A method, apparatus, device, and storage medium for detecting regional accessibility

Abstract

This application discloses a method, apparatus, device, and storage medium for detecting the accessibility of a region. It queries road segments within a target region, obtains trajectory information of several objects within the target region, and identifies target objects traversing each road segment based on the trajectory information, thus obtaining corresponding object groups. Based on the object groups corresponding to each road segment, the diversity index of the road segment can be determined, thereby determining whether a large number of different objects have traversed that road segment, i.e., whether the road segment is publicly available. Therefore, based on the diversity index corresponding to each road segment, the accessibility detection result of the target region can be determined. This application can quickly determine the accessibility detection result of a target region, supports real-time updates, and has low implementation cost, improving the accuracy of provided geographic information and enhancing the user experience of map services. The technical solution of this application can be widely applied in the field of map technology.

Description

Technical Field

[0001] This application relates to the field of map technology, and in particular to a method, apparatus, device, and storage medium for detecting regional accessibility. Background Technology

[0002] With the rapid development of information technology, related services have gradually become integrated into people's lives. For example, map services refer to services that provide geospatial data and map visualization functions through the Internet or local networks. The core function of map services is to present geographic information in a graphical way (i.e., map data). It allows users to view map data on web pages, mobile applications, or other platforms and perform corresponding operations, such as zooming, panning, searching for locations, and route planning.

[0003] In related technologies, when using map services, users often want to know whether certain areas are passable, i.e., they want the map service to clearly mark the passability information of an area, such as whether it is a passable area or a restricted area. Currently, some existing technical solutions often analyze existing historical tracks; if a historical track passes through an area, it is marked as passable. With this approach, some areas that only allow certain specific groups of people to pass may actually be restricted areas, yet they are still marked as passable. It is evident that existing technical solutions lack accuracy in determining the passability information of areas, easily leading to incorrect guidance and affecting the user experience of map services. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for detecting regional accessibility, which can quickly determine the accessibility detection results of a target area, improve the accuracy of providing geographic information, and enhance the user experience of map services.

[0005] One aspect of this application provides a method for detecting regional accessibility, the method comprising:

[0006] Query the road segments contained within the target area;

[0007] Obtain trajectory information of several objects within the target area;

[0008] Based on the trajectory information, target objects passed through each road segment are determined from the objects to obtain an object group corresponding to each road segment; wherein, the object group includes the target objects corresponding to the road segment;

[0009] The diversity index of the road segment is determined based on the object group corresponding to the road segment;

[0010] Based on the diversity index of each road segment, the accessibility detection result of the target area is determined; wherein, the accessibility detection result is used to characterize whether the target area is a passable area or a restricted area.

[0011] On the other hand, embodiments of this application provide a regional accessibility detection device, the device comprising:

[0012] The query unit is used to query road segments contained within a target area;

[0013] The acquisition unit is used to acquire trajectory information of several objects within the target area;

[0014] An integration unit is configured to determine, based on the trajectory information, the target objects traversed on each road segment from the objects, thereby obtaining an object group corresponding to each road segment; wherein the object group includes the target objects corresponding to the road segment;

[0015] The processing unit is used to determine the diversity index of the road segment based on the object group corresponding to the road segment;

[0016] The discrimination unit is used to determine the accessibility detection result of the target area based on the diversity index of each road segment; wherein the accessibility detection result is used to characterize whether the target area is a passable area or a restricted area.

[0017] Optionally, in some embodiments, the processing unit is specifically used for:

[0018] Count the number of times each target object in the object group passes through the road segment;

[0019] The total number of times each of the target objects passes through the road segment is determined based on the sum of the number of times each of the target objects passes through the road segment.

[0020] The probability of occurrence of the target object is determined based on the ratio of the number of times the target object passes through the road segment to the total number of times it passes through the road segment.

[0021] The diversity index of the road segment is determined based on the occurrence probability corresponding to each target object.

[0022] Optionally, in some embodiments, the processing unit is specifically used for:

[0023] Calculate the square of the occurrence probability corresponding to the target object to obtain the first index data corresponding to the target object;

[0024] The first indicator data corresponding to each of the target objects is summed to obtain the second indicator data;

[0025] The diversity index of the road segment is obtained based on the difference between the data of indicator 1 and the second indicator.

[0026] Optionally, in some embodiments, the detection device further includes a rejection unit, which is specifically used for:

[0027] Compare the total number of occurrences and the number threshold corresponding to the road segment;

[0028] If the total number of occurrences for the road segment is less than the threshold number, the data corresponding to the road segment is removed.

[0029] Optionally, in some embodiments, the acquisition unit is specifically used for:

[0030] The location information of the object within the target area is continuously collected, and the first collection time corresponding to each location information is recorded;

[0031] Based on the location information and the order of the first acquisition time, the trajectory information of the object is determined within the target area.

[0032] Optionally, in some embodiments, the acquisition unit is specifically used for:

[0033] Acquire video data within the target area;

[0034] Target detection is performed based on the video data to identify objects that have passed through the target area;

[0035] Based on the video data, the object is re-identified to determine the object's trajectory information within the target area.

[0036] Optionally, in some embodiments, the detection device further includes a deletion unit, which is specifically used for:

[0037] Query the second acquisition time corresponding to the trajectory information;

[0038] Detect whether the second collection time falls within a predetermined period; wherein, the predetermined period includes holidays;

[0039] If it is determined that the second collection time falls within the predetermined period, the trajectory information is deleted.

[0040] Optionally, in some embodiments, the discrimination unit is specifically used for:

[0041] The diversity index of each road segment is compared with a preset threshold.

[0042] If the diversity index of all the road segments is less than or equal to the preset threshold, the accessibility detection result of the target area is determined to be that the target area belongs to the restricted access area.

[0043] Optionally, in some embodiments, the discrimination unit is specifically used for:

[0044] Detect whether the endpoint of the road segment is located at the edge of the target area;

[0045] If the endpoint of the road segment is not located at the edge of the target area, the road segment is identified as the target road segment;

[0046] The diversity index of the target road segment is compared with a preset threshold;

[0047] If the diversity index of the target road segment is greater than the preset threshold, the accessibility detection result of the target area is determined to be that the target area belongs to the passable area.

[0048] Optionally, in some embodiments, the discrimination unit is specifically used for:

[0049] If the accessibility detection result of the target area indicates that the target area is a passable area, the weight of each road segment is determined based on the diversity index of each road segment; wherein, the diversity index and the weight are positively correlated.

[0050] Based on the weights, a depth-first search is performed on the road segments, and a recommended route through the target area is determined based on the search results.

[0051] On the other hand, embodiments of this application provide an electronic device, including a processor and a memory;

[0052] The memory is used to store computer programs;

[0053] The processor executes the computer program to implement the aforementioned method for detecting regional accessibility.

[0054] On the other hand, embodiments of this application provide a computer-readable storage medium storing a computer program, which is executed by a processor to implement the aforementioned method for detecting regional accessibility.

[0055] On the other hand, embodiments of this application also provide a computer program product, which includes a computer program stored in a computer-readable storage medium. The processor of a computer device reads the computer program from the computer-readable storage medium and executes the computer program, causing the computer device to perform the aforementioned detection method for regional accessibility.

