Collaborative parking method and device, electronic equipment and storage medium

Abstract

The invention provides a collaborative parking method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent parking. The method comprises the following steps: acquiring a predicted parking path of each vehicle in a preset scene through a preset rule; whether path conflicts and space occupation conflicts exist among the vehicles or not is detected according to the predicted parking paths, and when the path conflicts and / or the space occupation conflicts exist among the vehicles, the predicted parking paths of the vehicles with the path conflicts and / or the space occupation conflicts are optimized. According to the method, the predicted parking path of each vehicle in the preset scene is obtained through the preset rule, so that the predicted parking path of each vehicle can be determined, information sharing among vehicles of different brands and models can be realized, and then path conflicts and space occupation conflicts among the vehicles are detected according to the predicted parking paths, so that the parking efficiency of the vehicles is improved. At the moment, the predicted parking path is optimized, orderly and efficient parking among multiple vehicles in the parking lot is achieved, and the parking efficiency and the space utilization rate are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent parking technology, and in particular to a collaborative parking method, device, electronic equipment and storage medium. Background Art

[0002] With the acceleration of urbanization and the improvement of residents' living standards, the number of cars has shown a rapid growth trend. However, the ensuing "difficult parking" problem has become a major pain point in urban traffic management. Whether in bustling commercial areas, residential areas, or in public places such as office buildings and hospitals, the shortage of parking spaces and disorderly parking of vehicles are common, seriously affecting traffic order and the quality of life of citizens.

[0003] Traditional independent parking methods often lead to problems such as insufficient space utilization in parking lots, low parking efficiency and traffic congestion. For example, traditional parking lots have low space utilization, there are often large gaps between parking spaces, and the parking area is not compactly planned. Although it is conducive to the entry and exit of vehicles, it also leads to a lot of waste of space and it is impossible to park more vehicles in limited land resources. Low parking efficiency is also a prominent problem of traditional parking methods. Car owners need to spend a lot of time looking for vacant parking spaces in parking lots, especially during peak hours or in busy areas. This situation is even more serious. Repeated detours to find parking spaces not only waste time, but also aggravate traffic congestion in parking lots. Summary of the invention

[0004] The problem solved by the present invention is how to improve parking efficiency and space utilization.

[0005] In order to solve the above problems, the present invention provides a collaborative parking method, device, electronic device and storage medium.

[0006] In a first aspect, the present invention provides a collaborative parking method, comprising:

[0007] Obtain the estimated parking path of each vehicle in a preset scene through preset rules;

[0008] The predicted parking paths are used to detect whether there are path conflicts and space occupancy conflicts between the vehicles. When there are path conflicts and / or space occupancy conflicts between the vehicles, the predicted parking paths of the vehicles with path conflicts and / or space occupancy conflicts are optimized.

[0009] Optionally, obtaining the estimated parking path of each vehicle in the preset scene by using preset rules includes:

[0010] Acquiring key parking parameters of each of the vehicles through a cloud and / or a vehicle communication protocol, wherein the key parking parameters include a position, a speed, a steering angle, and a parking destination of the vehicle;

[0011] Constructing a kinematic model of each of the vehicles according to the kinematic characteristics of each of the vehicles;

[0012] Using a path planning algorithm, generating a preliminary parking path for each of the vehicles according to the kinematic model, the parking destination and the preset scenario;

[0013] The preliminary parking path of each of the vehicles is adjusted according to the position, speed and steering angle of each of the vehicles to determine an estimated parking path of each of the vehicles.

[0014] Optionally, obtaining key parking parameters of each vehicle through the cloud and / or vehicle communication protocol includes:

[0015] When the vehicle does not support communication with the cloud and the vehicle communication protocol, key parking parameters of the vehicle collected by the feature vehicle are obtained through the cloud and / or the vehicle communication protocol, wherein the feature vehicle includes a vehicle whose computing power is sufficient to collect the key parking parameters of the vehicle and supports communication with the cloud and / or the vehicle communication protocol.

