Public transportation trajectory identification method and device, electronic equipment and storage medium

Abstract

The application provides a public transport trajectory identification method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining potential passengers based on public transport stop point signals and 5G trajectory data of a user; marking a target station with the earliest time in the 5G network trajectory data of the potential passengers and a time period when the potential passengers appear at the target station; matching public transport vehicles passing through the target station one by one; obtaining the overall deviation of each route section from the target station to subsequent stations for each potential public transport vehicle and the user based on the 5G network trajectory data of the user, trajectory line data of the potential public transport vehicle and a timetable; and determining the user trajectory based on the overall deviation. The application can more accurately identify the user's travel mode of taking public transport.

Description

Technical Field

[0001] This invention relates to the field of traffic analysis, and more particularly to a method, apparatus, electronic device, and storage medium for identifying public transportation trajectories. Background Technology

[0002] Ensuring residents' travel is a crucial mission of urban transportation planning. Timely understanding of urban residents' travel patterns and their evolution not only provides insights into the current state of the city's transportation structure but also offers valuable reference for future urban planning and traffic management.

[0003] Traditional technical solutions suffer from low accuracy in identifying travel modes. With the development of the transportation industry and the increasing variety of travel modes, analysis based on weighted results struggles to identify similar travel modes for users. For long-distance travel, the results for trains and buses are unclear, while for short-distance travel, the results for buses, electric vehicles, etc., are ambiguous. Furthermore, it's difficult to identify user travel trajectories. Public transportation networks are complex, and even if the travel mode is confirmed, multiple routes still exist based on the user's origin and destination, making accurate identification of travel trajectories challenging. Finally, there are deficiencies in identifying individuals entering and exiting public transportation, and the distinction between passengers and staff is unclear. Summary of the Invention

[0004] This invention provides a method and apparatus for identifying public transportation routes, in order to address the technical deficiencies existing in the prior art.

[0005] This invention provides a public transportation trajectory recognition method, comprising:

[0006] Potential passengers are identified based on signals from public transportation stops and users' 5G trajectory data.

[0007] The earliest target station and the time period during which the potential passenger appeared at the target station are marked in the 5G network trajectory data;

[0008] Each public transportation vehicle that passes through the target station is matched one by one. Based on the arrival time of each public transportation vehicle at the target station, the station parking time threshold, and the time period in which it appears at the target station, it is determined whether the public transportation vehicle matches the target station, thereby obtaining potential public transportation vehicles that match the target station.

[0009] Based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicles, the overall deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations.

[0010] The user trajectory is determined based on the overall deviation.

[0011] According to the public transportation trajectory recognition method of the present invention, before determining potential passengers based on public transportation vehicle stop signals and users' 5G trajectory data, the method includes:

[0012] The system uses road testing equipment to acquire the trajectory data of the public transportation vehicle and the 5G network trajectory data of the user. The trajectory data of the public transportation vehicle includes signals from several public transportation vehicle stops. The 5G network trajectory data of the user includes a set of 5G signals covering the stops.

[0013] According to the public transportation trajectory recognition method of the present invention, the step of determining whether a public transportation vehicle matches the target station based on the arrival time of each public transportation vehicle passing through the target station, a station parking time threshold, and the time period during which the vehicle appears at the target station includes:

[0014] like If the public transportation vehicle matches the target station, then the public transportation vehicle is determined to be a match for the target station; otherwise, the public transportation vehicle is determined to be a mismatch for the target station.

[0015] Among them, the Indicates the time it takes for public transportation to arrive at the destination station; Indicates the station parking time threshold. This indicates the time period during which the event occurred at the target site.

[0016] According to the public transportation trajectory recognition method of the present invention, the step of obtaining the overall deviation between each potential public transportation vehicle and the user from each route segment consisting of the target station and several subsequent stations based on the user's 5G network trajectory data, the trajectory route data of the potential public transportation vehicle, and the timetable includes:

[0017] Based on the location information in the user's 5G network trajectory data and the trajectory route data of the potential public transportation vehicles, the spatial deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations.

[0018] Based on the time information in the timetable of potential public transportation vehicles and the user's 5G network trajectory data, the time deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations is obtained.

