Scheduling optimization method and system for three-dimensional intelligent parking

Abstract

The invention discloses a scheduling optimization method and system for three-dimensional intelligent parking, and relates to the technical field of parking scheduling. The method comprises the following steps: as a target vehicle enters a garage, determining vehicle identity information through front-end sensing acquisition; a three-dimensional simulated diagram of the three-dimensional parking lot is constructed, a parking scheduling model is constructed, and the three-dimensional simulated diagram is updated in real time along with parking distribution; vehicle identity information is recognized, a parking decision is made based on the parking scheduling model, a parking scheduling strategy is determined, and compensation based on parking turnover time exists in the parking scheduling strategy; and transmitting the parking scheduling strategy to a garage intelligent terminal, generating parking guide information and parking control information, and performing three-dimensional intelligent parking management. The technical problems of low parking scheduling efficiency and unreasonable parking resource allocation in the prior art are solved, and the technical effects of improving the parking efficiency, optimizing the parking resource allocation and further improving the user experience are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of parking scheduling, and in particular to a scheduling optimization method and system for three-dimensional intelligent parking. Background Art

[0002] With the acceleration of urbanization, the number of vehicles in cities continues to grow, and the problem of parking difficulties is becoming increasingly serious. Due to limited space and backward scheduling methods, traditional parking lots are unable to efficiently utilize existing resources, often leading to parking space waste, low parking efficiency, and long vehicle detention time. In addition, existing parking management systems usually rely on manual or simple fixed rules to allocate parking spaces, lack intelligent dynamic scheduling capabilities, and are difficult to adapt to complex scenarios with peak traffic flow, diversified vehicle models, and rapidly changing parking needs. Especially in multi-story or three-dimensional parking lots, the scheduling and guidance process of vehicles needs to consider the distribution of three-dimensional space and dynamically updated parking conditions, which further increases the complexity of parking management. Summary of the invention

[0003] The present application provides a scheduling optimization method and system for three-dimensional intelligent parking, which solves the technical problems of low parking scheduling efficiency and unreasonable parking resource allocation in the prior art.

[0004] In view of the above problems, the present application provides a scheduling optimization method and system for three-dimensional intelligent parking.

[0005] In a first aspect of the present application, a scheduling optimization method for three-dimensional intelligent parking is provided, the method comprising:

[0006] As the target vehicle enters the garage, the vehicle identity information is determined through front-end sensor collection, wherein the vehicle identity information at least includes the license plate number and the vehicle model; a three-dimensional simulation diagram of the three-dimensional parking lot is constructed, and a parking scheduling model is constructed, wherein the three-dimensional simulation diagram is updated in real time with the parking distribution; the vehicle identity information is identified, and parking decisions are made based on the parking scheduling model, and a parking scheduling strategy is determined, wherein the parking scheduling strategy includes compensation based on the parking turnaround time; the parking scheduling strategy is transmitted to the garage intelligent terminal, and parking guidance information and parking control information are generated to perform three-dimensional intelligent parking management.

[0007] The second aspect of the present application provides a scheduling optimization system for three-dimensional intelligent parking, the system comprising:

[0008] Data acquisition module: as the target vehicle enters the garage, the vehicle identity information is determined through front-end sensor collection, wherein the vehicle identity information at least includes the license plate number and vehicle model; model construction module: constructs a three-dimensional simulation diagram of the three-dimensional parking lot and a parking scheduling model, wherein the three-dimensional simulation diagram is updated in real time with the parking distribution; decision generation module: identifies the vehicle identity information, makes parking decisions based on the parking scheduling model, and determines the parking scheduling strategy, wherein the parking scheduling strategy includes compensation based on the parking turnaround time; parking management module: transmits the parking scheduling strategy to the garage intelligent terminal, generates parking guidance information and parking control information, and performs three-dimensional intelligent parking management.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, as the target vehicle enters the garage, the vehicle identity information is determined through front-end sensor collection, where the vehicle identity information at least includes the license plate number and vehicle model. Next, a three-dimensional simulation diagram of the three-dimensional parking lot is constructed, and a parking scheduling model is constructed, where the three-dimensional simulation diagram is updated in real time with the parking distribution. Then, the vehicle identity information is identified, and parking decisions are made based on the parking scheduling model to determine the parking scheduling strategy, where the parking scheduling strategy has compensation based on the parking turnaround time. Finally, the parking scheduling strategy is transmitted to the garage intelligent terminal, and parking guidance information and parking control information are generated to perform three-dimensional intelligent parking management. The technical problems of low parking scheduling efficiency and unreasonable parking resource allocation in the prior art are solved, and the technical effects of improving parking efficiency, optimizing parking resource allocation, and thus improving user experience are achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic flow chart of a scheduling optimization method for three-dimensional intelligent parking provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of a scheduling optimization system for three-dimensional intelligent parking provided in an embodiment of the present application.

