User train number identification method in high-speed rail network perception optimization

Abstract

The invention provides a user train number identification method in high-speed rail network perception optimization, and relates to the technical field of traffic communication, and the method comprises the steps: complementing inevitable stations between any two stations based on the train time table of each train number for the train numbers appearing at the same time at any two stations, and obtaining the complemented train number of the inevitable stations; based on the distance between the base station position and the station in the signaling reported by the terminal of the user, determining the station that the user may pass through; on the basis of a station stop confidence model, determining each station which the user actually passes through from each station which the user possibly passes through; on the basis of each station which the user actually passes through, determining the necessary station complemented train number which the user may take from each necessary station complemented train number; and carrying out space-time matching on the necessary station complemented train number possibly taken by the user and each station actually passed by the user so as to determine the train number actually taken by the user from the necessary station complemented train number possibly taken by the user. The invention aims to reduce the train number identification cost.

Description

Technical Field

[0001] This application relates to the field of transportation communication technology, specifically to a user train number identification method in high-speed rail network perception optimization. Background Technology

[0002] With the rapid expansion of the railway network, higher demands are being placed on the quality of mobile communication services along the lines. Railway wireless networks are characterized by high speed, high mobility, high frequency deviation, sudden surges in passenger flow, serious public network intrusion, and complex scenarios (including complex scenarios such as 8-carriage, 16-carriage, and two-carriage intersections). Therefore, a refined analysis is needed to assess and optimize the wireless network quality, taking into account these characteristics. Currently, two main methods are used for wireless network quality assessment and optimization: drive testing and signaling-based perception analysis. Drive testing collects signal strength (RSRP / SINR) and location information through test terminals to analyze issues such as weak coverage and over-coverage. Signaling-based perception analysis utilizes MR (Measurement Report) and XDR (Signaling Details) data generated by existing network users to correlate user behavior with network performance.

[0003] Road testing is primarily used in the early stages of network construction, such as mobile network testing and acceptance before the opening of high-speed rail lines. Signaling-based perception analysis, on the other hand, is widely used in daily quality assessment and optimization after railway lines open, and is currently the mainstream analytical method. To improve the ability to analyze complex scenarios, some industry researchers have attempted to first identify user train numbers and then perform overall analysis on a train-by-train basis. This approach can effectively support complex scenarios such as 8-carriage trains (obtained by associating train number information), 16-carriage trains, and trains passing each other. However, current signaling-based perception analysis methods generally suffer from the following problems: interference from nearby stations, failure in transfer scenarios, and difficulty in identifying single-stop direct trains within the province. Summary of the Invention

[0004] In view of this, this application provides a user train number identification method in high-speed rail network perception optimization. It aims to solve or partially solve the problems existing in the background technology.

[0005] The first aspect of this application provides a user train number identification method in high-speed rail network perception optimization, the method comprising: Based on the train timetable for each train, for any two trains that appear at the same time, complete the necessary stations between those two stations to obtain the trains with the necessary stations. Based on the distance between the base station location and the site in the signaling reported by the user's terminal, the sites that the user may pass through are determined. Based on the station stop confidence model, the stations that the user actually passed through are determined from the stations that the user may have passed through. Based on the stations the user actually passes through, the train schedules that the user may take are determined from the complete train schedules of each necessary station. The complete train schedules of the stations the user may take are spatiotemporally matched with the stations the user actually passes through, so as to determine the train the user actually takes from the complete train schedules of the stations the user may take.

[0006] A second aspect of this application provides a user train number identification system for high-speed rail network perception optimization, the system comprising: The station completion module is used to complete the necessary stations between any two stations for trains that appear at the same time, based on the train timetable of each train, and obtain the trains with necessary stations. The first route site determination module is used to determine the sites that the user may pass through based on the distance between the base station location and the site in the signaling reported by the user's terminal. The second route station determination module is used to determine the stations that the user actually passes through from the stations that the user may pass through, based on the station stop confidence model. The first train number determination module is used to determine the train numbers that the user may take based on the stations the user actually passes through, from the train numbers supplemented by each necessary station. The second train number determination module is used to perform spatiotemporal matching between the train numbers that the user may take and the stations that the user actually passes through, so as to determine the train number that the user actually takes from the train numbers that the user may take and the stations that the user actually passes through.

[0007] The user train number identification method in high-speed rail network perception optimization provided in this application has the following advantages: The user train number identification method in the high-speed rail network perception optimization provided in this application, based on the train timetable, completes the list of necessary stations between any two stops recorded in the timetable for each train (i.e., stations not recorded in the timetable that the train will pass through but will not stop at), to obtain all the stations that each train must pass through in its entire travel path. Then, based on the distance between the base station location and the station in the signaling reported by the user's terminal, the stations that the user may pass through are determined. Based on the station stop confidence model, the stations that the user actually passes through are determined from the stations that the user may pass through. Based on the stations that the user actually passes through, the train numbers that the user may take are completed from the train numbers completed from each necessary station. The train numbers that the user may take through the completed train numbers are spatiotemporally matched with the stations that the user actually passes through, to determine the train that the user actually takes from the train numbers that the user may take through the completed train numbers. This application utilizes readily available train timetables to construct a station topology structure for user train number identification (e.g., constructing all stations that each train must pass through in its entire journey and using them for user train number identification). Because it employs a station completion method, even for direct trains containing only the origin and destination, it can predict which users will take these trains, thereby improving the robustness and accuracy of train number identification in complex scenarios. It also eliminates the reliance on road testing (e.g., it does not require road testing to determine all stations that each train must pass through in its entire journey), resulting in low implementation costs and enabling 24 / 7 daily production optimization support. Attached Figure Description

[0008] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a flowchart illustrating a user train number identification method in high-speed rail network perception optimization according to one embodiment of this application; Figure 2 This is a schematic diagram illustrating the determination of train connection paths in a user train number identification method in high-speed rail network perception optimization according to an embodiment of this application; Figure 3 This is another flowchart illustrating a user train number identification method in high-speed rail network perception optimization according to one embodiment of this application; Figure 4 This is a schematic diagram illustrating a user train number identification system in high-speed rail network perception optimization, as shown in one embodiment of this application. Detailed Implementation

[0010] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0011] Before describing this application, the background of this application should be explained. Currently, with the rapid expansion of the railway network, higher requirements are being placed on the quality of mobile communication services along the lines. Railway wireless networks are characterized by high speed, high mobility, high frequency deviation, sudden large passenger flows, serious public network intrusion, and complex scenarios (including complex scenarios such as 8-car, 16-car, and two-car intersections). Therefore, a refined analysis of these characteristics is required when conducting wireless network quality assessment and optimization. Currently, two main methods are relied upon for wireless network quality assessment and optimization: road testing and signaling-based perception analysis.