[0019] Based on the spatial deviation and its first preset weight, the temporal deviation and its second preset weight, the overall deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations.

[0020] According to the public transportation trajectory recognition method of the present invention, the step of determining the user trajectory based on the overall deviation includes:

[0021] The public transportation corresponding to the line segment with the first deviation among all potential public transportation vehicles is identified as the transportation vehicle used by the user, wherein the first deviation is the minimum overall deviation;

[0022] The segment with the first deviation among all potential public transport vehicles is identified as the route of the user's vehicle.

[0023] According to the public transportation trajectory recognition method of the present invention, the step of determining the user trajectory based on the overall deviation includes:

[0024] Compare the first deviation among all potential public transportation modes with the preset deviation threshold;

[0025] The public transportation vehicle corresponding to the line segment with the first deviation less than the preset deviation threshold and the smallest first deviation is identified as the transportation vehicle used by the user.

[0026] If the minimum deviation is not less than the preset deviation threshold, then the user is determined to be a non-passenger.

[0027] According to the public transportation trajectory recognition method of the present invention, after determining the user trajectory based on the overall deviation, the method includes:

[0028] The subsequent stations in the user's mode of transportation are determined as the arrival stations, and the stations along the way between the target station and the arrival stations are determined as intermediate stations.

[0029] Based on the trajectory data of the public transportation vehicle, the target station, and the arrival station, the user's boarding and departure times are determined.

[0030] The user's stay duration is obtained based on the travel time and departure time;

[0031] The user's identity is identified based on the user's dwell time and a preset threshold for staff dwell time.

[0032] The present invention also provides a public transportation trajectory recognition device, comprising:

[0033] The potential passenger identification module is used to identify potential passengers based on public transportation stop signals and users' 5G trajectory data.

[0034] A time stamping module is used to mark the earliest target station and the time period in which the potential passenger appeared in the 5G network trajectory data;

[0035] The matching module is used to match public transportation vehicles that pass through the target station one by one. Based on the arrival time of each public transportation vehicle at the target station, the station parking time threshold, and the time period in which it appears at the target station, it determines whether the public transportation vehicle matches the target station and obtains potential public transportation vehicles that match the target station.

[0036] The overall deviation determination module is used to obtain the overall deviation between each potential public transportation vehicle and the user from each line segment consisting of the target station to several subsequent stations, based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicle.

[0037] The trajectory determination module is used to determine the user trajectory based on the overall deviation.

[0038] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the above-described public transportation trajectory recognition methods.

[0039] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described public transportation trajectory recognition methods.

[0040] This invention uses public transportation stop signals and user 5G trajectory data to obtain the overall deviation between each potential public transportation vehicle and the user, which is composed of each route segment from the target station to several subsequent stations. Based on the overall deviation, the user's travel mode of taking public transportation can be more accurately identified, and the user's trajectory and specific time of boarding and leaving public transportation can be obtained. This is of great significance for traffic network optimization and dynamic scheduling. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0042] Figure 1 This is one of the flowcharts illustrating the public transportation trajectory recognition method provided by the present invention;

[0043] Figure 2 This is a schematic diagram of the public transportation trajectory recognition device provided by the present invention;

[0044] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0046] The following is combined Figure 1 A public transportation trajectory recognition method according to the present invention is described, the method comprising:

[0047] S1. Based on public transportation stop signals and users' 5G trajectory data, potential passengers are identified;

[0048] Public transportation itself has a fixed travel trajectory, and each public transportation vehicle has a corresponding fixed public transportation route. If the user's 5G trajectory data contains... and public transportation stop signals The intersection of these two sets is not empty. If the intersection is empty, the passenger is identified as a potential passenger. If the intersection is empty, the passenger is not a potential passenger and is ignored. The following analysis will focus only on potential passengers.

[0049] S2. Mark the earliest target station and the time period when the potential passenger appeared at the target station in the 5G network trajectory data;

[0050] Mark the earliest stop in the 5G network trajectory data of potential passengers as target station X and the time period in which they appear at target station X. .in, This indicates the time of appearance at the target station X in the trajectory. This indicates the departure time at the target station X in the trajectory.

