Parking area recommendation method, device, server, storage medium and program product

Abstract

The disclosed embodiments relate to a parking area recommendation method, device, server, storage medium and program product. The method comprises: obtaining a parking area recommendation request sent by a target device in a target vehicle; determining a target parking area from multiple parking areas according to the parking area recommendation request; the multiple parking areas are determined in advance by clustering and aggregating the parking positions of multiple vehicles during driving; feeding back indication information of the target parking area to the target device so that the target device can display the indication information; the indication information includes at least one of the center point and boundary line of the target parking area. The use of this method can improve the recommendation effect of parking areas.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of data analysis, and in particular, to a parking area recommendation method, device, server, storage medium, and program product. Background Art

[0002] With the development of the Internet and positioning technology, navigation software is becoming more and more important in people's lives. Common functions of navigation software include route planning and parking area search, where parking area search includes parking area search during driving and parking area search at the destination.

[0003] In the related art, the parking areas recommended by navigation software are mainly obtained through manual outdoor collection and image recognition. However, the efficiency of manual outdoor collection is low, and it is not easy to obtain a sufficient number of parking areas; image recognition technology has problems with recognition accuracy, and it is easy to have inaccurate parking areas. Therefore, it may be difficult for navigation software to recommend parking areas, or the recommended parking areas may be inaccurate, resulting in poor recommendation effect. Summary of the invention

[0004] The embodiments of the present disclosure provide a parking area recommendation method, device, server, storage medium and program product, which can improve the recommendation effect of parking areas.

[0005] In a first aspect, an embodiment of the present disclosure provides a parking area recommendation method, the method comprising:

[0006] Obtaining a parking area recommendation request sent by a target device; the target device is located in a target vehicle;

[0007] Determining a target parking area from a plurality of parking areas according to the parking area recommendation request; the plurality of parking areas are determined in advance by clustering and aggregating parking positions of a plurality of vehicles during driving;

[0008] The indication information of the target parking area is fed back to the target device so that the target device displays the indication information; the indication information includes at least one of a center point and a boundary line of the target parking area.

[0009] In a second aspect, an embodiment of the present disclosure provides a parking area recommendation device, the device comprising:

[0010] A request acquisition module, used to acquire a parking area recommendation request sent by a target device; the target device is located in a target vehicle;

[0011] A first area determination module is used to determine a target parking area from a plurality of parking areas according to the parking area recommendation request; the plurality of parking areas are determined in advance by clustering and aggregating parking positions of a plurality of vehicles during driving;

[0012] The information feedback module is used to feed back the indication information of the target parking area to the target device so that the target device can display the indication information; the indication information includes at least one of the center point and the boundary line of the target parking area.

[0013] In a third aspect, an embodiment of the present disclosure provides a server, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the computer program.

[0014] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in the first aspect above.

[0015] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, including a computer program, which implements the method described in the first aspect when executed by a processor.

[0016] The parking area recommendation method, device, server, storage medium and program product provided in the embodiments of the present disclosure obtain a parking area recommendation request sent by a target device; determine a target parking area from multiple parking areas according to the parking area recommendation request; and feed back indication information of the target parking area to the target device so that the target device can display the indication information. In the embodiments of the present disclosure, the multiple parking areas are determined by the server in advance according to the parking positions of multiple vehicles during driving by clustering and aggregating them, that is, the server can automatically mine the parking areas. Therefore, not only a large number of parking areas can be obtained, the problem of low efficiency of manual outdoor collection can be solved, and the acquisition efficiency of parking areas can be improved; but also the problem of low accuracy of image recognition can be solved, and the recognition accuracy of parking areas can be improved. In this way, a large number of accurate parking areas can be recommended, thereby improving the recommendation effect of parking areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A diagram showing an application environment of a parking area recommendation method in an embodiment;

[0018] Figure 2 A schematic diagram of a flow chart of a parking area recommendation method in one embodiment;

[0019] Figure 3 A schematic diagram of a process of feeding back a target parking area to a target vehicle in one embodiment;

