Parking lot management method and system based on behavior recognition

Abstract

The invention discloses a parking lot management method and system based on behavior recognition, and relates to the technical field of data processing. Firstly, historical parking record data of each vehicle is analyzed to obtain a parking behavior representation value of each vehicle, so that personalized parking recommendation routes and optimized utilization of parking resources of a parking lot are provided for users, and then facility data in an operation area of the parking lot are analyzed to obtain a parking behavior representation value of each vehicle. The method can recommend a region with less traffic flow for a user, improves the parking resource utilization condition of the parking lot operation sub-regions, obtains a recommended parking route result of each vehicle through screening and analysis, facilitates the improvement of the parking efficiency and comfort of the user, and improves the user experience. The parking lot can be helped to reasonably allocate parking resources, parking lot congestion and resource waste are reduced, operation management of the parking lot is optimized, and the overall operation efficiency and service level of the parking lot are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a parking lot management method and system based on behavior recognition. Background Art

[0002] In the field of urban traffic management, city centers usually face the problem of tight parking spaces. It is necessary to adjust parking resource allocation according to real-time demand and optimize the utilization of parking resources. Therefore, parking management systems are widely used in the field of urban traffic management.

[0003] The prior art, such as the invention patent announcement with announcement number: CN116523350B, is a smart parking lot traffic flow planning and management system based on data analysis, including a server, a vehicle monitoring and identification module, a vehicle fee control module, a parking performance backtracking module and a car owner value decision analysis module; the invention performs parking performance backtracking analysis and car owner value analysis on the vehicle users corresponding to the parking lot one by one, so as to carry out subsequent planning and management based on different vehicle users in a targeted manner, which is conducive to ensuring the management effect of the parking lot, and by receiving the parking space request of the corresponding vehicle user and determining the matching parking space, it is convenient for users to make parking space reservations in advance while also realizing the timely release of parking spaces, further improving the intelligence level and management effect of the parking lot, and by conducting periodic management analysis on the corresponding parking lot for subsequent parking lot management planning, the parking safety and efficiency in the parking lot are improved while ensuring operating income.

[0004] Prior art, such as the invention patent announcement with announcement number: CN115222158B, discloses a smart city parking lot management method, system and device based on the Internet of Things. The smart city parking lot management method based on the Internet of Things is executed by a management platform, and the method includes obtaining the user location of the user platform based on the service platform, and determining a candidate parking lot that meets preset conditions; determining the time when the vehicle to be parked arrives at the candidate parking lot based on the user location; determining the vacant parking space information when the vehicle to be parked arrives at the candidate parking lot; determining the recommended information based on the vacant parking space information; and sending the recommended information to the user platform based on the service platform. The system includes a user platform, a service platform, a management platform, a sensor network platform and an object platform. The method can be implemented by a smart city parking lot management device based on the Internet of Things.

[0005] Combined with the above solutions, it is found that currently in the field of parking lot management technology, usually only the number of parking spaces is analyzed, and the route navigation of the parking lot lacks analysis of the environmental facilities of the parking spaces, resulting in users being unable to find suitable parking spaces, affecting users' parking efficiency and speed, and then causing traffic congestion in the parking lot, which may increase the difficulty of parking lot management and affect the utilization rate of the parking lot. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a parking lot management method and system based on behavior recognition, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a parking lot management method based on behavior recognition, including a parking space publishing terminal sending characteristic data of each vehicle, and analyzing the historical parking record data of each vehicle to obtain a parking behavior representation value of each vehicle.

[0008] The facility data within the parking lot operation area is monitored and acquired, and the facility data within the parking lot operation area is analyzed, and the environmental facility characterization value in each parking lot operation sub-area is obtained in combination with the current vehicle position.

[0009] According to the parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area, the recommended parking route result of each vehicle is obtained through screening analysis, and the recommended parking route result of each vehicle is imported into the parking space guidance screen terminal for output display.

[0010] Furthermore, the historical parking record data of each vehicle includes the cumulative parking duration and the cumulative parking times of each vehicle in each parking lot operation sub-area.

[0011] Furthermore, the historical parking record data of each vehicle is analyzed to obtain a parking behavior characterization value of each vehicle. The specific process is: the parking lot operation area is divided to obtain each parking lot operation sub-area, each parking lot operation sub-area is analyzed, and the cumulative parking time and the cumulative number of parking times of each vehicle in each parking lot operation sub-area are counted, and the parking behavior characterization value of each vehicle is obtained after processing.

[0012] Furthermore, the parking behavior characterization value of each vehicle is a numerical quantification result obtained by analyzing the historical parking record data of each vehicle, and is used to comprehensively quantify the impact of the historical parking behavior of each vehicle on the optimal parking operation sub-area of ​​the vehicle.

[0013] Furthermore, the facility data within the parking lot operation area is analyzed, and combined with the current vehicle position, the environmental facility characterization value in each parking lot operation sub-area is obtained. The specific analysis process is: obtaining the layout information of the parking lot operation area, monitoring the position coordinates of each vehicle in the parking lot operation area, and obtaining the distance between each parking lot operation sub-area and the current position of each vehicle.

[0014] According to the distance between each parking lot operation sub-area and the current position of each vehicle, the number of vacant parking spaces in each parking lot operation sub-area is counted, and the first characterization value of the environmental facilities in each parking lot operation sub-area is obtained through processing.

[0015] The vehicle in and out conditions in each parking lot operation sub-area are monitored, and the vehicle flow in each parking lot operation sub-area is statistically obtained.

[0016] The water depth data of different positions of each vacant parking space in each parking lot operation sub-area are monitored and counted, and the average water depth of each vacant parking space in each parking lot operation sub-area is obtained after processing.