[0016] Optionally, detecting whether there is a path conflict and a space occupancy conflict between the vehicles according to the predicted parking path, and when there is a path conflict and / or a space occupancy conflict between the vehicles, optimizing the predicted parking path of the vehicles with the path conflict and / or the space occupancy conflict comprises:

[0017] detecting path conflicts and / or space occupancy conflicts between the vehicles according to the predicted parking path;

[0018] When a parking destination of any of the vehicles is located on an estimated parking path of another vehicle, determining that there is a path conflict between the vehicles;

[0019] When any of the vehicles stays on the estimated parking path of another vehicle, determining that there is a space occupation conflict between the vehicles;

[0020] When the path conflict and / or the space occupancy conflict exists between the vehicles, an optimization algorithm is used to adjust the driving order and driving routes of the vehicles with the path conflict and / or the space occupancy conflict, wherein the optimization algorithm includes global path planning and a priority mechanism, the global path planning is used to determine the optimal path of the vehicles, and the priority mechanism is used to determine the parking priority between the vehicles.

[0021] Optionally, the optimizing the predicted parking path of the vehicle having path conflict and / or space occupancy conflict further includes:

[0022] When any of the vehicles is parked according to the optimized parking path, if the status of other vehicles and / or the preset scene changes, the parking path is optimized again.

[0023] Optionally, the collaborative parking method further includes:

[0024] When any of the vehicles fails to obtain the key parking parameters of other vehicles, the vehicle is controlled to autonomously cruise to a memory parking space through memory parking.

[0025] Optionally, the collaborative parking method further includes:

[0026] Displaying the real-time parking path and parking progress of the vehicle on a user interaction interface;

[0027] Corresponding interaction information is fed back according to the user's operation instructions on the user interaction interface.

[0028] In a second aspect, the present invention provides a collaborative parking device, comprising:

[0029] The first module is used to obtain the estimated parking path of each vehicle in a preset scene through preset rules;

[0030] The second module is used to detect whether there is a path conflict and a space occupancy conflict between the vehicles according to the predicted parking path, and when there is a path conflict and / or a space occupancy conflict between the vehicles, optimize the predicted parking path of the vehicles with the path conflict and / or the space occupancy conflict.

[0031] In a third aspect, the present invention provides an electronic device, including a memory and a processor;

[0032] The memory is used to store computer programs;

[0033] The processor is used to implement the collaborative parking method as described in the first aspect when executing the computer program.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the collaborative parking method as described in the first aspect is implemented.

[0035] The beneficial effects of the collaborative parking method of the present invention are as follows: first, the predicted parking path of each vehicle in a preset scene is obtained through preset rules, such as obtaining key parking parameters of other vehicles in the parking lot from the cloud, or obtaining key parking parameters of other vehicles through a vehicle communication protocol, so that the predicted parking path of each vehicle can be determined, and information sharing between vehicles of different brands and models can be achieved. Then, path conflicts and space occupancy conflicts between vehicles are detected based on the predicted parking path. For example, when the parking destination of a vehicle is located on the predicted parking path of other vehicles, or when a vehicle stays on the predicted parking path of other vehicles, it is determined that there is a path conflict and space occupancy conflict between the vehicles. At this time, the predicted parking path is optimized to achieve orderly and efficient parking among multiple vehicles in the parking lot, thereby improving parking efficiency and space utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a schematic diagram of a process flow of a collaborative parking method according to an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a process of obtaining an estimated parking path according to an embodiment of the present invention;

[0038] Figure 3 A schematic diagram of a process for optimizing an estimated parking path according to an embodiment of the present invention;

[0039] Figure 4 A schematic diagram of a user interaction process according to an embodiment of the present invention;

[0040] Figure 5 A system architecture diagram of a collaborative parking device according to an embodiment of the present invention;

[0041] Figure 6 4 is a system architecture diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be interpreted as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not intended to limit the scope of protection of the present invention.

