Vehicle control method and device, vehicle, medium, program product and chip system

Abstract

The invention relates to a vehicle control method and device, a vehicle, a medium, a program product and a chip system in the technical field of intelligent auxiliary driving, and the method comprises the steps: obtaining an image of a parking area collected by the vehicle, determining the parking space attribute information of a parking space, and enabling the parking space attribute information to be a plurality of pieces of attribute information detected from the image, the parking space attributes are determined according to the multiple pieces of attribute information in sequence; and executing a vehicle parking prompt according to the parking space attribute information. According to the invention, by using image identification and an intelligent algorithm, intelligent auxiliary parking space attribute judgment and prompt are realized, errors and uncertainty of manual judgment are reduced, parking risks are reduced, and the convenience and parking experience of a driver in taking a car are improved.

Description

Technical Field

[0001] This disclosure relates to the field of intelligent assisted driving technology, and in particular to a vehicle control method, device, vehicle, medium, program product and chip system. Background Technology

[0002] Drivers often mistakenly park their vehicles in private or designated parking spaces. This can lead to disputes, fines, or even the risk of the vehicle being towed away. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides a vehicle control method, device, vehicle, medium, program product, and chip system.

[0004] According to a first aspect of the present disclosure, a vehicle control method is provided, comprising: acquiring an image of a parking area collected by a vehicle; determining parking space attribute information, wherein the parking space attribute information is obtained by detecting multiple attribute information from the image and sequentially determining the parking space attribute through the multiple attribute information; and executing a vehicle parking prompt based on the parking space attribute information.

[0005] The aforementioned technical solution, by acquiring images of the parking area and sequentially detecting parking space attribute information, can accurately determine whether a parking space is available for parking. This effectively avoids disputes, fines, and vehicle towing caused by drivers mistakenly occupying private, reserved, or special-operation parking spaces. It also provides clear and concise parking guidance to drivers, improving parking efficiency and safety. Thus, by utilizing image recognition and intelligent algorithms, it achieves intelligent-assisted parking space attribute judgment and prompts, reducing errors and uncertainties in manual judgment, lowering parking risks, and improving the convenience and parking experience for drivers.

[0006] In some possible implementations, acquiring an image of the parking area collected by the vehicle and determining the parking space attribute information includes: acquiring an image of the parking area collected by the vehicle and detecting the multiple attribute information; determining element information at each position in an information tuple based on the detection results of the attribute information; determining the parking space attribute information of the parking space based on the element information at each position in the information tuple, wherein if the element information at any position indicates that the parking space attribute is not a preset target result, then the determination of the parking space attribute information using the element information at the next position is stopped.

[0007] The aforementioned technical solution's detection and stopping mechanism effectively reduces unnecessary calculations, improves detection efficiency, and lowers system resource consumption. By accurately storing attribute information through information tuples, it ensures data orderliness and integrity. This enhances the accuracy and efficiency of analyzing parking space attribute information, enabling rapid and precise determination of parking space attributes, preventing drivers from parking incorrectly, reducing disputes, fines, and the risk of vehicles being towed, and improving parking safety and convenience.

[0008] In some possible implementations, determining the parking space attribute information of the parking space based on the element information at each position in the information tuple includes: if the element information at any position in the information tuple indicates that the parking space attribute is not the corresponding preset target result, then determining that the parking space attribute information is a dedicated parking space; or, If all elements in the information tuple at each location represent the parking space attribute as the corresponding preset target result, then the parking space attribute information of the parking space is determined to be a public parking space.

[0009] The aforementioned technical solution, through precise comparison of information tuple elements with preset target results, can quickly and accurately distinguish between reserved and public parking spaces. This provides drivers with clear and unambiguous parking guidance, avoiding disputes, fines, or vehicle towing caused by mistakenly parking in reserved spaces, effectively improving parking safety and compliance. Furthermore, it can be widely applied to various intelligent parking systems, improving the efficiency and intelligence of parking management while reducing management costs.

[0010] In some possible implementations, the multi-attribute information includes: parking space frame lines, parking space locking devices, and parking space-specific identifiers. The step of determining the element information at each position in the information tuple based on the detection results of the attribute information includes: if the detection results of the parking space frame lines and the parking space locking devices are both corresponding target detection results, then determining the positional relationship between the parking space locking devices and the parking space frame lines; if the detection results of the parking space frame lines and the parking space-specific identifiers are both corresponding target detection results, then determining the attribution relationship between the parking space-specific identifiers and the parking space frame lines; and determining the element information at each position in the information tuple based on the positional relationship and the attribution relationship.

[0011] The aforementioned technical solution accurately detects parking space boundaries, locking devices, and unique markings, and meticulously determines their location and ownership relationships to populate information tuples. This effectively avoids misjudgments of parking spaces due to inaccurate information, helping drivers clearly understand parking availability and reducing disputes, fines, and vehicle towing caused by mistakenly parking in designated spaces. Simultaneously, it improves the intelligence level of parking management, enabling more rational use of parking resources, reducing management costs, and enhancing the user experience.

[0012] In some possible implementations, the step of executing a vehicle parking reminder based on the parking space attribute information includes: if the parking space attribute information indicates that the parking space is a reserved parking space, then executing a no-parking reminder through a no-parking reminder method.

[0013] The aforementioned technical solution identifies designated parking spaces and provides targeted prompts and warnings, effectively preventing disputes, fines, and vehicle towing caused by drivers mistakenly parking in designated spaces, thus protecting the rights of parking space owners. Simultaneously, it provides drivers with clear and concise parking guidance, improving parking efficiency and safety.

[0014] In some possible implementations, the step of executing a no-parking reminder by means of a no-parking reminder if the parking space attribute information indicates that the parking space is a dedicated parking space includes: if the parking space attribute information indicates that the parking space is a dedicated parking space with a dedicated identifier, then displaying a no-parking reminder by means of a no-parking reminder, and displaying the dedicated identifier at the target location corresponding to the parking space.

[0015] The above-mentioned technical solution identifies parking spaces as exclusive parking spaces with special markings and can display "No Parking" and the special markings to remind drivers, effectively avoiding disputes, fines, and vehicle towing caused by drivers mistakenly parking in exclusive parking spaces, thus protecting the rights and interests of parking space owners.

[0016] In some possible implementations, the method further includes: if the driving intention of the vehicle is to park in the designated parking space, then a parking warning reminder is executed through a target warning method.

[0017] When the above technical solution detects that the driver intends to park in the designated parking space, it can trigger a target warning mode to provide a stronger reminder to the driver to park in the designated parking space. This can improve the effectiveness of the reminder to the user and reduce the risk of the user parking the vehicle in the designated parking space.