[0017] According to the traffic volume in each parking lot operation sub-area and the average water depth of each vacant parking space in each parking lot operation sub-area, the second characterization value of the environmental facilities in each parking lot operation sub-area is analyzed and obtained.

[0018] According to the first characterization value of the environmental facilities in each parking lot operation sub-area and the second characterization value of the environmental facilities in each parking lot operation sub-area, the environmental facility characterization value in each parking lot operation sub-area is obtained through weighted analysis.

[0019] Furthermore, the environmental facility characterization value in each parking lot operation sub-area is a numerical quantification result obtained by analyzing the environmental facilities in the parking lot operation area, and is used to comprehensively quantify the impact of the parking lot environmental facilities on the parking route of the vehicle.

[0020] Furthermore, the screening analysis obtains the recommended parking route results for each vehicle. The specific analysis process is: based on the parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area, a comprehensive analysis is performed to obtain the parking route index value in each parking lot operation sub-area for each vehicle.

[0021] The parking route index value in each parking lot operation sub-area of ​​each vehicle is a numerical quantification result obtained by analyzing the parking lot operation area and the historical parking record data of each vehicle, and is used to quantify the influence of different factors on the recommended parking route result of the vehicle.

[0022] The parking route index values ​​in each parking lot operation sub-area of ​​each vehicle are sorted from large to small, and the operation sub-area corresponding to the parking route index value in each parking lot operation sub-area of ​​each vehicle ranked first is selected as the recommended parking sub-area, and the parking route of the recommended parking sub-area is obtained. The recommended parking route result of each vehicle is imported into the parking space guidance screen terminal for output display.

[0023] Furthermore, the parking behavior characterization value of each vehicle is specifically analyzed under the following conditions:

[0024] In the formula, δ i represents the parking behavior characterization value of the i-th vehicle, ε i→jrepresents the cumulative parking time of the i-th vehicle in the j-th parking lot operation sub-area, Δε represents the set reference parking time, μ1 represents the impact factor corresponding to the set parking time, and ρ i→j represents the cumulative number of parking times of the i-th vehicle in the j-th parking lot operation sub-area, Δρ represents the set reference parking times, μ2 represents the impact factor corresponding to the set parking times, i represents the number of each vehicle, i=1,2,3,…n, n represents the total number of vehicles, j represents the number of each parking lot operation sub-area, j=1,2,3,…m, m represents the total number of parking lot operation sub-areas.

[0025] Furthermore, the parking route index value of each parking lot operation sub-area of ​​each vehicle is specifically analyzed under the following conditions:

[0026] In the formula, α i→j represents the parking route index of the i-th vehicle in the j-th parking lot operation sub-area, δ i represents the parking behavior characterization value of the i-th vehicle, θ1 represents the weight factor corresponding to the set parking behavior characterization value, γ j represents the environmental facility characterization value in the jth parking lot operation sub-area, θ2 represents the weight factor corresponding to the set environmental facility characterization value, e represents a natural constant, i represents the number of each vehicle, i = 1, 2, 3, ... n, n represents the total number of vehicles, j represents the number of each parking lot operation sub-area, j = 1, 2, 3, ... m, m represents the total number of parking lot operation sub-areas.

[0027] A second aspect of the present invention provides a parking lot management system based on behavior recognition, comprising:

[0028] The vehicle parking behavior analysis module is used for the parking space publishing terminal to send the characteristic data of each vehicle, and analyze the historical parking record data of each vehicle to obtain the parking behavior representation value of each vehicle.

[0029] The parking lot environment facility analysis module is used to monitor and obtain facility data within the parking lot operation area, analyze the facility data within the parking lot operation area, and obtain the environmental facility representation value in each parking lot operation sub-area in combination with the current vehicle position.

[0030] The recommended parking route analysis module is used to obtain the recommended parking route results for each vehicle based on the parking behavior representation value of each vehicle and the environmental facility representation value in each parking lot operation sub-area, and import the recommended parking route results for each vehicle into the parking space guidance screen terminal for output display.

[0031] The present invention has the following beneficial effects:

[0032] (1) The present invention provides a parking lot management method based on behavior recognition. First, the historical parking record data of each vehicle is analyzed to obtain the parking behavior characterization value of each vehicle, which can analyze the parking habits and behavior patterns of each vehicle. Then, the facility data in the parking lot operation area is analyzed to obtain the environmental facility characterization value in each parking lot operation sub-area, which is helpful for analyzing the environmental conditions and facility conditions of the parking lot. Then, the recommended parking route results for each vehicle are obtained by screening, which can help users quickly find a suitable parking location.

[0033] (2) The present invention obtains the parking behavior characterization value of each vehicle through analysis, which helps to provide personalized parking recommendations based on the parking habits and behavior characterization values ​​of each vehicle in each parking lot operation sub-area. Users can quickly find a location that suits their parking habits, improve the user's experience and satisfaction during the parking process, and reduce the user's wandering and searching time in the parking lot.

[0034] (3) The present invention obtains the environmental facility characterization value in each parking lot operation sub-area by analyzing, and can recommend parking areas with good facilities to users, and recommend areas with less water depth and less traffic flow, which helps users avoid choosing parking spaces with serious water accumulation, reduces the impact of environmental factors on vehicles during parking, and optimizes users' parking experience.

[0035] (4) The present invention obtains the recommended parking route results for each vehicle through screening analysis, taking into account the parking behavior preferences of the vehicles and the environmental facilities of the operating sub-areas. Users can avoid unnecessary parking searches and waiting time, and can experience more efficient and convenient services. It can also effectively balance the parking resource utilization of each parking lot operating sub-area, avoiding resource waste and congestion.

