Parking space recommendation method and device, electronic equipment, storage medium and program product

Abstract

Embodiments of the present disclosure relate to a parking space recommendation method and device, electronic equipment, a storage medium and a program product. The method comprises: determining a plurality of initial parking spaces within a preset range around a target vehicle; determining a parking path of the target vehicle for each of the initial parking spaces; determining a difficulty coefficient of the target vehicle for each of the initial parking spaces according to at least one of obstacle information on both sides of each of the initial parking spaces and path information of each of the parking paths; and determining a recommended target parking space according to the difficulty coefficient of each of the initial parking spaces. The recommended target parking space is determined according to the difficulty coefficient of the target vehicle for each of the initial parking spaces, and the difficulty of the target vehicle for each of the initial parking spaces is considered, thereby avoiding the problem that the target vehicle is difficult to park in the determined target parking space, and making the recommended target parking space a better parking space.

Description

Technical Field

[0001] This disclosure relates to the field of autonomous driving technology, and in particular to a parking space recommendation method, apparatus, electronic device, storage medium, and program product. Background Technology

[0002] With the development of autonomous driving technology, automatic parking technology has also developed rapidly. As a result, existing vehicles already have the function of recommending parking spaces.

[0003] In traditional technology, after finding a parking space, an automatic parking system directly recommends the nearest space to the user. However, this traditional method may have the problem of recommending spaces that are difficult to navigate. Summary of the Invention

[0004] This disclosure provides a parking space recommendation method, apparatus, electronic device, storage medium, and program product, which can be used to solve the problem that traditional parking space recommendation methods have the problem of difficulty in recommending parking spaces.

[0005] In a first aspect, embodiments of this disclosure provide a parking space recommendation method, the method comprising:

[0006] Determine multiple initial parking spaces within a preset range around the target vehicle;

[0007] Determine the parking path for the target vehicle to park in each of the initial parking spaces;

[0008] Based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path, determine the difficulty coefficient of the target vehicle parking in each initial parking space.

[0009] Based on the difficulty coefficient of each initial parking space, a recommended target parking space is determined.

[0010] Secondly, embodiments of this disclosure provide a parking space recommendation device, the device comprising:

[0011] The first determining module is used to determine multiple initial parking spaces within a preset range around the target vehicle;

[0012] The second determining module is used to determine the parking path of the target vehicle into each of the initial parking spaces;

[0013] The third determining module is used to determine the difficulty coefficient of the target vehicle parking in each of the initial parking spaces based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path.

[0014] The recommendation module is used to determine the target parking space based on the difficulty coefficient of each initial parking space.

[0015] Thirdly, embodiments of this disclosure provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect above.

[0016] Fourthly, embodiments of this disclosure provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect above.

[0017] Fifthly, embodiments of this disclosure provide a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0018] The parking space recommendation method, apparatus, electronic device, storage medium, and program product provided in this disclosure determine multiple initial parking spaces within a preset range around a target vehicle and determine the parking path for the target vehicle to park in each initial parking space. Based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path, the difficulty coefficient of the target vehicle parking in each initial parking space can be determined. Therefore, a recommended target parking space can be determined based on the difficulty coefficient of the target vehicle parking in each initial parking space. Since the recommended target parking space is determined based on the difficulty coefficient of the target vehicle parking in each initial parking space, the difficulty of the target vehicle parking in each initial parking space is taken into account, thereby avoiding the problem of the target vehicle having difficulty parking in the determined target parking space, making the recommended target parking space a superior parking space. Attached Figure Description

[0019] Figure 1 This is a diagram illustrating the application environment of a parking space recommendation method in one embodiment.

[0020] Figure 2 This is a flowchart illustrating a parking space recommendation method in one embodiment;

[0021] Figure 3 This is a flowchart illustrating the parking space recommendation method in another embodiment;

[0022] Figure 4 This is a structural block diagram of a parking space recommendation device in one embodiment;

[0023] Figure 5 This is a diagram of the internal structure of an electronic device in one embodiment. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the embodiments of this disclosure will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of this disclosure and are not intended to limit the embodiments of this disclosure.

