Road determination method, apparatus, and related device

Abstract

The present application provides a road determination method, device and related equipment, the road determination method comprises: obtaining at least two signaling data, the signaling data is the data that the electronic device and the base station interact, the base station corresponding to the at least two signaling data is continuously distributed in the target area, and the base station corresponding to at least part of signaling data in the at least two signaling data is different;According to the at least two signaling data and the shape of at least one road included in the target area in the electronic map obtained in advance, the moving track of the electronic device is generated;According to the moving track, the target road is determined in the at least one road.In this way, even when the signal is poor, the moving track of the electronic device can be generated according to the at least two signaling data and the shape of at least one road included in the target area in the electronic map obtained in advance, and the target road is determined according to the moving track, thereby improving the accuracy of the determined target road.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a road determination method, apparatus and related equipment. Background Technology

[0002] With the development of electronic map technology, electronic maps have become increasingly important in people's lives. People can use electronic maps for navigation or positioning. However, currently, it is usually necessary to locate the user's current location to infer the user's driving route. Thus, when the signal is poor, the inference of the user's driving route is likely to be poor. Summary of the Invention

[0003] This application provides a road determination method, apparatus, and related equipment to solve the problem of poor prediction of a user's driving route.

[0004] To solve the above problems, this application is implemented as follows:

[0005] In a first aspect, embodiments of this application provide a road determination method, including:

[0006] Acquire at least two signaling data, wherein the signaling data is data of interaction between electronic devices and base stations, the base stations corresponding to the at least two signaling data are continuously distributed in the target area, and at least some of the signaling data correspond to different base stations;

[0007] The movement trajectory of the electronic device is generated based on the shape of at least one road within the target area in the at least two signaling data and the pre-acquired electronic map;

[0008] The target road is determined from the at least one road based on the movement trajectory.

[0009] Secondly, embodiments of this application provide a road determination device, comprising:

[0010] The first acquisition module is used to acquire at least two signaling data, wherein the signaling data is data of interaction between electronic devices and base stations, the base stations corresponding to the at least two signaling data are continuously distributed in the target area, and at least some of the signaling data correspond to different base stations;

[0011] A generation module is used to generate the movement trajectory of the electronic device based on the shape of at least one road included in the target area in the at least two signaling data and a pre-acquired electronic map;

[0012] The first determining module is used to determine the target road in the at least one road based on the movement trajectory.

[0013] Thirdly, embodiments of this application also provide an electronic device, including: a transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; the processor is configured to read the program in the memory to implement the steps in the method described in the first aspect above.

[0014] Fourthly, embodiments of this application also provide a readable storage medium for storing a program, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0015] In this embodiment, at least two signaling data are acquired. The signaling data is data from the interaction between the electronic device and the base station. The base stations corresponding to the at least two signaling data are continuously distributed in the target area, and at least some of the signaling data correspond to different base stations. The movement trajectory of the electronic device is generated based on the at least two signaling data and the shape of at least one road included in the target area in a pre-acquired electronic map. The target road is determined based on the movement trajectory in the at least one road.

[0016] In this way, even when the signal is poor, the movement trajectory of the electronic device can be generated based on at least two signaling data and the shape of at least one road included in the target area in the pre-acquired electronic map, and the target road can be determined based on the movement trajectory, thereby improving the accuracy of the determined target road. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram illustrating an application scenario to which the embodiments of this application can be applied;

[0019] Figure 2 This is one of the flowcharts of the road determination method provided in the embodiments of this application;

[0020] Figure 3 This is a schematic diagram of the structure of the server, communication network server, application module, and electronic device provided in the embodiments of this application;

[0021] Figure 4 This is the second flowchart of the road determination method provided in the embodiments of this application;

[0022] Figure 5This is a diagram showing the positional relationship between points A and B and the road, provided in an embodiment of this application.

[0023] Figure 6 This is a schematic diagram of the road determination device provided in the embodiments of this application;

[0024] Figure 7 This is a schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices. Additionally, the use of "and / or" in this application indicates at least one of the connected objects, such as A and / or B and / or C, representing seven possibilities: including A alone, B alone, C alone, and the presence of both A and B, both B and C, both A and C, and the presence of A, B, and C.

