate fusion text information; Optimize the language of the fusion text information, add guiding sentences, adapt the fusion text information to the user's reading method, and obtain preliminary guidance content; Call the instruction generation module to format package the preliminary guidance content, add instruction identifier, instruction length and verification information, and generate parking fee guidance instruction; Call the wireless communication module to establish communication connection with the user's vehicle terminal, and send the parking fee guidance instruction to the user's vehicle terminal. 8.The intelligent parking fee guidance method with parking space navigation of claim 7, wherein, The call instruction generation module formats the preliminary guidance content, adds instruction identifier, instruction length and verification information, and generates parking fee guidance instruction, including: Call the format definition unit in the instruction generation module to obtain the instruction format specification supported by the user's vehicle terminal, which includes the structure requirements of instruction header, instruction body and instruction tail; According to the instruction format specification, add instruction identifier to the head of the preliminary guidance content, and the instruction identifier is used to identify that the instruction corresponding to the instruction identifier is a parking fee guidance instruction; The character length of the preliminary guide content is calculated, the character length is converted into a numerical value in a preset format, and the numerical value is added as an instruction length after the instruction identifier; The preliminary guide content is subjected to a check calculation, and a check code is generated using a preset check algorithm, the check algorithm including a cyclic redundancy check algorithm; The check code is added to the tail of the preliminary guide content to form a complete instruction structure including an instruction header, an instruction body, and an instruction tail, and the complete instruction structure is the structure of the parking fee guide instruction; The complete instruction structure is subjected to encoding processing to be converted into a binary data format to generate the parking fee guide instruction. 9.The intelligent parking fee guidance method with parking space navigation of claim 2, wherein, The real-time image information is subjected to vehicle existence identification processing to generate an occupancy state identifier of the parking space, and the vehicle existence identification processing includes: The real-time image information is subjected to image preprocessing to eliminate noise interference in the image to obtain denoised image information; The denoised image information is subjected to image segmentation to divide the image into a parking space region and a non-parking space region, the parking space region being an image range corresponding to the parking space; The parking space region is subjected to edge detection to extract boundary contour features of the parking space region, the boundary contour features including four boundary lines of the parking space; Pixel gray scale distribution features in the parking space region are analyzed, and a mean value and a variance of the pixel gray scale are calculated, the mean value and the variance being used to reflect a vehicle parking situation in the parking space region; The mean value and the variance of the pixel gray scale are compared with a preset vehicle existence determination threshold to generate a threshold comparison result; The threshold comparison result is used to generate the occupancy state identifier, if the mean value is less than the threshold and the variance is greater than the threshold, an occupied identifier is generated, and if the mean value is greater than the threshold and the variance is less than the threshold, an unoccupied identifier is generated; The occupancy state identifier of the parking space is associated with a corresponding parking space number to generate a state association table including the parking space number and the occupancy state identifier.

10. A smart parking fee guidance system combined with parking space navigation, characterized in that, The intelligent parking fee guide system combined with parking space navigation includes a processor and a memory, the memory and the processor are connected, the memory is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the memory to realize the intelligent parking fee guide method combined with parking space navigation in any one of claims 1-9.

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