[0020] Figure 4 A schematic diagram of a flow chart of a step of determining a target parking area in one embodiment;

[0021] Figure 5 A schematic diagram of a process of updating the boundary of a target parking area in one embodiment;

[0022] Figure 6 A schematic diagram of a flow chart of adjusting the confidence level of a target parking area in one embodiment;

[0023] Figure 7 This is one of the structural block diagrams of a parking area recommendation device in one embodiment;

[0024] Figure 8 This is a second structural block diagram of a parking area recommendation device in an embodiment;

[0025] Fig. 9 This is a third structural block diagram of a parking area recommendation device in one embodiment;

[0026] Fig.10 This is a fourth structural block diagram of a parking area recommendation device in one embodiment;

[0027] Fig.11 FIG. 4 is a diagram showing the internal structure of a server in one embodiment. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure more clear, the embodiments of the present disclosure are further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present disclosure and are not used to limit the embodiments of the present disclosure.

[0029] First of all, before specifically introducing the technical solution of the embodiment of the present disclosure, the technical background or technical evolution context on which the embodiment of the present disclosure is based is introduced. With the development of the Internet and positioning technology, people often use navigation software to find parking areas on the way and parking areas at the destination. The parking areas provided by the navigation software are mainly obtained by manual outdoor collection and image recognition. However, the efficiency of manual outdoor collection is low, and it is not easy to obtain a sufficient number of parking areas; image recognition technology has problems with recognition accuracy, and it is easy to have inaccurate parking areas. Therefore, it may be difficult for the navigation software to recommend parking areas, or the recommended parking areas may be inaccurate, and the recommendation effect is poor.

[0030] In response to the above problems, the embodiments of the present disclosure provide a parking area recommendation scheme, wherein the server obtains a parking area recommendation request sent by a target device in a target vehicle; determines a target parking area from multiple parking areas according to the parking area recommendation request; and feeds back indication information of the target parking area to the target device so that the target device can display the indication information. Since the multiple parking areas are determined by the server in advance according to the parking positions of multiple vehicles during driving by clustering and aggregating them, the technical scheme provided by the embodiments of the present disclosure can not only automatically mine out parking areas, obtain a large number of parking areas, and improve the efficiency of obtaining parking areas; but also, by mining parking areas through clustering and aggregating them, the recognition accuracy of parking areas can also be improved, so that a large number of accurate parking areas can be recommended, thereby improving the recommendation effect of parking areas. In addition, it should be noted that the applicants have made a lot of creative efforts in the above technical concepts and the technical schemes described in the following embodiments.

[0031] The technical solutions involved in the embodiments of the present disclosure are introduced below in combination with the scenarios to which the embodiments of the present disclosure are applied.

[0032] The parking area recommendation method provided by the embodiment of the present disclosure can be applied to Figure 1 In the application environment shown. The application environment includes an electronic device 102 and a server 104, wherein the electronic device is located in a vehicle, and the electronic device 102 communicates with the server 104 through a network, so that the server 104 can obtain the parking position of the vehicle during driving, that is, obtain the parking point. The electronic device 102 can be, but is not limited to, various smart phones, tablet computers, portable wearable devices, and vehicle-mounted devices, and the server 104 can be implemented as an independent server or a server cluster composed of multiple servers.

[0033] In one embodiment, Figure 2 As shown, a parking area recommendation method is provided, which is applied to Figure 1 The server in the example is used to illustrate the following steps:

[0034] Step 201: Obtain a parking area recommendation request sent by a target device.

[0035] Wherein, the target device is located in the target vehicle. It can be understood that the position of the target device can be used to represent the position of the target vehicle.

[0036] When the user needs to find a parking area, the target device can send a parking area recommendation request to the server. Alternatively, when the user uses the target device for navigation, the target device automatically sends a parking area recommendation request to the server according to the location of the target vehicle. The disclosed embodiment does not limit the triggering conditions of the parking area recommendation request.

[0037] After the target device sends the parking area recommendation request, the server receives the parking area recommendation request.

[0038] Step 202: determining a target parking area from a plurality of parking areas according to a parking area recommendation request.

