Intelligent parking method for parking hall and related equipment

Abstract

The invention provides an intelligent parking method for a parking hall and related equipment, and relates to the technical field of intelligent parking, and the method comprises the steps: carrying out the parking space suitability analysis based on a vehicle detection matrix, and obtaining a detection result, the vehicle detection matrix being determined based on the quality features and geometric features of vehicles; under the condition that the detection result meets the preset condition of the parking space, the vehicle is driven into a parking hall for initial parking; and controlling the vehicle to enter a preset position based on the initial parking position and orientation to complete the parking process.

Description

Technical Field

[0001] The present application relates to the field of smart parking technology, and in particular to an intelligent parking method and related equipment for a parking hall. Background Art

[0002] With the acceleration of urbanization, the demand for urban parking is increasing. Traditional parking methods can no longer meet the needs of modern cities for parking efficiency and space utilization. As an efficient parking solution, mechanical three-dimensional parking equipment has received widespread attention and application in solving urban parking problems in recent years.

[0003] At present, many mechanical three-dimensional parking systems rely on mechanical equipment such as turntables and lifting platforms to adjust the position and orientation of vehicles. However, the adjustment accuracy of these devices is usually limited, and it often takes multiple adjustments to accurately park the vehicle. This inefficient adjustment process not only prolongs the waiting time of the garage, but also makes it difficult for high-flow, high-frequency garage applications to meet actual needs, limiting its application in modern cities. In addition, vehicle shape detection in traditional garages usually occurs inside the car hall. When the vehicle shape does not meet the parking space requirements, the driver often needs to drive the vehicle out of the car hall for adjustment, which increases the cumbersomeness and time waste of the parking process. Many existing mechanical garage systems still rely on manual guidance, especially for drivers who are not familiar with the system, who need manual assistance to complete the adjustment of vehicle positioning and orientation. This not only increases the complexity of the operation, but also significantly increases the maintenance cost of the system and its dependence on manual labor. Therefore, there is an urgent need for an intelligent parking method for parking halls to solve the above-mentioned problems. Summary of the invention

[0004] A series of simplified concepts are introduced in the Summary of the Invention section, which will be further described in detail in the Detailed Description of the Invention section. The Summary of the Invention section of this application does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0005] In a first aspect, the present application provides an intelligent parking method for a parking hall, comprising:

[0006] Performing parking space adaptability analysis based on a vehicle detection matrix to obtain a detection result, wherein the vehicle detection matrix is ​​determined based on mass characteristics and geometric characteristics of the vehicle;

[0007] When the above detection results meet the preset conditions of the parking space, the vehicle enters the parking hall for initial parking;

[0008] Based on the initial parking position and orientation, the vehicle is controlled to enter the preset position to complete the parking process, wherein the vehicle control is achieved through the vehicle loading platform at the bottom of the vehicle.

[0009] In a feasible implementation manner, the above parking space adaptability analysis is performed based on the vehicle detection matrix to obtain the detection results, including:

[0010] Using a pressure sensor to obtain the actual mass of the vehicle, the above mass characteristics are obtained;

[0011] The length, width and height of the vehicle are measured using holographic spectral imaging method to obtain the above-mentioned geometric features;

[0012] Based on the quality features and the geometric features, generate the detection matrix;

[0013] Based on the above detection matrix and the spatial parameter vector of the parking hall, it is determined whether the vehicle meets the current parking space conditions and the detection result is obtained.

[0014] In a feasible implementation manner, the above-mentioned determination of whether the vehicle meets the current parking space conditions based on the above-mentioned detection matrix and the spatial parameter vector of the parking hall, and obtaining the detection result, includes:

[0015] Based on the difference between the detection matrix and each parameter in the spatial parameter vector of the parking hall, an adaptability vector is obtained, wherein the difference is calculated based on an adaptability function, and the adaptability function is a step function that sets a tolerance range;

[0016] Based on the above adaptability vector, the detection result is obtained.

