Parking space detection method, device, equipment, medium, program product and vehicle

Abstract

The present disclosure relates to a parking space detection method, device, equipment, medium, program product and vehicle. The parking space detection method comprises: acquiring environment information of a vehicle at a current time and a first bird's eye view (BEV) image frame of the vehicle at a previous time; the environment information comprises a surround view image frame around the vehicle and vehicle pose information of the vehicle; determining a second BEV image frame according to the surround view image frame, the vehicle pose information of the vehicle and the first BEV image frame; and performing parking space detection based on the second BEV image frame. The parking space detection method provided by the present disclosure can provide more complete data basis for vehicle parking, which is more convenient for vehicle parking, thereby improving the accuracy, safety and parking efficiency of parking.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of automatic driving, and in particular to a parking space detection method, device, equipment, medium, program product and vehicle. BACKGROUND

[0002] In the related art, parking space detection is a basic part of environment perception of an automatic parking system. In the cruising stage, parking space detection can obtain complete storage space information of a parking space for storage space detection due to less occlusion. However, in the parking stage, the parking space detection result is not complete due to occlusion of the vehicle itself, thereby affecting automatic parking of the vehicle. SUMMARY

[0003] The present disclosure provides a parking space detection method, device, equipment, medium, program product and vehicle to at least solve the technical problem that the parking space detection result is not complete in the related art, thereby affecting automatic parking of the vehicle. The technical solutions of the present disclosure are as follows.

[0004] According to a first aspect of an embodiment of the present disclosure, a parking space detection method is provided, comprising:

[0005] obtaining environment information of a vehicle at a current time and a first bird's eye view (BEV) image frame of the vehicle at a previous time; wherein the environment information comprises a surround view image frame around the vehicle and vehicle pose information of the vehicle;

[0006] determining a second BEV image frame according to the surround view image frame, the vehicle pose information of the vehicle and the first BEV image frame;

[0007] performing parking space detection based on the second BEV image frame.

[0008] In a possible implementation, the determining of the second BEV image frame according to the surround view image frame, the vehicle pose information of the vehicle and the first BEV image frame comprises:

[0009] performing splicing processing on the environment image frame, the vehicle pose information and the first BEV image frame to obtain the second BEV image frame.

[0010] In a possible implementation, the surround view image frame comprises at least surround view image frames of at least four sides around the vehicle, and the environment image frame is collected by a camera device arranged on the vehicle; the camera device is arranged on each of the four sides of the vehicle, and at least one camera device is arranged on each side.

[0011] In a possible implementation, the method further comprises:

[0012] storing the second BEV image frame.

[0013] In a possible implementation, the method further includes:

[0014] deleting the first BEV image frame.

[0015] According to a second aspect of the embodiments of the present disclosure, a parking space detection apparatus is provided, including:

[0016] an acquisition module, configured to acquire environment information of a vehicle at a current time and a first bird's eye view (BEV) image frame of the vehicle at a previous time; wherein the environment information includes a surround view image frame around the vehicle and vehicle pose information of the vehicle;

[0017] a determination module, configured to determine a second BEV image frame according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame;

[0018] a detection module, configured to perform parking space detection based on the second BEV image frame.

[0019] In a possible implementation, the determination module is configured to:

[0020] stitch the environment image frame, the vehicle pose information, and the first BEV image frame to obtain the second BEV image frame.

[0021] In a possible implementation, the surround view image frame includes at least four surround view image frames of at least four sides around the vehicle, and the environment image frame is collected by a camera device arranged on the vehicle; the camera device is arranged on each of the four sides of the vehicle, and at least one camera device is arranged on each side.

[0022] In a possible implementation, the method further includes:

[0023] a storage module, configured to store the second BEV image frame.

[0024] In a possible implementation, the method further includes:

[0025] a deletion module, configured to delete the first BEV image frame.

[0026] According to a third aspect of the embodiments of the present disclosure, an electronic device is provided, including:

[0027] a processor;

[0028] a memory for storing instructions executable by the processor;

[0029] wherein the processor is configured to execute the instructions to implement the parking space detection method according to any one of the first aspect.

[0030] According to a fourth aspect of the embodiments of the present disclosure, a storage medium is provided, which, when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform the parking space detection method according to any one of the first aspect.

[0031] According to a fifth aspect of the embodiments of the present disclosure, a computer program product is provided, which comprises a computer program, and the computer program, when executed by a processor, implements the parking space detection method according to any one of the first aspect.

