Method, apparatus, computer device, and storage medium for recognizing state of urban functional area

Abstract

The application relates to a city functional area state identification method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: in response to a state identification request of a to-be-identified city functional area, acquiring a moving object trajectory information set and remote sensing image data; performing trajectory road matching on the moving object trajectory information in the moving object trajectory information set to obtain a trajectory matching road, and performing feature extraction on the moving object trajectory information to obtain moving object trajectory feature information; acquiring road attribute information of the trajectory matching road, obtaining road flow characteristics of different attribute roads according to the road attribute information and the moving object trajectory feature information; obtaining a dynamic identification result according to the road attribute information and the road flow characteristics, and obtaining a static identification result according to the remote sensing image data; and obtaining a state identification result according to the dynamic identification result and the static identification result. The method can realize real-time and accurate city functional area state identification.

Description

Technical Field

[0001] This application relates to the field of big data technology, and in particular to a method, apparatus, computer equipment, and storage medium for identifying the status of urban functional areas. Background Technology

[0002] With the development of computer technology, urban functional zone identification technology has emerged. Urban functional zones refer to the spatial distribution of various functional activities within a city and the corresponding sub-districts. Influenced by numerous factors such as nature, economy, history, and society, they form and develop along with the city's growth. Modern cities, based on the environmental, social, technological, and economic requirements of each function, and to avoid mutual interference between industrial production, transportation, and residents' lives, while also promoting production and environmental protection and the rational use of land and natural conditions, divide the city into several urban functional zones according to certain functions.

[0003] In traditional technologies, the main approach to identifying urban functional zones is to use land use data and urban functional classification systems obtained from remote sensing images, and then use geographic grid systems and functional weights to obtain the current status of urban functional zones.

[0004] However, traditional methods can only statically assess the status of urban functional areas using remote sensing images, lacking real-time accuracy and the ability to accurately determine the status of urban functional areas in real time. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, device, computer equipment, storage medium, and program product for identifying the status of urban functional areas that can achieve real-time and accurate judgment of the status of urban functional areas, in order to address the above-mentioned technical problems.

[0006] A method for identifying the status of urban functional zones, the method comprising:

[0007] In response to the status identification request of the urban functional area to be identified, obtain the set of trajectory information of moving objects corresponding to the urban functional area to be identified and remote sensing image data;

[0008] Trajectory road matching is performed on the trajectory information of moving objects in the trajectory information set to obtain the trajectory matching road, and feature extraction is performed on the trajectory information of moving objects to obtain the trajectory feature information of moving objects;

[0009] Obtain road attribute information of the trajectory matching road, and obtain road traffic flow characteristics of roads with different attributes based on the road attribute information and the trajectory feature information of the moving object;

[0010] Based on road attribute information and road traffic characteristics, the status of the urban functional area to be identified is determined to obtain dynamic identification results. Based on remote sensing image data, the urban functional area to be identified is identified to obtain static identification results.

[0011] The state recognition result is obtained based on the dynamic recognition result and the static recognition result.

[0012] A device for identifying the status of urban functional areas, the device comprising:

[0013] The acquisition module is used to respond to the status recognition request of the urban functional area to be identified, and to acquire the set of trajectory information of moving objects corresponding to the urban functional area to be identified, as well as remote sensing image data.

[0014] The first processing module is used to perform trajectory road matching on the trajectory information of the moving object in the trajectory information set to obtain the trajectory matching road, and to extract features from the trajectory information of the moving object to obtain the trajectory feature information of the moving object.

[0015] The traffic flow feature extraction module is used to obtain road attribute information of the trajectory matching road, and obtain the road traffic flow features of roads with different attributes based on the road attribute information and the trajectory feature information of the moving object.

[0016] The status recognition module is used to determine the status of the urban functional area to be identified based on road attribute information and road traffic characteristics, to obtain dynamic recognition results, and to identify the urban functional area to be identified based on remote sensing image data, to obtain static recognition results.

[0017] The second processing module is used to obtain the state recognition result based on the dynamic recognition result and the static recognition result.

[0018] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps:

[0019] In response to the status identification request of the urban functional area to be identified, obtain the set of trajectory information of moving objects corresponding to the urban functional area to be identified and remote sensing image data;

[0020] Trajectory road matching is performed on the trajectory information of moving objects in the trajectory information set to obtain the trajectory matching road, and feature extraction is performed on the trajectory information of moving objects to obtain the trajectory feature information of moving objects;

[0021] Obtain road attribute information of the trajectory matching road, and obtain road traffic flow characteristics of roads with different attributes based on the road attribute information and the trajectory feature information of the moving object;

[0022] Based on road attribute information and road traffic characteristics, the status of the urban functional area to be identified is determined to obtain dynamic identification results. Based on remote sensing image data, the urban functional area to be identified is identified to obtain static identification results.

[0023] The state recognition result is obtained based on the dynamic recognition result and the static recognition result.

[0024] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0025] In response to the status identification request of the urban functional area to be identified, obtain the set of trajectory information of moving objects corresponding to the urban functional area to be identified and remote sensing image data;

[0026] Trajectory road matching is performed on the trajectory information of moving objects in the trajectory information set to obtain the trajectory matching road, and feature extraction is performed on the trajectory information of moving objects to obtain the trajectory feature information of moving objects;

[0027] Obtain road attribute information of the trajectory matching road, and obtain road traffic flow characteristics of roads with different attributes based on the road attribute information and the trajectory feature information of the moving object;

[0028] Based on road attribute information and road traffic characteristics, the status of the urban functional area to be identified is determined to obtain dynamic identification results. Based on remote sensing image data, the urban functional area to be identified is identified to obtain static identification results.

[0029] The state recognition result is obtained based on the dynamic recognition result and the static recognition result.

[0030] A computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0031] In response to the status identification request of the urban functional area to be identified, obtain the set of trajectory information of moving objects corresponding to the urban functional area to be identified and remote sensing image data;

[0032] Trajectory road matching is performed on the trajectory information of moving objects in the trajectory information set to obtain the trajectory matching road, and feature extraction is performed on the trajectory information of moving objects to obtain the trajectory feature information of moving objects;

[0033] Obtain road attribute information of the trajectory matching road, and obtain road traffic flow characteristics of roads with different attributes based on the road attribute information and the trajectory feature information of the moving object;

[0034] Based on road attribute information and road traffic characteristics, the status of the urban functional area to be identified is determined to obtain dynamic identification results. Based on remote sensing image data, the urban functional area to be identified is identified to obtain static identification results.

[0035] The state recognition result is obtained based on the dynamic recognition result and the static recognition result.