[0036] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0038] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0039] Figure 3 An example image of parking route indicator values. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] See also Figure 1 As shown, the first aspect of an embodiment of the present invention provides a technical solution: a parking lot management method based on behavior recognition, comprising a parking space publishing terminal sending characteristic data of each vehicle, and analyzing the historical parking record data of each vehicle to obtain a parking behavior characterization value of each vehicle.

[0042] The facility data within the parking lot operation area is monitored and acquired, and the facility data within the parking lot operation area is analyzed, and the environmental facility characterization value in each parking lot operation sub-area is obtained in combination with the current vehicle position.

[0043] According to the parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area, the recommended parking route result of each vehicle is obtained through screening analysis, and the recommended parking route result of each vehicle is imported into the parking space guidance screen terminal for output display.

[0044] Specifically, the historical parking record data of each vehicle includes the cumulative parking duration and the cumulative parking times of each vehicle in each parking lot operation sub-area.

[0045] Specifically, the historical parking record data of each vehicle is analyzed to obtain the parking behavior characterization value of each vehicle. The specific process is: divide the parking lot operation area to obtain each parking lot operation sub-area, analyze each parking lot operation sub-area, and count the cumulative parking time and cumulative parking times of each vehicle in each parking lot operation sub-area, and obtain the parking behavior characterization value of each vehicle after processing.

[0046] Specifically, the parking behavior representation value of each vehicle is a numerical quantification result obtained by analyzing the historical parking record data of each vehicle, and is used to comprehensively quantify the impact of the historical parking behavior of each vehicle on the optimal parking operation sub-area of ​​the vehicle.

[0047] Specifically, the facility data within the parking lot operation area is analyzed, and combined with the current vehicle position, the environmental facility characterization value in each parking lot operation sub-area is obtained. The specific analysis process is: obtaining the layout information of the parking lot operation area, monitoring the position coordinates of each vehicle in the parking lot operation area, and obtaining the distance between each parking lot operation sub-area and the current position of each vehicle.

[0048] According to the distance between each parking lot operation sub-area and the current position of each vehicle, the number of vacant parking spaces in each parking lot operation sub-area is counted, and the first characterization value of the environmental facilities in each parking lot operation sub-area is obtained through processing.

[0049] It should be noted that the first characterization value of the environmental facilities in each parking lot operation sub-area represents the numerical quantification result obtained by analyzing the facilities in the parking lot operation area, and serves as the analysis basis of the environmental facility characterization value in each parking lot operation sub-area, which can be obtained by the following analysis method, and the specific analysis conditions are as follows:

[0050]

[0051] In the formula, σ j represents the first characterization value of the environmental facilities in the jth parking lot operation sub-area, τ i→j represents the distance between the i-th vehicle and the j-th parking lot operation sub-area, Δτ represents the set reference distance, Indicates the impact factor corresponding to the set distance, β j represents the number of vacant parking spaces in the jth parking lot operation sub-area, Δβ represents the number of reference vacant parking spaces, It represents the impact factor corresponding to the set number of vacant parking spaces, i represents the number of each vehicle, i=1,2,3,…n, n represents the total number of vehicles, j represents the number of each parking lot operation sub-area, j=1,2,3,…m, m represents the total number of parking lot operation sub-areas.

[0052] It needs to be explained that the distance between each parking lot operating sub-area and the current position of each vehicle is measured by the on-board navigation system. The signal strength of the Bluetooth beacon between the current position of a vehicle and a parking lot operating sub-area is measured by the on-board navigation system, and then the distance between the parking lot operating sub-area and the current position of the vehicle is obtained through the trilateral measurement method.

[0053] It should be explained that the number of vacant parking spaces in each parking lot operation sub-area is obtained by detecting the status of the parking spaces through cameras. For example, the number of vacant parking spaces in a parking lot operation sub-area can be obtained as 3 through camera detection.

[0054] It should be noted that, in this embodiment, the impact factor corresponding to the preset distance and the impact factor corresponding to the number of vacant parking spaces are obtained from the parking lot operation database.

[0055] In a specific embodiment, through historical data, the relationship between the distance between each parking lot operation sub-area and the current position of each vehicle, the number of vacant parking spaces in each parking lot operation sub-area and the first characterization value of the environmental facilities in each parking lot operation sub-area is fitted to obtain a fitting curve. According to the fitting curve, the influencing factor corresponding to the distance between each parking lot operation sub-area and the current position of each vehicle and the influencing factor corresponding to the number of vacant parking spaces are determined, and the real-time distance between each parking lot operation sub-area and the current position of each vehicle and the number of vacant parking spaces in each parking lot operation sub-area are substituted into the fitting curve to obtain the corresponding influencing factor.

[0056] It should be noted that the impact factor corresponding to the distance and the impact factor corresponding to the number of vacant parking spaces are both numbers between 0 and 1.

[0057] It should be explained that in this embodiment, analyzing the distance between each parking lot operation sub-area and the current position of each vehicle and the number of free parking spaces in each parking lot operation sub-area helps to optimize the parking route and improve the traffic flow of the parking lot. The analysis method of this embodiment, the distance between each parking lot operation sub-area and the current position of each vehicle and the number of free parking spaces in each parking lot operation sub-area jointly affect the recommended parking route result of the vehicle.

[0058] In this implementation scheme, analyzing the distance between each parking lot operation sub-area and the current position of each vehicle helps users avoid congested points in parking areas, analyzing the number of vacant parking spaces in each parking lot operation sub-area more accurately analyzes and predicts the utilization rate of parking spaces in the parking lot operation sub-area, and analyzing the first characterization value of environmental facilities in each parking lot operation sub-area helps optimize recommended parking routes.

[0059] The vehicle in and out conditions in each parking lot operation sub-area are monitored, and the vehicle flow in each parking lot operation sub-area is statistically obtained.

