Off-line map management method based on user behavior prediction and related equipment

Abstract

The invention discloses an off-line map management method based on user behavior prediction and related equipment, and relates to the technical field of intelligent navigation, and the method comprises the following steps: obtaining user geographic behavior data; determining a user behavior model and a geographic range of a user life circle based on the user geographic behavior data; downloading and storing a target offline map according to the geographical range of the user's life circle; and when it is monitored that the user behavior track changes, updating the user behavior model and the geographic range of the user life circle, and managing the target offline map based on an updating result. According to the method, the area where the user is about to go out is predicted, the off-line map is downloaded in advance, and fine updating is continuously carried out according to the change of the user track, so that the flow consumption is low, and the user can still normally use navigation when going to a new destination in a life circle and in a network-free scene.

Description

Technical Field

[0001] This application relates to the field of intelligent navigation technology, and in particular, to an offline map management method and related devices based on user behavior prediction. Background Art

[0002] At present, the vast majority of in-vehicle navigation software will pre-install or remind users to download the offline map of the local city to make up for the inaccessibility of point of interest (POI) search, route planning, and navigation guidance in closed and weak network environments such as underground parking lots and long tunnels due to network request failures. In the industry, there are methods of downloading and upgrading offline maps in a rough manner according to city levels, and there are also methods of tile-by-tile downloading offline maps in the area around the route planned by the user. However, the problems are as follows: the former consumes a huge amount of traffic, and users need to download the offline maps of multiple cities when migrating to multiple cities; the latter caches the offline maps only according to the user's historical trajectory or the route being planned, and can only be used for the same or similar routes next time, and new routes are unavailable. Moreover, if the user does not initiate a navigation route, such as in the cruise state, it cannot be used.

[0003] Therefore, how to predict the user's travel area, download the offline map in advance and update and manage the offline map has become an urgent technical problem to be solved. Summary of the Invention

[0004] A series of simplified concepts are introduced in the Summary of the Invention section, which will be further described in detail in the Detailed Description section. The Summary of the Invention section of this application does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the protection scope of the claimed technical solution.

[0005] In a first aspect, this application proposes an offline map management method based on user behavior prediction, including:

[0006] Obtain user geographical behavior data;

[0007] Based on the user geographical behavior data, determine the user behavior model and the geographical scope of the user's living circle;

[0008] According to the geographical scope of the user's living circle, download and store the target offline map;

[0009] When it is detected that the user behavior trajectory changes, update the user behavior model and the geographical scope of the user's living circle, and manage the target offline map based on the update result.

[0010] In a feasible implementation manner, in the step of determining the user behavior model and the geographical range of the user's living circle based on the user's geographical behavior data, the step of determining the user behavior model includes:

[0011] Based on the user's geographical behavior data, obtain the parking location data and the stay duration data within a preset time period;

[0012] According to the parking location data and the stay duration data, determine the user's home address and company address;

[0013] Based on the user's geographical behavior data, obtain the access frequency of historical navigation destinations and the types of favorite addresses;

[0014] According to the access frequency of the historical navigation destinations and the types of favorite addresses, extract the user's target frequency access addresses, historical favorite addresses, and points of interest;

[0015] According to the user's home address, company address, target frequency access addresses, historical favorite addresses, and points of interest, determine the user behavior model.

[0016] In a feasible implementation manner, the step of extracting the user's target frequency access addresses includes:

[0017] Screen the destinations in the historical navigation destinations whose access frequency exceeds the preset access frequency threshold, and remove the home address and the company address from the screened destinations to obtain the initial access addresses;

[0018] Extract the target frequency access addresses from the initial access addresses based on the target frequency.

[0019] In a feasible implementation manner, in the step of determining the user behavior model and the geographical range of the user's living circle based on the user's geographical behavior data, the step of determining the geographical range of the user's living circle includes:

[0020] Taking the home address and the company address as the centers, respectively generate buffers with a first preset radius;

[0021] Extract the round-trip routes between the home address, the company address, the target frequency access addresses, and the points of interest, and generate route buffers with a first preset width along the round-trip routes;

[0022] Based on the historical access frequency and the maximum distance of the user going to the points of interest, generate a buffer with a second preset radius centered on the home address;

[0023] Combine the buffer with the first preset radius, the route buffer with the first preset width, and the buffer with the second preset radius, and remove the overlapping areas to determine the geographical scope of the user's living circle.

