Stereo garage parking lot intelligent management method and system

Abstract

The invention discloses an intelligent management method and system for a stereo garage parking lot, and particularly relates to the technical field of parking management, and the method comprises the following steps: when a vehicle enters a garage, the system marks the vehicle as a target vehicle, obtains the total amount of garage remaining spaces in an area where the vehicle is located and an adjacent area, carries out the remaining space analysis, and judges whether a recommendation mechanism is triggered or not; if the parking space is triggered, the system obtains the nearest unoccupied parking space according to the position of the vehicle and preliminarily judges whether the parking space is suitable for parking or not, and if not, the next parking space continues to be found until the proper parking space is found or a garage leaving signal is sent out; the system analyzes the surrounding parking information of the target parking space and deduces a parking recommendation level, if a preset requirement is met, recommendation guidance is carried out, and otherwise, a proper parking space continues to be searched or a parking-out signal is sent out; according to the method, the vacancy condition of each area of the parking lot is monitored in real time, and the recommendation strategy is adjusted according to the analysis result, so that the parking space utilization rate of the parking lot can be maximized, and the parking space resource waste is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of parking management, and more specifically, to an intelligent management method and system for a three-dimensional garage parking lot. Background Art

[0002] With the acceleration of urbanization and the continuous increase in the number of vehicles, the problem of parking difficulties is becoming increasingly serious, especially in large parking lots and urban central areas, where vehicles often face problems such as time-consuming and difficult parking. Traditional parking management systems mostly rely on manual or simple automated equipment, and cannot effectively solve problems such as uneven allocation of parking resources, low parking space utilization, and unclear parking guidance.

[0003] Although the existing intelligent parking system can monitor and guide parking spaces to a certain extent, there are still many deficiencies in practical applications. For example, the accuracy of parking space recommendations is insufficient, and practical issues such as vehicle model, parking space size, and parking conditions of surrounding vehicles are not taken into account when recommending parking spaces, resulting in car owners still facing problems such as insufficient space and high parking difficulty when parking. Therefore, how to effectively guide vehicles to quickly find suitable parking spaces through intelligent systems in complex parking scenarios and maximize the utilization rate of parking spaces in parking lots has become a technical problem that needs to be solved urgently in the field of parking management. Summary of the invention

[0004] To achieve the above object, the present invention provides the following technical solutions: A method for intelligent management of a three-dimensional garage parking lot comprises the following steps: When a vehicle enters a garage, it is marked as a target vehicle. The total number of remaining garage spaces in the garage area where the vehicle enters is obtained, as well as the total number of remaining garage spaces in the adjacent garage areas, and the remaining space is analyzed. Based on the analysis results, it is determined whether to trigger the recommendation mechanism. When the recommendation mechanism is triggered, the nearest vacant parking space is obtained based on the current position of the target vehicle, and then a preliminary judgment is made as to whether the parking space is suitable for parking. If not, the next vacant parking space is searched for until a suitable parking space is found and marked as the target parking space or a signal to leave the parking lot is issued; Acquiring surrounding parking information of the target parking space and performing a surrounding parking status analysis operation, and inferring a parking recommendation level based on the result of the surrounding parking status analysis operation to obtain a parking recommendation level for the target parking space; Based on the parking recommendation level of the target parking space, determine whether it meets the preset recommendation requirements. If so, provide location recommendation guidance. If not, continue to look for the next vacant parking space until a satisfactory location is found and provide location recommendation guidance or send out a signal to leave the parking lot.

[0005] In a preferred embodiment, the residual analysis refers to: Get the total number of remaining garage spaces in the garage area where the entrance is located and mark it as SZ, and the total number of remaining garage spaces in the adjacent garage area and mark it as XLi, where i represents the number of the adjacent garage area. Then calculate the ratio of the total number of remaining garage spaces SZ in the garage area where the entrance is located to the total number of garage parking spaces in the garage area where the entrance is located and mark it as BL. Calculate the ratio of the total number of remaining garage spaces XLi of all adjacent garage areas to their own total number of garage parking spaces and mark it as YLi.

[0006] In a preferred embodiment, judging whether to trigger the recommendation mechanism according to the analysis result refers to: The proportion value BL corresponding to the garage where the entrance is located and the proportion value YLi corresponding to the adjacent garage area are compared with the preset surplus threshold. If the proportion value BL corresponding to the garage where the entrance is located and the proportion value YLi corresponding to the adjacent garage area are both greater than or equal to the preset surplus threshold, the recommendation mechanism is triggered. If any one of the proportion value BL corresponding to the garage where the entrance is located and the proportion value YLi corresponding to the adjacent garage area is less than the preset surplus threshold, the recommendation mechanism is not triggered.

[0007] In a preferred embodiment, preliminarily determining whether the parking space is suitable for parking refers to: When traversing all the vacant parking spaces for the first time, obtain the model information of the target vehicle entering the garage, find the standard parking space level corresponding to the model information of the target vehicle, then find the vacant parking space closest to the target vehicle and obtain its corresponding parking space level. If it is smaller or larger than the standard parking space level corresponding to the model information of the target vehicle, the parking space is not suitable for parking. Only when it is equal to the standard parking space level corresponding to the model information of the target vehicle, the parking space is suitable for parking and is marked as the target parking space; When traversing all the available parking spaces for the second time, find the available parking space closest to the target vehicle and obtain its corresponding parking space level. Only when it is greater than the standard parking space level corresponding to the model information of the target vehicle, the parking space is suitable for parking and is marked as the target parking space; If a suitable parking space is still not found during the second traversal, a signal to exit the garage is issued.

[0008] In a preferred embodiment, acquiring the surrounding parking information of the target parking space refers to: The surrounding parking space information of the target parking space, the model information of the vehicles parked in the surrounding parking spaces, and the status information of the vehicles parked in the surrounding parking spaces are obtained respectively.

[0009] The surrounding parking status analysis operation refers to: A vehicle model influence index is generated according to information about surrounding parking spaces of the target parking space and information about models of vehicles parked in the surrounding parking spaces, and a parking influence index is generated according to status information of vehicles parked in the surrounding parking spaces.