[0060] The water depth data of different positions of each vacant parking space in each parking lot operation sub-area are monitored and counted, and the average water depth of each vacant parking space in each parking lot operation sub-area is obtained after processing.

[0061] According to the traffic volume in each parking lot operation sub-area and the average water depth of each vacant parking space in each parking lot operation sub-area, the second characterization value of the environmental facilities in each parking lot operation sub-area is analyzed and obtained.

[0062] It should be noted that the second characterization value of the environmental facilities in each parking lot operation sub-area represents the numerical quantification result obtained by analyzing the environment in the parking lot operation area, and serves as the analysis basis of the environmental facility characterization value in each parking lot operation sub-area, which can be obtained by the following analysis method, and the specific analysis conditions are as follows:

[0063]

[0064] In the formula, ∈ j represents the second characterization value of the environmental facilities in the jth parking lot operation sub-area, b j represents the traffic flow in the jth parking lot operation sub-area, Δb represents the set reference traffic flow, Indicates the impact factor corresponding to the set traffic flow, c j→k represents the average water depth of the kth vacant parking space in the jth parking lot operation sub-area, Δc represents the set reference average water depth, represents the influencing factor corresponding to the set average water depth, j represents the number of each parking lot operation sub-area, j=1,2,3,…m, m represents the total number of parking lot operation sub-areas, k represents the number of each vacant parking space, k=1,2,3,…L, L represents the total number of vacant parking spaces.

[0065] It needs to be explained that the traffic flow in each parking lot operation sub-area refers to the traffic flow through a parking lot operation sub-area per unit time, which can be monitored by a vehicle volume counter. For example, assuming that the vehicle volume counter monitors that 20 vehicles enter and exit a parking lot operation sub-area in a certain hour, then the traffic flow of the parking lot operation sub-area in this hour is 20 vehicles / hour.

[0066] It needs to be explained that the average water depth of each vacant parking space in each parking lot operation sub-area refers to the average depth of water accumulation on the parking space, which can be measured by a water level meter installed in the parking space. For example, assuming that the three water level meters of a vacant parking space in a parking lot operation sub-area measure the water depths to be 5cm, 6cm, and 10cm respectively, then the average water depth of the vacant parking space in the parking lot operation sub-area is (5cm+6cm+10cm)÷3=7cm.

[0067] It should be noted that, in this embodiment, the influencing factor corresponding to the preset vehicle flow rate and the influencing factor corresponding to the average water depth are obtained from the parking lot operation database.

[0068] In a specific embodiment, historical data is used to fit the relationship between the traffic flow in each parking lot operation sub-area, the average water depth of each vacant parking space in each parking lot operation sub-area, and the second characterization value of the environmental facilities in each parking lot operation sub-area to obtain a fitting curve. According to the fitting curve, the influencing factor corresponding to the traffic flow in each parking lot operation sub-area and the influencing factor corresponding to the average water depth of each vacant parking space are determined, and the real-time traffic flow in each parking lot operation sub-area and the average water depth of each vacant parking space in each parking lot operation sub-area are substituted into the fitting curve to obtain the corresponding influencing factor.

[0069] It should be noted that the impact factor corresponding to the traffic flow in each parking lot operation sub-area and the impact factor corresponding to the average water depth of each vacant parking space are both numbers between 0 and 1.

[0070] It should be explained that in this embodiment, the analysis of the traffic flow in each parking lot operation sub-area and the average water depth of each vacant parking space in each parking lot operation sub-area helps to improve the operation efficiency and service quality of the parking lot, and can also optimize the user's parking experience. The analysis method of this embodiment, the traffic flow in each parking lot operation sub-area and the average water depth of each vacant parking space in each parking lot operation sub-area jointly affect the recommended parking route results of the vehicle.

[0071] In this implementation scheme, analyzing the traffic flow in each parking lot operation sub-area helps to optimize parking management and resource allocation. Analyzing the average water depth of each vacant parking space in each parking lot operation sub-area can provide vehicles with more intelligent parking route recommendations, avoid parking spaces with severe waterlogging, and improve user parking efficiency. Analyzing the second characterization value of environmental facilities in each parking lot operation sub-area helps to improve user satisfaction with the parking lot environment, avoid vehicles waiting or parking for a long time in areas with high traffic flow or severe waterlogging, and improve the overall user experience.

[0072] According to the first characterization value of the environmental facilities in each parking lot operation sub-area and the second characterization value of the environmental facilities in each parking lot operation sub-area, the environmental facility characterization value in each parking lot operation sub-area is obtained through weighted analysis.

[0073] It should be noted that the environmental facility characterization value of each parking lot operation sub-area represents the numerical quantification result obtained by analyzing the environment and facilities in the parking lot operation area, and serves as the analysis basis for the parking route index value of each parking lot operation sub-area of ​​each vehicle. It can be obtained by the following analysis method, and the specific analysis conditions are as follows:

[0074]

[0075] In the formula, γ j represents the environmental facility characterization value in the jth parking lot operation sub-area, σ j represents the first characterization value of the environmental facilities in the jth parking lot operation sub-area, ω1 represents the weight factor corresponding to the set first characterization value of the environmental facilities, ∈ j represents the second characterization value of the environmental facilities in the jth parking lot operation sub-area, ω2 represents the weight factor corresponding to the set second characterization value of the environmental facilities, e represents a natural constant, j represents the number of each parking lot operation sub-area, j=1,2,3,…m, m represents the total number of parking lot operation sub-areas.