[0012] The drive test method collects signal strength (RSRP / SINR) and location information through test terminals to analyze issues such as weak coverage and over-coverage. The advantage of this approach is its high accuracy, and it allows for manual recording of information in various scenarios; the disadvantages are high testing costs, long testing cycles, and difficulty in routinely supporting daily optimization.

[0013] Signaling-based perception analysis utilizes MR (Measurement Report) and XDR (Signaling Details) data generated by existing network users to correlate user behavior with network performance. The advantages of this approach are low implementation cost and the ability to routinely support daily optimization. However, its disadvantages include difficulty in identifying complex scenarios such as 8-carriage, 16-carriage, or two-carriage intersections, and the fact that network performance analysis is primarily conducted on a passenger-by-passenger basis, failing to support refined railway scenario optimization.

[0014] Currently, drive testing is mainly used in the early stages of network construction, such as mobile network testing and acceptance before the opening of high-speed rail lines. Signaling-based perception analysis, on the other hand, is widely used in daily quality assessment and optimization after railway lines open, and is currently the mainstream analytical method. To improve the ability of signaling-based perception analysis methods to analyze complex scenarios, the industry has attempted a solution that first identifies passenger train numbers and then performs overall analysis on a train-by-train basis, which can effectively support complex scenarios such as 8-carriage (obtained by associating train number information), 16-carriage, and two-train intersections. However, current signaling-based perception analysis methods generally suffer from the following problems: Interference from nearby stations. For example, two stations are close in a straight line (e.g., 2 kilometers). For inactive passengers who use the network less, signaling is already sparse. In addition, some trains have short stop times (e.g., 2 minutes), which means that no signaling is reported within a short distance (e.g., 1 kilometer) of the station, making it impossible to accurately identify the train station that stops there.

[0015] The transfer scenario fails. If a user transfers, the origin and destination stations belong to different train numbers, causing the train number to be unidentifiable or incorrectly identified. For example, if a passenger transfers from station A to station B via train number 1, and then from station B to station C via train number 2, the current method will mistakenly identify it as a direct route from station A to station C.

[0016] Identifying single-stop direct trains within a province is difficult. For example, if a train only stops once in a province, the mobile operator in that province only has signaling data within that province and cannot see when it arrives at its destination in another province. The train timetable also doesn't show which stations the train passes through within the province; identification can only be done based on the train's departure time from its originating station, which makes identification very difficult.

[0017] In light of the existing problems such as interference from nearby stations, failure in transfer scenarios, and difficulty in identifying direct trains at single stations, this application provides a user train number identification method that requires no additional road testing, is low-cost, and has high accuracy, in order to achieve the following objectives: accurately identify the necessary stations of train numbers and effectively eliminate false judgments of fake stops at nearby train stations; support the derivation of transfer train numbers; accurately complete the actual necessary stations of direct train numbers that only include the origin and destination, thereby improving the robustness and accuracy of train number identification in complex scenarios.

[0018] refer to Figure 1 , Figure 1 This is a flowchart illustrating a user train number identification method in high-speed rail network perception optimization, as shown in one embodiment of this application. Figure 1 As shown, the method includes: Step S01: Based on the train timetable for each train, for any two trains that appear at the same time, complete the necessary stations between the two stations to obtain the trains with the necessary stations.

[0019] In this embodiment, under railway operation scenarios, each train has its own timetable, which records the stops along its route, as well as the arrival and departure times at each stop. In addition, many trains pass through stations along their routes but do not stop at them; these stations are not recorded in the train's own timetable. The solution provided in this application first performs a completion operation on trains with such stations (i.e., those not recorded in the train's own timetable) to recover all the necessary stops along their routes. Then, based on the recovered results (i.e., all the necessary stops for each train along its route), the subsequent train identification for the user is performed.

[0020] In this embodiment, the entire railway system's network is vast. While the information recorded in a single train's timetable is limited, the information recorded in the timetables of all trains operating within the entire network is abundant. Furthermore, trains within the railway system's network operate in an intersecting manner. Therefore, this application conceives that although a single train's timetable does not record stations it passes through but does not stop at, the abundant information recorded in the timetables of numerous other trains can be used to determine all the necessary stations a single train must pass through. This allows for the completion of the train's train schedule by obtaining the necessary stations corresponding to that train. The completed train schedule is still the same train, but it records all the necessary stations it passes through. For example, if train number 1 stops at stations A, C, and D, its timetable will only record A, C, and D. However, in reality, train number 1 will pass through but not stop at station B between stations A and C. This application supplements the timetable of other train numbers by adding station B, which is a necessary stop between stations A, C, and D of train number 1, to obtain the complete train number corresponding to train number 1 that records all the necessary stops A, B, C, and D of train number 1.

[0021] Specifically, the first step is to obtain the train timetables for all train services in the entire railway system and determine the stations each train will stop at. For all stops of the same train service, there may be a necessary stop between any two adjacent stations that the train will pass through but will not stop at. One possible implementation for determining the necessary stop between any two adjacent stops of the same train service is to obtain all other train timetables including those for the two stations, and based on the information in these other timetables, determine the necessary stop between the two stations. This implementation method can determine the necessary stop between any two adjacent stations of the same train service. Then, based on the determined necessary stops for the train service, the train service is completed to obtain a complete train service with necessary stops. This complete train service record records all necessary stops for the corresponding train service, including stations that the train will stop at and stations that the train will pass through but will not stop at.

[0022] Step S02: Based on the distance between the base station location and the site in the signaling reported by the user's terminal, determine the sites that the user may pass through.