[0014] Explanation of the accompanying drawings: data collection module 11, model building module 12, decision making module 13, parking management module 14. DETAILED DESCRIPTION

[0015] The present application solves the technical problems of low parking scheduling efficiency and unreasonable parking resource allocation in the prior art by providing a scheduling optimization method and system for three-dimensional intelligent parking.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0018] Embodiment 1, as Figure 1 As shown, the present application provides a scheduling optimization method for three-dimensional intelligent parking, wherein the method includes:

[0019] As the target vehicle enters the warehouse, the vehicle identity information is determined through front-end sensor collection, wherein the vehicle identity information at least includes the license plate number and vehicle model.

[0020] When the target vehicle enters the entrance of the parking lot, the system collects real-time information about the vehicle through the deployed front-end sensor equipment, including license plate recognition cameras and vehicle model recognition devices. The license plate recognition camera quickly captures and analyzes the license plate number based on image processing algorithms and deep learning models, thereby accurately obtaining the unique identity information of the vehicle. At the same time, the vehicle model recognition device extracts the features of the vehicle appearance and matches them with the vehicle model data in the database to identify the type of vehicle, such as SUV, sedan or truck, as well as the specific size and related attributes of the vehicle. This vehicle identity information not only provides a basis for the allocation of parking spaces in the parking lot, but also optimizes the dynamic adjustment of vehicle parking in combination with the scheduling needs of the parking lot.

[0021] A three-dimensional simulation diagram of a stereoscopic parking lot is constructed, and a parking scheduling model is constructed, wherein the three-dimensional simulation diagram is updated in real time with the parking distribution.

[0022] By constructing a three-dimensional simulation map and a parking scheduling model, dynamic management and visualization of spatial resources in the parking lot can be achieved. Specifically, laser scanning, depth cameras, ultrasonic sensors and other sensing devices are used to collect comprehensive data on the physical space structure of the parking lot, and obtain information such as the three-dimensional spatial coordinates, parking space distribution, channel layout and vehicle parking status of the parking lot; based on these data, a real-time three-dimensional simulation map of the parking lot is generated using three-dimensional modeling technology to truly present the multi-layered layout of the parking lot, the available parking spaces and the dynamic distribution of vehicles. At the same time, a parking scheduling model is constructed in combination with the three-dimensional simulation map. The parking scheduling model uses the spatial structure characteristics of the parking lot and the dynamic data of vehicles to dynamically allocate parking spaces and plan paths through optimization algorithms (such as ant colony algorithms, genetic algorithms, etc.). The three-dimensional simulation map can be updated in real time with the entry and exit of vehicles in the parking lot, the occupancy status of parking spaces and the changes in parking distribution, ensuring that the scheduling model always runs based on the latest parking lot status.

[0023] Furthermore, before constructing the three-dimensional simulation diagram of the stereoscopic parking lot, the following steps are included:

[0024] Perform a three-dimensional spatial scan of the garage to determine parking space distribution information; traverse the parking space distribution information, read parking space geometry information, match the parking space geometry information with the vehicle size, and determine a matching result; and identify the parking space distribution information based on the matching result.