[0051] S3. Match each public transportation vehicle that passes through the target station one by one. Based on the arrival time of each public transportation vehicle that passes through the target station, the station parking time threshold, and the time period in which it appears at the target station, determine whether the public transportation vehicle matches the target station and obtain potential public transportation vehicles that match the target station.

[0052] The arrival time of public transportation at the destination station is Station parking time threshold It is pre-set. This indicates the time period that occurs at the target site X. Vehicles listed are recorded as potential public transport route vehicles. If the field is empty, they are not recorded as potential public transport route vehicles and are ignored. Further analysis is only conducted on vehicles recorded as potential public transport route vehicles.

[0053] S4. Based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicles, obtain the overall deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations.

[0054] S5. Based on the overall deviation, determine the user trajectory.

[0055] The trajectory with the smallest overall deviation can be used as the basis for determining the user's trajectory, thus selecting the user trajectory that best matches reality.

[0056] According to the public transportation trajectory recognition method of the present invention, before determining potential passengers based on public transportation vehicle stop signals and users' 5G trajectory data, the method includes:

[0057] The system uses road testing equipment to acquire the trajectory data of the public transportation vehicle and the 5G network trajectory data of the user. The trajectory data of the public transportation vehicle includes signals from several public transportation vehicle stops. The 5G network trajectory data of the user includes a set of 5G signals covering the stops.

[0058] This invention uses public transportation stop signals and user 5G trajectory data to obtain the overall deviation between each potential public transportation vehicle and the user, which is composed of each route segment from the target station to several subsequent stations. Based on the overall deviation, the user's travel mode of taking public transportation can be more accurately identified, and the user's trajectory and specific time of boarding and leaving public transportation can be obtained. This is of great significance for traffic network optimization and dynamic scheduling.

[0059] According to the public transportation trajectory recognition method of the present invention, the step of determining whether a public transportation vehicle matches the target station based on the arrival time of each public transportation vehicle passing through the target station, a station parking time threshold, and the time period during which the vehicle appears at the target station includes:

[0060] like If the public transportation vehicle matches the target station, then the public transportation vehicle is determined to be a match for the target station; otherwise, the public transportation vehicle is determined to be a mismatch for the target station.

[0061] Among them, the Indicates the time it takes for public transportation to arrive at the destination station; Indicates the station parking time threshold. This indicates the time period during which the event occurred at the target site.

[0062] According to the public transportation trajectory recognition method of the present invention, the step of obtaining the overall deviation between each potential public transportation vehicle and the user from each route segment consisting of the target station and several subsequent stations based on the user's 5G network trajectory data, the trajectory route data of the potential public transportation vehicle, and the timetable includes:

[0063] Based on the location information in the user's 5G network trajectory data and the trajectory route data of the potential public transportation vehicles, the spatial deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations.

[0064] Based on the time information in the timetable of potential public transportation vehicles and the user's 5G network trajectory data, the time deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations is obtained.

[0065] Based on the spatial deviation and its first preset weight, the temporal deviation and its second preset weight, the overall deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations.

[0066] Spatial deviation calculation is based on Distance, formula as follows ,in The spatial deviation from target station X to subsequent station i. Let X be the edit distance from the target station X to the subsequent station i, where the user trajectory converges to the vehicle trajectory. Let X be the number of 5G signals for the vehicle trajectory from the target station X to the subsequent station i. No processing is done for the location points deleted when the user trajectory converges. For the added location points, the time is divided equally by combining the start time of the preceding and following points to get the start time of the added point.

[0067] The calculation of spatial deviation and temporal deviation can be performed in any order; the temporal deviation can be calculated first, followed by the spatial deviation.

[0068] The calculation method for time deviation of several stations is as follows:

[0069]

[0070] in Let x be the time deviation from the target station x to the subsequent station i, where The time it takes for the user to arrive at station n+1, where This represents the time it takes for the vehicle to arrive at station n+1.