[0018] In some possible implementations, the step of providing a vehicle parking prompt based on the parking space attribute information includes: if the parking space attribute information indicates that the parking space is a public parking space, then providing a parking permission prompt by means of a parking permission prompt.

[0019] When the above technical solution identifies a parking space as a public parking space, it can issue a parking permission prompt, thereby improving the convenience of finding a public parking space to park a vehicle.

[0020] In some possible implementations, the method further includes: if the vehicle's autonomous valet parking function is active, then performing autonomous valet parking based on the parking space attribute information.

[0021] The above technical solution improves the adaptability and safety of autonomous valet parking by dynamically sensing parking space attribute information and coordinating with the autonomous valet parking function.

[0022] In some possible implementations, the step of performing autonomous valet parking based on the parking space attribute information includes: identifying the parking space as a public parking space based on the parking space attribute information, and determining it as a target valet parking space; planning a valet parking route based on the target valet parking space and the vehicle's location; detecting the target parking space based on the valet parking route, and controlling the vehicle to park in the target parking space when the vehicle reaches the target parking space.

[0023] The above technical solution combines dynamic screening of public parking spaces with the vehicle's autonomous valet parking function. Based on accurate parking space identification, it can reduce the need for users to make secondary adjustments and improve the robustness and user experience of autonomous valet parking.

[0024] According to a second aspect of the present disclosure, a vehicle control device is provided, comprising: The acquisition and determination module is configured to acquire an image of the parking area collected by the vehicle, determine the parking space attribute information, wherein the parking space attribute information is obtained by detecting multiple attribute information from the image and determining the parking space attribute in sequence through the multiple attribute information; The prompt module is configured to provide vehicle parking prompts based on the parking space attribute information.

[0025] In some possible implementations, the acquisition and determination module is configured as follows: Acquire images of the parking area captured by the vehicle and detect the multiple attribute information; Based on the detection results of the attribute information, determine the element information at each position in the information tuple; Based on the element information at each position in the information tuple, the parking space attribute information of the parking space is determined. If the element information at any position indicates that the parking space attribute is not a preset target result, then the determination of the parking space attribute information by using the element information at the next position is stopped.

[0026] In some possible implementations, the prompting module is configured as follows: If the parking space attribute information indicates that the parking space is a reserved parking space, then a no-parking reminder will be issued.

[0027] In some possible implementations, the prompting module is configured as follows: If the parking space attribute information indicates that the parking space is a public parking space, then a parking permission prompt will be executed through a parking permission prompt.

[0028] In some possible implementations, the device further includes a parking module configured to: If the vehicle's autonomous valet parking function is active, then autonomous valet parking will be performed based on the parking space attribute information.

[0029] According to a third aspect of the present disclosure, a vehicle is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the executable instructions stored in the memory to implement the method of any one of the first aspects.

[0030] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in any of the first aspects.

[0031] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0032] According to a sixth aspect of the present disclosure, a chip system is provided, the chip system comprising: a processing unit and an interface circuit, the processing unit acquiring program instructions through the interface circuit, the program instructions being executed by the processing unit, the processing unit being configured to perform the steps of the method as described in any of the first aspects.

[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0035] Figure 1 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment.

[0036] Figure 2 This is an implementation illustrated according to an exemplary embodiment. Figure 1 The flowchart for step S11.

[0037] Figure 3 This is an implementation illustrated according to an exemplary embodiment. Figure 2 The flowchart of step S112.

[0038] Figure 4 This is a flowchart illustrating another vehicle control method according to an exemplary embodiment.

[0039] Figure 5 This is a block diagram illustrating a vehicle control device according to an exemplary embodiment.

[0040] Figure 6 This is a block diagram illustrating a vehicle according to an exemplary embodiment.

[0041] Figure 7 This is a block diagram illustrating a chip system according to an exemplary embodiment. Detailed Implementation

[0042] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0043] It should be noted that all actions involving the acquisition of signals, information, or data in this disclosure are carried out in accordance with the relevant data protection laws and policies of the country where the location is situated, and with the authorization granted by the owner of the relevant device.

[0044] Before introducing the vehicle control method, device, vehicle, medium, program product, and chip system provided in this disclosure, let's first discuss the technical solutions and problems existing in the relevant scenarios. In these scenarios, ultrasonic or geomagnetic sensors are installed at each parking space to detect the presence of a vehicle, or cameras are installed to monitor each parking space point by point. Alternatively, multiple cameras are deployed in the parking lot to capture images and stitch them together to form a panoramic view, which is then processed by a central server to identify vacant parking spaces. Parking information is then disseminated through guidance screens within the parking lot or through the user's mobile application to guide drivers to park.

[0045] First, the high capital expenditures from equipment procurement, wiring, and network configuration, coupled with ongoing maintenance, result in substantial operating costs. Second, its functionality is strictly limited to specific parking lots that have undergone intelligent upgrades, failing to cover the vast majority of un-upgraded ordinary parking lots. More importantly, in many mixed-use residential and commercial buildings, while it can effectively detect parking space occupancy, it cannot distinguish between a temporarily occupied public parking space and a legally occupied private parking space unless deeply integrated with a complex backend database and access control.

[0046] In another scenario, parking infrastructure can broadcast various status information to vehicles via vehicle-to-everything (V2X) communication systems, including "parking lock status." In this mode, vehicles can proactively query the parking management system for available parking spaces using the V2X communication protocol. However, the construction of parking infrastructure is progressing slowly, making it impossible to quickly upgrade all parking lots.

[0047] In another scenario, an in-vehicle vision system based on artificial markers uses onboard cameras to recognize QR codes pre-installed on each parking space. The QR code carries information such as the parking space number and dimensions. The vehicle decodes the QR code to obtain parking space attributes, such as whether it is reserved or a public parking space. This also requires the deployment and modification of QR codes on a massive number of existing parking spaces. Furthermore, pasted or painted QR codes are highly susceptible to wear, dirt, obstruction, and malicious damage, severely impacting system reliability. In addition, it requires the active cooperation of parking lot owners to standardize and maintain each parking space, which is costly and challenging.

[0048] In conclusion, whether it's on-site sensors, V2X communication, or artificial markers, the source of their "intelligence" or "information" lies in the parking infrastructure. Vehicles in these systems play the role of passive information receivers, rather than active environmental understanders.

[0049] Figure 1 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment, such as... Figure 1 As shown, this method can be applied to the vehicle side and includes the following steps.