[0025] Before constructing a three-dimensional simulation diagram of a three-dimensional parking lot, the three-dimensional space of the garage is fully scanned by using a laser radar, a depth camera or other three-dimensional scanning equipment to collect the three-dimensional spatial data of the garage, obtain the relevant information such as the building structure, parking space location, lane width, and column location in the parking lot, and generate the parking space distribution information in the parking lot through these scanning data, including the specific location, direction, size, and status (free or occupied) of each parking space. The collected parking space distribution information is traversed one by one, and the geometric information of each parking space is read, including the length, width, and height of the parking space, the available space, and the distribution of surrounding obstacles. On this basis, combined with the vehicle size information (such as length, width, height, etc.), the parking space geometry information is accurately matched with the vehicle size to determine which parking spaces are suitable for parking the current target vehicle. For example, for larger SUV models, only parking spaces with ample space and close to wider passages are matched; for small cars, compact parking spaces are matched first to improve the overall space utilization. After the matching result is determined, the parking space distribution information is marked based on the matching result. For example, a parking space that is vacant and matches the current vehicle can be marked as green, a parking space that is vacant but does not match the current vehicle can be marked as yellow, and an occupied parking space can be marked as red.

[0026] The vehicle identity information is identified, a parking decision is made based on the parking scheduling model, and a parking scheduling strategy is determined, wherein the parking scheduling strategy includes compensation based on parking turnaround time.

[0027] After identifying the vehicle identity information, parking decisions are made based on the parking scheduling model, which comprehensively considers factors such as the matching degree between vehicles and parking spaces, parking efficiency, overall parking lot utilization, and special needs to determine the best parking scheduling strategy. Specifically, the matching degree between vehicles and parking spaces is ensured by analyzing the geometric dimensions of parking spaces and vehicle dimensions, parking efficiency is improved by optimizing vehicle driving paths and shortening parking time, and parking lot utilization is avoided by reasonably distributing vehicles to avoid excessive concentration in different areas. At the same time, a compensation mechanism based on parking turnover time is introduced. By analyzing historical data and real-time dynamics, the parking time of the target vehicle is predicted, and the allocation strategy is dynamically adjusted according to the current parking space occupancy rate and historical turnover time of the parking lot. For example, short-term parking vehicles are given priority to parking spaces close to the exit to reduce driving time, while long-term parking vehicles are arranged in parking spaces away from the main channel or high-traffic areas to improve turnover efficiency.

[0028] Furthermore, based on the parking scheduling model, parking decisions are made and parking scheduling strategies are determined, including:

[0029] According to the three-dimensional simulation diagram, a prepared parking space is determined, wherein the prepared parking space is an idle parking space; according to the vehicle model, a vehicle size is determined; according to the vehicle size, the prepared parking space is screened to determine an alternative parking space; a parking decision is made for the alternative parking space to determine the parking scheduling strategy.

[0030] Specifically, based on the real-time updated three-dimensional simulation map, all idle parking spaces in the parking lot are identified and marked as reserve parking spaces. These parking spaces are the basic candidate parking spaces that can currently be used for parking vehicles. Combined with the vehicle model data in the identified vehicle identity information, the size information of the vehicle is calculated and determined, including key parameters such as the length, width and height of the vehicle. The reserve parking spaces are screened according to the vehicle size, and parking spaces that cannot accommodate the vehicle are eliminated, such as parking spaces with insufficient length, limited width, or obstacles around the parking spaces, and finally a group of reserve parking spaces that meet the vehicle size requirements are generated. For the selected reserve parking spaces, the parking scheduling model is further combined to make parking decisions, comprehensively considering the distribution of parking spaces, distances from entrances and exits, parking turnover time, parking space utilization, and special needs of vehicles (such as electric vehicle charging needs or proximity to elevators, etc.), and the optimal parking scheduling strategy is determined through weight calculation and optimization algorithms.

[0031] Furthermore, making a parking decision for the candidate parking space and determining the parking scheduling strategy includes:

[0032] Based on the principle of proximity, a group of parking spaces based on the alternative parking spaces is determined, wherein the group of parking spaces is N parking spaces that meet the proximity priority. For the group of parking spaces, concurrent parking collision analysis and compensation based on parking turnaround time are performed to determine the parking scheduling strategy.

