Parking fee estimation method and device, electronic equipment and storage medium

Abstract

The invention discloses a parking fee estimation method and device, electronic equipment and a storage medium, and relates to the computer technology, and the method comprises the steps: obtaining a basic parking rule when the vehicle state of a target vehicle is detected to trigger a parking charging condition, and obtaining a basic charging parameter from the basic parking rule; when it is detected that the vehicle state of the target vehicle is an entrance state, a dynamic charging parameter is obtained; and when it is detected that the vehicle state of the target vehicle is a departure state, the parking duration, the basic charging parameters and the dynamic charging parameters of the target vehicle are input into an estimated charging model, and an estimated parking amount of the target vehicle is obtained. According to the embodiment of the invention, the pre-estimated parking amount displayed to the user by the pre-estimated charging model is more accurate, and the transparency of the parking fee can be improved and the user departure experience can be improved by further displaying the pre-estimated parking amount of the target vehicle to the user because the user has clear the parking amount before departure.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a parking fee estimation method, device, electronic device, and storage medium. Background Art

[0002] In the current mainstream parking fee payment scenario, parking lots generally use a time-based charging system based on license plate recognition. The specific process is as follows: when a vehicle enters the parking lot entrance, a high-definition camera deployed next to the gate automatically captures the license plate number and accurately records the vehicle's entry time into the system database. When the vehicle leaves, a scanning device at the exit recognizes the license plate again. The system calculates the difference between the exit time and the entry time and combines it with preset charging rules (e.g., x yuan / hour, with less than an hour being charged as a full hour) to automatically generate the final parking fee. Although this traditional model achieves automated billing, it suffers from significant user experience shortcomings.

[0003] Since they are not clear about the specific fees corresponding to the parking time, car owners find it difficult to plan their time reasonably before leaving the parking lot. They often need to passively accept parking fees at the exit. When they find that the fees exceed their expectations, they are unable to adjust their itinerary, resulting in a poor user experience. Summary of the Invention

[0004] The present application provides a parking fee estimation method, device, electronic device and storage medium, which can improve the user's parking experience by estimating parking fees for users.

[0005] In a first aspect, the present application provides a parking fee estimation method, comprising:

[0006] When detecting that the vehicle state of the target vehicle triggers a parking billing condition, obtaining basic parking rules and obtaining basic billing parameters from the basic parking rules;

[0007] When detecting that the vehicle state of the target vehicle is an entry state, obtaining dynamic billing parameters;

[0008] When it is detected that the vehicle state of the target vehicle is the departure state, the parking time of the target vehicle, the basic billing parameters and the dynamic billing parameters are input into the estimated charging model to obtain the estimated parking amount of the target vehicle.

[0009] In a second aspect, the present application provides a parking fee estimation device, the device comprising:

[0010] A basic parameter acquisition module is used to acquire basic parking rules when detecting that the vehicle status of the target vehicle triggers the parking billing condition, and to acquire basic billing parameters from the basic parking rules;

[0011] A dynamic parameter acquisition module, configured to acquire dynamic charging parameters when detecting that the vehicle state of the target vehicle is an entry state;

[0012] The parking fee estimation module is used to input the parking time of the target vehicle, the basic billing parameters and the dynamic billing parameters into the estimated billing model when it is detected that the vehicle state of the target vehicle is the departure state, so as to obtain the estimated parking fee of the target vehicle.

[0013] In a third aspect, the present application further provides an electronic device, comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the parking fee estimation method described in any embodiment of the present application.

[0017] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the parking fee estimation method described in any embodiment of the present application when executed.

[0018] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the parking fee estimation method described in any embodiment of the present application.

[0019] The parking fee estimation solution provided in the embodiment of the present application first obtains the basic parking rules and obtains the basic billing parameters from the basic parking rules when it is detected that the vehicle status of the target vehicle triggers the parking billing conditions; then obtains the dynamic billing parameters when it is detected that the vehicle status of the target vehicle is the entry status; finally, when it is detected that the vehicle status of the target vehicle is the departure status, the parking time, basic billing parameters and dynamic billing parameters of the target vehicle are input into the estimated billing model to obtain the estimated parking amount of the target vehicle. This embodiment determines the estimated parking amount by considering the basic billing parameters and dynamic billing parameters, which can make the estimated parking amount displayed to the user by the estimated billing model more accurate. Furthermore, by showing the estimated parking amount of the target vehicle to the user, since the user has clearly determined the parking amount before leaving, the transparency of the parking fee can be improved, and the user's departure experience can be improved.

[0020] It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the parking fee estimation device, or may be packaged separately from the processor of the parking fee estimation device, and this application does not limit this.

[0021] The descriptions of the second, third, fourth and fifth aspects of this application can refer to the detailed description of the first aspect; and the beneficial effects of the descriptions of the second, fourth and fifth aspects can refer to the analysis of the beneficial effects of the first aspect, which will not be repeated here.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description.