[0043] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0044] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to"; the term "based on" means "based at least in part on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments"; the term "optionally" means "optional embodiments". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc. mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0045] It should be noted that the modifications of "one" and "plurality" mentioned in the present invention are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0046] The names of the messages or information exchanged between multiple devices in the embodiments of the present invention are only used for illustrative purposes, and are not used to limit the scope of these messages or information.

[0047] like Figure 1 As shown, a collaborative parking method provided by an embodiment of the present invention includes:

[0048] S100: Obtaining the estimated parking path of each vehicle in a preset scene according to preset rules.

[0049] Specifically, taking the preset scenario of a parking lot as an example, before each vehicle performs collaborative parking in the parking lot, the user needs to turn on collaborative parking on his own vehicle. Then the vehicle will obtain the estimated parking path of other vehicles in the parking lot through preset rules. The estimated parking path of the vehicle can be confirmed by the vehicle side through information such as the vehicle position of the vehicle.

[0050] S200: Detecting whether there is a path conflict and a space occupancy conflict between the vehicles according to the predicted parking path, and when there is a path conflict and / or a space occupancy conflict between the vehicles, optimizing the predicted parking path of the vehicles with the path conflict and / or the space occupancy conflict.

[0051] Specifically, the vehicle side can detect whether there is a path conflict and space occupancy conflict between the vehicle itself and other vehicles based on the expected parking path of the vehicle itself and the expected parking paths of other vehicles. When there is a path conflict and / or space occupancy conflict between the vehicle itself and other vehicles, the expected parking path of the vehicle itself is optimized; when the vehicle-side computing power of the vehicle itself cannot meet the collaborative parking function, the corresponding calculation process can be carried out in the cloud, and the result can be sent to the vehicle side after the cloud calculation is completed. When calculating through the cloud, the expected parking paths of each vehicle in the parking lot can be optimized, that is, not only the expected parking path of the vehicle itself can be optimized, but also the expected parking paths of other vehicles can be optimized.

[0052] Among them, the cloud can introduce a priority mechanism. By analyzing the status of each vehicle (such as arrival time, distance from the parking space, etc.), different priorities can be assigned to vehicles to ensure the smooth progress of collaborative parking. For example, each vehicle is assigned a suitable time period, during which it is allowed to enter or pass through a specific area to avoid congestion (time window allocation), or its priority is dynamically adjusted according to real-time traffic conditions and target distance (dynamic priority adjustment).

[0053] Among them, the vehicle side and the cloud side can "negotiate" the order in which vehicles pass or park. For example, vehicles work together to seek an optimal solution for all vehicles, or each vehicle optimizes its path based on its own goals. The cloud side prevents conflicts through corresponding mechanism design.

[0054] Among them, after each parking task is completed, the performance of this planning process can be evaluated, including indicators such as path length, parking time, and conflict resolution efficiency. Based on the evaluation results, the algorithm parameters and strategies can be continuously optimized to improve the efficiency and success rate of future parking tasks. For example, each vehicle is regarded as an independent intelligent agent, and its decision-making is continuously optimized through learning. The intelligent agent gradually learns how to achieve the best parking effect without affecting other vehicles by interacting with the environment. Similarly, vehicles can share experience and learning results, and the overall system is continuously optimized. Each vehicle can also learn independently, and the algorithm avoids conflicts through incentive mechanisms.

[0055] Among them, the optimization objectives may include:

[0056] (1) The paths of the vehicles should not conflict with each other as much as possible;

[0057] (2) The vehicle can reach the target parking space smoothly;

[0058] (3) Make the route as short as possible and optimize parking time.

[0059] Among them, path conflict refers to the updated parking destination of the vehicle being on the expected parking path of other vehicles; space occupancy conflict refers to the vehicle staying on the expected parking path of other vehicles.