[0033] Preferably, based on the principle of proximity, a group of parking spaces is selected from the candidate parking spaces to ensure that the location of this group of parking spaces is close to the current entrance of the vehicle or other designated areas (such as the parking area preferred by the owner) to meet the requirement of proximity priority. Specifically, the spatial distance between each candidate parking space and the vehicle is calculated according to the current position of the vehicle, and the distances are sorted from near to far, and finally N parking spaces that meet the proximity priority are selected to form a group of parking space sets. Next, for this group of parking spaces, a concurrent parking collision analysis is performed, and the path conflicts or congestion that may occur when multiple vehicles park at adjacent or close parking spaces at the same time are evaluated in combination with the real-time dynamic information of other vehicles in the parking lot, so as to ensure that the scheduling strategy will not cause parking path conflicts during execution. At the same time, this group of parking spaces is also optimized and adjusted based on the compensation mechanism of parking turnover time, that is, by analyzing historical parking data and real-time dynamics, the parking turnover time of each parking space is predicted, and the strategy of short-term parking priority close to the exit and long-term parking distribution away from the main channel is dynamically optimized. Based on the above analysis results, the optimal parking scheduling strategy is finally determined to allocate the target vehicles to the best parking spaces that meet the proximity principle, avoid path conflicts and are optimized after turnaround time compensation, so as to achieve efficient utilization of parking resources and intelligent management of vehicle parking processes.

[0034] Furthermore, for the group of parking spaces, concurrent parking collision analysis and compensation based on parking turnaround time are performed, including:

[0035] A collision avoidance analysis is performed on the one group of parking spaces under concurrent parking to determine two groups of parking spaces, wherein the concurrent parking refers to vehicles that have parking needs within a preset time interval, and the two groups of parking are ∈ one group of parking spaces; based on the parking turnover function, the two groups of parking spaces are screened to determine the target parking space.

[0036] Specifically, a collision avoidance analysis is performed on a group of parking spaces under concurrent parking. Concurrent parking refers to the situation where multiple vehicles have parking needs at the same time within a preset time interval, which may lead to path conflicts or competition in parking space allocation. To this end, based on the real-time vehicle dynamic information in the parking lot, combined with the driving path, arrival time and parking space distribution of each vehicle, the path overlap and parking space conflicts that may occur during the driving process of multiple vehicles are predicted. Through the collision avoidance algorithm, these potential conflicts are analyzed and the parking space allocation strategy is readjusted to avoid multiple vehicles competing for adjacent parking spaces or shared channel resources at the same time. Finally, two groups of parking spaces that have been analyzed after avoidance analysis are selected from a group of parking spaces, that is, the set of parking spaces that minimize path conflicts under concurrent parking conditions.

[0037] The two groups of parking spaces are further screened based on the parking turnover function to determine the final target parking space. The parking turnover function is an optimization model defined based on the historical data of the parking lot and the current status of the vehicle, which is used to predict the parking time of each parking space and its impact on the utilization rate of parking lot resources. The parking turnover function comprehensively considers the following factors: the historical turnover time distribution of the parking space, the expected parking time of the vehicle, the distance between the parking space location and the main passage of the parking lot, etc. By calculating and sorting the parking turnover time of the two groups of parking spaces, priority is given to parking spaces with higher parking turnover efficiency. For example, short-term parking vehicles are preferentially allocated to parking spaces close to passages or exits, while long-term parking vehicles are allocated to areas away from the main passages to reduce the occupancy of high-demand parking spaces.

[0038] Furthermore, before screening the two groups of parking spaces based on the parking turnover function, the following steps are performed:

[0039] Determine a three-dimensional parking cycle, wherein the three-dimensional parking cycle is based on a time span for a three-dimensional parking component to complete a group of three-dimensional parking, and the three-dimensional parking component at least includes a lifting plate and a vehicle loading plate; construct a parking turnover function based on the three-dimensional parking cycle; and perform parking space decision constraints based on the parking turnover function.

[0040] Before screening the two groups of parking spaces based on the parking turnover function, the three-dimensional parking cycle is first determined as the basic parameter for parking scheduling optimization. The three-dimensional parking cycle is the time span required for a group of three-dimensional parking components in the parking lot to complete a complete parking operation; the three-dimensional parking components at least include a lifting plate and a vehicle loading plate, where the lifting plate is responsible for lifting the vehicle to the target parking layer in the multi-story three-dimensional parking lot, and the vehicle loading plate completes the accurate placement of the vehicle on the parking space. By calculating the lifting time of the lifting plate, the moving time of the vehicle loading plate, and the possible waiting time, the specific value of the parking cycle is obtained.

[0041] Based on this three-dimensional parking cycle, the system constructs a parking turnover function, which comprehensively considers the parking cycle, the distance from the parking space to the entrance and exit, historical parking turnover data, and the estimated parking time of the vehicle to optimize the utilization efficiency of parking resources.

