Intelligent parking management method and system

Abstract

The invention relates to the technical field of intelligent parking, in particular to an intelligent parking management method and system.The intelligent parking management method comprises the steps that vehicle information, the common parking space vacancy amount and the charging parking space vacancy amount are obtained in real time through an information obtaining module; if it is recognized that the vehicle enters the peak period, the historical average idle number of charging parking spaces, the historical parking gap rate of long-term vehicles and the historical average parking duration of temporary vehicles in the same peak period are analyzed based on historical data; carrying out fusion analysis on the basis of the historical average idle number of the charging parking spaces, the long-term historical parking gap rate of the vehicles and the temporary historical average parking duration of the vehicles, and dynamically calculating the number of removable charging parking spaces which can be temporarily used as common parking spaces; and the charging parking space is moved according to the calculation result, and the parking guarantee problem of the long-term vehicle in the parking peak period is improved in a mode of temporarily occupying the charging parking space.

Description

Technical Field

[0001] The present application relates to the technical field of smart parking, and in particular to a smart parking management method and system. Background Art

[0002] With the rapid advancement of global urbanization, cities are expanding and populations are continuously concentrating in them. At the same time, the number of cars, the primary means of transportation, is increasing at an alarming rate. These two combined trends have led to an increasingly prominent urban parking problem, not only causing significant inconvenience for citizens' daily commutes but also posing a severe challenge to the rational utilization and efficient management of urban transportation resources. Against this backdrop, smart parking management systems have emerged as a core technology to alleviate urban parking challenges and improve the efficiency of transportation resource utilization.

[0003] Existing smart parking management systems have, to a certain extent, played a positive role in parking management. Most systems provide basic vehicle registration, quickly and accurately recording vehicle entry information through technologies such as license plate recognition and electronic tag reading. Parking guidance uses sensors and signs to help drivers easily find available spaces. Billing automatically calculates parking fees and completes payment based on factors such as parking duration and vehicle type. However, with the increasing complexity of urban traffic environments and rising demands for parking service quality, these basic functions are no longer sufficient to meet actual needs.

[0004] Non-binding parking spaces are common in many parking lots. For these types of parking lots, securing parking for long-term vehicles rented on a monthly or annual basis during peak hours is particularly challenging. In unmanned parking lots where long-term vehicles are not tied to fixed spaces, a variety of factors can lead to a lack of available spaces during peak hours.

[0005] First, there's a lack of effective forecasting and resource allocation strategies. Parking lot managers, lacking comprehensive data analysis tools and accurate forecasting models, are unable to accurately predict vehicle flow and demand distribution at different times of the day. Vehicle travel patterns vary significantly across different days (weekdays, weekends, holidays, etc.) and time of day (peak and off-peak periods, etc.). Without accurate knowledge of these patterns, parking lots struggle to reserve sufficient spaces for long-term users during peak periods, leading to irrational resource allocation. Long-term users may find themselves desperately in need of parking only to find the parking lot completely filled with temporarily parked vehicles, leaving them with nowhere to park.

[0006] Secondly, the squeeze on regular parking spaces by charging spaces is another significant factor that cannot be ignored. With the booming new energy vehicle industry and their increasing market share, the number of charging spaces in parking lots has also increased. However, the management and use of these spaces presents a dilemma. On the one hand, to ensure the charging needs of new energy vehicles, non-charging vehicles are often prohibited from parking in charging spaces. However, during peak parking periods, this regulation makes already scarce parking spaces even more scarce, further compressing the space for long-term vehicles. On the other hand, if non-charging vehicles are not restricted from parking in charging spaces, charging spaces will be occupied by non-charging vehicles for a long time, preventing new energy vehicles that truly need charging from charging in a timely manner, affecting their normal use and defeating the original purpose of providing charging spaces.

[0007] Furthermore, there is a lack of effective control over vehicle size. Different types of vehicles, such as small sedans, mid-size SUVs, large buses, and trucks, vary significantly in size. Large vehicles, especially some large SUVs and trucks, may occupy multiple parking spaces, reducing the number of available parking spaces. In unmanned parking lots, the lack of strict size restrictions and proper guidance allows some large vehicles to be parked haphazardly, further exacerbating parking shortages during peak hours. Summary of the Invention

[0008] In order to improve the parking guarantee problem of long-term vehicles during peak parking periods, this application provides a smart parking management method and system.