[0071] The spatial deviation is weighted by a first preset weight, and the temporal deviation is weighted by a first preset weight. The two weights are then added together to obtain the overall deviation between each potential public transport vehicle and the user for each route segment consisting of the target station and several subsequent stations. Both the first preset weight and the second preset weight are real numbers, and the first preset weight can be set to be greater than the second preset weight.

[0072] For example, the route from the target station to the first, second, third, and so on, can constitute the first, second, third, and so on of each subsequent station. Each potential public transportation vehicle may have multiple route segments. Here, based on the spatial and temporal deviations of each route segment, the overall deviation of each route segment is calculated. The specific number of route segments can be determined based on the user's 5G trajectory data and public transportation vehicle stop signals.

[0073] According to the public transportation trajectory recognition method of the present invention, the step of determining the user trajectory based on the overall deviation includes:

[0074] The public transportation corresponding to the line segment with the first deviation among all potential public transportation vehicles is identified as the transportation vehicle used by the user, wherein the first deviation is the minimum overall deviation;

[0075] The segment with the first deviation among all potential public transport vehicles is identified as the route of the user's vehicle.

[0076] According to the public transportation trajectory recognition method of the present invention, the step of determining the user trajectory based on the overall deviation includes:

[0077] Compare the first deviation among all potential public transportation modes with the preset deviation threshold;

[0078] The public transportation vehicle corresponding to the line segment with the first deviation less than the preset deviation threshold and the smallest first deviation is identified as the transportation vehicle used by the user.

[0079] If the minimum deviation is not less than the preset deviation threshold, then the user is determined to be a non-passenger.

[0080] A preset deviation threshold can be used to identify whether a user is a passenger or a non-passenger.

[0081] from Capture user trajectory at the starting point Non-passenger personnel from The process begins at the starting point and ends if the user has no subsequent trajectory. If there is a subsequent trajectory, the public transportation trajectory recognition method of this invention can be used to determine whether there are any further records of taking public transportation.

[0082] According to the public transportation trajectory recognition method of the present invention, after determining the user trajectory based on the overall deviation, the method includes:

[0083] The subsequent stations on the user's transportation route are identified as arrival stations, and the stations along the way between the target station and the arrival station are identified as intermediate stations.

[0084] In particular, for fixed trajectories where there is little or no interference from other modes of transportation, it is only necessary to match the station areas. For example, for airplanes, it is only necessary to match the departure and arrival areas, and the minimum deviation between the area and time is the route taken.

[0085] According to the public transportation trajectory recognition method of the present invention, after determining the user trajectory based on the overall deviation, the method includes:

[0086] Based on the trajectory data of the public transportation vehicle, the target station, and the arrival station, the user's boarding and departure times are determined.

[0087] The user's stay duration is obtained based on the travel time and departure time;

[0088] The user's identity is identified based on the user's dwell time and a preset threshold for staff dwell time.

[0089] Furthermore, the preset thresholds for staff stay duration include thresholds for station staff stay duration, thresholds for potential staff stay duration on public transportation, and thresholds for the number of days per month that staff on public transportation meet the characteristics of potential staff. Thresholds for station staff stay duration on public transportation can be set. The threshold for the duration of potential workers' stay on transportation is The number of days per month that employees on public transportation meet the threshold for potential employee characteristics is [not specified]. For regional stations (such as passenger stations, train stations, and airports), the time spent at the station by non-passenger arrivals must meet the threshold requirements. For those identified as staff at public transportation stations, the opposite indicates users picking up / dropping off passengers or passing through; for users whose routes are identified, the duration of their stay on public transportation today is also considered. The duration of stay on public transportation today is for passengers. And it met the requirements last month. Number of days If the criteria are met, the user is a staff member on public transportation; otherwise, they are a passenger. This invention can not only more accurately determine a user's travel mode and identify their public transportation trajectory, as well as the specific boarding and departure times of public transportation vehicles, but also identify staff members on public transportation vehicles, staff members at public transportation stations, passengers, and users picking up / dropping off passengers / passing by users; it can determine the user identity of relevant personnel in the trajectory and perform refined analysis.

