Control method, apparatus, and storage medium

Abstract

The embodiment of the present disclosure provides a control method, device and storage medium, and relates to the field of automatic control. The control method comprises the following steps: determining a first parking area to be driven into by a movable device; obtaining historical parking information according to the first parking area, wherein the historical parking information at least comprises at least one target position point determined based on a historical driving path of the movable device under user control to drive into a second parking area, and the second parking area is a same type of parking area as the first parking area; generating a target path of the movable device from a current position to drive into the first parking area according to the historical parking information, so that a first similarity between the target path and the historical parking information is greater than or equal to a first preset similarity threshold; and controlling the movable device to drive according to the target path.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of automatic driving, and more particularly, to a control method, device and storage medium. BACKGROUND

[0002] With the development of automatic driving technology, an automated parking assist system has been applied more and more. For a movable device such as a vehicle, after the movable device locks a target parking area such as a parking space, a charging position or a stopping position for driving in, the movable device can be controlled to drive into the target parking area based on the automated parking assist system. Path planning is a key step of the automated parking assist system, and therefore, how to improve the efficiency and reliability of path planning is crucial to the control of the movable device in an automatic parking scenario. SUMMARY

[0003] In view of this, the embodiments of the present disclosure provide a new technical solution for controlling a movable device.

[0004] According to a first aspect of the embodiments of the present disclosure, a control method is provided, and the method comprises:

[0005] determining a first parking area to be driven into by a movable device;

[0006] obtaining historical parking information according to the first parking area; wherein the historical parking information at least comprises at least one target position point determined based on a historical driving path of the movable device driving into a second parking area under user control, and the second parking area and the first parking area are parking areas of the same type;

[0007] generating a target path of the movable device driving into the first parking area from a current position according to the historical parking information, so that a first similarity of the target path and the historical parking information is greater than or equal to a first preset similarity threshold;

[0008] controlling the movable device to drive according to the target path.

[0009] Optionally, the at least one target position point at least comprises a gear shifting position point at which the movable device performs a gear shifting operation in the historical driving path.

[0010] The historical parking information further comprises a device historical state of the movable device at each target position point, the device historical state comprises at least one of a heading angle, a speed, an acceleration and a gear state of the movable device at the target position point, and the first similarity comprises a device state similarity.

[0011] Optionally, the generating the target path of the movable device from the current position to the first parking area according to the historical parking information comprises:

[0012] performing a preset path search algorithm according to the historical parking information to generate the target path of the movable device from the current position to the first parking area;

[0013] The preset path search algorithm at least comprises a first cost function, and the first cost function is used to obtain a first similarity degree between the target path and the historical parking information.

[0014] Optionally, the generating the target path of the movable device from the current position to the first parking area according to the historical parking information comprises:

[0015] generating a spatial node set corresponding to each of the target position points according to the historical parking information; wherein a distance between each spatial node in the spatial node set and the target position point is less than or equal to a first preset distance threshold;

[0016] taking the spatial nodes in the spatial node set as candidate nodes of the preset path search algorithm to search and generate the target path.

[0017] Optionally, the historical parking information further comprises a device historical state of the movable device at each of the target position points; and the spatial node set further comprises a device expected state corresponding to each spatial node, and a second similarity degree between the device expected state corresponding to the spatial node and a device historical state of a target position point corresponding to the spatial node is greater than or equal to a second preset similarity threshold.

[0018] Optionally, the historical parking information is generated in advance based on the following manner: obtaining the historical driving path of the movable device under user control to drive into a second parking area; and determining at least one of the target position points according to the historical driving path to generate the historical parking information.

[0019] The obtaining the historical parking information according to the first parking area comprises: in a case that a parking mode of the movable device is a preset mode, obtaining the historical parking information according to the first parking area; wherein the parking mode is a mode determined based on user input, and the preset mode is used to indicate that the movable device uses the historical parking information to assist in generating the target path after determining the first parking area.

[0020] Optionally, the historical parking information further comprises a historical drivable area determined based on a historical driving path of the movable device.

[0021] The method further includes:

[0022] detecting, according to sensor data of the movable device, a target obstacle of a preset type;

[0023] determining, according to the target obstacle and the historical drivable area, whether the target obstacle can be driven through by the movable device.

[0024] Optionally, the determining, according to the target obstacle and the historical drivable area, whether the target obstacle can be driven through by the movable device includes:

[0025] if the target obstacle is located in the historical drivable area, determining that the target obstacle can be driven through by the movable device; or

[0026] if the target obstacle is located outside the historical drivable area, determining, based on an external shape parameter of the target obstacle, whether the target obstacle can be driven through by the movable device.

[0027] According to a second aspect of the embodiments of the present disclosure, a control device is provided, including a memory and a processor, the memory is used to store computer instructions, and the processor is used to call the computer instructions from the memory to execute the method according to the first aspect.

[0028] According to a third aspect of the embodiments of the present disclosure, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the method according to the first aspect.

[0029] Based on the control method provided by the embodiments of the present disclosure, since the historical parking information is determined based on the historical driving path of the movable device in the second parking area under the control of the user, the individual preference of the user for the driving path of the movable device can be reflected, so that the efficiency and reliability of the path planning can be improved, and the user experience of controlling the parking of the movable device can be improved.

[0030] Other features and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments thereof, taken in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0031] The accompanying drawings incorporated in and forming a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0032] Figure 1 FIG. 1 is a schematic diagram of an intelligent network system to which the method provided by the embodiments of the present disclosure can be applied.

[0033] Figure 2 is according to Figure 1 is a schematic diagram of a movable device provided by the embodiment of the present disclosure.

[0034] Figure 3 is a flowchart of a control method provided by the embodiment of the present disclosure.

[0035] Figure 4 is a schematic diagram of a set of spatial nodes provided by the embodiment of the present disclosure.

[0036] Figure 5 is a schematic diagram of a historical driving path provided by the embodiment of the present disclosure.