[0009] In the first aspect, the present application provides a smart parking management method and system, which adopts the following technical solutions:

[0010] A smart parking management method and system comprises the following steps:

[0011] Real-time acquisition of vehicle information, the number of available regular parking spaces, and the number of available charging parking spaces. The vehicle information includes vehicle type, charging type, and vehicle size. The vehicle type includes electric vehicles and non-electric vehicles, and the charging type includes temporary vehicles, long-term vehicles, and special vehicles.

[0012] If a peak period is identified, the average number of available charging parking spaces, the historical parking gap rate for long-term vehicles, and the average parking duration for temporary vehicles during the same peak period are analyzed based on historical data.

[0013] Based on the historical average number of vacant charging parking spaces, the historical parking gap rate for long-term vehicles, and the historical average parking duration of temporary vehicles, a fusion analysis is conducted to dynamically calculate the number of charging parking spaces that can be temporarily used as ordinary parking spaces.

[0014] Obtain the number of long-term vehicles entering the market during peak hours in real time, and calculate the difference in long-term vehicle entry based on the predicted number of long-term vehicle entry during peak hours;

[0015] If the difference in the number of long-term parking spaces is greater than the number of currently available ordinary parking spaces, the charging parking spaces will be used as temporary ordinary parking spaces. When the number of used charging parking spaces is greater than or equal to the number of available charging parking spaces, or the number of available charging parking spaces is less than the preset value, the use of charging parking spaces will be stopped.

[0016] If the difference in the number of long-term vehicles entering the parking lot is greater than the number of currently available ordinary parking spaces and the use of charging parking spaces is stopped, or the vehicle size is larger than the preset value, temporary vehicles are prohibited from entering.

[0017] In one embodiment, the method for obtaining the historical average number of vacant charging parking spaces includes:

[0018] Based on historical data, calculate the historical average occupancy rate of charging parking spaces;

[0019] Based on the historical average occupancy rate of charging parking spaces and the total number of charging parking spaces, the historical average number of available charging parking spaces is calculated.

[0020] In one embodiment, the step of calculating the historical average occupancy rate of charging parking spaces based on historical data specifically includes:

[0021] Based on historical data, obtain the actual charging time of all charging parking spaces corresponding to the same peak period;

[0022] Calculate the average charging time based on the actual charging time of the charging parking space;

[0023] Calculate the theoretical charging time during peak hours based on the duration of the peak hours and the total number of charging spaces;

[0024] The historical average occupancy rate of charging parking spaces is calculated based on the average charging time and the theoretical charging time.

[0025] In one embodiment, the method for obtaining the long-term vehicle historical parking gap rate includes:

[0026] Based on historical data, the number of long-term vehicles without parking spaces during the same peak period is obtained. The number of long-term vehicles without parking spaces is represented by the number of long-term vehicles with zero vacant ordinary parking spaces upon entry.

[0027] Get the total number of long-term vehicle admissions during the same peak period;

[0028] Based on the number of long-term vehicles without parking spaces and the total number of long-term vehicles entering the parking lot, the historical parking gap rate for long-term vehicles is calculated.

[0029] In one embodiment, the method for obtaining the historical average parking time of the temporary vehicle includes:

[0030] Based on historical data, obtain the total parking time of temporary vehicles entering the parking lot during the same peak period;

[0031] Get the total number of temporary vehicles entering the park during the same peak period;

[0032] Based on the total parking time of temporary vehicles and the total number of temporary vehicles entering the parking lot, the historical average parking time of temporary vehicles is calculated.

[0033] In one embodiment, the step of dynamically calculating the number of parking spaces available for charging that can be temporarily used as ordinary parking spaces specifically includes:

[0034] Based on the historical parking gap rate of long-term vehicles, predict the current number of parking gaps for long-term vehicles;

[0035] The current number of parking vacancies for long-term vehicles is combined with the historical average number of vacant charging parking spaces, and a decay calculation is performed based on the historical average parking time of temporary vehicles to obtain the number of available charging parking spaces.