[0090] See Figure 2 The public transportation trajectory recognition device provided by the present invention is described below. The public transportation trajectory recognition device described below can be referred to in correspondence with the public transportation trajectory recognition method described above. The public transportation trajectory recognition device includes:

[0091] The potential passenger identification module 10 is used to identify potential passengers based on public transportation stop signals and users' 5G trajectory data.

[0092] Public transportation itself has a fixed travel trajectory, and each public transportation vehicle has a corresponding fixed public transportation route. If the user's 5G trajectory data contains... and public transportation stop signals The intersection of these two sets is not empty. If the intersection is empty, the passenger is identified as a potential passenger. If the intersection is empty, the passenger is not a potential passenger and is ignored. The following analysis will focus only on potential passengers.

[0093] The time stamping module 20 is used to mark the earliest target station and the time period in which the potential passenger appeared in the 5G network trajectory data.

[0094] Mark the earliest stop in the 5G network trajectory data of potential passengers as target station X and the time period in which they appear at target station X. .

[0095] The matching module 30 is used to match public transportation vehicles that pass through the target station one by one. Based on the arrival time of each public transportation vehicle that passes through the target station, the station parking time threshold, and the time period of its appearance at the target station, it determines whether the public transportation vehicle matches the target station and obtains potential public transportation vehicles that match the target station.

[0096] The arrival time of public transportation at the destination station is Station parking time threshold It is pre-set. This indicates the time period that occurs at the target site X. Vehicles listed are recorded as potential public transport route vehicles. If the field is empty, they are not recorded as potential public transport route vehicles and are ignored. Further analysis is only conducted on vehicles recorded as potential public transport route vehicles.

[0097] The overall deviation determination module 40 is used to obtain the overall deviation between each potential public transportation vehicle and the user from the target station to several subsequent stations based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicle.

[0098] The trajectory determination module 50 is used to determine the user trajectory based on the overall deviation.

[0099] The trajectory with the smallest overall deviation can be used as the basis for determining the user's trajectory, thus selecting the user trajectory that best matches reality.

[0100] According to the public transportation trajectory recognition device of the present invention, the device further includes a data acquisition module, the data acquisition module being used for:

[0101] The system uses road testing equipment to acquire the trajectory data of the public transportation vehicle and the 5G network trajectory data of the user. The trajectory data of the public transportation vehicle includes signals from several public transportation vehicle stops. The 5G network trajectory data of the user includes a set of 5G signals covering the stops.

[0102] According to the public transportation trajectory recognition device of the present invention, the matching module 30 is used for:

[0103] like If the public transportation vehicle matches the target station, then the public transportation vehicle is determined to be a match for the target station; otherwise, the public transportation vehicle is determined to be a mismatch for the target station.

[0104] Among them, the Indicates the time it takes for public transportation to arrive at the destination station; Indicates the station parking time threshold. This indicates the time period during which the event occurred at the target site.

[0105] According to the public transportation trajectory recognition device of the present invention, the overall deviation determination module 40 is used for:

[0106] Based on the location information in the user's 5G network trajectory data and the trajectory route data of the potential public transportation vehicles, the spatial deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations.

[0107] Based on the time information in the timetable of potential public transportation vehicles and the user's 5G network trajectory data, the time deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations is obtained.

[0108] Based on the spatial deviation and its first preset weight, the temporal deviation and its second preset weight, the overall deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations.

[0109] Spatial deviation calculation is based on Distance, formula as follows ,in The spatial deviation from target station X to subsequent station i. Let X be the edit distance from the target station X to the subsequent station i, where the user trajectory converges to the vehicle trajectory. Let X be the number of 5G signals for the vehicle trajectory from the target station X to the subsequent station i. No processing is done for the location points deleted when the user trajectory converges. For the added location points, the time is divided equally by combining the start time of the preceding and following points to get the start time of the added point.

[0110] The calculation of spatial deviation and temporal deviation can be performed in any order; the temporal deviation can be calculated first, followed by the spatial deviation.

[0111] The calculation method for time deviation of several stations is as follows:

[0112]

[0113] in Let x be the time deviation from the target station x to the subsequent station i, where The time it takes for the user to arrive at station n+1, where This represents the time it takes for the vehicle to arrive at station n+1.