[0027] Please see Figure 1 , Figure 1 This is an application scenario diagram to which the embodiments of this application can be applied, such as... Figure 1 As shown, it includes an electronic device 11 and three base stations 12. The electronic device 11 and each base station 12 can communicate with each other, and the resulting communication information is the initial data or signaling data described later. Furthermore, Figure 1 In the diagram, the three electronic devices 11 represent the same electronic device 11 located at different positions in the road segment over time.

[0028] In practical applications, electronic device 11 can be a terminal (also known as user equipment, UE), which can be a mobile phone, tablet computer, laptop computer, personal digital assistant (PDA), mobile internet device (MID), wearable device, or vehicle-mounted device, etc. Network-side equipment can be a base station, access and mobility management function (AMF), relay, access point, or other network elements, etc.

[0029] The road determination method provided in the embodiments of this application will be described below.

[0030] See Figure 2 , Figure 2 This is a schematic flowchart of the road determination method provided in the embodiments of this application. Figure 2 The road determination method shown can be executed by the server. For example... Figure 2 As shown, the road determination method may include the following steps:

[0031] Step 201: Obtain at least two signaling data, wherein the signaling data is data exchanged between electronic devices and base stations, the base stations corresponding to the at least two signaling data are continuously distributed in the target area, and at least some of the signaling data correspond to different base stations.

[0032] The signaling data can be data that is exchanged between the electronic device and the base station. The actions performed by the electronic device are not limited here. For example, when the electronic device is a mobile phone, the signaling information mentioned above can refer to the information generated by the mobile phone and the base station performing the following operations, including at least one of the following operations: calling, receiving, SMS, roaming, and Mobile Switching Center (MSC) handover.

[0033] It should be noted that the method of obtaining signaling data is not limited here; for example, see: Figure 3 The signaling data can be stored in the signaling monitoring platform in the communication network server 31, and the server 32 of this application can be electrically connected to the aforementioned signaling monitoring platform. In this way, the server 32 can obtain the aforementioned at least two signaling data from the signaling monitoring platform.

[0034] For example, server 32 may include a signaling acquisition service module 321, a database 322, and a data analysis module 323. The signaling acquisition service module 321 can be electrically connected to both the database 322 and the data analysis module 323. The database 322 can be electrically connected to the data analysis module 323. The signaling acquisition service module 321 can periodically read the aforementioned signaling data from the signaling monitoring platform. Furthermore, the signaling acquisition service module 321 can store the aforementioned signaling data in the database 322 corresponding to server 32 and periodically delete processed signaling data. Then, the database 322 can synchronize unprocessed signaling data to various application modules 33 of server 32 (e.g., the server's processor). Additionally, the data analysis module 323 can perform sampling and speed calculations, while the application modules 33 can perform path estimation or route push. Electronic devices 34 can access the data on the application modules 33 through applications such as browsers. For specific procedures, please refer to [link to relevant documentation]. Figure 3 .

[0035] In addition, to protect user privacy, signaling data can be encrypted. The specific encryption method is not limited here. For example, the user's unique identifier in the signaling data can be encrypted to prevent reverse engineering, thereby protecting user privacy.

[0036] The target area can refer to the area where the road to be predicted is located, and the target area can include multiple roads with the same or similar shapes. The target area can generally be located in an area to be developed or an area under development.

[0037] The target area may include multiple base stations, and at least two signaling data can be sent to one of the multiple base stations respectively. Since the location and arrangement order of the base stations are determined, the sending location and sending order of the at least two signaling data should also be determined, thereby making the accuracy of generating the movement trajectory of the electronic device based on the at least two signaling data higher, and at the same time, it is also easier to determine the reliability of the at least two signaling data.

[0038] As an optional implementation, before acquiring at least two signaling data points, the method further includes:

[0039] Data preprocessing is performed from multiple initial data sets to obtain the at least two signaling data sets;

[0040] The data preprocessing includes at least one of the following methods: abnormal data filtering and interference data filtering.

