Passenger transport hub user travel characteristic analysis method and system based on signaling data

Abstract

The invention discloses a passenger transport hub user travel feature analysis method and system based on signaling data, and the method comprises the steps: obtaining the signaling data of the travel of a target user, and carrying out the data deduplication operation, and obtaining a travel data set; mapping the position information in the travel data set into a map model, and obtaining a transportation junction and a travel track passed by the target user; determining a travel tool used by the target user; dividing the travel track based on a travel tool to obtain corresponding travel road sections; acquiring summarized data of the target user in all travel road sections; wherein the summarized data comprises a starting point, an end point, a timestamp and a travel tool corresponding to each travel road section; and performing statistical analysis on the summarized data to obtain travel characteristics of the target user. According to the invention, through processing and analyzing the signaling data of the user travel, the travel characteristics of the passenger transport hub user can be effectively obtained, so that a more flexible and dynamic adjustment basis is provided for public transport scheduling.

Description

Technical Field

[0001] The present invention relates to the field of big data analysis technology, and in particular to a method, system, computer-readable storage medium and electronic device for analyzing travel characteristics of passengers at a passenger hub based on signaling data. Background Art

[0002] With the acceleration of urbanization and the continuous increase in population density, the efficiency and sustainability of the public transportation system, as an important part of urban transportation, directly affect the overall traffic flow of the city and the travel quality of residents. Specifically, through in-depth mining of user travel data at hub stations, travel patterns and behavior patterns can be revealed, thus providing a scientific basis for public transportation scheduling optimization, facility layout, passenger flow prediction and other decisions. Therefore, how to effectively obtain the travel characteristics of passenger hub users has become an urgent problem to be solved. Summary of the invention

[0003] The purpose of the embodiments of the present invention is to provide a method, system, computer-readable storage medium and electronic device for analyzing the travel characteristics of passengers at passenger hubs based on signaling data. By processing and analyzing the signaling data of users' travel, the travel characteristics of passengers at passenger hubs can be effectively obtained, thereby providing a more flexible and dynamic adjustment basis for public transportation scheduling.

[0004] The first aspect of the present invention provides a method for analyzing the travel characteristics of users at a passenger hub based on signaling data, which is executed by a server. The method includes:

[0005] Obtain the signaling data of the target user's travel, and perform data deduplication operations to obtain a travel data set;

[0006] Mapping the location information in the travel data set into a map model to obtain the transportation hubs passed by the target user and the travel trajectory of the target user; wherein the travel trajectory includes: the connecting routes between the transportation hubs;

[0007] Determining the means of transportation used by the target user;

[0008] Dividing the travel trajectory based on the travel tool to obtain corresponding travel sections;

[0009] Obtain summary data of the target user in all the travel sections; wherein the summary data includes: the starting point, the end point, the timestamp and the travel tool corresponding to each of the travel sections;

[0010] Statistical analysis is performed on the summary data to obtain travel characteristics of the target user.

[0011] Optionally, the acquiring of signaling data of a target user's travel and performing a data deduplication operation to obtain a travel data set includes:

[0012] Each time when receiving signaling data of a target user's trip sent by a base station, assigning a hash value to the signaling data;

[0013] Determine whether the hash value corresponding to the currently received signaling data is repeated with the stored hash value;

[0014] If yes, deleting the signaling data currently received;

[0015] If not, the currently received signaling data is added to the travel data set.

[0016] Optionally, mapping the location information in the travel data set into a map model to obtain the transportation hubs passed by the target user and the travel trajectory of the target user includes:

[0017] Mapping the location information in the travel data set to the map model one by one, and determining the transportation hubs along the route of the target user through the regional scope of the transportation hubs;

[0018] All the location points corresponding to the location information are connected in sequence according to the time sequence of the route to obtain the travel trajectory of the target user.

[0019] Optionally, determining the travel tool used by the target user includes:

[0020] The means of transportation used by the target user is determined according to the type of the transportation hub.