[0060] In this embodiment, the estimated parking path of each vehicle in the preset scene is first obtained through preset rules, for example, key parking parameters of other vehicles in the parking lot are obtained from the cloud, or key parking parameters of other vehicles are obtained through vehicle communication protocols, so that the estimated parking path of each vehicle can be determined, and information sharing between vehicles of different brands and models can be achieved. Then, path conflicts and space occupancy conflicts between vehicles are detected according to the estimated parking path. For example, when the parking destination of a vehicle is located on the estimated parking path of other vehicles, or when a vehicle stays on the estimated parking path of other vehicles, it is determined that there are path conflicts and space occupancy conflicts between the vehicles. At this time, the estimated parking path is optimized to achieve orderly and efficient parking among multiple vehicles in the parking lot, thereby improving parking efficiency and space utilization.

[0061] Optionally, obtaining the estimated parking path of each vehicle in the preset scene by using preset rules includes:

[0062] S110: Acquire key parking parameters of each of the vehicles through the cloud and / or vehicle communication protocol, wherein the key parking parameters include the position, speed, steering angle, and parking destination of the vehicle.

[0063] Specifically, combined Figure 2 As shown, taking the preset scenario of a parking lot as an example, after the vehicle enters the parking lot, the vehicle location and other information will be uploaded to the cloud. When the vehicle turns on collaborative parking, the key parking parameters of other vehicles in the parking lot (such as the vehicle's location, speed, steering angle and parking destination, as well as acceleration and other parameters) can be obtained from the cloud. When the key parking parameters cannot be uploaded to the cloud, the vehicle location and other information can be broadcast to the entire parking lot through the vehicle communication protocol. When the vehicle turns on collaborative parking, the broadcast content will be detected to obtain the key parking parameters of other vehicles, thereby realizing information sharing between vehicles of different brands and models, and then using the key parking parameters for collaborative parking path planning, thereby realizing orderly and efficient parking among multiple vehicles in the parking lot.

[0064] S120: Constructing a kinematic model of each of the vehicles according to the kinematic characteristics of each of the vehicles.

[0065] Specifically, combined Figure 2 As shown, the kinematic characteristics of the vehicle include vehicle length, steering angle, minimum turning radius, etc. The kinematic model of each vehicle can be constructed based on the kinematic characteristics of the vehicle.

[0066] S130: using a path planning algorithm to generate a preliminary parking path for each of the vehicles according to the kinematic model, the parking destination and the preset scenario.

[0067] Specifically, combined Figure 2 As shown, a preliminary parking path for each vehicle can be generated by using a path planning algorithm in combination with the parking lot environment, vehicle kinematic model, and parking destination.

[0068] Among them, commonly used path planning algorithms include grid map-based algorithms (A* and Dijkstra) and spline curve-based algorithms (Bezier curve, Dubins curve), etc. For example, A* and Dijkstra algorithms are used to search for the optimal path from the starting point (current vehicle position) to the end point (parking destination).

[0069] S140: Adjusting the preliminary parking path of each of the vehicles according to the position, speed and steering angle of each of the vehicles to determine an estimated parking path of each of the vehicles.

[0070] Specifically, combined Figure 2 As shown in the figure, after a preliminary path is planned, the path needs to be further optimized, including path smoothing (the planned path may have sharp corners or discontinuous turning changes, so the path needs to be smoothed), speed adjustment (dynamically adjust the vehicle's speed according to the complexity of the path, the turning radius, and the distance to the parking position) and obstacle avoidance optimization (in a parking lot environment, other vehicles, pedestrians, or fixed obstacles may require the vehicle to adjust the path in real time to avoid collisions), so as to determine the expected parking path for each vehicle.

[0071] Among them, the vehicle's position is used to determine the relative position of the vehicle and surrounding obstacles, so as to perform obstacle avoidance analysis. When planning the path, the system will judge the distance to the obstacle based on the current position and dynamically adjust the route to avoid collision.

[0072] When planning a path, speed affects the range of movement of the vehicle within a certain period of time. Therefore, the path planning algorithm must determine whether the planned path is feasible based on the current speed of the vehicle and whether it is necessary to reduce the speed in certain areas to improve the vehicle's control ability.