[0017] In a feasible implementation, it also includes:

[0018] When the above detection results do not meet the preset conditions of the parking space, the vehicle enters the ground parking lot to perform the parking operation.

[0019] In a feasible implementation manner, the above-mentioned control of the vehicle into a preset position based on the initial parking position and orientation to complete the parking process includes:

[0020] Based on the initial parking position and orientation, calculating the deviation of the vehicle position from the preset position;

[0021] Based on the sliding mode control algorithm, according to the above deviation and deviation change rate, the vehicle loading platform action is dynamically adjusted to guide the vehicle to move to the preset position;

[0022] When the deviation between the current vehicle position and the preset position is less than a preset value, the parking process ends and the vehicle completes parking.

[0023] In a feasible implementation, it also includes:

[0024] Deep reinforcement learning algorithm is introduced to optimize the control strategy of the vehicle parking process.

[0025] In a feasible implementation, it also includes:

[0026] Real-time monitoring of temperature and humidity changes, lighting conditions and air quality inside the parking hall, and adjustment of the control strategy of the vehicle parking process according to environmental parameters.

[0027] In a second aspect, the present application proposes an intelligent parking device for a parking hall, comprising:

[0028] A vehicle detection unit, used to perform parking space adaptability analysis based on a vehicle detection matrix to obtain a detection result, wherein the vehicle detection matrix is ​​determined based on mass characteristics and geometric characteristics of the vehicle;

[0029] The initial parking unit is used for the vehicle to enter the parking hall for initial parking when the above detection result meets the preset conditions of the parking space;

[0030] The vehicle adjustment unit is used to control the vehicle to enter a preset position based on the initial parking position and orientation to complete the parking process, wherein the vehicle control is achieved through the vehicle loading platform at the bottom of the vehicle.

[0031] In a third aspect, an electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is used to implement the steps of the intelligent parking method for a parking hall as described in any one of the first aspects above when executing the computer program stored in the memory.

[0032] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the intelligent parking method for a parking hall as described in any one of the first aspects above is implemented.

[0033] In summary, the embodiments of the present invention make the positioning and orientation adjustment of vehicles in the parking hall more accurate by introducing a vehicle loading workbench and an intelligent control algorithm. By optimizing the control strategy, the precise alignment of the vehicle can be achieved during the adjustment process, thereby greatly improving the parking efficiency and shortening the waiting time, which is particularly suitable for high-flow and high-frequency parking needs. The driver only needs to drive the car into the parking hall without complicated reversing and steering operations, and the system automatically completes the precise positioning and orientation adjustment of the vehicle. This design avoids the cumbersome steps in the traditional system where the driver needs to drive out of the parking hall again or rely on manual guidance, greatly reduces the need for manual intervention, reduces the complexity of operation, and improves the user experience. Combined with the environmental perception system, the temperature, humidity, light and other environmental changes inside the parking hall are monitored in real time, and the control strategy of the parking process is dynamically adjusted according to these changes. This enables the system to adapt to changes in the parking hall environment, ensure that the vehicle can still be accurately positioned under various complex environmental conditions, and avoid the accumulation of errors caused by changes in environmental factors in the traditional system. Through the intelligent control system, the accuracy and efficiency of the vehicle adjustment process are optimized, manual intervention is reduced, the system's automation level and adaptability are improved, and the convenience and reliability of the parking process are greatly improved. It is particularly suitable for high-frequency and high-flow parking needs in modern cities. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present specification. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0035] Figure 1 A schematic diagram of a flow chart of an intelligent parking method for a parking hall provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of the structure of an intelligent parking device for a parking hall provided in an embodiment of the present application;

[0037] Figure 3 A schematic diagram of an intelligent parking electronic device for a parking hall provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than the content illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0039] See also Figure 1 , is a flow chart of an intelligent parking method for a parking hall provided in an embodiment of the present application, which may specifically include:

[0040] S110, performing parking space adaptability analysis based on a vehicle detection matrix to obtain a detection result, wherein the vehicle detection matrix is ​​determined based on mass characteristics and geometric characteristics of the vehicle;

[0041] Exemplarily, the process of constructing a vehicle detection matrix involves a variety of sensors and data acquisition technologies. High-precision sensors are used to obtain the quality characteristics of each vehicle, including physical parameters such as weight and size. These characteristics not only reflect the basic properties of the vehicle, but also lay the foundation for the reasonable allocation of parking spaces. At the same time, the geometric characteristics of the vehicle, such as shape, volume and height, are extracted through the holographic spectral imaging algorithm. This information is integrated into a multidimensional matrix to form comprehensive vehicle detection data.

[0042] S120: If the above detection result meets the preset conditions of the parking space, the vehicle enters the parking hall for initial parking;

[0043] For example, after the vehicle passes the appearance inspection and other condition inspections and is confirmed to meet the preset conditions of the parking space (such as size, weight, etc.), it can enter the parking hall. During this process, the driver does not need to worry about whether the parking position is correct, because there are no complicated parking equipment or obstacles in the parking hall. The parking hall is designed as a large plane, and the driver only needs to drive the vehicle into the parking hall, and then he can easily get off and leave without reversing or interacting with mechanical equipment. Once the driver gets off and leaves the parking hall, the door of the parking hall closes automatically, and the subsequent vehicle position adjustment is completed by the vehicle loading workbench in the parking hall.

[0044] S130. Based on the initial parking position and orientation, control the vehicle to enter a preset position to complete the parking process, wherein the vehicle control is achieved through a vehicle loading platform at the bottom of the vehicle.

[0045] Exemplarily, the vehicle first enters the parking hall through step S120 and parks at the initial position. At this time, the orientation and position of the vehicle may not be completely aligned with the preset parking space. Once the vehicle stops and the initial parking position is confirmed, the vehicle loading platform in the parking hall begins to take over the adjustment process. The vehicle loading platform controls the bottom support structure of the vehicle and combines the translation and rotation functions to achieve precise adjustment of the vehicle's position and orientation. The vehicle loading platform can flexibly move the vehicle in two-dimensional space, push the vehicle to the target position through the lateral movement function, and use the rotation function to adjust the direction of the vehicle so that it is finally aligned with the inner door of the parking hall. The entire adjustment process is fully automated by the intelligent control system without manual intervention. During the operation, the vehicle loading platform uses precise movement and rotation to park the vehicle quickly and safely in the designated parking space, and ensure that the vehicle's orientation meets the standard requirements of the parking hall. After the adjustment is completed, the vehicle loading platform stops operating, the vehicle is parked smoothly, and the whole process is efficient and stable.

[0046] In some examples, the parking space adaptability analysis based on the vehicle detection matrix is ​​performed to obtain the detection results, including:

[0047] Using a pressure sensor to obtain the actual mass of the vehicle, the above mass characteristics are obtained;

[0048] The length, width and height of the vehicle are measured using holographic spectral imaging method to obtain the above-mentioned geometric features;

[0049] Based on the quality features and the geometric features, generate the detection matrix;

[0050] Based on the above detection matrix and the spatial parameter vector of the parking hall, it is determined whether the vehicle meets the current parking space conditions and the detection results are obtained, including:

[0051] Based on the difference between the detection matrix and each parameter in the spatial parameter vector of the parking hall, an adaptability vector is obtained, wherein the difference is calculated based on an adaptability function, and the adaptability function is a step function that sets a tolerance range;

[0052] Based on the above suitability vector, it is determined whether the vehicle is suitable for the current parking space to obtain a recognition result.

[0053] Exemplarily, when a vehicle enters a parking area, its physical characteristics are accurately measured and analyzed, including:

[0054] Vehicle weight detection is one of the key technologies in intelligent parking systems, providing necessary data support for vehicle adaptability analysis, parking space allocation, and subsequent automatic parking adjustments in parking halls. Pressure sensors realize weighing functions by detecting the pressure generated by the weight of the vehicle on its surface, and are characterized by mature design, low cost, and high accuracy.