[0021] Optionally, determining the travel tool used by the target user according to the type of the transportation hub is specifically:

[0022] When the transportation hub is a multi-transportation hub, the travel tool used by the target user at the multi-transportation hub is determined based on the single-transportation hubs that are adjacent to and before the multi-transportation hub in the travel trajectory.

[0023] Optionally, the starting point and the end point of the travel section are determined by the following steps:

[0024] Determine the starting point of use of the travel tool by sending first signaling data to the server through the first base station corresponding to the travel tool;

[0025] The last point of use of the travel tool is determined by the final signaling data sent to the server by the last base station corresponding to the travel tool.

[0026] Optionally, the method further comprises:

[0027] The passing point data between the starting point and the end point of each travel section is deleted.

[0028] The second aspect of the present invention provides a passenger hub user travel characteristics analysis system based on signaling data, including:

[0029] The travel data acquisition module is used to obtain the signaling data of the target user's travel and perform data deduplication operations to obtain a travel data set;

[0030] A travel trajectory construction module is used to map the location information in the travel data set to a map model, obtain the transportation hubs passed by the target user, and the travel trajectory of the target user; wherein the travel trajectory includes: the connection routes between the transportation hubs;

[0031] A travel tool determination module, used to determine the travel tool used by the target user;

[0032] A travel segment division module, used for dividing the travel trajectory based on the travel tool to obtain corresponding travel segments;

[0033] A data summary module, used to obtain summary data of the target user in all the travel sections; wherein the summary data includes: the starting point, the end point, the timestamp and the travel tool corresponding to each of the travel sections;

[0034] The travel characteristics analysis module is used to perform statistical analysis on the summary data to obtain the travel characteristics of the target user.

[0035] An embodiment of the third aspect of the present invention provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute the method for analyzing travel characteristics of passenger hub users based on signaling data as described in any embodiment of the first aspect above.

[0036] An embodiment of the fourth aspect of the present invention provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the method for analyzing travel characteristics of users in a passenger hub based on signaling data as described in any embodiment of the first aspect above.

[0037] Compared with the prior art, the embodiments of the present invention provide a method, system, computer-readable storage medium and electronic device for analyzing the travel characteristics of users at a passenger hub based on signaling data, the method comprising: obtaining the signaling data of the target user's travel, and performing data deduplication operations to obtain a travel data set; mapping the location information in the travel data set to a map model to obtain the transportation hubs passed by the target user, and the travel trajectory of the target user; determining the travel tool used by the target user; dividing the travel trajectory based on the travel tool to obtain the corresponding travel sections; obtaining the summary data of the target user in all travel sections; wherein the summary data includes: the starting point, end point, timestamp and travel tool corresponding to each travel section; performing statistical analysis on the summary data to obtain the travel characteristics of the target user. The present invention can effectively obtain the travel characteristics of users at passenger hubs by processing and analyzing the signaling data of user travel, thereby providing a more flexible and dynamic adjustment basis for public transportation scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of an embodiment of a method for analyzing travel characteristics of passenger hub users based on signaling data provided by the present invention;

[0039] Figure 2 It is a structural schematic diagram of an embodiment of a passenger hub user travel characteristics analysis system based on signaling data provided by the present invention;

[0040] Figure 3 It is a structural schematic diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this technical field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 , is a flow chart of an embodiment of a method for analyzing travel characteristics of passenger hub users based on signaling data provided by the present invention.

[0043] The first aspect of the present invention provides a method for analyzing the travel characteristics of passenger hub users based on signaling data, which is executed by a server. The method includes steps S11 to S16, which are as follows:

[0044] Step S11: Acquire the signaling data of the target user's travel, and perform a data deduplication operation to obtain a travel data set;

[0045] Step S12: Mapping the location information in the travel data set to a map model, obtaining the transportation hubs passed by the target user, and the travel trajectory of the target user; wherein the travel trajectory includes: the connection routes between the transportation hubs;

[0046] Step S13: Determine the travel tool used by the target user;

[0047] Step S14: dividing the travel trajectory based on the travel tool to obtain corresponding travel sections;

[0048] Step S15: Obtain summary data of the target user in all the travel sections; wherein the summary data includes: the starting point, the end point, the timestamp and the travel tool corresponding to each of the travel sections;

[0049] Step S16: Perform statistical analysis on the summary data to obtain the travel characteristics of the target user.

