A parking space prediction management system based on big data

Abstract

The present invention relates to the field of parking space prediction technology, specifically to a parking lot parking space prediction management system based on big data, the system comprising: a data acquisition and processing module, an environmental data analysis module, a historical data analysis module, a parking lot management module and a parking lot database. The present invention provides a parking lot parking space prediction management system based on big data, comprehensively analyzes the parking space vacancy probability of each target area of ​​the parking lot, and implements different management for areas with high parking space vacancy probability and areas with low parking space vacancy probability, effectively improving the parking space utilization rate of high vacancy probability areas and low vacancy probability areas of the parking lot, which is conducive to optimizing parking resource allocation, thereby alleviating the problem of parking difficulty, helping to promote staggered sharing of parking space resources, maximizing parking space usage time, reducing resource waste, and optimizing parking lot resource allocation, thereby improving the parking experience of car owners.

Description

Technical Field

[0001] The present invention relates to the technical field of parking space prediction, and in particular to a parking lot parking space prediction management system based on big data. Background Art

[0002] With the rapid development of my country's economy and the increase in my country's per capita income level, the number of cars in cities has increased rapidly, and the demand for parking has continued to increase. In most cities in my country, there is a dilemma of "too many cars and too few parking spaces". Traditional parking lot management methods can no longer meet people's needs.

[0003] For example, the invention patent with announcement number: CN117133144B discloses a parking space prediction method and system for a smart city parking lot based on the Internet of Things, which is used to solve the problem that the existing smart parking management system based on the Internet of Things cannot predict the parking spaces in the pre-selected parking lot and cannot intelligently reselect the congested parking lot, resulting in the pre-selected parking spaces being full and congested at the parking lot entrance, causing traffic jams and the problem that the user's parking efficiency cannot be guaranteed; the parking space prediction method of the parking lot can predict the parking spaces in the parking lot, and the predicted situation of the parking lot can be checked anytime and anywhere, so as to make timely scheduling and management, and intelligently reselect the congested parking lot, thereby improving the user's parking efficiency, reducing the difficulty of user parking, and reducing the probability of traffic jams, making an outstanding contribution to smart city transportation.

[0004] For example, the invention patent with announcement number: CN115775467B discloses an intelligent management system and method for parking lot services based on the Internet of Things, which relates to the field of parking lot service management technology. The method includes collecting vehicle data information, marking vehicles that exceed the length threshold and width threshold of the vehicle; constructing a parking time prediction model, calculating the predicted value of the time it takes for the marked vehicle to reach each free parking space; constructing a parked vehicle judgment model, judging the type of parked vehicles in the adjacent parking spaces of each free parking space; constructing an optimal parking space recommendation model, taking the free parking space with the highest parking space recommendation score as the initial optimal parking space; real-time monitoring of the entry status of the owners of each entrance of the parking lot, judging whether the total time predicted to be consumed by the owner to drive his vehicle out of the parking space exceeds the time it takes for the marked vehicle to reach the parking space where the owner's vehicle is located; if not, calculating the recommendation score of the parking space where the owner's vehicle is located and its adjacent parking spaces, and outputting the parking space with a higher score as the best parking space to the user port.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it was found that the above technology has at least the following technical problems: the traditional parking lot management method mainly predicts the availability of parking spaces through historical data analysis and recommends the best parking spaces. However, recommending a single parking space through historical data analysis cannot adapt to the flexible changes in different time periods and different parking needs. The accuracy of parking space prediction is limited, making it difficult to dynamically manage parking spaces. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a parking lot space prediction management system based on big data, 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: The present invention provides a parking lot space prediction management system based on big data, including: a data acquisition and processing module for collecting and integrating parking lot data, including parking lot environment basic data and parking lot historical data.

[0008] The environmental data analysis module is used to divide the parking lot into areas according to the basic data of the parking lot environment, mark them into target areas, extract the parking lot environment characteristic data from the basic data of the parking lot environment, and comprehensively analyze the parking lot environment characteristic impact index.

[0009] The historical data analysis module is used to comprehensively analyze the parking space utilization evaluation index of each target area based on the historical data of the parking lot.

[0010] The parking lot management module is used to obtain the parking space vacancy probability evaluation index of each target area based on the parking lot environment characteristic impact index and the parking space utilization evaluation index of each target area through comprehensive analysis, evaluate the vacancy situation of parking spaces in the parking lot, and manage the parking lot according to the evaluation results.

[0011] As a further method, the parking lot is divided into areas according to the basic data of the parking lot environment. The specific process is: obtaining the locations of each entrance and exit of the parking lot from the basic data of the parking lot environment, dividing the parking lot into areas according to the locations of each entrance and exit and the set distance parameters, and marking the divided areas as target areas.