[0025] First, before introducing the technical solutions of the embodiments of this disclosure, the technical background or evolution of the embodiments of this disclosure will be introduced. Typically, in the field of autonomous driving, the current technical background is that after finding a parking space, the automatic parking system directly recommends the parking space closest to the vehicle to the user, which may result in parking difficulties at the recommended parking space. Based on this background, through long-term model simulation research and development, as well as the collection, demonstration, and verification of experimental data, the applicant has found that if there are obstacles on both sides of the recommended parking space, the recommended parking space is narrow, or the curvature of the parking path to the recommended parking space is large, the recommended parking space will have parking difficulties. Therefore, how to recommend a better parking space during automatic parking has become a pressing problem to be solved. Furthermore, it should be noted that the applicant has devoted considerable creative effort to determining the potential parking difficulties when using the parking space closest to the vehicle as the recommended parking space, and to the technical solutions described in the following embodiments.

[0026] The technical solutions involved in the embodiments of this disclosure will be described below in conjunction with the scenarios in which they are applied.

[0027] The parking space recommendation method provided in this disclosure can be applied to, for example... Figure 1 The application environment is shown. The target vehicle 201 can be various motor vehicles, such as cars, trucks, etc. The target vehicle 201 may include onboard camera equipment and radar equipment. The target vehicle 201 is equipped with a processing component that can communicate with the onboard camera equipment and radar equipment wirelessly or via a wired connection. The parking spaces within a preset range around the target vehicle 201 can be perpendicular, horizontal, or angled, etc. Figure 1 This is just one example of the types of parking spaces within a preset range around the target vehicle 201. This embodiment does not limit the types of parking spaces within a preset range around the target vehicle 201.

[0028] In one embodiment, such as Figure 2 As shown, a parking space recommendation method is provided, which is then applied to... Figure 1 Taking the vehicle in question as an example, the steps include:

[0029] S201, determine multiple initial parking spaces within a preset range around the target vehicle.

[0030] Optionally, the initial parking space can be any one of a perpendicular parking space, a parallel parking space, or an angled parking space. For example, the preset range around the target vehicle can be the area covered by a circle with the target vehicle as the origin and a radius of 10m.

[0031] Optionally, the target vehicle can determine multiple initial parking spaces based on point cloud data within a preset range around it, or it can determine multiple initial parking spaces based on image data within a preset range around it; or, there may be multiple cameras set up in the environment where the target vehicle is located, and these cameras can obtain information on available parking spaces within a preset range around the target vehicle. Therefore, the target vehicle can determine multiple initial parking spaces within a preset range around itself through communication connections with these cameras.

[0032] Optionally, the multiple initial parking spaces determined for the target vehicle can be parking spaces of the same type, for example, all of them can be perpendicular parking spaces; or they can be parking spaces of different types, for example, they can be a combination of perpendicular parking spaces and horizontal parking spaces. It should be noted that the multiple initial parking spaces determined in this embodiment can be parking spaces marked with parking lines or parking spaces without parking lines.

[0033] S202, determine the parking path for the target vehicle to park in each initial parking space.

[0034] Optionally, in this embodiment, the target vehicle can determine its parking path into each initial parking space based on its current location and the locations of each initial parking space using a preset path planning algorithm.

[0035] Optionally, the parking paths determined for the target vehicle can be parking paths with high curvature or parking paths with low curvature; each determined parking path may include multiple path segments or a single path, etc. Optionally, the path information of each determined parking path may include at least one of the following: the number of parking path segments, the curvature value of each path segment, and the path length of the parking path.

[0036] S203, based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path, determine the difficulty coefficient of the target vehicle parking in each initial parking space.

[0037] Optionally, in this embodiment, the target vehicle can determine the difficulty coefficient of parking in each initial parking space based on the obstacle information on both sides of each initial parking space; or, the target vehicle can determine the difficulty coefficient of parking in each initial parking space based on the path information of each parking path; or, the target vehicle can determine the difficulty coefficient of parking in each initial parking space based on the obstacle information on both sides of each initial parking space and the path information of each parking path.