[0050] It should be noted that signaling data refers to the communication signal data between a mobile device and a mobile network, including: the location information of the mobile device and the network connection status, etc. When obtaining the signaling data of the target user's travel, the signaling data of the mobile terminal is first collected in real time through the base station, and then the signaling data collected by the base station is sent to the server.

[0051] It is worth noting that a transportation hub is a place for users to travel, such as a bus station, a subway station, a railway station, and an airport. When a target user needs to travel, the user first arrives at the transportation hub, and when the user enters the transportation hub or passes through the transportation hub by means of transportation, the base station collects the signaling data of the target user's mobile terminal, and then imports the signaling data into the map model of the server, and obtains the departure place, arrival place, and itinerary trajectory of the user's travel through the map model.

[0052] In the specific implementation, first, the signaling data of the target user is collected through the base station, and the collected signaling data is sent to the server. Then, the location information in the travel data set is imported into the map model, so that the location information can display the corresponding punctuation on the map, and the travel trajectory of the target user is determined by these punctuation. Next, the travel tool used by the user is determined, and the travel trajectory is divided according to the travel tools used between different hubs to obtain the travel section corresponding to each travel tool. Subsequently, the data information of the target user in all travel sections is summarized and constituted as summary data; the summary data includes but is not limited to the starting point, end point, travel tool used, and travel timestamp of the target user in the corresponding travel section. Finally, the summary data is statistically analyzed to obtain the travel characteristics of the target user, and the travel characteristics are displayed on the interface.

[0053] In step S16, the summary data is statistically analyzed, mainly including: location data analysis, travel pattern analysis, time data analysis and travel mode analysis. Location data analysis is to analyze the user's travel trajectory, frequented places and travel frequency through the user's location data. By analyzing the user's travel pattern, information such as their workplace, residence and points of interest can be inferred. Time data analysis focuses on analyzing the user's travel time distribution, so as to understand their commuting time, leisure time and commuting habits. Travel mode analysis focuses on the user's travel mode selection, helping transportation planners to deeply understand the user's preferences and needs for different transportation modes, and providing strong technical support for optimizing the public transportation system.

[0054] In an optional embodiment, the acquiring of the signaling data of the target user's travel and performing a data deduplication operation to obtain a travel data set includes:

[0055] Each time when receiving signaling data of a target user's trip sent by a base station, assigning a hash value to the signaling data;

[0056] Determine whether the hash value corresponding to the currently received signaling data is repeated with the stored hash value;

[0057] If yes, deleting the signaling data currently received;

[0058] If not, the currently received signaling data is added to the travel data set.

[0059] It should be noted that each time the server receives signaling data sent by the base station, it will create a unique hash value for the new / currently received signaling data, and quickly determine whether the new signaling data is repeated through the stored hash value. Specifically, when new signaling data d is received, a hash value of the signaling data d is created based on h(d)=hash(d), and a check is made as to whether h(d) exists in the stored hash value; if so, the new signaling data d is deleted, otherwise, the new signaling data d is added to the travel data set.

[0060] It is worth noting that the signaling data is obtained through the following steps:

[0061] (1) When the user is located in the area of ​​a transportation hub, the base station collects signaling data from the user's mobile terminal;

[0062] (2) After the base station collects the user's signaling data, it sends the signaling data to the server through the transmission module.

[0063] Every time a user arrives at a transportation hub, the base station collects signaling data and transmits the signaling data to the server. Therefore, the server can obtain the transportation hub information of all the routes along the target user's travel route.

[0064] In an optional embodiment, mapping the location information in the travel data set into a map model to obtain the transportation hubs passed by the target user and the travel trajectory of the target user includes:

[0065] Mapping the location information in the travel data set to the map model one by one, and determining the transportation hubs along the route of the target user through the regional scope of the transportation hubs;

[0066] All the location points corresponding to the location information are connected in sequence according to the time sequence of the route to obtain the travel trajectory of the target user.