[0056] The embodiments of this application include at least the following beneficial effects: This application provides a method, apparatus, device, and storage medium for detecting the accessibility of a region. It queries road segments within a target region, obtains trajectory information of several objects within the target region, and, based on the trajectory information, identifies the target objects traversing each road segment, thus obtaining the corresponding object groups. Based on the object groups corresponding to each road segment, the diversity index of the road segment can be determined, thereby determining whether a large number of different objects have traversed that road segment, i.e., whether the road segment is publicly available. Therefore, based on the diversity index corresponding to each road segment, the accessibility detection result of the target region can be determined. This application can quickly determine the accessibility detection result of a target region, supports real-time updates, and has low implementation costs, which can improve the accuracy of providing geographic information and improve the user experience of map services. Attached Figure Description

[0057] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0058] Figure 1 This is a schematic diagram illustrating a scenario of using map services provided in an embodiment of this application;

[0059] Figure 2 This is a system architecture diagram of a method for detecting regional accessibility provided in the embodiments of this application;

[0060] Figure 3 This is a schematic diagram of the interface of an in-vehicle navigation system provided in the embodiments of this application;

[0061] Figure 4 This is a flowchart illustrating a method for detecting regional accessibility provided in an embodiment of this application.

[0062] Figure 5 This is a schematic diagram of a road network within a region, provided in an embodiment of this application.

[0063] Figure 6 This is a schematic diagram illustrating the principle of obtaining trajectory information of an object according to an embodiment of this application;

[0064] Figure 7 This is a schematic diagram of a process for deleting trajectory information provided in an embodiment of this application;

[0065] Figure 8 This is a flowchart illustrating a method for determining the accessibility detection result of a target area, as provided in an embodiment of this application.

[0066] Figure 9This is a schematic diagram of another process for determining the accessibility detection result of a target area according to an embodiment of this application;

[0067] Figure 10 This is a schematic diagram of a process for determining a recommended route provided in an embodiment of this application;

[0068] Figure 11 This is a structural block diagram of a regional accessibility detection device provided in the embodiments of this application;

[0069] Figure 12 This is a structural block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0071] It is understood that the terms “first,” “second,” etc., used in this application may be used to describe various concepts herein, but unless otherwise stated, these concepts are not limited by these terms. These terms are used only to distinguish one concept from another.

[0072] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0073] Before providing a further detailed description of the embodiments of this application, the nouns and terms used in the embodiments of this application are explained, and the nouns and terms used in the embodiments of this application shall be interpreted as follows:

[0074] 1) Artificial Intelligence (AI) is the theory, methods, technology, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results. In other words, AI is a comprehensive technology within computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a way similar to human intelligence. AI studies the design principles and implementation methods of various intelligent machines, enabling them to possess the functions of perception, reasoning, and decision-making.

[0075] Artificial intelligence (AI) is a comprehensive discipline encompassing a wide range of fields, including both hardware and software technologies. Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, pre-trained model technology, operating / interactive systems, and mechatronics. Among these, pre-trained models, also known as large-scale models or foundational models, can be widely applied to downstream tasks across various AI fields after fine-tuning. AI software technologies primarily include computer vision, speech processing, natural language processing, and machine learning / deep learning.

[0076] 2) Computer vision (CV) is an important branch of artificial intelligence (AI), aiming to enable computers to "see" and understand image or video content like humans. By simulating the working principle of the human visual system, computer vision technology can analyze, interpret, and process image and video data, thereby achieving automated decision-making and task execution.

[0077] 3) Machine Learning (ML) is a multidisciplinary field involving probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory. It specifically studies how computers can simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to endow computers with intelligence; its applications span all areas of artificial intelligence. Machine learning and deep learning typically include techniques such as artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and pre-trained learning. Pre-trained models are the latest development in deep learning, integrating the above techniques.

[0078] With the rapid development of information technology, related services have gradually become integrated into people's lives. For example, map services refer to services that provide geospatial data and map visualization functions through the Internet or local networks. The core function of map services is to present geographic information in a graphical way (i.e., map data). It allows users to view map data on web pages, mobile applications, or other platforms and perform corresponding operations, such as zooming, panning, searching for locations, and route planning.

[0079] Map services can provide a variety of functions. For example, in some embodiments, a map service can provide route planning and navigation functions, such as calculating the optimal route based on a specified origin and destination, and then providing real-time navigation guidance. In some embodiments, a map service can provide the function of displaying real-time traffic conditions, such as using different colors on the map to distinguish the traffic conditions of different roads (e.g., green for smooth traffic, yellow for slow traffic, and red for congestion). In some embodiments, a map service can provide public transportation query functions, such as querying routes, timetables, and fare information for public transportation such as buses, subways, and trains. In some embodiments, a map service can provide location search and point-of-interest (POI) recommendation functions, allowing users to search for specific locations or categories of locations, and the map service can provide detailed information about the locations or POIs.

[0080] Of course, it is understandable that the specific functions that map services can provide are not limited to this, and this application will not elaborate on this.

[0081] In related technologies, when using map services, it is desirable to know whether certain areas are accessible. For example, please refer to... Figure 1 For example, someone plans to walk from point A to point B, but part of the route is in private or factory areas, and it's unclear whether passage is permitted. Or, some city center areas may be pedestrian streets or commercial streets, where vehicles are not allowed, or vehicle access is restricted only during specific times (such as weekends). Furthermore, food delivery workers may need to know whether certain residential complexes allow other people to enter in order to plan their deliveries.

[0082] For the scenarios mentioned above, it is desirable for map services to clearly mark the accessibility information of areas. For example, for a certain mode of transportation, it is necessary to determine whether the target area is a passable area or a restricted area. Here, the target area is the area whose accessibility information needs to be determined. Currently, some existing technical solutions often analyze existing historical tracks. If a historical track is found to have passed through the area, it is marked as a passable area. This approach is mainly for areas that are inaccessible or impassable, such as construction areas and nature reserves. By analyzing historical tracks, if a historical track passes through the target area, the target area is considered passable; if no historical track passes through the target area, it is considered impassable and a restricted area.

[0083] However, in real-world applications, certain areas may only allow passage for specific groups of people. For example, in factory areas, workers or managers may be allowed to enter and exit; in city centers, while ordinary vehicles are prohibited, public service vehicles (such as patrol cars, medical vehicles, or fire trucks) may still be allowed to pass; and in residential communities, residents can move freely within their designated areas. In such cases, existing technical solutions may mark target areas as passable, when in reality these areas are restricted. Therefore, existing technical solutions suffer from insufficient accuracy in determining area passability information, easily leading to incorrect guidance and impacting the user experience of map services.

[0084] In other technical solutions, manual data collection is used to determine the accessibility information of a target area. For example, through site visits, it is recorded whether all residents are allowed to pass through each residential community. If a community has a sign at its entrance indicating "No Entry for External Vehicles," then it is recorded that the community is a restricted area for vehicles. However, this method is very costly and, due to slow updates, also suffers from insufficient accuracy.