[0038] Optionally, in this embodiment, the target vehicle can determine the obstacle information on both sides of each initial parking space based on the point cloud data collected by its own LiDAR and / or the image data collected by the vehicle-mounted camera. For example, the obstacles on both sides of the initial parking space can be vehicles parked on both sides of the initial parking space, signs on both sides of the initial parking space, or objects placed on both sides of the initial parking space, etc.

[0039] S204 determines the recommended target parking space based on the difficulty coefficient of each initial parking space.

[0040] Optionally, in this embodiment, the target vehicle can sort the difficulty coefficients of each initial parking space, determine the top few initial parking spaces as candidate parking spaces, and then determine the target parking space from the candidate parking spaces. For example, the top five initial parking spaces with the highest difficulty coefficients can be determined as candidate parking spaces, and then the target parking space can be determined from the candidate parking spaces based on factors such as the distance between the candidate parking spaces and the target vehicle.

[0041] In the above parking space recommendation method, by determining multiple initial parking spaces within a preset range around the target vehicle and determining the parking path of the target vehicle into each initial parking space, the difficulty coefficient of the target vehicle parking into each initial parking space can be determined based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path. Thus, a recommended target parking space can be determined based on the difficulty coefficient of the target vehicle parking into each initial parking space. Since the recommended target parking space is determined based on the difficulty coefficient of the target vehicle parking into each initial parking space, the difficulty of the target vehicle parking into each initial parking space is taken into account, thereby avoiding the problem that the target vehicle is too difficult to park into the determined target parking space, making the recommended target parking space a better parking space.

[0042] In the scenario described above, where the difficulty coefficient of parking a target vehicle into each initial parking space is determined based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path, in one embodiment, such as Figure 3 As shown, the above S203 includes:

[0043] S301, for each initial parking space, if it is determined that there are obstacles on both sides of the initial parking space based on the obstacle information on both sides of the initial parking space, and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold, then the difficulty coefficient is determined based on the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space.

[0044] Optionally, in this embodiment, the preset distance threshold is determined based on the width of the target vehicle and the width of the target vehicle's door extending beyond the vehicle's outer contour after opening. For example, if L_V represents the width of the target vehicle and L_door represents the width of the target vehicle's door extending beyond the vehicle's outer contour after opening, then the preset distance threshold can be expressed as L_V + 2 * L_door.

[0045] Optionally, the obstacle information on both sides of the initial parking space may include information on whether there are obstacles on both sides of the initial parking space and the distance between the obstacles on both sides of the initial parking space, etc. In this embodiment, if the target vehicle determines that there are obstacles on both sides of the initial parking space based on the obstacle information on both sides of the initial parking space, and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold, the target vehicle can determine the difficulty coefficient of parking into the initial parking space based on the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space. For example, the target vehicle can sum the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space to determine the difficulty coefficient of parking into the initial parking space.

[0046] S302, if it is determined from the obstacle information on both sides of the initial parking space that there are no obstacles on both sides of the initial parking space or the distance between the obstacles on both sides of the initial parking space is greater than or equal to the distance threshold, then the difficulty coefficient is determined from the path information corresponding to the initial parking space.

[0047] Optionally, in this embodiment, if the target vehicle determines, based on the obstacle information on both sides of the initial parking space, that there are no obstacles on either side of the initial parking space, or if there are obstacles on both sides of the initial parking space but the distance between the obstacles on both sides is greater than or equal to the aforementioned distance threshold, then the target vehicle can determine the difficulty coefficient for parking in the initial parking space based on the path information corresponding to the initial parking space. Optionally, in this embodiment, the target vehicle can determine the difficulty coefficient for parking in the initial parking space as the sum of the path information corresponding to the initial parking space.