[0039] The plurality of parking areas are determined by clustering and aggregating the parking positions of the plurality of vehicles in the driving process in advance by the server. It can be understood that the server has excavated the plurality of parking areas in advance according to the parking positions of the plurality of vehicles in the driving process.

[0040] After receiving the parking area recommendation request, the server may determine the location of the target vehicle according to the parking area recommendation request, thereby determining the target parking area from multiple parking areas according to the location of the target vehicle. The server may also determine the destination of the target vehicle according to the parking area recommendation request, thereby determining the target parking area from multiple parking areas according to the destination of the target vehicle. The embodiments of the present disclosure are not limited to this.

[0041] Step 203: Feedback the indication information of the target parking area to the target device, so that the target device displays the indication information.

[0042] The indication information includes at least one of a center point and a boundary line of the target parking area, and the center point of the target parking area can be determined according to the boundary line of the target parking area.

[0043] After determining the target parking area, the server generates indication information according to the target parking area, and feeds back the indication information of the target parking area to the target device. After receiving the indication information of the target parking area, the target device displays the indication information.

[0044] For example, the server feeds back the center point and boundary line of the target parking area to the target device, and the target device displays the center point and boundary line of the target parking area, thereby recommending the target parking area to the target user.

[0045] In the above parking area recommendation method, the server obtains a parking area recommendation request sent by a target device in a target vehicle; determines a target parking area from multiple parking areas according to the parking area recommendation request; and feeds back indication information of the target parking area to the target device so that the target device can display the indication information. Since multiple parking areas are determined by the server in advance according to the parking positions of multiple vehicles during driving by clustering and aggregating, the disclosed embodiment can not only automatically mine out parking areas, obtain a large number of parking areas, and improve the efficiency of obtaining parking areas; and mining parking areas by clustering and aggregating can also improve the recognition accuracy of parking areas, so that a large number of accurate parking areas can be recommended, thereby improving the recommendation effect of parking areas.

[0046] In one example, if Figure 3 As shown, before determining the target parking area from the plurality of parking areas according to the parking area recommendation request, the embodiment of the present disclosure may further include:

[0047] Step 301, obtaining a set of parking spots.

[0048] The parking point set includes multiple parking points, and a parking point is a parking position of a vehicle during driving.

[0049] The server may first obtain the driving trajectories of multiple vehicles, and then determine the parking position of each vehicle during the driving process according to the driving trajectories of each vehicle; thereafter, the server aggregates the multiple parking positions of the multiple vehicles to obtain a parking point set.

[0050] In practical applications, the server obtains the driving trajectories of multiple vehicles by communicating with electronic devices on the vehicles. For example, the server obtains the driving trajectories by communicating with the onboard devices on the vehicles; or the server obtains the driving trajectories by communicating with the smart phones placed on the vehicles. The disclosed embodiments do not limit the method for obtaining the driving trajectories.

[0051] Before the server obtains the driving trajectory, it needs to obtain the user's authorization. For example, the server asks the user whether to allow the driving trajectory to be obtained. If the user allows the driving trajectory to be obtained, the server obtains the driving trajectory from the electronic device on the vehicle. In this way, the user's personal privacy can be protected.

[0052] Step 302: clustering the parking points in the parking point set according to the position of each parking point in the parking point set to obtain a plurality of parking point clusters.

[0053] After obtaining the parking point set, the server may cluster the parking points in the parking point set in a variety of ways, thereby obtaining a plurality of parking point clusters.

[0054] For example, the server may cluster the parking points in the parking point set using a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm based on the location of each parking point; the server may also cluster the parking points in the parking point set using a k-means algorithm based on the location of each parking point. The disclosed embodiment does not limit the clustering method, and it may be selected according to actual conditions.

[0055] Step 303: Aggregate the multiple parking point clusters based on the distances between the parking point clusters to obtain multiple aggregated parking point clusters.

[0056] Each aggregated parking point cluster includes at least one parking point cluster.