[0037] Figure 6 is a schematic diagram of a target position point provided by the embodiment of the present disclosure.

[0038] Figure 7 is a schematic diagram of a historical drivable area provided by the embodiment of the present disclosure.

[0039] Figure 8 is a flowchart of a control method provided by the embodiment of the present disclosure.

[0040] Figure 9 is a schematic diagram of a control device provided by the embodiment of the present disclosure. DETAILED DESCRIPTION

[0041] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. If need be, the relative arrangement, numerical expressions, and numerical values of components and steps set forth in these embodiments are not limiting to the scope of the present disclosure.

[0042] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way limiting to the scope of the disclosure and its applications or uses.

[0043] Techniques, methods, and apparatus known to those of ordinary skill in the relevant art can not be discussed in detail herein, but should be considered part of the specification, where appropriate.

[0044] In all of the examples shown and discussed herein, any specific values should be interpreted as merely illustrative and not as a limitation. Thus, other examples of the exemplary embodiments can have different values.

[0045] It should be noted that like references and characters herein relate to like items throughout the figures, and once an item is defined in one figure, it need not be discussed further in subsequent figures.

[0046] The element involved in the embodiments of the present disclosure can represent part or all of the element, for example, the element involved in the embodiments of the present disclosure can be at least part of the element, or the whole element.

[0047] The element involved in the embodiments of the present disclosure can be one or more, for example, "one", "the", "above", "said", "preceding" and the like, used to represent that the corresponding element is first mentioned or mentioned again, and does not have the meaning of limiting the number.

[0048] It should be noted that the collection, storage, use, processing, transmission, provision, disclosure, deletion and the like of data in the present disclosure are carried out in compliance with the relevant data protection regulations and policies of the country or region where the data is located, and with the full authorization of the corresponding data owner.

[0049] First, the application scenario of the embodiments of the present disclosure is described.

[0050] Figure 1 A schematic diagram of an intelligent network contact system 100 to which the method provided by the embodiments of the present disclosure can be applied. As shown in the figure, the intelligent network contact system 100 can include: a movable device 101, a server 102, a user terminal 103. Figure 1

[0051] In some examples, the movable device 101 can be a movable device such as a vehicle, a robot, a ship, etc., for example, a vehicle with automatic driving function, a robot that can move autonomously (such as a cargo robot, a detection robot or a sweeping robot, etc.), etc. Among them, automatic driving is also called unmanned driving or intelligent driving, and the vehicle with automatic driving function can realize driving tasks such as environment perception, decision planning and control execution. The level of automatic driving can refer to the intelligent grading standard of Society of Automotive Engineers (SAE), for example, L0 level is manual driving, L1 is auxiliary driving, L2 is partial automatic driving, L3 is conditional automatic driving, L4 is high automatic driving, and L5 is complete automatic driving. The above classification method of automatic driving level is only as an example, and the classification standard and level of automatic driving in the embodiments of the present disclosure are not limited.

[0052] ​In some examples, the server 102 can be a single server or a distributed server cluster composed of multiple servers, which can be deployed in a local server or a cloud server. The server 102 can communicate with the movable device 101 and / or the user terminal 103 based on a communication network, and provide various services for the movable device 101 and / or the user terminal 103. For example, the server can receive perception data sent by the movable device, and provide services such as high-precision map, data analysis, decision planning, etc. for the movable device. For another example, the server can receive query instructions or control instructions sent by the user terminal, and provide corresponding services for the user.

[0053] In some examples, the user terminal 103 can be any form of electronic device providing services for users, such as a personal computer, a notebook computer, a smart tablet, a smart phone, a smart wearable device, etc. The user can interact with the movable device or the server through a human-computer interaction terminal configured by the movable device 101, or through the user terminal 103. For example, the user can query the state and / or parameters of the movable device, or control the movable device to perform a set task and / or modify a configuration parameter, etc. through the user terminal. The user terminal runs an application based on the intelligent network system to realize the interaction with the movable device or the server. The application can be a local application, a web application or a mini-program, etc., which is not limited here.

[0054] In some examples, the above-mentioned application running on the user terminal can provide authentication or authorization services for the user. The user who successfully passes the authentication and is granted corresponding permissions can query and / or control the movable device within the scope of the granted permissions.

[0055] The movable device 101, the server 102 and the user terminal 103 can communicate through a communication link provided by the communication network 104. The communication network 104 can include one or more networks of any type. For example, the communication network 104 can include an Internet, a local area network (LAN), a wide area network (WAN), a virtual private network (VPN), a public switched telephone network (PSTN), a satellite communication network, Wi-Fi, 2G, 3G, 4G, 5G, 6G, NB-IoT, eMTC, infrared, Bluetooth, NFC, etc. The communication network between the movable device 101 and the server 102, between the user terminal 103 and the server 102, and between the user terminal 103 and the movable device 101 can be the same or different.

[0056] It should be noted that, Figure 1The structure of the intelligent network contact system 100 shown in the figure is only illustrative, and the intelligent network contact system in the embodiments of the present disclosure is not limited to the above structure, and can further include more or less devices, or can be combined or split. For example, the intelligent network contact system can also not include user terminals and / or servers; for another example, the user terminals and servers can be combined and deployed.

[0057] Figure 2 According to Figure 1 A schematic diagram of a mobile device 101 is provided according to the embodiments shown in the figure. As shown in the figure, the mobile device 101 can include a perception component 1011, a computing platform 1012, an execution component 1013, and the like. Among them, the perception component 1011, the computing platform 1012 and the execution component 1013 can be connected through a bus or other means. Figure 2

[0058] In some examples, the perception component 1011 can be used to collect information of the mobile device itself or the outside, and the perception component 1011 can include at least one of a visual sensing unit, a radar, a positioning navigation unit, an inertial measurement unit (IMU) or other sensing units, wherein the visual sensing unit can include one or more cameras, the radar can include at least one of a laser radar, a millimeter wave radar, an ultrasonic radar or other radars, and the positioning navigation unit can include at least one of a GPS system, a Beidou system or other global positioning systems.