[0012] As a further method, the comprehensive analysis obtains the parking lot environment characteristic impact index. The specific analysis process is: deploy a number of historical time monitoring points, and the parking lot environment characteristic data, including the vehicle flow and the number of commercial facilities around the parking lot at each historical time monitoring point, extract the critical vehicle flow and the critical number of commercial facilities from the parking lot database, and conduct a comprehensive analysis to obtain the parking lot environment characteristic impact index.

[0013] As a further method, the comprehensive analysis obtains the parking space utilization evaluation index of each target area. The specific analysis process is: the parking lot historical data, including the effective idle times and the duration of each effective idle interval of each parking space in each target area within a preset historical period, and the preset historical period duration are obtained at the same time, and the parking space utilization evaluation index of each target area is obtained through comprehensive analysis.

[0014] As a further method, the comprehensive analysis obtains a parking space vacancy probability evaluation index for each target area. The specific analysis process is: based on the parking lot environment characteristic impact index and the parking space utilization evaluation index of each target area, a comprehensive analysis is performed to obtain a parking space vacancy probability evaluation index for each target area. The parking space vacancy probability evaluation index for each target area is used to quantitatively evaluate the vacancy probability of parking spaces in the target area of ​​the parking lot.

[0015] As a further method, the vacancy situation of parking spaces in the parking lot is evaluated, and the parking lot is managed according to the evaluation results. The specific process is: the parking space vacancy probability evaluation indicators of each target area are sorted in descending order, and the sequence positions corresponding to the first quartile and the third quartile are calculated according to the total number of target areas. The target areas before the sequence position corresponding to the first quartile are marked as high vacancy probability areas of each parking lot, and the target areas after the sequence position corresponding to the third quartile are marked as low vacancy probability areas of each parking lot, and the high vacancy probability areas and low vacancy probability areas of the parking lot are managed respectively.

[0016] As a further method, the parking lot environmental characteristics impact index is a quantitative evaluation data obtained by comprehensively analyzing the traffic volume and the number of commercial facilities around the parking lot at each historical monitoring point. It is used to quantitatively evaluate the impact of the parking lot surrounding environment on the parking lot space utilization rate, and provide a data basis for evaluating the probability of vacant parking spaces in the parking lot.

[0017] As a further method, the parking space utilization evaluation index of each target area is a quantitative evaluation data obtained by comprehensively analyzing the number of effective idle times and the duration of each idle interval of each parking space in each target area within a preset historical period. It is used to quantitatively evaluate the utilization rate of parking spaces in each target area of ​​the parking lot, and provide a data basis for evaluating the probability of idle parking spaces in the parking lot.

[0018] As a further method, the parking lot environment characteristic impact index, the specific numerical expression is:

[0019]

[0020] Where τH represents the parking lot environmental characteristics impact index, e represents the natural constant, t represents the number of each historical time monitoring point, t=1,2,3,...,h, h represents the total number of historical time monitoring points, Ct represents the traffic flow around the parking lot at the t-th historical time monitoring point, P t represents the number of commercial facilities around the parking lot at the t-th historical monitoring point, ΔC represents the critical vehicle flow, ΔP represents the critical number of commercial facilities, δ1 represents the environmental characteristic influencing factor corresponding to the set vehicle flow, and δ2 represents the environmental characteristic influencing factor corresponding to the set number of commercial facilities.

[0021] As a further method, the parking space vacancy probability evaluation index of each target area is specifically expressed as:

[0022] G n =coth(L n *ρ 1n +τH*ρ2);

[0023] In the formula, G n represents the parking space vacancy probability evaluation index of the nth target area, L n represents the parking space utilization evaluation index of the nth target area, τH represents the parking lot environment characteristic impact index, ρ 1n represents the parking space vacancy probability assessment influence factor corresponding to the parking space utilization rate assessment index of the set nth target area, and ρ2 represents the parking space vacancy probability assessment influence factor corresponding to the set parking lot environment characteristic impact index.

[0024] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0025] (1) The present invention provides a parking space prediction management system based on big data, which comprehensively analyzes the parking space vacancy probability of each target area of ​​the parking lot, and implements different management for areas with high parking space vacancy probability and areas with low parking space vacancy probability, respectively, thereby effectively improving the parking space utilization rate in areas with high and low parking space vacancy probability, which is beneficial to optimizing parking resource allocation and alleviating parking difficulties, thereby improving the parking experience of car owners.

[0026] (2) The present invention provides a basis for improving the utilization rate of parking spaces by evaluating the impact of the surrounding environmental characteristics of the parking lot on the probability of vacant parking spaces. By understanding the surrounding environmental characteristics, it is helpful to adjust the parking space allocation strategy according to the demand differences in different areas, thereby improving the utilization efficiency of parking spaces and reducing the probability of congestion. The analysis of the surrounding environment is also helpful to promote smart parking solutions and improve management efficiency and user experience.