[0057] After the server determines the multiple parking point clusters, it can aggregate the multiple parking point clusters according to the distances between the multiple parking point clusters. For example, multiple parking point clusters with close distances can be aggregated into one aggregated parking point cluster.

[0058] Step 304 : determining a plurality of parking areas based on the aggregated parking point clusters.

[0059] After obtaining the plurality of aggregated parking point clusters, the server may determine a corresponding parking area for each aggregated parking point cluster according to the aggregated parking point cluster, that is, each parking point in the aggregated parking point cluster is within the parking area.

[0060] In one example, after determining multiple parking areas, the parking areas can be stored in a preset parking area database. The preset parking area database may include a mining parking area database, a collection parking area database, and an identification parking area database; the mining parking area database is used to store the multiple parking areas determined based on the above-mentioned aggregated parking point clusters, the collection parking area database is used to store parking areas collected artificially outdoors; and the identification parking area database is used to store parking areas identified by images. The disclosed embodiment does not limit the parking area database, and it can be set according to actual conditions.

[0061] In the above embodiment, the server first obtains a parking point set; then, according to the position of each parking point in the parking point set, the parking points in the parking point set are clustered to obtain multiple parking point clusters; then, based on the distance between each parking point cluster, the multiple parking point clusters are aggregated to obtain multiple aggregated parking point clusters; finally, multiple parking areas are determined based on the aggregated parking point clusters. The disclosed embodiment can not only obtain a large number of parking areas by automatically mining parking areas, solve the problem of low efficiency of manual outdoor collection, and improve the acquisition efficiency of parking areas; but also solve the problem of low accuracy of image recognition, and improve the recognition accuracy of parking areas, so that a large number of accurate parking areas can be recommended, thereby improving the recommendation effect of parking areas.

[0062] In one embodiment, the process of aggregating multiple parking point clusters based on the distances between the parking point clusters to obtain multiple aggregated parking point clusters may include: aggregating parking point clusters whose distances among the multiple parking point clusters are less than a preset distance threshold into one aggregated parking point cluster.

[0063] The server calculates the distance between each two parking point clusters in the multiple parking point clusters. If the distance is less than a preset distance threshold, it indicates that the distance between the two parking point clusters is relatively close, and the two parking point clusters can be regarded as one cluster. Similarly, multiple parking point clusters that can be regarded as one cluster are aggregated together to obtain an aggregated parking point cluster.

[0064] In one embodiment, the distance between two parking point clusters can be calculated in a variety of ways. For example, the distance between the two parking point clusters can be calculated based on the center points of the two parking point clusters; or the distance between the two parking point clusters can be calculated based on the parking points that are farthest from each other in the two parking point clusters. The distance calculation method in the embodiment of the present disclosure is not limited and can be set according to actual conditions.

[0065] In the above embodiment, the parking point clusters whose distances are less than the preset distance threshold in the multiple parking point clusters are aggregated into an aggregated parking point cluster. The disclosed embodiment obtains an aggregated parking point cluster by aggregating the parking point clusters, and can more accurately determine the parking area based on the aggregated parking point clusters, thereby improving the recognition accuracy of the parking area.

[0066] In one embodiment, Figure 4 As shown, based on the above embodiment, the embodiment of the present disclosure may further include the following steps:

[0067] Step 401, obtaining the confidence level of each parking area.

[0068] The confidence level is used to indicate the probability that the parking area is a real parking area where the vehicle can park. If the confidence level of the parking area is high, it indicates that the parking area is likely to be a real parking area; if the confidence level of the parking area is low, it indicates that the parking area is likely to be a real parking area. When the confidence level of the parking area is lower than the preset confidence threshold, the parking area will no longer be recommended to the user.

[0069] The server may obtain the confidence of each parking area from a preset parking area database. The confidence of each parking area may be a default value, or an updated value after the server updates the confidence according to the recommendation and usage of each parking area. This disclosure embodiment does not limit this.

[0070] Step 402 : determining the position of a target vehicle according to the parking area recommendation request, and determining a target parking area from a plurality of parking areas according to the position of the target vehicle and the confidence of each parking area.