[0059] ​In some examples, the computing platform 1012 can include a device with computing capability for processing the perception information collected by the perception component 1011 to obtain control information, and sending corresponding control instructions to the execution component 1013 to enable the execution component 1013 to perform corresponding actions, thereby achieving control of the movable device 101. For example, the computing platform 1012 can perform one or more of positioning and mapping (SLAM), information collection and processing, decision making, planning, control, and the like, thereby achieving autonomous control of the movable device. The computing platform 1012 can include at least one processor and at least one memory, and each processor can execute instructions stored in the memory to implement the method provided by the embodiments of the present disclosure. The processor in the embodiments of the present disclosure can include at least one of a central processing unit (CPU), a graphic processing unit (GPU), a neural-network processing unit (NPU), a tensor processing unit (TPU), a data processing unit (DPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a system on chip (SOC), an application specific integrated circuit (ASIC), a micro controller unit (MCU), or other processors. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. In addition to storing instructions, the memory can also store data, such as high-definition map, path information, position, direction, speed, and the like of the movable device. The data stored in the memory can be obtained and used by the processor.

[0060] In some examples, the computing platform of the movable device can independently perform a computing task, or can complete the computing task by communicating with a server. For example, the computing platform of the movable device can cooperate with the server to complete a corresponding computing task.

[0061] The computing platform 1012 can be arranged in the movable device 101, or part or all of the computing platform 1012 can also be arranged in the server corresponding to the movable device, for example, part of the computing platform 1012 with high real-time requirement is arranged in the movable device, and the other part of the computing platform 1012 with low real-time requirement is arranged in the server corresponding to the movable device.

[0062] In some examples, the execution component 1013 is configured to perform corresponding actions based on the control of the computing platform 1012, so that the movable device 101 completes the moving task. The execution component 1013 can include, for example, a power component, a brake component, a transmission component, a steering component, etc.

[0063] It should be noted that, Figure 2 The structure of the movable device 101 shown in FIG. 1 is only schematic, and the movable device in the embodiments of the present disclosure is not limited to the above structure, and can further include more or fewer components, or the device can be combined or split. For example, the movable device can not include the computing platform described above. For another example, the movable device can further include a communication component, an interface component, a multimedia component, an input component, an output component, etc.

[0064] The embodiments of the present disclosure can be applied to an automatic parking scenario, especially an automatic parking scenario based on path planning and vehicle control in a narrow range such as a parking lot. For a movable device such as a vehicle, after the movable device locks a target parking area such as a parking space, a charging position or a stopping position to wait for driving in, the movable device can perform path planning based on an automatic parking assistance system, and control the movable device to drive into the target parking area based on the planned path. Path planning is a key step of the automatic parking assistance system, and therefore, how to improve the efficiency and reliability of path planning is crucial for the control of the movable device in the automatic parking scenario.

[0065] In the related art, when the movable device locks the target parking area, the movable device can perform path planning based on general path planning strategies such as a geometric reverse driving model, a trajectory sampling method and a general path search algorithm. However, this way ignores the individual preferences of the user for the driving path of the movable device, resulting in low efficiency and reliability of path planning, and affecting the user experience.

[0066] To solve the problems in the related art, the embodiments of the present disclosure provide a control method. Figure 3 FIG. 1 is a flow diagram of a control method provided by the embodiments of the present disclosure. The control method can be performed by the movable device and / or the server as shown in FIG. 1. Figure 1 The control method of the present embodiment can include the following steps S310 to S340, as shown in FIG. 3. Figure 3 ​

[0067] Step S310, determine a first parking area where the movable device is to be parked.

[0068] The first parking area can be a parking area where the movable device can be parked, which can be determined based on the surrounding environment information of the movable device, which can be detected by sensors of the movable device or determined based on the position of the movable device. For example, the movable device is a vehicle, the parking area can be a parking space where the vehicle can be parked, which can be a parking space line parking space surrounded by clear parking space boundary lines or a space parking space surrounded by surrounding objects (such as vehicles, columns, etc.).

[0069] In some examples, the parking area where the movable device can be parked can have multiple area types, such as vertical parking area, parallel parking area, inclined parking area, etc. For example, the area type of the parking area can be used to indicate the relative relationship between the target parking direction of the movable device after parking in the parking area and the current driving direction of the movable device when locking the parking area near the parking area and starting to drive into the parking area. For example, if the target parking direction is parallel to the current driving direction (such as the same direction or a difference of 180 degrees), the area type of the parking area is a parallel parking area; for another example, if the target parking direction is perpendicular to the current driving direction (such as a difference of 90 degrees or 270 degrees), the area type of the parking area is a vertical parking area; for another example, if the angle difference between the target parking direction and the current driving direction is an angle other than 0 degrees, 90 degrees, 180 degrees and 270 degrees (such as 30 degrees, 45 degrees or 60 degrees), the area type of the parking area can be defined as an inclined parking area.

[0070] For example, the movable device is a vehicle and the parking area is a parking space, the area type of the parking area can be the type of the parking space, which can include parallel parking space, vertical parking space and inclined parking space. Among them, the parallel parking space can be a parking space where the vehicle is parked parallel to the driving direction of the road; the vertical parking space can be a parking space where the vehicle is parked perpendicular to the driving direction of the road; the inclined parking space can be a parking space where the vehicle is parked at an angle of 30 degrees, 45 degrees or 60 degrees to the driving direction of the road. It should be noted that the driving direction of the road can be the current driving direction of the vehicle when locking the parking space near the parking space and starting to drive into the parking space.

[0071] Step S320, obtain historical parking information according to the first parking area.

[0072] The historical parking information can be information determined based on a historical driving path of the movable device driving into the second parking area under user control. The second parking area and the first parking area can be parking areas of the same type, for example, the second parking area and the first parking area can both be vertical parking areas. It can be understood that the second parking area and the first parking area can be the same parking area, or can be different parking areas but of the same type.