[0073] Among them, the vehicle's steering angle determines the vehicle's real-time driving trajectory during driving. The path planning algorithm will not only plan an ideal path, but also continuously adjust the path according to the real-time steering angle to ensure that the vehicle can accurately drive along the planned path.

[0074] It can be seen that the vehicle's current position, speed, and steering angle interact with each other to determine the feasibility and optimization of path planning:

[0075] (1) Real-time path adjustment: The vehicle’s current position and steering angle provide real-time information about the vehicle’s direction and position, while the speed determines where the vehicle is likely to be in the next few seconds. The combination of these three allows the system to continuously adjust the path as it executes.

[0076] (2) Dynamic constraints: The steering angle limits the vehicle’s ability to navigate curves at different speeds, while the speed affects the feasibility of the vehicle completing complex turns. The current position provides real-time status for planning, ensuring that path planning is always based on the vehicle’s actual motion status.

[0077] (3) Parking accuracy and safety: As the vehicle approaches the target parking space, the speed should be gradually reduced, and the steering angle needs to be precisely controlled to ensure that the vehicle stops straight. The current position provides the basis for this precise adjustment.

[0078] In this optional embodiment, by obtaining the key parking parameters of the vehicle through the cloud and / or vehicle communication protocol, and determining the expected parking path of the vehicle based on the key parking parameters, information sharing between vehicles of different brands and models can be achieved, thereby achieving orderly and efficient parking among multiple vehicles in the parking lot.

[0079] Optionally, obtaining key parking parameters of each vehicle through the cloud and / or vehicle communication protocol includes:

[0080] When the vehicle does not support communication with the cloud and the vehicle communication protocol, key parking parameters of the vehicle collected by the feature vehicle are obtained through the cloud and / or the vehicle communication protocol, wherein the feature vehicle includes a vehicle whose computing power is sufficient to collect the key parking parameters of the vehicle and supports communication with the cloud and / or the vehicle communication protocol.

[0081] Specifically, for some vehicles in the parking lot that neither support communication with the cloud nor support the vehicle communication protocol, in order to ensure that these vehicles are integrated into the collaborative parking system, the key parking parameters of these vehicles can be collected (for example, through cameras, radars, ultrasonic sensors and other equipment) by vehicles with a higher computing power limit in the parking lot (called feature vehicles), and uploaded to the cloud for other vehicles (collaborative parking function) to obtain, or obtained by other vehicles through the vehicle communication protocol, so that vehicles in the parking lot that support the collaborative parking function can avoid these vehicles when parking.

[0082] In this optional embodiment, key parking parameters of vehicles that neither support communication with the cloud nor support vehicle communication protocols are collected through feature vehicles, so that vehicles in the parking lot that support collaborative parking functions can avoid these vehicles when parking, thereby achieving orderly and efficient parking among multiple vehicles in the parking lot.

[0083] Optionally, detecting whether there is a path conflict and a space occupancy conflict between the vehicles according to the predicted parking path, and when there is a path conflict and / or a space occupancy conflict between the vehicles, optimizing the predicted parking path of the vehicles with the path conflict and / or the space occupancy conflict comprises:

[0084] S210: Detecting path conflicts and / or space occupancy conflicts between the vehicles according to the predicted parking path.

[0085] Specifically, combined Figure 3 As shown, the predicted parking path can, on the one hand, detect real-time path conflicts and / or real-time space occupancy conflicts between vehicles. When there are real-time path conflicts and / or real-time space occupancy conflicts between vehicles, a re-planning mechanism (prioritizing real-time conflicts) can be triggered. On the other hand, future path conflicts and / or future space occupancy conflicts can also be predicted to avoid conflicts in advance. For example, when the own vehicle is in the parking process (10 seconds left to complete parking), another vehicle is expected to enter the parking queue in 15 seconds, and the parking destination of the vehicle is on the parking path of the own vehicle, then the vehicle and the own vehicle may have a path conflict in the future, which can be avoided in advance.