[0041] In this embodiment of the application, since multiple initial data can be preprocessed, and the data preprocessing includes at least one of the following methods: abnormal data filtering processing and interference data filtering processing, abnormal data and interference data can be filtered out, thereby making the reliability of at least two signaling data obtained higher.

[0042] As an optional implementation, when the data preprocessing includes anomaly filtering, the data preprocessing from multiple initial data sets to obtain the at least two signaling data sets includes:

[0043] Data that meets preset conditions from multiple initial data sets are filtered out to determine the at least two signaling data sets.

[0044] The preset conditions include at least one of the following: abnormal location, abnormal base station matching, duplicate location, back-and-forth location switching, and location switching not conforming to the preset trajectory.

[0045] The data with abnormal location can include: initial data with missing location attributes, initial data with abnormal location area code (LAC), and initial data with abnormal cell code (CellID). In this way, the above-mentioned data with abnormal location can be filtered out.

[0046] Among them, base station matching anomaly can refer to the following: due to untimely maintenance of base station information, the base station code in the initial data of some locations may fail to match the base station code in the base station information database, thus making it impossible to obtain the latitude and longitude information of the corresponding base station.

[0047] Location duplication can refer to multiple initial data entries appearing consecutively at the same location when the location signaling data of the same user is sorted by time. During data preprocessing, multiple initial data entries appearing consecutively at the same location can be merged, retaining the first initial data entry at that location and deleting subsequent duplicate initial data entries at that location. It should be noted that the aforementioned location can refer to the location of the base station or the latitude and longitude location corresponding to the initial data when it was generated.

[0048] Among them, location switching refers to the initial data generated when a user switches back and forth between two locations (location A and location B) for the same user's location initial data sorted by time (e.g., ABA switching). When preprocessing the initial data of location switching, for an ABA switching group, the first initial data appearing at that location can be retained, and subsequent duplicate initial data appearing at that location can be deleted.

[0049] In this context, "location switching not conforming to the preset trajectory" can refer to the following: when the initial data is switched in chronological order, it does not follow the preset trajectory. For example, if the distribution order of base stations on a road is base station A, base station B, and base station C, then according to the normal switching order, the initial data should be received in chronological order as initial data 1 interacting with base station A, initial data 2 interacting with base station B, and initial data 3 interacting with base station C. If the initial data is received in the order of initial data 1, initial data 3, and initial data 2, then it is clear that the above initial data reception order does not conform to the normal reception order. Therefore, it can be determined that the movement trajectory corresponding to initial data 1, initial data 3, and initial data 2 does not conform to the preset trajectory.

[0050] It should be noted that the initial data points for the aforementioned position switching that do not conform to the preset trajectory can also be referred to as the initial data points for the drift position.

[0051] In this embodiment of the application, data that meets preset conditions from multiple initial data are filtered out to determine at least two signaling data; in this way, multiple initial data can be filtered out, thereby improving the accuracy and reliability of the final at least two signaling data.

[0052] As an optional implementation, when the data preprocessing includes interference data filtering, the data preprocessing from multiple initial data to obtain the at least two signaling data includes:

[0053] The at least two signaling data are determined from a plurality of initial data, wherein the at least two signaling data are data generated by travel using the target mode of transportation;

[0054] The target means of transportation includes: automobiles.

[0055] The initial data may include data generated from other modes of transportation. Trajectories generated from these other modes of transportation are highly random and do not strictly follow actual roads. Therefore, it is necessary to filter out this data, obtaining only at least two signaling data points generated from the target mode of transportation. These other modes of transportation may include at least one of walking, cycling, or subway.

[0056] The aforementioned vehicles include at least one of vehicles for carrying people and vehicles for carrying goods, and vehicles for carrying people may include at least one of private cars and buses.

[0057] In this embodiment, by determining at least two signaling data points generated from traveling using the target mode of transportation from multiple initial data points, interference from initial data points generated from traveling using other modes of transportation can be reduced, resulting in higher accuracy of the target road determined based on at least two signaling data points.