[0114] The spatial deviation is weighted by a first preset weight, and the temporal deviation is weighted by a first preset weight. The two weights are then added together to obtain the overall deviation between each potential public transport vehicle and the user for each route segment consisting of the target station and several subsequent stations. Both the first preset weight and the second preset weight are real numbers, and the first preset weight can be set to be greater than the second preset weight.

[0115] For example, the route from the target station to the first, second, third, and so on, can constitute the first, second, third, and so on of each subsequent station. Each potential public transportation vehicle may have multiple route segments. Here, based on the spatial and temporal deviations of each route segment, the overall deviation of each route segment is calculated. The specific number of route segments can be determined based on the user's 5G trajectory data and public transportation vehicle stop signals.

[0116] According to the public transportation trajectory recognition device of the present invention, the trajectory determination module 50 is used for:

[0117] The public transportation corresponding to the line segment with the first deviation among all potential public transportation vehicles is identified as the transportation vehicle used by the user, wherein the first deviation is the minimum overall deviation;

[0118] The segment with the first deviation among all potential public transport vehicles is identified as the route of the user's vehicle.

[0119] According to the public transportation trajectory recognition device of the present invention, the trajectory determination module 50 is used for:

[0120] Compare the first deviation among all potential public transportation modes with the preset deviation threshold;

[0121] The public transportation vehicle corresponding to the line segment with the first deviation less than the preset deviation threshold and the smallest first deviation is identified as the transportation vehicle used by the user.

[0122] If the minimum deviation is not less than the preset deviation threshold, then the user is determined to be a non-passenger.

[0123] A preset deviation threshold can be used to identify whether a user is a passenger or a non-passenger.

[0124] from Capture user trajectory at the starting point Non-passenger personnel from The process begins at the starting point and ends if the user has no subsequent trajectory. If there is a subsequent trajectory, the public transportation trajectory recognition method of this invention can be used to determine whether there are any further records of taking public transportation.

[0125] According to the public transportation trajectory recognition device of the present invention, the device further includes a station determination module, the station determination module being used for:

[0126] The subsequent stations on the user's transportation route are identified as arrival stations, and the stations along the way between the target station and the arrival station are identified as intermediate stations.

[0127] In particular, for fixed trajectories where there is little or no interference from other modes of transportation, it is only necessary to match the station areas. For example, for airplanes, it is only necessary to match the departure and arrival areas, and the minimum deviation between the area and time is the route taken.

[0128] According to the public transportation trajectory recognition device of the present invention, the device further includes a user identity determination module, the user identity determination module being used for:

[0129] Based on the trajectory data of the public transportation vehicle, the target station, and the arrival station, the user's boarding and departure times are determined.

[0130] The user's stay duration is obtained based on the travel time and departure time;

[0131] The user's identity is identified based on the user's dwell time and a preset threshold for staff dwell time.

[0132] Furthermore, the preset thresholds for staff stay duration include thresholds for station staff stay duration, thresholds for potential staff stay duration on public transportation, and thresholds for the number of days per month that staff on public transportation meet the characteristics of potential staff. Thresholds for station staff stay duration on public transportation can be set. The threshold for the duration of potential workers' stay on transportation is The number of days per month that employees on public transportation meet the threshold for potential employee characteristics is [not specified]. For regional stations (such as passenger stations, train stations, and airports), the time spent at the station by non-passenger arrivals must meet the threshold requirements. For those identified as staff at public transportation stations, the opposite indicates users picking up / dropping off passengers or passing through; for users whose routes are identified, the duration of their stay on public transportation today is also considered. The duration of stay on public transportation today is for passengers. And it met the requirements last month. Number of days If the criteria are met, the user is a staff member on public transportation; otherwise, they are a passenger. This invention can not only more accurately determine a user's travel mode and identify their public transportation trajectory, as well as the specific boarding and departure times of public transportation vehicles, but also identify staff members on public transportation vehicles, staff members at public transportation stations, passengers, and users picking up / dropping off passengers / passing by users; it can determine the user identity of relevant personnel in the trajectory and perform refined analysis.