[0050] In step S11, an image of the parking area collected by the vehicle is acquired, and the parking space attribute information is determined. The parking space attribute information is obtained by detecting multiple attribute information from the image and determining the parking space attribute in sequence through the multiple attribute information.

[0051] The parking area image can be an image acquired by an image acquisition device (such as a camera) on the vehicle during the vehicle's driving or parking process, and can include visual information of the parking space, the vehicle parked in the parking space, and the surrounding environment of the parking space.

[0052] Among them, parking space attribute information is used to describe the characteristics of parking spaces, including whether they are public parking spaces, private parking spaces, reserved parking spaces, special operation parking spaces, etc.

[0053] This system allows for the sequential determination of parking space attributes based on multiple attribute information in a pre-defined order. The parking space's attribute information is then determined based on the results of these determinations. Specifically, the system can determine parking space attributes sequentially using multiple attribute information in a pre-defined order, or it can determine parking space attributes sequentially using multiple attribute information based on their priority.

[0054] In this embodiment, the vehicle image acquisition device continuously acquires images of the parking area, and then uses an image recognition algorithm to first detect whether there are parking spaces in the images. If parking spaces exist, it then detects whether the parking spaces have specific attribute information such as private parking space markings. This sequential detection ensures the accuracy and completeness of the information acquisition, avoids interference from irrelevant information, and reduces computational load.

[0055] In one possible implementation, the image acquisition module on the vehicle can utilize the vehicle's existing camera hardware, such as a 360-degree surround view system composed of four wide-angle or fisheye cameras. The image acquisition module captures raw image frames in real time, performs necessary preprocessing such as image correction (distortion removal) and stitching fusion, generates a top-down view or surround view, and stably delivers the processed video stream to the vision processing unit.

[0056] The vision processing unit can be a dedicated graphics processing unit or neural network processor, responsible for running the core multi-object detection algorithm, and then detecting multiple attribute information separately. The association logic engine can receive the detection results from the vision processing unit. That is, all detected detection results (such as category labels, confidence scores, and bounding box coordinates) are used to establish logical relationships between attribute information, thereby determining the parking space attribute information.

[0057] For example, after a vehicle's camera captures an image of a parking area, it first identifies whether there is a rectangular area (parking space marker) enclosed by white lines in the image. If detected, it further checks whether there are any exclusive markings such as "private parking space" or license plate numbers within the rectangular area. If no exclusive markings are detected, it continues to check whether there are any reserved markings in the surrounding area. For example, in a shopping mall parking lot, the camera first determines that there is a parking space, then identifies that there are no "private parking space" markings on the space, further confirms that there are no reserved markings in the surrounding area, and finally determines that the parking space is a public parking space.

[0058] In step S12, a vehicle parking prompt is executed based on the parking space attribute information.

[0059] Among them, the vehicle parking prompt can be a prompt message issued to the driver based on the analysis results of parking space attribute information, indicating whether parking is permitted.

[0060] In one possible implementation, the vehicle can be configured with a state database, such as a non-volatile storage unit, which can be deployed locally in the vehicle's infotainment system or synchronized with a cloud server via an in-vehicle communication module (T-BOX). This database stores the geographical location information (such as GPS coordinates combined with local map data) and parking space attribute information (such as associated license plate numbers) of historically identified fixed parking spaces. This allows the vehicle to retrieve information more quickly when subsequently visiting the same parking lot, effectively enabling a memory function.

[0061] Once a parking space is confirmed as a reserved space, its geographical location, coordinates on the parking lot's partial map, and associated license plate number can be stored in a status database. When a vehicle re-enters the same parking lot, this data can be pre-loaded. This way, even if the parking space is obstructed by other objects or in poor lighting conditions, the system can provide accurate guidance to the driver based on memory, improving system stability and user experience.

[0062] Parking prompts can be displayed on the in-vehicle infotainment system screen and digital instrument panel via a human-machine interaction controller, using graphic overlays, text prompts, and sound alarms to intuitively convey parking space attribute information to the driver.

[0063] The aforementioned technical solution, by acquiring images of the parking area and sequentially detecting parking space attribute information, can accurately determine whether a parking space is available for parking. This effectively avoids disputes, fines, and vehicle towing caused by drivers mistakenly occupying private, reserved, or special-operation parking spaces. It also provides clear and concise parking guidance to drivers, improving parking efficiency and safety. In this way, by utilizing image recognition and intelligent algorithms, intelligent assistance in determining and prompting parking space attributes is achieved, reducing errors and uncertainties in manual judgment, lowering parking risks, and providing drivers with a more convenient and reassuring parking experience.

[0064] See also some possible implementation methods. Figure 2 As shown, in step S11, acquiring the image of the parking area collected by the vehicle and determining the parking space attribute information includes: In step S111, an image of the parking area collected by the vehicle is acquired, and the multiple attribute information is detected.

[0065] In this embodiment, after acquiring an image of a parking area, the vehicle image acquisition device detects multiple attribute information. If the detection result of a certain attribute information does not match a preset target result, subsequent detection is stopped, and it is determined that invalid calculations are unnecessary. For example, if the preceding attribute information is a parking space, the subsequent attribute information, a parking lock, is only detected if the detection result indicates that a parking space exists. If the detection result indicates that no parking space exists, the detection of the parking lock is stopped. Similarly, if a parking lock is the preceding attribute information, the subsequent attribute information, a unique identifier, is only detected if the detection result indicates that a parking lock exists. If the detection result indicates that no parking lock exists, the detection of the unique identifier is stopped.

[0066] One possible approach involves using a single, unified deep learning model to simultaneously detect multiple attributes. Compared to running separate detection models for each attribute (e.g., parking space, parking lock, license plate), a single model offers significant advantages in computational efficiency and resource consumption.

[0067] The performance of this model is highly dependent on the quality and diversity of the training dataset. Therefore, a large-scale, diverse parking lot image dataset can be constructed, with precise annotation of multiple attributes in the images, such as parking space, parking lock, and license plate sign. The training dataset can cover various real-world scenarios, including different lighting conditions (daytime, nighttime, indoor garages), weather conditions (sunny, rainy), parking lock types (O-type, K-type, etc.), license plate styles, and different shooting angles and occlusion conditions.

[0068] The network architecture of this model can be based on mature backbone networks (such as ResNet, EfficientNet, etc.) and includes a multi-attribute information detection head suitable for multi-attribute information recognition. The output of the model is the detection result of each attribute information in the image, giving its category label, a confidence score, and its bounding box position in the image coordinate system.