[0027] (3) By analyzing the parking space utilization rate of each target area of ​​the parking lot, the present invention helps to promote the staggered sharing of parking space resources, maximize the parking space usage time, reduce the waste of resources, and optimize the allocation of parking lot resources. By real-time monitoring of the parking space utilization rate of each target area, it helps to quickly respond to changes in parking space demand, reduce invalid idle parking spaces, and improve the overall operating efficiency of the parking lot. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0029] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0030] Figure 2 The figure is a schematic diagram of the functional relationship between the parking space utilization evaluation index and the parking space vacancy probability evaluation index of each target area involved in the embodiment of the present invention. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0032] Reference Figure 1 As shown, the present invention provides a parking lot space prediction management system based on big data, including: a data acquisition and processing module for collecting and integrating parking lot data, including parking lot environment basic data and parking lot historical data.

[0033] Specifically, the basic data of the parking lot environment includes the location of each parking lot entrance and exit, the traffic volume around the parking lot, and the number of commercial facilities. The location of each parking lot entrance and exit is obtained by extracting and collecting specific information on the parking lot map drawn by drones equipped with high-definition cameras, the traffic volume around the parking lot is obtained by retrieving historical monitoring data from surrounding traffic monitoring equipment, and the number of commercial facilities is obtained by analyzing the specific information on the distribution of commercial facilities obtained on the network map of monitoring points at each historical time. The historical data of the parking lot includes the number of effective idle times of each parking space in each target area and the duration of each idle interval.

[0034] The environmental data analysis module is used to divide the parking lot into areas according to the basic data of the parking lot environment, mark them into target areas, extract the parking lot environment characteristic data from the basic data of the parking lot environment, and comprehensively analyze the parking lot environment characteristic impact index.

[0035] Specifically, the parking lot is divided into areas according to the basic data of the parking lot environment. The specific process is: the locations of the entrances and exits of the parking lot are obtained from the basic data of the parking lot environment, the parking lot is divided into areas according to the locations of the entrances and exits and the set distance parameters, and the divided areas are marked as target areas.

[0036] In a specific embodiment, the main entrance and exit locations of the parking lot are clearly defined, and reasonable distance parameters are set, such as a convenient entry and exit distance range of 50 to 100 meters. Then, the actual distances from different areas in the parking lot to each entrance and exit are evaluated through measurement or map tools to determine the convenience of different areas and entrances and exits. Generally speaking, the areas that are closer to the entrances and exits and more convenient to enter and exit are more frequently used and are suitable for temporary parking or vehicles with rapid turnover, while areas with relatively inconvenient entry and exit are suitable for vehicles that are parked for a long time or do not need to pick up the car frequently. In the division process, attention should also be paid to the connectivity and traffic organization between the areas to ensure that vehicles can enter and exit smoothly and avoid congestion and conflict. At the same time, according to the size, shape and usage requirements of the parking lot, it can be further subdivided into multiple sub-areas to meet the parking needs of different car owners. Through reasonable area division, the space utilization of the parking lot can be optimized and the parking efficiency and convenience can be improved.

[0037] Furthermore, a comprehensive analysis is performed to obtain the parking lot environmental characteristic impact index. The specific analysis process is as follows: a number of historical time monitoring points are deployed, and the parking lot environmental characteristic data, including the vehicle flow and the number of commercial facilities around the parking lot at each historical time monitoring point, are extracted from the parking lot database to obtain the critical vehicle flow and the critical number of commercial facilities, and the parking lot environmental characteristic impact index is obtained through comprehensive analysis.

[0038] It should be explained that the parking lot environmental characteristics impact index is a quantitative assessment data obtained through a comprehensive analysis of the traffic volume and the number of commercial facilities around the parking lot at each historical monitoring point. It is used to quantitatively assess the impact of the parking lot surrounding environment on the parking lot space utilization rate and provide a data basis for assessing the probability of vacant parking spaces in the parking lot.

[0039] In a specific embodiment, the parking lot environment characteristic impact index is expressed as follows:

[0040]

[0041] Where τH represents the parking lot environmental characteristics impact index, e represents the natural constant, t represents the number of each historical time monitoring point, t=1,2,3,...,h, h represents the total number of historical time monitoring points, C t represents the traffic flow around the parking lot at the t-th historical time monitoring point, P t represents the number of commercial facilities around the parking lot at the t-th historical monitoring point, ΔC represents the critical vehicle flow, ΔP represents the critical number of commercial facilities, δ1 represents the environmental characteristic influencing factor corresponding to the set vehicle flow, and δ2 represents the environmental characteristic influencing factor corresponding to the set number of commercial facilities.