[0055] The pressure sensor works based on its internal mechanical strain element or piezoelectric element. When the vehicle's wheel contacts the sensor surface, the sensor converts the pressure signal into an electrical signal, and the weight of the vehicle is calculated through the system's signal processing module. The output signal of the pressure sensor has high linearity and stability, and can work reliably for a long time in various parking environments.

[0056] In order to ensure the accuracy and stability of the measurement, the system needs to calibrate and calibrate the pressure sensor regularly during design. During the calibration process, the sensor is tested with a standard object of known weight to generate a correction coefficient to eliminate errors caused by environmental changes, sensor aging, etc. At the same time, in order to avoid instantaneous fluctuations caused by the dynamic load of the vehicle, the data can be smoothed in combination with a filtering algorithm to improve the stability of the weighing data.

[0057] Pressure sensors are suitable for most environments, including high-traffic parking lots. Their rugged construction is able to withstand frequent vehicle contact and is not susceptible to performance degradation due to external environmental changes (such as humidity or temperature fluctuations). Through installation and protection design, the sensor can continue to provide accurate and reliable weight detection data.

[0058] Use holographic spectral imaging technology to obtain the three-dimensional shape information of the vehicle, and generate an accurate three-dimensional model of the vehicle by analyzing the interference and diffraction of light, including:

[0059] Holographic spectral imaging technology uses the interference and diffraction of light to accurately scan the shape of the vehicle and generate a three-dimensional model of the vehicle. In this way, the system can capture the basic dimensions of the vehicle, such as length, width, and height. The device emits light waves of a specific wavelength, covering the outer surface of the vehicle to form a complete light wave interference pattern; the scanned interference pattern is solved by a computer algorithm and converted into three-dimensional point cloud data, which represents all the geometric surfaces of the vehicle; the point cloud data is processed to generate a three-dimensional shape model of the vehicle, which contains all the key geometric features of the vehicle (length, width, height, etc.).

[0060] Based on the three-dimensional data, the key geometric information of the vehicle is represented as a feature vector, denoted as V. The feature vector summarizes the three-dimensional shape of the vehicle and is expressed as:

[0061] V = [L, W, H] T

[0062] Wherein, L is the length of the vehicle; W is the width of the vehicle; H is the height of the vehicle.

[0063] The feature vector V generated by holographic spectral imaging technology can help the parking system accurately analyze the compatibility of the vehicle and the parking space. The length, width and height information in the feature vector V can be used to determine whether the vehicle can adapt to the space requirements of the target parking space.

[0064] Combining the quality features and geometric features, a high-dimensional detection matrix D is constructed to fully describe the physical characteristics of the vehicle, which is expressed as:

[0065] D = [m, L, W, H] T

[0066] According to the vehicle detection matrix D and the parking hall space parameter vector S, it is judged whether the vehicle is suitable for the current parking space. The parking hall space parameter vector S is expressed as:

[0067] S=[m max , L max ,W max ,H max ] T

[0068] Among them, m max L is the maximum vehicle mass allowed in the parking space; max The maximum length allowed for a parking space; W max The maximum width allowed for a parking space; H max The maximum height allowed for a parking space.

[0069] In order to determine whether the vehicle meets the requirements of the parking space, the adaptability function f is defined adapt (D, S), used to compare the vehicle detection matrix D and the parking hall space parameter vector S, where the adaptability function is expressed as:

[0070] f adapt (D, S) = σ δ (SD)=[σ δ (m max -m), σ δ (L max -L), ..., σ δ (H max -H)] T

[0071] Among them, σ δ (·) is a step function that maps each difference to compliance or non-compliance, expressed as:

[0072]

[0073] If the parameter meets the limit, the output is 1; if the parameter exceeds the limit, the output is 0; a tolerance range δ is introduced on each parameter, indicating that the vehicle is allowed to slightly exceed the limit of the parking space without being directly regarded as unsuitable.