[0048] In this embodiment, for each initial parking space, the target vehicle can determine whether there are obstacles on both sides of the initial parking space based on the obstacle information on both sides of the initial parking space, and the relationship between the distance between the obstacles on both sides of the initial parking space and a preset distance threshold when obstacles exist. Thus, when there are obstacles on both sides of the initial parking space and the distance between the obstacles on both sides of the initial parking space is less than the preset distance threshold, the difficulty coefficient of the target vehicle parking into the initial parking space can be determined based on the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space. When there are no obstacles on both sides of the initial parking space or the distance between the obstacles on both sides of the initial parking space is greater than or equal to the distance threshold, the difficulty coefficient of the target vehicle parking into the initial parking space can be determined based on the path information corresponding to the initial parking space. This allows for accurate determination of the difficulty coefficient of the target vehicle parking into the initial parking space based on the different obstacle information on both sides of the initial parking space, improving the accuracy of the determined difficulty coefficient of the target vehicle parking into the initial parking space.

[0049] In the scenario described above, where the difficulty coefficient of parking the target vehicle into the initial parking space is determined based on the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space, in one embodiment, S301 includes: determining the difficulty coefficient based on the weighted sum of the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space.

[0050] Optionally, in this embodiment, if the target vehicle determines that there are obstacles on both sides of the initial parking space, and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold, the target vehicle can determine the difficulty coefficient of parking into the initial parking space based on the path information corresponding to the initial parking space and the weighted sum of the distances between the obstacles on both sides of the initial parking space. For example, in this embodiment, the target vehicle can determine the difficulty coefficient of parking into the initial parking space according to the formula: P = a1*N + a2*L_path + a3*(C1+C2+…+Cn) / n + a4*L_slot, where P represents the difficulty coefficient of parking into the initial parking space, a1, a2, a3, a4 represent the parking difficulty weighting coefficients, N represents the number of segments of the parking path, L_path represents the path length of the parking path, C1, C2,…, Cn represent the curvature values ​​of each segment of the path, n indicates the number of gear shifts during the parking process, and L_slot represents the distance between the obstacles on both sides of the initial parking space.

[0051] In this embodiment, when the target vehicle determines that there are obstacles on both sides of the initial parking space and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold, the target vehicle can quickly determine the difficulty coefficient of parking into the initial parking space based on the path information corresponding to the initial parking space and the weighted sum of the distances between the obstacles on both sides of the initial parking space. This process is relatively simple, thereby improving the efficiency of determining the difficulty coefficient of parking into the initial parking space.

[0052] In the scenario described above, where the difficulty coefficient of a target vehicle parking in the initial parking space is determined based on the path information corresponding to the initial parking space, in one embodiment, S302 includes: determining the difficulty coefficient based on the weighted sum of the path information corresponding to the initial parking space.

[0053] For example, in this embodiment, the target vehicle can determine the difficulty coefficient of parking into the initial parking space according to the following formula: P=a1*N+a2*L_path+a3*(C1+C2+…+Cn) / n, where P represents the difficulty coefficient of parking into the initial parking space, a1,a2,a3 represent the parking difficulty weighting coefficients, N represents the number of segments of the parking path, L_path represents the path length of the parking path, C1,C2,…,Cn represent the curvature values ​​of each segment of the path, n indicates the number of gear shifts during the parking process, and L_slot represents the distance between the obstacles on both sides of the initial parking space.

[0054] In this embodiment, when the target vehicle determines that there are no obstacles on either side of the initial parking space or the distance between the obstacles on either side of the initial parking space is greater than or equal to the distance threshold, the target vehicle can quickly determine the difficulty coefficient of parking into the initial parking space based on the weighted sum of the path information corresponding to the initial parking space, thereby improving the efficiency of determining the difficulty coefficient of parking into the initial parking space.

[0055] In one embodiment, in the scenario where multiple initial parking spaces are determined within a preset range around the target vehicle, S201 includes: determining multiple initial parking spaces within a preset range around the target vehicle based on ultrasonic radar data and / or image data collected by an onboard camera.

[0056] Optionally, in this embodiment, the target vehicle can determine multiple initial parking spaces within a preset range based on ultrasonic radar data collected by its own ultrasonic radar, or it can determine multiple initial parking spaces within a preset range based on image data collected by its own vehicle-mounted camera; alternatively, the target vehicle can also identify areas marked with parking spaces within a preset range based on ultrasonic radar data, and then determine multiple initial parking spaces from the areas marked with parking spaces based on image data collected by the vehicle-mounted camera.