[0076] In a specific embodiment, Table 1 shows the environmental facility characterization values ​​corresponding to the first characterization values ​​and the second characterization values ​​of different environmental facilities in a parking lot operation sub-area. The weight factors corresponding to the first characterization values ​​of the environmental facilities and the weight factors corresponding to the second characterization values ​​of the environmental facilities are both numbers between 0 and 1. In this embodiment, the weight factor corresponding to the first characterization value of the environmental facilities is 0.3, and the weight factor corresponding to the second characterization value of the environmental facilities is 0.7.

[0077] Table 1 Different first characterization values ​​and second characterization values ​​of environmental facilities in a parking lot operation sub-area and their corresponding environmental facility characterization values

[0078] The first characteristic value of environmental facilities Second Characteristic Value of Environmental Facilities Environmental facility characterization value 1.0 1.0 4.319 1.5 1.0 5.275 1.0 2.0 5.224 1.5 2.0 6.270

[0079] It should be explained that in Table 1, as the different first characterization values ​​of environmental facilities and the second characterization values ​​of environmental facilities in the parking lot operation sub-area increase, the environmental facility characterization value gradually increases. The environmental facility characterization value in the parking lot operation sub-area in Table 1 combines the first characterization value of environmental facilities and the second characterization value of environmental facilities for analysis, lists four different first characterization values ​​of environmental facilities and the second characterization values ​​of environmental facilities, and obtains the environmental facility characterization value in the parking lot operation sub-area through the formula. The numerical values ​​of these environmental facility characterization values ​​provide the influence of different first characterization values ​​of environmental facilities and the second characterization values ​​of environmental facilities on the environmental facility characterization value. The environmental facility characterization value comprehensively considers the first characterization value of environmental facilities and the second characterization value of environmental facilities, and provides data support for the selection of parking routes, thereby improving the overall parking experience and comfort of users.

[0080] It should be noted that analyzing the first characterization value of environmental facilities in each parking lot operation sub-area is helpful to evaluate the parking demand and supply situation in each parking lot operation sub-area, which can more effectively allocate parking lot resources and improve parking lot resource utilization and efficiency.

[0081] It should be noted that analyzing the second characterization value of the environmental facilities in each parking lot operation sub-area helps users choose a more suitable parking location, avoids interference or damage caused by accumulated water when parking, and enables users to use parking facilities more efficiently.

[0082] It should be noted that, in this embodiment, the weight factor corresponding to the preset first characterization value of the environmental facility and the weight factor corresponding to the second characterization value of the environmental facility are obtained from the parking lot operation database.

[0083] In a specific embodiment, through historical data, the relationship between the first characterization value of environmental facilities, the second characterization value of environmental facilities and the characterization value of environmental facilities in each parking lot operation sub-area is fitted to obtain a fitting curve, and the weight factor corresponding to the first characterization value of environmental facilities and the weight factor corresponding to the second characterization value of environmental facilities are determined according to the fitting curve. The real-time first characterization value of environmental facilities and the second characterization value of environmental facilities in each parking lot operation sub-area are substituted into the fitting curve to obtain the corresponding weight factors.

[0084] It should be explained that, in this embodiment, analyzing the first characterization value and the second characterization value of environmental facilities in each parking lot operation sub-area helps to evaluate the overall environmental quality and facility conditions in the parking lot operation sub-area. The analysis method of this embodiment, the first characterization value and the second characterization value of environmental facilities in each parking lot operation sub-area jointly affect the screening of recommended parking routes.

[0085] In this implementation scheme, analyzing the first characterization value of environmental facilities in each parking lot operation sub-area helps to improve the utilization rate of parking spaces in the parking lot operation sub-area, and analyzing the second characterization value of environmental facilities in each parking lot operation sub-area helps to avoid possible vehicle damage or inconvenience accidents. The environmental facility characterization values ​​obtained by analysis help users optimize parking routes and improve their overall parking experience and comfort.

[0086] Specifically, the environmental facility characterization value in each parking lot operation sub-area is a numerical quantification result obtained by analyzing the environmental facilities in the parking lot operation area, and is used to comprehensively quantify the impact of the parking lot environmental facilities on the parking route of the vehicle.

[0087] Specifically, the screening analysis obtains the recommended parking route results for each vehicle. The specific analysis process is: based on the parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area, a comprehensive analysis is performed to obtain the parking route index value in each parking lot operation sub-area for each vehicle.

[0088] The parking route index value in each parking lot operation sub-area of ​​each vehicle is a numerical quantification result obtained by analyzing the parking lot operation area and the historical parking record data of each vehicle, and is used to quantify the influence of different factors on the recommended parking route result of the vehicle.

[0089] The parking route index values ​​in each parking lot operation sub-area of ​​each vehicle are sorted from large to small, and the operation sub-area corresponding to the parking route index value in each parking lot operation sub-area of ​​each vehicle ranked first is selected as the recommended parking sub-area, and the parking route of the recommended parking sub-area is obtained. The recommended parking route result of each vehicle is imported into the parking space guidance screen terminal for output display.

[0090] In this implementation scheme, the parking route index values ​​in each parking lot operation sub-area of ​​each vehicle are analyzed to quantify the influence of different factors on the parking route selection of each vehicle. According to the historical parking behavior of each vehicle and the parking lot environment and facilities, personalized parking suggestions and recommended parking lot operation sub-areas can be provided to users, thereby reducing the user's search time in the parking lot, improving the user's parking efficiency, and enhancing the convenience and comfort of parking.