[0010] In a preferred embodiment, the logic for obtaining the vehicle model influence index is: Get the Boolean variable results of the two adjacent parking spaces around the target parking space according to the preset strategy, and respectively get the parking space level LCl of the parking space on the left side of the target parking space, the parking space level LCr of the parking space on the right side, the standard parking space level SCl corresponding to the model of the vehicle parked in the left parking space, and the standard parking space level SCr corresponding to the model of the vehicle parked in the right parking space, and then substitute them into the following formula for calculation: ; , They are respectively a Boolean variable indicating whether there is a car parked on the left side of the target parking space and a Boolean variable indicating whether there is a wall on the left side of the target parking space, obtained according to the current layout of the parking lot. , They are respectively a Boolean variable indicating whether there is a car parked on the right side of the target parking space and a Boolean variable indicating whether there is a wall on the right side of the target parking space, obtained according to the current layout of the parking lot. , are the preset influence weights for the left and right sides of the target parking space, is the vehicle model impact index.

[0011] In a preferred embodiment, the logic for obtaining the parking impact index is: When the target parking space is a horizontal parking space, obtain the shortest distance between the vehicles parked on its left and right sides and its symmetry axis, and then perform the following calculation: ; is the standard parking space level corresponding to the target vehicle, is the shortest distance between the vehicle parked in the parking space on the left side of the target parking space and the symmetry axis of the target parking space. The shortest distance between the vehicle parked in the parking space to the right of the target parking space and the symmetry axis of the target parking space; When the target parking space is a vertical parking space, obtain the shortest distance between the vehicles parked in the parking spaces in front and behind it and its symmetry axis 2, and then perform the following calculation: ; is the standard parking space level corresponding to the target vehicle, is the shortest distance between the vehicle parked in the parking space in front of the target parking space and the second symmetry axis of the target parking space, is the shortest distance between the vehicle parked in the parking space behind the target parking space and the second symmetry axis of the target parking space, , Boolean variables indicating whether there are cars parked in front of and behind the target parking space according to the current layout of the parking lot; is the parking impact index.

[0012] In a preferred embodiment, the parking recommendation level of the target parking space is inferred by fuzzy logic according to the parking influence index, the vehicle type influence index, and the ratio of the parking level corresponding to the target parking space to the standard parking level corresponding to the target vehicle.

[0013] In a preferred embodiment, a three-dimensional parking garage intelligent management system includes: The remaining space analysis module: When a vehicle enters a garage, it is marked as a target vehicle. The total number of remaining spaces in the garage area where the vehicle enters the garage and the total number of remaining spaces in the adjacent garage areas are obtained and remaining space analysis is performed. The recommendation mechanism is determined based on the analysis results. Initial judgment module: When the recommendation mechanism is triggered, the nearest vacant parking space is obtained according to the current position of the target vehicle, and then a preliminary judgment is made as to whether the parking space is suitable for parking. If not, the next vacant parking space is searched until a suitable parking space is found and marked as the target parking space or a signal for leaving the parking space is issued; The parking space analysis module acquires the surrounding parking information of the target parking space and performs a surrounding parking status analysis operation, and infers the parking recommendation level based on the result of the surrounding parking status analysis operation to obtain the parking recommendation level of the target parking space; The recommendation guidance module determines whether the parking recommendation level of the target parking space meets the preset recommendation requirements based on the parking recommendation level of the target parking space. If it does, it will provide location recommendation guidance. If it does not, it will continue to look for the next vacant parking space until a satisfactory location is found and provide location recommendation guidance or send out a signal to leave the parking lot.

[0014] Technical effects and advantages of the present invention: Through the reserve analysis and intelligent recommendation mechanism in the present invention, the system can quickly calculate and recommend suitable parking spaces based on the real-time location of the vehicle, the number of parking spaces available, and the type of vehicle, thereby reducing the time car owners spend searching for parking spaces and improving parking efficiency. In particular, when parking spaces are tight, the system can dynamically guide vehicles to areas with more remaining spaces, avoiding repeated searching in a small area.

[0015] The present invention monitors the vacancy situation of each area of ​​the parking lot in real time, adjusts the recommendation strategy according to the analysis results, and reasonably allocates parking space resources. By preferentially guiding vehicles to park in more suitable parking areas, the system can maximize the parking space utilization rate of the parking lot and reduce the waste of parking space resources.

[0016] The present invention intelligently determines whether a parking space is suitable for the target vehicle based on the vehicle type impact index, parking impact index, and the matching relationship between the parking space and the vehicle standard level, thereby avoiding the increased difficulty of parking due to inappropriate parking spaces. This can reduce the difficulty of parking operations for car owners, especially avoid the problem of insufficient space or excessive parking space, and improve the parking experience.

[0017] Through real-time surplus analysis, the present invention can effectively balance the use of parking spaces in various areas of the parking lot, avoiding congestion caused by vehicles concentrating in a certain parking area. Even during peak parking periods, the system can quickly adjust parking strategies through surplus analysis and guidance mechanisms, reduce the phenomenon of vehicles making ineffective detours in the parking lot, and reduce the waiting time of car owners.

[0018] Dynamic adjustment can make more rational use of parking resources, avoid overcrowding on some floors and vacant parking spaces on other floors. By adjusting the analysis area based on real-time data, new vehicles can be better guided to suitable parking spaces, reducing the time for vehicles to search in a cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings; Figure 1 The schematic diagram of an intelligent management method for a three-dimensional garage parking lot in the present invention.

[0020] Figure 2 The present invention is a schematic diagram of an intelligent management system for a three-dimensional garage parking lot. DETAILED DESCRIPTION

[0021] 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.

[0022] Reference Figure 1 - Figure 2 The following examples are obtained: Embodiment 1: A method for intelligent management of a three-dimensional garage parking lot, comprising the following steps: When a vehicle enters a garage, it is marked as a target vehicle. The total number of remaining garage spaces in the garage area where the vehicle enters is obtained, as well as the total number of remaining garage spaces in the adjacent garage area, and a surplus analysis is performed. Based on the analysis results, it is determined whether to trigger the recommendation mechanism. This step ensures that the system has a real-time understanding of the overall vacancy status of the garage. By obtaining parking space data in the current and adjacent areas, the system can determine in advance whether it is necessary to guide vehicles into other areas to avoid congestion caused by concentrated parking and improve parking efficiency. The surplus analysis is to balance the load of the parking area. If there is a shortage of parking spaces in a certain area, but there are a large number of vacant parking spaces in the adjacent area, the system can intelligently recommend vehicles to areas with more vacancies to avoid congestion and optimize the distribution of parking spaces.