[0071] The server receives the parking area recommendation request and obtains the position of the target vehicle through the target device; then, the server determines the target parking area from the multiple parking areas according to the position of the target vehicle and the confidence of the parking area.

[0072] In one of the embodiments, the process of determining the target parking area from the plurality of parking areas may include: determining a plurality of candidate parking areas within a preset range around the target vehicle from the plurality of parking areas according to the position of the target vehicle; and determining the target parking area from the plurality of candidate parking areas according to the confidence level of each candidate parking area.

[0073] For example, after receiving the parking area recommendation request, the server obtains the location of the target vehicle according to the parking area recommendation request; then, it searches for multiple candidate parking areas within a preset range around the target vehicle from multiple parking areas, and sorts the multiple candidate parking areas in order from high to low confidence, and then determines the first sorted candidate parking area as the target parking area.

[0074] In one of the embodiments, the process of determining the target parking area from the plurality of parking areas may include: determining a driving path of the target vehicle according to the position of the target vehicle and the destination of the target vehicle, and determining a plurality of candidate parking areas located around the driving path from the plurality of parking areas; and determining the target parking area from the plurality of candidate parking areas according to the confidence level of each candidate parking area.

[0075] For example, after receiving the parking area recommendation request, the server can obtain the location of the target vehicle and the destination of the target vehicle according to the parking area recommendation request; determine the driving path of the target vehicle according to the location of the target vehicle and the destination of the target vehicle; search for multiple candidate parking areas around the driving path from multiple parking areas; and determine the candidate parking area with the highest confidence as the target parking area. The multiple candidate parking areas around the driving path include the parking area at the destination of the target vehicle.

[0076] It can be understood that the method of determining the target parking area is not limited to the examples listed above in the embodiments of the present disclosure, and other determination methods may also be used.

[0077] In the above embodiment, the confidence of each parking area is obtained; the position of the target vehicle is determined according to the parking area recommendation request, and the target parking area is determined from multiple parking areas according to the position of the target vehicle and the confidence of each parking area. The disclosed embodiment recommends the target parking area to the user based on the confidence of the parking area, which can improve the recommendation accuracy and recommendation effect, thereby improving the user experience and increasing the user stickiness of the product.

[0078] In one embodiment, Figure 5 As shown, based on the above embodiment, the embodiment of the present disclosure may further include the following steps:

[0079] Step 501, obtaining the actual parking position of the target vehicle through the target device.

[0080] After feeding back the indication information of the target parking area to the target device, the server obtains the driving trajectory of the target vehicle through the target device, thereby determining the actual parking position of the target vehicle.

[0081] Step 502: If the actual parking position is outside the target parking area, the actual parking position is used as a new boundary point of the target parking area.

[0082] After obtaining the actual parking position of the target vehicle, the server determines whether the actual parking position of the target vehicle is outside the target parking area. If the actual parking position of the target vehicle is outside the target parking area, it indicates that the target parking area is not accurate, and the actual parking position of the target vehicle is used as a new boundary point of the target parking area. If the actual parking position of the target vehicle is within the target parking area, it indicates that the target parking area is relatively accurate.

[0083] Step 503: updating the boundary of the target parking area based on the newly added boundary points.

[0084] According to the above steps, the server can obtain a large number of newly added boundary points. After that, the server updates the boundary of the target parking area according to the newly added boundary points. For example, the original boundary line of the target parking area is translated or reshaped according to the newly added boundary points.

[0085] In one embodiment, the process of updating the boundary of the target parking area based on the newly added boundary points may include: generating a fitting boundary line based on the newly added boundary points; and replacing the original boundary line of the target parking area based on the fitting boundary line.

[0086] In practical applications, other methods may be used to update the boundary of the target parking area, which is not limited in the embodiments of the present disclosure.

[0087] It can be understood that after the boundary of the target parking area is updated, the center point of the target parking area is also updated accordingly.