[0036] In one embodiment, the step of predicting the current number of parking vacancies for long-term vehicles based on the historical parking vacancies rate for long-term vehicles specifically includes:

[0037] Based on historical data, the total number of long-term vehicle admissions and the number of long-term vehicle registrations during the same peak period are obtained, and the historical admission ratio of long-term vehicles is calculated.

[0038] Get the current registration number of long-term vehicles;

[0039] The predicted number of long-term vehicle admissions is estimated based on the historical admission ratio of long-term vehicles and the current number of long-term vehicle registrations. The current number of parking gaps for long-term vehicles is calculated using the predicted number of long-term vehicle admissions and the historical parking gap rate for long-term vehicles.

[0040] In one embodiment, the calculation formula for the number of available charging parking spaces is:

[0041] ;

[0042] Where M A M is the number of parking spaces that can be used for charging. k is the historical average number of vacant charging parking spaces, M L is the number of parking gaps for long-term vehicles, λ is the attenuation coefficient, T T is the historical average parking time of temporary vehicles, T 高 n is the duration of the nth peak period.

[0043] In one embodiment, the calculation formula for the number of available charging parking spaces is:

[0044] ;

[0045] Where M A is the number of available charging parking spaces, Mk is the historical average number of vacant charging parking spaces, M L is the number of parking gaps for long-term vehicles, λ is the attenuation coefficient, T T is the historical average parking time of temporary vehicles, T 高 n is the duration of the nth peak period, W K and W L is the weight coefficient, and W K +W L =1.

[0046] Secondly, this application provides a smart parking management method and system, which adopts the following technical solutions:

[0047] A smart parking management system, comprising:

[0048] An information acquisition module is used to acquire vehicle information, the number of available common parking spaces, and the number of available charging parking spaces in real time. The vehicle information includes vehicle type, charging type, and vehicle size. The vehicle type includes electric vehicles and non-electric vehicles, and the charging type includes temporary vehicles, long-term vehicles, and special vehicles.

[0049] The data analysis module is used to determine whether the peak period has arrived. If so, it analyzes the historical average number of vacant charging parking spaces, the historical parking gap rate for long-term vehicles, and the historical average parking duration for temporary vehicles during the same peak period based on historical data.

[0050] The parking space calculation module dynamically calculates the number of available charging parking spaces that can be temporarily used as ordinary parking spaces based on a fusion analysis of the historical average number of vacant charging parking spaces, the historical parking gap rate for long-term vehicles, and the historical average parking duration of temporary vehicles.

[0051] The entry difference calculation module obtains the entry volume of long-term vehicles during peak hours in real time, and calculates the entry difference of long-term vehicles based on the predicted entry volume of long-term vehicles during peak hours;

[0052] The parking space diversion control module diverts charging parking spaces as temporary ordinary parking spaces if the difference in the number of long-term vehicles entering the parking lot is greater than the number of currently available ordinary parking spaces. When the number of diverted charging parking spaces is greater than or equal to the number of diverted charging parking spaces, or the number of available charging parking spaces is less than a preset value, the diversion of charging parking spaces is stopped.

[0053] The vehicle access control module prohibits temporary vehicles from entering if the difference between the long-term vehicle entry and the number of currently available ordinary parking spaces is greater than the number of charging parking spaces, or if the vehicle size is greater than the preset value.

[0054] In summary, this application has the following beneficial effects:

[0055] 1. Precisely manage large vehicles and ensure consistent parking data: Leveraging a precise vehicle size measurement mechanism, large vehicles are strictly controlled. Real-time vehicle size information is captured during vehicle entry and exit, enabling the parking lot to accurately track the compatibility of each incoming vehicle with a parking space, ensuring high consistency between recorded entry and exit information and actual parking space occupancy data. This not only facilitates refined parking lot management, avoiding wasted space and parking chaos caused by mismatches between vehicle size and parking spaces, but also provides an accurate data foundation for subsequent parking resource scheduling.