[0042] Table 1 Example of parking lot environmental characteristics impact index data

[0043]

[0044] It should be explained that, in this embodiment, the critical vehicle flow is set to 500 vehicles / hour, the critical number of commercial facilities is set to 10, the environmental characteristic impact factor corresponding to the vehicle flow is set to 0.5, and the environmental characteristic impact factor corresponding to the number of commercial facilities is set to 0.3. The impact factors are all extracted from the parking lot database. For the convenience of calculation, each group of historical time monitoring points is set to 5, and the parking lot environment characteristic impact index value of each historical time monitoring point is the same.

[0045] It should be explained that, as can be seen from Table 1, when the values ​​of other parameters remain unchanged, the greater the traffic volume around the parking lot, the greater the impact index of the parking lot environment characteristics; the greater the number of commercial facilities around the parking lot, the greater the impact index of the parking lot environment characteristics; the two are in a positive proportional relationship.

[0046] It needs to be explained that commercial facilities around parking lots usually provide goods for purchase and some basic services, and are characterized by providing consumers with convenient and diverse choices, as well as cherishing consumers' purchasing experience. Commercial facilities can be divided into urban, suburban and tourist areas according to their location. They include department stores, large wholesale stores, centralized specialty stores, centralized restaurants, shopping centers, etc. The prosperity of business around parking lots can increase the demand for parking spaces and improve the utilization rate of parking lots. For example, parking lots in hot consumption areas such as catering, entertainment, and shopping often reach saturation during peak hours. The increase in commercial activities can also extend the parking demand time from day to night. At the same time, higher traffic volume around parking lots usually means higher consumption potential, which helps business prosperity and further affects the utilization rate of parking spaces in parking lots.

[0047] In order to balance commercial needs and smooth traffic, parking lot entrances and exits and surrounding roads need to be scientifically planned to avoid traffic congestion caused by excessive traffic and ensure convenient entry and exit for customers.

[0048] It should be explained that the value range of the environmental characteristic influencing factors corresponding to the vehicle flow and the environmental characteristic influencing factors corresponding to the number of commercial facilities set in this embodiment is [0, 1]. A mapping table is established between the vehicle flow and the number of commercial facilities and the corresponding environmental characteristic influencing factors. According to the real-time vehicle flow and the number of commercial facilities, the environmental characteristic influencing factors corresponding to the real-time vehicle flow and the environmental characteristic influencing factors corresponding to the number of commercial facilities are obtained through the mapping table.

[0049] It should be explained that in this embodiment, the surrounding traffic flow directly affects the use of the parking lot. A large traffic flow usually means more parking demand, which may lead to an increase in parking space utilization. For example, parking lots located near the city center or commercial district tend to have a higher parking space utilization rate due to frequent surrounding work, shopping, dining and other activities. On the contrary, parking lot utilization rates may be relatively low in suburban areas or areas with less traffic. The number and type of commercial facilities will also affect the parking space utilization rate of the parking lot. Commercial facilities usually attract different types of vehicles, such as shopping carts, delivery trucks, etc., which may increase the frequency of parking lot use. In addition, the prosperity and flow of people in the commercial area will also affect the parking demand. For example, a parking lot near a large shopping mall may require more parking spaces to meet demand due to a large passenger flow. Comprehensive analysis of the surrounding traffic flow and the number of commercial facilities in the parking lot can provide a comprehensive assessment of the environmental characteristics of the parking lot, thereby formulating a strategy to improve the utilization rate of parking spaces. For example, by analyzing the data, managers can decide whether to add parking spaces, adjust opening hours, implement dynamic pricing strategies, etc. to adapt to parking space needs in different time periods. At the same time, the pressure on parking lots can be alleviated to a certain extent by optimizing surrounding traffic and public transportation services and reducing dependence on private cars.

[0050] The historical data analysis module is used to comprehensively analyze the parking space utilization evaluation index of each target area based on the historical data of the parking lot.

[0051] Specifically, a parking space utilization evaluation index for each target area is obtained through comprehensive analysis. The specific analysis process is as follows: the parking lot historical data includes the number of effective idle times and the duration of each effective idle interval for each parking space in each target area within a preset historical period, and the preset historical period duration is obtained at the same time, and a parking space utilization evaluation index for each target area is obtained through comprehensive analysis.

[0052] Furthermore, the number of idle times and the duration of each idle interval of each parking space in each target area within a preset historical period are extracted from the parking lot historical data, and the parking space idle interval time threshold is extracted from the parking lot database. The duration of each idle interval of each parking space is compared with the parking space idle interval time threshold. If the duration of an idle interval is greater than the parking space idle interval time threshold, the idle time is marked as a valid idle time, and the idle interval time is marked as a valid idle time.

[0053] It should be explained that the parking space utilization evaluation index of each target area is a quantitative evaluation data obtained by comprehensively analyzing the number of effective idle times and the duration of each idle interval of each parking space in each target area within a preset historical period. It is used to quantitatively evaluate the utilization rate of parking spaces in each target area of ​​the parking lot, and provide a data basis for evaluating the probability of idle parking spaces in the parking lot.