[0067] It should be noted that the map model has been imported into the server in advance, and the map model includes: the marking of the hub location and the text annotation of the hub. Therefore, once the location information in the travel data set is connected to the map model, the location marking of the target user can be displayed in the map model and the transportation hubs of all routes can be determined.

[0068] A map model is a computer data model used to describe geographic information in the real world. When the embodiment of the present invention is used, the traffic hubs along the way are specially marked on the map model, and the travel tools used are marked on the corresponding traffic hubs. When the location information is extracted from the collected signaling data, the travel tools used by the user at the hub can be directly displayed through the corresponding traffic hub.

[0069] On the map model, the location of each transportation hub is represented by an interval. When the user is located in a transportation hub, the base station collects the user's signaling data and transmits the collected signaling data to the server. The server then transmits the signaling data to the map model. The map model extracts the location information in the signaling data, maps the location information to the map, and determines the corresponding transportation hub interval. The map model displays the location information in the form of points, so that the user's location can be quickly located. When the user moves to the next transportation hub by means of transportation, the base station collects the user's signaling data again and repeats the above steps. After each update, a new point will be added to the map model, and eventually the user's complete travel trajectory will be formed by connecting multiple transportation hubs.

[0070] In an optional embodiment, determining the travel tool used by the target user includes:

[0071] The means of transportation used by the target user is determined according to the type of the transportation hub.

[0072] It should be noted that a transportation hub is a location for users to travel, such as a bus station, a subway station, a railway station, and an airport. The embodiment of the present invention needs to first import the location information in the travel data set into the map model, obtain the transportation hubs that the target user passes through, and then determine the travel tool used by the target user through the type of transportation hub displayed in the map model.

[0073] In an optional embodiment, determining the travel tool used by the target user according to the type of the transportation hub is specifically:

[0074] When the transportation hub is a multi-transportation hub, the travel tool used by the target user at the multi-transportation hub is determined based on the single-transportation hubs that are adjacent to and before the multi-transportation hub in the travel trajectory.

[0075] It should be noted that if the transportation hub along the route is a single-type transportation hub, the travel tool used by the target user at the single-type transportation hub can be directly determined. If the transportation hub is a multi-type transportation hub (not a single-type transportation hub), it is necessary to determine the travel tool used by the target user at the multi-type transportation hub through the single-type transportation hubs adjacent to and before the multi-type transportation hub in the travel trajectory.

[0076] In other words, when the i-th, j-th, and k-th points (i>j>k) in a certain journey are all single-vehicle hubs, it is directly determined that the target user uses this single vehicle in this journey. When the i-th and k-th points are multiple-vehicle hubs, the vehicle / travel tool used in this journey is determined by the hubs passed in the middle (such as the j-th point).

[0077] In an optional embodiment, the starting point and the end point of the travel section are determined by the following steps:

[0078] Determine the starting point of use of the travel tool by sending first signaling data to the server through the first base station corresponding to the travel tool;

[0079] The last point of use of the travel tool is determined by the final signaling data sent to the server by the last base station corresponding to the travel tool.

[0080] It should be noted that the starting point is determined by receiving the first signaling data from the first base station in the same travel section, the end point is determined by receiving the final signaling data from the last base station in the same travel section, and the passing point is the location information point corresponding to the signaling data located between the starting point and the end point in the same travel section.

[0081] In an optional embodiment, the method further includes:

[0082] The passing point data between the starting point and the end point of each travel section is deleted.

[0083] It should be noted that for a trip (travel segment) using the same travel tool, the server only retains the starting point data and the end point data of the travel segment, and the data of the passing points between the two will be deleted. By deleting the passing point data, the server's storage requirements can be reduced, thereby improving overall performance. When storage pressure is reduced, the server can allocate more resources to other computing and processing tasks, thereby improving response speed and concurrent processing capabilities.