[0023] It is understandable that before using the technical solutions disclosed in the embodiments of this application, the type, scope of use, and usage scenarios of the personal information involved in this application should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 This is a flow chart of a parking fee estimation method provided in an embodiment of the present application;

[0026] Figure 2 This is another flowchart of the parking fee estimation method provided in an embodiment of the present application;

[0027] Figure 3 This is another flowchart of the parking fee estimation method provided in an embodiment of the present application;

[0028] Figure 4 This is a schematic diagram of the structure of the parking fee estimation device provided in an embodiment of the present application;

[0029] Figure 5 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the present invention, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this embodiment. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the present application and are not intended to limit the present application. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions of the present application, not all of the structures.

[0033] Figure 1 This is a flow chart of a parking fee estimation method provided in an embodiment of the present application. This embodiment is applicable to estimating parking fees for users from their perspective. The method can be performed by a parking fee estimation device, which can be implemented in hardware and / or software and integrated into an electronic device that performs the method. Preferably, the electronic device in the embodiment of the present application can be a server, a computer, or the like.

[0034] refer to Figure 1 The parking fee estimation method of this embodiment includes but is not limited to the following steps:

[0035] S110. When it is detected that the vehicle status of the target vehicle triggers a parking billing condition, basic parking rules are obtained, and basic billing parameters are obtained from the basic parking rules.

[0036] The target vehicle is the vehicle that currently needs to make an estimate of the parking fee. The purpose of the solution provided by this embodiment is to proactively display the estimated parking fee to the user from the user's perspective, which is specifically determined by a combination of basic billing parameters and dynamic billing parameters. Among them, the basic billing parameters are generally marked on the fee notice board, such as "10 yuan for the first hour, 5 yuan / 30 minutes thereafter", and considering that the fee notice board is generally set up on the roadside or at the entrance of the parking lot, the detection should be triggered before the user enters the parking lot. Since the method of obtaining the basic parking rules in this embodiment is implemented by equipping the on-board visual device with a text recognition algorithm, in order to reduce the amount of system data calculation, the solution provided by this embodiment will only be executed when the parking billing conditions are determined to be triggered based on the vehicle status of the target vehicle, otherwise it will not be executed. The solution provided by this embodiment commissions service value by proactively predicting parking needs.

[0037] In a preferred embodiment, the above-mentioned detection of the target vehicle's vehicle status triggering the parking charge condition can be achieved in the following manner:

[0038] Method 1: Obtain navigation information from the vehicle's computer, or from a mobile terminal connected to the vehicle's computer. The navigation information includes a target destination. Upon detecting that the target vehicle has traveled within a preset range of the target destination, parking fee conditions are triggered. This method of detecting whether parking fee conditions have been triggered pre-determined by combining the navigation system's destination information with the user's parking intention, triggering the fee preparation process in advance as the vehicle approaches the destination. The preset range of the target destination can be understood as 500 meters or 1000 meters from the target destination. The parking fee conditions are triggered by capturing ambient information using the vehicle's onboard visual equipment to derive basic parking rules from the surrounding environment. For example, basic parking rules may be indicated on roadside parking signs or display screens at a shopping mall. Basic fee parameters are obtained by analyzing captured video images. Since roadside parking signs or display screens can capture information even before a vehicle enters the parking lot, this embodiment triggers the implementation of the solution provided by this embodiment upon detecting that the vehicle is approaching the target destination, preventing the omission of critical information.

[0039] Method 2: When the target vehicle's current speed is detected to be lower than a preset speed and a parking sign is identified, parking fee conditions are triggered. If the user is driving a vehicle without a navigation system, the target destination cannot be determined based on the connected navigation system. Therefore, in this method, when the user reaches the target destination and needs to stop, the vehicle's speed is first reduced. However, to avoid misjudgments due to vehicle deceleration, traffic lights, and other factors, the vehicle's speed is first reduced. Upon detecting the reduced speed, the visual device captures surrounding information and, upon identifying a parking sign, parking fee conditions are triggered. The preset speed can be 10 km / h or 15 km / h, and the specific preset speed is not restricted. The parking sign can be a conventionally colored P sign located on the roadside or near a parking lot, typically blue. In this case, parking fee conditions are determined to be triggered, and the basic parking rules contained in the parking sign are further analyzed to obtain basic fee parameters.

[0040] The specific method for determining the conditions for triggering parking billing is selected based on the actual vehicle status when the user is driving the vehicle, and is not restricted here.

[0041] Furthermore, the basic billing parameters can be obtained from the basic parking rules by analyzing the basic parking rules from the image information captured by the visual device through an optical character recognition (OCR) algorithm to obtain the basic billing parameters, and the basic billing parameters can be output in a structured manner, such as in the form of fields such as {unit time amount, free time, tiered rate, capped amount}.

[0042] Preferably, the basic billing parameters in this embodiment include multiple basic sub-parameters, and the basic sub-parameters include at least one of the unit time amount, free time, tiered rate and capped amount.