[0023] In this embodiment, signaling reported by the user's terminal device is acquired, and the distance between the base station and each site is determined based on the base station location in the signaling. If the distance between the base station location and a certain site is lower than a preset distance threshold, it is determined that the user may pass through that site.

[0024] Step S03: Based on the station stop confidence model, determine the stations that the user actually passed through from the stations that the user may have passed through.

[0025] In this embodiment, a station stop confidence model is pre-constructed. This model is used to analyze the possible stations a user might pass through, in order to filter out the stations the user actually passes through from the possible stations. One optional implementation is as follows: the closer the base station location in the signaling reported by the user's terminal is to a station, the longer the time spent at that station, and the more indoor distributed cell space is occupied at that station, the higher the station stop confidence model assigns that station a higher stop confidence score. If the stop confidence score corresponding to a station exceeds a set threshold, then that station is determined to be a station the user actually passed through. If no station among a user's possible stations has a stop confidence score exceeding the set threshold, then the user is determined not to be a railway passenger, and the user will not participate in the subsequent train identification.

[0026] Step S04: Based on the stations the user actually passes through, determine the train schedules that the user may take from the complete train schedules of each necessary station.

[0027] In this embodiment, among all the train numbers with mandatory stops obtained through the completion operation in step S01, there is a special type of train. The timetables of these trains already record all the mandatory stops they will pass through, and no completion is performed on these trains during the completion operation. Since the timetables of these trains record all the mandatory stops they will pass through, for ease of description in the subsequent train identification process, this application also refers to them as mandatory stop completed train numbers. After obtaining the stations the user actually passes through in step S03, from all the mandatory stop completed train numbers, it is determined which mandatory stop completed train numbers will pass through the stations the user actually passes through. These mandatory stop completed train numbers that will pass through the stations the user actually passes through are then filtered out. These filtered mandatory stop completed train numbers are determined as the mandatory stop completed train numbers that the user may take.

[0028] Step S05: Perform spatiotemporal matching between the complete train schedules of the stations the user may pass through and the stations the user actually passes through, so as to determine the train the user actually takes from the complete train schedules of the stations the user may pass through.

[0029] In this embodiment, after determining the complete train routes with possible stops for the user through step S04, the stations in these complete train routes are spatiotemporally matched with the stations the user actually travels through. One optional implementation of spatiotemporal matching is as follows: if a station in the complete train routes with possible stops for the user is the same as a station the user actually travels through, then the spatial matching for that station is considered successful. After successful spatial matching, temporal matching is further performed. If, for the spatially matched station, the departure time of the complete train route at that station is very close to the user's latest departure time at that station (e.g., 30 minutes), then the temporal matching for that station is considered successful. Thus, it is determined that the station in the complete train routes with possible stops is spatiotemporally matched with the station the user actually travels through. Using the same implementation, each station in each complete train route with possible stops for the user can be spatiotemporally matched with each station the user actually travels through. After completing all spatiotemporal matching, the number of stations in the complete train schedule that the user may take is counted to find the number of stations that are successfully matched with the stations the user actually takes. The complete train schedule with the most stations that are successfully matched or the highest percentage of stations that are successfully matched is determined as the train schedule the user actually takes. For example, the complete train numbers that a user might take include train numbers a, b, and c. Train number a has 10 stations, of which 6 stations can be successfully matched spatiotemporally with 5 stations that the user actually passes through. Train number b has 20 stations, of which 7 stations can be successfully matched spatiotemporally with 7 stations that the user actually passes through. Train number c has 12 stations, of which 4 stations can be successfully matched spatiotemporally with 4 stations that the user actually passes through. Train number b with the most successfully matched stations (7 stations) is determined as the train number the user actually takes. Alternatively, train number a with the highest ratio of successfully matched stations (0.6 stations) is determined as the train number the user actually takes.

[0030] The user train number identification method in high-speed rail network perception optimization provided in this application is based on easily accessible train timetables and constructs a station topology structure for user train number identification (e.g., constructing all stations that each train must pass through in its entire travel path and using them for user train number identification). Because it uses a station completion method, even for direct trains containing only the origin and destination, it can predict which users will take these trains, thereby improving the robustness and accuracy of train number identification in complex scenarios. It also eliminates the reliance on road testing (e.g., it does not require road testing to determine all stations that each train must pass through in its entire travel path), resulting in low implementation cost and support for 24 / 7 daily production optimization. The station topology structure refers to the connection relationships between stations (which are directional) and the connecting paths between any two stations (a sequential list of stations that must be passed through but not necessarily stopped at when traveling from one station to another).

[0031] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, after determining the actual train numbers taken by multiple users, the method further includes: Step S06: Based on the actual train numbers taken by each user, determine all users who took the same train number.

[0032] In this embodiment, after obtaining a large number of actual train rides taken by users through steps S1 to S5, all users who took the same train ride are determined based on the actual train rides taken by each user.

[0033] Step S07: Divide all users traveling on the same train into a terminal group and analyze the wireless network quality of the terminal group.

[0034] In this embodiment, after obtaining all users traveling on the same train in step S06, the terminals of all users traveling on the same train are grouped into a terminal group. Since a terminal group for the same train has a large number of users and they are all on the same travel route, analyzing the wireless network quality along that route as a cluster provides more effective analysis samples and thus yields more accurate analysis results. Specifically, one terminal group corresponds to one train, and this terminal group consists of the terminals of all users traveling on that train.

[0035] Step S08: Based on the spatiotemporal information of each user for each train, determine the trains that intersect.

[0036] In this embodiment, this application provides another implementation method for analyzing wireless network quality. Specifically, for each train, the specific location of the train at each time moment is determined based on the spatiotemporal information of the users within that train. Then, based on the determined specific locations of each train at each time moment, trains that intersect are identified. For example, based on the spatiotemporal information of the users in train 1, it is determined that train 1 is at location c at time a. Simultaneously, based on the spatiotemporal information of the users in train 2, it is determined that train 2 is also at location c at time a. Therefore, it is determined that train 1 and train 2 intersect at location c at time a. The number of intersecting trains can be multiple, such as three or more. The spatiotemporal information of the users can be determined based on the base station location and time in the signaling reported by the user's terminal device.