[0056] 2. Intelligently allocate charging spaces to improve peak parking availability for long-term vehicles: The system tracks the number of long-term vehicle entries in real time and, based on historical data, predicts peak-period vehicle arrivals. By precisely calculating the difference between the two, it accurately assesses parking demand. When this difference exceeds the current number of available regular parking spaces, the system intelligently and dynamically allocates charging spaces, temporarily converting them into regular spaces for long-term vehicles. This effectively alleviates the parking shortage faced by long-term vehicles during peak periods, significantly improving parking availability for long-term users during peak hours, significantly enhancing their parking experience, and increasing their satisfaction and loyalty to the parking service. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a system architecture diagram of the smart parking management system of this embodiment;

[0058] Figure 2 It is a flow chart of the smart parking management method of this embodiment.

[0059] In the figure, 10, information acquisition module; 20, data analysis module; 30, parking space calculation module; 40, entry difference calculation module; 50, parking space misappropriation control module; 60, vehicle admission control module; 70, vehicle exit control module. DETAILED DESCRIPTION

[0060] The present application is further described in detail below with reference to the accompanying drawings.

[0061] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. However, it should be understood by those skilled in the art that the present application can be implemented without these details. In some cases, in order to avoid unnecessary descriptions that make various aspects of the present application obscure, the well-known methods, processes, systems, components and / or circuits that have been described at a higher level will not be described in detail. It is obvious to those skilled in the art that various changes can be made to the embodiments disclosed in the present application, and the general principles defined in the present application can be applied to other embodiments and application scenarios without departing from the principles and scope of the present application. Therefore, the present application is not limited to the embodiments shown, but conforms to the broadest scope consistent with the scope claimed for protection in the present application.

[0062] It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0063] In the description of this application, "several" means one or more, "many" means more than two, "greater than," "less than," and "exceed" are understood to exclude the number itself, while "above," "below," and "within" are understood to include the number itself. The use of "first" and "second" in the description is solely for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, implicitly specifying the number of the indicated technical features, or implicitly specifying the order of the indicated technical features.

[0064] In the description of this application, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any combination in one or more embodiments or examples.

[0065] A smart parking management system, such as Figure 1 As shown, it includes an information acquisition module 10, a data analysis module 20, a parking space calculation module 30, an entry difference calculation module 40, a parking space misappropriation control module 50, a vehicle admission control module 60 and a vehicle exit control module 70.

[0066] The information acquisition module 10 includes at least a vehicle information collection submodule and a parking space status monitoring submodule.

[0067] The vehicle information acquisition submodule is used to obtain vehicle information. It integrates at least a high-definition camera and a laser sensor, and the laser sensor is used to obtain vehicle size information.

[0068] High-definition cameras are used to scan license plates, identifying information such as the license plate number and color. The information obtained from the license plate scans is used to determine the vehicle type and fee type. Vehicle types include electric and non-electric vehicles, and fee types include temporary vehicles, long-term vehicles, and special vehicles. Long-term vehicles are license plates leased on a monthly or annual basis, and there is no additional fee for entry and exit during the lease period. Temporary vehicles are vehicles with license plates that are charged based on time after entry. Special vehicles have special information on their license plates, such as specific words and letters on the license plate number or a specific license plate color. This special information is pre-entered into the system, and special vehicles can enjoy parking discounts or be exempted from parking fees upon entry.

[0069] The parking space status monitoring submodule is used to detect the usage of ordinary parking spaces and charging parking spaces. Among them, the parking space status monitoring submodule is at least required to be able to identify the charging status of the charging parking space. The identification method can be through a combination of high-definition cameras and charging status of charging seats, or it can be obtained by collecting information through preset QR codes and starting the charging input method of the charging seat.

[0070] The number of available ordinary parking spaces can be calculated based on the total number of ordinary parking spaces, the number of vehicles entering and exiting the parking lot, and the number of vehicles charging.