[0023] When the recommendation mechanism is triggered, the nearest vacant parking space is obtained based on the current position of the target vehicle, and then a preliminary judgment is made as to whether the parking space is suitable for parking. If not, the next vacant parking space is searched for until a suitable parking space is found and marked as the target parking space or a signal for leaving the parking lot is issued. By intelligently judging whether a parking space is suitable for the target vehicle, the vehicle is prevented from being parked in an inappropriate parking space, such as a parking space with insufficient space or a parking space that cannot be parked smoothly. This can improve the parking experience of car owners and reduce the difficulty of parking.

[0024] The surrounding parking information of the target parking space is obtained and the surrounding parking status analysis operation is performed. Based on the results of the surrounding parking status analysis operation, the parking recommendation level is inferred to obtain the parking recommendation level of the target parking space; the parking status analysis is to more accurately evaluate the availability and parking difficulty of the parking space. If the surrounding parking conditions are poor (such as vehicles parked irregularly, too close, etc.), even if the parking space itself is suitable for parking, the system may judge that parking is difficult, which will affect the recommendation results. By quantitatively evaluating the parking recommendation level of each parking space, the system can more accurately judge the suitability of the parking space and provide more targeted parking suggestions. This step ensures that the recommended parking space is not only free, but also suitable for the target vehicle, reducing the troubles that may be encountered during parking.

[0025] Based on the parking recommendation level of the target parking space, it is determined whether it meets the preset recommendation requirements. If it does, the location recommendation guidance is provided. If it does not, the next vacant parking space is searched for until a satisfactory location is found and the location recommendation guidance is provided or a signal for leaving the parking lot is issued. This step is the final verification of the recommended parking space to ensure that the availability and parking difficulty of the parking space are within an acceptable range. If the parking space does not meet the recommendation requirements, the system will continue to search for a more suitable parking space until a parking space that meets the conditions is found or the vehicle is advised to leave the parking lot. This ensures a smooth experience for the owner during parking and improves the efficiency of overall garage management.

[0026] The exit signal is a notification signal sent by the system when there are no vacant parking spaces suitable for the target vehicle in the garage, prompting the owner to consider leaving the current parking lot. This may be because all parking spaces in the current parking lot are full, or all parking spaces suitable for the target vehicle (based on parking space size, surrounding vehicle conditions, etc.) do not meet the recommended standards. The issuance of the exit signal is intended to avoid meaningless detours in the parking lot, reduce the waiting time of the owner and the traffic pressure in the garage. This mechanism enables the system to guide the owner to leave in a timely manner when parking space resources are tight or the parking lot is not suitable for parking, and prevent time from being wasted on ineffective searches for parking spaces.

[0027] Relationship between surplus analysis and recommendation mechanism: When a vehicle enters a parking lot, the system first obtains the number of vacant parking spaces in the area where the vehicle is located and in adjacent areas, and performs surplus analysis. The results of surplus analysis help the system determine whether the current parking area can meet parking needs. If there are sufficient parking spaces in the area, there is no need to start a complex recommendation mechanism, and the system can directly guide the vehicle to find a parking space.

[0028] When the remaining analysis results show that there are sufficient parking spaces in the current area, the system will not trigger the recommendation mechanism, and the vehicle can find a parking space on its own. This method reduces the consumption of computing resources because there is no need to perform complex operations such as parking space suitability judgment and vehicle status analysis.

[0029] If the remaining analysis results show that the current area has a shortage of parking spaces, or there are many vacant parking spaces in the adjacent area, the system triggers the recommendation mechanism. The recommendation mechanism intelligently determines the most suitable parking space based on factors such as the vehicle's real-time location, parking space size, and surrounding parking environment.

[0030] By performing margin analysis at the time of entry, it is possible to avoid wasting computing resources when there are sufficient parking spaces. When there are sufficient parking spaces, the system does not need to use complex parking space adaptation algorithms, nor does it need to analyze the surrounding parking environment in real time. It can directly guide vehicles to the nearest area. This method effectively reduces the computing load of the system.

[0031] The margin analysis is a fast, low-complexity judgment process that only requires calculating the number of parking spaces in the current and adjacent areas. The recommendation mechanism, on the other hand, requires comprehensive analysis of multiple complex factors such as parking space suitability, vehicle size, surrounding parking conditions, etc. By performing the margin analysis at the beginning, the system can reduce the number of times the recommendation mechanism is triggered, thereby saving a lot of computing resources.

[0032] There are several reasons why we choose to obtain the number of vacant parking spaces in the area where the vehicle is located and the adjacent areas for surplus analysis instead of analyzing all areas of the entire parking lot: The parking space data of the entire parking lot may be very large, especially in large parking lots. If the vacant parking spaces in all areas are analyzed, the system needs to process a large amount of data and make complex judgments, which will increase the computing load and time consumption. By only analyzing the area where the vehicle is located and the adjacent areas, the amount of calculation can be greatly reduced and the system performance can be optimized. The analysis of the local area can get the results faster than the analysis of the whole area. The system can quickly make parking guidance decisions and improve the smooth experience of the vehicle after entering the parking lot.

[0033] After a vehicle enters a parking lot, the owner usually hopes to find an available parking space in the current area or nearby. Analyzing the number of available parking spaces in the area where the vehicle is located and in adjacent areas can give priority to meeting the demand for "parking nearby". If a suitable parking space can be found in the nearby area, there is no need to waste time directing the vehicle to a farther area, which improves the user experience. Areas far from the vehicle entrance are usually not the first choice for parking, and are only considered when there is a shortage of parking spaces in a local area. Therefore, the parking space surplus analysis for these areas can be postponed or triggered on demand.

[0034] The parking lot management system usually divides the parking area into multiple small areas, each with independent parking space information. When a vehicle enters an area, the system only needs to analyze the data of the current area and its adjacent areas, which can not only make parking recommendations quickly, but also avoid too much complex full-field analysis. If the owner wants a closer parking area, the system only needs to guide the owner in the nearby area. If the full-field analysis is performed, it will contain a lot of invalid data that is irrelevant to the target vehicle (such as empty parking spaces far away from the current vehicle position), which will not help improve parking efficiency, but increase the processing complexity of the system.