[0054] In a specific embodiment, the numerical expression of the parking space utilization evaluation index of each target area is:

[0055]

[0056] Where Ln represents the parking space utilization evaluation index of the nth target area, n represents the number of each target area, n = 1, 2, 3, ..., m, m represents the total number of target areas, i represents the number of each parking space, i = 1, 2, 3, ..., s, s represents the total number of parking spaces, T ni Indicates the number of valid idle times of the i-th parking space in the n-th target area, represents the critical effective idle times, r represents the number of each effective idle times, r = 1, 2, 3, ..., g, g represents the total number of effective idle times, X nir represents the length of the rth effective idle interval of the ith parking space in the nth target area, D represents the length of the preset historical cycle, ε1 represents the parking space utilization evaluation influencing factor corresponding to the preset effective idle times, and ε2 represents the parking space utilization evaluation influencing factor corresponding to the preset effective idle interval length.

[0057] It should be explained that, in this embodiment, when the number of effective idle times of the i-th parking space in the n-th target area is greater, the parking space utilization evaluation index of the n-th target area is smaller; when the length of the r-th effective idle interval of the i-th parking space in the n-th target area is longer, the parking space utilization evaluation index of the n-th target area is also smaller, and both are in inverse proportional relationship.

[0058] It should be explained that, in this embodiment, the parking space utilization evaluation influence factor corresponding to the preset effective idle number of times and the parking space utilization evaluation influence factor corresponding to the effective idle interval duration are both extracted from the parking lot database, and the value range of the parking space utilization evaluation influence factor corresponding to the effective idle number of times and the parking space utilization evaluation influence factor corresponding to the effective idle interval duration is [0, 1]. A mapping table is established between the effective idle number of times and the effective idle interval duration and the corresponding parking space utilization evaluation influence factors respectively. According to the real-time effective idle number of times and the effective idle interval duration, the parking space utilization evaluation influence factor corresponding to the real-time effective idle number of times and the parking space utilization evaluation influence factor corresponding to the effective idle interval duration are obtained through the mapping table.

[0059] It should be explained that in this embodiment, the number of effective idle times refers to the number of idle parking spaces in the parking lot during the observation time. This indicator reflects the dynamic idle state of the parking lot. The more times, the more idle opportunities the parking lot has during the observation period, and the parking space utilization rate may be low. By counting the number of effective idle times, managers can understand which time periods of the day the parking lot has idle parking spaces, so as to adjust management strategies, such as improving the utilization rate of parking spaces by sharing parking at different times. The effective idle interval duration refers to the effective idle duration. This indicator can reflect the busyness of the parking lot. A short interval duration means that the idle parking spaces are quickly occupied, indicating that the parking lot utilization rate is high; otherwise, it means that the parking space utilization rate is not high. For example, if a parking lot has an extremely short idle interval duration during peak hours, it means that the parking space demand is large and the utilization rate is high. It may be necessary to take measures such as increasing parking spaces and adjusting opening hours to cope with the demand. By analyzing the number of effective idle times and the effective idle duration, the parking lot manager can understand the idleness of the parking lot, and then set the appropriate historical cycle duration based on these data. In this way, when the parking space idle time exceeds the preset historical cycle duration, measures can be taken to improve the utilization rate of the parking space, thereby improving the overall operational efficiency of the parking lot. Combining the two indicators of effective idle times and effective idle interval duration can more comprehensively evaluate and optimize parking lot operations. If the number of effective idle times is high and the interval duration is short, it may indicate that the parking lot is overcrowded during certain periods and needs to increase the supply of parking spaces or optimize the allocation of usage time; if the number of times is low and the interval duration is long, it may mean that the parking lot utilization rate is low during certain periods and the utilization rate of parking spaces during this period can be improved through staggered sharing and other methods. By improving the layout and sign system of the parking lot, the time spent looking for parking spaces can be reduced, thereby improving the parking experience and parking space utilization rate.

[0060] The parking lot management module is used to obtain the parking space vacancy probability evaluation index of each target area based on the parking lot environment characteristic impact index and the parking space utilization evaluation index of each target area through comprehensive analysis, evaluate the vacancy situation of parking spaces in the parking lot, and manage the parking lot according to the evaluation results.

[0061] Specifically, a comprehensive analysis is performed to obtain a parking space vacancy probability evaluation index for each target area. The specific analysis process is as follows: based on the parking lot environment characteristic impact index and the parking space utilization rate evaluation index for each target area, a comprehensive analysis is performed to obtain a parking space vacancy probability evaluation index for each target area. The parking space vacancy probability evaluation index for each target area is used to quantitatively evaluate the vacancy probability of parking spaces in the target area of ​​the parking lot.