[0069] In another possible approach, multi-attribute information detection can be performed based on computer vision, especially for computationally limited in-vehicle platforms, where a cascaded traditional computer vision processing workflow can be employed. For example, firstly, algorithms detect straight lines in the image, and then, combined with corner detection, identify and segment the boundaries of parking spaces. Next, within the identified parking space area (where parking space is considered a previous attribute, and the detection result indicates the presence of a parking space as a pre-defined target), a lightweight classifier (e.g., a support vector machine trained based on histogram of oriented gradients) is run to detect the presence of parking space locks. Then, in the vicinity of the detected lock (where the lock is considered a previous attribute, and the detection result indicates the presence of a parking lock as a pre-defined target), optical character recognition technology is applied to identify and extract the license plate number. This approach can improve recognition accuracy even in situations with varying lighting, partial occlusion, and complex backgrounds.

[0070] In step S112, the element information at each position in the information tuple is determined based on the detection results of the attribute information.

[0071] Among them, element information is the specific attribute information stored at each location in the information tuple, which is used to reflect the detection results of different attribute information of parking spaces, such as whether it is a private parking space or whether it is reserved.

[0072] In this embodiment of the disclosure, the element information at the corresponding position in the information tuple is determined based on the detected attribute information results, and the detection results are accurately filled into the corresponding position of the tuple.

[0073] In step S113, the parking space attribute information is determined based on the element information at each position in the information tuple. If the element information at any position indicates that the parking space attribute is not a preset target result, the determination of the parking space attribute information using the element information at the next position is stopped.

[0074] In this embodiment of the disclosure, the information tuple can represent each position through a two-dimensional array, and then corresponding element information exists at each position. Then, according to the order of each position in the information tuple, the element information is retrieved sequentially to determine the parking space attribute. If the parking space attribute determined by the element information corresponding to any position is not the preset target result, then the determination result corresponding to that position is used as the parking space attribute information, and the determination of the parking space attribute information through the element information of the next adjacent position is stopped.

[0075] In this embodiment, the parking space attribute information, such as whether it is a public parking space where parking is permitted, is analyzed and determined by combining the element information at each position in the comprehensive information tuple and through preset rules and algorithms. For example, if a complete three-information tuple (space, lock, plate) is formed, the parking space can be determined to be a private parking space since all three attribute information have identified the preset target result; if only a two-information tuple (space, lock) is formed, that is, the license plate cannot be identified in the neighborhood of the parking space, the parking space can be determined to be a "private / reserved parking space (information unknown)". In this way, fault tolerance can be configured, which is suitable for scenarios where only a ground lock is installed but no license plate is set; if only a one-information tuple (space) is formed, that is, no lock is detected inside or near it, the parking space can be determined to be a public parking space.

[0076] The above-mentioned technical solution employs a sequential detection and stopping mechanism, effectively reducing unnecessary calculations, improving detection efficiency, and lowering system resource consumption. By accurately storing attribute information through information tuples, it ensures data orderliness and integrity. This enhances the accuracy and efficiency of analyzing parking space attribute information, enabling rapid and precise determination of parking space attributes, preventing drivers from parking incorrectly, reducing disputes, fines, and the risk of vehicles being towed, and improving parking safety and convenience.

[0077] In some possible implementations, in step S113, determining the parking space attribute information based on the element information at each position in the information tuple includes: If the element information at any position in the information tuple represents a parking space attribute that is not the corresponding preset target result, then the parking space attribute information of the parking space is determined to be a dedicated parking space.

[0078] Among them, a reserved parking space is a parking space that excludes the occupation and use of others, and the right to use it belongs exclusively to a specific individual or organization. These are parking spaces set up to meet the temporary or transient parking needs of other vehicles.

[0079] In this embodiment, the element information at each position in the information tuple can be analyzed and judged. When the detection result of the element information at any position in the information tuple does not match the corresponding preset target result, it indicates that the parking space has special attributes and does not meet the standard conditions for a public parking space, thus determining that this parking space is a private parking space.

[0080] If all elements in the information tuple at each location represent the parking space attribute as the corresponding preset target result, then the parking space attribute information of the parking space is determined to be a public parking space.

[0081] Public parking spaces are those that are not designated to belong to any individual or entity and are either public or shared. The right to use them belongs to the entire group (such as all homeowners in a residential community or all operators in a shopping mall), not to individuals. These spaces are designed to meet temporary or transient parking needs. Any vehicle can park in these spaces as long as they are not occupied by other vehicles.

[0082] In this embodiment of the disclosure, if the detection results of element information at all positions in the information tuple are consistent with the corresponding preset target results, it indicates that the parking space does not have any special restrictions and meets the characteristics of a public parking space. Therefore, the parking space is determined to be a public parking space.

[0083] For example, in a parking lot, the information tuple includes location elements such as "whether there is a private sign" and "whether it is a reserved time slot". If a private sign is detected for the parking space, meaning the detection result for the "whether there is a private sign" location element does not match the preset target result (no private sign), then regardless of the other location element information, the parking space is determined to be a private parking space. If the "whether there is a private sign" detection does not show a private sign, and the "whether it is a reserved time slot" detection also does not show a reserved time slot, meaning all location element information detection results match the preset target result, then the parking space can be determined to be a public parking space.

[0084] The aforementioned technical solution, through precise comparison of information tuple elements with preset target results, can quickly and accurately distinguish between reserved and public parking spaces. This provides drivers with clear and unambiguous parking guidance, avoiding disputes, fines, or vehicle towing caused by mistakenly parking in reserved spaces, effectively improving parking safety and compliance. Furthermore, it can be widely applied to various intelligent parking systems, improving the efficiency and intelligence of parking management while reducing management costs.

[0085] In some possible implementations, the multi-attribute information includes: parking space boundary lines, parking space locking devices, and parking space-specific identifiers, see [link / reference]. Figure 3 As shown, in step S112, determining the element information at each position in the information tuple based on the detection result of the attribute information includes: In step S1121, if the detection result of the parking space frame line and the detection result of the parking space locking device are both corresponding target detection results, then the positional relationship between the parking space locking device and the parking space frame line is determined.

[0086] Parking space lines are lines used to clearly define the boundaries of parking spaces, such as lines drawn on the ground in white or yellow. Parking space locking devices are installed in parking spaces to prevent other vehicles from occupying them arbitrarily, such as ground locks. Positional relationship refers to the specific position of the parking space locking device relative to the parking space lines, such as whether it is within the parking space lines or in the normal locked position.