[0035] Most parking lots are designed to be divided into zones, each serving different traffic needs. After entering the parking lot, vehicles usually choose to park in an area that is closer to their destination. The system analyzes the parking spaces in the current and adjacent areas, which can effectively meet the design concept of parking lot management. If there are insufficient parking spaces in a certain area, the system can dynamically adjust according to the current parking space occupancy status and guide car owners to adjacent areas. This strategy ensures balanced parking space utilization in the parking lot while avoiding the waste of resources caused by comprehensive analysis of the entire parking lot during peak parking periods.

[0036] Margin analysis refers to: The total amount of remaining garage spaces in the garage area where the entrance is located is obtained and marked as SZ, and the total amount of remaining garage spaces in the adjacent garage area is marked as XLi, i represents the number of the adjacent garage area, and then the ratio of the total amount of remaining garage spaces SZ in the garage area where the entrance is located to the total amount of garage parking spaces in the garage area where the entrance is located is calculated and marked as BL, and the ratio of the total amount of remaining garage spaces XLi in all adjacent garage areas to the total amount of garage parking spaces in the garage area itself is calculated and marked as YLi. Judging whether to trigger the recommendation mechanism according to the analysis results refers to comparing the ratio value BL corresponding to the garage where the entrance is located and the ratio value YLi corresponding to the adjacent garage area with the preset surplus threshold. If the ratio value BL corresponding to the garage where the entrance is located and the ratio value YLi corresponding to the adjacent garage area are both greater than or equal to the preset surplus threshold, the recommendation mechanism is triggered. If any of the ratio value BL corresponding to the garage where the entrance is located and the ratio value YLi corresponding to the adjacent garage area is less than the preset surplus threshold, the recommendation mechanism is not triggered.

[0037] Prioritize the current area: If the vehicle is already in a certain area, the system will first analyze the vacant parking spaces in this area. If there are enough vacant parking spaces in the current area, the system will prioritize the parking spaces in the current area. Prioritizing the current area helps car owners park faster and reduce the time spent looking for parking spaces. It also conforms to the car owners' own parking habits, avoids additional movement of the vehicle in the parking lot, and improves parking efficiency.

[0038] Find the available parking spaces in the adjacent areas: If the available parking spaces in the current area are insufficient to meet the demand, the system will analyze the available parking spaces in the adjacent areas. At this time, the system will guide the vehicles to the adjacent areas with the most available parking spaces based on the available parking spaces analysis results. By analyzing the available parking spaces in the adjacent areas, the system can effectively balance the parking space utilization rate in each area of ​​the parking lot, avoiding some areas being too crowded while other areas are too empty.

[0039] The initial judgment on whether the parking space is suitable for parking refers to: When traversing all the vacant parking spaces for the first time, obtain the model information of the target vehicle entering the garage, find the standard parking space level corresponding to the model information of the target vehicle, then find the vacant parking space closest to the target vehicle and obtain its corresponding parking space level. If it is smaller or larger than the standard parking space level corresponding to the model information of the target vehicle, the parking space is not suitable for parking. Only when it is equal to the standard parking space level corresponding to the model information of the target vehicle, the parking space is suitable for parking and is marked as the target parking space; When traversing all the available parking spaces for the second time, find the available parking space closest to the target vehicle and obtain its corresponding parking space level. Only when it is greater than the standard parking space level corresponding to the model information of the target vehicle, the parking space is suitable for parking and is marked as the target parking space; If a suitable parking space is still not found during the second traversal, a signal to exit the garage is issued.

[0040] The first traversal is to match the target vehicle as much as possible: In the first traversal, the system will give priority to finding an empty parking space that matches the standard parking space level corresponding to the target vehicle model information. The main purpose of this traversal is to find a parking space that is just right for the target vehicle, that is, the size of the parking space completely matches the size of the vehicle. Through strict matching, the system can ensure the best parking experience for the target vehicle, while avoiding parking difficulties or waste of resources caused by parking spaces that are too small or too large. In other words, the target vehicle is parked in the most suitable parking space as much as possible to improve the convenience of vehicle parking.

[0041] The second pass is a fallback: In the second pass, if the system cannot find a parking space that exactly matches the vehicle's standard parking space level, it starts looking for a parking space that is slightly larger than the vehicle's standard parking space level, and no longer considers a parking space that exactly matches. This is to ensure that the target vehicle can find an available parking space, but it also means that the parking space may be slightly larger than the standard parking space.

[0042] By first trying to strictly match, and then relaxing the conditions, the system is able to maximize the use of parking resources. The relative scarcity of large parking spaces means that these spaces should be reserved for larger vehicles first, rather than being allocated to small cars first. With this strategy, small cars will try to park in standard parking spaces, while larger vehicles will be reserved for large parking spaces, so that parking resources can be used more efficiently.

[0043] If large parking spaces are allocated to larger vehicles first, small vehicles will try to park in standard parking spaces, which leaves more parking options for vehicles that may enter the parking lot later (especially large vehicles). Because large vehicles require larger parking spaces, the second traversal can avoid allocating these parking spaces to small vehicles first, ensuring the reasonable allocation of parking resources.

[0044] Send out a signal when there is no suitable parking space: If a suitable parking space is still not found after two traversals, the system will send out a signal to guide the vehicle out of the parking lot. This design prevents vehicles from circling meaninglessly in the parking lot when there are not enough parking spaces or it is impossible to park, avoids congestion in the garage, and improves overall parking efficiency.

[0045] Gradually relax the conditions: The first traversal only looks for strictly matching parking spaces, and the second traversal starts looking for larger parking spaces. This strategy can ensure efficient use of parking resources while taking into account the needs of different types of vehicles. Through two traversals, the system can maximize the parking needs of the target vehicle and leave more suitable parking spaces for subsequent vehicles.

[0046] Acquiring the parking information around the target parking space means: The surrounding parking space information of the target parking space, the model information of the vehicles parked in the surrounding parking spaces, and the status information of the vehicles parked in the surrounding parking spaces are obtained respectively. The surrounding parking status analysis operation refers to: generating a model influence index according to the surrounding parking space information of the target parking space and the model information of the vehicles parked in the surrounding parking spaces, and generating a parking influence index according to the status information of the vehicles parked in the surrounding parking spaces.

[0047] Conceptual idea: When one side of the target parking space is a wall, only the impact on the other side needs to be considered. At the same time, when there is no vehicle parked in the adjacent parking space, the impact of parking should be relatively small because there is no direct space occupation problem. Therefore, specific processing logic needs to be designed for such situations.