[0085] In view of this, this application provides a method, apparatus, device, and storage medium for detecting the traversability of a region. This application queries road segments within a target region to obtain trajectory information of several objects within the target region. Based on the trajectory information, the target objects traversing each road segment can be identified, resulting in corresponding object groups. Based on the object groups corresponding to each road segment, the diversity index of the road segment can be determined, thereby determining whether a large number of different objects have traversed that road segment, i.e., whether the road segment is publicly available. Therefore, based on the diversity index corresponding to each road segment, the traversability detection result of the target region can be determined. This application can quickly determine the traversability detection result of a target region, supports real-time updates, and has low implementation costs. It can improve the accuracy of providing geographic information and is beneficial to improving the user experience of map services.

[0086] It should be noted that in this application, the collection and processing of relevant data should strictly comply with the requirements of relevant national laws and regulations in the actual application, and the informed consent or separate consent of the personal information subject should be obtained. Subsequent data use and processing should be carried out within the scope of laws and regulations and the authorization of the personal information subject.

[0087] System architecture and scenario description used in the embodiments of this application

[0088] Figure 2 This is a system architecture diagram of a regional accessibility detection method provided in this application embodiment, which includes a terminal device 240, an Internet 230, a gateway 220, a backend server 210, etc.

[0089] In this embodiment, the terminal device 240 may include various forms such as a desktop computer, laptop computer, PDA (personal digital assistant), mobile phone, vehicle terminal, home theater terminal, and dedicated terminal. Furthermore, it can be a single device or a collection of multiple devices. The terminal device 240 can communicate with the Internet 230 via wired or wireless means to exchange data.

[0090] A backend server 210 refers to a computer system that can provide certain services to terminal devices 240. Compared to ordinary terminal devices 240, backend servers 210 have higher requirements in terms of stability, security, and performance. A backend server 210 can be a single high-performance computer in a network platform, a cluster of multiple high-performance computers, a portion of a single high-performance computer (e.g., a virtual machine), or a combination of portions of multiple high-performance computers (e.g., virtual machines).

[0091] Gateway 220, also known as an internetwork connector or protocol converter, is a computer system or device that acts as a translator, enabling network interconnection at the transport layer. It bridges the gap between two systems using different communication protocols, data formats, languages, or even completely different architectures. Gateways can also provide filtering and security functions. Messages sent from terminal device 240 to backend server 210 are forwarded to the corresponding backend server 210 via gateway 220. Messages sent from backend server 210 to terminal device 240 are also forwarded to the corresponding terminal device 240 via gateway 220.

[0092] The backend server 210 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0093] The regional accessibility detection method provided in this application embodiment can be executed on the backend server 210 side, and the regional accessibility detection task is realized based on the data transmission between the terminal device 240 and the backend server 210.

[0094] For example, in this embodiment of the application, a map service-related application may be installed on the terminal device 240, and the backend server 210 may be the backend server of the application. The backend server 210 can query the road segments contained within the target area, and then obtain the trajectory information (if any) of each terminal device 240 in the target area. Based on this trajectory information, it can determine the target terminals passing through each road segment from the terminal devices 240, obtaining the terminal group corresponding to each road segment; based on the terminal group corresponding to the road segment, it determines the diversity index of the road segment; based on the diversity index of the road segment, it determines the traversability detection result of the target area. Then, the backend server 210 can generate identification information corresponding to the traversability detection result in the application for display on all terminal devices 240.

[0095] Of course, it is understood that the implementation environment corresponding to the method in the embodiments of this application is not limited to that of the implementation environment. Figure 2 As shown, those skilled in the art can flexibly select the specific implementation environment according to actual needs, and this application does not impose any restrictions on this.

[0096] The area accessibility detection method provided in this application can be executed in various scenarios, and the following is an exemplary description of this method.

[0097] (a) Scenarios of in-vehicle navigation

[0098] The method provided in this application embodiment can be applied to in-vehicle navigation scenarios.

[0099] In-vehicle navigation systems are common in modern vehicles. They provide drivers with route planning, traffic updates, and destination guidance through GPS (Global Positioning System), map data, and real-time traffic information. To ensure accuracy and safety, in-vehicle navigation systems need robust area accessibility detection capabilities.

[0100] In this scenario, the method described in the embodiments of this application can be applied. For example, please refer to... Figure 3 , Figure 3 A schematic diagram of the interface of an in-vehicle navigation system provided in an embodiment of this application is shown. For example... Figure 3 As shown, the navigation route information can be displayed on the interface of the in-vehicle navigation system. When determining the navigation route information, the accessibility of each area can be detected based on the method in this embodiment. If it is found that private vehicles are not allowed to pass through certain areas, the driver can be prompted through a prompt box 310 on the interface of the in-vehicle navigation system, and other detour routes can be planned.

[0101] (II) Scenarios of food delivery services

[0102] The method provided in this application embodiment can be applied to the scenario of food delivery services.

[0103] In the context of food delivery services, the area accessibility detection method in this embodiment can be used to determine whether a specific area (such as a residential community) is permitted for delivery riders to enter, ensuring the smooth operation of the delivery service. For example, the food delivery platform can collaborate with a relevant map service platform, which can then execute the method described in this embodiment to determine the accessibility detection results for each residential community. When a delivery rider arrives at a residential community, they can clearly understand whether they are allowed to enter the community to perform the delivery task, or whether the food needs to be placed at a designated location outside the community, facilitating the smoother completion of food delivery orders.

[0104] General Description of Embodiments in this Application

[0105] Please refer to Figure 4 , Figure 4 A flowchart illustrating a method for detecting regional accessibility provided in an embodiment of this application is shown. Figure 4 As shown, a method for detecting regional accessibility according to an embodiment of this application includes, but is not limited to, the following steps:

[0106] Step 410: Query the road segments contained within the target area;

[0107] Step 420: Obtain trajectory information of several objects within the target area;

[0108] Step 430: Based on the trajectory information, determine the target objects passed through each road segment from the objects to obtain the object group corresponding to each road segment; wherein, the object group includes the target objects corresponding to the road segment;

[0109] Step 440: Determine the diversity index of the road segment based on the object group corresponding to the road segment;

[0110] Step 450: Determine the accessibility detection results of the target area based on the diversity index of each road segment; wherein, the accessibility detection results are used to characterize whether the target area is a passable area or a restricted area.

[0111] This application provides a method for detecting regional accessibility. This method can quickly determine the accessibility detection results of a target area, supports real-time updates, and has low implementation cost. It can improve the accuracy of providing geographic information and improve the user experience of map services.

[0112] In this application embodiment, the area requiring accessibility detection is denoted as the target area. The specific type of the target area is not limited in this application. For example, in some embodiments, the target area may be a residential community. By detecting the accessibility of the residential community, it is easy to determine whether non-residents can pass through the community. In some embodiments, the target area may be a commercial area. For example, vehicle accessibility can be detected in commercial areas to facilitate the planning of vehicle routes. Of course, in some embodiments, the target area may also be a factory, school, hospital, outdoor activity area, etc. Furthermore, in this application embodiment, the target area can be, in addition to the aforementioned independent specific areas, a comprehensive area flexibly defined according to needs, which may contain different building types and has any shape; this application does not limit this.

[0113] In step 410, the target area is queried for road segments. Here, a road segment (link) refers to a section of a road, generally the part between one intersection and another, which is the basic unit in traffic management and navigation systems.