[0024] In a feasible implementation manner, the downloading and storing the target offline map according to the geographical scope of the user's living circle includes:

[0025] Obtain an offline map according to the geographical scope of the user's living circle;

[0026] Detect the version status of the offline map;

[0027] When it is detected that the version status is updated, download and store the updated offline map as the target offline map based on a preset time interval.

[0028] In a feasible implementation manner, when it is monitored that the user behavior trajectory changes, updating the user behavior model and the geographical scope of the user's living circle, and managing the target offline map based on the update result includes:

[0029] If it is monitored that a navigation destination or a favorite address is added to the user behavior trajectory, update the geographical scope of the user's living circle based on the added navigation destination and the favorite address;

[0030] If it is monitored that the user behavior trajectory exceeds the geographical scope of the current user's living circle, return to the step of obtaining the user's geographical behavior data until the user behavior model is updated;

[0031] Adjust the target map based on the updated geographical scope of the user's living circle and the user behavior model.

[0032] In a feasible implementation manner, the offline map management method based on user behavior prediction further includes:

[0033] In an environment where there is no network connection or the network signal strength is lower than a preset threshold, trigger the target offline map to provide navigation services for the user.

[0034] In a second aspect, the present application provides an offline map management system based on user behavior prediction, which is applied to the offline map management method based on user behavior prediction described in any of the above implementation manners, and includes:

[0035] A data acquisition module, configured to obtain user geographical behavior data;

[0036] A data analysis module, configured to determine a user behavior model and the geographical scope of the user's living circle based on the user geographical behavior data;

[0037] A map download module, configured to download and store a target offline map according to the geographical scope of the user's living circle;

[0038] A map update module, configured to update the user behavior model and the geographical scope of the user's living circle when it is detected that the user's behavior trajectory changes, and manage the target offline map based on the update result.

[0039] In a third aspect, an electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program stored in the memory, the steps of the offline map management method based on user behavior prediction according to any one of the first aspects described above are implemented.

[0040] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the offline map management method based on user behavior prediction according to any one of the first aspects are implemented.

[0041] In summary, the offline map management method based on user behavior prediction proposed in the present application predicts the area where the user is about to travel, downloads the offline map in advance, and continuously updates it in a refined manner according to the change of the user's trajectory. It not only has low traffic consumption, but also allows the user to still use the navigation normally when going to a new destination within their living circle and in a no-network scenario.

[0042] For the offline map management method based on user behavior prediction proposed in the present application, other advantages, objectives, and features of the present application will be partially reflected by the following description, and partially will be understood by those skilled in the art through the research and practice of the present application. Description of the Drawings

[0043] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to limit this specification. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0044] Figure 1 It is a flowchart of an offline map management method based on user behavior prediction provided by an embodiment of the present application;

[0045] Figure 2 It is a schematic diagram of determining the geographical scope of the user's living circle provided by an embodiment of the present application;

[0046] Figure 3 It is a functional module diagram of an offline map management system based on user behavior prediction provided by an embodiment of the present application;

[0047] Figure 4 A schematic structural diagram of an electronic device for offline map management based on user behavior prediction provided by an embodiment of the present application. Specific implementation manners

[0048] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It should be understood that the accompanying drawings in the present application are only for the purposes of illustration and description, and are not used to limit the protection scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in the present application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical context relationships may be reversed or implemented simultaneously. In addition, those skilled in the art may add one or more other operations to the flowchart or remove one or more operations from the flowchart under the guidance of the content of the present application.

[0049] In addition, the described embodiments are only some embodiments of the present application, rather than all embodiments. The components of the embodiments of the present application usually described and illustrated in the accompanying drawings herein may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application claimed, but merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts fall within the protection scope of the present application.

[0050] In this document, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or sequence between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device including a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element. The term "more than two" includes two or more than two.