[0071] The data analysis module 20 is used to determine whether the peak period has arrived. If the peak period has been identified, the module analyzes the historical average number of vacant charging parking spaces, the historical parking gap rate for long-term vehicles, and the historical average parking time for temporary vehicles during the same peak period based on historical data.

[0072] The parking space calculation module 30 performs a fusion analysis based on the historical average number of vacant charging parking spaces, the historical parking gap rate of long-term vehicles, and the historical average parking time of temporary vehicles, and dynamically calculates the number of charging parking spaces that can be temporarily used as ordinary parking spaces.

[0073] The entry difference calculation module 40 obtains the entry volume of long-term vehicles during the peak period in real time, and calculates the long-term vehicle entry difference based on the predicted entry volume of long-term vehicles during the peak period.

[0074] The parking space appropriation control module 50 appropriates charging parking spaces as temporary ordinary parking spaces if the difference in the number of long-term vehicles entering the parking lot is greater than the number of currently available ordinary parking spaces. When the number of appropriated charging parking spaces is greater than or equal to the number of available charging parking spaces, or the number of available charging parking spaces is less than a preset value, the appropriation of charging parking spaces is stopped.

[0075] The vehicle admission control module 60 prohibits temporary vehicles from entering if the difference between the long-term vehicle admission and the long-term vehicle admission is greater than the number of currently available ordinary parking spaces and the charging parking spaces are stopped from being appropriated, or if the vehicle size is greater than a preset value.

[0076] The vehicle exit control module 70 includes a high-definition camera. When a vehicle exits, it identifies the vehicle license plate information and calculates the fee. When charging for temporary vehicles, discounts can be made based on coupons, merchant discounts, etc.

[0077] The smart parking management method corresponding to the above system specifically includes the following steps:

[0078] S100. Acquire vehicle information, the number of available ordinary parking spaces, and the number of available charging parking spaces in real time. The vehicle information includes vehicle type, charging type, and vehicle size. Vehicle types include electric vehicles and non-electric vehicles. Charging types include temporary vehicles, long-term vehicles, and special vehicles.

[0079] S200: If it is identified that a peak period has arrived, the historical average number of vacant charging parking spaces, the historical parking gap rate for long-term vehicles, and the historical average parking time for temporary vehicles during the same peak period are analyzed based on historical data.

[0080] Specifically, the method for obtaining the historical average number of vacant charging parking spaces includes:

[0081] Step 1: Based on historical data, calculate the historical average occupancy rate of charging parking spaces.

[0082] In this embodiment, the actual charging demand of the charging parking space is calculated by using the charging time rather than the parking space occupancy method. This step specifically includes:

[0083] Based on historical data, obtain the actual charging time of all charging parking spaces corresponding to the same peak period;

[0084] Calculate the average charging time based on the actual charging time of the charging parking space;

[0085] Calculate the theoretical charging time during peak hours based on the duration of the peak hours and the total number of charging spaces;

[0086] The historical average occupancy rate of charging parking spaces is calculated based on the average charging time and the theoretical charging time.

[0087] Specifically, the data is collected from historical data on a daily basis to form multiple data sets. Each data set includes charging data for all charging spaces during the peak period of that day. The data sets are then summed to obtain the actual charging time for each charging space on that day. The average charging time is then calculated by averaging the data on a daily basis.

[0088] The theoretical charging time refers to the theoretical value of the total charging time that can be achieved by all charging spaces during peak hours.

[0089] Based on the above settings, the calculation formula for the historical average occupancy rate of charging parking spaces is as follows:

[0090] ;

[0091] Where R c is the historical average occupancy rate of charging parking spaces, T i c-occ T is the charging time of the peak period charging parking space on day i, total is the peak period duration, M c is the total number of charging parking spaces.

[0092] Step 2: Calculate the historical average number of available charging parking spaces based on the historical average occupancy rate of charging parking spaces and the total number of charging parking spaces.

[0093] The historical average number of idle charging parking spaces needs to be rounded after calculation. Therefore, the calculation formula for the historical average number of idle charging parking spaces is as follows:

[0094] ;

[0095] Where M k is the historical average number of vacant charging parking spaces, and floor() is the rounding function.