[0114] In this embodiment, the method of dividing road segments is not limited. In some embodiments, road segments can be divided based on intersections in the road network. If there is a road between two intersections and there are no other intersections on that road, that road can be identified as a road segment. For example, please refer to... Figure 5 , Figure 5 A schematic diagram of a road network within a region, as provided in an embodiment of this application, is shown. For example... Figure 5 As shown, in a certain area, there is a first building 510 and a second building 520. Between the first building 510 and the second building 520, there is a line 530. The line 530 goes directly from the first building 510 to the second building 520 without any other intersections in between. The starting point and the ending point of the line 530 are both intersections. At this time, the line 530 can be defined as a road segment.

[0115] In other embodiments, road segments can also be divided based on other road characteristics. For example, road segments can be divided based on length; if a route is long, it can be divided into multiple segments for easier management and statistics. For example, road segments can be divided based on road type; for instance, if a road changes from a regular road to a highway at a certain point, the roads on both sides of that point can be divided into different segments. In this application, the specific method of dividing road segments is not limited. A road segment has two endpoints and its shape can be arbitrary.

[0116] In this embodiment of the application, the road segment information for each road can be pre-defined. During acquisition, it can be queried in the database corresponding to the relevant map service. For step 410, when querying the road segments contained within the target area, the information of the target area can be input into the data to obtain the corresponding road segment information.

[0117] It is understood that, in the embodiments of this application, the number of road segments included in the target area can be one or more, such as two or more, and this application does not limit this.

[0118] In step 420, trajectory information of several objects within the target area is obtained. Here, the objects can be terminal devices or other means of transportation such as vehicles, which can be set according to actual needs. Of course, in some other cases, the objects can also include both terminal devices and vehicles, and this application does not impose any restrictions on this.

[0119] In step 420, trajectory information of several objects within the target area is obtained. These objects must have appeared within the target area; objects not appearing within the target area do not need to be acquired. Alternatively, in some embodiments, trajectory information of all objects can be acquired, and those appearing within the target area can be filtered out. Then, the trajectory information of these objects within the target area is extracted. This application does not impose any limitations on this. Here, "several" indicates that the specific number of objects is not limited. Generally, the number of objects passing through the target area is multiple, which can be any number of two or more.

[0120] It should be noted that, in the embodiments of this application, when obtaining the trajectory information of an object in the target area, in some cases, the trajectory information of all objects (such as terminal devices and vehicles) that have appeared in the target area can be obtained, and in other cases, the category of the object can be specified in advance (for example, the category of the object can be specified as terminal device), and then only the trajectory information of the specific category of object can be obtained. This application does not impose any restrictions on this.

[0121] In some embodiments, when acquiring trajectory information of an object within a target area, it can be based on the object's location. For example, if the object is a terminal device, the location information of the terminal device can be obtained through the Global Positioning System (GPS), the BeiDou Navigation Satellite System, etc. In this way, the location information of the object within the target area can be continuously collected, and the collection time corresponding to each location information is recorded. In this embodiment, this is recorded as the first collection time, thus obtaining a series of comprehensive location information records.

[0122] After obtaining the object's location information, the object's trajectory within the target area can be determined based on the sequence of each location and its corresponding first acquisition time. Specifically, the locations can be connected in chronological order of their first acquisition times; the resulting line represents the object's trajectory within the target area.

[0123] For example, please refer to Figure 6 , Figure 6 This illustration shows a schematic diagram illustrating the principle of obtaining the trajectory information of an object in an embodiment of this application. For example... Figure 6 As shown in this embodiment, the object can be located periodically to obtain location information. This location information is then marked on a map to obtain a location point 610, and the first acquisition time corresponding to the location point 610 is recorded. In this way, by continuously acquiring the object's location information within the target area, multiple location points 610 can be obtained. By connecting the various location points 610 according to the chronological order of the first acquisition times, the object's trajectory information can be obtained.

[0124] In other embodiments, a re-identification method can also be used when acquiring the trajectory information of an object within the target area. Re-identification is a computer vision application in the field of artificial intelligence. It can be used to achieve cross-viewpoint matching and recognition of the same object in different video data or scenes. Through the re-identification strategy, the trajectory of the object can be detected, thereby obtaining the trajectory information of the object within the target area.

[0125] Specifically, in this embodiment, video data within a target area can be acquired. For example, the target area may be a residential community with multiple cameras installed, which essentially cover all locations within the target area. In this embodiment, recorded video data can be acquired from each camera, and based on the video data, object detection can be performed on objects appearing within the target area. Here, relevant object detection models can be used to identify objects, such as machine learning models or deep learning models, like YOLO (You Only Look Once), Faster R-CNN, SSD (Single Shot MultiBox Detector), etc. This application does not impose any limitations on this.

[0126] For each identified object target, in this embodiment, re-identification can be performed on the video data. The relevant model for re-identification can be ResNet, DenseNet, etc., and this application does not impose any limitations on this. During the re-identification process, the model will calculate the similarity of objects in different frames within the video data. Commonly used similarity metrics include Euclidean distance and cosine similarity. Based on the similarity, objects in different frames can be matched to determine which frames contain the same object. According to the matching results, the positions of the same object in different frames can be connected to generate trajectory information.

[0127] Of course, it is understood that the implementation of obtaining the trajectory information of the object in the target area in the embodiments of this application is not limited to the above types. Those skilled in the art can implement it flexibly according to actual needs, and this application does not impose any restrictions on it.

[0128] It should be noted that in the embodiments of this application, when obtaining the trajectory information of an object within the target area, the object's permission or consent is obtained first (i.e., if the object is a terminal device or a vehicle, the user's consent is obtained). Furthermore, the collection, use, and processing of this trajectory information comply with relevant laws, regulations, and standards. For example, when obtaining trajectory information, the object's individual permission or consent is obtained through pop-ups or redirection to a confirmation page. Only after explicitly obtaining the object's individual permission or consent is the necessary data for the normal operation of the embodiments of this application obtained.

[0129] In step 430, for each road segment, based on the trajectory information, objects that have passed through that road segment can be identified from the objects. In this embodiment, the objects that have passed through the road segment are recorded as the target objects corresponding to that road segment. After identifying the target objects corresponding to the road segment, they can be added to the object group corresponding to the road segment. Each road segment corresponds to one object group. In this embodiment, each object group may include one or more target objects, or it may not include any target objects. This application does not impose any restrictions on this.

[0130] Specifically, in this embodiment, when determining the target object traversed on each road segment based on trajectory information, for each object, if its trajectory information completely covers a certain road segment, it can be identified as the target object corresponding to that road segment and added to the object group corresponding to that road segment. If the object's trajectory information only partially involves a certain road segment, the object can not be identified as the target object corresponding to that road segment. It is understood that for an object, the number of road segments covered by its trajectory information may be large; therefore, an object may exist in multiple object groups simultaneously. For object groups corresponding to different road segments, there may be partially overlapping target objects or completely identical target objects; this application does not impose any restrictions on this.

[0131] It should be noted that, in this embodiment of the application, for each target object in the object group, the number of times they pass through the corresponding road segment is also counted. This number can be the number of times they have completely walked through the road segment.

[0132] In step 440, after determining the object group corresponding to the road segment, the diversity index of the road segment can be determined based on the object group. In this embodiment, the diversity index is an indicator used to measure the diversity of members within a group. It can be understood that a higher diversity index indicates higher diversity within the group, and vice versa. In this embodiment, the specific implementation method for determining the diversity index is not limited.