[0051] Please refer to Figure 1 , a flowchart of a method for offline map management based on user behavior prediction provided by an embodiment of the present application, which specifically may include:

[0052] S110. Obtain user's geographical behavior data.

[0053] Exemplarily, obtain the historical search of the in-vehicle device and mobile phone maps of the user, the destinations of historical navigation, the time of the destinations of historical navigation, the historical favorite addresses, home address, company address, and target frequently visited addresses (such as common addresses) of the in-vehicle device and mobile phone maps, so as to obtain the user's geographical behavior data.

[0054] S120. Based on the user's geographical behavior data, determine the user behavior model and the geographical scope of the user's living circle.

[0055] Exemplarily, obtain the user behavior pattern and the activity area of the user according to the user's geographical behavior data, then model the user behavior pattern to determine the user behavior model, and define the activity area of the user to determine the geographical scope of the user's living circle.

[0056] S130. According to the geographical scope of the user's living circle, download and store the target offline map.

[0057] Exemplarily, downloading the offline map based on the geographical scope of the user's living circle can accurately cover the areas where the user may be active. Ensure that the user can obtain offline map support within their living circle (including multiple activity areas such as home, work, daily travel, and interest activities), without missing important areas, avoiding the situation where the user has no available map in the absence of network, and improving the user's navigation experience. And only download the offline map related to the user's living circle, without downloading too much useless map data, avoiding unnecessary large-area map downloads, effectively reducing traffic consumption, and reasonably utilizing network resources and device storage resources.

[0058] S140. When it is detected that the user's behavior trajectory changes, update the user behavior model and the geographical scope of the user's living circle, and manage the target offline map based on the update result.

[0059] Exemplarily, performing corresponding updates and management when it is detected that the user's behavior trajectory changes can improve the user's personalized service experience, accurately capture the change of demand; optimize resource utilization, avoid waste, and concentrate resources on the areas actually needed; ensure that accurate and complete navigation services can also be provided in the new activity area; and can also adapt to dynamic environmental changes, keep in sync with the user's actual behavior, and meet the navigation needs in different stages and scenarios.

[0060] In some examples, in the step of determining the user behavior model and the geographical scope of the user's living circle based on the user's geographical behavior data, the steps of determining the user behavior model include:

[0061] Based on the user's geographical behavior data, obtain the parking location data and the residence duration data within a preset time period;

[0062] Determine the user's home address and company address based on the parking location data and the stay duration data;

[0063] Based on the user's geographical behavior data, obtain the access frequency of historical navigation destinations and the types of favorite addresses;

[0064] Extract the user's target frequency access addresses, historical favorite addresses, and points of interest according to the access frequency of historical navigation destinations and the types of favorite addresses;

[0065] Determine the user behavior model according to the user's home address, company address, target frequency access addresses, historical favorite addresses, and points of interest.

[0066] Exemplarily, based on the user's geographical behavior data, obtain the parking location data and the stay duration data of the user's in-vehicle driving in the past year. If the user has set the home address and the company address in the mobile map or the in-vehicle map, use them as the commuting addresses between the user's home and company; if the user has not set them, calculate the addresses where the user parks continuously for more than 5 hours every day for a week, and determine the user's home address and company address according to the time period of day and night. Extract the user's target frequency access addresses according to the access frequency of the user's historical navigation destinations in the mobile map or the in-vehicle map (such as the frequently searched addresses). Obtain the historical favorite addresses according to the list of addresses favorited on the user's mobile phone or in-vehicle device. Analyze the user group according to the user's historical navigation destinations, the types of favorite addresses, and the corresponding time on the user's mobile phone or in-vehicle device, and obtain the user's points of interest. For example, for the daily commuting + weekend baby-walking group, the point of interest is the baby-walking park; for the daily commuting + weekend supermarket group, the point of interest is the supermarket; for the weekend self-driving tour group, the point of interest is the self-driving tour scenic area; for the weekend shopping mall group, the point of interest is the shopping mall, etc. Finally, determine the user behavior model according to the user's home address, company address, target frequency access addresses, historical favorite addresses, and points of interest, and construct a user portrait.