[0036] The aforementioned urban functional area status identification method, device, computer equipment, storage medium, and program product, in response to a status identification request for the urban functional area to be identified, acquire a set of moving object trajectory information corresponding to the urban functional area to be identified, as well as remote sensing image data. They perform trajectory road matching on the moving object trajectory information in the set of moving object trajectory information to obtain the trajectory-matching roads. By extracting features from the moving object trajectory information, they obtain the moving object trajectory feature information. Based on the road attribute information of the trajectory-matching roads, and according to the road attribute information and the moving object trajectory feature information, they obtain the road flow characteristics of roads with different attributes. Furthermore, based on the road attribute information and road flow characteristics, they determine the status of the urban functional area to be identified, obtaining a dynamic identification result. By identifying the urban functional area to be identified based on the remote sensing image data, they obtain a static identification result. Therefore, by combining the dynamic and static identification results, they obtain the status identification result, achieving real-time and accurate urban functional area status identification. Attached Figure Description

[0037] Figure 1 This is an application environment diagram of the urban functional area status identification method in one embodiment;

[0038] Figure 2 This is a flowchart illustrating a method for identifying the status of urban functional areas in one embodiment;

[0039] Figure 3 This is a schematic diagram of trajectory road matching in one embodiment;

[0040] Figure 4 This is an application scenario diagram of the urban functional area status recognition method in one embodiment;

[0041] Figure 5 This is a schematic diagram illustrating the service area status determination in one embodiment;

[0042] Figure 6 This is a flowchart illustrating the urban functional area status identification method in another embodiment;

[0043] Figure 7 This is a structural block diagram of an urban functional area status identification device in one embodiment;

[0044] Figure 8This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0045] 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.

[0046] The urban functional zone status identification method provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on another network server. When a user needs to determine the status of a city functional area to be identified, they send a status identification request for the city functional area to be identified to server 104 via terminal 102. Server 104 responds to the status identification request by obtaining a set of motion object trajectory information corresponding to the city functional area to be identified, as well as remote sensing image data. It performs trajectory-road matching on the motion object trajectory information in the set of motion object trajectory information to obtain the matching road, extracts features from the motion object trajectory information to obtain the motion object trajectory feature information, obtains the road attribute information of the matching road, and obtains the road traffic characteristics of roads with different attributes based on the road attribute information and the motion object trajectory feature information. Based on the road attribute information and the road traffic characteristics, it determines the status of the city functional area to be identified, obtaining a dynamic identification result. It then performs functional area identification on the city functional area to be identified based on the remote sensing image data, obtaining a static identification result. Based on the dynamic and static identification results, it obtains the status identification result and pushes the status identification result to terminal 102. Terminal 102 includes, but is not limited to, mobile phones, computers, smart voice interaction devices, smart home appliances, and vehicle terminals. Server 104 can be implemented using a standalone server, a server cluster consisting of multiple servers, or a node on a blockchain.

[0047] In one embodiment, such as Figure 2 As shown, a method for identifying the status of urban functional areas is provided, and this method is applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0048] Step 202: In response to the status recognition request of the urban functional area to be identified, obtain the set of trajectory information of moving objects corresponding to the urban functional area to be identified and remote sensing image data.

[0049] Among them, the urban functional areas to be identified refer to urban functional areas that require status identification. For example, the urban functional areas to be identified can specifically refer to service areas that require status identification. Status identification refers to confirming the current status of the urban functional areas to be identified, which can be one of the following: open, closed, or newly built. Open means that the urban functional area has gone from being unusable to being usable; closed means that the urban functional area has gone from being usable to being unusable; and newly built means that the urban functional area has gone from non-existent to being established.

[0050] The set of trajectory information of moving objects corresponding to the urban functional area to be identified refers to the set of trajectory information of moving objects within the area to be identified. The location of the area to be identified corresponds to the location of the urban functional area to be identified. When the location of the urban functional area to be identified is the entire administrative region, the area to be identified is that administrative region. When the location of the urban functional area to be identified is a specific location of a single urban functional area, the area to be identified is the area within the preset radiation range corresponding to that single urban functional area location. The preset radiation range can be set as needed, for example, the preset radiation range can be ten kilometers, twenty kilometers, etc.

[0051] In this context, "moving object" refers to a specific movable object corresponding to the urban functional area to be identified. Specifically, a moving object can refer to at least one of a user-driven vehicle, an autonomous vehicle, or a remotely controlled moving object. "Moving object trajectory information" refers to the trajectory information generated by the moving object during its movement. For example, moving object trajectory information can specifically refer to trajectory point data generated by a user-driven vehicle during its journey, uploaded to the server via an application. This includes trajectory point location, trajectory point speed, and trajectory point angle. The trajectory point location can specifically refer to the latitude and longitude of the trajectory point, the trajectory point speed is the vehicle's speed at the trajectory point, and the trajectory point angle is the angle between the current trajectory point and the next trajectory point. When determining the trajectory point angle, the direction with an angle of 0 needs to be pre-specified; for example, true north can be pre-specified as the direction with an angle of 0. For example, trajectory point data can specifically refer to GPS (Global Positioning System) point data. It should be noted that the application in this embodiment refers to an application that the moving object may use during its movement; for example, an application specifically refers to a navigation application. "Remote sensing image data" refers to film or photographs that record the electromagnetic wave magnitudes of various ground features.

[0052] Specifically, when a user needs to confirm the status of a city functional area to be identified, the user will send a status identification request for the city functional area to be identified to the server through the terminal. The server responds to the status identification request for the city functional area to be identified, determines the area to be identified based on the location of the city functional area to be identified, and obtains a set of trajectory information of moving objects within the area to be identified.

[0053] Simultaneously, the server will retrieve the remote sensing image data corresponding to the urban functional area to be identified from the database containing remote sensing images, based on the location of the functional area to be identified. The database contains remote sensing images and the image coordinates corresponding to the remote sensing images. When remote sensing image data is needed, the server will match the location of the functional area to be identified with the image coordinates corresponding to the remote sensing images to determine the area to be identified and retrieve the remote sensing image corresponding to the area to be identified as the remote sensing image data corresponding to the urban functional area to be identified.

[0054] Step 204: Perform trajectory road matching on the trajectory information of the moving object in the trajectory information set to obtain the trajectory matching road, and extract features from the trajectory information of the moving object to obtain the trajectory feature information of the moving object.

[0055] Trajectory-road matching refers to accurately matching the trajectory of a moving object to an actual road based on its trajectory information. The matched road is the road that matches the trajectory information of the moving object. The trajectory feature information of the moving object refers to information used to describe the characteristics of its trajectory. For example, the trajectory feature information may specifically include average speed, angle change, dwell time, and travel time. Angle change refers to the average angle change of trajectory points along a road; dwell time refers to the duration for which the speed is below a preset dwell speed threshold; and travel time refers to the time spent traversing a road. The preset dwell speed threshold can be set as needed; for example, a preset dwell speed threshold could be 5 km / h.

[0056] Specifically, the trajectory information of a moving object is a collection of trajectory point data. When performing trajectory road matching, the server determines the trajectory points to be matched corresponding to the trajectory information of the moving object based on the trajectory information of the moving object in the collection of trajectory information, and obtains map road data. The map road data is used to perform road matching on the trajectory points to be matched, matching the trajectory points to be matched to the roads, and obtaining the matching roads corresponding to the trajectory points to be matched. Then, all the matching roads corresponding to the trajectory points to be matched are collected to obtain the trajectory matching roads corresponding to the trajectory information of the moving object.