[0074] The difference of each parameter is calculated, and the difference SD between the parking hall parameter vector S and the vehicle detection matrix D is calculated to obtain an adaptability vector, where the adaptability vector represents the remaining space or excess of each parameter. adapt The element value of (D, S) determines whether the vehicle is suitable for the current parking space. If f adapt All elements of (D, S) are 1, indicating that all parameters of the vehicle are within the tolerance range of the parking space and the vehicle is suitable for the current parking space; if f adapt If there is an element of 0 in (D,S), it means that the corresponding parameter exceeds the tolerance range and the vehicle is not suitable for the parking space.

[0075] In some examples, it also includes:

[0076] When the detection result does not meet the preset conditions of the parking space, the vehicle drives into the ground parking lot to perform the parking operation.

[0077] For example, after the vehicle passes the weight detection and appearance detection, if it is found that the vehicle does not meet the preset conditions of the parking space (such as size mismatch, weight exceeding the standard, etc.), the system will automatically identify and refuse to allow it to enter the parking hall. If the test results do not meet the preset conditions, the vehicle will be guided into the ground parking lot. This process relies on the system's real-time monitoring and decision-making of the vehicle status to ensure that the vehicle can be safely parked in a suitable area. Once the vehicle enters the ground parking lot, the parking operation will follow the traditional ground parking process. The driver can choose a suitable parking space to park. Usually, there is no complex automation equipment or position adjustment involved at this time, and the driver needs to complete the parking in the traditional way.

[0078] In some examples, the above-mentioned control of the vehicle into a preset position based on the initial parking position and orientation to complete the parking process includes:

[0079] Based on the initial parking position and orientation, calculating the deviation of the vehicle position from the preset position;

[0080] Based on the sliding mode control algorithm, according to the above deviation and deviation change rate, the vehicle loading platform action is dynamically adjusted to guide the vehicle to move to the preset position;

[0081] When the deviation between the current vehicle position and the preset position is less than a preset value, the parking process ends and the vehicle completes parking.

[0082] Exemplarily, based on the vehicle's initial parking position P0 (x0, y0) and the vehicle's initial orientation θ0, the system first calculates the deviation between the vehicle's current position and the preset target position P'(x', y'). This deviation includes lateral deviation in position and angular deviation in orientation, and this calculation is used to provide a benchmark for subsequent adjustments. Based on the calculated deviation and deviation change rate, the system uses a sliding mode control algorithm to make real-time adjustments to the vehicle carrier workbench. Sliding mode control handles vehicle position deviations by designing appropriate sliding surfaces, so that the control system can quickly and stably guide the vehicle to the preset position. The algorithm dynamically adjusts the rotation angle of the vehicle carrier workbench based on the vehicle's current deviation and deviation change rate. θ and lateral displacement d , in order to minimize the deviation and move the vehicle to the preset position. When the position deviation of the vehicle is less than the preset threshold, the parking process is completed. At this point, the vehicle has been accurately aligned with the inner door of the hall and meets the parking requirements. The system will end the adjustment process and the vehicle's parking task is completed.

[0083] For example, the sliding mode control method is used to design the sliding mode surface to dynamically adjust the action of the vehicle-carrying platform according to the deviation and the deviation change rate to ensure that the system can converge to the target state in a complex environment, which is expressed as:

[0084]

[0085] Among them, λ is the sliding surface adjustment parameter, which controls the speed of deviation convergence; ΔP error (t) represents the deviation between the actual position of the vehicle and the target position.

[0086] u(t)=-K·sign(S(t))

[0087] Among them, u(t) is the real-time correction value obtained based on sliding mode control; K is the control gain; sign(S(t)) is the sign function of the sliding mode controller, which controls the vehicle-carrying workbench to make detailed adjustments.