[0073] In some examples, the historical parking information can include one or more of the following first information to fourth information. Wherein:

[0074] The first information included in the historical parking information can be a historical driving path of the movable device driving into the second parking area under user control.

[0075] For example, the historical driving path can be directly taken as the historical parking information. Alternatively, if there are multiple candidate historical driving paths of the movable device driving into the second parking area under user control, the multiple candidate historical driving paths can be aggregated to obtain the historical driving path, and the number of historical driving paths is less than or equal to the number of candidate historical driving paths. By aggregation, similar candidate historical driving paths can be fused into one historical driving path.

[0076] The second information included in the historical parking information can be at least one target position point determined based on the historical driving path of the movable device driving into the second parking area under user control.

[0077] The target position point can be represented in a parking area coordinate system, which can be a coordinate system constructed with a center point of the parking area as the origin, an extension direction of an entrance boundary line of the parking area as the x-axis, and a direction perpendicular to the x-axis as the y-axis. In this way, the coordinates of the target position point determined based on the center point of the second parking area can still be used when the center point of the first parking area is taken as the origin.

[0078] For example, the target position point can be any position point of the historical driving path, such as a gear shifting position point, a turning point with a large curvature, etc. For example, the above-mentioned target position point can include a gear shifting position point at which the movable device performs a gear shifting operation in the historical driving path.

[0079] The third information included in the historical parking information can be a device historical state of the movable device at each target position point.

[0080] The device historical state can include at least one of a heading angle, a speed, an acceleration, and a gear state of the movable device at the target position point. The gear state can include any one of a forward gear, a reverse gear, a forward gear to reverse gear switching, a reverse gear to forward gear switching, etc.

[0081] The fourth information included in the historical parking information can be a historical drivable area determined based on a historical driving path of the movable device.

[0082] For example, if the historical driving path is a plurality of paths, the historical drivable area can be a drivable area determined based on a union of the plurality of historical driving paths.

[0083] The historical parking information can include one or more of the first to fourth information described above, for example, the historical parking information can at least include at least one target position point determined based on a historical driving path of the movable device under user control into the second parking area. Since the historical parking information is information determined based on the historical driving path of the movable device under user control into the second parking area, it can reflect the individual preferences of the user for the driving path of the movable device.

[0084] In step S330, a target path of the movable device from the current position into the first parking area is generated according to the historical parking information.

[0085] For example, the current position of the movable device can be taken as the starting point, and the target position expected after the movable device parks in the first parking area can be taken as the end point. In combination with the surrounding environment information and the historical parking information of the movable device, path planning is performed to obtain the target path of the movable device from the current position into the first parking area.

[0086] In some examples, the target path generated in this step has a first similarity to the historical parking information greater than or equal to a first preset similarity threshold. The first similarity can include a position similarity and / or a device state similarity, and the first preset similarity threshold can also include a position similarity threshold and / or a device state similarity threshold. The first preset similarity threshold can be any value preset in advance, for example, a value in the range of 0 to 1, and the preset similarity threshold can be 0.5, 0.8 or 0.9. The first preset similarity threshold can also be the maximum value among the similarities of a plurality of planning paths generated based on the historical parking information to the historical parking information.

[0087] There can be various ways to obtain the first similarity, for example:

[0088] In one implementation, when the historical parking information includes at least one target position point, the first similarity can at least include a position similarity calculated based on the minimum distance difference between each target position point and the target path.

[0089] In another implementation, in a case where the historical stop information includes at least one target position point and a device historical state of each target position point, the first similarity can include a position similarity and a device state similarity. For example, the position similarity can be calculated based on a distance difference between each target position point and a target path point corresponding to the target position point, which can be the closest point to the target position point on the target path. For another example, the device state similarity can be determined based on a device state difference between each target position point and the target path point, which can represent a difference between the device historical state of the movable device at each target position point and a device planned state of the planned movable device at the target path point corresponding to the target position point. For an example, the closest target path point to each target position point on the target path can be determined, the distance difference between each target position point and the corresponding target path point can be calculated, and the device state difference between the device historical state of the movable device at each target position point and the device planned state of the planned movable device at the target path point corresponding to the target position point can be calculated, so that the first similarity can be calculated based on the distance difference and the device state difference. It should be noted that the device state difference can include at least one of a difference in heading angle, a difference in speed, a difference in acceleration, and a difference in gear state (e.g., 1 for the same and 0 for the different).

[0090] In another implementation, in a case where the historical stop information includes the historical driving path, the first similarity can represent a similarity between the target path and the historical driving path, which can be calculated by a geometric space similarity calculation method, a time series similarity measurement method, or the like.

[0091] In this way, the first similarity between the target path and the historical stop information can be obtained by any of the above implementations, and it is determined whether the first similarity is greater than or equal to a first preset similarity threshold.

[0092] In step S340, the movable device is controlled to drive according to the target path.

[0093] For an example, the movable device can be controlled to drive based on the target path to enter the first stop area, so as to complete the stop of the movable device.

[0094] Based on the steps S310 to S340, the first parking area to be driven into by the movable device is determined first; the historical parking information of the movable device driving into the second parking area of the same type under the control of the user is obtained according to the first parking area; the target path of the movable device driving into the first parking area from the current position is generated according to the historical parking information, so that the first similarity between the target path and the historical parking information is greater than or equal to the first preset similarity threshold; and the movable device is controlled to drive according to the target path. In this way, since the historical parking information is information determined based on the historical driving path of the movable device driving into the second parking area under the control of the user, the historical parking information can be used to reflect the individual preference of the user for the driving path of the movable device, thereby improving the efficiency and reliability of path planning and improving the user experience when the movable device is parked. For a vehicle, the user experience in an automatic parking scenario can be improved.

[0095] In some embodiments of the present disclosure, the manner in which the step S330 generates the target path according to the historical parking information can be that a preset path search algorithm is executed according to the historical parking information to generate the target path of the movable device driving into the first parking area from the current position.