[0032] According to a sixth aspect of the embodiments of the present disclosure, a vehicle is provided, which comprises the parking space detection apparatus according to any one of the second aspect.

[0033] The technical solutions provided by the embodiments of the present disclosure at least bring the following beneficial effects:

[0034] In the embodiments of the present disclosure, the environment information of the vehicle at the current moment and the first bird's eye view (BEV) image frame of the vehicle at the previous moment are acquired; wherein the environment information comprises a surround view image frame around the vehicle and vehicle pose information of the vehicle; a second BEV image frame is determined according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame; and a parking space is detected based on the second BEV image frame. In this way, since the vehicle pose information of the vehicle can represent the position and attitude of the vehicle, the surround view image frame can represent the information around the vehicle, and the first BEV image frame at the previous moment includes the information of the position covered by the vehicle body at the previous moment, i.e., the missing part of the image information in the second BEV image. Therefore, the second BEV image determined based on the vehicle pose information of the vehicle, the surround view image frame, and the first BEV image frame at the previous moment can completely represent the image information around the vehicle and at the bottom of the vehicle at the current moment. In this way, more complete data basis can be provided for the vehicle parking, which is more convenient for the vehicle parking, so as to improve the accuracy, safety and parking efficiency of the parking.

[0035] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0036] The accompanying drawings, which are incorporated into and form part of the specification, illustrate one embodiment consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure, and do not constitute an undue limitation on the present disclosure.

[0037] Figure 1 is a flowchart of a parking space detection method according to an exemplary embodiment.

[0038] Figure 2is a schematic diagram of a setting position of a camera device according to an example embodiment.

[0039] Figure 3 is a flowchart of another parking space detection method according to an example embodiment.

[0040] Figure 4 is a block diagram of a parking space detection device according to an example embodiment.

[0041] Figure 5 is a block diagram of an electronic device according to an example embodiment. DETAILED DESCRIPTION

[0042] In order for those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings.

[0043] It should be noted that the terms "first", "second", and the like in the specification and claims of the present disclosure and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in an order other than that illustrated or described herein. The embodiments described in the following example embodiments do not represent all embodiments consistent with the present disclosure. Rather, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0044] The parking space detection method, device, equipment, medium, program product and vehicle provided by the embodiments of the present disclosure will be described in detail below with reference to the drawings.

[0045] Figure 1 is a flowchart of a parking space detection method according to an example embodiment, which can be applied to a vehicle, for example, a vehicle controller or a parking space detection device arranged on the vehicle, etc. As shown in Figure 1 the method can include the following steps.

[0046] In step S101, the environment information of the vehicle at the current time and the first bird's eye view (BEV) image frame of the vehicle at the previous time are acquired.

[0047] The environment information includes the surround view image frame around the vehicle and the vehicle pose information of the vehicle. The vehicle pose information may, for example, include the wheel speed, the vehicle heading angle, the tire steering angle, the tire side slip angle, etc. of the vehicle, or the vehicle pose information may only include one or several of the foregoing, or may also include other parameters representing the vehicle pose information.

[0048] In the embodiments of the present disclosure, when the parking space detection is performed, the environment information of the vehicle at the current time can be acquired, for example, the surround view image frame and the vehicle pose information of the vehicle at the current time can be acquired; wherein the surround view image frame can be the image frame around the vehicle, and the bird's eye view (BEV) image frame of the vehicle at the previous time can also be acquired. The previous time can be the time closest to the current time and before the current time when the first BEV image frame is acquired. Taking the current time as 10:00 and acquiring the surround view image frame and the BEV image frame of the previous time every second as an example, the first BEV image frame can be the BEV image acquired at 09:59. It can be understood that the first BEV image can also be an image frame obtained based on the surround view image frame of the previous time and the BEV image frame of the previous time of the previous time. For example, still taking the current time as 10:00 as an example, the first BEV image is the BEV image frame of 09:59 at the previous time of the current time, and the previous time of the previous time is 09:58, and the BEV image frame of 09:59 can be obtained based on the surround view image frame of 09:59 and the BEV image frame of 09:58.

[0049] In step S102, the second BEV image frame is determined according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame.

[0050] In the embodiments of the present disclosure, after the surround view image frame of the vehicle at the current time, the vehicle pose information of the vehicle, and the first bird's eye view (BEV) image frame of the vehicle at the previous time are acquired, the BEV image frame at the current time, i.e., the second BEV image frame, can be determined according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame. That is, the second BEV image frame is obtained based on the surround view image frame at the current time, the vehicle pose information, and the first BEV image frame at the previous time. It can be understood that since the BEV image at each time is obtained based on the surround view image frame at the current time, the vehicle pose information, and the BEV image frame at the previous time, therefore, each time BEV image frame obtained based thereon includes the surround view image frame around the vehicle, and also includes the image frame of the position covered by the vehicle body. In this way, the second BEV image frame is more complete.