[0133] In step 450, after determining the diversity index of the road segment, the accessibility test results of the target area can be determined based on the diversity index.

[0134] Understandably, if the objects passing through the various road segments within a target area are highly homogeneous—for example, only a specific group of objects—the target area is likely a restricted access zone. For instance, for a target area like a residential community, if non-residents are not allowed to enter, then the objects passing through the various road segments within the community will generally be residents. The number of members corresponding to each road segment will be relatively small, resulting in a low diversity index for the road segments, indicating that the objects passing through those segments are essentially unchanged. In this case, it can be determined that the target area is a restricted access zone, meaning only specific objects are allowed to pass.

[0135] Conversely, if the objects passing through the various road segments in the target area are highly diverse—for example, many different objects pass through the target area, and the number of target objects corresponding to each road segment is large—then the target area is likely to be a passable area. For instance, for a target area of ​​the type of outdoor plaza, it allows all objects to pass through. Then, many objects pass through the various road segments within the plaza, and the number of members in each road segment's object group is relatively large, resulting in a high road segment diversity index. In this case, it can be determined that the target area is a passable area, meaning it is open to all objects.

[0136] Therefore, in this embodiment, the traversability detection result of the target area can be determined based on the diversity index of road segments. For example, if most road segments in the target area have a high diversity index, they can be identified as traversable areas; conversely, if most road segments in the target area have a low diversity index, they can be identified as restricted traversable areas. Specifically, in this embodiment, a diversity index threshold, denoted as the preset threshold, and a proportion threshold can be set. If the diversity index of a road segment is greater than the preset threshold, it can be recorded as a traversable road segment. If the proportion of traversable road segments in the target area is greater than the proportion threshold, the target area can be identified as a traversable area. If the proportion of traversable road segments in the target area is less than or equal to the proportion threshold, the target area can be identified as a restricted traversable area.

[0137] It is understood that the regional accessibility detection method provided in this application query the road segments contained within the target area, obtain the trajectory information of several objects within the target area, and determine the target objects passing through each road segment based on the trajectory information, thus obtaining the corresponding object group. Based on the object group corresponding to the road segment, the diversity index of the road segment can be determined, thereby determining whether a large number of different objects have passed through the road segment, i.e., whether the road segment is publicly available. Therefore, based on the diversity index corresponding to each road segment, the accessibility detection result of the target area can be determined. This application can quickly determine the accessibility detection result of the target area, supports real-time updates, and has low implementation cost, which can improve the accuracy of providing geographic information and improve the user experience of map services.

[0138] Specifically, in some embodiments, reference is made to Figure 7 After obtaining the trajectory information of several objects within the target area, the method in this application further includes:

[0139] Step 710: Query the second collection time corresponding to the trajectory information;

[0140] Step 720: Check whether the second collection time is within the predetermined period; wherein, the predetermined period includes holidays;

[0141] Step 730: If it is determined that the second collection time is within the predetermined period, delete the trajectory information.

[0142] In this embodiment of the application, certain areas may be open to the public during specific time periods. For example, some parks or roads may be open to traffic during holidays but not under normal circumstances. In such cases, if trajectory information from holidays is collected, it may interfere with the final detection results.

[0143] Therefore, in this embodiment, after collecting trajectory information, the collection time corresponding to each trajectory information can be queried. In this embodiment, this time is recorded as the second collection time. Unlike the aforementioned first collection time, since trajectory information is a series of locations, the second collection time is not a single point in time, but a period of time. In this embodiment, it can be determined whether the second collection time falls within a predetermined period. This predetermined period can be the aforementioned holidays, but is not limited to them, and this application does not impose any restrictions on this.

[0144] If the second acquisition time corresponding to the trajectory information falls within the predetermined period, the trajectory information can be deleted. This effectively improves the validity of the trajectory information, reduces interference factors caused by certain special time nodes, and can improve the accuracy of detection.

[0145] Specifically, based on the target group corresponding to the road segment, the diversity index of the road segment is determined, including:

[0146] The number of times each target object in the group passes through a road segment;

[0147] The total number of times each road segment is traversed is determined based on the total number of times all target objects pass through the road segment.

[0148] The probability of occurrence of the target object is determined by the ratio of the number of times the target object passes through the road segment to the total number of times it passes through the road segment.

[0149] The diversity index of road segments is determined based on the occurrence probability of each target object.

[0150] In this embodiment, when determining the diversity index of a road segment, in some cases, the number of times each target object in the object group passes through the road segment can be counted. For example, if a target object has a route in the target area that it does not travel back and forth on, then the number of times it passes through the corresponding road segment is 1; if a target object repeatedly passes through a road segment N times, then the corresponding number of times is N (N is a positive integer). In this embodiment, there is no limit to the number of times each target object passes through a road segment; it can be once or multiple times.

[0151] For a given road segment, the total number of times a target object in the target group passes through it can be calculated and recorded as the total number of times. Then, the probability of occurrence of that target object can be determined based on the ratio of the number of times a target object passes through the road segment to the total number of times. For example, if a target object passes through a road segment 9 times, and the total number of times for that road segment is 100, then the probability of occurrence of the target object is 0.09. In this embodiment, the diversity index of the road segment can be determined based on the probability of occurrence of each target object.

[0152] For example, in some embodiments, the diversity index of a road segment is determined based on the occurrence probability of each target object, including:

[0153] Calculate the square of the probability of occurrence of the target object to obtain the first indicator data corresponding to the target object;

[0154] The second indicator data is obtained by summing the first indicator data corresponding to each target object;

[0155] The diversity index of the road segment is obtained based on the difference between the data of indicator 1 and indicator 2.

[0156] In this embodiment of the application, the following formula can be used to calculate the diversity index of a road segment:

[0157]

[0158] In the formula, D represents the diversity index of the road segment, i represents the number of the target object corresponding to the road segment, S represents the total number of target objects corresponding to the road segment, and P i This represents the probability of the target object appearing, where i and S are positive integers.

[0159] Specifically, when calculating the diversity index of a road segment, the square of the probability of occurrence for each target object can be calculated first, and in this embodiment, this is recorded as the first index data. Next, the first index data corresponding to each target object can be summed, and the resulting value is recorded as the second index data. Then, the difference between the first and second index data can be calculated to obtain the diversity index of the road segment.

[0160] In this embodiment, the principle for determining the diversity index is as follows: A target object is selected from the object group corresponding to the road segment, and the probability of selecting that target object again is determined; this is the first index data. It can be understood that if there are few target objects in the object group, and the probability of each target object appearing is high, then the probability of selecting that target object again will also be high, hence the first index data will be relatively high. The first index data corresponding to each target object is accumulated to obtain the second index data. The second index data represents the overall probability of selecting the same target object. The higher the second index data, the worse the diversity of the object group. Therefore, the diversity index of the road segment can be obtained by calculating the difference between 1 and the second index data.

[0161] Specifically, in some embodiments, the method in this application further includes:

[0162] Compare the total number of occurrences for each road segment with the frequency threshold;

[0163] If the total number of occurrences for a road segment is less than the threshold, the data for that road segment is removed.