[0096] The preset path search algorithm can be a heuristic path search algorithm, such as an A-star search algorithm, a Dijkstra algorithm, a BFS (Breadth-First Search) search algorithm, etc.

[0097] In some examples, the preset path search algorithm can include a first cost function, which can be used to represent the first similarity between the target path and the historical parking information. For example, the first cost function can obtain a first cost of a to-be-searched node, which can be inversely proportional to the first similarity, i.e., the greater the first similarity, the smaller the first cost, and the to-be-searched node is more preferred as a target node on the target path. It should be noted that the specific manner of obtaining the first similarity can refer to the description in the foregoing embodiments of the present disclosure, which will not be described here.

[0098] It should be noted that the preset path search algorithm can also include cost functions in related technologies such as heuristic cost and path cost. Based on the present embodiment, the first cost function described above can be added to the cost functions of the preset path search algorithm in related technologies, so that the target path obtained by searching can be constrained based on the first similarity between the target path and the historical parking information. The multiple cost functions of the preset path search algorithm can be weighted and averaged to evaluate the candidate path obtained by searching, and the target path is output by selection.

[0099] In some examples, a set of spatial nodes corresponding to each target location can be generated based on historical docking information; the spatial nodes in the set of spatial nodes are used as candidate nodes for a preset path search algorithm to search and generate the target path.

[0100] For example, the aforementioned historical parking information includes at least one target location point, and the distance between each spatial node in the set of spatial nodes and the target location point can be less than or equal to a first preset distance threshold.

[0101] For example, each target location point can be used as the center of a circle, and a first preset distance threshold can be used as the radius to obtain a target spatial region. Multiple spatial nodes can be sampled in the target spatial region to generate a set of spatial nodes corresponding to each target location point. Figure 4 This is a schematic diagram of a spatial node set provided in an embodiment of this disclosure. For example... Figure 4 As shown, when planning the route between the starting point 401 and the ending point 402, target locations 410 and 420 are determined based on historical stop information. The spatial node set 411 corresponding to target location 410 includes multiple spatial nodes, and the spatial node set 421 corresponding to target location 420 also includes multiple spatial nodes. Each target location's corresponding spatial node set includes the target location itself. It should be noted that... Figure 4 The endpoint 402 is represented by the state after a mobile device (such as a vehicle) is parked in a parking area (such as a parking space).

[0102] Furthermore, the aforementioned historical docking information may also include the historical device status of the mobile device at each target location. The set of spatial nodes may also include the expected device status corresponding to each spatial node. The second similarity between the expected device status corresponding to the spatial node and the historical device status at the target location corresponding to the spatial node may be greater than or equal to a second preset similarity threshold. This set of spatial nodes may also be referred to as a state spatial node set.

[0103] The device's historical state can include at least one of the following: heading angle, speed, acceleration, and gear position when the mobile device is at the target location. The second similarity can characterize the difference between the expected state of the device corresponding to the spatial node (e.g., heading angle, speed, acceleration, or gear position) and the historical state of the device corresponding to the target location (e.g., heading angle, speed, acceleration, or gear position). The second preset similarity threshold can be a pre-set maximum difference, such as the maximum difference in heading angle, speed, or acceleration. It should be noted that if the device state includes a gear position, which can be represented by 0 and 1 (e.g., 0 for reverse and 1 for forward), then the second preset similarity threshold between the gear position in the expected state and the gear position in the historical state can be 0, meaning their gear positions are the same.

[0104] In this way, the spatial nodes in the set of spatial nodes are taken as candidate nodes of the preset path search algorithm, and the target path is searched to generate, so that the first similarity between the target path and the historical parking information is greater than or equal to the first preset similarity threshold.

[0105] In some examples, the step S330 of generating the target path according to the historical parking information can be implemented based on a graph search path planning module. For example, in an automatic parking process, a set of state space nodes is constructed around a target position point included in the historical parking information, and a path is searched through a graph structure. Each node in the set of state space nodes includes a movable device state (for example, a position, an attitude, and a gear state) and a second similarity to the target position point. In the search process, a heuristic search (for example, an A-star search algorithm or a Dijkstra algorithm) can be used to obtain a plurality of candidate paths, and the candidate paths are weighted and evaluated in combination with a first similarity between the search path and the target position point, and the target path is output by selection to generate.

[0106] In some embodiments of the present disclosure, the control method can further determine a parking mode of the movable device, and in a case where the parking mode of the movable device is a preset mode, the historical parking information can be acquired according to the first parking area, and the target path can be generated according to the historical parking information and the environmental information. Conversely, in a case where the parking mode of the movable device is not the preset mode, the historical parking information can not be considered, and the target path can be directly generated based on the environmental information.

[0107] The parking mode can be a mode determined based on a user input, and the preset mode can be used to indicate that the movable device uses the historical parking information to assist in generating the target path after determining the first parking area. In this way, the user can autonomously decide whether to enable the preset mode to use the historical parking information to assist in generating the target path.

[0108] In some examples, if the target path fails to be generated based on the historical parking information, for example, the target path fails to be searched and generated based on the preset path search algorithm, the historical parking information can not be used, and the current position of the movable device can be directly taken as a starting point to re-execute a general path planning algorithm to generate the target path. In addition, a near-distance obstacle avoidance strategy can be combined to ensure the driving safety of the movable device. In this way, the reliability of vehicle control can be further improved.

[0109] In some embodiments of the present disclosure, the historical parking information can be acquired by the following steps: acquiring a historical driving path of the movable device entering the second parking area under user control, and generating the historical parking information according to the historical driving path.

[0110] In some examples, the server can record a historical driving path of the movable device entering the second parking area, and generate the historical parking information according to the historical driving path.