[0096] Methods for obtaining long-term historical parking gap rates include:

[0097] Based on historical data, the number of long-term vehicles without parking spaces during the same peak period is obtained. The number of long-term vehicles without parking spaces is represented by the number of long-term vehicles with 0 vacant ordinary parking spaces when entering the venue.

[0098] Get the total number of long-term vehicle admissions during the same peak period.

[0099] Based on the number of long-term vehicles without parking spaces and the total number of long-term vehicles entering the parking lot, the historical parking gap rate for long-term vehicles is calculated. The specific calculation formula for the historical parking gap rate for long-term vehicles is:

[0100] ;

[0101] Where R L is the historical parking gap rate of long-term vehicles, M L i is the number of long-term cars with 0 empty parking spaces during the peak period on the i-th day, M 总 i is the total number of long-term vehicles entering the peak period on day i.

[0102] Methods for obtaining the historical average parking duration of temporary vehicles include:

[0103] Based on historical data, obtain the total parking time of temporary vehicles entering the parking lot during the same peak period.

[0104] Get the total number of temporary vehicles entering the venue during the same peak period.

[0105] Based on the total parking time of temporary vehicles and the total number of temporary vehicles entering the parking lot, the historical average parking time of temporary vehicles is calculated. The calculation formula for the historical average parking time of temporary vehicles is:

[0106] ;

[0107] Where, T t is the historical average parking time of temporary vehicles, T i is the total parking time of temporary vehicles entering the parking lot during the peak period on the i-th day, M t is the total number of temporary vehicles entering the peak period on day i.

[0108] S300: Based on the historical average number of vacant charging parking spaces, the historical parking gap rate for long-term vehicles, and the historical average parking duration of temporary vehicles, a fusion analysis is performed to dynamically calculate the number of charging parking spaces that can be temporarily used as ordinary parking spaces.

[0109] Specifically, in this step, the current number of long-term parking spaces is predicted based on the historical parking gap rate for long-term vehicles. This number is then combined with the historical average number of available charging spaces. Finally, a decay calculation is performed based on the historical average parking duration of temporary vehicles to determine the number of available charging spaces.

[0110] In this embodiment, the step of predicting the current number of parking vacancies for long-term vehicles based on the historical parking vacancies rate for long-term vehicles specifically includes:

[0111] Based on historical data, the total number of long-term vehicle entries and the number of long-term vehicle registrations during the same peak period are obtained to calculate the historical admission ratio of long-term vehicles. The historical admission ratio of long-term vehicles is an average, so the daily admission ratio is calculated by dividing the total number of long-term vehicle entries by the number of long-term vehicle registrations. The average is then taken on a daily basis to obtain the historical admission ratio of long-term vehicles.

[0112] After that, get the current registration count of long-term vehicles.

[0113] Then, based on the historical admission ratio of long-term vehicles and the current number of long-term vehicle registrations, the predicted number of long-term vehicle admissions is obtained by multiplying the product. It should be noted that this embodiment only provides a method for predicting the predicted number of long-term vehicle admissions; other methods can also be used to obtain the predicted number of long-term vehicle admissions, such as through model prediction.

[0114] Finally, the current number of parking gaps for long-term vehicles is calculated by multiplying the predicted number of long-term vehicle entries and the historical parking gap rate for long-term vehicles.

[0115] There are multiple ways to calculate the number of available charging parking spaces based on the different ways of integrating the current number of parking gaps for long-term vehicles with the historical average number of vacant charging parking spaces.

[0116] In one embodiment, the formula for calculating the number of available charging parking spaces is:

[0117] ;

[0118] Where M A M is the number of parking spaces that can be used for charging. k is the historical average number of vacant charging parking spaces, M L is the number of parking gaps for long-term vehicles, λ is the attenuation coefficient, T T is the historical average parking time of temporary vehicles, T 高 n is the duration of the nth peak period.