[0048] Acquisition logic steps: When the target parking space is a horizontal parking space, it usually affects the vehicle door opening safety and the difficulty of the driver getting on and off the vehicle. When the target parking space is a vertical parking space, it is usually not necessary to consider the impact of opening the door.

[0049] When the target parking space is a horizontal parking space, if one side of the target parking space is a wall, only the parking spaces on the other side are considered. Introduce a Boolean variable: whether there is a vehicle in the left parking space : If there is a vehicle parked, set to 1; otherwise, set to 0.

[0050] Is there any vehicle in the right parking space? : If there is a vehicle parked, set to 1; otherwise, set to 0.

[0051] Is there a wall on the left? : If the left side is a wall, set to 1; otherwise, set to 0.

[0052] Is there a wall on the right? : If the right side is a wall, set to 1; otherwise, set to 0.

[0053] If one side is a wall (for example, the left side), only the impact of the other side (the right side) is considered. Vice versa. Boolean variables enable the system to quickly judge and skip unnecessary calculations. If there is no car or a wall on one side, the system can immediately know which parts need to be processed and which parts can be ignored through the "0" and "1" judgments of the Boolean variables. By using Boolean variables, complex nested conditions are avoided, making the system more efficient and intuitive when calculating the comprehensive vehicle model impact index.

[0054] The logic for obtaining the vehicle model impact index is: Get the Boolean variable results of the two adjacent parking spaces around the target parking space according to the preset strategy, and respectively get the parking space level LCl of the parking space on the left side of the target parking space, the parking space level LCr of the parking space on the right side, the standard parking space level SCl corresponding to the model of the vehicle parked in the left parking space, and the standard parking space level SCr corresponding to the model of the vehicle parked in the right parking space, and then substitute them into the following formula for calculation: ; , They are respectively a Boolean variable indicating whether there is a car parked on the left side of the target parking space and a Boolean variable indicating whether there is a wall on the left side of the target parking space, obtained according to the current layout of the parking lot. , They are respectively the Boolean variables of whether there is a car parked on the right side of the target parking space and whether there is a wall on the right side of the target parking space according to the current layout of the parking lot. The corresponding Boolean variable will be set to 1 when there is a car parked on the side, and set to 0 when there is no car. For example, when there is a car parked on the left side of the target parking space, Will be set to 1, and set to 0 when there is no car. , The influence weights for the left and right sides of the target parking space are preset respectively. They are usually set according to the specific situation. The left side (driver's side) usually has a larger weight because this side has a higher demand for parking space. The vehicle model impact index. The larger the vehicle model impact index, the more difficult it is to park in the target parking space, or the more affected the target parking space is by the vehicles on the left and right. The vehicle model impact index is calculated by the degree of matching between the vehicle models of the surrounding parking spaces and the parking space grades. If the vehicle model impact index is large, it means that the surrounding vehicles occupy more space and the parking spaces are relatively tight. The target parking space may be subject to more space restrictions, and more skills or higher attention are required when parking.

[0055] When there are larger vehicles in the parking spaces to the left and right of the target parking space, and the standard parking spaces required by these vehicles are of a higher grade, or the actual parking spaces are of a lower grade, the vehicle type impact index calculated by the system will become larger. At this time, the parking operation in the target parking space will be more restricted, especially in operations such as opening the door and adjusting the parking space, and the owner may need to be more careful.

[0056] When there is a wall on one side, the Boolean variable of the wall will be set to 1, so that the influence of this side is ignored. This is to avoid the wall from having an unnecessary impact on the parking operation of the target parking space. The specific processing is as follows: If there is a wall next to it or there is no vehicle parked next to the target parking space, since the wall will not have an actual impact, the standard parking space level and parking space level can be set to a preset constant value. For example, the ratio of this side can be Set to 1, indicating that there is no parking pressure on this side. If it is greater than 1, it means that the space occupied by the vehicle is more than the parking space required, and the parking space is relatively tight. This can simplify the formula so that it can operate normally when there is a wall or there is no vehicle parked in the adjacent parking space and maintain reasonable and fast operation.

[0057] The logic for obtaining the parking impact index is: When the target parking space is a horizontal parking space, obtain the shortest distance between the vehicles parked on its left and right sides and its symmetry axis, and then perform the following calculation: ; is the standard parking space level corresponding to the target vehicle, is the shortest distance between the vehicle parked in the parking space on the left side of the target parking space and the symmetry axis of the target parking space. The shortest distance between the vehicle parked in the parking space on the right side of the target parking space and the symmetry axis of the target parking space. The shortest distance between the vehicle parked in the parking space and the target parking space indicates the tightness of the left and right spaces when parking. If the distance is small, the parking impact index increases and the parking difficulty increases. When the target parking space is a vertical parking space, obtain the shortest distance between the vehicles parked in the parking spaces in front and behind it and its symmetry axis 2, and then perform the following calculation: ; is the standard parking space level corresponding to the target vehicle, is the shortest distance between the vehicle parked in the parking space in front of the target parking space and the second symmetry axis of the target parking space, The shortest distance between the vehicle parked in the parking space behind the target parking space and the second symmetry axis of the target parking space. The shortest distance between the vehicle parked in the front and rear parking spaces and the target parking space indicates the space limitation for vehicles to enter and exit the parking space. If the front and rear distance is small, the difficulty of parking increases. , Boolean variables representing whether there are cars parked in front of or behind the target parking space according to the current layout of the parking lot; the corresponding Boolean variable will be set to 1 if there is a car parked in front of the target parking space, and set to 0 if there is no car. It will be set to 1, and it will be set to 0 when there is no car. When there is no car, it may be a wall or other building, but when the parking lot is designed, it will be considered not to affect the adjacent parking spaces, and when there is no car, it will be set to 0. Corresponding Or when no car is set to 0 Corresponding It can be set to a preset constant value to make the calculation reasonable, and obtain the shortest distance according to the actual situation when there is a car is the parking impact index.

[0058] Symmetry axis 1: In the case of horizontal parking spaces (left and right), "symmetry axis 1" can be understood as the center line of the parking space. That is, the central axis of the parking space from left to right. When the vehicle is parked in the parking space, the parking spaces on the left and right sides should be symmetrical with this axis.