[0164] In this embodiment, road segments can also be filtered based on the total number of occurrences. It's understandable that if the total number of occurrences for a road segment is very small, it means that few objects pass through it. In this case, calculating its diversity index is more likely to be biased, because the passage of a few objects can significantly affect the diversity index result. Moreover, since the total number of occurrences for these road segments is small, they have little impact on the overall trafficability of the target area and are likely to be road segments in corners. During analysis, data corresponding to these road segments can be removed.

[0165] Specifically, in this embodiment, a threshold value can be preset, for example, 500 times. If the total number of times corresponding to a road segment is less than the threshold value, its corresponding data can be deleted. This application does not limit the specific size of the threshold value. Here, deleting the data corresponding to a road segment can delete its related object groups and diversity indices, etc., which will not be used subsequently.

[0166] Specifically, in some embodiments, reference is made to Figure 8 Based on the diversity index of each road segment, the trafficability detection results of the target area are determined, including:

[0167] Step 810: Compare the diversity index of each road segment with the preset threshold;

[0168] Step 820: If the diversity index of all road segments is less than or equal to the preset threshold, determine that the target area belongs to the restricted traffic area.

[0169] In this embodiment of the application, when determining the accessibility detection result of the target area based on the diversity index of the road segment, in some cases, the diversity index of the road segment can be compared with a preset threshold. If it is found that the diversity index of all road segments is less than or equal to the preset threshold, it means that there are not many different objects passing through each road segment. At this time, the accessibility detection result can be determined that the target area belongs to the restricted access area.

[0170] Specifically, in some embodiments, reference is made to Figure 9 Based on the diversity index of each road segment, the trafficability detection results of the target area are determined, including:

[0171] Step 910: Detect whether the endpoint of the road segment is located at the edge of the target area;

[0172] Step 920: If the endpoint of the road segment is not located at the edge of the target area, the road segment is identified as the target road segment;

[0173] Step 930: Compare the diversity index of the target road segment with the preset threshold;

[0174] Step 940: If the diversity index of the target road segment is greater than the preset threshold, determine that the target area is a passable area based on the passability detection result.

[0175] In this embodiment of the application, when determining the accessibility detection result of a target area based on the diversity index of road segments, in some cases, the judgment can be made based on the situation of road segments located near the center of the target area. It is understood that if many different objects pass through road segments near the center of the target area, it indicates that the target area is likely to be a passable area, because most people can enter it.

[0176] Specifically, during the detection process, road segments near the center of the target area can be identified first; in this embodiment, these are referred to as target road segments. For each road segment, it can be detected whether its endpoints (i.e., the start and end points) are located at the edge of the target area. If they are, it indicates that the road segment is relatively peripheral to the target area, and it is likely that people frequently pass through these road segments. For example, for a residential community, there may be a road segment at its entrance; even if people cannot enter the community, non-residents will still pass through this road segment at the entrance. Therefore, in this embodiment, these road segments can be excluded.

[0177] If the endpoint of a road segment is not located at the edge of the target area, it indicates that it is a road segment near the center of the target area. In this embodiment, this road segment can be identified as a target road segment. Then, the diversity index of the target road segment can be compared with a preset threshold. If it is greater than the preset threshold, the accessibility detection result of the target area can be determined as belonging to a passable area. Here, the number of target road segments used for judgment can be one or more. To improve accuracy as much as possible, the diversity indices of multiple target road segments can be compared with the preset threshold. If all are greater than the preset threshold, the accessibility detection result of the target area can be determined as belonging to a passable area.

[0178] Specifically, in some embodiments, reference is made to Figure 10 The method in this application also includes:

[0179] Step 1010: If the accessibility detection result of the target area indicates that the target area is a passable area, determine the weight of each road segment based on the diversity index of each road segment; where the diversity index and the weight are positively correlated.

[0180] Step 1020: Perform a depth-first search on the road segments according to their weights, and determine the recommended route through the target area based on the search results.

[0181] In this embodiment, if the accessibility detection result of the target area indicates that it is a passable area, a recommended route corresponding to the target area can also be determined. Specifically, in this embodiment, a depth-first search can be performed on each road segment. Depth-First Search (DFS) is an algorithm used to traverse or search a graph. It starts from the root node (or any starting node) and explores each branch as deeply as possible until it can no longer proceed, at which point it backtracks to the previous node and continues to explore other unvisited branches.

[0182] In this embodiment of the application, a road segment can be selected starting from the entrance or exit of the target area, and each road segment can be traversed through a depth-first search until a route from the entrance to the exit is found, which can be determined as the recommended route output.

[0183] Specifically, in this embodiment of the application, when using depth-first search, the weight of each road segment can be determined based on its diversity index. For example, if a road segment has a higher diversity index, it can be assigned a higher weight. During the search traversal, road segments can be selected for priority traversal based on their weights. Since road segments with higher diversity indices correspond to higher weights, these road segments can be traversed first. Moreover, these road segments traverse a wider variety of objects and are more likely to be frequently used, thus improving the efficiency of route recommendation.

[0184] Reference Figure 11 In this embodiment of the application, a regional accessibility detection device is also provided, which includes:

[0185] The query unit 1110 is used to query the road segments contained within the target area;

[0186] Acquisition unit 1120 is used to acquire trajectory information of several objects within the target area;

[0187] The integration unit 1130 is used to determine the target objects passed through each road segment from the objects based on the trajectory information, and obtain the object group corresponding to each road segment; wherein, the object group includes the target objects corresponding to the road segment;

[0188] Processing unit 1140 is used to determine the diversity index of a road segment based on the object group corresponding to the road segment;

[0189] The discrimination unit 1150 is used to determine the accessibility detection result of the target area based on the diversity index of each road segment; wherein, the accessibility detection result is used to characterize whether the target area belongs to the passable area or the target area belongs to the restricted area.

[0190] Optionally, in some embodiments, the acquisition unit is specifically used for:

[0191] Continuously collect the location information of the object within the target area and record the first collection time corresponding to each location information;

[0192] Based on location information and the order of the first data collection time, the trajectory information of the object is determined within the target area.

[0193] Optionally, in some embodiments, the acquisition unit is specifically used for:

[0194] Acquire video data within the target area;

[0195] Target detection is performed based on video data to identify objects that have passed through the target area;

[0196] Based on video data, the object is re-identified to determine its trajectory information within the target area.

[0197] Optionally, in some embodiments, the detection device further includes a deletion unit, which is specifically used for:

[0198] Query the second collection time corresponding to the trajectory information;

[0199] The system checks whether the second data collection time falls within a predetermined period; the predetermined period includes holidays.

[0200] If it is determined that the second data collection time falls within the predetermined period, the trajectory information is deleted.

[0201] Optionally, in some embodiments, the processing unit is specifically used for:

[0202] The number of times each target object in the group passes through a road segment;

[0203] The total number of times each road segment is traversed is determined based on the total number of times all target objects pass through the road segment.

[0204] The probability of occurrence of the target object is determined by the ratio of the number of times the target object passes through the road segment to the total number of times it passes through the road segment.

[0205] The diversity index of road segments is determined based on the occurrence probability of each target object.