[0043] Among them, the unit time amount refers to the basic fee charged by the parking lot according to a fixed time unit (such as 1 hour). For example, a parking lot sets a "unit time amount of 5 yuan / hour", which means that 5 yuan is charged for each parking hour, and less than 1 hour is calculated as 1 hour; the free time refers to the initial time after the vehicle enters the parking lot without paying, which is used to buffer temporary parking needs (such as picking up passengers, short shopping). For example, a common "free time of 30 minutes" is seen in shopping mall parking lots, which means that vehicles can leave the parking lot within 30 minutes after entering without paying; the tiered rate refers to setting different billing standards according to the parking time, such as 1 hour: 10 yuan; 2-4 hours: 8 yuan / hour; more than 4 hours: 15 yuan / hour, etc.; the capped amount refers to the maximum charge for a single day or single parking, which is used to avoid users incurring high fees due to extra-long parking (such as overnight or delay due to a breakdown). For example, if a "capped amount of 80 yuan / day" is set, the daily fee will not exceed 80 yuan regardless of how long the parking is.

[0044] S120: When it is detected that the vehicle state of the target vehicle is the entry state, obtain dynamic billing parameters.

[0045] The entry status indicates the vehicle's state when entering the parking lot. Specifically, the vehicle's entry status is determined to be when the target vehicle decelerates and the visual recognition device captures the entrance sign, or when the target vehicle is detected by a parking lot scanner and the entry bar is raised.

[0046] Dynamic billing parameters represent parameters that may affect the dynamic fluctuation of parking fees due to factors such as entry time or user identification. In this embodiment, the dynamic billing parameters include multiple dynamic sub-parameters. Specifically, the dynamic sub-parameters include at least one of a holiday factor, a time interval factor, and a user identification factor.

[0047] Among them, holiday factors refer to parameters that dynamically adjust parking billing rules based on the attributes of special dates such as statutory holidays and public holidays. For example, during long holidays such as the Spring Festival and National Day, parking lots may increase rates or adjust free hours to cope with traffic peaks; time interval factors refer to parameters that set differentiated billing rules based on traffic differences at different times of the day (such as morning peak, midday flat peak, and night time) or on different days of the week (such as weekdays and weekends). For example, commercial parking lots implement peak rates from 8:00 to 18:00 on weekdays and low rates at other times; user identity factors refer to parameters that provide differentiated billing strategies based on personalized attributes such as the owner's membership level, vehicle type (such as new energy vehicles, VIP vehicles), and user points. For example, member users enjoy parking discounts, and new energy vehicle owners enjoy the first hour free offer.

[0048] Furthermore, the obtained dynamic billing parameters may also be output in a structured manner, such as in the form of fields such as {holiday factor, time interval factor, user identity factor}.

[0049] It should be noted that the method for obtaining basic billing parameters and dynamic billing parameters in this application, based on the capture method based on the visual equipment installed in the vehicle, can also be further obtained through the call method of pre-stored database, or obtained based on the analysis method of historical parking records. The reason for this setting is that the multiple basic sub-parameters contained in the basic billing parameters and the multiple dynamic sub-parameters contained in the dynamic billing parameters cannot necessarily be obtained every time by capturing the surrounding environment information based on the visual equipment. Therefore, it is necessary to further call based on the parameters pre-stored in the database, or analyze the historical parking records to clarify each basic sub-parameter and each dynamic sub-parameter.

[0050] In a possible scenario, a conflict may arise between parameter values ​​captured by a visual device and those pre-stored in a database or recorded in historical parking records. In this case, the parameter values ​​obtained through analysis using the current visual device capture take precedence. Because parking lot rules are subject to dynamic change, this embodiment prioritizes the current visual device capture method over the database-based call method, which in turn prioritizes the database-based call method over the analysis method based on historical parking records. Consequently, the corresponding parameter values ​​pre-stored in the database are updated based on the currently recognized parameter values.

[0051] S130. When it is detected that the vehicle state of the target vehicle is the departure state, the parking time, basic billing parameters and dynamic billing parameters of the target vehicle are input into the estimated charging model to obtain the estimated parking amount of the target vehicle.

[0052] The departure state refers to the state when the vehicle speed increases from 0 and the movement trajectory is towards the parking lot exit. At this time, the fare estimation operation needs to be triggered.

[0053] Specifically, the fee estimation method provided in this embodiment is achieved by inputting the parking time, basic billing parameters and dynamic billing parameters of the target vehicle into the estimated charging model, thereby outputting the estimated parking amount of the target vehicle to the user based on the estimated charging model.

[0054] The parking duration is defined as the time when the vehicle's speed drops to zero and it is positioned inside the parking lot. The specific parking duration is calculated by taking the difference between the vehicle's entry timestamp (the time when the target vehicle is scanned by the parking lot's scanner) and the vehicle's exit timestamp (the time when the vehicle moves), and is accurate to the minute.