[0067] Through multi-dimensional data collection and analysis, the user behavior model can be characterized more accurately. The accurate determination of the home address and the company address, as well as the excavation of the user's frequent locations and points of interest, make the user behavior model closer to the user's real life and travel patterns, providing a more reliable basis for the subsequent offline map management based on this user behavior model, so as to more accurately meet the user's map needs in different scenarios.

[0068] In some examples, extracting the user's target frequency access addresses includes:

[0069] Screen the destinations in the historical navigation destinations whose access frequency exceeds the preset access frequency threshold, and remove the home address and the company address from the screened destinations to obtain the initial access addresses;

[0070] The target frequency access address is extracted from the initial access address based on the target frequency.

[0071] Exemplarily, if the user has set a frequently used address on the mobile map or in-vehicle map, this is used as the user's target frequency access address; if the user has not set it, the addresses searched more than 5 times on the in-vehicle or mobile map are calculated, and the top two addresses with the highest search frequencies (excluding the home address and company address) are taken as the target frequency access address. By setting the access frequency threshold and excluding specific addresses, irrelevant or low-frequency locations can be effectively filtered out, and the locations that the user actually visits frequently can be accurately extracted as the target frequency access address. This helps to further refine the user behavior model, making the understanding of the user's travel preferences more accurate. Furthermore, in offline map management, the map areas related to these high-frequency locations can be more targeted for downloading and management, improving resource utilization efficiency.

[0072] In some examples, in the process of determining the user behavior model and the geographical scope of the user's living circle based on the user's geographical behavior data, the steps of determining the geographical scope of the user's living circle include:

[0073] Taking the home address and the company address as the centers, buffer zones with a first preset radius are generated respectively;

[0074] The round-trip routes between the home address, the company address, the target frequency access address, and the points of interest are extracted, and a route buffer zone with a first preset width is generated along the round-trip routes;

[0075] Based on the historical access frequency and the maximum distance of the user going to the points of interest, a buffer zone with a second preset radius centered on the home address is generated;

[0076] Combining the buffer zone with the first preset radius, the route buffer zone with the first preset width, and the buffer zone with the second preset radius, and removing the overlapping areas to determine the geographical scope of the user's living circle.

[0077] Exemplarily, as Figure 2 shown, taking the home address and the company address as the centers, buffer zones with a first preset radius (area ①) are generated respectively: here the first preset radius is set to 10 km. For example, if the longitude and latitude of the user's home address are (longitude A, latitude A), and the longitude and latitude of the company address are (longitude B, latitude B), then a circle is drawn with the home address as the center and a radius of 10 km. This circular area is the buffer zone with the first preset radius centered on the home address; similarly, a corresponding buffer zone is generated with the company address as the center and a radius of 10 km. These two buffer zones cover the areas where the user is more likely to be active around the home and the company, such as daily shopping and leisure activities in the vicinity.

[0078] Extract the round-trip routes between the home address, company address, target frequency access address, and points of interest, and generate a route buffer with a first preset width (area ②) along the round-trip routes: Assume the first preset width is set to 2 km. For example, there is a fixed round-trip route for a user from home to a frequently visited supermarket (one of the target frequency access addresses). Expand the area 2 km to each side along this route to form a strip-shaped route buffer. For the round-trip route from the company to a point of interest (such as a park frequently visited on weekends), also expand 2 km to each side along it to generate a buffer. These route buffers consider the possible activity ranges of users during their daily commutes and on the way to frequently visited locations and points of interest.

[0079] Generate a buffer with a second preset radius (area ③) centered on the home address based on the historical access frequency and maximum distance of the user's trips to points of interest: After analyzing the historical data of the user's trips to points of interest (such as a self-driving tour scenic spot, which is the point of interest farthest from home and has been visited more than 3 times), it is found that the radius of this point of interest from home is 50 km. At this time, the second preset radius is 50 km. Generate a buffer with a radius of 50 km centered on the home address, incorporating the relatively far areas that the user may reach due to interest activities into the scope of the living circle.