[0062] In a specific embodiment, the parking space vacancy probability evaluation index of each target area is specifically expressed as:

[0063] G n =coth(L n *ρ 1n +τH*ρ2);

[0064] In the formula, G n represents the parking space vacancy probability evaluation index of the nth target area, L n represents the parking space utilization evaluation index of the nth target area, τH represents the parking lot environment characteristic impact index, ρ 1n represents the parking space vacancy probability assessment influence factor corresponding to the parking space utilization rate assessment index of the set nth target area, and ρ2 represents the parking space vacancy probability assessment influence factor corresponding to the set parking lot environment characteristic impact index.

[0065] It should be explained that the value range of the parking space vacancy probability assessment influence factor corresponding to the parking space utilization evaluation index of each target area set in this embodiment and the parking space vacancy probability assessment influence factor corresponding to the set parking lot environment characteristic influence index is [0, 1]. Both are extracted from the parking lot database. A mapping table is established between the parking space utilization evaluation index and the parking lot environment characteristic influence index of each target area and the corresponding parking space vacancy probability assessment influence factor. According to the real-time parking space utilization evaluation index and the parking lot environment characteristic influence index of each target area, the parking space vacancy probability assessment influence factor corresponding to the real-time parking space utilization evaluation index of each target area and the parking space vacancy probability assessment influence factor corresponding to the parking lot environment characteristic influence index are obtained through the mapping table.

[0066] It needs to be explained that Figure 2 As shown, curve b represents the relationship between the parking space utilization evaluation index and the parking space vacancy probability evaluation index of each target area when the parking lot environment characteristic impact index is 2.2, curve c represents the relationship between the parking space utilization evaluation index and the parking space vacancy probability evaluation index of each target area when the parking lot environment characteristic impact index is 1.8, and curve d represents the relationship between the parking space utilization evaluation index and the parking space vacancy probability evaluation index of each target area when the parking lot environment characteristic impact index is 1.4. Figure 2 It can be obtained that when the parking lot environment characteristics influence index is larger, it means that the impact of parking lot environment characteristics on parking space utilization rate is greater, and the parking space vacancy probability evaluation index of each target area is smaller. As the parking space utilization rate evaluation index of each target area increases, the parking space vacancy probability evaluation index of each target area decreases, and the two are inversely proportional.

[0067] It should be explained that in this embodiment, by analyzing the surrounding traffic flow and the usage pattern of commercial facilities, the demand for parking spaces in a specific period can be predicted, thereby estimating the probability of parking spaces being idle during peak and non-peak periods. The opening hours of commercial facilities, promotional activities, holidays and other factors will affect the demand for parking. Understanding these periodic changes helps to assess the probability of parking spaces being idle during these periods. The availability and convenience of public transportation will affect the use of private cars. In areas with developed public transportation, the probability of parking spaces being idle in parking lots may be higher because more people may choose public transportation rather than driving. At the same time, high parking space utilization means that parking lot resources have been fully explored and utilized, which can help managers identify which time periods and areas have a large demand for parking spaces, thereby adjusting the parking space opening hours or increasing the supply of parking spaces in the corresponding areas. By monitoring the parking space utilization rate in real time, managers can quickly respond to changes in parking space demand, such as increasing open parking spaces during peak demand periods, or making appropriate adjustments during off-peak periods, reducing invalid idle parking spaces, and improving the overall operational efficiency of parking lots. High parking space utilization reduces the time required to find parking spaces, alleviates traffic congestion caused by finding parking spaces, and improves urban traffic flow. Users can quickly and accurately find vacant parking spaces, saving time and energy in finding parking spaces, and improving parking experience and satisfaction. Data analysis of parking space utilization can promote the staggered sharing of parking space resources, such as encouraging units that work during the day to make parking spaces available to residents at night, and vice versa, to maximize the use time of parking spaces and reduce resource waste. By comprehensively considering the environmental characteristics of parking lots and parking space utilization, the probability of parking spaces being idle can be estimated more accurately, thus providing strong decision support for parking lot management. This analysis can also help predict future parking demand and provide a reference for urban planning and parking lot construction.

[0068] Specifically, the vacancy situation of parking spaces in the parking lot is evaluated, and the parking lot is managed according to the evaluation results. The specific process is: the parking space vacancy probability evaluation indicators of each target area are sorted in descending order, and the sequence positions corresponding to the first quartile and the third quartile are calculated according to the total number of target areas. The target areas before the sequence position corresponding to the first quartile are marked as high vacancy probability areas of each parking lot, and the target areas after the sequence position corresponding to the third quartile are marked as low vacancy probability areas of each parking lot. The high vacancy probability areas and low vacancy probability areas of the parking lot are managed separately.

[0069] Specifically, the positions of the first quartile (Q1) and the third quartile (Q3) are calculated. The position of Q1 is usually determined using the formula (m+1)×0.25, while the position of Q3 is determined using the formula (m+1)×0.75, where m represents the total number of target areas.