[0086] S220: When the parking destination of any of the vehicles is located on the estimated parking path of another vehicle, it is determined that there is a path conflict between the vehicles.

[0087] Specifically, combined Figure 3 As shown, taking vehicle A and vehicle B as an example, after vehicle A updates its parking destination, if the updated parking destination is located on the estimated parking path of vehicle B, it is determined that there is a real-time path conflict between vehicle A and vehicle B.

[0088] S230: When any of the vehicles stops on the predicted parking path of another vehicle, it is determined that there is a space occupation conflict between the vehicles.

[0089] Specifically, combined Figure 3 As shown, taking vehicle A and vehicle B as an example, when vehicle A stops on the estimated parking path of vehicle B, it is determined that there is a real-time space occupancy conflict between vehicle A and vehicle B.

[0090] S240: When the path conflict and / or the space occupancy conflict exists between the vehicles, an optimization algorithm is used to adjust the driving order and driving routes of the vehicles with the path conflict and / or the space occupancy conflict, wherein the optimization algorithm includes global path planning and a priority mechanism, the global path planning is used to determine the optimal path of the vehicles, and the priority mechanism is used to determine the parking priority between the vehicles.

[0091] Specifically, combined Figure 3 As shown, when there is a real-time path conflict and / or real-time space occupancy conflict between vehicles, the re-planning mechanism is triggered. At this time, the optimization algorithm is used to adjust the driving order and route of the vehicles, guide the vehicles to detour or wait for free space before parking, ensure that all vehicles can smoothly reach their respective target parking spaces, and minimize the path length and parking time.

[0092] Among them, the optimization algorithm includes global path planning and priority mechanism. In a multi-vehicle environment, global path planning is needed to formulate the driving path of each vehicle to ensure that the paths of each vehicle do not conflict. In addition, by assigning priorities, it is ensured that multiple vehicles can park in a coordinated manner. For example, a specific time period is assigned to each vehicle to enter or pass through a parking area, or the vehicle dynamically adjusts its priority based on factors such as its distance from the target parking space and arrival time.

[0093] Among them, optimization algorithms include genetic algorithms, etc. Each algorithm mainly considers factors such as path length, parking time, traffic flow, mutual influence between vehicles, and safe distance to avoid collision to re-plan the path of each vehicle; the optimization algorithm can also predict possible collisions or path overlaps in the future and avoid them in advance.

[0094] In this optional embodiment, when there is a path conflict and / or space occupancy conflict between vehicles, a re-planning mechanism is triggered and an optimization algorithm is used to adjust the driving order and routes of the vehicles to ensure that all vehicles can smoothly reach their respective target parking spaces while minimizing the path length and parking time, thereby achieving orderly and efficient parking among multiple vehicles in the parking lot.

[0095] Optionally, the optimizing the predicted parking path of the vehicle having path conflict and / or space occupancy conflict further includes:

[0096] When any of the vehicles is parked according to the optimized parking path, if the status of other vehicles and / or the preset scene changes, the parking path is optimized again.

[0097] Specifically, the planned new path will be sent to the vehicle control system in real time, and the vehicle control system will control the vehicle to park according to the optimized parking path. At this time, the vehicle execution status can still be monitored in real time. If the status of other vehicles changes (such as vehicle failure, etc.) or the status of the preset scene changes (such as pedestrians crossing, etc.), the parking path can be optimized again, that is, the dynamic adjustment function is supported. During the parking process, the path planning is updated in real time according to the changes in the vehicle status to ensure the smooth progress of the parking process.

[0098] In this optional embodiment, by optimizing the parking path again when the status of other vehicles changes or the status of the preset scene changes, real-time adjustment and feedback of the parking process are achieved to ensure the smooth progress of the parking process.

[0099] Optionally, the collaborative parking method further includes:

[0100] When any of the vehicles fails to obtain the key parking parameters of other vehicles, the vehicle is controlled to autonomously cruise to a memory parking space through memory parking.