[0119] In another embodiment, the formula for calculating the number of usable charging parking spaces is:

[0120] ;

[0121] Where M A is the number of available charging parking spaces, Mk is the historical average number of vacant charging parking spaces, M L is the number of parking gaps for long-term vehicles, λ is the attenuation coefficient, T T is the historical average parking time of temporary vehicles, T 高 n is the duration of the nth peak period, W K and W L is the weight coefficient, and W K +W L =1.

[0122] S400: Acquire the number of long-term vehicles entering the parking lot during the peak period in real time, and calculate the long-term vehicle entry difference based on the predicted number of long-term vehicles entering the parking lot during the peak period.

[0123] S500: If the difference in the number of long-term parking spaces is greater than the number of currently available ordinary parking spaces, the charging parking spaces are used as temporary ordinary parking spaces. When the number of used charging parking spaces is greater than or equal to the number of available charging parking spaces, or the number of available charging parking spaces is less than a preset value, the use of charging parking spaces is stopped.

[0124] S600: If the difference in the number of long-term vehicles entering the parking lot is greater than the number of currently available ordinary parking spaces and the use of charging parking spaces is stopped, or if the vehicle size is greater than a preset value, temporary vehicles are prohibited from entering.

[0125] The embodiments of this specific implementation method are all preferred embodiments of the present application and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A smart parking management method, characterized in that: The following steps are involved: Real-time acquisition of vehicle information, the number of available regular parking spaces, and the number of available charging parking spaces. The vehicle information includes vehicle type, charging type, and vehicle size. The vehicle type includes electric vehicles and non-electric vehicles, and the charging type includes temporary vehicles, long-term vehicles, and special vehicles. If a peak period is identified, the average number of available charging parking spaces, the historical parking gap rate for long-term vehicles, and the average parking duration for temporary vehicles during the same peak period are analyzed based on historical data. Based on the historical average number of vacant charging parking spaces, the historical parking gap rate for long-term vehicles, and the historical average parking duration of temporary vehicles, a fusion analysis is conducted to dynamically calculate the number of charging parking spaces that can be temporarily used as ordinary parking spaces. Obtain the number of long-term vehicles entering the market during peak hours in real time, and calculate the difference in long-term vehicle entry based on the predicted number of long-term vehicle entry during peak hours; If the difference in the number of long-term parking spaces is greater than the number of available regular parking spaces, the charging parking spaces will be used as temporary regular parking spaces. When the number of used charging parking spaces is greater than or equal to the number of available charging parking spaces, or the number of available charging parking spaces is less than a preset value, the use of charging parking spaces will be stopped. If the difference in the number of long-term vehicles entering the parking lot is greater than the number of currently available ordinary parking spaces and the use of charging parking spaces is stopped, or the vehicle size is larger than the preset value, temporary vehicles are prohibited from entering.

2. A smart parking management method according to claim 1, characterized in that: The method for obtaining the historical average number of vacant charging parking spaces includes: Based on historical data, calculate the historical average occupancy rate of charging parking spaces; Based on the historical average occupancy rate of charging parking spaces and the total number of charging parking spaces, the historical average number of available charging parking spaces is calculated.

3. A smart parking management method according to claim 2, characterized in that: The step of calculating the historical average occupancy rate of charging parking spaces based on historical data specifically includes: Based on historical data, obtain the actual charging time of all charging parking spaces corresponding to the same peak period; Calculate the average charging time based on the actual charging time of the charging parking space; Calculate the theoretical charging time during peak hours based on the duration of the peak hours and the total number of charging spaces; The historical average occupancy rate of charging parking spaces is calculated based on the average charging time and the theoretical charging time.

4. A smart parking management method according to claim 1, characterized in that: The method for obtaining the historical parking gap rate of long-term vehicles includes: Based on historical data, the number of long-term vehicles without parking spaces during the same peak period is obtained. The number of long-term vehicles without parking spaces is represented by the number of long-term vehicles with zero vacant ordinary parking spaces upon entry. Get the total number of long-term vehicle admissions during the same peak period; Based on the number of long-term vehicles without parking spaces and the total number of long-term vehicles entering the parking lot, the historical parking gap rate for long-term vehicles is calculated.