[0070] Specifically, for areas with high vacancy probability in parking lots, more car owners can be attracted to park by reducing parking fees in areas with high vacancy probability. This price incentive can effectively improve the utilization rate of parking spaces. Encourage car owners to make reservations for parking spaces with high vacancy probability through mobile applications or websites to ensure parking spaces in advance. This can not only improve the utilization rate of parking spaces, but also reduce the time car owners spend looking for parking spaces. Adjust parking space allocation based on real-time data to allocate parking spaces in areas with high vacancy probability to car owners in need, especially during peak hours. Implement some promotional activities in areas with high vacancy probability, such as first-time parking discounts or continuous parking discounts, to increase the utilization rate of parking spaces. Cooperate with surrounding commercial institutions or residential communities to implement staggered shared parking plans to provide vacant parking spaces to other users during non-peak hours. Improve the quality of facilities in areas with high vacancy probability, such as improving lighting, adding surveillance cameras, and providing better signage, to improve the parking experience of car owners. Inform car owners of the existence of areas with high vacancy probability through publicity activities to increase the visibility of these areas. Regularly review the operation data of parking lots, adjust management strategies according to actual conditions, and ensure the effectiveness of measures. By implementing these management measures, the parking space utilization rate of parking lots with high vacancy probability can be effectively improved, the allocation of parking resources can be optimized, and the parking experience of car owners can be improved.

[0071] Furthermore, for areas with low vacancy probability, parking fees can be increased to curb excessive parking demand, encourage car owners to park outside peak hours, or choose other parking places. According to the time period and demand changes, a dynamic parking pricing strategy is implemented, with higher fees during peak hours, so as to balance the utilization of parking spaces during peak and off-peak hours. Through intelligent parking systems or reservation parking services, the allocation of parking spaces is optimized to ensure that car owners in need can get parking spaces in time. Cooperate with surrounding units or residential communities to implement staggered shared parking plans to share vacant parking spaces during non-peak hours with other users, thereby improving the efficiency of parking space use. For areas with low vacancy probability, ensure the quality and safety of parking spaces, provide good lighting and monitoring to improve the parking experience, and reduce vacancy caused by poor parking environment. Through publicity and education activities, the public's awareness of the problem of parking difficulties is raised, and citizens are encouraged to use public transportation or travel during non-peak hours. Regularly review the operation data of parking lots, adjust management strategies according to actual conditions, and ensure the effectiveness of measures. By implementing these management measures, the utilization rate of parking spaces in parking lots with low vacancy probability can be effectively improved, the problem of parking difficulties can be alleviated, and the satisfaction of car owners can be improved.

[0072] It should be explained that in this embodiment, the parking lot database is used to store parking lot related data, including parking lot historical data, i.e., the effective idle times of each parking space in each target area, the duration of each idle interval, the critical traffic volume and the critical number of commercial facilities, the environmental characteristic influencing factors corresponding to the traffic volume and the environmental characteristic influencing factors corresponding to the number of commercial facilities, the parking space idle interval threshold, the parking space utilization evaluation influencing factors corresponding to the effective idle times and the parking space utilization evaluation influencing factors corresponding to the effective idle interval, the parking space utilization evaluation index of each target area corresponding to the probability evaluation influencing factors of the parking space idleness and the parking space environmental characteristic impact index corresponding to the probability evaluation influencing factors of the parking space idleness and the preset historical cycle duration. The data source of the parking lot database can be obtained through the parking lot supporting management system, including but not limited to parking space identification, entry and exit records, and fee management. These systems will record the entry and exit time of the vehicle, the use of the parking space, the parking fee and other information in real time, and update the database in real time. It is also possible to obtain information such as the time and location of the vehicle entering and leaving the parking lot through the video monitoring system, which can be used as a supplement to the database to improve the accuracy of the data. The license plate recognition system can also automatically identify the vehicle's license plate, allowing the vehicle to quickly enter and exit, and this information can also be entered into the database.