[0057] Specifically, while performing trajectory and road matching, the server calculates the corresponding average speed, angle change, dwell time, and travel time based on the trajectory point position, velocity, and angle of the trajectory point in the trajectory information of the moving object. The average speed, angle change, dwell time, and travel time are then used as the trajectory feature information of the moving object.

[0058] Step 206: Obtain road attribute information of the trajectory matching road, and obtain road flow characteristics of roads with different attributes based on the road attribute information and the trajectory feature information of the moving object.

[0059] The road attribute information describes the properties of the trajectory-matched road. These are inherent attributes of the trajectory-matched road itself, including road type, road function attributes, and topology attributes. The road type can specifically be at least one of the following: expressway, national highway, provincial highway, etc. The road function attribute can specifically be at least one of the following: urban functional area connecting road, toll station, etc. The topology attribute describes the connection relationship between the trajectory-matched road and other roads. For example, when the trajectory-matched road is an expressway, the topology attribute can specifically refer to the connection relationship between this expressway and other expressways, urban functional area connecting roads, toll stations, etc. Urban functional area connecting roads refer to roads leading into urban functional areas.

[0060] Among these, roads with different attributes refer to roads that possess different attributes. For example, highways and roads connecting urban functional areas are roads with different attributes. Road flow characteristics refer to the features used to describe the trajectory flow on a road. For example, road flow characteristics can specifically refer to the number of trajectories entering urban functional areas, the number of trajectories not entering urban functional areas, and the total number of trajectories entering the road.

[0061] Specifically, after obtaining the trajectory-matched road, the server acquires the road attribute information of the matched road. Using this road attribute information and the trajectory feature information of the moving object, the server classifies the moving object's trajectory, determines its category, and statistically analyzes the classification results to obtain the road traffic characteristics of roads with different attributes. Specifically, when classifying the moving object's trajectory using road attribute information and trajectory feature information, the trajectory can be divided into trajectories entering urban functional areas and trajectories not entering urban functional areas. By analyzing whether the moving object's trajectory has entered an urban functional area, the server can use the moving object's trajectory to achieve real-time judgment of the status of urban functional areas.

[0062] Step 208: Based on road attribute information and road traffic characteristics, determine the status of the urban functional area to be identified to obtain dynamic identification results, and perform functional area identification based on remote sensing image data to obtain static identification results.

[0063] Specifically, the conditions for judging the status of urban functional zones are different for roads with different attributes. Therefore, the server needs to first determine the conditions for judging the status of urban functional zones corresponding to different road attributes based on the road attribute information. Then, based on the conditions for judging the status of urban functional zones and the road traffic characteristics, it calculates the urban functional zone status judgment value corresponding to the conditions for judging the status of urban functional zones. By comparing the conditions for judging the status of urban functional zones and the urban functional zone status judgment value, the status judgment result corresponding to different road attributes is obtained. Using the status judgment result, the status of the urban functional zone to be identified is determined, and a dynamic identification result is obtained.

[0064] Specifically, the server extracts features from the remote sensing image data to obtain remote sensing feature information. This feature information is then used to identify the functional zones of the city to be identified, resulting in a static identification result. This static identification result includes the existence of functional zones and, if present, their corresponding functional zone types. Further, the server pre-trains a functional zone identification model. By inputting the remote sensing image data into this pre-trained model, the static identification result can be obtained. This pre-trained model is based on training remote sensing image data with functional zone labels used to distinguish different functional zone types.

[0065] Step 210: Obtain the state recognition result based on the dynamic recognition result and the static recognition result.

[0066] Specifically, dynamic recognition results correspond to static recognition results. Each dynamic recognition result has a corresponding target static recognition result. The server determines the corresponding target static recognition result based on the dynamic recognition result and compares whether the target static recognition result is consistent with the static recognition result. This allows the static recognition result to be used to assist in judging whether the dynamic recognition result is accurate. When the target static recognition result is consistent with the static recognition result, it means that the dynamic recognition result is accurate, and the server can directly use the dynamic recognition result as the status recognition result. When the target static recognition result is inconsistent with the static recognition result, it means that the dynamic recognition result may be incorrect, and the server will use the static recognition result as the status recognition result.

[0067] Specifically, the dynamic identification result can indicate whether the urban functional area to be identified is open, closed, or newly built. When the urban functional area to be identified is open or newly built, it indicates that a functional area exists there, and the corresponding target static identification result should be "functional area exists." When the urban functional area to be identified is closed, it indicates that a functional area does not exist there, and the corresponding target static identification result should be "functional area does not exist." Furthermore, when it is necessary to identify the status of a specific type of functional area, the target static identification result will also include the specific functional area type. When the server compares the target static identification result with the static identification result for consistency, if both the target static identification result and the static identification result indicate the existence of a functional area, it is also necessary to compare whether the specific functional area type in the target static identification result is consistent with the functional area type in the static identification result. Only when the specific functional area type and the functional area type are consistent can the target static identification result be considered consistent with the static identification result. For example, when the target static identification result indicates the existence of a functional area and the functional area is a service area, and the static identification result indicates the existence of a functional area and the functional area is a residential area, the target static identification result and the static identification result are inconsistent.

[0068] The aforementioned urban functional area status identification method, in response to a status identification request for the urban functional area to be identified, acquires a set of moving object trajectory information and remote sensing image data. It performs trajectory-road matching on the moving object trajectory information in the set to obtain matching roads. By extracting features from the moving object trajectory information, it obtains the moving object trajectory feature information. Based on the road attribute information of the matching roads, and according to the road attribute information and the moving object trajectory feature information, it obtains the road flow characteristics of roads with different attributes. Then, based on the road attribute information and road flow characteristics, it determines the status of the urban functional area to be identified, obtaining a dynamic identification result. By identifying the urban functional area to be identified based on the remote sensing image data, it obtains a static identification result. Therefore, by combining the dynamic and static identification results, it obtains the status identification result, achieving real-time and accurate urban functional area status identification.

[0069] In one embodiment, trajectory path matching is performed on the trajectory information of moving objects in the set of moving object trajectory information to obtain the trajectory matching path, including:

[0070] Based on the trajectory information of the moving object in the trajectory information set, determine the corresponding trajectory points to be matched, and obtain map road data;

[0071] Based on the map road data, road matching is performed on the trajectory points to be matched to obtain the trajectory matching road.

[0072] Map road data refers to data that describes the characteristics of each actual road, including its location and direction.

[0073] Specifically, the server will take the trajectory points included in the trajectory information of the moving object in the set of moving object trajectory information as the trajectory points to be matched with the trajectory information of the moving object, obtain map road data, mark the positions of the trajectory points to be matched on the map road data, use the map road data and the positions of the trajectory points to be matched to determine the candidate matching roads corresponding to the trajectory points to be matched, perform road matching between the candidate matching roads and the trajectory points to be matched to determine the matching roads corresponding to the trajectory points to be matched, and then collect all the matching roads corresponding to the trajectory points to be matched to obtain the trajectory matching roads corresponding to the trajectory information of the moving object.