[0058] It should be noted that the mode of travel used to determine the initial data is not limited here. As an optional implementation method, the initial data generated using each mode of travel can carry corresponding tag information, and the tag information carried by the initial data generated using different modes of travel will be different.

[0059] As another alternative implementation, a pre-trained model can be used to identify the initial data generated by different modes of travel. When training the model, the sample data used can include initial sample data generated by multiple modes of travel. The initial sample data can include at least one of the feature information of travel distance, travel duration and travel speed, and the above feature information corresponds one-to-one with the mode of travel. In this way, the above feature information corresponding to the initial sample data generated by different modes of travel is different. After multiple iterations of training, the model can accurately identify the mode of travel corresponding to the initial data.

[0060] For example, Gaussian membership functions and S-shaped membership functions can be used to identify the initial data generated by different travel modes. Gaussian membership functions can identify initial data with restrictions in both positive and negative directions, while S-shaped membership functions can identify initial data with restrictions in only one direction.

[0061] The Gaussian membership function is in the form of:

[0062]

[0063] The S-shaped membership function is:

[0064]

[0065] In this context, parameters σ and a are used to determine the width of the curve; parameters c and b are used to determine the center of the curve; x is the independent variable, representing the average speed, which can be determined based on the statistical indicators of travel characteristics in each city in recent years (parameters such as average travel distance, average travel time, and average travel speed of each mode of travel), while exp is used to represent an exponential function with the natural constant e as the base.

[0066] Step 202: Generate the movement trajectory of the electronic device based on the shape of at least one road within the target area in the at least two signaling data and the pre-acquired electronic map.

[0067] The location where a signaling data is sent can be determined as a point. The general direction of the movement trajectory can be determined based on at least two points where at least two signaling data are sent. Then, the shape of the road is combined to connect the at least two points, so that the movement trajectory can conform to the shape of the road, making the movement trajectory more consistent with the trajectory of a real road.

[0068] In addition, the target area may include multiple base stations. Since at least some of the signaling data corresponds to different base stations, the critical area of ​​the base station in the target area can be located based on the aforementioned at least some signaling data, thereby further narrowing down the scope of the target area.

[0069] In addition, by matching the aforementioned base station critical areas with the electronic map, a base station critical area covering multiple roads within the target area can be generated, thereby enhancing the positioning accuracy of the base station critical area. At least one road in the defense can be located within the aforementioned base station critical area, thus further narrowing the range of the base station critical area. At the same time, the base station critical area and at least one road are mapped onto the same electronic map, facilitating the subsequent positioning of the target road within at least one road.

[0070] It should be noted that a positioning model can be used to determine the critical area of ​​a base station. The positioning model can be trained over a long period of time using data such as the time advance, signal strength, and statistical data of the critical area of ​​the base station, thereby improving the positioning accuracy of the positioning model in the critical area of ​​the base station.

[0071] Step 203: Determine the target road in the at least one road based on the movement trajectory.

[0072] It should be noted that the method for determining the target road from at least one road based on the movement trajectory is not specifically limited here. As an optional implementation, the road with the highest shape matching degree to the movement trajectory can be determined as the target road.

[0073] As another optional implementation, determining the target road among the at least one road based on the movement trajectory includes:

[0074] Calculate the weighted sum of the movement trajectory and preset parameters of each of the at least one road;

[0075] The road with the smallest weighted sum of preset parameters and the movement trajectory among the at least one road is determined as the target road;

[0076] The preset parameters include at least one of the following parameters: the length of the movement trajectory, the distance between the position corresponding to each signaling data in the movement trajectory and the road, and the angle between the position corresponding to each signaling data in the movement trajectory and the direction of the road.

[0077] The length of the movement trajectory can be divided into multiple trajectory segments depending on the base station corresponding to the signaling data. These trajectory segments can also be called road segments. For example, the first signaling data corresponds to the first base station, the second signaling data corresponds to the second base station, and the third signaling data corresponds to the third base station. The first, second, and third base stations are distributed sequentially. Thus, the road segment between the first and second base stations (i.e., the road segment corresponding to the first and second signaling data) can be determined as the first road segment, and the road segment between the second and third base stations (i.e., the road segment corresponding to the second and third signaling data) can be determined as the second road segment.