[0042] The parking turnover function is defined as: T = α·C + β·D + γ·H, where T represents the turnover efficiency score of the parking space, C is the three-dimensional parking cycle (i.e., the sum of the operation time of the lifting plate and the loading plate), D is the distance from the parking space to the entrance or main passage, H is the average parking time of the parking space in the historical turnover data, and α, β, and γ are weight coefficients used to adjust the impact of different factors according to specific scenarios. Based on the parking turnover function, constraints are imposed on the allocation of parking spaces. By analyzing the turnover efficiency scores of parking spaces, high-scoring parking spaces are selected to meet the parking needs of vehicles. For example, short-term parking vehicles are given priority in parking spaces close to exits with short turnover times, while long-term parking vehicles are allocated to areas away from main passages to ensure efficient use of parking resources and balance of regional circulation.

[0043] The parking scheduling strategy is transmitted to the garage intelligent terminal to generate parking guidance information and parking control information to perform three-dimensional intelligent parking management.

[0044] After the parking scheduling strategy is formulated, the parking scheduling strategy is transmitted to the garage intelligent terminal to ensure the execution of the scheduling strategy and the real-time nature of parking management. Specifically, the parking scheduling strategy includes target parking space allocation information, vehicle path planning information, and related operation instructions. After being transmitted to the intelligent terminal, the intelligent terminal generates parking guidance information and parking control information according to the strategy. The parking guidance information includes the driving path planning, target parking space location, and dynamic navigation instructions after the vehicle enters the parking lot, which are pushed to the owner in real time through voice prompts, LED display screens, or mobile applications to ensure that the owner can quickly find the target parking space and reduce the time wasted due to parking confusion. At the same time, the intelligent terminal generates parking control information for controlling the operation process of three-dimensional parking components (such as lifting plates and vehicle loading plates). Specifically, the parking control information includes lifting instructions, vehicle loading plate movement instructions, and parking space locking or release instructions, through which the vehicle can achieve full automation from the parking entrance to the target parking space.

[0045] Furthermore, the generating of parking guidance information and parking control information to perform three-dimensional intelligent parking management includes:

[0046] According to the parking scheduling strategy, parking guidance information and parking control information are generated; the parking guidance information is transmitted to the target vehicle terminal to provide user parking guidance; when the target vehicle reaches the preset parking position, based on the parking control information, the three-dimensional parking structure is controlled to manage the parking of the target vehicle at the preset parking position.

[0047] Specifically, parking guidance information and parking control information are generated according to the parking scheduling strategy, wherein the parking guidance information includes the specific location of the target parking space, the optimal driving path and real-time navigation instructions, while the parking control information includes control instructions for the three-dimensional parking components, such as the lifting and lowering operation of the lifting plate, the horizontal movement instructions of the vehicle loading plate and the switching of the parking space locking or release state. The parking guidance information is transmitted to the target vehicle terminal (such as the vehicle navigation system, the owner's mobile phone application or the LED display screen in the parking lot) through wireless communication (such as Bluetooth or Internet of Things devices), providing the owner with real-time parking guidance to ensure that it can quickly and accurately drive to the preset parking position. When the target vehicle arrives at the preset parking position, the system automatically triggers the execution of the parking control information, and completes the parking operation of the vehicle from the current stop point to the target parking space by intelligently controlling the three-dimensional parking components (such as the lifting plate and the vehicle loading plate). For example, the lifting plate moves vertically according to the parking layer where the target parking space is located, and the vehicle loading plate moves horizontally to accurately park the vehicle, and at the same time dynamically adjusts related operations to ensure the safe parking of the vehicle. By combining parking guidance information with parking control information, the system realizes intelligent management of the entire process from user parking guidance to automatic control of three-dimensional parking components, which not only improves the utilization efficiency of parking resources, but also provides users with a convenient and efficient parking experience.