[0091] Specifically, the parking behavior characterization value of each vehicle is analyzed under the following conditions:

[0092]

[0093] In the formula, δ i represents the parking behavior characterization value of the i-th vehicle, ε i→j represents the cumulative parking time of the i-th vehicle in the j-th parking lot operation sub-area, Δε represents the set reference parking time, μ1 represents the impact factor corresponding to the set parking time, and ρ i→j represents the cumulative number of parking times of the i-th vehicle in the j-th parking lot operation sub-area, Δρ represents the set reference parking times, μ2 represents the impact factor corresponding to the set parking times, i represents the number of each vehicle, i=1,2,3,…n, n represents the total number of vehicles, j represents the number of each parking lot operation sub-area, j=1,2,3,…m, m represents the total number of parking lot operation sub-areas.

[0094] It should be explained that the cumulative parking time of each vehicle in each parking lot operation sub-area refers to the total parking time of each vehicle in each parking lot operation sub-area, which is obtained from the parking lot operation database. For example, assuming that a vehicle is parked 3 times in a parking lot operation sub-area, and the 3 parking times are 2.0h, 2.5h and 1.5h respectively, then the cumulative parking time of the vehicle in the parking lot operation sub-area is 2.0h+2.5h+1.5h=6h.

[0095] It should be noted that, in this embodiment, the reference parking time is obtained from the parking lot operation database. In a specific embodiment, the reference parking time is usually obtained by statistically analyzing historical data. The specific steps are to calculate the cumulative parking time of each vehicle in each parking lot operation sub-area in history, and calculate the average value of these data to obtain the reference parking time. For example, assuming that the average value of the cumulative parking time of a certain vehicle in a certain parking lot operation sub-area in the historical data is 10 hours, according to the statistical results, it can be obtained that the reference parking time of the vehicle in the parking lot operation sub-area is 10 hours.

[0096] It should be explained that the cumulative number of parking times of each vehicle in each parking lot operation sub-area refers to the total number of parking times of each vehicle in each parking lot operation sub-area, which is obtained from the parking lot operation database. For example, it is obtained from the parking lot operation database that the number of parking times of a certain vehicle in a certain parking lot operation sub-area is 5 times.

[0097] It should be noted that, in this embodiment, the reference parking number is obtained from the parking lot operation database. In a specific embodiment, the reference parking number is usually obtained by statistically analyzing historical data. The specific steps are to count the cumulative parking times of each vehicle in each parking lot operation sub-area in history, and calculate the average value of these data to obtain the reference parking number. For example, assuming that the average value of the cumulative parking times of a certain vehicle in a certain parking lot operation sub-area in the historical data is 30, according to the statistical results, it can be obtained that the reference parking number of the vehicle in the parking lot operation sub-area is 30.

[0098] It should be noted that, in this embodiment, the impact factor corresponding to the preset parking duration and the impact factor corresponding to the number of parking times are obtained from the parking lot operation database.

[0099] In a specific embodiment, through historical data, the relationship between the cumulative parking time, the cumulative number of parking times and the parking behavior characterization value of each vehicle in each parking lot operation sub-area is fitted to obtain a fitting curve, and the influencing factor corresponding to the parking time and the influencing factor corresponding to the parking number are determined according to the fitting curve, and the real-time cumulative parking time and cumulative number of parking times of each vehicle in each parking lot operation sub-area are substituted into the fitting curve to obtain the corresponding influencing factor.

[0100] It should be noted that the impact factor corresponding to the parking duration and the impact factor corresponding to the number of parking times are both numbers between 0 and 1.

[0101] It should be explained that in this embodiment, the cumulative parking time of each vehicle in each parking lot operation sub-area and the cumulative number of parking times of each vehicle in each parking lot operation sub-area are analyzed, which helps to improve personalized recommended routes for users. According to the analysis method of this embodiment, the longer the cumulative parking time of each vehicle in each parking lot operation sub-area and the more the cumulative number of parking times of each vehicle in each parking lot operation sub-area, the more accurately the parking needs of users can be analyzed, and the allocation of parking spaces and resource utilization in each parking lot operation sub-area can be optimized.

[0102] In this implementation scheme, analyzing the cumulative parking time of each vehicle in each parking lot operation sub-area can more effectively select a parking area that suits the user's needs. Analyzing the cumulative parking times of each vehicle in each parking lot operation sub-area can help improve the user's parking efficiency and reduce the time spent looking for parking spaces. Analyzing the parking behavior characterization value of each vehicle can help more accurately select a parking route that suits the user's parking habits.

[0103] Specifically, the parking route index value of each vehicle in each parking lot operation sub-area is analyzed under the following conditions:

[0104]

[0105] In the formula, α i→j represents the parking route index of the i-th vehicle in the j-th parking lot operation sub-area, δ i represents the parking behavior characterization value of the i-th vehicle, θ1 represents the weight factor corresponding to the set parking behavior characterization value, γ j represents the environmental facility characterization value in the jth parking lot operation sub-area, θ2 represents the weight factor corresponding to the set environmental facility characterization value, e represents a natural constant, i represents the number of each vehicle, i = 1, 2, 3, ... n, n represents the total number of vehicles, j represents the number of each parking lot operation sub-area, j = 1, 2, 3, ... m, m represents the total number of parking lot operation sub-areas.