[0111] In some other examples, the historical driving path of the movable device entering the second parking area under user control can be obtained in response to a user inputted teaching start instruction, and the historical parking information can be generated according to the historical driving path. For example, after receiving the user inputted teaching start instruction, the movable device enters a teaching mode, and the historical driving path of the movable device entering the second parking area under user control is obtained, so as to realize the user control over the historical parking information, and avoid generating the historical parking information based on the historical driving path that is not expected by the user.

[0112] In some other examples, the historical parking information can be displayed to the user, and the user specified historical parking information can be deleted in response to a user inputted information deletion instruction. For example, if the second parking area of the movable device corresponds to one or more historical parking information, the historical parking information can be displayed to the user, and if the user determines that one or more historical parking information does not meet the user expectation, the historical parking information that does not meet the user expectation can be deleted by the information deletion instruction, and the historical parking information that meets the user expectation can be retained. In this way, the target path generated based on the historical parking information can be more in line with the user habits and individual preferences, and the user experience can be further improved.

[0113] In some examples, at least one target position point can be determined according to the historical driving path, so as to generate the historical parking information.

[0114] For example, the target position point can include a gear shifting position point. During the process that the user controls the movable device to enter the second parking area, the user controlled gear shifting behavior and its space-time position can be recorded, the position point at which the gear shifting behavior occurs can be taken as the target position point, and the relative position of the target position point relative to the second parking area can be recorded, for example, the relative offset of the position point at which the forward gear is switched to the reverse gear to the second parking area. Optionally, the above target position point can be saved in the user behavior database as the historical parking information.

[0115] The following is an example of a historical driving path and a target position point. Figure 5 and Figure 6 The historical driving path and the target position point are further illustrated in the following examples. Figure 5 is a schematic diagram of a historical driving path provided by an embodiment of the present disclosure, as shown in Figure 5As shown, the historical driving path of the user control the movable device to drive from the starting point S to the ending point E of the parking area includes a route sequentially connected by S-A-B-C-E, wherein A / B / C are three shift points, for example, the movable device drives from the starting point S to A, continues to drive to B after switching from forward gear to reverse gear, continues to drive to C after switching from reverse gear to forward gear, and continues to drive to E after switching from forward gear to reverse gear, thereby completing parking. It should be noted that, Figure 5 The two corner points of the parking area entrance in the above formula are P0 and P1 as shown in the figure, and the wall opposite to the parking area will affect the path planning of the movable device driving into the parking area.

[0116] Figure 6 is a schematic diagram of a target position point provided by an embodiment of the present disclosure. Based on Figure 5 The historical driving path as shown, the three position points A / B / C as shown in Figure 6 are extracted as target position points in the historical parking information, and a state space node set corresponding to each position point can be constructed with each target position point as the center and a preset length as the radius, as shown by the dashed circle in the figure.

[0117] In an implementation manner, only information related to the target position point, such as the position of the target position point and the device historical state (such as attitude, heading angle, speed, acceleration and gear state), and the like, can be recorded, and the entire historical driving trajectory does not need to be recorded, so as to improve efficiency and reduce data storage amount.

[0118] In some examples, the historical driving path can be one or more, and the historical driving path can be subjected to feature extraction and clustering processing to generate historical parking information reflecting individual preferences of the user for the driving path of the movable device. For example, if the shift point positions in the multiple historical driving paths are not completely the same, the shift points can be subjected to clustering processing based on positions, for example, multiple shift points with similar positions can be clustered into one target position point to generate the historical parking information. For another example, if the multiple historical driving paths are not completely the same, the multiple historical driving paths can be subjected to clustering processing based on positions, for example, multiple historical driving paths with similar positions can be clustered into one historical driving path to generate the historical parking information.

[0119] In this way, the historical parking information reflecting individual preferences of the user for the driving path of the movable device can be generated in the above manner, the historical parking information can also be called paradigm data recording individual shift behaviors of the user, and the target path of the movable device driving into the first parking area from the current position based on the historical parking information can be more close to the individual preferences of the user, thereby improving the efficiency and reliability of the path planning and improving the user experience when controlling the movable device to park.

[0120] In some embodiments of the present disclosure, the historical parking information described above can include historical drivable areas determined based on the historical driving path of the movable device (i.e., the aforementioned fourth information). In this way, the control method can further include: detecting a target obstacle of a preset type according to sensor data of the movable device; and determining whether the target obstacle can be driven through by the movable device according to the target obstacle and the historical drivable areas. The target obstacle of the preset type can be a static obstacle that is labeled by a perception component of the movable device as having a detected obstacle height with a credibility less than or equal to a preset credibility threshold. The credibility threshold can be a preset value, for example, the credibility can have a value range of 0 to 1, and the credibility threshold can be 0.5, 0.3, or 0.2. In this way, for obstacles that cannot be accurately detected by the perception component, it can be determined whether the obstacle can be driven through by the movable device based on the historical parking information. Further, the target obstacle of the preset type can also satisfy a condition that the height is less than or equal to a first preset height threshold. The first preset height threshold can be a preset data, and the first preset height threshold can be greater than or equal to a second preset height threshold that the movable device can drive through. The second preset height threshold can be a threshold determined based on device parameters (e.g., chassis height) of the movable device. Alternatively, the target obstacle of the preset type can include low roadside or other obstacles.

[0121] In some examples, if the target obstacle is located within the historical drivable areas, it is determined that the target obstacle can be driven through by the movable device.

[0122] In other examples, if the target obstacle is located outside the historical drivable areas, it can be determined whether the target obstacle can be driven through by the movable device based on an external parameter of the target obstacle. The external parameter can include the height of the target obstacle. For example, if the height of the target obstacle is greater than a second preset height threshold that the movable device can drive through, the target obstacle cannot be driven through by the movable device, and vice versa, if the height of the target obstacle is less than or equal to the second preset height threshold that the movable device can drive through, the target obstacle can be driven through by the movable device.