[0206] Optionally, in some embodiments, the processing unit is specifically used for:

[0207] Calculate the square of the probability of occurrence of the target object to obtain the first indicator data corresponding to the target object;

[0208] The second indicator data is obtained by summing the first indicator data corresponding to each target object;

[0209] The diversity index of the road segment is obtained based on the difference between the data of indicator 1 and indicator 2.

[0210] Optionally, in some embodiments, the detection device further includes a rejection unit, which is specifically used for:

[0211] Compare the total number of occurrences for each road segment with the frequency threshold;

[0212] If the total number of occurrences for a road segment is less than the threshold, the data for that road segment is removed.

[0213] Optionally, in some embodiments, the discrimination unit is specifically used for:

[0214] The diversity index of each road segment is compared with the preset threshold;

[0215] If the diversity index of all road segments is less than or equal to the preset threshold, the trafficability detection result of the target area is determined to be that the target area belongs to the restricted traffic area.

[0216] Optionally, in some embodiments, the discrimination unit is specifically used for:

[0217] Detect whether the endpoints of the road segment are located at the edge of the target area;

[0218] If the endpoint of a road segment is not located at the edge of the target area, the road segment is identified as the target road segment.

[0219] Compare the diversity index of the target road segment with a preset threshold;

[0220] If the diversity index of the target road segment is greater than the preset threshold, the accessibility detection result of the target area is determined to be that the target area belongs to the passable area.

[0221] Optionally, in some embodiments, the discrimination unit is specifically used for:

[0222] If the accessibility test result of the target area indicates that the target area is a passable area, the weight of each road segment is determined based on the diversity index of each road segment; where the diversity index and the weight are positively correlated.

[0223] Based on the weights, a depth-first search is performed on the road segments, and a recommended route through the target area is determined based on the search results.

[0224] It is understandable that, such as Figure 4 The content of the area accessibility detection method embodiments shown is applicable to the area accessibility detection device embodiments of this invention. The specific functions implemented by the area accessibility detection device embodiments of this invention are the same as those shown in the examples. Figure 4 The method for detecting regional accessibility shown in the embodiment is the same, and the beneficial effects achieved are the same as those described above. Figure 4 The beneficial effects achieved by the illustrated method embodiment for detecting regional accessibility are also the same.

[0225] This application also discloses an electronic device, including:

[0226] At least one processor;

[0227] At least one memory for storing at least one program;

[0228] When at least one program is executed by at least one processor, such that at least one processor implements as Figure 4 The illustrated embodiment of the method for detecting regional accessibility.

[0229] The electronic device in the embodiments of this application may be a terminal device, a computer device, or a server device.

[0230] For example, refer to Figure 12 , Figure 12 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Taking a terminal device as an example, Figure 12In this context, the electronic device 1200 may include an RF (Radio Frequency) circuit 1210, a memory 1220 including one or more computer-readable storage media, an input unit 1230, a display unit 1240, a sensor 1250, an audio circuit 1260, a short-range wireless transmission module 1270, a processor 1280 including one or more processing cores, and a power supply 1290, among other components. Those skilled in the art will understand that... Figure 12 The device structure shown does not constitute a limitation on the terminal device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0231] RF circuit 1210 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and hands it over to one or more processors 1280 for processing; additionally, it transmits uplink data to the base station. Typically, RF circuit 1210 includes, but is not limited to, an antenna, at least one amplifier, a tuner, one or more oscillators, a SIM card, a transceiver, a coupler, an LNA (Low Noise Amplifier), a duplexer, etc. Furthermore, RF circuit 1210 can also communicate wirelessly with networks and other devices. Wireless communication can use any communication standard or protocol, including but not limited to GSM (Global System for Mobile communication), GPRS (General Packet Radio Service), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), LTE (Long Term Evolution), email, SMS (Short Messaging Service), etc.

[0232] Memory 1220 can be used to store software programs and modules (or units). Processor 1280 executes various functional applications and data processing by running the software programs and modules (or units) stored in memory 1220. Memory 1220 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of electronic device 1200 (such as audio data, telephone directory, etc.). Furthermore, memory 1220 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, memory 1220 may also include a memory controller to provide access to memory 1220 for processor 1280 and input unit 1230. Although Figure 12 The RF circuit 1210 is shown, but it is understood that it is not a necessary component of the electronic device 1200 and can be omitted as needed without changing the nature of the invention.

[0233] The input unit 1230 can be used to receive input numerical or character information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to object settings and function control. Specifically, the input unit 1230 may include a touch-sensitive surface 1231 and other input devices 1232. The touch-sensitive surface 1231, also known as a touch display screen or touchpad, can collect touch operations on or near the object (such as operations performed by the object using a finger, stylus, or any suitable object or accessory on or near the touch-sensitive surface 1231), and drive the corresponding connection device according to a pre-set program. Optionally, the touch-sensitive surface 1231 may include two parts: a touch detection device and a touch controller. The touch detection device detects the touch position of the object and detects the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 1280, and can receive and execute instructions from the processor 1280. In addition, the touch-sensitive surface 1231 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. Besides the touch-sensitive surface 1231, the input unit 1230 may also include other input devices 1232. Specifically, other input devices 1232 may include, but are not limited to, one or more of the following: a physical keyboard, function keys (such as volume control buttons, power buttons, etc.), a trackball, a mouse, and a joystick.

[0234] The display unit 1240 can be used to display information input by an object or information provided to an object, as well as various graphical object interfaces for controlling the electronic device 1200. These graphical object interfaces can be composed of graphics, text, icons, video, and any combination thereof. The display unit 1240 may include a display panel 1241, which may optionally be configured as an LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or similar display. Further, a touch-sensitive surface 1231 may cover the display panel 1241. When the touch-sensitive surface 1231 detects a touch operation on or near it, it transmits the information to the processor 1280 to determine the type of touch event. Subsequently, the processor 1280 provides corresponding visual output on the display panel 1241 according to the type of touch event. Although in Figure 12 In this embodiment, the touch-sensitive surface 1231 and the display panel 1241 are implemented as two separate components to realize input and output functions. However, in some embodiments, the touch-sensitive surface 1231 and the display panel 1241 can be integrated to realize input and output functions.

[0235] The electronic device 1200 may also include at least one sensor 1250, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 1241 according to the ambient light level, and the proximity sensor can turn off the display panel 1241 or the backlight when the electronic device 1200 is moved to the ear. As a type of motion sensor, a gravity acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition-related functions (such as pedometers, taps), etc. Other sensors that the electronic device 1200 may also be configured with, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0236] Audio circuitry 1260, speaker 1261, and microphone 1262 provide an audio interface between the device and electronic device 1200. Audio circuitry 1260 converts received audio data into electrical signals and transmits them to speaker 1261, where speaker 1261 converts them into sound signals for output. Conversely, microphone 1262 converts collected sound signals into electrical signals, which are then received by audio circuitry 1260, converted back into audio data, processed by processor 1280, and transmitted via RF circuitry 1210 to another electronic device, or output to memory 1220 for further processing. Audio circuitry 1260 may also include an earphone jack to facilitate communication between external headphones and electronic device 1200.

[0237] The short-range wireless transmission module 1270 can be a WIFI (wireless fidelity) module, Bluetooth module, or infrared module, etc. The electronic device 1200 can transmit information with wireless transmission modules on other devices via the short-range wireless transmission module 1270.