[0037] Step S09: For intersecting trains, during the corresponding intersecting time period, perform wireless network quality analysis on all terminal combinations of the intersecting trains.

[0038] In this embodiment, after determining the train numbers that intersect in step S08, wireless network quality analysis is performed on all terminal groups corresponding to the multiple train numbers that intersect during the time period in which the intersect occurs. This method can further increase the number of analysis samples for wireless network quality analysis, thereby improving the accuracy of the analysis.

[0039] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, step S01 may include steps S01_1 to S01_4: Step S01_1: Based on the train timetable for each train, determine the connection relationship between any two stations.

[0040] In this embodiment, this application provides an optional implementation method for station completion. Specifically, the train timetables of all trains in the entire railway network are obtained, and based on these train timetables, the connection relationship between any two stations is determined. This connection relationship includes direct connections within the same train number, adjacent connections within direct connections within the same train number, connections accessible with one transfer, connections accessible with multiple transfers, and inaccessible connections. Two stations having a direct connection within the same train number means that the two stations are in the same train timetable, i.e., the two stations can be reached directly by the same train. Two stations having an adjacent connection within the same direct connection means that the two stations belong to the same direct connection within the same train number, and in all trains where the two stations appear simultaneously, they are directly adjacent. For example, stations A and B only appear in the timetables of three different train numbers, namely ABD, ABEF, and ABGE. It can be seen that in all trains where the two stations appear simultaneously, they are directly adjacent, therefore the relationship between A and B is an adjacent relationship within the same direct connection within the same train number. Two stations are considered reachable with a single transfer if they are not both listed on the timetable of any train service, but can be reached by a single transfer. The determination of whether two stations are reachable with a single transfer is made by checking if there is a direct train connecting them. If so, the two stations are considered reachable with a single transfer. For example, stations A and C form a pair, both of which are directly connected to station B by the same train service. Therefore, A and C are reachable with a single transfer because A to B can be reached by one train, B to C by another train, and A to C can be reached with a single transfer. Two stations are considered reachable with multiple transfers if two or more transfers are required to reach each other. Two stations are considered inaccessible if a finite number of transfers are not possible between them.

[0041] Step S01_2: For the first station and the second station, traverse all trains and determine the initial directed path between the first station and the second station based on the train timetable of trains that appear at both the first station and the second station.

[0042] In this embodiment, both the first station and the second station can be any station in the railway system, but they are different. For the first station and the second station, all train services are traversed, and train services that simultaneously record the first station and the second station are selected from their own timetables. Then, a sequence of stations with the first station and the second station as the starting and ending stations, recorded in the timetables of these train services, is selected as the initial directed path between the first station and the second station.

[0043] For example, assume the first station is B and the second station is E. By iterating through all train schedules, we find three trains whose timetables simultaneously record both the first and second stations: train number 1, train number 2, and train number 3. Train number 1's timetable records stations B, C, E, F, G in sequence; train number 2's timetable records stations A, B, D, E, H, G in sequence; and train number 3's timetable records stations A, B, C, D, E, F, G in sequence. We select the station sequence BCE from train number 1's timetable, which uses station B as the starting and ending station and station E as the ending station, as the initial directed path between B and E. Similarly, we select the station sequence BDE from train number 2's timetable, which uses station B as the starting and ending station and station E as the ending station, as the initial directed path between B and E. Finally, we select the station sequence BCDE from train number 3's timetable, which uses station B as the starting and ending station and station E as the initial directed path between B and E.

[0044] Step S01_3: For the initial directed path between the first station and the second station, if the connection relationship between the first station and the second station is not an adjacent relationship, and the first station and the second station have one and only one common adjacent station, the common adjacent station is determined as a necessary station of the initial directed path between the first station and the second station.

[0045] In this embodiment, the specific connection relationship between any two stations in the entire railway system can be determined through step S01_1, including direct connections on the same train, adjacent connections within direct connections on the same train, connections accessible with one transfer, connections accessible with multiple transfers, and inaccessible connections. Since the first station and the second station are stations in the railway system, the connection relationship between the first station and the second station is also obtained through step S01_1. After obtaining the initial directed path between the first station and the second station through step S01_2, a query is performed on all the connection relationship results obtained in step S01_1 to determine whether the first station and the second station are adjacent. If they are not adjacent, and by querying all train timetables, if it is determined that the first station and the second station have exactly one common adjacent station, then that common adjacent station is determined as a necessary station on the initial directed path between the first station and the second station. Through the same implementation method, for any two stations in the entire railway system, their initial directed path can be determined, and the necessary stations on their initial directed path can also be determined.

[0046] For example, assume the first station is A and the second station is C. By querying all train timetables, we find that the timetables record three stations adjacent to the first station A: B, D, and E. We also find four stations adjacent to the second station C: B, F, G, and H. Since the first station A and the second station C have exactly one common adjacent station B, we determine that station B is a necessary stop between the first station A and the second station C.

[0047] Step S01_4: Complete the initial directed path between the first station and the second station through the necessary stops to obtain the necessary stop complete train number for any two stations that appear at the same time.

[0048] In this embodiment, after obtaining the necessary stations of the initial directed path between the first station and the second station through steps S01_1 to S01_3, the necessary stations are used to complete the initial directed path between the first station and the second station, resulting in the completed directed path between the first station and the second station. If both the first station and the second station appear in the train timetable of a train service, the completed directed path between the first station and the second station is taken as the necessary station for this segment between the first station and the second station in that train service, thereby obtaining the train service complete with the necessary station.

[0049] For example, the timetable for train number 1 sequentially records stations ADEF. Through steps S01_1 to S01_3, the initial directed path for station AD is ACD. Simultaneously, the mandatory station along the initial directed path of station AC is B. Therefore, station B is used to complete the mandatory stations for train number 1, resulting in ABCDEF. Similarly, through steps S01_1 to S01_3, the initial directed path for station DE is DE, which also has no mandatory stations. Likewise, through steps S01_1 to S01_3, the initial directed path for station EF is EF, which also has no mandatory stations. Therefore, after completing the station information for train number 1, the final train number corresponding to the mandatory stations ABCDEF is obtained.