[0074] In this embodiment, by determining the corresponding trajectory point to be matched based on the trajectory information of the moving object in the trajectory information set, and obtaining map road data, the road matching of the trajectory point to be matched can be performed using the map road data, thereby realizing the determination of the road for trajectory matching.

[0075] In one embodiment, based on map road data, road matching is performed on the trajectory points to be matched to obtain the trajectory matching roads, including:

[0076] Based on map road data, candidate matching roads corresponding to the trajectory points to be matched are determined;

[0077] Calculate the road distance and road angle between the trajectory point to be matched and the candidate matching road, respectively;

[0078] The road matching degree between the trajectory point to be matched and the candidate matching road is determined based on the road distance and the road angle.

[0079] Based on the road matching degree, the trajectory matching road is obtained.

[0080] Here, road distance refers to the distance from the trajectory point to be matched to the candidate matching road. Road angle refers to the minimum angle between the trajectory extension line corresponding to the trajectory point to be matched and the candidate matching road. The trajectory extension line is the extension line obtained by connecting the trajectory point to be matched with the trajectory point at the next time step. Road matching degree is used to describe the degree of matching between the trajectory point to be matched and the candidate matching road.

[0081] Specifically, the server marks the location of the trajectory point to be matched on the map road data. Based on the location of the trajectory point, it determines the actual roads near the trajectory point on the map road data. These actual roads are then used as candidate matching roads corresponding to the trajectory point. Next, based on the locations of the trajectory point and the candidate matching roads, the road distance between the trajectory point and the candidate matching roads is determined. Finally, based on the trajectory extension of the trajectory point and the actual direction of the candidate matching roads, the road angle between the trajectory point and the candidate matching roads is determined. Based on the road distance and the road angle, a weighted calculation of the road matching degree between the trajectory point and the candidate matching roads is performed. The candidate matching road with the maximum road matching degree is determined as the matching road corresponding to the trajectory point. All matching roads corresponding to the trajectory point are then aggregated to obtain the trajectory matching road corresponding to the trajectory information of the moving object. The actual roads near the trajectory point on the map road data refer to actual roads whose distance from the trajectory point is within a preset distance threshold range. The preset distance threshold can be set as needed.

[0082] Specifically, the server can use a pre-set weighted calculation formula to calculate the road matching degree between the trajectory point to be matched and the candidate matching roads. The pre-set weighted calculation formula can be customized as needed. For example, a pre-set weighted calculation formula could be Y = w1*d + w2*cos(a), where Y is the road matching degree, w1 and w2 are weight coefficients, d is the road distance, and a is the road angle. For example... Figure 3 As shown, for a trajectory point p to be matched, the actual roads near it on the map road data are l1 and l2. The server will determine that l1 and l2 are both candidate matching roads corresponding to the trajectory point p. The road distance d1 and road angle a1 between the trajectory point p and the candidate matching road l1 are calculated respectively, and the road distance d2 and road angle a2 between the trajectory point p and the candidate matching road l2 are calculated respectively. Based on the road distance and road angle, the road matching degree Y1 between the trajectory point p and the candidate matching road l1 and the road matching degree Y2 between the trajectory point p and the candidate matching road l2 are calculated by weight. By comparing the road matching degree Y1 and the road matching degree Y2, the matching road corresponding to the trajectory point p is determined to be l2.

[0083] In this embodiment, by determining candidate matching roads corresponding to the trajectory point to be matched based on map road data, the road distance and road angle between the trajectory point to be matched and the candidate matching roads are calculated respectively. The road matching degree between the trajectory point to be matched and the candidate matching roads can be determined by using the road distance and road angle, so that the trajectory matching road can be determined based on the road matching degree.

[0084] In one embodiment, the road traffic flow characteristics of roads with different attributes are obtained based on road attribute information and moving object trajectory feature information, including:

[0085] The trajectories of moving objects are classified based on road attribute information and trajectory feature information.

[0086] Based on the classification results, the number of trajectories entering urban functional areas, the number of trajectories not entering urban functional areas, and the total number of trajectories entering roads corresponding to different road attributes are counted.

[0087] Based on the number of trajectories entering urban functional areas, the number of trajectories not entering urban functional areas, and the total number of trajectories entering roads, the road flow characteristics of roads with different attributes are obtained.

[0088] Classifying the trajectory of a moving object refers to determining the category of the trajectory. Specifically, the categories of the trajectory of a moving object can be such as trajectories entering urban functional areas or trajectories not entering urban functional areas.

[0089] Specifically, based on different road attribute information, the server will use different trajectory classification conditions for different attribute roads to classify the trajectory of moving objects. After obtaining the classification results, the server will count the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road for different attribute roads. The number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road will be used as the road traffic characteristics of different attribute roads.

[0090] The different road attributes include highways and urban functional area connecting roads. When the trajectory matching road is a highway, since the trajectory matching road itself does not have urban functional area connecting roads, it is impossible to determine whether the trajectory of the moving object is a trajectory entering an urban functional area based on the road attributes. On highways, vehicles rarely make large changes in driving direction and rarely travel at low speeds. Therefore, when these phenomena occur, there may be an urban functional area on this highway. Therefore, for highways, the server uses trajectory classification conditions to determine whether the angle change is greater than a preset angle change threshold, whether the ratio of dwell time to travel time is greater than a preset time ratio threshold, and whether the dwell time is greater than a preset dwell time threshold. When the angle change is greater than the preset angle change threshold, the ratio of dwell time to travel time is greater than the preset time ratio threshold, and the dwell time is greater than the preset dwell time threshold, the server will classify the trajectory of the moving object as a trajectory entering an urban functional area; otherwise, it is a trajectory not entering an urban functional area. The preset angle change threshold, preset time ratio threshold, and preset dwell time threshold can be set as needed.

[0091] In this scenario, when the matched trajectory is a connecting road to an urban functional area, theoretically, it means the moving object can only travel within that area. However, due to trajectory reporting errors and inherent errors in the trajectory matching process, the moving object may not have actually traveled to the connecting road. Therefore, it's necessary to determine whether the moving object's trajectory indicates it has entered the urban functional area. The server uses the following trajectory classification criteria: whether the average speed is less than a preset average speed threshold and whether the dwell time is greater than a preset dwell time threshold. If the average speed is less than the preset average speed threshold and the dwell time is greater than the preset dwell time threshold, the server will classify the moving object's trajectory as a trajectory indicating it has entered the urban functional area; otherwise, it is classified as a trajectory indicating it has not entered the urban functional area. The preset average speed threshold can be set as needed.

[0092] The number of trajectories entering urban functional areas and non-entering urban functional areas corresponding to roads with different attributes can be obtained directly from the classification results of roads with different attributes. The total number of trajectories entering roads corresponding to roads with different attributes refers to the sum of the number of trajectories of moving objects on all roads with different attributes, which can be obtained by superimposing the number of trajectories of moving objects on roads with different attributes.

[0093] In this embodiment, the trajectory of the moving object is classified according to the road attribute information and the trajectory feature information of the moving object. Based on the classification results, the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road corresponding to different attribute roads are counted. Based on the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road, the road traffic characteristics of roads with different attributes can be obtained.