[0080] Finally, combine the above-generated buffer with a first preset radius (10 km), the route buffer with a first preset width (2 km), and the buffer with a second preset radius (50 km), and remove the overlapping areas to determine the geographical scope of the user's living circle. The user's living circle determined in this way comprehensively covers the activity areas of the user in multiple aspects such as home, work, daily travel, and interest activities, providing an accurate scope basis for subsequent accurate downloading of offline maps.

[0081] In some examples, download and store the target offline map according to the geographical scope of the user's living circle, including:

[0082] Obtain the offline map according to the geographical scope of the user's living circle;

[0083] Detect the version status of the offline map;

[0084] When it is detected that the version status is updated, download and store the updated offline map as the target offline map based on a preset time interval.

[0085] Exemplarily, first, obtain the offline map according to the geographical scope of the user's living circle, which ensures that the obtained offline map matches the user's actual activity area. Then, detect the version status of the offline map. When it is detected that the version status has an update, instead of downloading randomly immediately, it is downloaded based on a preset time interval, and the updated offline map is stored as the target offline map. Specifically, when downloading and updating the offline map, the system will closely monitor the operation situation. If it is found that there are multiple downloads and updates in the same area in a short period, new download requests will be temporarily blocked, and only when the preset time interval is met, will the download and update operations be allowed again. The purpose of this mechanism is to avoid unnecessary traffic waste and ensure the reasonable utilization of traffic resources.

[0086] Through the mechanism of version detection and downloading and updating based on a preset time interval, it effectively ensures that the offline map used by the user is always in the latest state, can timely reflect important data such as the latest geographical information and road conditions, and provides accurate and reliable map services for users. At the same time, combined with the abnormal monitoring and processing mechanism, it effectively avoids traffic waste caused by frequent downloading and updating of maps in the same area. On the basis of meeting the user's demand for the accuracy of map data, it realizes the optimal allocation of traffic resources, reduces the user's traffic cost, and improves the operation efficiency and resource utilization rate of the entire offline map management system.

[0087] In some examples, when it is detected that the user's behavior trajectory changes, update the user behavior model and the geographical scope of the user's living circle, and manage the target offline map based on the update results, including:

[0088] If it is detected that a navigation destination or a favorite address is added to the user's behavior trajectory, update the geographical scope of the user's living circle based on the added navigation destination and favorite address;

[0089] If it is detected that the user's behavior trajectory exceeds the geographical scope of the current user's living circle, return to the step of obtaining the user's geographical behavior data until the user behavior model is updated;

[0090] Adjust the target map based on the updated geographical scope of the user's living circle and the user behavior model.

[0091] Exemplarily, if it is detected that a navigation destination or a favorite address is added to the user's behavior trajectory, this means that the user's travel preferences or the locations of interest have changed. At this time, based on this new information, the geographical scope of the user's living circle is updated so that it can timely reflect the user's new activity area. If it is detected that the user's behavior trajectory exceeds the geographical scope of the current user's living circle, it indicates that the current user behavior model and the definition of the living circle may be inaccurate. It is necessary to start from obtaining the user's geographical behavior data again and comprehensively update the user behavior model to better adapt to the user's new behavior pattern. Finally, based on the updated geographical scope of the user's living circle and the user behavior model, the target map is adjusted to ensure that the offline map always matches the user's current behavior and activity range.

[0092] This dynamic update and adjustment mechanism enables the offline map to closely follow the changes in the user's behavior. Timely updating the living circle scope and the behavior model ensures that the downloaded offline map always covers the user's actual activity area, providing accurate and comprehensive map services for the user. At the same time, when there are significant changes in the user's behavior, re-obtaining data to update the user behavior model can better predict the user's future travel needs, improving the system's adaptability and the user experience.

[0093] In some examples, the offline map management method based on user behavior prediction further includes:

[0094] In an environment where there is no network connection or the network signal strength is lower than a preset threshold, trigger the target offline map to provide navigation services for the user.