[0057] In this embodiment, the target vehicle can accurately determine multiple initial parking spaces within a preset range around the target vehicle based on ultrasonic radar data and / or image data collected by the vehicle-mounted camera, thereby improving the accuracy of the multiple initial parking spaces determined by the target vehicle.

[0058] In the scenario described above where a target parking space is determined based on the difficulty coefficient of each initial parking space, in one embodiment, S204 includes: determining the initial parking space with the lowest difficulty coefficient as the target parking space.

[0059] In this embodiment, the target vehicle can select the initial parking space with the lowest difficulty coefficient among all initial parking spaces as the recommended target parking space. It should be noted that in this embodiment, if two of the aforementioned initial parking spaces have the same difficulty coefficient and are the lowest difficulty coefficients, the target vehicle can determine the target parking space based on the distance between these two initial parking spaces and the target vehicle. For example, the initial parking space with the shortest distance to the target vehicle among these two initial parking spaces can be selected as the target parking space.

[0060] In this embodiment, the difficulty coefficients of multiple initial parking spaces within a preset range around the target vehicle are determined. This allows the target vehicle to quickly identify the initial parking space with the lowest difficulty coefficient from among the multiple initial parking spaces. The target parking space recommended by the target vehicle is the initial parking space with the lowest difficulty coefficient. In other words, this process improves the efficiency of the target vehicle in identifying the recommended target parking space.

[0061] The following describes an embodiment of this disclosure using a specific travel scenario. The method includes the following steps:

[0062] S1, based on ultrasonic radar data and / or image data collected by vehicle-mounted cameras, determines multiple initial parking spaces within a preset range around the target vehicle.

[0063] S2 determines the parking path for the target vehicle to park in each initial parking space.

[0064] S3. For each initial parking space, if it is determined that there are obstacles on both sides of the initial parking space based on the obstacle information on both sides of the initial parking space, and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold, then the difficulty coefficient is determined based on the weighted sum of the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space; the path information includes at least one of the following: the number of segments of the parking path, the curvature value of each segment of the path, and the path length of the parking path.

[0065] S4. If it is determined from the obstacle information on both sides of the initial parking space that there are no obstacles on both sides of the initial parking space or the distance between the obstacles on both sides of the initial parking space is greater than or equal to the distance threshold, then the difficulty coefficient is determined based on the weighted sum of the path information corresponding to the initial parking space.

[0066] S5 identifies the initial parking space with the lowest difficulty level as the target parking space.

[0067] The working principle of the parking space recommendation method provided in this embodiment is described in detail in the above embodiments, and will not be repeated here.

[0068] It should be understood that, although Figure 2-3 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2-3 At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0069] In one embodiment, such as Figure 4 As shown, a parking space recommendation device is provided, comprising: a first determining module, a second determining module, a third determining module, and a recommendation module, wherein:

[0070] The first determining module is used to determine multiple initial parking spaces within a preset range around the target vehicle;

[0071] The second determining module is used to determine the parking path of the target vehicle into each initial parking space;

[0072] The third determining module is used to determine the difficulty coefficient of the target vehicle parking in each initial parking space based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path.

[0073] The recommendation module is used to determine the target parking space based on the difficulty coefficient of each initial parking space.

[0074] Optionally, the path information includes at least one of the following parameters: the number of segments of the parking path, the curvature value of each segment, and the path length of the parking path.

[0075] The parking space recommendation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0076] Based on the above embodiments, optionally, the third determining module includes: a first determining unit and a second determining unit, wherein:

[0077] The first determining unit is used to determine the difficulty coefficient for each initial parking space if, based on the obstacle information on both sides of the initial parking space, it is determined that there are obstacles on both sides of the initial parking space, and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold.