[0084] It is worth noting that the acquisition process of the target user's summary data in all travel sections includes: data reception, data classification, data storage and data backup. Data reception refers to receiving the signaling data corresponding to the starting point and end point of each travel section; data classification is to classify the data according to the user's travel location, time and travel mode; data storage is to store the classified data in the server; data backup is to back up the stored data.

[0085] After receiving data transmitted by a server, the embodiment of the present invention first classifies the data, stores the classified data separately, and then backs up the stored data to prevent the situation where data cannot be restored due to data loss.

[0086] Specifically, the data classification process is to process the received data according to time, location and travel mode, and save them separately. This classification method helps to intuitively display the user's preferred travel time period, frequented locations and transportation methods when evaluating the user's travel. Data backup is to use the backup data to restore the original data in unexpected situations such as data loss, hardware failure or virus attack, so as to ensure the integrity and reliability of the data. The backup mechanism provides effective protection and emergency recovery capabilities for the data, which can effectively reduce the risk of data loss or damage.

[0087] See also Figure 2 , is a structural diagram of an embodiment of a passenger hub user travel characteristics analysis system based on signaling data provided by the present invention.

[0088] The second aspect of the present invention provides a passenger hub user travel characteristics analysis system based on signaling data, which is used to implement the passenger hub user travel characteristics analysis method based on signaling data described in any embodiment of the first aspect, and the system includes:

[0089] The travel data acquisition module 11 is used to acquire the signaling data of the target user's travel and perform data deduplication operation to obtain a travel data set;

[0090] The travel trajectory construction module 12 is used to map the location information in the travel data set to a map model, and obtain the transportation hubs passed by the target user, as well as the travel trajectory of the target user; wherein the travel trajectory includes: the connection routes between the transportation hubs;

[0091] A travel tool determination module 13, used to determine the travel tool used by the target user;

[0092] A travel segment division module 14 is used to divide the travel trajectory based on the travel tool to obtain corresponding travel segments;

[0093] The data summary module 15 is used to obtain the summary data of the target user in all the travel sections; wherein the summary data includes: the starting point, the end point, the timestamp and the travel tool corresponding to each travel section;

[0094] The travel characteristics analysis module 16 is used to perform statistical analysis on the summary data to obtain the travel characteristics of the target user.

[0095] It should be noted that the passenger hub user travel characteristics analysis system based on signaling data provided in the embodiment of the second aspect of the present invention can realize all the processes of the passenger hub user travel characteristics analysis method based on signaling data described in any embodiment of the first aspect above, and the functions of each module in the system and the technical effects achieved are respectively the same as the functions and technical effects achieved by the passenger hub user travel characteristics analysis method based on signaling data described in the embodiment of the first aspect above, and will not be repeated here.

[0096] An embodiment of the third aspect of the present invention provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute the method for analyzing travel characteristics of passenger hub users based on signaling data as described in any one of the above-mentioned first aspects.

[0097] See also Figure 3 , is a structural diagram of an embodiment of an electronic device provided by the present invention.

[0098] An embodiment of the fourth aspect of the present invention provides an electronic device, comprising a processor 21, a memory 22, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the method for analyzing travel characteristics of users in a passenger hub based on signaling data as described in any one of the first aspects above when executing the computer program.

[0099] Preferably, the computer program can be divided into one or more modules / units (such as computer program 1, computer program 2, ...), and the one or more modules / units are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules / units can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0100] The processor 21 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or the processor 21 can also be any conventional processor. The processor 21 is the control center of the electronic device, and various parts of the electronic device are connected using various interfaces and lines.

[0101] The memory 22 mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function, etc., and the data storage area can store related data, etc. In addition, the memory 22 can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, and a flash card (Flash Card), etc., or the memory 22 can also be other volatile solid-state storage devices.

[0102] It should be noted that the above electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that Figure 3The structural diagram shown is only a structural example of the above-mentioned electronic device, and does not constitute a structural limitation of the above-mentioned electronic device. The above-mentioned electronic device may include more or less components than shown in the figure, or a combination of certain components, or different components.