[0095] Exemplarily, in an environment where there is no network connection or the network signal strength is lower than a preset threshold, the target offline map will be automatically triggered to provide navigation services for the user, ensuring that the user can still obtain map navigation support even in a poor network situation, thus greatly enhancing the usability and the user experience of the target offline map. In real life, users may encounter various situations with poor network environments or even no network, such as remote areas or underground parking lots. Through this setting, even in these situations, users can still rely on the downloaded target offline map to normally use the navigation function and will not be trapped due to network problems, meeting the user's map navigation needs in different scenarios and enhancing the stability and reliability of the target offline map.

[0096] In summary, in an offline map management method based on user behavior prediction proposed in this application, according to user geographical behavior data such as the user's vehicle location points and historical destinations, a user behavior model with unique characteristics for each user is established, and the offline maps between the user's life trajectory circle, daily commuting routes, and daily favorite addresses are downloaded in advance and refined and dynamically updated for navigation use in scenarios without network or with weak network, such as daily commuting, taking children out, and traveling.

[0097] It should be noted that the above embodiments are only the best examples and do not limit the implementation manners of the present application.

[0098] Based on the same inventive concept, an offline map management system based on user behavior prediction corresponding to the offline map management method based on user behavior prediction provided in the above embodiments is also provided in the embodiments of the present application. Since the principle of solving problems by the offline map management system based on user behavior prediction in the embodiments of the present application is similar to that of the offline map management method based on user behavior prediction in the above embodiments of the present application, the implementation of the system can refer to the implementation of the method, and the repeated parts will not be described again.

[0099] As Figure 3 shown, Figure 3 is a functional module diagram of an offline map management system based on user behavior prediction provided by the present application. The system includes:

[0100] A data collection module 21, configured to obtain user geographical behavior data;

[0101] A data analysis module 22, configured to determine a user behavior model and the geographical scope of a user's living circle based on the user geographical behavior data;

[0102] A map download module 23, configured to download and store a target offline map according to the geographical scope of the user's living circle;

[0103] A map update module 24, configured to update the user behavior model and the geographical scope of the user's living circle when it is detected that the user behavior trajectory changes, and manage the target offline map based on the update result.

[0104] Exemplarily, the data collection module 21 obtains user geographical behavior data, the data analysis module 22 determines the user behavior model and the geographical scope of the living circle accordingly, the map download module 23 downloads and stores the target offline map according to the living circle scope, and the map update module 24 updates the behavior model and the living circle scope when it is detected that the user behavior trajectory changes, and manages the target offline map based on the update result. The offline map management system based on user behavior prediction provided by the present application predicts the activity area according to the user behavior, prepares a suitable offline map in advance, and can dynamically adjust the management strategy according to the user behavior, accurately meet the requirements, reasonably utilize resources, reduce traffic consumption, and provide personalized, accurate and efficient offline map services that fit the actual situation of the user.

[0105] As Figure 4As shown in the figure, based on the same application concept, an embodiment of the present application further provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored on the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, the steps of any of the above-mentioned offline map management methods based on user behavior prediction are implemented.

[0106] Since the electronic device introduced in this embodiment is the device used to implement an offline map management method based on user behavior prediction in an embodiment of the present application, based on the method introduced in the embodiment of the present application, those skilled in the art can understand the specific implementation manners and various variations of the electronic device in this embodiment. Therefore, the specific implementation of how this electronic device implements the method in the embodiment of the present application will not be described in detail here. As long as the device used by those skilled in the art to implement the method in the embodiment of the present application belongs to the scope protected by the present application.

[0107] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0109] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0110] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one process or multiple processes and / or blocks. Figure 1 one process or multiple processes and / or blocks Figure 1 steps for implementing the functions specified in one block or multiple blocks.

[0111] An embodiment of the present application also provides a computer program product, which includes computer software instructions. When the computer software instructions run on a processing device, the processing device is caused to execute the process of the offline map management method based on user behavior prediction in the corresponding embodiment.

[0112] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be stored by a computer, or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0113] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and modules can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0114] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division. In actual implementation, there can be other division methods. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections between each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can be in electrical, mechanical, or other forms.