[0050] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, step S01_1 may include steps S01_1a to S01_1e: Step S01_1a: Iterate through all train services, add every two stations in the same train service to the direct train service list, and mark whether each pair of added stations is directly adjacent and which train service they belong to.

[0051] In this embodiment, all train services in the railway system are traversed, and every two stations in the same train service are added to the direct train service list and the corresponding train service is marked. At the same time, it is marked whether the two stations added to the direct train service list are directly adjacent. The criterion for determining whether they are directly adjacent is whether the two stations are adjacent in the train timetable of their respective train services.

[0052] For example, the timetable for train number 1 records stations ABC, and the timetable for train number 2 records stations AB. For train number 1, stations AB are recorded in the direct train list, and the corresponding train number is recorded as train number 1 in this data entry, marking stations AB as directly adjacent. Similarly, stations AC are recorded in the direct train list, and the corresponding train number is recorded as train number 1 in this data entry, marking stations AC as not directly adjacent. Stations BC are also recorded in the direct train list, and the corresponding train number is recorded as train number 1 in this data entry, marking stations BC as directly adjacent. For train number 2, stations AB are recorded in the direct train list, and the corresponding train number is recorded as train number 2 in this data entry, marking stations AB as directly adjacent. The direct train list is a map table where the key is "station 1 name_station 2 name" and the value is a list of connections, including whether the train numbers corresponding to two stations in a data entry are directly adjacent.

[0053] Step S01_1b: Traverse any two stations in the direct train list. If the two stations currently traversed satisfy the condition that they are directly adjacent in all simultaneously occurring trains, determine the connection relationship between the two stations currently traversed as an adjacent relationship.

[0054] In this embodiment, the connection relationship between any two stations in a railway system is determined. Since the implementation method for determining the connection relationship between any two stations in a railway system is the same, a specific pair of stations is used as an example for explanation. First, the list of direct trains with the same train number is traversed. Data entries recording the two stations are selected from the constructed list of direct trains with the same train number. If the adjacent information within these data entries is all directly adjacent, the connection relationship between the two stations is determined to be an adjacent relationship. Through the same implementation method, it is possible to determine whether the connection relationship between any two stations in a railway system is an adjacent relationship.

[0055] For example, if the two stations to be determined are station A and station B, the system iterates through the constructed list of direct trains with the same service, querying the data entries for stations A and B. The final query result includes three data entries: one for train 1 corresponding to stations A and B (this entry records that stations A and B are directly adjacent); one for train 2 corresponding to stations A and B (this entry also records that stations A and B are directly adjacent); and one for train 3 corresponding to stations A and B (this entry also records that stations A and B are directly adjacent). Since all data entries for stations A and B indicate that they are directly adjacent, stations A and B are determined to be adjacent.

[0056] Step S01_1c: If the two stations currently traversed do not meet the condition that they are directly adjacent in all simultaneously occurring train services, determine the connection relationship between the two stations currently traversed as a direct relationship for the same train service.

[0057] In this embodiment, since the implementation method for determining the connection relationship between any two stations in a railway system is the same, we will also use two specific stations as an example for explanation. First, we traverse the list of direct trains with the same train number, and filter out data entries that record the two stations from the constructed list of direct trains with the same train number. If there are records in the adjacent information of these data entries where the two stations are not directly adjacent, then the connection relationship between the two stations is determined to be a direct train relationship. Through the same implementation method, we can determine whether the connection relationship between any two stations in a railway system is a direct train relationship.

[0058] Step S01_1d: If the first station and the second station do not appear in the same data entry in the same direct train list, and there is a third station that is in the same direct train relationship with the first station and the second station respectively, then the connection relationship between the first station and the second station is determined to be a one-transfer reachable relationship.

[0059] In this embodiment, the first station, the second station, and the third station are any stations in the railway system, but they are all different from each other. If the first station and the second station do not appear in the same data entry in the same direct train list, that is, the first station and the second station cannot be directly connected by the same train. However, if a third station exists that is directly connected to the first station by the same train (i.e., the third station and the first station will appear in the same data entry in the same direct train list), and also directly connected to the second station by the same train (i.e., the third station and the second station will appear in the same data entry in the same direct train list), then the connection between the first station and the second station is determined to be a one-transfer reachable relationship. For example, the first station is A and the second station is C. The first station A and the second station C will not appear in the same data entry in the list of direct trains, so they are not considered to be in a direct train relationship. However, the first station A and the third station B can be reached by the same train, and the second station C can also be reached by the same train as the third station B. Therefore, the first station A and the second station C can be reached by one transfer from the first station A to the third station B and then through the third station B to the second station C. Thus, the connection between the first station A and the second station C is determined to be a one-transfer reachable relationship.

[0060] Step S01_1e: If there is no direct train connection or a single transfer connection between the two stations currently being traversed, then the relationship between the two stations currently being traversed is determined to be unreachable.

[0061] In this embodiment, if there is no direct train connection or a single transfer between two stations, the relationship between the two stations currently being traversed is determined to be unreachable. Steps S01_1a to S01_1e can be used to obtain the connection relationship between any two stations in the entire railway system.

[0062] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, step S01_4 may include steps S01_4a to S01_4e: Step S01_4a: Complete the initial directed path between the first station and the second station using the necessary stations to obtain multiple completed directed paths between the first station and the second station.

[0063] In this embodiment, the first and second stations typically appear in multiple train timetables. Therefore, there are usually multiple initial directed paths between the first and second stations. The method for determining the necessary stations for each initial directed path between the first and second stations is the same as in step S01_3, and will not be repeated here. For an initial directed path between the first and second stations, the necessary stations of the determined initial directed path are used to complete the initial directed path, resulting in a corresponding completed directed path. For example, if the initial directed path is ACD, and the necessary station of the determined initial directed path is station B between stations A and C, then station B is used to complete the initial directed path ACD, resulting in the corresponding completed directed path ABCD. By using the same implementation method, multiple initial directed paths between the first and second stations can be completed to obtain multiple corresponding completed directed paths.

[0064] Step S01_4b: Aggregate the multiple completed directed paths between the first station and the second station based on whether they completely contain each other.