[0055] The estimated charging model can determine the estimated parking amount through the following logic. First, the tiered rule is matched according to the parking time. For example, 180 minutes is 3 hours, where the tiered rule is 1st hour: 5 yuan; 2nd hour: 3 yuan; 3rd hour: 10 yuan (calculated at 10 yuan per hour after 2 hours); if there is no free time discount, the basic amount corresponding to the basic billing parameters can be determined to be 5+3+10=18 yuan; further superimposed with dynamic parameters, such as the current time is not a holiday and there is no holiday factor impact; the current parking time is night, and there is a 10% discount for night parking (21:00-7:00); further, the current user is a mall member and there is a 10% discount; the estimated parking amount is comprehensively determined to be 18*0.9*0.9=14.58 yuan; further determine whether the total fee exceeds the capped amount (such as the daily cap of 80 yuan): in this example, 14.58 yuan is less than 80 yuan, no adjustment is required, and the final estimated amount is 14.58 yuan.

[0056] A preferred implementation method, in the implementation method of this embodiment, the current parking time of the target vehicle can be obtained at every preset time interval; the current parking time, basic billing parameters and dynamic billing parameters are input into the estimated billing model to obtain the current estimated parking amount of the target vehicle, and a push message containing the current estimated parking amount is sent to the user's mobile terminal.

[0057] In the current embodiment, the current parking duration of the target vehicle is obtained at preset intervals, and a push message with the current estimated parking fee is sent to the user's mobile terminal. This allows the user to clearly understand the current parking fee and decide whether to adjust their plans to complete their parking tasks in the next time period. The preset duration can be 30 minutes or 1 hour. The system sends a push message containing the current estimated parking fee to the user's linked mobile terminal via SMS, parking app notifications, or other means. The message content typically displays information such as the estimated fee, parking duration, and billing basis, allowing users to stay informed of parking fee trends.

[0058] In one application scenario, if a user is shopping in a mall and has budgeted 15 yuan for parking, they may consider leaving when they find out the current parking fee has reached 14.58 yuan. This avoids the user finding out upon leaving that the parking fee has been increased by ten yuan due to a few minutes of overtime, which would cause losses to the user and reduce the user experience. This method allows users to receive regular estimated fee reminders during the parking process, keep abreast of parking costs, and avoid unexpected fees due to long parking periods or unfamiliarity with billing rules. This enhances their sense of control over parking consumption and facilitates users to rationally arrange subsequent trips. For example, when shopping in a mall, users receive a parking fee estimate push notification and can adjust their shopping time accordingly to avoid incurring additional high fees due to overtime.

[0059] In another preferred embodiment, the solution provided in this embodiment is implemented based on a pre-estimated charging model. Since the pre-estimated charging model comprehensively considers at least one basic sub-parameter of the amount per unit time, free time, tiered rates, and capped amount, as well as a dynamic sub-parameter of at least one of holiday factors, time interval factors, and user identity factors, due to the different ways in which each basic sub-parameter and dynamic sub-parameter are obtained, this embodiment assigns a sub-weight to each basic sub-parameter and each dynamic sub-parameter before performing model calculation based on the pre-estimated charging model. For each basic sub-parameter or each dynamic sub-parameter, the sub-weight based on the acquisition method of the current visual device is higher than the sub-weight based on pre-stored database storage, and higher than the sub-weight based on historical parking records.

[0060] Specifically, the above step S130 can be achieved through the following steps:

[0061] a) Determine, according to the acquisition methods corresponding to each basic sub-parameter and each dynamic sub-parameter, a first sub-weight corresponding to each basic sub-parameter and a second sub-weight corresponding to each dynamic sub-parameter.

[0062] The system pre-assigns sub-weights corresponding to different sources for each basic sub-parameter (unit time amount, free time, tiered rate, and capped amount) and dynamic sub-parameter (holiday factors, time interval factors, user identity factors, etc.). For example, the weight for visual device capture is set to 1.0; the weight for database pre-storage is set to 0.8; and the weight for historical parking records is set to 0.6. These weights can be flexibly adjusted based on actual operational needs and data reliability.

[0063] When obtaining basic sub-parameters, determine the acquisition method. If the unit time amount is captured by the current visual device (such as the information on the public sign read by the entrance camera), it is assigned a first sub-weight of 1.0; if it is retrieved from pre-stored rules in the database, the first sub-weight is 0.8; if it is inferred based on historical parking records, the first sub-weight is 0.6. The same applies to other basic sub-parameters.

[0064] When obtaining dynamic sub-parameters, taking the time interval factor as an example, if the current peak hour is captured by visual equipment (such as a camera identifying the time period signs displayed in the parking lot in real time), its second sub-weight is 1.0; if the information is obtained from the time period classification rules pre-stored in the database, the second sub-weight is 0.8; if the attributes of the same time period are inferred based on historical parking records, the second sub-weight is 0.6. The weights of other dynamic sub-parameters are determined according to the same logic.

[0065] b) Inputting the parking duration, each basic sub-parameter and its corresponding first sub-weight, and each dynamic sub-parameter and its corresponding second sub-weight into a parking fee model to obtain an estimated parking fee for the target vehicle.