[0106] It needs to be explained that Figure 3 As shown, Figure 3is an example image of parking route index values, wherein the x-axis represents the environmental facility characterization value in each parking lot operation sub-area, and the y-axis represents the parking route index value in each parking lot operation sub-area of ​​a certain vehicle. In this embodiment, the weight factor corresponding to the parking behavior characterization value is 0.4, and the weight factor corresponding to the environmental facility characterization value is 0.6. Three different groups of example parameters are defined in the figure, corresponding to different situations of the three curves, respectively represented by solid lines, dashed lines and dotted lines, and the corresponding curve labels are a, b, and c, respectively. When the parking behavior characterization value of the vehicle is 1, the functional relationship image between the environmental facility characterization value in each parking lot operation sub-area and the parking route index value in each parking lot operation sub-area of ​​the vehicle is shown as curve a. When the parking behavior characterization value of the vehicle is 2, the environmental facility characterization value in each parking lot operation sub-area is 0.6. The functional relationship between the value and the parking route index value in each parking lot operation sub-area of ​​the vehicle is shown as curve b. When the parking behavior characterization value of the vehicle is 3, the functional relationship between the environmental facility characterization value in each parking lot operation sub-area and the parking route index value in each parking lot operation sub-area of ​​the vehicle is shown as curve c. The parking route index value in each parking lot operation sub-area of ​​the vehicle increases with the increase of the environmental facility characterization value in each parking lot operation sub-area, and when the parking behavior characterization value of the vehicle increases, the parking route index value in each parking lot operation sub-area of ​​the vehicle increases accordingly. The parking route index value in each parking lot operation sub-area of ​​the vehicle can be quickly and accurately obtained through the curve, which solves the problem of inaccurate parking route evaluation in the prior art and can reduce the time required for users to park.

[0107] It should be noted that analyzing the parking behavior representation value of each vehicle can help users find the most suitable parking space more quickly, provide personalized recommendations, and reduce the time spent looking for parking spaces. It can also optimize parking routes based on the parking behavior of vehicles, enhance user satisfaction and parking experience, and improve the overall utilization and efficiency of parking lots.

[0108] It should be noted that analyzing the environmental facility characterization values ​​in each parking lot operation sub-area can reduce users' parking time and congestion inside the parking lot. Users can find suitable parking spaces more easily, improve parking efficiency, and help reduce traffic pressure inside the parking lot.

[0109] It should be noted that, in this embodiment, the weight factors corresponding to the preset parking behavior characterization values ​​and the weight factors corresponding to the environmental facility characterization values ​​are obtained from the parking lot operation database.

[0110] In a specific embodiment, through historical data, the relationship between the parking behavior characterization value of each vehicle, the environmental facility characterization value in each parking lot operation sub-area and the parking route index value in each parking lot operation sub-area of ​​each vehicle is fitted to obtain a fitting curve, and the weight factor corresponding to the parking behavior characterization value and the weight factor corresponding to the environmental facility characterization value are determined according to the fitting curve. The real-time parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area are substituted into the fitting curve to obtain the corresponding weight factor.

[0111] It should be noted that the weight factor corresponding to the parking behavior characterization value and the weight factor corresponding to the environmental facility characterization value are both numbers between 0 and 1.

[0112] It should be explained that, in this embodiment, analyzing the parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area helps to customize the optimal parking route for each vehicle. The analysis method of this embodiment, the parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area jointly affect the personalized parking route recommendation of the vehicle.

[0113] In this implementation scheme, analyzing the parking behavior characterization value of each vehicle helps to recommend the most suitable parking route based on the user's parking habits, analyzing the environmental facility characterization value in each parking lot operation sub-area helps to recommend safer, cleaner or more convenient parking lot operation sub-areas to users, and analyzing the parking route index value in each parking lot operation sub-area for each vehicle helps users avoid congestion, waterlogging and other problems and choose more suitable parking areas and routes.

[0114] It should be noted that a parking lot management method based on behavior recognition also includes a parking lot operation database, which is used to store the cumulative parking time, cumulative parking times, reference distance, reference number of vacant parking spaces, reference traffic flow, reference average water accumulation depth, reference parking time, reference parking times, influencing factors corresponding to distance, influencing factors corresponding to the number of vacant parking spaces, influencing factors corresponding to traffic flow, influencing factors corresponding to average water accumulation depth, weight factors corresponding to the first characterization value of environmental facilities, weight factors corresponding to the second characterization value of environmental facilities, influencing factors corresponding to parking time, influencing factors corresponding to the number of parking times, weight factors corresponding to parking behavior characterization values, and weight factors corresponding to environmental facility characterization values.

[0115] The second aspect of the present invention provides a parking lot management system based on behavior recognition, including: a vehicle parking behavior analysis module, which is used for the parking space publishing terminal to send the characteristic data of each vehicle, and analyze the historical parking record data of each vehicle to obtain the parking behavior characterization value of each vehicle.

[0116] The parking lot environment facility analysis module is used to monitor and obtain facility data within the parking lot operation area, analyze the facility data within the parking lot operation area, and obtain the environmental facility representation value in each parking lot operation sub-area in combination with the current vehicle position.

[0117] The recommended parking route analysis module is used to obtain the recommended parking route results for each vehicle based on the parking behavior representation value of each vehicle and the environmental facility representation value in each parking lot operation sub-area, and import the recommended parking route results for each vehicle into the parking space guidance screen terminal for output display.

[0118] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0119] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A parking lot management method based on behavior recognition, characterized in that: include: The parking space publishing terminal sends the characteristic data of each vehicle and analyzes the historical parking record data of each vehicle to obtain the parking behavior representation value of each vehicle; Monitor and obtain facility data within the parking lot operation area, analyze the facility data within the parking lot operation area, and obtain the environmental facility representation value in each parking lot operation sub-area in combination with the current vehicle position; According to the parking behavior characterization value of each vehicle and the environmental facility characterization value in each parking lot operation sub-area, the recommended parking route result of each vehicle is obtained through screening analysis, and the recommended parking route result of each vehicle is imported into the parking space guidance screen terminal for output display.

2. The parking lot management method based on behavior recognition according to claim 1 is characterized by: The historical parking record data of each vehicle includes the cumulative parking duration and the cumulative parking times of each vehicle in each parking lot operation sub-area.