[0078] The formula for calculating the weighted sum is: Weighted sum = (Road segment travel distance 1 + ... + Road segment travel distance m) * Weighting coefficient 1 + (Point distance 1 + ... + Point distance n) * Weighting coefficient 2 + (Direction angle 1 + ... + Direction angle n) * Weighting coefficient 3;

[0079] Among them, the road segment travel distance 1 and the road segment travel distance m can be the first road segment, the second road segment, or the third road segment mentioned above, respectively; the point distance 1 and the point distance n can both be the distance between the location corresponding to a certain signaling data and the road; and the direction angle 1 and the direction angle n can both be the angle between the location corresponding to a certain signaling data and the direction of the road.

[0080]

[0081]

[0082]

[0083] In this embodiment, the road with the smallest weighted sum of preset parameters and movement trajectory among at least one road is determined as the target road. This makes the accuracy of the determined target road higher, that is, the accuracy of the prediction result of the target road is higher.

[0084] It should be noted that the calculation method for the weighted sum of each road and movement trajectory can refer to the calculation method of the above calculation formula; the above is only an illustrative example.

[0085] As an optional implementation, after determining the target road in the at least one road based on the movement trajectory, the method further includes:

[0086] If the matching degree between the movement trajectory and the target road is less than a preset threshold, the mismatch portion between the movement trajectory and the target road is determined;

[0087] Obtain the remote sensing image corresponding to the mismatched portion;

[0088] The target roads in the electronic map are updated based on the remote sensing imagery.

[0089] The matching degree between the movement trajectory and the target road can refer to the degree of overlap between the movement trajectory and the target road. The higher the degree of overlap, the higher the matching degree. The specific value of the preset threshold is not limited here. For example, the value of the preset threshold can be 90%.

[0090] In addition, to simplify the calculation, the matching degree between the movement trajectory and the target road can also refer to the degree of overlap between the points corresponding to at least two signaling data in the movement trajectory and the target road. When more than a preset threshold of points overlap with the target road, the matching degree between the movement trajectory and the target road is considered to be higher than the preset threshold.

[0091] In this embodiment, only the remote sensing images corresponding to the mismatched parts need to be acquired, and the target roads in the electronic map are updated based on the remote sensing images. Compared with the method of acquiring remote sensing images of all roads for updating, this method can save on usage costs. At the same time, it can make the parts of the target roads to be updated more targeted and the accuracy of updating the target roads higher.

[0092] For example: see Figure 4 , Figure 4 This can be understood as a combination of various embodiments in the examples of this application. For specific embodiments, please refer to [link / reference]. Figure 4 The steps shown are as follows.

[0093] The method for determining whether a point in the movement trajectory is located inside or outside the road can be found in the following description: The shape enclosed by the road can be considered a closed shape, for example: see... Figure 5 Road 501 is a closed shape, and points A and B can be considered as points on the trajectory. When the number of times the ray originating from point A crosses the polygon boundary is even, all even-numbered crossings (including the last one) are exits, and all odd-numbered crossings (including the first one) are entries. Therefore, we can deduce that the points are outside the polygon. Point A crosses the polygon 2 times (entries) and 3 times (exits), a total of 5 times, which is an odd number, so it is inside the polygon. The number of times the ray originating from point B crosses the polygon is 1 time (entries) and 1 time (exits), a total of 2 times, which is an even number, so it is outside the polygon.

[0094] In this embodiment of the application, through steps 201 to 203, even when the signal is poor, the movement trajectory of the electronic device can be generated based on at least two signaling data and the shape of at least one road included in the target area in the pre-acquired electronic map, and the target road can be determined based on the movement trajectory, thereby improving the accuracy of the determined target road.