[0087] In this embodiment, the parking space frame line, parking space locking device, and parking space-specific markings are first detected. When the detection results of the parking space frame line and the parking space locking device both meet the preset target results, the positional relationship between the parking space locking device and the parking space frame line can be analyzed, such as determining whether the parking lock is within the parking space frame line and in a normal locking state.

[0088] In one possible implementation, for each parking_lock object, the positional relationship between its bounding box and the current parking_space region is calculated. For example, it can be determined whether the center point of the parking lock's bounding box falls inside the polygon of the parking space region. If the parking lock is geometrically determined to be inside the parking space (e.g., the center point is inside, or the intersection-union ratio of the two bounding boxes is greater than a preset threshold), a temporary (space, lock) association pair is formed.

[0089] In step S1122, if the detection results of the parking space frame line and the detection results of the parking space exclusive identifier are both corresponding target detection results, then the attribution relationship between the parking space exclusive identifier and the parking space frame line is determined.

[0090] Among them, exclusive parking space markings are signs used to indicate the exclusive nature of parking spaces, such as the word "private" for private parking spaces, specific numbers or markings for reserved parking spaces, or the license plate numbers of vehicles parked in parking spaces, etc., to distinguish the usage rights of parking spaces.

[0091] In one possible implementation, the parking space is identified by the license plate number of the vehicle parked in the space. For example, if different vehicles with different license plate numbers park in the space throughout the day, it indicates that the space is a public parking space. If only the same vehicle with the same license plate number parks in the space each day, it indicates that the space is a private parking space.

[0092] In this embodiment of the disclosure, if the detection results of both the parking space frame line and the parking space exclusive sign are the preset target results, the attribution relationship between the parking space exclusive sign and the parking space frame line can be determined, such as whether the parking space exclusive sign is the sign corresponding to the detected parking space.

[0093] In one possible implementation, for each newly formed (space, lock) association pair, the existence of a license_plate_sign object can be searched within the spatial neighborhood of the parking_lock object. Proximity can be defined by calculating the Euclidean distance between the center point of the parking lock's bounding box and the center point of the license plate's bounding box. If this distance is less than a preset distance threshold (e.g., a one-pixel distance estimated based on the camera height and physical world size on the vehicle), a match is considered successful, ultimately forming a triple representing a strong association: (space, lock, plate).

[0094] It can be explained that in the relevant scenarios, vehicles, pedestrians, or traffic signs in the image can be identified. However, simple detection is insufficient to complete complex tasks. For example, even if a parking lock and a license plate are detected simultaneously, the inherent relationship between them cannot be understood; the license plate could belong to a passing vehicle or be an advertisement on a wall. In this embodiment of the disclosure, a logical structure of "ownership" or "subordination" is established between the detected discrete objects through specific geometric rules and logical reasoning. This endows a higher-order scene understanding capability, namely, recognizing that "the parking lock belongs to the parking space, and the license plate indicates the ownership of the parking lock."

[0095] In step S1123, the element information of each position in the information tuple is determined according to the positional relationship and attribution relationship.

[0096] In this embodiment of the disclosure, the element information of each position in the information tuple is accurately filled according to the determined positional and attribution relationships to obtain the information tuple. For example, a list including all detected objects and their bounding box information can be represented as: {parking_space_1, parking_space_2,..., parking_lock_1,..., license_plate_sign_1,...}.

[0097] The aforementioned technical solution accurately detects parking space boundaries, locking devices, and unique markings, and meticulously determines their location and ownership relationships to populate information tuples. This effectively avoids misjudgments of parking spaces due to inaccurate information, helping drivers clearly understand parking availability and reducing disputes, fines, and vehicle towing caused by mistakenly parking in designated spaces. Simultaneously, it improves the intelligence level of parking management, enabling more rational use of parking resources, reducing management costs, and enhancing the user experience.

[0098] See also some possible implementation methods. Figure 4 As shown, in step S12, the step of providing a vehicle parking suggestion based on the parking space attribute information includes: In step S121, if the parking space attribute information indicates that the parking space is a dedicated parking space, then a no-parking reminder is executed through a no-parking reminder method.

[0099] Among them, the no-parking reminder can be conveyed to the driver in the form of voice, image, light, etc., such as a voice broadcast "This is a reserved parking space, no parking" or a display screen showing a red warning sign.

[0100] In this embodiment of the disclosure, if the parking space attribute information shows that the parking space is a reserved parking space, a no-parking reminder method can be triggered to make the driver clearly aware that parking is not allowed through various sensory stimulation methods.

[0101] The aforementioned technical solution identifies designated parking spaces and provides targeted prompts and warnings, effectively preventing disputes, fines, and vehicle towing caused by drivers mistakenly parking in designated spaces, thus protecting the rights of parking space owners. Simultaneously, it provides drivers with clear and concise parking guidance, improving parking efficiency and safety.

[0102] In some possible implementations, if the parking space attribute information indicates that the parking space is a reserved parking space, then a no-parking warning is issued via a no-parking warning method, including: If the parking space attribute information indicates that the parking space is a dedicated parking space with a unique identifier, then a no-parking reminder is displayed through the no-parking reminder method, and / or the unique identifier is displayed at the target location corresponding to the parking space.

[0103] In one possible implementation, detected parking spaces can be overlaid in real-time on the parking assistance view (such as a 360-degree surround view) of the in-vehicle infotainment system. For example, different colored borders can be used to identify parking spaces with different attributes: green represents public parking spaces, red represents private parking spaces that do not match the vehicle's license plate, and blue represents a private parking space for the vehicle (e.g., a detected license plate that matches the vehicle's license plate). Simultaneously, the identified license plate number can be displayed next to the red or blue border.

[0104] The above-mentioned technical solution identifies parking spaces as exclusive parking spaces with special markings and can display "No Parking" and the special markings to remind drivers, effectively avoiding disputes, fines, and vehicle towing caused by drivers mistakenly parking in exclusive parking spaces, thus protecting the rights and interests of parking space owners.

[0105] See also: [The text continues with more details about possible implementation methods.] Figure 4 As shown, the method further includes: In step S122, if the driving intention of the vehicle is to park in the designated parking space, a parking warning reminder is issued through a target warning method.

[0106] In one possible implementation, when a driver's intention (e.g., the vehicle begins to turn or approach) is detected as an attempt to enter a parking space marked in red (reserved by another vehicle), an audible alert can be immediately triggered, such as an announcement: "Warning: This is a reserved parking space, belonging to vehicle [license plate number]." This proactive warning can effectively prevent accidental parking.