[0123] It should be noted that due to the performance limitations of the perception modules in intelligent connected systems, they cannot accurately determine whether mobile devices can pass through pre-defined types of target obstacles, such as low-lying obstacles with high ambiguity or traversable curbs. Therefore, intelligent connected systems often adopt a conservative strategy to avoid these target obstacles, which may lead to lengthy path planning and path planning failures. In this embodiment, however, for pre-defined types of target obstacles, the ability of mobile devices to pass through can be determined based on historical parking information. For example, if the target obstacle is located within a historically drivable area, it is determined that the target obstacle can be passed through. This avoids unnecessary redundancy in the generated target path and improves the efficiency of mobile devices entering the parking area.

[0124] Optionally, in this embodiment, if the speed of the mobile device is less than or equal to a preset speed threshold, it can be determined whether the target obstacle can be traversed by the mobile device based on the target obstacle and the historical drivable area; conversely, if the speed of the mobile device is greater than the preset speed threshold, it can still be determined whether the target obstacle can be traversed by the mobile device based on the shape parameters of the target obstacle. The preset speed can be a pre-set low-speed driving threshold, such as 10 km / h, 5 km / h, or 2 km / h.

[0125] by Figure 7 For example, Figure 7 This is a schematic diagram of a historical drivable area provided in an embodiment of the present disclosure. The historical drivable area 701 can be determined based on the historical driving path of the mobile device. If a target obstacle of a preset type is detected to be located in the historical drivable area 701 based on the sensor data of the mobile device, it can be determined whether the target obstacle can be driven through by the mobile device. Conversely, if the target obstacle is located in the area 702 that the user has not driven through, it is dynamically determined whether the target obstacle can be driven through by the mobile device based on the shape parameters of the target obstacle.

[0126] In this way, in low-speed scenarios, determining whether a target obstacle can be traversed by a mobile device based on the target obstacle and historical drivable areas can further improve the reliability of path planning.

[0127] Figure 8 This is a flowchart illustrating a control method provided in an embodiment of this disclosure. The control method can be... Figure 1 The illustrated mobile device and / or server execute. For example... Figure 8 As shown, the control method of this embodiment may include the following steps S810 to S860.

[0128] Step S810: Obtain historical docking information for mobile devices.

[0129] For example, a historical driving path of the movable device driving into the second parking area under user control can be acquired, and historical parking information can be generated according to the historical driving path.

[0130] In some examples, when the movable device is in a user teaching mode, a historical driving path of the movable device driving into the second parking area under user control can be acquired, and historical parking information can be generated according to the historical driving path.

[0131] In some examples, the movable device can be caused to enter the user teaching mode to record the historical parking information in response to a user input teaching start instruction. For example, each time the trajectory and gear shifting point of the movable device under user control is recorded as a (position, pose, gear shifting state) tuple, thereby obtaining the historical parking information.

[0132] Further, feature extraction and gear shifting point clustering can be performed to generate a user personalized parking model as the historical parking information.

[0133] Step S820, in an automatic parking scenario of the movable device, a first parking area to be driven into by the movable device is determined.

[0134] Step S830, historical parking information is acquired according to the first parking area.

[0135] For example, in an automatic parking scenario of the movable device, after the first parking area (for example, a parking space) to be parked into is determined, the first parking area is taken as a reference to query matching historical parking information (for example, a gear shifting position point).

[0136] Step S840, a set of spatial nodes is generated according to the historical parking information.

[0137] For example, a set of spatial nodes corresponding to each target position point can be generated according to the historical parking information.

[0138] Step S850, a preset path search algorithm is executed according to the set of spatial nodes to search for a target path.

[0139] For example, the spatial nodes in the set of spatial nodes can be taken as candidate nodes of the preset path search algorithm to search for the target path.

[0140] In some examples, a state diagram can be constructed according to the historical parking information, and a feasible path can be constructed in combination with perception map information. A paradigm similarity evaluation function can be introduced in path searching to improve naturalness of the path and consistency with user preferences.

[0141] Furthermore, the perception module of the mobile device can detect and determine suspicious areas (i.e., whether there are preset type of target obstacles) in real time. Based on historical parking information, it integrates user teaching behavior and overtaking records (such as information on the mobile device's historical driving path through the suspicious area) and dynamically updates the label of whether the suspicious area is drivable to improve the efficiency of path planning.

[0142] Step S860: Control the movement of the mobile device according to the target path.

[0143] It should be noted that the specific implementation of the above steps in this embodiment can be referred to the description in the foregoing embodiments of this disclosure, and will not be repeated here.

[0144] In this way, based on historical parking information and a preset path search algorithm, the optimal target path can be generated and the mobile device can be controlled to drive until it enters the first parking area and completes parking, thereby improving the user experience when controlling the parking of mobile devices.

[0145] Figure 9 This is a schematic diagram of the structure of a control device provided in an embodiment of this disclosure. Figure 9 As shown, the control device 1000 may include a memory 1010 and a processor 1020. The memory 1010 may be used to store computer instructions, and the processor 1020 may be used to retrieve computer instructions from the memory 1010 to execute all or part of the steps of any of the methods in the foregoing embodiments of this disclosure. The processor may be one or more processors, which may execute instructions individually or jointly. Similarly, the memory may be one or more memories, which may store the aforementioned computer instructions individually or jointly.

[0146] In some examples, the control device can be Figure 1 The server and / or mobile device in the context. In other examples, the control device can also be any electronic device, such as a controller for a mobile device.

[0147] This disclosure also provides a mobile device that may include a memory and a processor. The memory may be used to store computer instructions, and the processor may be used to retrieve the computer instructions from the memory to perform all or part of the steps of any of the methods in the foregoing embodiments of this disclosure. The processor may be one or more processors, which may execute the instructions individually or jointly. Similarly, the memory may be one or more memories, which may store the aforementioned computer instructions individually or jointly.

[0148] The mobile device provided in this embodiment can be... Figure 1 or Figure 2The illustrated movable device. In some examples, the movable device can be a vehicle, which can be an electric vehicle, a hybrid vehicle, a fuel cell vehicle, or other type of vehicle. The vehicle can be an autonomous vehicle or a non-autonomous vehicle.