[0059] In this scenario, when calculating the distance between the target vehicle and the vehicles on the left and right sides, the first axis of symmetry is used to measure the distance of the vehicle relative to the parking spaces on both sides.

[0060] Symmetry Axis 2: In the case of vertical parking spaces (front and back), the "Symmetry Axis 2" represents the central axis when the vehicles are parked front and back. In this scenario, the symmetry axis from front to back of the parking space helps measure the space occupied by the front and back of the vehicles.

[0061] Symmetry axis two is mainly used for distance calculation between front and rear parking spaces to assess the impact of parking in front and behind the vehicle.

[0062] The reason why the parking impact index calculation needs to be divided into horizontal parking spaces and vertical parking spaces: It should be noted that: since the actual situation is generally taken into consideration when designing parking spaces, such as safety bars to restrict vehicles, therefore, when the horizontal parking space is also involved in parking spaces planned at the rear, its impact can be ignored, because the design of the safety bar will ensure that it will not affect the current parking space. If it parks in the current parking space, it will be deemed that there is a car parked in the current parking space and it will not be traversed and searched for. At the same time, the parking lot can set up an alarm device to avoid this situation when one car occupies multiple spaces, and notify the owner in time to move.

[0063] Horizontal parking spaces: Generally speaking, horizontal parking spaces are the most common parking method, and vehicles need to consider the parking impact on the left and right sides. Therefore, the impact of horizontal parking spaces is mainly reflected in the distance between the left and right parking spaces and the vehicle, as well as the difficulty of opening and closing the doors and the vehicle entering and exiting. The impact of horizontal parking spaces is mainly the parking pressure in the left and right directions.

[0064] Vertical parking spaces: Vertical parking spaces mainly consider the space and distance of front and rear parking. In this case, when parking a vehicle, there is no need to consider the impact of the door opening, but more attention is paid to the degree of space occupied by the front and rear of the vehicle. Therefore, the parking impact index of vertical parking spaces is related to the front and rear distance, which affects the smoothness of vehicle entry and exit.

[0065] The reason why the vehicle model impact index only considers horizontal parking spaces: The vehicle model impact index focuses on the matching of the size of the vehicle and the parking space, especially whether there is enough space on the left and right. When parking, especially in horizontal parking spaces, the most important thing for car owners to pay attention to is the space on the left and right, such as whether there is enough space to open the door and whether it is easy to enter the parking space. Vertical parking spaces are usually not affected by the left and right doors. Therefore, when calculating the vehicle model impact index, horizontal parking spaces are the main consideration, and for vertical parking spaces, the left and right space is not affected.

[0066] The greater the parking impact index, the more difficult it is to park. This indicates that the parking conditions around the target parking space have a greater impact on the parking space. Specifically, the left and right parking spaces have a greater impact (horizontal parking spaces): If the vehicles in the left and right parking spaces are close to the target parking space, parking will be limited by space and the difficulty of parking will increase. The front and rear parking spaces have a greater impact (vertical parking spaces): In the case of vertical parking spaces, if the distance between the front and rear parking spaces is too close, it may affect the operation of vehicles entering or exiting the parking space.

[0067] The recommended parking grade of the target parking space is inferred through fuzzy logic according to the parking influence index, vehicle type influence index, and the ratio of the parking grade corresponding to the target parking space to the standard parking grade corresponding to the target vehicle.

[0068] Input fuzzification: First, the three input variables that affect the parking recommendation level are fuzzified. These three variables are: Parking impact index: According to the parking situation around the target parking space, it can be divided into "low impact", "medium impact" and "high impact". Vehicle type impact index: According to the matching situation between the vehicle and the parking space, it can be divided into "good match", "average match" and "poor match". Ratio of parking space level to vehicle standard parking space level: According to the standard matching degree between the parking space and the vehicle, it can be divided into "just match", "slightly larger" and "too large". These input quantities are converted into different fuzzy sets in terms of numerical values, so that the suitability of the parking space can be expressed in an imprecise way.

[0069] Establish a fuzzy rule base: Next, formulate a set of fuzzy rule bases through experience or system preset rules. These rules are used to describe the parking recommendation level under different combinations of input variables. For example: if the "parking impact index" is "low impact", and the "vehicle model impact index" is "better match", and the "ratio of parking space level to vehicle standard parking space level" is "just match", then the parking recommendation level is "high". If the "parking impact index" is "high impact", and the "vehicle model impact index" is "poor match", and the "ratio of parking space level to vehicle standard parking space level" is "too large", then the parking recommendation level is "low". Through these rules, the system can evaluate the recommendation level of the target parking space under different parking environments and conditions.

[0070] Fuzzy reasoning: Fuzzy reasoning is performed based on the above fuzzy rule base. The three fuzzified variables input are matched with the rule base to obtain the recommended parking level. Finally, the result of fuzzy reasoning is defuzzified and converted into a clear value or level (such as "high", "medium" or "low"). The result after defuzzification is the parking recommendation level of the target parking space.

[0071] The preset recommendation requirement can be understood as a standard for the parking system to determine the suitability of a parking space. Different parking lots may set different recommendation requirements according to actual conditions. The present invention takes the following as an example: Minimum requirement for parking recommendation level: The system will preset a threshold for parking recommendation level (e.g., "medium" level). If the recommendation level of the target parking space is higher than or equal to the threshold, the parking space is considered suitable for parking; otherwise, the parking space is not recommended.

[0072] Location recommendation guidance means that when the parking recommendation level meets the preset recommendation requirements, the system provides guidance information to the car owner to help the car owner find and park in the target parking space. The specific guidance steps are as follows: Parking space recommendation prompt: When the parking space meets the recommendation requirements, the system provides the location information of the parking space to the car owner through display screens, in-vehicle navigation, mobile phone applications, etc. For example, the in-vehicle navigation will indicate the nearest parking space on the nth floor and nth row of the parking lot, and mark the parking space number. Path guidance: The system provides a shortest route or the most convenient route to guide the car owner to the target parking space based on the car owner's location. The guidance process can be completed through guidance signs in the parking lot, such as LED signs, ground navigation lights, etc.