[0107] In this embodiment of the disclosure, when the driver's intention to park in the designated parking space is detected, a target warning method can be triggered to provide a stronger warning to the driver to park in the designated parking space, thereby improving the effectiveness of the reminder to the user and reducing the risk of the user parking the vehicle in the designated parking space.

[0108] See also: [The text continues with more details about possible implementation methods.] Figure 4 As shown, in step S12, the step of providing a vehicle parking suggestion based on the parking space attribute information includes: In step S123, if the parking space attribute information indicates that the parking space is a public parking space, then a parking permission prompt is executed through a parking permission prompt method.

[0109] In one possible implementation, if a parking space is identified as a private space, it is determined to be a reserved space. The in-car voice system can announce, "This is a reserved parking space, parking is prohibited," while a red cross appears on the central control display. If the driver attempts to drive into this space, the vehicle's sensors detect the intention and can sound an alarm, simultaneously sending a warning message to the driver's phone, "You are attempting to park in a reserved space, please stop," and controlling the central control screen to flash a reminder. If another parking space is detected without special markings, it is determined to be a public parking space. The voice system can announce, "This is a public parking space, parking is permitted," and a green checkmark appears on the display, guiding the driver to park safely.

[0110] When the above technical solution identifies a parking space as a public parking space, it can issue a parking permission prompt, thereby improving the convenience of finding a public parking space to park a vehicle.

[0111] In some possible implementations, the method further includes: If the vehicle's autonomous valet parking function is active, then autonomous valet parking will be performed based on the parking space attribute information.

[0112] In this embodiment of the disclosure, the autonomous valet parking function can be activated by the autonomous valet parking system under user operation. For example, the user can activate the autonomous valet parking function by touching the user interaction page on the central control screen, or by operating a dedicated button set on the vehicle.

[0113] In this embodiment of the disclosure, the path planning result is converted into specific commands for steering, acceleration, and braking based on the parking space attribute information. After the autonomous valet parking system is activated, the drive actuators (electric power steering system, electronic braking system, and electronic throttle system) are driven to complete the parking action.

[0114] The above technical solution improves the adaptability and safety of autonomous valet parking by dynamically sensing parking space attribute information and coordinating with the autonomous valet parking function.

[0115] In some possible implementations, the step of performing autonomous valet parking based on the parking space attribute information includes: The parking space attribute information is used to identify the parking space as a public parking space, and it is then determined as the target valet parking space.

[0116] In this embodiment of the disclosure, a parking space identified by the vehicle in the past as a public parking space can be determined as a target valet parking space. Alternatively, parking spaces identified by other vehicles in the past as public parking spaces can also be determined as target valet parking spaces. Therefore, there can be one or more target valet parking spaces.

[0117] Based on the target valet parking space and the location of the vehicle, plan the valet parking route.

[0118] The target valet parking space is simply a parking space attribute that indicates it is a public parking space, not necessarily an empty parking space. Therefore, based on the vehicle's current location and one or more target valet parking spaces, a valet parking route can be planned, allowing the vehicle to detect whether the target valet parking space is available while cruising along the route.

[0119] In this embodiment of the disclosure, the driving path planning is based on the vehicle's current position, the coordinates of the target valet parking space, and the parking lot environment (channel width, curve radius, obstacle distribution) to generate a collision-free optimal trajectory from the starting point to the end point, including control parameters such as steering angle, vehicle speed, and acceleration.

[0120] Based on the valet parking route, the vehicle cruises to detect the target parking space, and when it reaches the target parking space, it controls the vehicle to park in the target parking space.

[0121] In this embodiment of the present disclosure, when the vehicle is cruising along the valet parking route, it uses sensors to detect in real time whether the target valet parking space is vacant (whether it is occupied or if obstacles have moved) and its own position deviation (lateral / longitudinal error with respect to the path). Then, when the cruise detects a target parking space that is vacant, the autonomous valet parking system controls the vehicle to park in the target parking space.

[0122] For example, if a driver activates the autonomous valet parking function at the drop-off area of ​​a parking lot entrance, the vehicle can then take over driving in response to the activation and begin autonomously searching for a parking space within the parking lot. During the journey, it continuously acquires images of parking spaces, scanning and classifying the attributes of all potential parking spaces along the way. The objective function of the autonomous valet parking function's parking decision algorithm is modified accordingly, and its search space is strictly limited to all parking spaces historically identified as public by the vehicle or other vehicles. This allows the vehicle to choose routes with more public parking spaces when executing the valet parking route. Therefore, the planning module receives not just a simple map containing only "occupied / vacant" information, but a map with rich semantic information such as "public / fixed / private." If the vehicle detects an available parking space based on the autonomously planned route, it can valet park there. This not only ensures parking in the nearest, compliant, and available public parking space but also eliminates the risk of the autonomous driving system illegally parking.

[0123] In this embodiment of the disclosure, one or more vehicle-mounted cameras can be used to collect image data of the parking area around the vehicle. The collected image data is then processed to simultaneously detect multi-attribute information, such as parking space markings, parking space locks, and license plate numbers on signs adjacent to the locks. A spatial association algorithm is then executed to establish logical relationships between one or more detected objects, specifically establishing a strong association between a detected parking space, a parking space lock located within that space, and a license plate number physically adjacent to that lock.

[0124] Furthermore, based on the association relationship, the attributes of the parking space are classified and judged: a parking space identified as containing a parking space lock, and that lock is associated with a specific license plate number, is detected as a public parking space or a private parking space. The detection result is then presented to the driver through the in-vehicle human-machine interface, providing clear parking guidance information and warnings to prevent the driver from mistakenly parking in someone else's private parking space.

[0125] Thus, as shown in Table 1, compared to related scenarios, this method eliminates the need for expensive sensors, additional cameras, or V2X communication hardware installed in parking lots, making it suitable for any type of parking lot, whether outdoor or underground. It also fully utilizes existing hardware such as surround-view cameras commonly found in vehicles. Deployment to a large vehicle fleet can be achieved quickly with minimal marginal cost through software updates. Furthermore, by providing advance warnings and clear guidance, it effectively avoids inconvenience and losses such as fines and disputes that drivers may face due to mistakenly parking in their designated spaces, thus improving the overall parking experience. Simultaneously, combined with autonomous valet parking functionality, the system can make intelligent and compliant parking decisions.

[0126]

[0127] Table 1 The above technical solution combines dynamic screening of public parking spaces with the vehicle's autonomous valet parking function. Based on accurate parking space identification, it can reduce the need for users to make secondary adjustments and improve the robustness and user experience of autonomous valet parking.