[0101] Specifically, when any vehicle fails to obtain the key parking parameters of other vehicles, the vehicle control system of the corresponding vehicle controls the vehicle to autonomously cruise to the memory parking space through memory parking; if during the memory parking process, memory parking obtains the key parking parameters of other vehicles, it can enter the collaborative parking mode and detect path conflicts and space occupancy conflicts between vehicles based on the expected parking path.

[0102] In this optional embodiment, when the vehicle fails to obtain key parking parameters of other vehicles, the vehicle is controlled to autonomously cruise to the memory parking space through memory parking, thereby ensuring a smooth parking process.

[0103] Optionally, the collaborative parking method further includes:

[0104] S300: Displaying the real-time parking path and parking progress of the vehicle on a user interaction interface.

[0105] Specifically, combined Figure 4 As shown, the real-time parking path and parking progress of the vehicle can be displayed on the user interaction interface (such as the vehicle screen) to let the user understand the current parking status and future path.

[0106] S400: Feedback corresponding interaction information according to the user's operation instruction on the user interaction interface.

[0107] Specifically, combined Figure 4 As shown, the user interaction interface supports multiple interaction methods such as voice or touch. For example, the user can inquire about the current parking progress by voice, and the user interaction interface will feedback the current parking status of the vehicle to the user, thereby improving the convenience of user operation.

[0108] In this optional embodiment, by providing a user interaction interface, the user can intuitively understand the current parking status of the vehicle, thereby improving the convenience of user operation.

[0109] like Figure 5 As shown, a collaborative parking device 500 provided in an embodiment of the present invention includes:

[0110] The first module 510 is used to obtain the estimated parking path of each vehicle in a preset scene according to a preset rule;

[0111] The second module 520 is used to detect whether there is a path conflict and a space occupancy conflict between the vehicles according to the predicted parking path, and when there is a path conflict and / or a space occupancy conflict between the vehicles, optimize the predicted parking path of the vehicles with the path conflict and / or the space occupancy conflict.

[0112] like Figure 6 As shown, an electronic device 600 provided by an embodiment of the present invention includes a memory 620 and a processor 610; the memory 620 is used to store a computer program; the processor 610 is used to implement the collaborative parking method as described above when executing the computer program.

[0113] In other words, an electronic device 600 includes a memory 620 and a processor 610 coupled to the memory 620; the memory 620 is configured to store a computer program; and the processor 610 is configured to perform the following operations when executing the computer program:

[0114] Obtain the estimated parking path of each vehicle in a preset scene through preset rules;

[0115] Path conflicts and space occupancy conflicts between the vehicles are detected according to the predicted parking path, and when path conflicts and / or space occupancy conflicts exist between the vehicles, the predicted parking path is optimized.

[0116] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the collaborative parking method as described above is implemented.

[0117] In other words, a non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor performs the following operations:

[0118] Obtain the estimated parking path of each vehicle in a preset scene through preset rules;

[0119] Path conflicts and space occupancy conflicts between the vehicles are detected according to the predicted parking path, and when path conflicts and / or space occupancy conflicts exist between the vehicles, the predicted parking path is optimized.

[0120] An electronic device 600 that can be used as a server or client of the present invention will now be described, which is an example of a hardware device that can be applied to various aspects of the present invention. The electronic device 600 is intended to represent various forms of digital electronic computer equipment, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device 600 can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples, and are not intended to limit the implementation of the present invention described and / or required herein.

[0121] The electronic device 600 includes a computing unit, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) or a computer program loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for the operation of the device can also be stored. The computing unit, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0122] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc. In the present application, the unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment of the present invention. In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0123] Although the present invention is disclosed as above, the protection scope of the present invention is not limited thereto. Those skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention, and these changes and modifications will fall within the protection scope of the present invention.