[0095] See Figure 6 , Figure 6 This is one of the structural diagrams of the road determination device provided in the embodiments of this application. For example... Figure 6 As shown, the road determination device 600 includes:

[0096] The first acquisition module 601 is used to acquire at least two signaling data, wherein the signaling data is data of interaction between electronic devices and base stations, the base stations corresponding to the at least two signaling data are continuously distributed in the target area, and at least some of the signaling data correspond to different base stations.

[0097] The generation module 602 is used to generate the movement trajectory of the electronic device based on the shape of at least one road included in the target area in the at least two signaling data and a pre-acquired electronic map;

[0098] The first determining module 603 is used to determine the target road in the at least one road based on the movement trajectory.

[0099] Optionally, the first determining module 603 includes:

[0100] The calculation submodule is used to calculate the weighted sum of the movement trajectory and preset parameters of each of the at least one road;

[0101] A determination submodule is used to determine the road with the smallest weighted sum of preset parameters and the movement trajectory among the at least one road as the target road;

[0102] The preset parameters include at least one of the following parameters: the length of the movement trajectory, the distance between the position corresponding to each signaling data in the movement trajectory and the road, and the angle between the position corresponding to each signaling data in the movement trajectory and the direction of the road.

[0103] Optionally, the road determining device 600 further includes:

[0104] The second determining module is used to determine the non-matching part of the movement trajectory and the target road when the matching degree between the movement trajectory and the target road is less than a preset threshold.

[0105] The second acquisition module is used to acquire the remote sensing image corresponding to the mismatched part;

[0106] The update module is used to update the target roads in the electronic map based on the remote sensing image.

[0107] Optionally, the road determining device 600 further includes:

[0108] A preprocessing module is used to preprocess data from multiple initial data to obtain the at least two signaling data;

[0109] The data preprocessing includes at least one of the following methods: abnormal data filtering and interference data filtering.

[0110] Optionally, if the data preprocessing includes abnormal data filtering, the preprocessing module is further configured to filter out data that meets preset conditions from multiple initial data to determine the at least two signaling data.

[0111] The preset conditions include at least one of the following: abnormal location, abnormal base station matching, duplicate location, back-and-forth location switching, and location switching not conforming to the preset trajectory.

[0112] Optionally, if the data preprocessing includes interference data filtering, the preprocessing module is further configured to determine the at least two signaling data from a plurality of initial data, wherein the at least two signaling data are data generated by traveling using the target mode of transportation;

[0113] The target means of transportation includes: automobiles.

[0114] The road determination device 600 can achieve the functions described in the embodiments of this application. Figure 2 The various processes in the method embodiments, and the ways to achieve the same beneficial effects, will not be repeated here to avoid repetition.

[0115] This application also provides an electronic device. Please refer to [link to relevant documentation]. Figure 7 The electronic device may include a processor 701, a memory 702, and a program 7021 stored in the memory 702 and capable of running on the processor 701.

[0116] When program 7021 is executed by processor 701, it can achieve the following: Figure 2 Any steps in the corresponding method embodiments and the achievement of the same beneficial effects will not be repeated here.

[0117] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by hardware related to program instructions, and the program can be stored in a readable medium. This application also provides a readable storage medium storing a computer program, which, when executed by a processor, can implement the above-described methods. Figure 2 Any step in the corresponding method embodiment can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0118] The storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0119] The above description represents the preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles described in this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining a road, characterized in that, include: Acquire at least two signaling data, wherein the signaling data is data of interaction between electronic devices and base stations, the base stations corresponding to the at least two signaling data are continuously distributed in the target area, and at least some of the signaling data correspond to different base stations; The movement trajectory of the electronic device is generated based on the shape of at least one road within the target area in the at least two signaling data and the pre-acquired electronic map; The target road is determined from the at least one road based on the movement trajectory; Determining the target road among the at least one road based on the movement trajectory includes: Calculate the weighted sum of the movement trajectory and preset parameters of each of the at least one road; The road with the smallest weighted sum of preset parameters and the movement trajectory among the at least one road is determined as the target road; The preset parameters include the following parameters: the length of the movement trajectory, the distance between the position corresponding to each signaling data in the movement trajectory and the road, and the angle between the position corresponding to each signaling data in the movement trajectory and the direction of the road.