[0149] The embodiments of the present disclosure further provide a computer readable storage medium, having stored thereon a computer program, which, when executed by a processor, implements any of the methods of the preceding embodiments of the present disclosure. Alternatively, the computer readable storage medium can be a non-transitory storage medium, but is not limited to this, and can also be a transitory storage medium.

[0150] The embodiments of the present disclosure further provide a chip, which can include a processing unit that can be used to execute all or part of the steps of any of the methods of the preceding embodiments of the present disclosure. The chip can be a chip in the form of an application specific integrated chip (ASIC), a system on chip (SOC), a field programmable gate array (FPGA), etc., and the embodiments of the present disclosure are not limited in this regard. Alternatively, the chip can further include a storage unit that can be used to store computer instructions, and the processing unit can be used to call the computer instructions from the storage unit to execute all or part of the steps of any of the methods of the preceding embodiments of the present disclosure.

[0151] The embodiments of the present disclosure further provide a computer program product, which can include a computer program that, when executed by a processor, can implement any of the methods of the preceding embodiments of the present disclosure.

[0152] The present disclosure can be a system, a method, and / or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions stored thereon for causing a processor to carry out any of the methods of the preceding embodiments of the present disclosure.

[0153] Computer readable storage media can be tangible storage media which can retain and store instructions for use by an instruction execution device. Computer readable storage media can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer readable storage media include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0154] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0155] Computer readable program instructions for carrying out operations of the present disclosure can be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate array (FPGA), or programmable logic array (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0156] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0157] These computer readable program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can include random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other data storage device. When the computer readable program instructions are loaded into the computer and other programmable data processing apparatus, a series of operational steps are implemented that provide processes such that the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0158] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0159] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0160] Embodiments of the present disclosure have been described above, and the description is intended to be illustrative, and not restrictive, of the disclosed embodiments. Many modifications and variations of the disclosed embodiments are possible in light of the above teachings. It is therefore to be understood that within the scope of the disclosed embodiments, modifications and variations of the disclosed embodiments can be practiced. It is also to be understood that the specific order or hierarchy of steps in the processes disclosed is an illustration of exemplary processes. Based upon the description and illustrations provided herein, those skilled in the art will understand that changes can be made to the order of steps in the processes and that many of the individual steps can be modified or eliminated. Additionally, the description and illustrations provided herein are not meant to limit the scope of the disclosed embodiments. The scope of the disclosed embodiments is limited only by the claims.

Claims

1. A control method characterized by, The method comprises: determining a first parking area to be driven into by a movable device; acquiring historical parking information according to the first parking area; wherein the historical parking information at least comprises at least one target position point determined based on a historical driving path of the movable device driving into a second parking area under user control, the second parking area being a same type of parking area as the first parking area; generating a target path for the movable device to drive into the first parking area from a current position according to the historical parking information, so that a first similarity of the target path to the historical parking information is greater than or equal to a first preset similarity threshold; controlling the movable device to drive according to the target path.

2. The method of claim 1, wherein the at least one target position point at least comprises a gear shifting position point at which the movable device performs a gear shifting operation in the historical driving path; the historical parking information further comprises a device historical state of the movable device at each target position point, the device historical state comprising at least one of a heading angle, a speed, an acceleration and a gear state of the movable device at the target position point, and the first similarity comprises a device state similarity.

3. The method of claim 1, wherein, The generating of the target path for the movable device to drive into the first parking area from the current position according to the historical parking information comprises: performing a preset path search algorithm according to the historical parking information to generate the target path for the movable device to drive into the first parking area from the current position; wherein the preset path search algorithm at least comprises a first cost function for acquiring the first similarity of the target path to the historical parking information.

4. The method of claim 3, wherein, The performing of the preset path search algorithm according to the historical parking information to generate the target path for the movable device to drive into the first parking area from the current position comprises: generating a spatial node set corresponding to each target position point according to the historical parking information; wherein each spatial node in the spatial node set is within a distance less than or equal to a first preset distance threshold from the target position point; taking the spatial nodes in the spatial node set as candidate nodes of the preset path search algorithm to search and generate the target path.

5. The method of claim 4, wherein the historical parking information further comprises a device historical state of the movable device at each target position point; and the spatial node set further comprises a device expected state corresponding to each spatial node, the device expected state corresponding to the spatial node having a second similarity to a device historical state of a target position point corresponding to the spatial node greater than or equal to a second preset similarity threshold.

6. The method of claim 1, wherein the historical parking information is generated in advance based on the following manner: acquiring the historical driving path of the movable device driving into the second parking area under user control; and determining at least one target position point according to the historical driving path to generate the historical parking information. The historical parking information is obtained according to the first parking area, including: in a case that a parking mode of the movable device is a preset mode, obtaining the historical parking information according to the first parking area; wherein the parking mode is a mode determined based on a user input, and the preset mode is used to indicate that the movable device uses the historical parking information to assist in generating the target path after the first parking area is determined.

7. The method according to any one of claims 1 to 6, characterized in that, The historical parking information further includes a historical drivable area determined based on a historical driving path of the movable device. The method further includes: detecting a target obstacle of a preset type according to sensor data of the movable device; determining whether the target obstacle can be driven through by the movable device according to the target obstacle and the historical drivable area.

8. The method of claim 7, wherein, The determining whether the target obstacle can be driven through by the movable device according to the target obstacle and the historical drivable area includes: if the target obstacle is located in the historical drivable area, determining that the target obstacle can be driven through by the movable device; or if the target obstacle is located outside the historical drivable area, determining whether the target obstacle can be driven through by the movable device based on an external shape parameter of the target obstacle.

9. A control device characterized by comprising: a memory and a processor, the memory being used to store computer instructions, and the processor being used to call the computer instructions from the memory to execute the method in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, a computer program is stored thereon, and the computer program, when executed by a processor, implements the method in any one of claims 1 to 8.

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