[0088] The adjustment of the vehicle platform not only considers the lateral displacement d and the rotation angle θ, but also introduces the deviation correction term ΔP adjust (t), ensuring that each adjustment process is optimized, expressed as:

[0089]

[0090] Where P0(x0, y0) is the initial position of the vehicle, θ0 is the initial orientation angle of the vehicle, d is the lateral displacement of the vehicle platform, which indicates the lateral distance when the vehicle platform is translated; d·cos(θ) is the component of the lateral displacement in the x-axis direction; d·sin(θ) is the component of the lateral displacement in the y-axis direction; ΔP adjust(t) is the deviation correction term, which indicates the displacement after the feedback mechanism is adjusted. It represents the correction amount of the current deviation by the control system (including sliding mode control) during the vehicle position adjustment process.

[0091] When the deviation between the current position of the vehicle and the preset parking position is less than the preset threshold, the parking process is completed. At this time, the vehicle loading platform stops adjusting, the vehicle is accurately parked at the preset position, and the entire parking process is completed.

[0092] Exemplarily, the preset parking position is aligned with the inner door of the car hall. During the parking process, the target position of the vehicle does not require precise parking in the center of the parking space, but it is necessary to ensure that the front or rear of the vehicle is facing the inner door of the car hall. This is because the inner door of the car hall is connected to the mechanical garage, and the manipulator in the mechanical garage will enter from the inner door of the car hall and take away the vehicle. When the vehicle is facing the inner door of the car hall, the manipulator in the car hall can easily enter from the inner door of the car hall and accurately grab the vehicle. The manipulator control system is responsible for taking the vehicle out of the car hall and sending the vehicle to the designated position in the mechanical garage through the movement of the manipulator. Due to the close cooperation between the equipment in the car hall and the automated operation of the mechanical garage, after the vehicle enters the target position, the vehicle loading workbench and parking equipment in the car hall will ensure that the vehicle can be aligned with the inner door of the car hall, and then the vehicle will be taken out of the car hall and sent to the mechanical garage for storage through the automated control of the manipulator.

[0093] In some examples, it also includes:

[0094] Deep reinforcement learning algorithm is introduced to optimize the control strategy of the vehicle parking process.

[0095] For example, deep reinforcement learning is a method that combines deep learning and reinforcement learning, which can learn the best control strategy through interaction with the environment in a dynamic environment. During the vehicle parking process, the deep reinforcement learning algorithm can effectively control the precise parking of the vehicle in a complex environment by continuously exploring and optimizing the strategy.

[0096] In the parking system, the agent (vehicle control system) interacts with the environment (parking hall) to perform actions during the parking process (such as vehicle loading platform control, position adjustment, etc.). The goal of the agent is to maximize its cumulative reward, that is, to park the vehicle accurately at the predetermined location and complete the parking process. The environment provides feedback, and based on the actions performed by the agent, rewards or penalties are calculated. The agent uses this feedback information to adjust its behavior.

[0097] During parking, the state space includes information such as the vehicle's current position, orientation, vehicle loading platform position, and preset parking position. Each state represents the specific situation of the vehicle at a certain moment in the parking process. The action space includes various operations for vehicle control, such as rotation, lateral movement, and speed adjustment. The agent selects the best action based on the current state to approach the target parking space.

[0098] In deep reinforcement learning, the reward function is a key part of guiding the learning of the agent. By defining a reasonable reward function, the agent can gradually learn how to optimize the parking process. When the vehicle moves towards the preset parking position, a positive reward is given. When the vehicle deviates from the target position, collides, or parks inaccurately, a negative reward is given. When the vehicle completes parking and aligns with the predetermined position, a higher reward is given, indicating that the task is completed.

[0099] During the training process, the deep reinforcement learning algorithm learns through an exploration-exploitation strategy. The agent first randomly explores the environment, performs some actions, obtains feedback, and updates its strategy. During this process, the agent continuously adjusts its strategy to reduce deviations and improve accuracy during parking. As the training progresses, the agent gradually learns how to adopt the optimal control strategy in different parking environments, allowing the vehicle to complete the parking task more efficiently and accurately.