[0238] The processor 1280 is the control center of the electronic device 1200. It connects various parts of the device via various interfaces and lines, and performs various functions and processes data of the electronic device 1200 by running or executing software programs or modules stored in the memory 1220 and calling data stored in the memory 1220, thereby providing overall control of the device. Optionally, the processor 1280 may include one or more processing cores; optionally, the processor 1280 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and application programs, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor 1280.

[0239] Electronic device 1200 also includes a power supply 1290 (such as a battery) for supplying power to various components. Optionally, the power supply 1290 can be logically connected to the processor 1280 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 1290 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0240] Although not shown, the electronic device 1200 may also include a camera, Bluetooth module, etc., which will not be described in detail here.

[0241] This application also discloses a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to implement, for example... Figure 4 The illustrated embodiment of the method for detecting regional accessibility.

[0242] Understandable, Figure 4 The content of the area accessibility detection method embodiments shown is applicable to the embodiments of this computer-readable storage medium. The specific functions implemented by the embodiments of this computer-readable storage medium are the same as those in the embodiments of this computer-readable storage medium. Figure 4 The method for detecting regional accessibility shown in the embodiment is the same, and the beneficial effects achieved are the same. Figure 4 The beneficial effects achieved by the illustrated method embodiment for detecting regional accessibility are also the same.

[0243] This application also discloses a computer program product or computer program, which includes computer instructions stored in the aforementioned computer-readable storage medium. Figure 12 The processor of the illustrated electronic device can read the computer instructions from the aforementioned computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform... Figure 4 The illustrated embodiment of the method for detecting regional accessibility.

[0244] Understandable, Figure 4 The content of the method embodiment for detecting regional accessibility shown is applicable to this computer program product or computer program embodiment. The specific functions implemented by this computer program product or computer program embodiment are the same as those in the embodiment. Figure 4 The method for detecting regional accessibility shown in the embodiment is the same, and the beneficial effects achieved are the same. Figure 4 The beneficial effects achieved by the illustrated method embodiment for detecting regional accessibility are also the same.

[0245] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this application are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0246] Furthermore, although this application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding this application. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional technology for an engineer. Therefore, those skilled in the art can implement the application set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of this application, which is determined by the full scope of the appended claims and their equivalents.

[0247] If a function is implemented as a software functional unit 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 this application, in essence, or the part that contributes to the prior art, or a part of the 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 cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0248] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0249] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0250] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0251] In the foregoing description of this specification, the references to terms such as "one embodiment," "another embodiment," or "some embodiments," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0252] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

[0253] The above is a detailed description of the preferred embodiments of this application, but this application is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A method for detecting regional accessibility, characterized in that, The method includes: Query the road segments contained within the target area; Obtain trajectory information of several objects within the target area; Based on the trajectory information, target objects passed through each road segment are determined from the objects to obtain an object group corresponding to each road segment; wherein, the object group includes the target objects corresponding to the road segment; The diversity index of the road segment is determined based on the object group corresponding to the road segment; Based on the diversity index of each road segment, the accessibility detection result of the target area is determined; wherein, the accessibility detection result is used to characterize whether the target area is a passable area or a restricted area.

2. The method for detecting regional accessibility according to claim 1, characterized in that, Determining the diversity index of the road segment based on the object group corresponding to the road segment includes: Count the number of times each target object in the object group passes through the road segment; The total number of times each of the target objects passes through the road segment is determined based on the sum of the number of times each of the target objects passes through the road segment. The probability of occurrence of the target object is determined based on the ratio of the number of times the target object passes through the road segment to the total number of times it passes through the road segment. The diversity index of the road segment is determined based on the occurrence probability corresponding to each target object.

3. The method for detecting regional traversability according to claim 2, characterized in that, Determining the diversity index of the road segment based on the occurrence probability corresponding to each of the target objects includes: Calculate the square of the occurrence probability corresponding to the target object to obtain the first index data corresponding to the target object; The first indicator data corresponding to each of the target objects is summed to obtain the second indicator data; The diversity index of the road segment is obtained based on the difference between the data of indicator 1 and the second indicator.

4. The method for detecting regional accessibility according to claim 2, characterized in that, The method further includes: Compare the total number of occurrences and the number threshold corresponding to the road segment; If the total number of occurrences for the road segment is less than the threshold number, the data corresponding to the road segment is removed.

5. The method for detecting regional traversability according to claim 1, characterized in that, The step of obtaining trajectory information of several objects within the target area includes: The location information of the object within the target area is continuously collected, and the first collection time corresponding to each location information is recorded; Based on the location information and the order of the first acquisition time, the trajectory information of the object is determined within the target area.

6. The method for detecting regional traversability according to claim 1, characterized in that, The step of obtaining trajectory information of several objects within the target area includes: Acquire video data within the target area; Target detection is performed based on the video data to identify objects that have passed through the target area; Based on the video data, the object is re-identified to determine the object's trajectory information within the target area.

7. The method for detecting regional traversability according to any one of claims 1-6, characterized in that, After obtaining the trajectory information of several objects within the target area, the method further includes: Query the second acquisition time corresponding to the trajectory information; Detect whether the second collection time falls within a predetermined period; wherein, the predetermined period includes holidays; If it is determined that the second collection time falls within the predetermined period, the trajectory information is deleted.

8. The method for detecting regional accessibility according to claim 1, characterized in that, The step of determining the trafficability detection result of the target area based on the diversity index of each road segment includes: The diversity index of each road segment is compared with a preset threshold. If the diversity index of all the road segments is less than or equal to the preset threshold, the accessibility detection result of the target area is determined to be that the target area belongs to the restricted access area.

9. The method for detecting regional traversability according to claim 1, characterized in that, The step of determining the trafficability detection result of the target area based on the diversity index of each road segment includes: Detect whether the endpoint of the road segment is located at the edge of the target area; If the endpoint of the road segment is not located at the edge of the target area, the road segment is identified as the target road segment; The diversity index of the target road segment is compared with a preset threshold; If the diversity index of the target road segment is greater than the preset threshold, the accessibility detection result of the target area is determined to be that the target area belongs to the passable area.

10. The method for detecting regional accessibility according to claim 1, characterized in that, The method further includes: If the accessibility detection result of the target area indicates that the target area is a passable area, the weight of each road segment is determined based on the diversity index of each road segment; wherein, the diversity index and the weight are positively correlated. Based on the weights, a depth-first search is performed on the road segments, and a recommended route through the target area is determined based on the search results.

11. A device for detecting regional accessibility, characterized in that, The device includes: The query unit is used to query road segments contained within a target area; The acquisition unit is used to acquire trajectory information of several objects within the target area; An integration unit is configured to determine, based on the trajectory information, the target objects traversed on each road segment from the objects, thereby obtaining an object group corresponding to each road segment; wherein, the object group includes the target objects corresponding to the road segment; The processing unit is used to determine the diversity index of the road segment based on the object group corresponding to the road segment; The discrimination unit is used to determine the accessibility detection result of the target area based on the diversity index of each road segment; wherein the accessibility detection result is used to characterize whether the target area is a passable area or a restricted area.

12. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the area accessibility detection method according to any one of claims 1 to 10.

13. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the area accessibility detection method according to any one of claims 1 to 10.

14. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the area accessibility detection method according to any one of claims 1 to 10.

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