[0094] In one embodiment, the state of the urban functional area to be identified is determined based on road attribute information and road traffic flow characteristics, and the dynamic identification result includes:

[0095] Based on road attribute information, determine the urban functional area status judgment conditions corresponding to roads with different attributes, and obtain the status judgment results corresponding to roads with different attributes based on the urban functional area status judgment conditions and road traffic characteristics.

[0096] Based on the state judgment result, the dynamic recognition result is obtained.

[0097] Specifically, the urban functional area status judgment conditions adopted for roads with different attributes are not the same. Therefore, the server needs to first determine the urban functional area status judgment conditions corresponding to different attribute roads based on the road attribute information, and then calculate the urban functional area status judgment value corresponding to the urban functional area status judgment conditions based on the urban functional area status judgment conditions and road traffic characteristics. By comparing the urban functional area status judgment conditions and the urban functional area status judgment value, the status judgment result corresponding to different attribute roads is obtained. The dynamic recognition result is obtained by combining the status judgment results.

[0098] Among them, roads with different attributes include expressways and urban functional area connecting roads. For expressways, if there is no topological relationship between them and urban functional area connecting roads, it means that there was originally no urban functional area on this expressway, and it is necessary to determine whether there is an urban functional area. The corresponding status judgment result can be that the urban functional area is newly established or does not exist. For urban functional area connecting roads, they are connected to urban functional areas, and it is only necessary to determine the status of the urban functional area they are connected to. The corresponding status judgment result can be that the urban functional area is open or closed.

[0099] In this embodiment, by determining the urban functional area status judgment conditions corresponding to roads with different attributes based on road attribute information, the status judgment results corresponding to roads with different attributes can be obtained based on the urban functional area status judgment conditions and road traffic characteristics, thereby obtaining dynamic recognition results based on the status judgment results.

[0100] In one embodiment, roads with different attributes include highways;

[0101] Based on road attribute information, the conditions for judging the status of urban functional zones corresponding to roads with different attributes are determined. Based on the conditions for judging the status of urban functional zones and road traffic characteristics, the status judgment results corresponding to roads with different attributes are obtained, including:

[0102] When the road attribute information is a highway and there is no topological connection relationship with the urban functional area connecting road, determine the first state judgment condition corresponding to the highway.

[0103] Based on the road traffic characteristics corresponding to the expressway, calculate the first state judgment value corresponding to the first state judgment condition;

[0104] When the first state judgment value meets the first state judgment condition, the state judgment result corresponding to the expressway is determined to be the construction of a new urban functional area.

[0105] Specifically, when the road attribute information is a highway and there is no topological connection relationship with the road connecting to the urban functional area, it means that there was originally no urban functional area on this highway. The server needs to determine whether there is an urban functional area on the highway at this time. At this time, the server will obtain the first state judgment condition corresponding to the highway, that is, the condition for judging whether the urban functional area exists. Based on the road traffic characteristics corresponding to the highway, the server will calculate the first state judgment value corresponding to the first state judgment condition and compare the first state judgment value with the first state judgment condition. When the first state judgment value reaches the first state judgment condition, it indicates that some moving objects have the characteristic of entering the urban functional area, indicating that there may be a newly built urban functional area here. The server will determine the state judgment result corresponding to the highway as the newly built urban functional area.

[0106] The first state judgment condition is used to determine whether an urban functional area exists. It can be set as needed. For example, the first state judgment condition can be that the ratio of the number of trajectories corresponding to highways entering urban functional areas to the total number of trajectories corresponding to urban functional areas is greater than a preset first threshold. The total number of trajectories corresponding to urban functional areas is the sum of the number of trajectories entering urban functional areas and the number of trajectories not entering urban functional areas. The preset first threshold can be set as needed. For example, the preset first threshold can be 0.1.

[0107] In this embodiment, by determining the first state judgment condition corresponding to the highway, and calculating the first state judgment value corresponding to the first state judgment condition based on the road traffic characteristics corresponding to the highway, the determination of the state judgment result corresponding to the highway can be achieved by using the first state judgment condition and the first state judgment value.

[0108] In one embodiment, roads with different attributes include urban functional area connecting roads;

[0109] Based on road attribute information, the conditions for judging the status of urban functional zones corresponding to roads with different attributes are determined. Based on the conditions for judging the status of urban functional zones and road traffic characteristics, the status judgment results corresponding to roads with different attributes are obtained, including:

[0110] When the road attribute information is a connecting road of urban functional area, determine the second state judgment condition corresponding to the connecting road of urban functional area.

[0111] Based on the road traffic characteristics corresponding to the roads connecting to urban functional areas, calculate the second state judgment value corresponding to the second state judgment condition;

[0112] Based on the second state judgment condition and the second state judgment value, the state judgment result corresponding to the road connecting the urban functional area is obtained.

[0113] The second state judgment condition refers to the conditions used to determine whether an urban functional area is open or closed. Different specific conditions are typically used to determine whether an urban functional area is open or closed. That is, the second state judgment condition includes conditions for determining whether an urban functional area is open and conditions for determining whether it is closed. The second state judgment value refers to the value calculated based on the second state judgment condition to determine the state of the urban functional area. Corresponding to the second state judgment condition, the second state judgment value includes a value for determining whether an urban functional area is open and a value for determining whether it is closed. The value for determining whether an urban functional area is open can be obtained from the conditions for determining whether it is open, and the value for determining whether it is closed can be obtained from the conditions for determining whether it is closed.

[0114] Specifically, when the road attribute information is a connecting road to an urban functional area, since the connecting road itself connects to an urban functional area, it is only necessary to determine whether the connected urban functional area is open or closed. In this case, the server will obtain the second state judgment conditions corresponding to the connecting road. These second state judgment conditions include conditions for determining whether the urban functional area is open and closed. After obtaining the second state judgment conditions, the server will calculate the second state judgment value corresponding to each judgment condition based on the road traffic characteristics corresponding to the connecting road. It will then compare each judgment condition with its corresponding second state judgment value, and based on the comparison result, obtain the state judgment result corresponding to the connecting road to the urban functional area.

[0115] The second state judgment condition includes the urban functional area opening judgment condition. The server calculates the urban functional area opening judgment value based on the urban functional area opening judgment condition and the road traffic characteristics corresponding to the connecting roads to the urban functional areas. If the urban functional area opening judgment value meets the urban functional area opening judgment condition, the state judgment result corresponding to the connecting road to the urban functional area is considered that the urban functional area is open. The urban functional area opening judgment condition can be set as needed. For example, the specific urban functional area opening judgment condition can be that the number of trajectories entering the urban functional area corresponding to the connecting road to the service area is greater than a preset second threshold, and the ratio of the number of trajectories entering the urban functional area corresponding to the connecting road to the service area to the total number of corresponding trajectories in the urban functional area is greater than a preset third threshold. The total number of corresponding trajectories in the urban functional area is the sum of the number of trajectories entering the urban functional area and the number of trajectories not entering the urban functional area. The preset second threshold can be set as needed; for example, it can be 5. The preset third threshold can also be set as needed; for example, it can be 0.2.