[0100] The introduction of deep reinforcement learning enables the control strategy in the vehicle parking process to be continuously optimized to adapt to different parking environments and vehicle characteristics. Through continuous learning, the system can adjust itself to cope with uncertainties, external disturbances or vehicle deviations, ensuring a more precise and efficient parking process. During this process, the actions of the vehicle loading platform and other automated equipment will be adjusted according to the strategy of the deep reinforcement learning algorithm, dynamically optimizing the parking path and process, avoiding the limitations of traditional static control methods.

[0101] In some examples, it also includes:

[0102] Real-time monitoring of temperature and humidity changes, lighting conditions and air quality inside the parking hall, and adjustment of the control strategy of the vehicle parking process according to environmental parameters.

[0103] Exemplarily, changes in temperature and humidity inside the parking hall may have an impact on the stability of the vehicle and the operation of the parking equipment. For example, extreme temperature or humidity may affect the accuracy and working efficiency of the vehicle's electronic equipment, control system, and mechanical equipment in the parking hall (such as vehicle loading platforms, sensors, etc.). According to the temperature and humidity monitoring results, if the temperature and humidity values ​​in the parking hall exceed the normal range, the system can automatically adjust the temperature and humidity control system in the parking hall based on feedback. This not only helps to protect the equipment in the car, avoid corrosion of mechanical parts due to excessive humidity, or equipment failure due to excessive temperature, but also creates a more stable environment for the vehicle parking process.

[0104] The lighting conditions in the parking hall directly affect the visibility of the environment and the accuracy of the operation in the parking hall. Too dark an environment may cause visual errors during parking and affect the accuracy of the equipment; while too strong lighting may cause reflection interference from the vehicle's appearance. According to the lighting conditions in the parking hall, the system can adjust the light intensity in the parking hall in real time to ensure visual clarity during parking.

[0105] The air quality in the hall, such as oxygen concentration, carbon dioxide concentration and other harmful gas content, may affect the normal operation of the equipment in the hall, especially the reliability of sensors, control systems and electrical components. When the air quality in the hall is detected to be substandard (for example, the carbon dioxide concentration is too high or the air circulation is poor), the system can start ventilation or air purification devices to ensure that the air quality in the hall remains within an appropriate range, which is not only conducive to the normal operation of the equipment in the hall, but also ensures the safety and reliability of the parking process.

[0106] See also Figure 2 , is a schematic diagram of the structure of an intelligent parking device for a parking hall provided in an embodiment of the present application, comprising:

[0107] A vehicle detection unit 21 is used to perform parking space adaptability analysis based on a vehicle detection matrix to obtain a detection result, wherein the vehicle detection matrix is ​​determined based on mass characteristics and geometric characteristics of the vehicle;

[0108] The initial parking unit 22 is used for the vehicle to enter the parking hall for initial parking when the above detection result meets the preset conditions of the parking space;

[0109] The vehicle adjustment unit 23 is used to control the vehicle to enter a preset position based on the initial parking position and orientation to complete the parking process, wherein the vehicle control is achieved through the vehicle loading platform at the bottom of the vehicle.

[0110] See also Figure 3 The embodiment of the present application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, the steps of any of the above-mentioned methods for intelligent parking in a parking hall are implemented.

[0111] Since the electronic device introduced in this embodiment is a device used to implement the intelligent parking device for the parking hall in the embodiment of the present application, based on the method introduced in the embodiment of the present application, the technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by the technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0112] During the specific implementation process, when the computer program 311 is executed by a processor, any implementation method in the embodiments corresponding to the first aspect can be implemented.

[0113] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0114] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-readable program code.

[0115] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0116] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0118] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes Figure 1 The process of the intelligent parking method for the parking hall in the corresponding embodiment.

[0119] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0120] 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.