[0128] This disclosure also provides a vehicle control device, see [link to relevant documentation] Figure 5 As shown, it includes: a determination module 510 and a prompt module 520.

[0129] The acquisition and determination module 510 is configured to acquire an image of the parking area collected by the vehicle and determine the parking space attribute information. The parking space attribute information is obtained by detecting multiple attribute information from the image and determining the parking space attribute in sequence through the multiple attribute information. The prompting module 520 is configured to perform a vehicle parking prompt based on the parking space attribute information.

[0130] In some possible implementations, the acquisition and determination module 510 is configured to: acquire an image of the parking area collected by the vehicle; detect the plurality of attribute information, wherein if the detection result of any attribute information is not a corresponding preset target result, stop the detection of the next attribute information; determine the element information of each position in the information tuple based on the detection result of the attribute information; and determine the parking space attribute information of the parking space based on the element information of each position in the information tuple.

[0131] In some possible implementations, the acquisition and determination module 510 is configured to: determine that the parking space attribute information of the parking space is a private parking space if the element information of any position in the information tuple indicates that the parking space attribute is not the corresponding preset target result; or, determine that the parking space attribute information of the parking space is a public parking space if the element information of all positions in the information tuple indicates that the parking space attribute is the corresponding preset target result.

[0132] In some possible implementations, the acquisition and determination module 510 is configured to: if the detection result of the parking space frame line and the detection result of the parking space locking device are both corresponding target detection results, then determine the positional relationship between the parking space locking device and the parking space frame line; if the detection result of the parking space frame line and the detection result of the parking space exclusive identifier are both corresponding target detection results, then determine the attribution relationship between the parking space exclusive identifier and the parking space frame line; and determine the element information at each position in the information tuple based on the positional relationship and the attribution relationship.

[0133] In some possible implementations, the prompting module 520 is configured to: if the parking space attribute information indicates that the parking space is a private parking space, then execute a no-parking prompt by means of a no-parking prompt.

[0134] In some possible implementations, the prompting module 520 is configured to: if the parking space attribute information indicates that the parking space is a dedicated parking space with a dedicated identifier, then display a no-parking prompt through the no-parking prompt method, and / or display the dedicated identifier at the target location corresponding to the parking space.

[0135] In some possible implementations, the prompting module 520 is configured to: if the driving intention of the vehicle is to park in the designated parking space, then execute a parking warning reminder through a target warning method.

[0136] In some possible implementations, the prompting module 520 is configured as follows: If the parking space attribute information indicates that the parking space is a public parking space, then a parking permission prompt will be executed through a parking permission prompt.

[0137] In some possible implementations, the device further includes a parking module configured to perform autonomous valet parking based on the parking space attribute information if the vehicle's autonomous valet parking function is active.

[0138] In some possible implementations, the parking module is configured to: identify the parking space attribute information as a public parking space and determine it as a target valet parking space; plan a valet parking route based on the target valet parking space and the vehicle's location; cruise to detect the target parking space based on the valet parking route, and control the vehicle to park in the target parking space when the cruise reaches the target parking space.

[0139] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0140] This disclosure also provides a vehicle, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the executable instructions stored in the memory to implement any of the methods described in the foregoing embodiments.

[0141] This disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described in the foregoing embodiments.

[0142] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in any of the foregoing embodiments.

[0143] Figure 6 This is a block diagram illustrating a vehicle 600 according to an exemplary embodiment. For example, vehicle 600 can be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicle. Vehicle 600 can be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0144] Reference Figure 6 The vehicle 600 may include various subsystems, such as an infotainment system 610, a perception system 620, a decision control system 630, a drive system 640, and a computing platform 650. The vehicle 600 may also include more or fewer subsystems, and each subsystem may include multiple components. Furthermore, each subsystem and each component of the vehicle 600 can be interconnected via wired or wireless means.

[0145] In some embodiments, the infotainment system 610 may include a communication system, an entertainment system, and a navigation system, etc.

[0146] The perception system 620 may include several sensors for sensing information about the environment surrounding the vehicle 600. For example, the perception system 620 may include a global positioning system (which may be GPS, BeiDou, or other positioning systems), an inertial measurement unit (IMU), lidar, millimeter-wave radar, ultrasonic radar, and a camera device.

[0147] The decision control system 630 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0148] The drive system 640 may include components that provide powered motion to the vehicle 600. In one embodiment, the drive system 640 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of internal combustion engines, electric motors, and compressed air engines. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0149] Some or all of the functions of vehicle 600 are controlled by computing platform 650. Computing platform 650 may include at least one processor 651 and memory 652, processor 651 can execute instructions 653 stored in memory 652.

[0150] Processor 651 can be any conventional processor, such as a commercially available CPU. Processors may also include graphics processing units (GPUs), field-programmable gate arrays (FPGAs), systems-on-chips (SoCs), application-specific integrated circuits (ASICs), or combinations thereof.

[0151] The memory 652 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 storage, flash memory, magnetic disk or optical disk.

[0152] In addition to instruction 653, memory 652 can also store data, such as road maps, route information, vehicle position, direction, speed, and other data. The data stored in memory 652 can be used by computing platform 650.

[0153] In this embodiment of the disclosure, processor 651 may execute instructions 653 to complete all or part of the steps of the vehicle control method described above.

[0154] This disclosure also provides a chip system, the chip system comprising: The processing unit and the interface circuit are provided. The processing unit obtains program instructions through the interface circuit. The program instructions are executed by the processing unit. The processing unit is used to perform the steps of the vehicle control method as described in any of the foregoing embodiments.

[0155] Some embodiments of this disclosure also provide a chip system, such as Figure 7 As shown, the chip system includes at least one processor 701 and at least one interface circuit 702. The processor 701 and the interface circuit 702 are interconnected via wiring. For example, the interface circuit 702 can be used to receive signals from other devices (e.g., the vehicle's memory). As another example, the interface circuit 702 can be used to send signals to other devices (e.g., the processor 701). Exemplarily, the interface circuit 702 can read instructions stored in memory and send those instructions to the processor 701. When the instructions are executed by the processor 701, the vehicle control device can perform the steps in the above embodiments. Of course, the chip system may also include other discrete devices, and some embodiments of this disclosure do not specifically limit this.

[0156] In some embodiments of this disclosure, the interface circuit 702 can acquire data, program instructions, and / or information from the internal storage area of ​​the chip system; it can also acquire data, program instructions, and / or information from outside the chip system.

[0157] Optionally, the chip system also includes a memory 703, which is used to store necessary computer programs and data.