[0066] The target vehicle's parking duration, each determined basic sub-parameter and its first sub-weight, and each dynamic sub-parameter and its second sub-weight are input into the parking fee model. The model calculates the estimated parking fee according to the following logic: First, the basic fee is calculated by combining the basic sub-parameter and its first sub-weight. For example, if the unit time amount is 5 yuan (first sub-weight 0.8), and parking is for 2 hours, the basic fee is initially calculated as 5×2=10 yuan, which is then multiplied by the weight of 0.8 to obtain the adjusted basic fee of 8 yuan. Then, the dynamic adjustment fee is calculated based on the dynamic sub-parameter and its second sub-weight. If the holiday factor causes the rate to increase by 20% (second sub-weight 0.9), the dynamic adjustment fee is the basic fee of 8 yuan × 20% × 0.9 = 1.44 yuan. Finally, the adjusted basic fee is added to the dynamic adjustment fee to obtain the estimated parking fee, that is, 8 + 1.44 = 9.44 yuan.

[0067] Optionally, since the final output of this solution is the estimated amount of parking fees, the estimated parking amount can be output in the form of an amount range for user reference. The upper and lower ranges of the current amount range can be the final calculated parking entry upper and lower floating preset amounts. For example, the estimated parking amount is 9.44, and the final amount output to the user is (8.44, 9.44); optionally, the upper and lower range influencing factors of the estimated parking amount can also be the amount range obtained when the first sub-weight and the second sub-weight take the maximum and minimum values ​​respectively. The specific output form of the estimated parking amount is not limited here.

[0068] Another preferred embodiment, please refer to Figure 2 , Figure 2 This is another flow chart of the parking fee estimation method provided by an embodiment of the present application. Since the final output of this embodiment is the estimated parking fee, there is a possibility that it may not match the actual fee. Therefore, in order to further improve the accuracy of the model estimation, the solution provided by this embodiment can also perform the following steps:

[0069] S210: Obtain the actual parking fee of the target vehicle.

[0070] The actual parking amount is the actual amount paid by the user by scanning the payment device when exiting the parking lot.

[0071] S220. When the actual parking amount does not match the estimated parking amount, the actual parking amount, the estimated parking amount, each basic sub-parameter and the corresponding first sub-weight, and each dynamic sub-parameter and the corresponding second sub-weight are stored in sequence to obtain a newly added sample sequence.

[0072] If the difference between the actual parking amount and the estimated parking amount exceeds a threshold, such as a preset error of ±5%, it is determined to be the actual parking amount and the estimated parking amount, and the sequence storage process is triggered to obtain a new sample sequence.

[0073] Specifically, the newly added sample sequence can encapsulate the above data into a sample sequence based on time sequence, for example: [vehicle ID, parking time, basic parameter group + weight, dynamic parameter group + weight, estimated amount, actual amount], etc.

[0074] S230: Adjust the weight parameters in the parking billing model according to the newly added sample sequence, and update the parking billing model according to the adjusted weight parameters to obtain an updated parking billing model.

[0075] Attribute the estimation errors in the newly added sample series and calculate the contribution of each parameter weight to the total error. For example, if the "Amount per Unit Duration" in a sample is underestimated due to using database storage (weight 0.8), and the actual parameter has been updated to a higher value through visual equipment, the weight of this parameter may need to be increased.

[0076] For a specific implementation, please refer to Figure 3 , Figure 3 This is another flow chart of the parking fee estimation method provided in the embodiment of the present application. The above step S230 can be specifically implemented by the following steps:

[0077] S231. Determine a loss function based on the difference between the actual parking fee and the estimated parking fee.

[0078] Specifically, the difference between the actual parking amount and the estimated parking amount can be expressed by means of a root mean square error or a mean absolute error to obtain a loss function.

[0079] S232. Determine the weight gradient values ​​corresponding to each first sub-weight and each second sub-weight according to the loss function.

[0080] In the current step, a back propagation algorithm may be used to calculate partial derivatives of the loss function and each first sub-weight and each second sub-weight, respectively, to obtain the degree of influence of each sub-weight on the estimated amount.

[0081] S233. For each basic sub-parameter, determine a first update sub-weight according to the corresponding first sub-weight and the corresponding weight gradient value; for each dynamic sub-parameter, determine a second update sub-weight according to the corresponding second sub-weight and the corresponding weight gradient value.

[0082] Specifically, the method for determining the first update sub-weight can be reflected by the following formula:

[0083]

[0084] in, represents the first updated sub-weight, is the first sub-weight used in the last estimated amount calculation, represents the learning rate, Indicates the weight gradient value corresponding to the first sub-weight.

[0085] For example, if the current weight of a basic parameter (such as "amount per unit time") (corresponding to the visual capture source), the gradient calculation result is Learning rate but, This indicates that the reliability of the parameter source needs to be slightly reduced, possibly due to the recent increase in capture errors of visual equipment.

[0086] The method for determining the second update sub-weight can be reflected by the following formula:

[0087]

[0088] in, represents the second updated sub-weight, The second sub-weight used in the last estimated amount calculation, represents the learning rate, Indicates the weight gradient value corresponding to the second sub-weight.