[0065] In this embodiment, among the multiple completed directed paths between the first and second stations obtained through step S01_4a, many of these paths may actually correspond to the same path. Therefore, this application will further aggregate these multiple completed directed paths between the first and second stations. Specifically, the stations of the multiple completed directed paths between the first and second stations are compared to determine whether the station of one completed directed path completely contains the station of another completed directed path. If they completely contain each other, the contained completed directed path is aggregated into the other contained completed directed path. This aggregation method is used to aggregate the multiple completed directed paths between the first and second stations until no further aggregation is possible. For example, the multiple completed directed paths between the first and second stations include completed directed paths ABCDE, ACDE, and ADE. Since completed directed paths ABCDE completely contain completed directed paths ACDE and ADE, the three are aggregated, retaining only completed directed paths ABCDE.

[0066] Step S01_4c: If the path obtained after aggregation is a single path, then this path shall be used as the final path between the first site and the second site.

[0067] In this embodiment, if after the aggregation process in step S01_4c, only one complete directed path remains between the first station and the second station, then this complete directed path is determined as the final path between the first station and the second station.

[0068] Step S01_4d: If the path obtained after aggregation is multiple paths, then the shortest path among these multiple paths shall be taken as the final path between the first station and the second station.

[0069] In this embodiment, if multiple completed directed paths remain between the first station and the second station after the aggregation process in step S01_4c, the shortest of these multiple completed directed paths is determined as the final path between the first station and the second station. Using the same implementation method, the final path between every two stations in the railway system can be obtained. This final path is either the unique path between the two stations or the shortest path between the two stations. The final path between two stations is a sequential list of stations that must be passed through, but do not necessarily stop at, to reach another station from one station.

[0070] Step S01_4e: Take the stations on the final path between the first station and the second station as the necessary stations for trains that appear simultaneously at the first station and the second station, and complete the necessary stations for the trains to obtain the trains that appear simultaneously at the first station and the second station.

[0071] In this embodiment, since the station completion method is the same for each train, we will use one train as an example for explanation. We obtain the train timetable for that train and determine the stations the train will stop at sequentially from it. Then, for every two adjacent stations in the timetable, we determine the final path between them. The stations in this final path are considered the train's required stations. We then add any required stations that exist in the final path but are not in the train's timetable to the train's required station list according to the order of the stations in the final path. This yields the train with the required stations completed for that train. This required station completed train list is the same as the original train list, except that it records all the calculated stations the train will pass through (including stations that will stop and stations that will only pass through but not stop at).

[0072] For example, the final path between every two stations in the railway system has been pre-determined. The timetable for train number 1 records the stations as ACDFG in sequence. The final path between two stations AC is ABC, the final path between two stations CD is station CD, the final path between two stations DF is DEF, and the final path between two stations FG is station FG. Therefore, stations B and E are determined to be necessary stops for train number 1. Since station B is between stations AC and station E is between stations DF, station B is added to the ACDFG section of the timetable, and station E is added to the DF section of the ACDFG section. This completes the train number record for all necessary stops ABCDEFG for train number 1.

[0073] In this embodiment, the application provides another optional completion implementation method: After the completion and aggregation processes in steps S01_4a to S01_4b, each pair of stations in the entire railway system will obtain a connecting path between each pair of stations (this connecting path refers to the sequential list of stations that must be passed through but do not necessarily stop at from one station to another), and there will be at least one connecting path between each pair of stations. Then, for the train number to be completed, based on the starting and ending stations of the train number, all connecting paths between the starting and ending stations are queried from all the connecting paths obtained after the completion and aggregation processes in steps S01_4a to S01_4b. From all the queried connecting paths, connecting paths containing all stations in the train timetable of the train number are selected. If only one connecting path is selected, all stations in that connecting path are determined as the list of mandatory stations for the train number, thereby obtaining the train number with mandatory stations corresponding to the train number. If the selected connecting paths include multiple paths, then all stations in the shortest of these paths are identified as the mandatory stations for that train service, thus obtaining the complete train service list based on the mandatory stations for that train service. For example... Figure 2 As shown, a direct train from Nanning East to Guangzhou South only stops at the origin and destination stations. The specific stations this direct train passes through cannot be obtained from its timetable. However, the mandatory station completion method provided in this application can complete the mandatory station list for such trains, identifying stations that the train passes through but does not stop at, thus obtaining the specific connecting routes for these trains. Furthermore, since these trains preferentially take the shortest route, this application selects the shortest connecting route for trains with multiple possible routes. Figure 2For the direct train from Nanning East to Guangzhou South, this application identifies two connecting routes: Route 1 is [Nanning East Station, Binyang Station, Laibin North Station, Liuzhou Station, Luzhai North Station, Yongfu South Station, Guilin Station, Guilin North Station, Yangshuo Station, Gongcheng Station, Zhongshan West Station, Hezhou Station, ..., Guangzhou South Station], and Route 2 is [Nanning East Station, Binyang Station, Guigang Station, Guiping Station, Pingnan South Station, Tengxian Station, Wuzhou South Station, ..., Guangzhou South Station]. Route 2 is shorter than Route 1. Therefore, for this direct train, Route 2, with the shorter distance, is selected as the actual connecting route taken by the train. This allows us to know which stations passengers on this direct train will pass through, providing more information for train identification.

[0074] For example, the timetable for train number 2 records stations ADFG in sequence. The starting and ending stations of this train are station A and station G, respectively. Searching for all connecting paths between the starting and ending stations yields three connecting paths: ABCDEFG, AHEJG, and ABDHEG. Since only ABCDEFG contains all stations ADFG recorded in the timetable for train number 2, all stations in the connecting path ABCDEFG are determined as the mandatory station list for train number 2, thus completing the train number with the mandatory stations for train number 2.

[0075] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, step S03 may include steps S03_1 to S03_4: Step S03_1: Based on the signaling reported by the user's terminal, determine the dwell time of each station the user may pass through, whether the indoor distribution cell of the railway station is occupied, and the distance between the user's terminal and each station the user may pass through.