[0103] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for analyzing the travel characteristics of passenger hub users based on signaling data, characterized in that: Executed by a server, the method includes: Obtain the signaling data of the target user's travel, and perform data deduplication operations to obtain a travel data set; Mapping the location information in the travel data set into a map model to obtain the transportation hubs passed by the target user and the travel trajectory of the target user; wherein the travel trajectory includes: the connecting routes between the transportation hubs; Determining the means of transportation used by the target user; Dividing the travel trajectory based on the travel tool to obtain corresponding travel sections; Obtain summary data of the target user in all the travel sections; wherein the summary data includes: the starting point, the end point, the timestamp and the travel tool corresponding to each of the travel sections; Statistical analysis is performed on the summary data to obtain travel characteristics of the target user.

2. The method for analyzing the travel characteristics of passenger hub users based on signaling data according to claim 1, characterized in that: The signaling data of the target user's travel is obtained, and the data deduplication operation is performed to obtain a travel data set, including: Each time when receiving signaling data of a target user's trip sent by a base station, assigning a hash value to the signaling data; Determine whether the hash value corresponding to the currently received signaling data is repeated with the stored hash value; If yes, deleting the signaling data currently received; If not, the currently received signaling data is added to the travel data set.

3. The method for analyzing the travel characteristics of passenger hub users based on signaling data according to claim 1, characterized in that: Mapping the location information in the travel data set to a map model to obtain the transportation hubs passed by the target user and the travel trajectory of the target user includes: Mapping the location information in the travel data set to the map model one by one, and determining the transportation hubs along the route of the target user through the regional scope of the transportation hubs; All the location points corresponding to the location information are connected in sequence according to the time sequence of the route to obtain the travel trajectory of the target user.

4. The method for analyzing the travel characteristics of passenger hub users based on signaling data according to claim 1, characterized in that: The determining of the travel tool used by the target user includes: The means of transportation used by the target user is determined according to the type of the transportation hub.

5. The method for analyzing the travel characteristics of passenger hub users based on signaling data according to claim 4, characterized in that: The determining, according to the type of the transportation hub, the travel tool used by the target user is specifically: When the transportation hub is a multi-transportation hub, the travel tool used by the target user at the multi-transportation hub is determined based on the single-transportation hubs that are adjacent to and before the multi-transportation hub in the travel trajectory.

6. The method for analyzing the travel characteristics of passenger hub users based on signaling data according to claim 1, characterized in that: The starting point and the end point of the travel section are determined by the following steps: Determine the starting point of use of the travel tool by sending first signaling data to the server through the first base station corresponding to the travel tool; The last point of use of the travel tool is determined by the final signaling data sent to the server by the last base station corresponding to the travel tool.

7. The method for analyzing the travel characteristics of passenger hub users based on signaling data according to claim 1, characterized in that: The method further comprises: The passing point data between the starting point and the end point of each travel section is deleted.

8. A passenger hub user travel characteristics analysis system based on signaling data, characterized in that: include: The travel data acquisition module is used to obtain the signaling data of the target user's travel and perform data deduplication operations to obtain a travel data set; A travel trajectory construction module is used to map the location information in the travel data set to a map model, obtain the transportation hubs passed by the target user, and the travel trajectory of the target user; wherein the travel trajectory includes: the connection routes between the transportation hubs; A travel tool determination module, used to determine the travel tool used by the target user; A travel segment division module, used for dividing the travel trajectory based on the travel tool to obtain corresponding travel segments; A data summary module, used to obtain summary data of the target user in all the travel sections; wherein the summary data includes: the starting point, the end point, the timestamp and the travel tool corresponding to each of the travel sections; The travel characteristics analysis module is used to perform statistical analysis on the summary data to obtain the travel characteristics of the target user.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute the method for analyzing travel characteristics of passenger hub users based on signaling data as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When executing the computer program, the processor implements the method for analyzing travel characteristics of users in a passenger hub based on signaling data as described in any one of claims 1 to 7.

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