[0051] In step S103, the parking space detection is performed based on the second BEV image frame.

[0052] In the embodiments of the present disclosure, after the second BEV image frame is determined, the parking space detection can be performed based on the second BEV image. It can be understood that the implementation manner of performing the parking space detection based on the second BEV image is similar to that in the related art, and will not be described herein.

[0053] In the embodiments of the present disclosure, the environment information of the vehicle at the current moment and the first bird's eye view (BEV) image frame of the vehicle at the previous moment are acquired; the environment information comprises a surround view image frame around the vehicle and vehicle pose information of the vehicle; a second BEV image frame is determined according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame; and a parking space is detected based on the second BEV image frame. In this way, since the vehicle pose information of the vehicle can represent the position and posture of the vehicle, the surround view image frame can represent the information around the vehicle, and the first BEV image frame at the previous moment includes the information of the position covered by the vehicle body at the previous moment, i.e., the missing part of the image information in the second BEV image. Therefore, the second BEV image determined based on the vehicle pose information of the vehicle, the surround view image frame, and the first BEV image frame at the previous moment can represent the image information around the vehicle and at the bottom of the vehicle at the current moment completely. In this way, more complete data basis can be provided for the vehicle parking, the vehicle parking is more convenient, and thus the accuracy, safety, and parking efficiency of parking can be improved.

[0054] In a possible implementation, the specific implementation of determining the second BEV image frame according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame in the above step is as follows:

[0055] The environment image frame, the vehicle pose information, and the first BEV image frame are spliced to obtain the second BEV image frame.

[0056] In the embodiments of the present disclosure, when the second BEV image frame is determined according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame, the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame can be spliced, and the BEV image frame obtained by splicing is determined as the second BEV image frame. For example, the surround view image frame at the current moment and the vehicle pose information of the vehicle can be spliced on the basis of the first BEV image at the previous moment, for example, the surround view image frame at the current moment and the vehicle pose information can be rendered by the first BEV image frame, the missing part of the image at the current moment is projected from the BEV image frame at the previous moment to the BEV image frame at the current moment, and the second BEV image is obtained. It can be understood that the specific implementation method of splicing the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame is similar to the splicing method in the related art. In this way, the second BEV image frame can be more comprehensive and complete, and thus more complete data basis can be provided for the parking space detection, and the accuracy of the parking space detection can be improved.

[0057] In some possible implementation manners, the surround view image frame includes at least a surround view image frame of at least four sides around the vehicle, and the environment image frame is collected by a camera arranged on the vehicle; the camera is arranged on each of the four sides of the vehicle, and at least one camera is arranged on each side.

[0058] In the embodiment of the present disclosure, the surround view image frame can be collected by a camera arranged on the vehicle, which can be a fisheye camera or other camera that can realize surround view image collection. For example, the camera can be arranged on at least four sides of the vehicle, and at least one camera can be arranged on each side of the vehicle. The camera arranged on each side is used to collect a surround view image frame of the side. Figure 2 , Figure 2 For example, one camera is arranged on each side of the vehicle, and a schematic diagram of the arrangement position of the camera is shown. It can be understood that two or more cameras can be arranged on each side, and the number of cameras arranged on different sides can be the same or different. The embodiment of the present disclosure can take fisheye images (i.e., surround view image frames) collected by four fisheye cameras mounted on the vehicle body, vehicle pose information, and dead reckoning as inputs, use the fisheye images and dead reckoning information to supplement the mapped BEV image, and the supplemented image can include image information lost due to self-vehicle occlusion. In this way, the camera is arranged on at least four sides of the vehicle, so that the surround view image frame can be collected by the camera on each side of the vehicle.

[0059] In some possible implementation manners, the method provided by the embodiment of the present disclosure can further include the following processing.

[0060] Store the second BEV image frame.

[0061] In the embodiment of the present disclosure, after obtaining the second BEV image, or after performing the parking space detection, the second BEV image can be stored. The stored second BEV image can be used to splice the BEV image of the first time point in combination with the surround view image frame and the vehicle pose information of the next time point, for parking space detection. In this way, real-time data basis can be provided for subsequent parking space detection, so as to improve the real-time performance and accuracy of the parking space detection result.