[0076] In this embodiment, some stations that a user may pass through are incorrectly identified because they are close to the user's route and need to be removed. This application provides a specific removal method. Specifically, for each station that a user may pass through, based on the information reported by the user's terminal, the method determines the user's dwell time at each station, whether the user occupies the indoor distribution cell of each station, and the distance between the user's terminal and each station.

[0077] Step S03_2: Based on the dwell time threshold, the dwell time of each station that the user may pass through, whether the indoor distribution cell of the railway station is occupied, the distance threshold, and the distance between the user's terminal and each station that the user may pass through, the confidence level of each station that the user may pass through is determined by the station dwell confidence model.

[0078] In this embodiment, the application pre-sets a stop duration threshold and a distance threshold. Based on the user's dwell time at each station that the user may pass through, whether the user occupies the indoor distribution cell of each station, the distance between the user's terminal and each station, and the stop duration threshold and distance threshold, the confidence level of each station that the user may pass through is determined through the station stop confidence model.

[0079] In this embodiment, one optional implementation is that the station stop confidence model calculates the confidence level of each station that a user may pass through using a corresponding algorithm. The expression of this algorithm is:

[0080] Where duration is the user's dwell time at the corresponding site, in minutes; dist is the distance between the user and the corresponding site, in meters; T is the high-confidence dwell time threshold, preferably set to 15 minutes; , The distance thresholds are set for high confidence and low confidence, respectively. The high confidence distance threshold is preferably set to 500 meters, and the low confidence distance threshold is preferably set to 3000 meters. , , The weighting coefficients for time, distance, and indoor distribution cell are respectively set, with the weighting coefficient for time preferably set to 0.5, the weighting coefficient for distance preferably set to 0.3, and the weighting coefficient for indoor distribution cell preferably set to 0.2. The reward factor for indoor cells is preferably set to 0.3; hasIndoor∈{0,1} indicates whether the indoor cell of the corresponding site is occupied. If occupied, the value is 1, and if not occupied, the value is 0.

[0081] In another alternative implementation, the site stopping confidence model can calculate the confidence level of a user's likely stops using at least one of the algorithms, for example, using only... The calculation result serves as the confidence level for the sites a user might visit. Furthermore, if a particular data point cannot be obtained, the item in the algorithm related to that data point is set to zero.

[0082] Step S03_3: From the various stations that the user may pass through, select the stations with a confidence level greater than the confidence level threshold as high-confidence stopping stations.

[0083] In this embodiment, the application pre-sets a confidence threshold. After calculating the confidence of each station that the user may pass through through step S03_2, the stations with a confidence greater than the confidence threshold are determined as the user's high-confidence stopping stations.

[0084] Step S03_4: Determine the high-confidence stops and the stops that have a direct train connection with the high-confidence stops among the various stops that the user may pass through as the actual stops that the user passes through.

[0085] In this embodiment, the user's high-confidence stops are first identified as the stops the user actually traversed. Simultaneously, using a direct route list, it is determined which of the user's possible stops have a direct route connection with the user's high-confidence stops. For each possible stop with a direct route connection to the user's high-confidence stops, that stop is also identified as a stop the user actually traversed. For example, if the user's possible stops are ACDG, and the filtered high-confidence stops are ADG, then among the possible stops ACDG, stops C and A have a direct route connection, while stops E and ACDG do not. Therefore, stop ACDG is identified as a stop the user actually traversed.

[0086] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, step S04 may include: when the number of high-confidence stopping stations is one, for each station actually passed by the user, determining the difference between all departure times of each necessary stop supplementary train number and the latest departure time of that station, and identifying necessary stop supplementary train numbers whose differences are less than a difference threshold and which stop at that station as necessary stop supplementary train numbers that the user may take.

[0087] In this embodiment, when the number of high-confidence stops for the selected user is one, for each stop the user actually passes through, the departure times of all the supplementary train services at each necessary stop are compared with the latest departure time of the user at each of the actual stops. If the difference between a certain departure time of a supplementary train service at a necessary stop and the latest departure time of the user at a certain stop is lower than a preset difference threshold, and the supplementary train service at the necessary stop stops at that stop, then the supplementary train service at the necessary stop is determined as a necessary supplementary train service that the user may take.

[0088] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, step S04 may include: when the number of high-confidence stops is greater than one, taking each stop actually passed by the user as a transfer station, querying all transfer train number combinations, and using the train numbers in the queried transfer train number combinations as necessary stops that the user may pass through to complete the train number; wherein, the queried transfer train number combinations include a first necessary stop complete train number and a second necessary stop complete train number, the transfer station and the first stop actually passed by the user appear in the first necessary stop complete train number, and the transfer station and the second stop actually passed by the user appear in the second necessary stop complete train number.

[0089] In this embodiment, when the number of high-confidence stops is greater than one, all stops except the first two stops in each actual route taken by the user are considered transfer stations. All feasible transfer train combinations are queried, and the trains in these combinations are used as the necessary stops for the user to complete the train schedule. Only one transfer is required to reach the desired transfer station combination. Each transfer train combination includes two trains: a first necessary stop completion train and a second necessary stop completion train. The transfer station and the user's first actual stop (i.e., the first stop the user actually passes through) appear in the first necessary stop completion train, and the transfer station and the user's second actual stop (i.e., the last stop the user actually passes through) appear in the second necessary stop completion train. An optional implementation of querying feasible transfer train combinations is as follows: For the first and last stations among all the stations the user actually passes through, if the first and last stations are not adjacent, and there is an intermediate station among all the stations the user actually passes through excluding the first and last stations, this intermediate station satisfies the following conditions: a candidate train (e.g., train number 1) passes through the first station and this intermediate station in sequence, and another candidate train (e.g., train number 2) passes through this intermediate station and the last station in sequence, then a valid transfer train combination consisting of train number 1 and train number 2 is determined to exist. This transfer train combination consisting of train number 1 and train number 2 is then included as a necessary stop for the user to complete the train schedule.

[0090] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, step S05 may include steps S05_1 to S05_4: Step S05_1: For each station the user actually passes through, determine the corresponding time matching degree by supplementing the departure time of that station in the complete train schedule based on the latest departure time of that station and the departure time of that station in the train schedule that the user may take.