[0088] In the above embodiment, the actual parking position of the target vehicle is obtained; if the actual parking position is outside the target parking area, the actual parking position is used as a new boundary point of the target parking area; and the boundary of the target parking area is updated based on the new boundary point. The disclosed embodiment can make the target parking area more accurate by updating the boundary of the target parking area, and then recommend a more accurate parking area to the user, which can improve the user experience.

[0089] In one embodiment, Figure 6 As shown, based on the above embodiment, the embodiment of the present disclosure may further include the following steps:

[0090] Step 601: Obtain a recommendation response for a target parking area through a target device.

[0091] The recommendation response includes accepting the recommendation and rejecting the recommendation.

[0092] After the server feeds back the indication information of the target parking area to the target device, the target device displays the target parking area according to the indication information, that is, recommends the target parking area to the user in the target vehicle.

[0093] In one implementation, the target device may display a pop-up window asking whether to accept the recommendation while displaying the target parking area. If an operation of accepting the recommendation is detected based on the pop-up window, a recommendation response for accepting the recommendation is sent to the server. If an operation of rejecting the recommendation is detected based on the pop-up window, a recommendation response for rejecting the recommendation is sent to the server. Correspondingly, the server receives the recommendation response.

[0094] In one implementation, after the target device displays the target parking area, the server obtains the actual parking position of the target vehicle and determines whether the actual parking position of the target vehicle is within a preset range around the target parking area. If the server determines that the actual parking position of the target vehicle is within the preset range around the target parking area, it indicates that the user has accepted the recommendation and parked the target vehicle around the recommended target parking area, and the server obtains a recommendation response for accepting the recommendation. If the server determines that the actual parking position of the target vehicle is not within the preset range around the target parking area, it indicates that the user has not accepted the recommendation and parked the target vehicle at a location far away from the target parking area, and the server obtains a recommendation response for rejecting the recommendation.

[0095] In practical applications, recommendation responses may also be obtained through other methods, which are not limited in the embodiments of the present disclosure.

[0096] Step 602: Update the confidence level of the target parking area according to the recommendation response.

[0097] If the recommendation response obtained by the server is to accept the recommendation, indicating that the probability that the target parking area is a real parking area is high, the confidence of the target parking area can be increased. If the recommendation response obtained by the server is to reject the recommendation, indicating that the probability that the target parking area is a real parking area is low, the confidence of the target parking area can be reduced. When the confidence of the target parking area is lower than the preset confidence threshold, the target parking area is adjusted to an unreasonable parking area, and the target parking area is no longer recommended to the user.

[0098] In one embodiment, the confidence level of the target parking area is updated by using a reinforcement learning model. The disclosed embodiment does not limit the structure of the reinforcement learning model, and it can be set according to actual conditions.

[0099] In the above embodiment, the target device obtains the recommendation response for the target parking area; and the confidence of the target parking area is updated according to the recommendation response. In the embodiment of the present disclosure, the confidence of the target parking area is adjusted according to the user's recommendation response to the target parking area, so that the parking area can be recommended to the user according to the confidence of each parking area in the future, thereby improving the recommendation effect and further improving the user experience.

[0100] It should be understood that although Figures 2 to 6 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figures 2 to 6At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0101] In one embodiment, Figure 7 As shown, a parking area recommendation device is provided, comprising:

[0102] The request acquisition module 701 is used to acquire a parking area recommendation request sent by a target device; the target device is located in a target vehicle;

[0103] A first area determination module 702 is used to determine a target parking area from a plurality of parking areas according to a parking area recommendation request; the plurality of parking areas are determined in advance by clustering and aggregating parking positions of a plurality of vehicles during driving;

[0104] The information feedback module 703 is used to feed back the indication information of the target parking area to the target device so that the target device can display the indication information; the indication information includes at least one of the center point and the boundary line of the target parking area.

[0105] In one embodiment, if Figure 8 As shown, the device also includes:

[0106] A set acquisition module 704 is used to acquire a parking point set; the parking point set includes multiple parking points, and a parking point is a parking position of a vehicle during driving;

[0107] A clustering module 705 is used to cluster the parking points in the parking point set according to the positions of the parking points in the parking point set to obtain a plurality of parking point clusters;

[0108] Aggregation module 706, configured to aggregate the plurality of parking point clusters based on the distances between the parking point clusters to obtain a plurality of aggregated parking point clusters, each of which includes at least one parking point cluster;

[0109] The second area determination module 707 is used to determine multiple parking areas based on the aggregated parking point clusters.