[0121] In the several embodiments provided in the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0122] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0124] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0125] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

[0126] Although the preferred embodiments of this specification have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of this specification.

[0127] Obviously, those skilled in the art can make various changes and modifications to this specification without departing from the spirit and scope of this specification. Thus, if these modifications and variations of this specification fall within the scope of the claims of this specification and their equivalents, this specification is also intended to include these modifications and variations.

Claims

1. An intelligent parking method for a parking hall, characterized in that: The method comprises: Performing a parking space adaptability analysis based on a vehicle detection matrix to obtain a detection result, wherein the vehicle detection matrix is ​​determined based on mass characteristics and geometric characteristics of the vehicle; When the detection result meets the preset conditions of the parking space, the vehicle enters the parking hall for initial parking; Based on the initial parking position and orientation, the vehicle is controlled to enter the preset position to complete the parking process, wherein the vehicle control is achieved through the vehicle loading platform at the bottom of the vehicle.

2. The intelligent parking method for a parking hall according to claim 1, characterized in that: The parking space adaptability analysis is performed based on the vehicle detection matrix to obtain the detection results, including: Using a pressure sensor to obtain the actual mass of the vehicle to obtain the mass characteristic; Measuring the length, width and height of the vehicle using a holographic spectral imaging method to obtain the geometric features; generating the detection matrix based on the quality feature and the geometric feature; Based on the detection matrix and the space parameter vector of the parking hall, it is determined whether the vehicle meets the current parking space conditions to obtain a detection result.

3. The intelligent parking method for a parking hall according to claim 2, characterized in that: The method of determining whether the vehicle meets the current parking space conditions based on the detection matrix and the space parameter vector of the parking hall to obtain the detection result includes: Obtaining an adaptability vector based on the difference between the detection matrix and each parameter in the spatial parameter vector of the parking hall, wherein the difference is calculated based on an adaptability function, and the adaptability function is a step function that sets a tolerance range; Based on the adaptability vector, a detection result is obtained.

4. The intelligent parking method for a parking hall according to claim 1, characterized in that: Also includes: When the detection result does not meet the preset conditions of the parking space, the vehicle drives into the ground parking lot to perform the parking operation.

5. The intelligent parking method for a parking hall according to claim 1, characterized in that: The method of controlling the vehicle to enter a preset position based on the initial parking position and orientation to complete the parking process includes: Based on the initial parking position and orientation, calculating the deviation of the vehicle position from the preset position; Based on the sliding mode control algorithm, according to the deviation and the rate of change of the deviation, the action of the vehicle loading platform is dynamically adjusted to guide the vehicle to move to the preset position; When the deviation between the current vehicle position and the preset position is less than a preset value, the parking process ends and the vehicle completes parking.

6. The intelligent parking method for a parking hall according to claim 5, characterized in that: Also includes: Deep reinforcement learning algorithm is introduced to optimize the control strategy of the vehicle parking process.

7. The intelligent parking method for a parking hall according to claim 5, characterized in that: Also includes: Real-time monitoring of temperature and humidity changes, lighting conditions and air quality inside the parking hall, and adjustment of the control strategy of the vehicle parking process according to environmental parameters.

8. An intelligent parking device for a parking hall, characterized in that: include: A vehicle detection unit, used to perform parking space adaptability analysis based on a vehicle detection matrix to obtain a detection result, wherein the vehicle detection matrix is ​​determined based on mass characteristics and geometric characteristics of the vehicle; An initial parking unit, used for driving the vehicle into the parking hall for initial parking when the detection result meets the preset conditions of the parking space; The vehicle adjustment unit is used to control the vehicle to enter a preset position based on the initial parking position and orientation to complete the parking process, wherein the vehicle control is achieved through the vehicle loading platform at the bottom of the vehicle.

9. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is used to implement the steps of the intelligent parking method for a parking hall as described in any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, an intelligent parking method for a parking hall as described in any one of claims 1 to 7 is implemented.

Images