[0116] The second state judgment condition includes the urban functional area closure judgment condition. The server calculates the urban functional area closure judgment value based on the urban functional area closure judgment condition and the road traffic characteristics corresponding to the connecting roads to the urban functional areas. If the urban functional area closure judgment value meets the urban functional area closure judgment condition, the state judgment result corresponding to the connecting road to the urban functional area is considered that the urban functional area is closed. The urban functional area closure judgment condition can be set as needed. For example, the specific urban functional area closure judgment condition can be that the number of trajectories entering the urban functional area corresponding to the connecting road to the service area is less than a preset fourth threshold, and the ratio of the total number of trajectories entering the service area to the total number of trajectories corresponding to the urban functional area corresponding to the connecting road to the service area is greater than a preset fifth threshold. The total number of trajectories corresponding to the urban functional area is the sum of the number of trajectories entering the urban functional area and the number of trajectories not entering the urban functional area. The preset fourth threshold can be set as needed; for example, it can be 2. The preset fifth threshold can also be set as needed; for example, it can be 5.

[0117] In this embodiment, by determining the second state judgment condition corresponding to the road connecting to the urban functional area, and calculating the second state judgment value corresponding to the second state judgment condition based on the road traffic characteristics corresponding to the road connecting to the urban functional area, the state judgment result corresponding to the road connecting to the urban functional area can be determined based on the second state judgment condition and the second state judgment value.

[0118] This application also provides an application scenario, such as Figure 4As shown, taking a service area as a specific urban functional area as an example, this application scenario utilizes the aforementioned urban functional area status identification method. Specifically, the application of this urban functional area status identification method in this scenario is as follows:

[0119] When a user needs to determine the status of a service area to be identified, they send a status identification request for the service area to be identified to the server via their terminal. The server responds to the request by acquiring a set of moving object trajectory information and remote sensing image data. Based on the moving object trajectory information in the set, it determines the corresponding GPS trajectory point to be matched and acquires map road data. Based on the map road data, it determines candidate matching roads corresponding to the GPS trajectory point to be matched, calculates the road distance and road angle between the GPS trajectory point to be matched and the candidate matching roads, and determines the road matching degree between the GPS trajectory point to be matched and the candidate matching roads based on the road distance and road angle. Based on the road matching degree, the matching road is obtained. Simultaneously, the server extracts features from the moving object trajectory information and calculates the moving object trajectory feature information, including average speed, angle change, dwell time, and travel time.

[0120] After obtaining the trajectory matching road and moving object trajectory feature information, the server acquires the road attribute information of the trajectory matching road, including service area connecting roads and highways. For service area connecting roads, the server classifies the corresponding moving object trajectory using average speed and dwell time. If the average speed is below 50 km / h and the dwell time is greater than five minutes, the moving object trajectory is considered to be entering a service area; otherwise, it is considered to be not entering a service area. For highways, the server classifies the corresponding moving object trajectory using angle change, dwell time, and the ratio of dwell time to travel time. If the angle change is greater than 30 degrees, the ratio of dwell time to travel time is greater than 0.3, and the dwell time is greater than five minutes, the moving object trajectory is considered to be entering a service area; otherwise, it is considered to be not entering a service area. After classification, the server will count the number of service area entry trajectories, the number of non-service area entry trajectories, and the total number of entry road trajectories for roads with different attributes, based on the classification results. The road traffic characteristics for roads with different attributes are then obtained based on these statistics. These different attribute roads include highways and service area connecting roads.

[0121] After obtaining road traffic flow characteristics, the server will determine the service area status based on the road traffic flow characteristics and road attribute information to obtain dynamic identification results. The specific judgment process can be described as follows: Figure 5 As shown.

[0122] When the road attribute information is a highway and there is no topological relationship with the road connecting to the service area, it means that there was no service area here originally. The server needs to determine whether a new service area has been built here. At this time, the server will first calculate the sum of the number of trajectories entering the service area and the number of trajectories not entering the service area, that is, the total number of trajectories corresponding to the urban functional area. Then, it will calculate the ratio of the number of trajectories entering the service area to the total number of trajectories corresponding to the urban functional area. When the ratio is greater than the preset first threshold, the status judgment result corresponding to the highway is determined to be that the service area has been built.

[0123] When the road attribute information is a service area connecting road, it indicates the existence of a corresponding service area. The server needs to determine the status of this service area. First, the server calculates the sum of the number of trajectories entering the service area and the number of trajectories not entering the service area, i.e., the total number of trajectories corresponding to urban functional areas. Then, it calculates a first ratio of the number of trajectories entering the service area to the total number of trajectories corresponding to urban functional areas, and a second ratio of the total number of trajectories entering the service area to the total number of trajectories corresponding to urban functional areas. When the number of trajectories entering the service area is greater than a preset second threshold, and the first ratio is greater than a preset third threshold, the status of the road corresponding to the service area connecting road is determined to be that the service area is open. When the number of trajectories entering the service area is less than a preset fourth threshold, and the second ratio is greater than a preset fifth threshold, the status of the road corresponding to the service area connecting road is determined to be that the service area is closed. It should be noted that when an urban functional area is a service area, the total number of trajectories entering the service area is the sum of the total number of trajectories on the highway and the total number of trajectories on the service area connecting road.

[0124] While obtaining the dynamic recognition results, the server will also perform functional area recognition on the urban functional areas to be identified based on the remote sensing image data to obtain static recognition results. Thus, the state recognition results can be obtained based on the dynamic and static recognition results.

[0125] Traditional technologies, relying solely on static assessments of remote sensing imagery, suffer from insufficient real-time performance and are primarily designed for identifying various types of urban functional zones, lacking specificity. In contrast, the urban functional zone status recognition method of this application, when applied to service area status recognition, can rapidly provide service area status changes by real-time analysis of moving object trajectory information, exhibiting high real-time performance. Furthermore, it achieves more accurate judgments specific to the service area scenario. By combining the static recognition results obtained from remote sensing imagery data for functional zone identification, real-time and accurate urban functional zone status recognition can be achieved. Moreover, by recognizing service area status, changes in the service area status of a specific region can be quickly and effectively determined, assisting vehicle navigation.

[0126] In one embodiment, such as Figure 6As shown, a flowchart is also provided to illustrate the urban functional area status identification method of this application, which specifically includes the following steps:

[0127] Step 602: Respond to the status recognition request of the urban functional area to be identified, and obtain the set of trajectory information of moving objects and remote sensing image data;

[0128] Step 604: Based on the trajectory information of the moving object in the trajectory information set, determine the corresponding trajectory point to be matched and obtain map road data;

[0129] Step 606: Based on the map road data, determine the candidate matching roads corresponding to the trajectory points to be matched;

[0130] Step 608: Calculate the road distance and road angle between the trajectory point to be matched and the candidate matching road, respectively;

[0131] Step 610: Determine the road matching degree between the trajectory point to be matched and the candidate matching road based on the road distance and road angle;

[0132] Step 612: Obtain the trajectory matching road based on the road matching degree;

[0133] Step 614: Extract features from the trajectory information of the moving object to obtain the trajectory feature information of the moving object;

[0134] Step 616: Obtain road attribute information of the trajectory matching road;

[0135] Step 618: Classify the trajectory of the moving object based on the road attribute information and the trajectory feature information of the moving object;

[0136] Step 620: Based on the classification results, count the number of trajectories entering urban functional areas, the number of trajectories not entering urban functional areas, and the total number of trajectories entering roads corresponding to different road attributes.