[0133] Figure 3 A schematic diagram of the physical structure of an electronic device is provided. This electronic device may include a processor 310, a communication interface 320, a memory 330, and a communication bus 340. The processor 310, communication interface 320, and memory 330 communicate with each other via the communication bus 340. The processor 310 can invoke logical instructions stored in the memory 330 to execute a public transportation trajectory recognition method, which includes:

[0134] S1. Based on public transportation stop signals and users' 5G trajectory data, potential passengers are identified;

[0135] S2. Mark the earliest target station and the time period when the potential passenger appeared at the target station in the 5G network trajectory data;

[0136] S3. Match each public transportation vehicle that passes through the target station one by one. Based on the arrival time of each public transportation vehicle that passes through the target station, the station parking time threshold, and the time period in which it appears at the target station, determine whether the public transportation vehicle matches the target station and obtain potential public transportation vehicles that match the target station.

[0137] S4. Based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicles, obtain the overall deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations.

[0138] S5. Based on the overall deviation, determine the user trajectory.

[0139] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0140] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the public transportation trajectory recognition method provided by the above methods, the method comprising:

[0141] S1. Based on public transportation stop signals and users' 5G trajectory data, potential passengers are identified;

[0142] S2. Mark the earliest target station and the time period when the potential passenger appeared at the target station in the 5G network trajectory data;

[0143] S3. Match each public transportation vehicle that passes through the target station one by one. Based on the arrival time of each public transportation vehicle that passes through the target station, the station parking time threshold, and the time period in which it appears at the target station, determine whether the public transportation vehicle matches the target station and obtain potential public transportation vehicles that match the target station.

[0144] S4. Based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicles, obtain the overall deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations.

[0145] S5. Based on the overall deviation, determine the user trajectory.

[0146] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the aforementioned public transportation trajectory recognition methods, the method comprising:

[0147] S1. Based on public transportation stop signals and users' 5G trajectory data, potential passengers are identified;

[0148] S2. Mark the earliest target station and the time period when the potential passenger appeared at the target station in the 5G network trajectory data;

[0149] S3. Match each public transportation vehicle that passes through the target station one by one. Based on the arrival time of each public transportation vehicle that passes through the target station, the station parking time threshold, and the time period in which it appears at the target station, determine whether the public transportation vehicle matches the target station and obtain potential public transportation vehicles that match the target station.

[0150] S4. Based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicles, obtain the overall deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations.

[0151] S5. Based on the overall deviation, determine the user trajectory.

[0152] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0153] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for recognizing public transportation routes, characterized in that, include: Potential passengers are identified based on signals from public transportation stops and users' 5G trajectory data. The earliest target station and the time period during which the potential passenger appeared at the target station are marked in the 5G network trajectory data; Each public transportation vehicle that passes through the target station is matched one by one. Based on the arrival time of each public transportation vehicle at the target station, the station parking time threshold, and the time period in which it appears at the target station, it is determined whether the public transportation vehicle matches the target station, thereby obtaining potential public transportation vehicles that match the target station. Based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicles, the overall deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations. Based on the overall deviation, the user trajectory is determined; Specifically, based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicles, the overall deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations is obtained, including: Based on the location information in the user's 5G network trajectory data and the trajectory route data of the potential public transportation vehicles, the spatial deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations. Based on the time information in the timetable of potential public transportation vehicles and the user's 5G network trajectory data, the time deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations is obtained. Based on the spatial deviation and its first preset weight, the temporal deviation and its second preset weight, the overall deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations. The spatial deviation is calculated using the following formula: ； in, The spatial deviation from target station X to subsequent station i. Let X be the edit distance from the target station X to the subsequent station i, where the user trajectory converges to the vehicle trajectory. The number of 5G signals along the vehicle trajectory from target station X to subsequent station i; The time deviation is calculated using the following formula: ； in, The time deviation from target station x to subsequent station i. The time it takes for the user to arrive at station n+1. This represents the time it takes for the vehicle to arrive at station n+1.