[0110] In one embodiment, the aggregation module 705 is specifically configured to aggregate parking point clusters whose distances among multiple parking point clusters are less than a preset distance threshold into one aggregated parking point cluster.

[0111] In one embodiment, the first area determination module 702 is specifically used to obtain the confidence of each parking area, where the confidence is used to indicate the probability that the parking area is a real parking area where the vehicle can park; determine the position of the target vehicle according to the parking area recommendation request, determine the target parking area from multiple parking areas according to the position of the target vehicle and the confidence of each parking area, and feed back the indication information of the target parking area to the target vehicle.

[0112] In one embodiment, the first area determination module 702 is specifically used to determine a plurality of candidate parking areas within a preset range around the target vehicle from a plurality of parking areas according to the position of the target vehicle; and determine a target parking area from the plurality of candidate parking areas according to the confidence level of each candidate parking area.

[0113] In one embodiment, if Fig. 9 As shown, the device also includes:

[0114] A response acquisition module 708 is used to acquire a recommendation response for a target parking area through a target device; the recommendation response includes accepting the recommendation and rejecting the recommendation;

[0115] The confidence updating module 709 is used to update the confidence of the target parking area according to the recommendation response.

[0116] In one embodiment, if Fig.10 As shown, the device also includes:

[0117] A position acquisition module 710 is used to acquire the actual parking position of the target vehicle through the target device;

[0118] A boundary point determination module 711 is used to use the actual parking position as a new boundary point of the target parking area if the actual parking position is outside the target parking area;

[0119] The boundary updating module 712 is used to update the boundary of the target parking area based on the newly added boundary points.

[0120] In one embodiment, the boundary updating module 712 is specifically configured to generate a fitted boundary line based on the newly added boundary points; and replace the original boundary line of the target parking area based on the fitted boundary line.

[0121] The specific definition of the parking area recommendation device can be found in the definition of the parking area recommendation method above, which will not be repeated here. Each module in the above parking area recommendation device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of a processor in an electronic device in the form of hardware, or can be stored in a memory in an electronic device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0122] Fig.11 FIG. 1 is a block diagram of a server 1400 according to an exemplary embodiment. Fig.11 The server 1400 includes a processing component 1420, which further includes one or more processors, and a memory resource represented by a memory 1422 for storing instructions or computer programs, such as applications, that can be executed by the processing component 1420. The application stored in the memory 1422 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1420 is configured to execute the instructions to perform the above-mentioned parking area determination method.

[0123] The server 1400 may also include a power supply component 1424 configured to perform power management of the device 1400, a wired or wireless network interface 1426 configured to connect the device 1400 to a network, and an input / output (I / O) interface 1428. The server 1400 may operate based on an operating system stored in the memory 1422, such as Windows 14 14erverTM, Mac O14 XTM, UnixTM, LinuxTM, FreeB14DTM or the like.

[0124] In an exemplary embodiment, a storage medium including instructions is also provided, such as a memory 1422 including instructions, which can be executed by a processor of the server 1400 to perform the above method. The storage medium can be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0125] In an exemplary embodiment, a computer program product is also provided, and when the computer program is executed by a processor, the above method can be implemented. The computer program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, part or all of the above method can be implemented in whole or in part according to the process or function described in the embodiment of the present disclosure.

[0126] It should be noted that the user information (including but not limited to user device information, user personal information, user location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0127] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the embodiments of the present 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 memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0128] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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.

[0129] The above-described embodiments only express several implementation methods of the embodiments of the present disclosure, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the embodiments of the present disclosure, and these all belong to the protection scope of the embodiments of the present disclosure. Therefore, the protection scope of the patent of the embodiments of the present disclosure shall be subject to the attached claims.