2. The method according to claim 1, characterized in that, After determining the target road in the at least one road based on the movement trajectory, the method further includes: If the matching degree between the movement trajectory and the target road is less than a preset threshold, the mismatch portion between the movement trajectory and the target road is determined; Obtain the remote sensing image corresponding to the mismatched portion; The target roads in the electronic map are updated based on the remote sensing imagery.

3. The method according to claim 1, characterized in that, Before acquiring at least two signaling data points, the method further includes: Data preprocessing is performed from multiple initial data sets to obtain the at least two signaling data sets; The data preprocessing includes at least one of the following methods: abnormal data filtering and interference data filtering.

4. The method according to claim 3, characterized in that, In cases where the data preprocessing includes anomaly filtering, the data preprocessing from multiple initial data sets to obtain the at least two signaling data sets includes: Data that meets preset conditions from multiple initial data sets are filtered out to determine the at least two signaling data sets. The preset conditions include at least one of the following: abnormal location, abnormal base station matching, duplicate location, back-and-forth location switching, and location switching not conforming to the preset trajectory.

5. The method according to claim 3, characterized in that, In cases where the data preprocessing includes interference data filtering, the data preprocessing from multiple initial data sets to obtain the at least two signaling data sets includes: The at least two signaling data are determined from a plurality of initial data, wherein the at least two signaling data are data generated by travel using the target mode of transportation; The target means of transportation includes: automobiles.

6. A road determining device, characterized in that, include: The first acquisition module is used to acquire at least two signaling data, wherein the signaling data is data of interaction between electronic devices and base stations, the base stations corresponding to the at least two signaling data are continuously distributed in the target area, and at least some of the signaling data correspond to different base stations; A generation module is used to generate the movement trajectory of the electronic device based on the shape of at least one road included in the target area in the at least two signaling data and a pre-acquired electronic map; A first determining module is configured to determine a target road in the at least one road based on the movement trajectory; The first determining module includes: The calculation submodule is used to calculate the weighted sum of the movement trajectory and preset parameters of each of the at least one road; A determination submodule is used to determine the road with the smallest weighted sum of preset parameters and the movement trajectory among the at least one road as the target road; The preset parameters include the following parameters: the length of the movement trajectory, the distance between the position corresponding to each signaling data in the movement trajectory and the road, and the angle between the position corresponding to each signaling data in the movement trajectory and the direction of the road.

7. The apparatus according to claim 6, characterized in that, The road determination device further includes: The second determining module is used to determine the non-matching part of the movement trajectory and the target road when the matching degree between the movement trajectory and the target road is less than a preset threshold. The second acquisition module is used to acquire the remote sensing image corresponding to the mismatched part; The update module is used to update the target roads in the electronic map based on the remote sensing image.

8. The apparatus according to claim 6, characterized in that, The road determination device further includes: A preprocessing module is used to preprocess data from multiple initial data to obtain the at least two signaling data; The data preprocessing includes at least one of the following methods: abnormal data filtering and interference data filtering.

9. The apparatus according to claim 8, characterized in that, In cases where the data preprocessing includes abnormal data filtering, the preprocessing module is further configured to filter out data that meets preset conditions from multiple initial data sets in order to determine the at least two signaling data sets. The preset conditions include at least one of the following: abnormal location, abnormal base station matching, duplicate location, back-and-forth location switching, and location switching not conforming to the preset trajectory.

10. The apparatus according to claim 8, characterized in that, In the case where the data preprocessing includes interference data filtering, the preprocessing module is further configured to determine the at least two signaling data from a plurality of initial data, wherein the at least two signaling data are data generated by traveling using the target mode of transportation; The target means of transportation includes: automobiles.

11. An electronic device, comprising: A transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; characterized in that the processor is configured to read the program in the memory to implement the steps of the road determination method as described in any one of claims 1 to 5.

12. A readable storage medium for storing a program, characterized in that, When the program is executed by the processor, it implements the steps in the road determination method as described in any one of claims 1 to 5.

Images