[0073] Embodiment 2: An intelligent management system for a three-dimensional parking garage, comprising: The remaining space analysis module: When a vehicle enters a garage, it is marked as a target vehicle. The total number of remaining spaces in the garage area where the vehicle enters the garage and the total number of remaining spaces in the adjacent garage areas are obtained and remaining space analysis is performed. The recommendation mechanism is determined based on the analysis results. Initial judgment module: When the recommendation mechanism is triggered, the nearest vacant parking space is obtained according to the current position of the target vehicle, and then a preliminary judgment is made as to whether the parking space is suitable for parking. If not, the next vacant parking space is searched until a suitable parking space is found and marked as the target parking space or a signal for leaving the parking space is issued; The parking space analysis module acquires the surrounding parking information of the target parking space and performs a surrounding parking status analysis operation, and infers the parking recommendation level based on the result of the surrounding parking status analysis operation to obtain the parking recommendation level of the target parking space; The recommendation guidance module determines whether the parking recommendation level of the target parking space meets the preset recommendation requirements based on the parking recommendation level of the target parking space. If it does, it will provide location recommendation guidance. If it does not, it will continue to look for the next vacant parking space until a satisfactory location is found and provide location recommendation guidance or send a signal to leave the parking lot. The dynamic adjustment module dynamically manages the target vehicle when the target vehicle deviates from the initial static recommended state.

[0074] Embodiment 3: A method for intelligent management of a three-dimensional garage parking lot, when a target vehicle leaves an initial static recommended state, dynamically manage the target vehicle: Exiting from the initial static recommendation state means that: the target vehicle moves from the current parking layer of the stereo garage to another parking layer or the target vehicle stays at the current parking layer of the stereo garage for a time that reaches a preset stay threshold; Dynamic management of the target vehicle means: if the target vehicle drives from the current parking floor of the three-dimensional parking garage to another parking floor, the total amount of remaining garage spaces in the garage area to which the other parking floor belongs and the total amount of remaining garage spaces in the adjacent garage area are analyzed; If the total stay time of the target vehicle in the stereo garage reaches a preset stay threshold, the number of surplus analysis of adjacent garage areas is dynamically adjusted according to the total stay time of the target vehicle in the stereo garage.

[0075] ; Indicates the total number of regions corresponding to the preset initial static recommendation state. In the present invention, the total number of regions for the initial margin analysis is the number of three layers, including one layer above and one layer below plus the current layer. Indicates the total residence time of the target vehicle in the stereo garage, Indicates the current stop level of the target vehicle in the stereo garage. The interference coefficient preset for the current stop level of the stereo garage, It indicates the total number of adjacent garage areas after dynamic adjustment for the remainder analysis, and follows the following principle: parking spaces in the parking layer that have been fully traversed will not be re-traversed during the remainder analysis. , denote the coefficients of the linear term and the quadratic term respectively, is a constant term, and the linear term represents the direct effect of the stay time T on the number of surplus analysis areas. As the stay time increases, the number of areas that need to be analyzed increases linearly, and the user's parking desire is strong. The quadratic term takes into account the nonlinear effects that may be caused by a long stay time. For example, long-term parking may indicate that the vehicle moves less, and the impact on the surrounding parking space demand gradually increases. Reasons for dynamic adjustment: Responding to actual needs: A vehicle staying longer on a certain floor may mean that the parking space mobility on that floor is low, so more attention needs to be paid to other possible empty parking areas. Resource optimization: Dynamic adjustment can make more reasonable use of parking resources, avoiding overcrowding on some floors and vacant parking spaces on other floors. Improving efficiency: By adjusting the analysis area based on real-time data, new vehicles can be better guided to suitable parking spaces, reducing the time vehicles spend searching in a cycle.

[0076] Long dwell times usually reflect the efficiency of parking space usage and vehicle mobility. Longer vehicle dwell times may indicate a higher demand for the current parking space or a lower parking space mobility in the area. Different parking levels may face different visit frequencies and parking space demands. For example, levels close to the ground or main entrances may be more popular and have higher demand, while lower levels or farther levels may have lower demand. By adjusting the level term in the formula , the margin analysis range of the current layer can be adjusted specifically to make resource allocation more reasonable.

[0077] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0078] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0079] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0080] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0081] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent management method for a three-dimensional garage parking lot, characterized in that: The following steps are involved: When a vehicle enters a garage, it is marked as a target vehicle. The total number of remaining garage spaces in the garage area where the vehicle enters is obtained, as well as the total number of remaining garage spaces in the adjacent garage areas, and the remaining space is analyzed. Based on the analysis results, it is determined whether to trigger the recommendation mechanism. When the recommendation mechanism is triggered, the nearest vacant parking space is obtained based on the current position of the target vehicle, and then a preliminary judgment is made as to whether the parking space is suitable for parking. If not, the next vacant parking space is searched for until a suitable parking space is found and marked as the target parking space or a signal to leave the parking space is issued; Acquiring surrounding parking information of the target parking space and performing a surrounding parking status analysis operation, and inferring a parking recommendation level based on the result of the surrounding parking status analysis operation to obtain a parking recommendation level for the target parking space; Based on the parking recommendation level of the target parking space, it is determined whether the preset recommendation requirements are met. If so, the location recommendation guidance is performed. If not, the next vacant parking space is continuously searched until a satisfactory location is found and the location recommendation guidance is performed or a departure signal is issued; When the target vehicle deviates from the initial static recommended state, the target vehicle is dynamically managed: Exiting from the initial static recommendation state means that: the target vehicle moves from the current parking layer of the stereo garage to another parking layer or the target vehicle stays at the current parking layer of the stereo garage for a time that reaches a preset stay threshold; Dynamic management of the target vehicle means: if the target vehicle drives from the current parking floor of the three-dimensional parking garage to another parking floor, the total amount of remaining garage spaces in the garage area to which the other parking floor belongs and the total amount of remaining garage spaces in the adjacent garage area are analyzed; If the total stay time of the target vehicle in the stereo garage reaches a preset stay threshold, the number of surplus analysis of adjacent garage areas is dynamically adjusted according to the total stay time of the target vehicle in the stereo garage.

2. The intelligent management method of a three-dimensional garage parking lot according to claim 1 is characterized in that: Margin analysis refers to: Get the total number of remaining garage spaces in the garage area where the entrance is located and mark it as SZ, and the total number of remaining garage spaces in the adjacent garage area and mark it as XLi, where i represents the number of the adjacent garage area. Then calculate the ratio of the total number of remaining garage spaces SZ in the garage area where the entrance is located to the total number of garage parking spaces in the garage area where the entrance is located and mark it as BL. Calculate the ratio of the total number of remaining garage spaces XLi of all adjacent garage areas to their own total number of garage parking spaces and mark it as YLi.