[0115] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical modules, that is, they can be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0116] In addition, in each embodiment of the present application, the functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0117] If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0118] The above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or perform equivalent replacements for some of the technical features. And these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. An offline map management method based on user behavior prediction, characterized in that: include: Obtain user geographic behavior data; Based on the user's geographic behavior data, determine the user behavior model and the geographic scope of the user's life circle; Downloading and storing a target offline map according to the geographical scope of the user's living circle; When changes in the user behavior trajectory are monitored, the user behavior model and the geographical range of the user life circle are updated, and the target offline map is managed based on the update result.

2. The offline map management method based on user behavior prediction according to claim 1 is characterized in that: In determining the user behavior model and the geographical scope of the user's living circle based on the user's geographical behavior data, the step of determining the user behavior model includes: Based on the user's geographic behavior data, obtaining parking location data and stay duration data within a preset time period; Determine the user's home address and company address based on the parking location data and the stay duration data; Based on the user's geographic behavior data, obtaining the visit frequency and favorite address type of historical navigation destinations; Extracting the user's target frequently visited addresses, historically collected addresses and points of interest according to the visit frequency of the historical navigation destination and the type of the collected addresses; The user behavior model is determined based on the user's home address, the company address, the target frequency visited address, the historical collection address and the point of interest.

3. The offline map management method based on user behavior prediction according to claim 2 is characterized in that: The extracting the target frequency access address of the user comprises: Filtering the destinations whose visit frequency exceeds a preset visit frequency threshold among the historical navigation destinations, and removing the home address and the company address from the filtered destinations to obtain an initial visit address; The target frequency access address is extracted from the initial access address based on the target frequency.

4. The offline map management method based on user behavior prediction according to claim 2 is characterized in that: In determining the user behavior model and the geographical scope of the user's life circle based on the user's geographical behavior data, the step of determining the geographical scope of the user's life circle includes: Taking the home address and the company address as the center, respectively generate a buffer zone with a first preset radius; Extracting a round-trip route between the home address, the company address, the target frequency visit address and the point of interest, and generating a route buffer of a first preset width along the round-trip route; Based on the historical visit frequency and maximum distance of the user to the point of interest, generating a buffer zone of a second preset radius centered on the home address; The buffer zone of the first preset radius, the route buffer zone of the first preset width, and the buffer zone of the second preset radius are combined, and duplicate areas are removed to determine the geographical scope of the user's living circle.

5. The offline map management method based on user behavior prediction according to claim 1 is characterized in that: The downloading and storing of the target offline map according to the geographical range of the user's living circle includes: Obtaining an offline map according to the geographical scope of the user's living circle; Detecting the version status of the offline map; When the version status update is detected, the updated offline map is downloaded and stored based on a preset time interval as the target offline map.

6. The offline map management method based on user behavior prediction according to claim 1, characterized in that: When a change in the user behavior trajectory is detected, the user behavior model and the geographical range of the user life circle are updated, and the target offline map is managed based on the update result, including: If it is detected that a navigation destination or a favorite address is added to the user's behavior trajectory, the geographical scope of the user's life circle is updated based on the added navigation destination and the favorite address; If it is monitored that the user behavior trajectory exceeds the geographical scope of the current user's living circle, return to the step of obtaining the user's geographical behavior data until the user behavior model is updated; The target map is adjusted based on the updated geographical scope of the user's life circle and the user behavior model.

7. The offline map management method based on user behavior prediction according to claim 1 is characterized in that: Also includes: In an environment where there is no network connection or the network signal strength is lower than a preset threshold, the target offline map is triggered to provide navigation services to the user.

8. An offline map management system based on user behavior prediction, applied to the offline map management method based on user behavior prediction as claimed in any one of claims 1 to 7, characterized in that: include: Data collection module, used to obtain user geographic behavior data; A data analysis module, used to determine a user behavior model and a geographical range of a user's living circle based on the user's geographical behavior data; A map download module, used to download and store a target offline map according to the geographical scope of the user's living circle; The map update module is used to update the user behavior model and the geographical scope of the user life circle when changes in the user behavior trajectory are monitored, and manage the target offline map based on the update result.

9. An electronic device, comprising: A memory and a processor, wherein the processor is used to implement the steps of the offline map management method based on user behavior prediction as described in any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the offline map management method based on user behavior prediction as described in any one of claims 1 to 7 are implemented.

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