[0089] For example, if the current weight of a dynamic parameter ("holiday parameter") (corresponding to database storage), if the gradient is (negative gradient means increasing weights reduces loss), learning rate but, This indicates that the credibility of the parameter source has increased, possibly because the database has been updated more frequently recently, resulting in more accurate data.

[0090] S234. Train the parking billing model according to the first update sub-weight corresponding to each basic sub-parameter and the second update sub-weight corresponding to each dynamic sub-parameter, and obtain an updated parking billing model when the value corresponding to the loss function reaches convergence.

[0091] By providing feedback and updating the parking pricing model with new training samples, the model can automatically learn the implicit patterns of parking pricing rules, becoming more fault-tolerant and providing more stable predictions. Furthermore, differentiated weights are assigned to different data sources for basic and dynamic sub-parameters, and dynamic adjustments are made through training to improve data utilization efficiency.

[0092] The parking fee estimation method provided in this embodiment first obtains the basic parking rules and obtains the basic billing parameters from the basic parking rules when it is detected that the vehicle status of the target vehicle triggers the parking billing conditions; then obtains the dynamic billing parameters when it is detected that the vehicle status of the target vehicle is the entry status; finally, when it is detected that the vehicle status of the target vehicle is the departure status, the parking time, basic billing parameters and dynamic billing parameters of the target vehicle are input into the estimated billing model to obtain the estimated parking amount of the target vehicle. This embodiment determines the estimated parking amount by considering the basic billing parameters and dynamic billing parameters, which can make the estimated parking amount displayed to the user by the estimated billing model more accurate. Furthermore, by displaying the estimated parking amount of the target vehicle to the user, since the user has already determined the parking amount before leaving, the transparency of the parking fee can be improved, and the user's departure experience can be enhanced.

[0093] Figure 4 This is a schematic diagram of the structure of the parking fee estimation device provided in the embodiment of the present application, which is suitable for executing the parking fee estimation method provided in the embodiment of the present application. Figure 4As shown, the device may specifically include: a basic parameter acquisition module 410, a dynamic parameter acquisition module 420 and a parking fee estimation module 430, wherein:

[0094] A basic parameter acquisition module 410 is configured to acquire basic parking rules and basic charging parameters from the basic parking rules when detecting that the vehicle status of the target vehicle triggers a parking charging condition;

[0095] The dynamic parameter acquisition module 420 is used to acquire dynamic charging parameters when detecting that the vehicle state of the target vehicle is the entry state;

[0096] The parking fee estimation module 430 is used to input the parking time of the target vehicle, the basic billing parameters and the dynamic billing parameters into the estimated billing model when it is detected that the vehicle state of the target vehicle is the departure state, so as to obtain the estimated parking fee of the target vehicle.

[0097] The parking fee estimation device provided in this embodiment first obtains the basic parking rules and the basic billing parameters from the basic parking rules when it detects that the vehicle status of the target vehicle triggers the parking billing conditions; then obtains the dynamic billing parameters when it detects that the vehicle status of the target vehicle is the entry status; finally, when it detects that the vehicle status of the target vehicle is the departure status, the parking time, basic billing parameters and dynamic billing parameters of the target vehicle are input into the estimated billing model to obtain the estimated parking amount of the target vehicle. This embodiment determines the estimated parking amount by considering the basic billing parameters and dynamic billing parameters, which can make the estimated parking amount displayed to the user by the estimated billing model more accurate. Furthermore, by showing the estimated parking amount of the target vehicle to the user, since the user has already determined the parking amount before leaving, the transparency of the parking fee can be improved, and the user's departure experience can be improved.

[0098] In one embodiment, the basic charging parameters and the dynamic charging parameters are obtained in the following manner:

[0099] The data can be obtained by capturing data using a current visual device, calling data pre-stored in a database, or analyzing historical parking records;

[0100] The capture method based on the current visual device has a higher priority than the call method based on pre-stored data in the database, and the call method based on pre-stored data in the database has a higher priority than the analysis method based on historical parking records.

[0101] The basic billing parameters include basic sub-parameters, and the basic sub-parameters include at least one of a unit time amount, a free time, a tiered rate, and a capped amount;

[0102] The dynamic charging parameters include dynamic sub-parameters, and the dynamic sub-parameters include at least one of a holiday factor, a time interval factor, and a user identity factor.

[0103] In one embodiment, each of the basic sub-parameters and each of the dynamic sub-parameters corresponds to a sub-weight; for each of the basic sub-parameters or each of the dynamic sub-parameters corresponding to the acquisition method, the sub-weight based on the current visual device capture method is higher than the sub-weight based on the database pre-stored method, and higher than the sub-weight based on historical parking records;

[0104] The parking fee estimation module 430 is specifically used to determine the first sub-weight corresponding to each basic sub-parameter and the second sub-weight corresponding to each dynamic sub-parameter according to the acquisition method corresponding to each basic sub-parameter and each dynamic sub-parameter; input the parking time, each basic sub-parameter and the corresponding first sub-weight, and each dynamic sub-parameter and the corresponding second sub-weight into the parking billing model to obtain the estimated parking fee for the target vehicle.