5. The smart parking management method according to claim 1, characterized in that: The method for obtaining the historical average parking time of the temporary vehicle includes: Based on historical data, obtain the total parking time of temporary vehicles entering the parking lot during the same peak period; Get the total number of temporary vehicles entering the park during the same peak period; Based on the total parking time of temporary vehicles and the total number of temporary vehicles entering the parking lot, the historical average parking time of temporary vehicles is calculated.

6. A smart parking management method according to claim 1, characterized in that: The step of dynamically calculating the number of parking spaces that can be temporarily used as ordinary parking spaces for charging specifically includes: Based on the historical parking gap rate of long-term vehicles, predict the current number of parking gaps for long-term vehicles; The current number of parking vacancies for long-term vehicles is combined with the historical average number of vacant charging parking spaces, and a decay calculation is performed based on the historical average parking time of temporary vehicles to obtain the number of available charging parking spaces.

7. A smart parking management method according to claim 6, characterized in that: The step of predicting the current number of parking vacancies for long-term vehicles based on the historical parking vacancies rate for long-term vehicles specifically includes: Based on historical data, the total number of long-term vehicle admissions and the number of long-term vehicle registrations during the same peak period are obtained, and the historical admission ratio of long-term vehicles is calculated. Get the current registration number of long-term vehicles; The predicted number of long-term vehicle admissions is estimated based on the historical admission ratio of long-term vehicles and the current number of long-term vehicle registrations. The current number of parking gaps for long-term vehicles is calculated using the predicted number of long-term vehicle admissions and the historical parking gap rate for long-term vehicles.

8. A smart parking management method according to claim 6 or 7, characterized in that: The calculation formula for the number of usable charging parking spaces is: ； Where M A M is the number of parking spaces that can be used for charging. k is the historical average number of vacant charging parking spaces, M L is the number of parking gaps for long-term vehicles, λ is the attenuation coefficient, T T is the historical average parking time of temporary vehicles, T 高 n is the duration of the nth peak period.

9. A smart parking management method according to claim 6 or 7, characterized in that: The calculation formula for the number of usable charging parking spaces is: ； Where M A is the number of available charging parking spaces, Mk is the historical average number of vacant charging parking spaces, M L is the number of parking gaps for long-term vehicles, λ is the attenuation coefficient, T T is the historical average parking time of temporary vehicles, T 高 n is the duration of the nth peak period, W K and W L is the weight coefficient, and W K +W L =1.

10. A smart parking management system, characterized in that: include: An information acquisition module (10) is used to acquire vehicle information, the number of available common parking spaces, and the number of available charging parking spaces in real time, wherein the vehicle information includes vehicle type, charging type, and vehicle size, wherein the vehicle type includes electric vehicles and non-electric vehicles, and the charging type includes temporary vehicles, long-term vehicles, and special vehicles; A data analysis module (20) is used to determine whether a peak period has been entered. If a peak period has been entered, the module analyzes the historical average number of vacant charging parking spaces, the historical parking gap rate of long-term vehicles, and the historical average parking time of temporary vehicles during the same peak period based on historical data; The parking space calculation module (30) performs a fusion analysis based on the historical average number of vacant charging parking spaces, the historical parking gap rate of long-term vehicles, and the historical average parking time of temporary vehicles, and dynamically calculates the number of charging parking spaces that can be temporarily used as ordinary parking spaces; An entry difference calculation module (40) obtains the entry volume of long-term vehicles during the peak period in real time, and calculates the entry difference of long-term vehicles based on the predicted entry volume of long-term vehicles during the peak period; The parking space appropriation control module (50) appropriates the charging parking space as a temporary ordinary parking space if the difference in the number of long-term vehicles entering the parking lot is greater than the number of currently available ordinary parking spaces; When the number of used charging parking spaces is greater than or equal to the number of available charging parking spaces, or the number of available charging parking spaces is less than a preset value, the use of charging parking spaces will be stopped. The vehicle admission control module (60) prohibits temporary vehicles from entering if the difference between the long-term vehicle admission and the number of currently available ordinary parking spaces is greater than the number of available charging parking spaces, or if the vehicle size is greater than a preset value.

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