[0062] In some possible implementation manners, the method provided by the embodiment of the present disclosure can further include the following processing.

[0063] Delete the first BEV image frame.

[0064] In the embodiments of the present disclosure, after obtaining the second BEV image or after performing the parking space detection, the first BEV image frame of the previous moment can also be deleted. That is, after obtaining the latest BEV image of the current moment each time or after performing the parking space detection each time, the BEV image of the previous moment can be deleted. In this way, the timely deletion of old data can avoid occupying too much memory resource, reduce the memory occupancy rate, avoid the situation that the memory is insufficient due to the storage of old data, thereby causing the parking space detection to fail, and further improve the parking space detection success rate.

[0065] To make the parking space detection method provided by the embodiments of the present disclosure clearer, the following will combine the accompanying drawings to Figure 3 The parking space detection method provided by the embodiments of the present disclosure will be described. As shown in Figure 3 The parking space detection method can include the following processing:

[0066] In step S301, the surround view image frame of the vehicle at the current moment and the vehicle pose information, and the first BEV image frame of the vehicle at the previous moment are obtained.

[0067] In step S302, the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame are spliced to determine the second BEV image frame.

[0068] In step S303, the parking space is detected based on the second BEV image frame.

[0069] In step S304, the second BEV image frame is stored, and the first BEV image frame is deleted.

[0070] In the embodiments of the present disclosure, by taking the fisheye image (i.e., the surround view image frame) collected by the four fisheye cameras installed on the vehicle body and the vehicle pose information and dead reckoning as inputs, the fisheye image and the vehicle pose information and dead reckoning information are used to supplement the mapped BEV image, so that the vehicle in the movement process supplements the incomplete BEV image in the parking process caused by the self-vehicle occlusion, and causes the problem of unstable detection state and missed detection of the warehouse space, improves the stability of the warehouse space detection, guarantees the original topological structure of the warehouse space, provides convenience for subsequent fusion, and provides more accurate data support for automatic parking. The present disclosure does not need to modify the original model prediction and training data, and only needs to render the input information to realize the parking space detection.

[0071] The specific implementation modes of the steps in the embodiments are similar to those of the above method embodiments, and will not be described here.

[0072] Based on the same inventive concept, the embodiments of the present disclosure also provide a parking space detection device, as shown in Figure 4 , Figure 4is a block diagram of a parking space detection device according to an exemplary embodiment. Referring to Figure 4 The parking space detection device 400 can include:

[0073] An acquisition module 410 is configured to acquire environment information of a vehicle at a current time and a first bird's eye view (BEV) image frame of the vehicle at a previous time; wherein the environment information includes a surround view image frame around the vehicle and vehicle pose information of the vehicle.

[0074] A determination module 420 is configured to determine a second BEV image frame according to the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame.

[0075] A detection module 430 is configured to perform parking space detection based on the second BEV image frame.

[0076] In some possible implementation manners, the determination module 420 is configured to:

[0077] stitch the environment image frame, the vehicle pose information, and the first BEV image frame to obtain the second BEV image frame.

[0078] In some possible implementation manners, the surround view image frame includes at least four surround view image frames of at least four sides around the vehicle, and the environment image frame is collected by a camera device arranged on the vehicle; the camera device is arranged on each of the four sides of the vehicle, and at least one camera device is arranged on each side.

[0079] In some possible implementation manners, the parking space detection device 400 further includes:

[0080] A storage module is configured to store the second BEV image frame.

[0081] In some possible implementation manners, the parking space detection device 400 further includes:

[0082] A deletion module is configured to delete the first BEV image frame.

[0083] As to the device in the above-described embodiments, the specific manners in which various modules perform operations and the technical effects have been described in detail in the embodiments of the method, and will not be described in detail here.

[0084] Based on the same inventive concept, the embodiments of the present disclosure further provide a vehicle including any one of the parking space detection devices shown in the above-described embodiments. The specific manners in which the vehicle performs operations and the technical effects have been described in detail in the embodiments of the method, and will not be described in detail here.

[0085] According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a storage medium, and a computer program product.

[0086] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure is shown. The electronic device 500 is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present disclosure described and / or claimed in this document.