[0105] In one embodiment, the device further includes an actual amount acquisition module, a sample sequence storage module, and a billing model update module, wherein:

[0106] An actual amount acquisition module is used to acquire the actual parking amount of the target vehicle;

[0107] a sample sequence storage module, configured to sequentially store the actual parking amount, the estimated parking amount, each of the basic sub-parameters and the corresponding first sub-weight, and each of the dynamic sub-parameters and the corresponding second sub-weight to obtain a newly added sample sequence when the actual parking amount and the estimated parking amount do not match;

[0108] The billing model updating module is used to adjust the weight parameters in the parking billing model according to the newly added sample sequence, and update the parking billing model according to the adjusted weight parameters to obtain an updated parking billing model.

[0109] In one embodiment, the billing model update module is specifically used to determine a loss function based on the difference between the actual parking amount and the estimated parking amount; determine the weight gradient value corresponding to each of the first sub-weights and each of the second sub-weights according to the loss function; for each of the basic sub-parameters, determine the first updated sub-weight according to the corresponding first sub-weight and the corresponding weight gradient value; for each of the dynamic sub-parameters, determine the second updated sub-weight according to the corresponding second sub-weight and the corresponding weight gradient value; train the parking billing model according to the first updated sub-weight corresponding to each of the basic sub-parameters and the second updated sub-weight corresponding to each of the dynamic sub-parameters, and obtain the updated parking billing model when the numerical value corresponding to the loss function reaches convergence.

[0110] In one embodiment, the basic parameter acquisition module 410 is also used to obtain navigation information from the vehicle-side terminal, or obtain navigation information from a mobile terminal that is communicatively connected to the vehicle-side terminal, wherein the navigation information includes a target destination; when it is detected that the target vehicle is traveling within a preset range of the target destination, it is determined that the parking billing condition is triggered; or, when it is detected that the current driving speed of the target vehicle is lower than a preset speed and a parking sign is identified, it is determined that the parking billing condition is triggered.

[0111] In one embodiment, the device further includes a current duration acquisition module and a current amount estimation module, wherein:

[0112] A current parking time acquisition module is used to acquire the current parking time of the target vehicle at intervals of a preset time;

[0113] The current amount estimation module is used to input the current parking time, the basic billing parameters and the dynamic billing parameters into the estimated billing model, obtain the current estimated parking amount of the target vehicle, and send a push message containing the current estimated parking amount to the user's mobile terminal.

[0114] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0115] An embodiment of the present application also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the parking fee estimation method described in any embodiment of the present application.

[0116] An embodiment of the present application further provides a computer-readable medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the parking fee estimation method described in any embodiment of the present application when executed.

[0117] Reference below Figure 5 , Figure 5 FIG1 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, which shows a schematic diagram of the structure of a computer system 500 suitable for implementing the electronic device in an embodiment of the present application. Figure 5 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0118] like Figure 5 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage unit 508 into a random access memory (RAM) 503. Various programs and data required for the operation of the system 500 are also stored in the RAM 503. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0119] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, and the like; an output section 507 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 508 including a hard disk; and a communication section 509 including a network interface card such as a LAN card or a modem. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 510 as needed, so that computer programs read therefrom can be installed into the storage section 508 as needed.

[0120] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 509, and / or installed from a removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, the above-mentioned functions defined in the system of the present application are executed.

[0121] It should be noted that the computer-readable medium shown in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, and optical cables, or any suitable combination thereof.

[0122] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of the boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0123] The modules and / or units described in the embodiments of this application may be implemented in software or hardware. The modules and / or units described may also be provided within a processor. For example, a processor may be described as including a basic parameter acquisition module, a dynamic parameter acquisition module, and a parking fee estimation module. The names of these modules do not, in some cases, limit the modules themselves.

[0124] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by a device, the device includes: when it is detected that the vehicle status of the target vehicle triggers the parking billing condition, obtaining basic parking rules and obtaining basic billing parameters from the basic parking rules; when it is detected that the vehicle status of the target vehicle is an entry state, obtaining dynamic billing parameters; when it is detected that the vehicle status of the target vehicle is a departure state, inputting the parking time of the target vehicle, the basic billing parameters, and the dynamic billing parameters into an estimated billing model to obtain an estimated parking amount for the target vehicle.

[0125] According to the technical solution of this embodiment, by considering both basic and dynamic billing parameters to determine the estimated parking fee, the estimated parking fee presented to the user by the estimated billing model is more accurate. Furthermore, by displaying the estimated parking fee for the target vehicle to the user, the user clearly knows the parking fee before leaving the parking lot, thereby improving the transparency of parking fees and enhancing the user's departure experience.

[0126] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A parking fee estimation method, characterized in that: include: When detecting that the vehicle state of the target vehicle triggers a parking billing condition, obtaining basic parking rules and obtaining basic billing parameters from the basic parking rules; When detecting that the vehicle state of the target vehicle is an entry state, obtaining dynamic billing parameters; When it is detected that the vehicle state of the target vehicle is the departure state, the parking time of the target vehicle, the basic billing parameters and the dynamic billing parameters are input into the estimated charging model to obtain the estimated parking amount of the target vehicle.