[0048] In summary, the embodiments of the present application have at least the following technical effects:

[0049] First, as the target vehicle enters the garage, the vehicle identity information is determined through front-end sensor collection, where the vehicle identity information at least includes the license plate number and vehicle model. Next, a three-dimensional simulation diagram of the three-dimensional parking lot is constructed, and a parking scheduling model is constructed, where the three-dimensional simulation diagram is updated in real time with the parking distribution. Then, the vehicle identity information is identified, and parking decisions are made based on the parking scheduling model to determine the parking scheduling strategy, where the parking scheduling strategy has compensation based on the parking turnaround time. Finally, the parking scheduling strategy is transmitted to the garage intelligent terminal, and parking guidance information and parking control information are generated to perform three-dimensional intelligent parking management. The technical problems of low parking scheduling efficiency and unreasonable parking resource allocation in the prior art are solved, and the technical effects of improving parking efficiency, optimizing parking resource allocation, and thus improving user experience are achieved.

[0050] Embodiment 2, based on the same inventive concept as the scheduling optimization method for three-dimensional intelligent parking in the above embodiment, Figure 2 As shown, the present application provides a scheduling optimization system for three-dimensional intelligent parking, wherein the system includes:

[0051] Data acquisition module 11: As the target vehicle enters the garage, the vehicle identity information is determined by front-end sensor collection, wherein the vehicle identity information at least includes the license plate number and the vehicle model; model construction module 12: constructs a three-dimensional simulation diagram of the three-dimensional parking lot and a parking scheduling model, wherein the three-dimensional simulation diagram is updated in real time with the parking distribution; decision generation module 13: identifies the vehicle identity information, makes parking decisions based on the parking scheduling model, and determines the parking scheduling strategy, wherein the parking scheduling strategy includes compensation based on the parking turnaround time; parking management module 14: transmits the parking scheduling strategy to the garage intelligent terminal, generates parking guidance information and parking control information, and performs three-dimensional intelligent parking management.

[0052] Furthermore, the decision generation module 13 is used to execute the following method:

[0053] According to the three-dimensional simulation diagram, a prepared parking space is determined, wherein the prepared parking space is an idle parking space; according to the vehicle model, a vehicle size is determined; according to the vehicle size, the prepared parking space is screened to determine an alternative parking space; a parking decision is made for the alternative parking space to determine the parking scheduling strategy.

[0054] Furthermore, the decision generation module 13 is used to execute the following method:

[0055] Based on the principle of proximity, a group of parking spaces based on the alternative parking spaces is determined, wherein the group of parking spaces is N parking spaces that meet the proximity priority. For the group of parking spaces, concurrent parking collision analysis and compensation based on parking turnaround time are performed to determine the parking scheduling strategy.

[0056] Furthermore, the decision generation module 13 is used to execute the following method:

[0057] A collision avoidance analysis is performed on the one group of parking spaces under concurrent parking to determine two groups of parking spaces, wherein the concurrent parking refers to vehicles that have parking needs within a preset time interval, and the two groups of parking are ∈ one group of parking spaces; based on the parking turnover function, the two groups of parking spaces are screened to determine the target parking space.

[0058] Furthermore, the decision generation module 13 is used to execute the following method:

[0059] Determine a three-dimensional parking cycle, wherein the three-dimensional parking cycle is based on a time span for a three-dimensional parking component to complete a group of three-dimensional parking, and the three-dimensional parking component at least includes a lifting plate and a vehicle loading plate; construct a parking turnover function based on the three-dimensional parking cycle; and perform parking space decision constraints based on the parking turnover function.

[0060] Furthermore, the parking management module 14 is used to execute the following method:

[0061] According to the parking scheduling strategy, parking guidance information and parking control information are generated; the parking guidance information is transmitted to the target vehicle terminal to provide user parking guidance; when the target vehicle reaches the preset parking position, based on the parking control information, the three-dimensional parking structure is controlled to manage the parking of the target vehicle at the preset parking position.

[0062] Furthermore, the model building module 12 is used to execute the following method:

[0063] Perform a three-dimensional spatial scan of the garage to determine parking space distribution information; traverse the parking space distribution information, read parking space geometry information, match the parking space geometry information with the vehicle size, and determine a matching result; and identify the parking space distribution information based on the matching result.