3. The intelligent management method of a three-dimensional garage parking lot according to claim 2 is characterized in that: Judging whether to trigger the recommendation mechanism based on the analysis results means: The proportion value BL corresponding to the garage where the entrance is located and the proportion value YLi corresponding to the adjacent garage area are compared with the preset surplus threshold. If the proportion value BL corresponding to the garage where the entrance is located and the proportion value YLi corresponding to the adjacent garage area are both greater than or equal to the preset surplus threshold, the recommendation mechanism is triggered. If any one of the proportion value BL corresponding to the garage where the entrance is located and the proportion value YLi corresponding to the adjacent garage area is less than the preset surplus threshold, the recommendation mechanism is not triggered.

4. The intelligent management method of a three-dimensional garage parking lot according to claim 3 is characterized in that: The initial judgment on whether the parking space is suitable for parking refers to: When traversing all the vacant parking spaces for the first time, obtain the model information of the target vehicle entering the garage, find the standard parking space level corresponding to the model information of the target vehicle, then find the vacant parking space closest to the target vehicle and obtain its corresponding parking space level. If it is smaller or larger than the standard parking space level corresponding to the model information of the target vehicle, the parking space is not suitable for parking. Only when it is equal to the standard parking space level corresponding to the model information of the target vehicle, the parking space is suitable for parking and is marked as the target parking space; When traversing all the available parking spaces for the second time, find the available parking space closest to the target vehicle and obtain its corresponding parking space level. Only when it is greater than the standard parking space level corresponding to the model information of the target vehicle, the parking space is suitable for parking and is marked as the target parking space; If a suitable parking space is still not found during the second traversal, a signal to exit the garage is issued.

5. The intelligent management method of a three-dimensional garage parking lot according to claim 4 is characterized in that: Acquiring the parking information around the target parking space means: The surrounding parking space information of the target parking space, the model information of the vehicles parked in the surrounding parking spaces, and the status information of the vehicles parked in the surrounding parking spaces are obtained respectively.

6. The intelligent management method of a three-dimensional garage parking lot according to claim 5 is characterized in that: The surrounding parking status analysis operation refers to: A vehicle model influence index is generated according to information about surrounding parking spaces of the target parking space and information about models of vehicles parked in the surrounding parking spaces, and a parking influence index is generated according to status information of vehicles parked in the surrounding parking spaces.

7. The intelligent management method of a three-dimensional garage parking lot according to claim 6 is characterized in that: The logic for obtaining the vehicle model impact index is: Get the Boolean variable results of the two adjacent parking spaces around the target parking space according to the preset strategy, and respectively get the parking space level LCl of the parking space on the left side of the target parking space, the parking space level LCr of the parking space on the right side, the standard parking space level SCl corresponding to the model of the vehicle parked in the left parking space, and the standard parking space level SCr corresponding to the model of the vehicle parked in the right parking space, and then substitute them into the following formula for calculation: ; , They are respectively a Boolean variable indicating whether there is a car parked on the left side of the target parking space and a Boolean variable indicating whether there is a wall on the left side of the target parking space, obtained according to the current layout of the parking lot. , They are respectively a Boolean variable indicating whether there is a car parked on the right side of the target parking space and a Boolean variable indicating whether there is a wall on the right side of the target parking space, obtained according to the current layout of the parking lot. , are the preset influence weights for the left and right sides of the target parking space, is the vehicle model impact index.

8. The intelligent management method of a three-dimensional garage parking lot according to claim 7 is characterized in that: The logic for obtaining the parking impact index is as follows: When the target parking space is a horizontal parking space, obtain the shortest distance between the vehicles parked on its left and right sides and its symmetry axis, and then perform the following calculation: ; is the standard parking space level corresponding to the target vehicle, is the shortest distance between the vehicle parked in the parking space on the left side of the target parking space and the symmetry axis of the target parking space. The shortest distance between the vehicle parked in the parking space to the right of the target parking space and the symmetry axis of the target parking space; When the target parking space is a vertical parking space, obtain the shortest distance between the vehicles parked in the parking spaces in front and behind it and its symmetry axis 2, and then perform the following calculation: ; is the standard parking space level corresponding to the target vehicle, is the shortest distance between the vehicle parked in the parking space in front of the target parking space and the second symmetry axis of the target parking space, is the shortest distance between the vehicle parked in the parking space behind the target parking space and the second symmetry axis of the target parking space, , Boolean variables indicating whether there are cars parked in front of and behind the target parking space according to the current layout of the parking lot; is the parking impact index.

9. The intelligent management method of a three-dimensional garage parking lot according to claim 8 is characterized in that: The recommended parking grade of the target parking space is inferred through fuzzy logic according to the parking influence index, vehicle type influence index, and the ratio of the parking grade corresponding to the target parking space to the standard parking grade corresponding to the target vehicle.

10. An intelligent management system for a three-dimensional garage parking lot, implemented based on an intelligent management method for a three-dimensional garage parking lot according to any one of claims 1 to 9, characterized in that: include: The remaining space analysis module: When a vehicle enters a garage, it is marked as a target vehicle. The total number of remaining spaces in the garage area where the vehicle enters the garage and the total number of remaining spaces in the adjacent garage areas are obtained and remaining space analysis is performed. The recommendation mechanism is determined based on the analysis results. Initial judgment module: When the recommendation mechanism is triggered, the nearest vacant parking space is obtained according to the current position of the target vehicle, and then a preliminary judgment is made as to whether the parking space is suitable for parking. If not, the next vacant parking space is searched until a suitable parking space is found and marked as the target parking space or a signal for leaving the parking space is issued; The parking space analysis module acquires the surrounding parking information of the target parking space and performs a surrounding parking status analysis operation, and infers the parking recommendation level based on the result of the surrounding parking status analysis operation to obtain the parking recommendation level of the target parking space; The recommendation guidance module determines whether the parking recommendation level of the target parking space meets the preset recommendation requirements based on the parking recommendation level of the target parking space. If it does, it will provide location recommendation guidance. If it does not, it will continue to look for the next vacant parking space until a satisfactory location is found and provide location recommendation guidance or send a signal to leave the parking lot. The dynamic adjustment module dynamically manages the target vehicle when the target vehicle deviates from the initial static recommended state.

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