2. The parking fee estimation method according to claim 1, characterized in that: The basic charging parameters and the dynamic charging parameters are obtained in the following manner: The data can be obtained by capturing data using a current visual device, calling data pre-stored in a database, or analyzing historical parking records; The capture method based on the current visual device has a higher priority than the call method based on pre-stored data in the database, and the call method based on pre-stored data in the database has a higher priority than the analysis method based on historical parking records. The basic billing parameters include basic sub-parameters, and the basic sub-parameters include at least one of a unit time amount, a free time, a tiered rate, and a capped amount; The dynamic charging parameters include dynamic sub-parameters, and the dynamic sub-parameters include at least one of a holiday factor, a time interval factor, and a user identity factor.

3. The parking fee estimation method according to claim 2, characterized in that: Each of the basic sub-parameters and each of the dynamic sub-parameters corresponds to a sub-weight; for each of the basic sub-parameters or each of the dynamic sub-parameters, the sub-weight based on the capture method of the current visual device is higher than the sub-weight based on the pre-stored database, and higher than the sub-weight based on historical parking records; The step of inputting the parking duration of the target vehicle, the basic charging parameters, and the dynamic charging parameters into an estimated charging model to obtain an estimated parking fee for the target vehicle includes: Determine, according to the acquisition methods corresponding to each of the basic sub-parameters and each of the dynamic sub-parameters, a first sub-weight corresponding to each of the basic sub-parameters and a second sub-weight corresponding to each of the dynamic sub-parameters; The parking duration, each of the basic sub-parameters and the corresponding first sub-weight, and each of the dynamic sub-parameters and the corresponding second sub-weight are input into the parking fee model to obtain the estimated parking fee for the target vehicle.

4. The parking fee estimation method according to claim 3, characterized in that: The method further comprises: Obtaining the actual parking fee of the target vehicle; When the actual parking amount does not match the estimated parking amount, the actual parking amount, the estimated parking amount, each of the basic sub-parameters and the corresponding first sub-weight, and each of the dynamic sub-parameters and the corresponding second sub-weight are sequentially stored to obtain a newly added sample sequence; The weight parameters in the parking fee charging model are adjusted according to the newly added sample sequence, and the parking fee charging model is updated according to the adjusted weight parameters to obtain an updated parking fee charging model.

5. The parking fee estimation method according to claim 4, characterized in that: The step of adjusting the weight parameters in the parking fee charging model according to the newly added sample sequence, and updating the parking fee charging model according to the adjusted weight parameters to obtain an updated parking fee charging model includes: determining a loss function according to the difference between the actual parking amount and the estimated parking amount; Determine, according to the loss function, a weight gradient value corresponding to each of the first sub-weights and each of the second sub-weights; For each of the basic sub-parameters, a first update sub-weight is determined according to the corresponding first sub-weight and the corresponding weight gradient value; for each of the dynamic sub-parameters, a second update sub-weight is determined according to the corresponding second sub-weight and the corresponding weight gradient value; The parking fee charging model is trained according to the first update sub-weight corresponding to each of the basic sub-parameters and the second update sub-weight corresponding to each of the dynamic sub-parameters, and the updated parking fee charging model is obtained when the value corresponding to the loss function reaches convergence.

6. The parking fee estimation method according to claim 1, characterized in that: The detection of the vehicle state of the target vehicle triggering the parking fee charging condition includes: Obtaining navigation information from the vehicle terminal, or obtaining navigation information from a mobile terminal in communication with the vehicle terminal, the navigation information including a target destination; and determining that the parking charge condition is triggered when detecting that the target vehicle has traveled within a preset range of the target destination; Alternatively, when it is detected that the current driving speed of the target vehicle is lower than a preset speed and a parking sign is identified, it is determined that the parking billing condition is triggered.

7. The parking fee estimation method according to claim 1, characterized in that: After obtaining the dynamic charging parameters, the method further includes: Obtaining the current parking time of the target vehicle at each preset time interval; The current parking time, the basic billing parameters and the dynamic billing parameters are input into the estimated billing model to obtain the current estimated parking amount of the target vehicle, and a push message containing the current estimated parking amount is sent to the user's mobile terminal.

8. A parking fee estimation device, characterized in that: include: A basic parameter acquisition module is used to acquire basic parking rules when detecting that the vehicle status of the target vehicle triggers the parking billing condition, and to acquire basic billing parameters from the basic parking rules; A dynamic parameter acquisition module, configured to acquire dynamic charging parameters when detecting that the vehicle state of the target vehicle is an entry state; The parking fee estimation module is used to input the parking time of the target vehicle, the basic billing parameters and the dynamic billing parameters into the estimated billing model when it is detected that the vehicle state of the target vehicle is the departure state, so as to obtain the estimated parking fee of the target vehicle.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the parking fee estimation method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the parking fee estimation method according to any one of claims 1 to 7 is implemented.

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