2. The public transportation trajectory recognition method according to claim 1, characterized in that, Before identifying potential passengers based on public transportation stop signals and users' 5G trajectory data, the process includes: The system uses road testing equipment to acquire the trajectory data of the public transportation vehicle and the 5G network trajectory data of the user. The trajectory data of the public transportation vehicle includes signals from several public transportation vehicle stops. The 5G network trajectory data of the user includes a set of 5G signals covering the stops.

3. The public transportation trajectory recognition method according to claim 1, characterized in that, The step of determining whether a public transport vehicle matches the target station based on the arrival time of each public transport vehicle passing through the target station, the station's parking time threshold, and the time period it appears at the target station includes: like If the condition is met, the public transportation vehicle is determined to match the target station; otherwise, the public transportation vehicle is determined not to match the target station. Among them, the Indicates the time it takes for public transportation to arrive at the destination station; Indicates the station parking time threshold. This indicates the time period during which the event occurred at the target site.

4. The public transportation trajectory recognition method according to claim 1, characterized in that, The process of determining the user trajectory based on the overall deviation includes: The public transportation corresponding to the line segment with the first deviation among all potential public transportation vehicles is identified as the transportation vehicle used by the user, wherein the first deviation is the minimum overall deviation; The segment with the first deviation among all potential public transport vehicles is identified as the route of the user's vehicle.

5. The public transportation trajectory recognition method according to claim 4, characterized in that, The process of determining the user trajectory based on the overall deviation includes: Compare the first deviation among all potential public transportation modes with the preset deviation threshold; The public transportation vehicle corresponding to the line segment with the first deviation less than the preset deviation threshold and the smallest first deviation is identified as the transportation vehicle used by the user. If the minimum deviation is not less than the preset deviation threshold, then the user is determined to be a non-passenger.

6. The public transportation trajectory recognition method according to claim 5, characterized in that, After determining the user trajectory based on the overall deviation, the process includes: The subsequent stations in the user's mode of transportation are determined as the arrival stations, and the stations along the way between the target station and the arrival stations are determined as intermediate stations. Based on the trajectory data of the public transportation vehicle, the target station, and the arrival station, the user's boarding and departure times are determined. The user's stay duration is obtained based on the travel time and departure time; The user's identity is identified based on the user's dwell time and a preset threshold for staff dwell time.

7. A public transportation trajectory recognition device, characterized in that, include: The potential passenger identification module is used to identify potential passengers based on public transportation stop signals and users' 5G trajectory data. A time stamping module is used to mark the earliest target station and the time period in which the potential passenger appeared in the 5G network trajectory data; The matching module is used to match public transportation vehicles that pass through the target station one by one. Based on the arrival time of each public transportation vehicle at the target station, the station parking time threshold, and the time period in which it appears at the target station, it determines whether the public transportation vehicle matches the target station and obtains potential public transportation vehicles that match the target station. The overall deviation determination module is used to obtain the overall deviation between each potential public transportation vehicle and the user from each line segment consisting of the target station to several subsequent stations, based on the user's 5G network trajectory data, the trajectory route data and timetable of the potential public transportation vehicle. The trajectory determination module is used to determine the user trajectory based on the overall deviation. The overall deviation determination module is used for: Based on the location information in the user's 5G network trajectory data and the trajectory route data of the potential public transportation vehicles, the spatial deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations. Based on the time information in the timetable of potential public transportation vehicles and the user's 5G network trajectory data, the time deviation between each potential public transportation vehicle and the user for each route segment consisting of the target station and several subsequent stations is obtained. Based on the spatial deviation and its first preset weight, the temporal deviation and its second preset weight, the overall deviation between each potential public transportation vehicle and the user is obtained for each route segment consisting of the target station and several subsequent stations. The spatial deviation is calculated using the following formula: ； in, The spatial deviation from target station X to subsequent station i. Let X be the edit distance from the target station X to the subsequent station i, where the user trajectory converges to the vehicle trajectory. The number of 5G signals along the vehicle trajectory from target station X to subsequent station i; The time deviation is calculated using the following formula: ； in, The time deviation from target station x to subsequent station i. The time it takes for the user to arrive at station n+1. This represents the time it takes for the vehicle to arrive at station n+1.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the public transportation trajectory recognition method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the public transportation trajectory recognition method as described in any one of claims 1 to 6.

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