[0073] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A parking lot space prediction management system based on big data, characterized in that: include: Data collection and processing module, used to collect and integrate parking lot data, including parking lot environment basic data and parking lot historical data; The environmental data analysis module is used to divide the parking lot into regions according to the basic data of the parking lot environment, mark them into target areas, extract the parking lot environment characteristic data from the basic data of the parking lot environment, and obtain the parking lot environment characteristic impact index through comprehensive analysis; The comprehensive analysis obtains the parking lot environmental characteristics impact index, and the specific analysis process is as follows: Deploy a number of historical time monitoring points, the parking lot environmental characteristic data includes the vehicle flow and the number of commercial facilities around the parking lot at each historical time monitoring point, extract the critical vehicle flow and the critical number of commercial facilities from the parking lot database, and comprehensively analyze to obtain the parking lot environmental characteristic impact index; The specific numerical expression of the parking lot environmental characteristic impact index is: ； In the formula, represents the parking lot environmental characteristics impact index, represents a natural constant, Indicates the number of each historical time monitoring point, , Indicates the total number of historical time monitoring points, Indicates The traffic volume around the parking lot at the historical time monitoring point, Indicates The number of commercial facilities around the parking lot at each historical monitoring point, represents the critical traffic volume, represents the number of critical commercial facilities, Indicates the environmental characteristic influencing factor corresponding to the set traffic flow, Indicates the environmental characteristic impact factor corresponding to the set number of commercial facilities; The historical data analysis module is used to comprehensively analyze the parking space utilization evaluation index of each target area based on the historical data of the parking lot; The numerical expression of the parking space utilization evaluation index of each target area is: ； In the formula, Indicates The parking space utilization evaluation index of the target area, Indicates the number of each target area, , represents the total number of target areas, Indicates the number of each parking space. , Indicates the total number of parking spaces. Indicates Target area The number of valid vacant parking spaces, Indicates the critical effective idle times, Indicates the number of valid idle times, , Indicates the total number of valid idle times, Indicates Target area Parking spaces The duration of the next effective idle interval, Indicates the preset historical period length. Indicates the parking space utilization evaluation influencing factor corresponding to the preset effective idle times, Indicates the parking space utilization evaluation influencing factor corresponding to the preset effective idle interval duration; The parking lot management module is used to obtain the parking space vacancy probability evaluation index of each target area through comprehensive analysis based on the parking lot environment characteristic impact index and the parking space utilization evaluation index of each target area, and evaluate the parking space vacancy situation of the parking lot, and manage the parking lot according to the evaluation results; The specific numerical expression of the parking space vacancy probability evaluation index of each target area is: ； In the formula, Indicates The parking space vacancy probability evaluation index of the target area is Indicates The parking space utilization evaluation index of the target area, represents the parking lot environmental characteristics impact index, Indicates the setting The parking space utilization evaluation index of the target area corresponds to the parking space vacancy probability evaluation influencing factor, It represents the parking space vacancy probability assessment impact factor corresponding to the set parking lot environment characteristic impact index.

2. The parking lot space prediction management system based on big data according to claim 1 is characterized by: The parking lot is divided into regions according to the basic parking lot environment data, and the specific process is as follows: The locations of the entrances and exits of the parking lot are obtained from the basic data of the parking lot environment, the parking lot is divided into areas according to the locations of the entrances and exits and the set distance parameters, and the divided areas are marked as target areas.

3. The parking lot space prediction management system based on big data according to claim 1 is characterized by: The comprehensive analysis obtains the parking space utilization evaluation index of each target area. The specific analysis process is as follows: The parking lot historical data includes the effective idle times and the effective idle interval duration of each parking space in each target area within a preset historical period, and the preset historical period duration is obtained at the same time, and a comprehensive analysis is performed to obtain a parking space utilization evaluation index for each target area.

4. The parking lot space prediction management system based on big data according to claim 1 is characterized by: The comprehensive analysis obtains the parking space vacancy probability evaluation index of each target area. The specific analysis process is as follows: According to the parking lot environment characteristic impact index and the parking space utilization rate evaluation index of each target area, a comprehensive analysis is performed to obtain the parking space vacancy probability evaluation index of each target area, and the parking space vacancy probability evaluation index of each target area is used to quantitatively evaluate the vacancy probability of parking spaces in the target area of ​​the parking lot.

5. The parking lot space prediction management system based on big data according to claim 4 is characterized by: The vacancy of parking spaces in the parking lot is evaluated, and the parking lot is managed according to the evaluation results. The specific process is as follows: The parking space vacancy probability evaluation indicators of each target area are sorted in descending order. According to the total number of target areas, the sequence positions corresponding to the first quartile and the third quartile are calculated. The target areas before the sequence position corresponding to the first quartile are marked as high vacancy probability areas of each parking lot, and the target areas after the sequence position corresponding to the third quartile are marked as low vacancy probability areas of each parking lot. The high vacancy probability areas and low vacancy probability areas of the parking lot are managed separately.

6. The parking lot space prediction management system based on big data according to claim 1 is characterized by: The parking lot environmental characteristics impact index is a quantitative assessment data obtained by comprehensively analyzing the traffic volume and the number of commercial facilities around the parking lot at each historical monitoring point. It is used to quantitatively assess the impact of the parking lot surrounding environment on the parking lot space utilization rate and provide a data basis for assessing the probability of vacant parking spaces in the parking lot.

7. The parking lot space prediction management system based on big data according to claim 5 is characterized by: The parking space utilization evaluation index of each target area is a quantitative evaluation data obtained by comprehensively analyzing the number of effective idle times and the duration of each idle interval of each parking space in each target area within a preset historical period. It is used to quantitatively evaluate the utilization rate of parking spaces in each target area of ​​the parking lot and provide a data basis for evaluating the probability of idle parking spaces in the parking lot.

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