Claims

1. A parking area recommendation method, characterized in that: The method comprises: Obtaining a parking area recommendation request sent by a target device; the target device is located in a target vehicle; Determining a target parking area from a plurality of parking areas according to the parking area recommendation request; the plurality of parking areas are determined in advance by clustering and aggregating parking positions of a plurality of vehicles during driving; Feeding back the indication information of the target parking area to the target device so that the target device displays the indication information; the indication information includes at least one of a center point and a boundary line of the target parking area; Wherein, determining a target parking area from a plurality of parking areas according to the parking area recommendation request comprises: Acquire the confidence of each parking area according to a preset parking area database, the recommendation and usage of each parking area, wherein the confidence is used to indicate the probability that the parking area is a real parking area where a vehicle can park; The position of the target vehicle is determined according to the parking area recommendation request, and the target parking area is determined from the plurality of parking areas according to the position of the target vehicle and the confidence level of each of the parking areas.

2. The method according to claim 1, characterized in that Before determining a target parking area from a plurality of parking areas according to the parking area recommendation request, the method further includes: Acquire a parking point set; the parking point set includes a plurality of parking points, and the parking points are parking positions of the vehicle during driving; According to the position of each parking point in the parking point set, clustering processing is performed on the parking points in the parking point set to obtain a plurality of parking point clusters; Based on the distances between the parking point clusters, the plurality of parking point clusters are aggregated to obtain a plurality of aggregated parking point clusters, each of the aggregated parking point clusters including at least one of the parking point clusters; The plurality of parking areas are determined based on the aggregated parking spot clusters.

3. The method according to claim 2, characterized in that The step of aggregating the plurality of parking point clusters based on the distances between the parking point clusters to obtain a plurality of aggregated parking point clusters includes: The parking point clusters whose distances among the plurality of parking point clusters are less than a preset distance threshold are aggregated into an aggregated parking point cluster.

4. The method according to claim 1, characterized in that: The step of determining the target parking area from the plurality of parking areas according to the position of the target vehicle and the confidence level of each parking area comprises: Determining a plurality of candidate parking areas located within a preset range around the target vehicle from the plurality of parking areas according to the position of the target vehicle; The target parking area is determined from the plurality of candidate parking areas according to the confidence level of each of the candidate parking areas.

5. The method according to claim 1, characterized in that After feeding back the indication information of the target parking area to the target device, the method further includes: Acquiring a recommendation response for the target parking area through the target device; the recommendation response includes accepting the recommendation and rejecting the recommendation; The confidence level of the target parking area is updated according to the recommendation response.

6. The method according to claim 1, characterized in that After feeding back the indication information of the target parking area to the target device, the method further includes: Acquiring the actual parking position of the target vehicle through the target device; If the actual parking position is outside the target parking area, the actual parking position is used as a new boundary point of the target parking area; The boundary of the target parking area is updated based on the newly added boundary point.

7. The method according to claim 6, characterized in that The updating process of the boundary of the target parking area based on the newly added boundary point includes: Generate a fitting boundary line based on the newly added boundary points; An original boundary line of the target parking area is replaced based on the fitted boundary line.

8. A parking area recommendation device, characterized in that: The device comprises: A request acquisition module, used to acquire a parking area recommendation request sent by a target device; the target device is located in a target vehicle; A first area determination module is used to determine a target parking area from a plurality of parking areas according to the parking area recommendation request; the plurality of parking areas are determined in advance by clustering and aggregating parking positions of a plurality of vehicles during driving; An information feedback module, used for feeding back the indication information of the target parking area to the target device, so that the target device displays the indication information; the indication information includes at least one of the center point and the boundary line of the target parking area; Among them, the first area determination module is specifically used to obtain the confidence of each parking area according to a preset parking area database, the recommendation and usage of each parking area, and the confidence is used to indicate the probability that the parking area is a real parking area available for vehicle parking; determine the position of the target vehicle according to the parking area recommendation request, and determine the target parking area from the multiple parking areas according to the position of the target vehicle and the confidence of each parking area.

9. A server 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, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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