[0078] The second determining unit is used to determine the difficulty coefficient based on the path information corresponding to the initial parking space if it is determined from the obstacle information on both sides of the initial parking space that there are no obstacles on both sides of the initial parking space or the distance between the obstacles on both sides of the initial parking space is greater than or equal to the distance threshold.

[0079] The parking space recommendation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0080] Based on the above embodiments, optionally, the first determining unit is used to determine the difficulty coefficient based on the parameter values ​​included in the path information corresponding to the initial parking space and the weighted sum of the distances between obstacles on both sides of the initial parking space.

[0081] The parking space recommendation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0082] Based on the above embodiments, optionally, the second determining unit is used to determine the difficulty coefficient based on the weighted sum of parameter values ​​included in the path information corresponding to the initial parking space.

[0083] The parking space recommendation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0084] Based on the above embodiments, optionally, the first determining module includes: a third determining unit, wherein:

[0085] The third determining unit is used to determine multiple initial parking spaces within a preset range around the target vehicle based on ultrasonic radar data and / or image data collected by the vehicle-mounted camera.

[0086] The parking space recommendation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0087] Based on the above embodiments, optionally, the recommendation module includes: a recommendation unit, wherein:

[0088] The recommendation unit is used to identify the initial parking space with the lowest difficulty level as the target parking space.

[0089] The parking space recommendation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0090] Specific limitations regarding the parking space recommendation device can be found in the limitations of the parking space recommendation method described above, and will not be repeated here. Each module in the aforementioned parking space recommendation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the electronic device in hardware form, or stored in the memory of the electronic device in software form, so that the processor can call and execute the corresponding operations of each module.

[0091] Figure 5 This is a block diagram illustrating an electronic device 1300 according to an exemplary embodiment. For example, the electronic device 1300 may be a vehicle-mounted terminal, etc.

[0092] Reference Figure 5 The electronic device 1300 may include one or more of the following components: a processing component 1302, a memory 1304, a power supply component 1306, a multimedia component 1308, an audio component 1310, an input / output (I / O) interface 1312, a sensor component 1314, and a communication component 1316. The memory stores computer programs or instructions that run on the processor.

[0093] Processing component 1302 typically controls the overall operation of electronic device 1300, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 1302 may include one or more processors 1320 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 1302 may include one or more modules to facilitate interaction between processing component 1302 and other components. For example, processing component 1302 may include a multimedia module to facilitate interaction between multimedia component 1308 and processing component 1302.

[0094] Memory 1304 is configured to store various types of data to support the operation of electronic device 1300. Examples of such data include instructions for any application or method operating on electronic device 1300, contact data, phonebook data, messages, pictures, videos, etc. Memory 1304 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.

[0095] Power supply component 1306 provides power to various components of electronic device 1300. Power supply component 1306 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 1300.

[0096] Multimedia component 1308 includes a touch display screen that provides an output interface between the electronic device 1300 and the user. In some embodiments, the touch display screen may include a liquid crystal display (LCD) and a touch panel (TP). The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of a touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 1308 includes a front-facing camera and / or a rear-facing camera. When the electronic device 1300 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0097] Audio component 1310 is configured to output and / or input audio signals. For example, audio component 1310 includes a microphone (MIC) configured to receive external audio signals when electronic device 1300 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 1304 or transmitted via communication component 1316. In some embodiments, audio component 1310 also includes a speaker for outputting audio signals.

[0098] I / O interface 1312 provides an interface between processing component 1302 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0099] Sensor assembly 1314 includes one or more sensors for providing state assessments of various aspects of electronic device 1300. For example, sensor assembly 1314 may detect the on / off state of electronic device 1300, the relative positioning of components such as the display and keypad of electronic device 1300, changes in position of electronic device 1300 or a component of electronic device 1300, the presence or absence of user contact with electronic device 1300, the orientation or acceleration / deceleration of electronic device 1300, and temperature changes of electronic device 1300. Sensor assembly 1314 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 1314 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 1314 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0100] Communication component 1316 is configured to facilitate wired or wireless communication between electronic device 1300 and other devices. Electronic device 1300 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 1316 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 1316 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0101] In an exemplary embodiment, the electronic device 1300 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described parking space recommendation method.