[0064] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0065] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0066] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A scheduling optimization method for three-dimensional intelligent parking, characterized in that: The method comprises: As the target vehicle enters the warehouse, the vehicle identity information is determined by front-end sensor collection, wherein the vehicle identity information at least includes the license plate number and the vehicle model; Constructing a three-dimensional simulation diagram of a three-dimensional parking lot and a parking scheduling model, wherein the three-dimensional simulation diagram is updated in real time with the parking distribution; Identify the vehicle identity information, make parking decisions based on the parking scheduling model, and determine a parking scheduling strategy, wherein the parking scheduling strategy includes compensation based on parking turnaround time; The parking scheduling strategy is transmitted to the garage intelligent terminal to generate parking guidance information and parking control information to perform three-dimensional intelligent parking management.

2. The scheduling optimization method for three-dimensional intelligent parking according to claim 1, characterized in that: Based on the parking scheduling model, parking decisions are made and parking scheduling strategies are determined, including: Determine a prepared parking space according to the three-dimensional simulation diagram, wherein the prepared parking space is an idle parking space; Determine the vehicle size based on the vehicle model; Screening the prepared parking spaces according to the size of the vehicle to determine the candidate parking spaces; A parking decision is made for the candidate parking spaces to determine the parking scheduling strategy.

3. The scheduling optimization method for three-dimensional intelligent parking according to claim 2, characterized in that: Making a parking decision for the candidate parking spaces and determining the parking scheduling strategy include: Based on the principle of proximity, determining a group of parking spaces based on the candidate parking spaces, wherein the group of parking spaces is N parking spaces that meet the proximity priority; For the group of parking spaces, concurrent parking collision analysis and compensation based on parking turnaround time are performed to determine the parking scheduling strategy.

4. The scheduling optimization method for three-dimensional intelligent parking according to claim 3, characterized in that: For the group of parking spaces, concurrent parking collision analysis and compensation based on parking turnaround time are performed, including: Performing collision avoidance analysis under concurrent parking on the one group of parking spaces to determine two groups of parking spaces, wherein the concurrent parking is vehicles that have parking requirements within a preset time interval, and the two groups of parking are ∈ one group of parking spaces; Based on the parking turnover function, the two groups of parking spaces are screened to determine a target parking space.

5. The scheduling optimization method for three-dimensional intelligent parking according to claim 4, characterized in that: Before screening the two groups of parking spaces based on the parking turnover function, the following steps are performed: Determine a three-dimensional parking cycle, wherein the three-dimensional parking cycle is based on a time span for a three-dimensional parking component to complete a set of three-dimensional parking, and the three-dimensional parking component at least includes a lifting plate and a vehicle loading plate; Based on the three-dimensional parking cycle, construct a parking turnover function; Based on the parking turnover function, parking space decision constraints are performed.

6. The scheduling optimization method for three-dimensional intelligent parking according to claim 5, characterized in that: The generating of parking guidance information and parking control information to perform three-dimensional intelligent parking management includes: Generate parking guidance information and parking control information according to the parking scheduling strategy; Transmitting the parking guidance information to the target vehicle terminal to provide parking guidance to the user; When the target vehicle reaches a preset parking position, the three-dimensional parking structure is controlled based on the parking control information to perform parking management on the target vehicle at the preset parking position.

7. The scheduling optimization method for three-dimensional intelligent parking according to claim 1, characterized in that: Before constructing the 3D simulation diagram of the stereo parking lot, it includes: Conduct three-dimensional space scanning of the garage to determine the parking space distribution information; Traversing the parking space distribution information, reading the parking space geometry information, matching the parking space geometry information with the vehicle size, and determining a matching result; Based on the matching result, the parking space distribution information is marked.

8. A dispatching optimization system for three-dimensional intelligent parking, characterized in that: A system for implementing the scheduling optimization method for three-dimensional intelligent parking according to any one of claims 1 to 7, the system comprising: Data collection module: As the target vehicle enters the warehouse, the vehicle identity information is determined through front-end sensor collection, where the vehicle identity information at least includes the license plate number and vehicle model; Model building module: construct a three-dimensional simulation diagram of the three-dimensional parking lot and a parking scheduling model, wherein the three-dimensional simulation diagram is updated in real time with the parking distribution; A decision generation module: identifying the vehicle identity information, making parking decisions based on the parking scheduling model, and determining a parking scheduling strategy, wherein the parking scheduling strategy includes compensation based on parking turnaround time; Parking management module: transmits the parking scheduling strategy to the garage intelligent terminal, generates parking guidance information and parking control information, and performs three-dimensional intelligent parking management.

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