Claims

1. A collaborative parking method, characterized in that: include: Obtain the estimated parking path of each vehicle in a preset scene through preset rules; The predicted parking paths are used to detect whether there are path conflicts and space occupancy conflicts between the vehicles. When there are path conflicts and / or space occupancy conflicts between the vehicles, the predicted parking paths of the vehicles with path conflicts and / or space occupancy conflicts are optimized.

2. The collaborative parking method according to claim 1, characterized in that: The method of obtaining the estimated parking path of each vehicle in the preset scene by using the preset rules includes: Acquiring key parking parameters of each of the vehicles through a cloud and / or a vehicle communication protocol, wherein the key parking parameters include a position, a speed, a steering angle, and a parking destination of the vehicle; Constructing a kinematic model of each of the vehicles according to the kinematic characteristics of each of the vehicles; Using a path planning algorithm, generating a preliminary parking path for each of the vehicles according to the kinematic model, the parking destination and the preset scenario; The preliminary parking path of each of the vehicles is adjusted according to the position, speed and steering angle of each of the vehicles to determine an estimated parking path of each of the vehicles.

3. The collaborative parking method according to claim 2, characterized in that: The obtaining of key parking parameters of each vehicle through the cloud and / or vehicle communication protocol includes: When the vehicle does not support communication with the cloud and the vehicle communication protocol, key parking parameters of the vehicle collected by the feature vehicle are obtained through the cloud and / or the vehicle communication protocol, wherein the feature vehicle includes a vehicle whose computing power is sufficient to collect the key parking parameters of the vehicle and supports communication with the cloud and / or the vehicle communication protocol.

4. The collaborative parking method according to claim 1, characterized in that: The detecting whether there is a path conflict and a space occupancy conflict between the vehicles according to the predicted parking path, and when there is a path conflict and / or a space occupancy conflict between the vehicles, optimizing the predicted parking path of the vehicles with the path conflict and / or the space occupancy conflict comprises: detecting path conflicts and / or space occupancy conflicts between the vehicles according to the predicted parking path; When a parking destination of any of the vehicles is located on an estimated parking path of another vehicle, determining that there is a path conflict between the vehicles; When any of the vehicles stays on the estimated parking path of another vehicle, determining that there is a space occupation conflict between the vehicles; When the path conflict and / or the space occupancy conflict exists between the vehicles, an optimization algorithm is used to adjust the driving order and driving routes of the vehicles with the path conflict and / or the space occupancy conflict, wherein the optimization algorithm includes global path planning and a priority mechanism, the global path planning is used to determine the optimal path of the vehicles, and the priority mechanism is used to determine the parking priority between the vehicles.

5. The collaborative parking method according to claim 4, characterized in that: The optimizing the estimated parking path of the vehicle having path conflict and / or space occupancy conflict further includes: When any of the vehicles is parked according to the optimized parking path, if the status of other vehicles and / or the preset scene changes, the parking path is optimized again.

6. The cooperative parking method according to any one of claims 1 to 5, characterized in that: Also includes: When any of the vehicles fails to obtain the key parking parameters of other vehicles, the vehicle is controlled to autonomously cruise to a memory parking space through memory parking.

7. The collaborative parking method according to any one of claims 1 to 5, characterized in that: Also includes: Displaying the real-time parking path and parking progress of the vehicle on a user interaction interface; Corresponding interaction information is fed back according to the user's operation instructions on the user interaction interface.

8. A cooperative parking device, characterized in that: include: The first module is used to obtain the estimated parking path of each vehicle in a preset scene through preset rules; The second module is used to detect whether there is a path conflict and a space occupancy conflict between the vehicles according to the predicted parking path, and when there is a path conflict and / or a space occupancy conflict between the vehicles, optimize the predicted parking path of the vehicles with the path conflict and / or the space occupancy conflict.

9. An electronic device, characterized in that: including memory and processor; The memory is used to store computer programs; The processor is used to implement the collaborative parking method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the collaborative parking method as described in any one of claims 1 to 7 is implemented.

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