[0102] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 1304 including instructions, which can be executed by a processor 1320 of an electronic device 1300 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0103] In an exemplary embodiment, a computer program product is also provided, which, when executed by a processor, can implement the above-described methods. The computer program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, some or all of the above-described methods can be implemented, wholly or partially, according to the processes or functions described in the embodiments of this disclosure.

[0104] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this disclosure can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0105] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0106] The above-described embodiments are merely illustrative of several implementation methods of the present disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present disclosure embodiments, and these all fall within the protection scope of the present disclosure embodiments. Therefore, the protection scope of the patent for the embodiments of the present disclosure should be determined by the appended claims.

Claims

1. A parking space recommendation method, characterized in that, The method includes: Determine multiple initial parking spaces within a preset range around the target vehicle; Determine the parking path for the target vehicle to park in each of the initial parking spaces; Based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path, determine the difficulty coefficient of the target vehicle parking in each initial parking space. Based on the difficulty coefficient of each initial parking space, a recommended target parking space is determined; the step of determining the difficulty coefficient of the target vehicle parking in each initial parking space based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path includes: For each initial parking space, if it is determined that there are obstacles on both sides of the initial parking space based on the obstacle information on both sides of the initial parking space, and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold, then the difficulty coefficient is determined based on the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space. If it is determined, based on the obstacle information on both sides of the initial parking space, that there are no obstacles on either side of the initial parking space or that the distance between the obstacles on either side of the initial parking space is greater than or equal to the distance threshold, then the difficulty coefficient is determined based on the path information corresponding to the initial parking space.

2. The method according to claim 1, characterized in that, The step of determining the difficulty coefficient based on the path information corresponding to the initial parking space and the distance between obstacles on both sides of the initial parking space includes: The difficulty coefficient is determined by a weighted sum of the path information corresponding to the initial parking space and the distances between the obstacles on both sides of the initial parking space.

3. The method according to claim 1, characterized in that, The step of determining the difficulty coefficient based on the path information corresponding to the initial parking space includes: The difficulty coefficient is determined by the weighted sum of the path information corresponding to the initial parking space.

4. The method according to any one of claims 1 to 3, characterized in that, The path information includes at least one of the following: the number of segments of the parking path, the curvature value of each segment, and the path length of the parking path.

5. The method according to claim 1, characterized in that, The step of determining multiple initial parking spaces within a preset range around the target vehicle includes: Based on ultrasonic radar data and / or image data collected by vehicle-mounted cameras, multiple initial parking spaces are determined within a preset range around the target vehicle.

6. The method according to claim 1, characterized in that, The step of determining the target parking space based on the difficulty coefficient of each initial parking space includes: The initial parking space with the lowest difficulty level is selected as the target parking space.

7. A parking space recommendation device, characterized in that, The device includes: The first determining module is used to determine multiple initial parking spaces within a preset range around the target vehicle; The second determining module is used to determine the parking path of the target vehicle into each of the initial parking spaces; The third determining module is used to determine the difficulty coefficient of the target vehicle parking in each of the initial parking spaces based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path. The determination of the difficulty coefficient of the target vehicle parking in each of the initial parking spaces based on at least one of the obstacle information on both sides of each initial parking space and the path information of each parking path includes: For each initial parking space, if it is determined that there are obstacles on both sides of the initial parking space based on the obstacle information on both sides of the initial parking space, and the distance between the obstacles on both sides of the initial parking space is less than a preset distance threshold, then the difficulty coefficient is determined based on the path information corresponding to the initial parking space and the distance between the obstacles on both sides of the initial parking space. If it is determined based on the obstacle information on both sides of the initial parking space that there are no obstacles on both sides of the initial parking space or that the distance between the obstacles on both sides of the initial parking space is greater than or equal to the distance threshold, then the difficulty coefficient is determined based on the path information corresponding to the initial parking space. The recommendation module is used to determine the target parking space based on the difficulty coefficient of each initial parking space.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements claim 1. The steps of the method described in any one of the 6.

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