[0087] As shown in Figure 5 The electronic device 500 includes a computing unit 501 that can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded into a random access memory (RAM) 503 from a storage unit 508. Various programs and data required for the operation of the device 500 can also be stored in the RAM 503. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0088] Various components in the electronic device 500 are connected to the I / O interface 505, including an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, a speaker, etc.; a storage unit 508, such as a magnetic disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0089] The computing unit 501 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 501 performs various methods and processes described above, such as the parking space detection method. For example, in some embodiments, the parking space detection method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded onto the RAM 503 and executed by the computing unit 501, one or more steps of the parking space detection method described above can be performed. Alternatively, in other embodiments, the computing unit 501 can be configured to perform the parking space detection method by any other appropriate means, such as by means of firmware.

[0090] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0091] Program code of a computer program product for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, implements the functions / operations specified in the flowcharts and / or the block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0092] In the context of this disclosure, a storage medium can be any tangible media that can contain or store program code for use by or in connection with an instruction execution system, apparatus, or device. A storage medium can be a machine-readable signal medium or a machine-readable storage medium. Storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of storage media can include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0093] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0094] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0095] The computer system can include clients and servers. This relationship can be. remote, where each server is stored on a remote computer from a client. The clients and the servers can be connected through a communication network. The relationship can be a client-server relationship over a network. Servers can be cloud servers, also known as cloud computing servers or cloud hosts, which are a host product in the cloud computing service system. The servers can be servers of a distributed system, or servers combined with a blockchain.

[0096] It should be understood that the various forms of flow shown above can be reordered, steps added or removed. For example, the steps described in the present disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of the present disclosure can be achieved, which are not limited herein.

[0097] The above detailed description does not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A parking space detection method, characterized in that, include: The vehicle acquires environmental information at the current moment and the first BEV image frame of the vehicle at the previous moment; wherein the environmental information includes surround view image frames around the vehicle and vehicle pose information of the vehicle. Based on the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame, a second BEV image frame is determined, which includes: rendering the surround view image frame and the vehicle pose information at the current moment through the first BEV image frame, and projecting the missing part of the image at the current moment from the first BEV image frame at the previous moment to the BEV image frame at the current moment to obtain the second BEV image. Parking space detection is performed based on the second BEV image frame.

2. The parking space detection method according to claim 1, characterized in that, Determining the second BEV image frame based on the surround view image frame, the vehicle pose information, and the first BEV image frame includes: The environmental image frame, the vehicle pose information, and the first BEV image frame are stitched together to obtain the second BEV image frame.

3. The parking space detection method according to claim 1, characterized in that, The surround view image frames include surround view image frames of at least four sides around the vehicle, and the environmental image frames are captured by camera devices installed on the vehicle; the camera devices are respectively installed on the four sides of the vehicle, and at least one camera device is installed on each side.

4. The parking space detection method according to claim 1, characterized in that, Also includes: Store the second BEV image frame.

5. The parking space detection method according to claim 1, characterized in that, Also includes: Delete the first BEV image frame.

6. A parking space detection device, characterized in that, include: The acquisition module is used to acquire the vehicle's environmental information at the current moment, as well as the vehicle's first BEV image frame at the previous moment; wherein, the environmental information includes the surrounding view image frames of the vehicle and the vehicle's pose information. The determining module is used to determine the second BEV image frame based on the surround view image frame, the vehicle pose information of the vehicle, and the first BEV image frame, wherein the determination includes: rendering the surround view image frame and the vehicle pose information at the current moment through the first BEV image frame, and projecting the missing part of the image at the current moment from the first BEV image frame at the previous moment to the BEV image frame at the current moment to obtain the second BEV image. The detection module is used to detect parking spaces based on the second BEV image frame.

7. The parking space detection device according to claim 6, characterized in that, The determining module is used for: The environmental image frame, the vehicle pose information, and the first BEV image frame are stitched together to obtain the second BEV image frame.

8. The parking space detection device according to claim 6, characterized in that, The surround view image frames include surround view image frames of at least four sides around the vehicle, and the environmental image frames are captured by camera devices installed on the vehicle; the camera devices are respectively installed on the four sides of the vehicle, and at least one camera device is installed on each side.

9. The parking space detection device according to claim 6, characterized in that, Also includes: A storage module for storing the second BEV image frame.

10. The parking space detection device according to claim 6, characterized in that, Also includes: The deletion module is used to delete the first BEV image frame.

11. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the parking space detection method as described in any one of claims 1 to 5.

12. A storage medium, wherein instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the parking space detection method as described in any one of claims 1 to 5.

13. A computer program product comprising a computer program that, when executed by a processor, implements the parking space detection method as described in any one of claims 1 to 5.

14. A vehicle, characterized in that, Includes the parking space detection device as described in any one of claims 6-10.

Images