[0137] Step 622: Based on the number of trajectories entering urban functional areas, the number of trajectories not entering urban functional areas, and the total number of trajectories entering roads, obtain the road flow characteristics of roads with different attributes.

[0138] Step 624: When the road with different attributes is a highway, proceed to step 626; when the road with different attributes is a connecting road between urban functional areas, proceed to step 632.

[0139] Step 626: When the road attribute information is a highway and there is no topological connection with the urban functional area connecting road, determine the first state judgment condition corresponding to the highway.

[0140] Step 628: Calculate the first state judgment value corresponding to the first state judgment condition based on the road traffic characteristics corresponding to the expressway.

[0141] Step 630: When the first state judgment value reaches the first state judgment condition, determine that the state judgment result corresponding to the expressway is the construction of a new urban functional area, and jump to step 638.

[0142] Step 632: When the road attribute information is a connecting road of urban functional area, determine the second state judgment condition corresponding to the connecting road of urban functional area;

[0143] Step 634: Calculate the second state judgment value corresponding to the second state judgment condition based on the road traffic characteristics corresponding to the road connecting the urban functional area;

[0144] Step 636: Based on the second state judgment condition and the second state judgment value, obtain the state judgment result corresponding to the road connecting the urban functional area;

[0145] Step 638: Based on the state judgment result, obtain the dynamic recognition result;

[0146] Step 640: Based on the remote sensing image data, perform functional area identification of the urban functional areas to be identified to obtain static identification results;

[0147] Step 642: Based on the dynamic recognition results and the static recognition results, obtain the state recognition results.

[0148] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps.

[0149] In one embodiment, such as Figure 7 As shown, a city functional area status identification device is provided. This device can be a software module, a hardware module, or a combination of both as part of a computer device. Specifically, the device includes: an acquisition module 702, a first processing module 704, a traffic feature extraction module 706, a status identification module 708, and a second processing module 710, wherein:

[0150] The acquisition module 702 is used to respond to the status recognition request of the urban functional area to be identified, and to acquire a set of trajectory information of moving objects and remote sensing image data;

[0151] The first processing module 704 is used to perform trajectory road matching on the trajectory information of the moving object in the trajectory information set to obtain the trajectory matching road, and to extract features from the trajectory information of the moving object to obtain the trajectory feature information of the moving object.

[0152] The traffic flow feature extraction module 706 is used to obtain road attribute information of the trajectory matching road and obtain the road traffic flow features of different attribute roads based on the road attribute information and the trajectory feature information of the moving object.

[0153] The status recognition module 708 is used to determine the status of the urban functional area to be identified based on road attribute information and road traffic characteristics, obtain dynamic recognition results, and perform functional area recognition based on remote sensing image data to obtain static recognition results.

[0154] The second processing module 710 is used to obtain the state recognition result based on the dynamic recognition result and the static recognition result.

[0155] The aforementioned urban functional area status identification device, in response to a status identification request for the urban functional area to be identified, acquires a set of moving object trajectory information and remote sensing image data. It performs trajectory road matching on the moving object trajectory information in the set of moving object trajectory information to obtain the matching roads. By extracting features from the moving object trajectory information, it obtains the moving object trajectory feature information. Based on the road attribute information of the matching roads, and according to the road attribute information and the moving object trajectory feature information, it obtains the road flow characteristics of roads with different attributes. Then, based on the road attribute information and road flow characteristics, it determines the status of the urban functional area to be identified, obtaining a dynamic identification result. By identifying the urban functional area to be identified based on the remote sensing image data, it obtains a static identification result. Therefore, by combining the dynamic and static identification results, it obtains the status identification result, achieving real-time and accurate urban functional area status identification.

[0156] In one embodiment, the first processing module is further configured to determine the corresponding trajectory point to be matched based on the trajectory information of the moving object in the trajectory information set, and obtain map road data, and perform road matching on the trajectory point to be matched based on the map road data to obtain the trajectory matching road.

[0157] In one embodiment, the first processing module is further configured to determine candidate matching roads corresponding to the trajectory point to be matched based on map road data, calculate the road distance and road angle between the trajectory point to be matched and the candidate matching roads respectively, determine the road matching degree between the trajectory point to be matched and the candidate matching roads based on the road distance and road angle, and obtain the trajectory matching road based on the road matching degree.

[0158] In one embodiment, the traffic flow feature extraction module is further configured to classify the trajectory of the moving object based on the road attribute information and the trajectory feature information of the moving object, and based on the classification results, count the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road corresponding to different attribute roads, and obtain the road traffic flow features of different attribute roads based on the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road.

[0159] In one embodiment, the state recognition module is further configured to determine the state judgment conditions of urban functional areas corresponding to roads with different attributes based on road attribute information, obtain the state judgment results corresponding to roads with different attributes based on the urban functional area state judgment conditions and road traffic characteristics, and obtain the dynamic recognition results based on the state judgment results.

[0160] In one embodiment, roads with different attributes include highways. The state recognition module is also used to determine the first state judgment condition corresponding to the highway when the road attribute information is highway and there is no topological connection relationship with the connecting road of the urban functional area. Based on the road traffic characteristics corresponding to the highway, the module calculates the first state judgment value corresponding to the first state judgment condition. When the first state judgment value reaches the first state judgment condition, the module determines that the state judgment result corresponding to the highway is newly built in the urban functional area.

[0161] In one embodiment, roads with different attributes include urban functional area connecting roads. The state recognition module is further used to determine the second state judgment condition corresponding to the urban functional area connecting road when the road attribute information is an urban functional area connecting road, calculate the second state judgment value corresponding to the second state judgment condition based on the road traffic flow characteristics corresponding to the urban functional area connecting road, and obtain the state judgment result corresponding to the urban functional area connecting road based on the second state judgment condition and the second state judgment value.

[0162] Specific limitations regarding the urban functional area status identification device can be found in the limitations of the urban functional area status identification method described above, and will not be repeated here. Each module in the aforementioned urban functional area status identification device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0163] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 8 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores map and road data, etc. The network interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a method for identifying the status of urban functional areas.

[0164] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0165] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0166] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0167] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the steps in the above method embodiments.

[0168] It should be noted that the information on the moving objects involved in this application (including but not limited to the trajectory information of the moving objects) and the data (including but not limited to the data used for analysis, the data stored, the data displayed, etc.) are all information and data authorized by the moving objects or fully authorized by all parties.