3. The parking lot management method based on behavior recognition according to claim 1 is characterized by: The historical parking record data of each vehicle is analyzed to obtain the parking behavior representation value of each vehicle. The specific process is as follows: The parking lot operation area is divided into each parking lot operation sub-area, each parking lot operation sub-area is analyzed, and the cumulative parking time and cumulative parking times of each vehicle in each parking lot operation sub-area are counted, and the parking behavior representation value of each vehicle is obtained after processing.

4. The parking lot management method based on behavior recognition according to claim 3 is characterized by: The parking behavior characterization value of each vehicle is a numerical quantification result obtained by analyzing the historical parking record data of each vehicle, and is used to comprehensively quantify the influence of the historical parking behavior of each vehicle on the optimal parking operation sub-area of ​​the vehicle.

5. The parking lot management method based on behavior recognition according to claim 1 is characterized by: The facility data in the parking lot operation area is analyzed, and combined with the current vehicle position, the environmental facility characterization value of each parking lot operation sub-area is obtained. The specific analysis process is as follows: Obtain the layout information of the parking lot operation area, monitor the position coordinates of each vehicle in the parking lot operation area, and obtain the distance between each parking lot operation sub-area and the current position of each vehicle; According to the distance between each parking lot operation sub-area and the current position of each vehicle, the number of vacant parking spaces in each parking lot operation sub-area is counted, and the first representation value of the environmental facilities in each parking lot operation sub-area is obtained through processing; Monitor the vehicle in and out conditions in each parking lot operation sub-area, and obtain the traffic flow in each parking lot operation sub-area by statistics; Monitor and collect data on the depth of water in different locations of each vacant parking space in each parking lot operation sub-area, and obtain the average depth of water in each vacant parking space in each parking lot operation sub-area after processing; According to the traffic flow in each parking lot operation sub-area and the average water depth of each vacant parking space in each parking lot operation sub-area, the second characterization value of the environmental facilities in each parking lot operation sub-area is analyzed and obtained; According to the first characterization value of the environmental facilities in each parking lot operation sub-area and the second characterization value of the environmental facilities in each parking lot operation sub-area, the environmental facility characterization value in each parking lot operation sub-area is obtained through weighted analysis.

6. The parking lot management method based on behavior recognition according to claim 5 is characterized by: The environmental facility characterization value in each parking lot operation sub-area is a numerical quantification result obtained by analyzing the environmental facilities in the parking lot operation area, and is used to comprehensively quantify the impact of the parking lot environmental facilities on the parking route of the vehicle.

7. The parking lot management method based on behavior recognition according to claim 1 is characterized by: The screening analysis obtains the recommended parking route results for each vehicle, and the specific analysis process is as follows: According to the parking behavior representation value of each vehicle and the environmental facility representation value in each parking lot operation sub-area, a comprehensive analysis is performed to obtain the parking route index value in each parking lot operation sub-area of ​​each vehicle; The parking route index value in each parking lot operation sub-area of ​​each vehicle is a numerical quantification result obtained by analyzing the parking lot operation area and the historical parking record data of each vehicle, and is used to quantify the influence of different factors on the recommended parking route result of the vehicle; The parking route index values ​​in each parking lot operation sub-area of ​​each vehicle are sorted from large to small, and the operation sub-area corresponding to the parking route index value in each parking lot operation sub-area of ​​each vehicle ranked first is selected as the recommended parking sub-area, and the parking route of the recommended parking sub-area is obtained. The recommended parking route result of each vehicle is imported into the parking space guidance screen terminal for output display.

8. The parking lot management method based on behavior recognition according to claim 4 is characterized by: The parking behavior characterization value of each vehicle is specifically analyzed under the following conditions: In the formula, δ i represents the parking behavior characterization value of the i-th vehicle, ε i→j represents the cumulative parking time of the i-th vehicle in the j-th parking lot operation sub-area, Δε represents the set reference parking time, μ1 represents the impact factor corresponding to the set parking time, and ρ i→j represents the cumulative number of parking times of the i-th vehicle in the j-th parking lot operation sub-area, Δρ represents the set reference parking times, μ2 represents the impact factor corresponding to the set parking times, i represents the number of each vehicle, i=1,2,3,…n, n represents the total number of vehicles, j represents the number of each parking lot operation sub-area, j=1,2,3,…m, m represents the total number of parking lot operation sub-areas.

9. The parking lot management method based on behavior recognition according to claim 7 is characterized by: The specific analysis conditions of the parking route index value of each vehicle in each parking lot operation sub-area are as follows: In the formula, α i→j represents the parking route index of the i-th vehicle in the j-th parking lot operation sub-area, δ i represents the parking behavior characterization value of the i-th vehicle, θ1 represents the weight factor corresponding to the set parking behavior characterization value, γ j represents the environmental facility characterization value in the jth parking lot operation sub-area, θ2 represents the weight factor corresponding to the set environmental facility characterization value, e represents a natural constant, i represents the number of each vehicle, i = 1, 2, 3, ... n, n represents the total number of vehicles, j represents the number of each parking lot operation sub-area, j = 1, 2, 3, ... m, m represents the total number of parking lot operation sub-areas.

10. A parking lot management system based on behavior recognition, characterized in that: include: The vehicle parking behavior analysis module is used for the parking space publishing terminal to send the characteristic data of each vehicle, and analyze the historical parking record data of each vehicle to obtain the parking behavior representation value of each vehicle; The parking lot environment facility analysis module is used to monitor and obtain the facility data within the parking lot operation area, analyze the facility data within the parking lot operation area, and obtain the environmental facility representation value in each parking lot operation sub-area in combination with the current vehicle position; The recommended parking route analysis module is used to obtain the recommended parking route results for each vehicle based on the parking behavior representation value of each vehicle and the environmental facility representation value in each parking lot operation sub-area, and import the recommended parking route results for each vehicle into the parking space guidance screen terminal for output display.

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