[0158] Those skilled in the art will also understand that the various illustrative logical blocks and steps listed in the embodiments of this application can be implemented by electronic hardware, computer software, or a combination of both. Whether such functionality is implemented through hardware or software depends on the specific application and the overall system design requirements. Those skilled in the art can implement the described functionality using various methods for each specific application, but such implementation should not be construed as exceeding the scope of protection of the embodiments of this application.

[0159] Similarly, although this disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. This disclosure includes all such modifications and variations and is limited only by the scope of the claims. In particular, with respect to the various functions performed by the components described above (e.g., elements, resources, etc.), unless otherwise indicated, the terminology used to describe such components is intended to correspond to any component (functionally equivalent) that performs the specific function of the described component, even if structurally not equivalent to the disclosed structure. Furthermore, although specific features of this disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations, as may be desired and advantageous to any given or particular application. Moreover, with regard to the terms “comprising,” “owning,” “having,” “having,” or variations thereof as used in the detailed description or claims, such terms are intended to be inclusive in a manner similar to the term “including.”

[0160] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

[0161] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

[0162] Unless otherwise specifically indicated, features of various embodiments of this disclosure described herein may be combined with each other. As used herein, the term “and / or” includes any one of the relevant listed items and any combination of any two or more; similarly, “at least one of…” includes any one of the relevant listed items and any combination of any two or more.

Claims

1. A vehicle control method, characterized in that, include: The system acquires images of the parking area captured by the vehicle, determines the parking space attribute information, which is obtained by detecting multiple attribute information from the image and determining the parking space attribute in sequence through the multiple attribute information; Based on the parking space attribute information, a vehicle parking prompt is executed.

2. The method according to claim 1, characterized in that, The step of acquiring images of the parking area collected by the vehicle and determining the parking space attribute information includes: Acquire images of the parking area captured by the vehicle and detect the multiple attribute information; Based on the detection results of the attribute information, determine the element information at each position in the information tuple; Based on the element information at each position in the information tuple, the parking space attribute information of the parking space is determined. If the element information at any position indicates that the parking space attribute is not a preset target result, then the determination of the parking space attribute information by using the element information at the next position is stopped.

3. The method according to claim 2, characterized in that, Determining the parking space attribute information based on the element information at each position in the information tuple includes: If the element information at any position in the information tuple represents a parking space attribute that is not the corresponding preset target result, then the parking space attribute information is determined to be a dedicated parking space; or... If all elements in the information tuple at each location represent the parking space attribute as the corresponding preset target result, then the parking space attribute information of the parking space is determined to be a public parking space.

4. The method according to claim 2, characterized in that, The multiple attribute information includes: parking space frame lines, parking space locking devices, and parking space-specific identifiers. The step of determining the element information at each position in the information tuple based on the detection results of the attribute information includes: If the detection results of the parking space frame line and the detection results of the parking space locking device are both corresponding target detection results, then the positional relationship between the parking space locking device and the parking space frame line is determined. If the detection results of the parking space frame line and the parking space exclusive sign are both corresponding target detection results, then the attribution relationship between the parking space exclusive sign and the parking space frame line is determined. Based on the positional and attribution relationships, determine the element information at each position in the information tuple.

5. The method according to claim 1, characterized in that, The step of providing vehicle parking guidance based on the parking space attribute information includes: If the parking space attribute information indicates that the parking space is a reserved parking space, then a no-parking reminder will be issued.

6. The method according to claim 5, characterized in that, If the parking space attribute information indicates that the parking space is a reserved parking space, then a no-parking reminder will be issued through a no-parking reminder method, including: If the parking space attribute information indicates that the parking space is a dedicated parking space with a unique identifier, then a no-parking reminder is displayed through the no-parking reminder method, and / or the unique identifier is displayed at the target location corresponding to the parking space.

7. The method according to claim 5, characterized in that, The method further includes: If the driver's intention is to park in the designated parking space, a parking warning reminder will be issued via a target warning method.

8. The method according to claim 1, characterized in that, The step of providing vehicle parking guidance based on the parking space attribute information includes: If the parking space attribute information indicates that the parking space is a public parking space, then a parking permission prompt will be executed through a parking permission prompt.

9. The method according to any one of claims 1-8, characterized in that, The method further includes: If the vehicle's autonomous valet parking function is active, then autonomous valet parking will be performed based on the parking space attribute information.

10. The method according to claim 9, characterized in that, The step of performing autonomous valet parking based on the parking space attribute information includes: The parking space attribute information is used to identify the parking space as a public parking space, and it is then determined as the target valet parking space. Based on the target valet parking space and the location of the vehicle, plan the valet parking route; Based on the valet parking route, the vehicle cruises to detect the target parking space, and when it reaches the target parking space, it controls the vehicle to park in the target parking space.

11. A vehicle control device, characterized in that, include: The acquisition and determination module is configured to acquire an image of the parking area collected by the vehicle, determine the parking space attribute information, wherein the parking space attribute information is obtained by detecting multiple attribute information from the image and determining the parking space attribute in sequence through the multiple attribute information; The prompt module is configured to provide vehicle parking prompts based on the parking space attribute information.

12. The apparatus according to claim 11, characterized in that, The acquisition and determination module is configured as follows: Acquire images of the parking area captured by the vehicle and detect the multiple attribute information; Based on the detection results of the attribute information, determine the element information at each position in the information tuple; Based on the element information at each position in the information tuple, the parking space attribute information of the parking space is determined. If the element information at any position indicates that the parking space attribute is not a preset target result, then the determination of the parking space attribute information by using the element information at the next position is stopped.

13. The apparatus according to claim 11, characterized in that, The prompting module is configured as follows: If the parking space attribute information indicates that the parking space is a reserved parking space, then a no-parking reminder will be issued.

14. The apparatus according to claim 11, characterized in that, The prompting module is configured as follows: If the parking space attribute information indicates that the parking space is a public parking space, then a parking permission prompt will be executed through a parking permission prompt.

15. The apparatus according to any one of claims 11-14, characterized in that, The device also includes a parking module, configured as follows: If the vehicle's autonomous valet parking function is active, then autonomous valet parking will be performed based on the parking space attribute information.

16. A vehicle, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to execute the executable instructions stored in the memory to implement the method of any one of claims 1-10.

17. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program performs the steps of the method described in any one of claims 1-10.

18. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1-10.

19. A chip system, characterized in that, The chip system includes: The processing unit and the interface circuit are provided. The processing unit obtains program instructions through the interface circuit, and the program instructions are executed by the processing unit. The processing unit is used to perform the steps of the method as described in any one of claims 1-10.

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