[0169] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0170] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0171] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for identifying the status of urban functional zones, characterized in that, The method includes: In response to the status recognition request of the urban functional area to be identified, the system acquires a set of trajectory information of moving objects corresponding to the urban functional area to be identified, as well as remote sensing image data. Trajectory road matching is performed on the trajectory information of the moving object in the set of trajectory information to obtain the trajectory matching road, and feature extraction is performed on the trajectory information of the moving object to obtain the trajectory feature information of the moving object; Obtain the road attribute information of the trajectory matching road, and obtain the road flow characteristics of roads with different attributes based on the road attribute information and the trajectory feature information of the moving object; the road flow characteristics include the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road. Based on the road attribute information, determine the urban functional area status judgment conditions corresponding to roads with different attributes, and based on the urban functional area status judgment conditions and the road traffic flow characteristics, obtain the status judgment results corresponding to roads with different attributes. Based on the state judgment result, a dynamic recognition result is obtained, and based on the remote sensing image data, the functional area of ​​the city to be identified is identified to obtain a static recognition result. Based on the dynamic recognition result, a target static recognition result corresponding to the dynamic recognition result is determined, and the target static recognition result and the static recognition result are compared to obtain a state recognition result.

2. The method according to claim 1, characterized in that, The step of performing trajectory road matching on the trajectory information of the moving object in the set of trajectory information to obtain the trajectory matching road includes: Based on the trajectory information of the moving object in the set of moving object trajectory information, determine the corresponding trajectory point to be matched, and obtain map road data; Based on the map road data, road matching is performed on the trajectory points to be matched to obtain the trajectory matching road.

3. The method according to claim 2, characterized in that, The step of performing road matching on the trajectory points to be matched based on the map road data to obtain the trajectory matching road includes: Based on the map road data, candidate matching roads corresponding to the trajectory points to be matched are determined; Calculate the road distance and road angle between the trajectory point to be matched and the candidate matching road, respectively; Based on the road distance and the road angle, determine the road matching degree between the trajectory point to be matched and the candidate matching road; Based on the road matching degree, the trajectory matching road is obtained.

4. The method according to claim 1, characterized in that, The step of obtaining road flow characteristics for roads with different attributes based on the road attribute information and the trajectory feature information of the moving object includes: The trajectory of the moving object is classified based on the road attribute information and the trajectory feature information of the moving object; Based on the classification results, the number of trajectories entering urban functional areas, the number of trajectories not entering urban functional areas, and the total number of trajectories entering roads corresponding to different road attributes are counted. Based on the number of trajectories entering urban functional areas, the number of trajectories not entering urban functional areas, and the total number of trajectories entering roads, the road flow characteristics of roads with different attributes are obtained.

5. The method according to claim 1, characterized in that, The roads with different attributes include highways; The step of determining the urban functional area status judgment conditions corresponding to roads with different attributes based on the road attribute information, and obtaining the status judgment results corresponding to roads with different attributes based on the urban functional area status judgment conditions and the road traffic flow characteristics, includes: When the road attribute information is a highway and there is no topological connection with the urban functional area connecting road, determine the first state judgment condition corresponding to the highway. Based on the road traffic characteristics corresponding to the expressway, calculate the first state judgment value corresponding to the first state judgment condition; When the first state judgment value reaches the first state judgment condition, the state judgment result corresponding to the expressway is determined to be the construction of a new urban functional area.

6. The method according to claim 1, characterized in that, The roads with different attributes include connecting roads between urban functional areas; The step of determining the urban functional area status judgment conditions corresponding to roads with different attributes based on the road attribute information, and determining the status judgment results corresponding to roads with different attributes based on the urban functional area status judgment conditions and the road traffic flow characteristics, includes: When the road attribute information is a connecting road of urban functional area, determine the second state judgment condition corresponding to the connecting road of urban functional area. Based on the road traffic characteristics corresponding to the connecting roads of the urban functional areas, calculate the second state judgment value corresponding to the second state judgment condition; Based on the second state judgment condition and the second state judgment value, the state judgment result corresponding to the connecting road of the urban functional area is obtained.

7. A device for identifying the status of urban functional areas, characterized in that, The device includes: The acquisition module is used to respond to the status recognition request of the urban functional area to be identified and acquire the set of trajectory information of moving objects corresponding to the urban functional area to be identified and remote sensing image data. The first processing module is used to perform trajectory road matching on the trajectory information of the moving object in the set of trajectory information of the moving object to obtain the trajectory matching road, and to extract features from the trajectory information of the moving object to obtain the trajectory feature information of the moving object; The traffic flow feature extraction module is used to obtain the road attribute information of the trajectory matching road, and obtain the road traffic flow features of different attribute roads based on the road attribute information and the trajectory feature information of the moving object; the road traffic flow features include the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road. The status recognition module is used to determine the status judgment conditions of urban functional areas corresponding to roads with different attributes based on the road attribute information, obtain the status judgment results corresponding to roads with different attributes based on the urban functional area status judgment conditions and the road traffic characteristics, obtain the dynamic recognition results based on the status judgment results, and perform functional area recognition on the urban functional area to be identified based on the remote sensing image data to obtain the static recognition results. The second processing module is used to determine the target static recognition result corresponding to the dynamic recognition result based on the dynamic recognition result, and compare the target static recognition result with the static recognition result to obtain the state recognition result.

8. The apparatus according to claim 7, characterized in that, The first processing module is further configured to determine the corresponding trajectory point to be matched based on the trajectory information of the moving object in the set of moving object trajectory information, and to obtain map road data, and to perform road matching on the trajectory point to be matched based on the map road data to obtain the trajectory matching road.

9. The apparatus according to claim 8, characterized in that, The first processing module is further configured to determine, based on the map road data, candidate matching roads corresponding to the trajectory point to be matched, calculate the road distance and road angle between the trajectory point to be matched and the candidate matching roads respectively, determine the road matching degree between the trajectory point to be matched and the candidate matching roads based on the road distance and the road angle, and obtain the trajectory matching road based on the road matching degree.

10. The apparatus according to claim 7, characterized in that, The traffic flow feature extraction module is further used to classify the trajectory of the moving object according to the road attribute information and the trajectory feature information of the moving object, and according to the classification results, to count the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road corresponding to different attribute roads, and to obtain the road traffic flow features of different attribute roads according to the number of trajectories entering the urban functional area, the number of trajectories not entering the urban functional area, and the total number of trajectories entering the road.

11. The apparatus according to claim 7, characterized in that, The different attribute roads include highways. The state recognition module is further used to determine the first state judgment condition corresponding to the highway when the road attribute information is highway and there is no topological connection relationship with the urban functional area connecting road. Based on the road traffic flow characteristics corresponding to the highway, the module calculates the first state judgment value corresponding to the first state judgment condition. When the first state judgment value reaches the first state judgment condition, the module determines that the state judgment result corresponding to the highway is newly built in the urban functional area.

12. The apparatus according to claim 7, characterized in that, The different attribute roads include urban functional area connecting roads. The state recognition module is further used to determine the second state judgment condition corresponding to the urban functional area connecting road when the road attribute information is an urban functional area connecting road, calculate the second state judgment value corresponding to the second state judgment condition based on the road traffic flow characteristics corresponding to the urban functional area connecting road, and obtain the state judgment result corresponding to the urban functional area connecting road based on the second state judgment condition and the second state judgment value.

13. A computer 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 steps of the method according to any one of claims 1 to 6.

14. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images