[0091] In this embodiment, after obtaining the complete train schedules for the stations the user might take, the actual train the user takes is further determined. Specifically, for each station the user actually passes through, the time matching degree between the complete train schedule for that station and the user at that station is determined based on the user's latest departure time at that station and the departure time of the complete train schedule for that station. Using the same implementation method, the number of stations on a complete train schedule that the user might take that matches the stations the user actually passes through corresponds to the number of time matching degrees. For example, if a complete train schedule 1 has 5 stations (A, B, C, D, E) and the user actually passes through 4 stations (A, C, D, F), then 3 of the stations on the complete train schedule 1 match the stations the user actually passes through. Accordingly, 3 time matching degrees are calculated for this complete train schedule 1. The average of all time matching degrees for a single complete train schedule that the user might take is taken to obtain the time matching degree corresponding to that complete train schedule.

[0092] In this embodiment, the complete train schedule that a user may take includes combinations of connecting trains. For a single combination of connecting trains, the connecting stations are designated as the destination of the first train and the origin of the second train in the combination. Then, a time matching degree is calculated for both the first and second trains in the combination. The average of all time matching degrees calculated for these two trains is taken to obtain the time matching degree for the single combination of connecting trains.

[0093] In this embodiment, an optional algorithm for determining the time matching degree is: The site number of the actual sites the user passed through; For the time the user passes through station i, take the earliest arrival time for the last station the user actually passes through, otherwise take the latest departure time. The time to complete the train number's transit station i is given for the necessary transit stations. For the last transit station of the train number, the arrival time is taken; otherwise, the departure time is taken. TRT is the maximum allowable deviation time, preferably 30 minutes.

[0094] Step S05_2: Determine the corresponding station coverage based on the number of stations the user actually passes through and the number of stations in the supplementary train schedule that overlap with the stations the user actually passes through.

[0095] In this embodiment, the station coverage of a train service with a single possible stop that a user might take is determined by dividing the number of stations in the complete train service that intersect with the stations the user actually passes through by the total number of stations the user actually passes through. For example, if all the possible stops of a train service with a single possible stop that a user might take are ABCDE, and the stations the user actually passes through are ACEG, then the number of stations in the complete train service with a possible stop that a user might take that intersects with the stations the user actually passes through is 3, and the total number of stations the user actually passes through is 4. Therefore, the station coverage of the complete train service with a possible stop that a user might take is determined to be 3 / 4.

[0096] In this embodiment, the complete list of train routes that a user might take includes combinations of connecting train routes. For a single combination of connecting train routes, the number of stations in the combination that intersect with the user's actual route is divided by the total number of stations the user actually travels through, to obtain the station coverage corresponding to that combination. For example, if a combination of connecting train routes consists of train 1 and train 2, with all stations of train 1 being ABC and all stations of train 2 being CDE, and the user's actual route being ACEG, then the number of stations intersecting with the user's actual route is 3, and the total number of stations the user actually travels through is 4. Therefore, the station coverage corresponding to this combination is determined to be 3 / 4. Thus, a complete list of train routes that a user might take from a certain stop will have a corresponding time matching degree and station coverage.

[0097] Step S05_3: Based on the time matching degree and station coverage of the complete train schedule for each necessary stop the user may take, determine the confidence level of the complete train schedule for each necessary stop the user may take.

[0098] In this embodiment, based on the time matching degree and station coverage of each possible stop along a train route, the confidence level of the possible train route along that stop is determined. One optional confidence level calculation method is to directly add the time matching degree and station coverage of each possible stop along a train route to obtain the confidence level of the possible train route along that stop. Another optional confidence level calculation method is to assign weights to the time matching degree and station coverage of each possible stop along a train route, and then perform a weighted summation of the time matching degree and station coverage of each possible stop along a train route to obtain the confidence level of the possible train route along that stop, expressed as: ,in, To complete the time matching accuracy of train routes for the corresponding necessary stops; , These are adjustable weight parameters (e.g., 0.5 each). This involves calculating the station coverage for complete train routes corresponding to necessary stops. Therefore, for each necessary stop a user might take, a confidence level can be calculated for each completed train route. Step S05_4: Arrange the train numbers from the possible stops the user might take in descending order of confidence level to determine the actual train number the user took.

[0099] In this embodiment, the confidence levels of the complete train numbers for each necessary stop that the user may take are arranged in descending order. Depending on the actual application needs, 1 to 3 train numbers can be selected as the actual train numbers taken by the user according to the order of confidence levels from high to low.

[0100] In conjunction with the above embodiments, in one implementation, this application also provides a user train number identification method in high-speed rail network perception optimization. In this user train number identification method in high-speed rail network perception optimization, determining the departure time of stations in the complete train number that must pass through includes: Step S001: If the station is a necessary stop for completing the train service, the departure time of the stop is determined by the time information recorded in the corresponding train timetable.

[0101] In this embodiment, since all the necessary stops in the supplementary train service include the stops recorded in the timetable of the supplementary train service, as well as stops that are only passed through but not stopped at, the departure time of the supplementary train service at these stops cannot be directly obtained, which will affect the calculation of time matching degree. Based on this, this application provides an optional implementation method for determining the departure time of all necessary stops in the supplementary train service. Specifically, the type of each necessary stop in the supplementary train service is determined. When the stop is a stop that will be recorded in the timetable of the supplementary train service, the departure time of the stop is determined by the time information recorded in the timetable of the supplementary train service.

[0102] Step S002: If the station is a necessary stop and a stop in the supplementary train number, determine the departure time of the stop in the corresponding train timetable that is located before the stop, and determine the travel time from the stop to the stop through the target train number through the train timetable of the target train number. The target train number is the train number of the stop and the stop recorded in its own train timetable.

[0103] In this embodiment, when a station is a stop that is only passed through but not stopped at, which is not recorded in the timetable of the train service that is a necessary stop, the nearest stop before that station is found in the timetable of the train service that is a necessary stop, and the departure time of that stop is obtained from the timetable. Then, the timetables that record the station and the nearest stop before that station are found from the timetables of all train services. Then, all the travel times from the stop to the station are found from these timetables, and the average value is taken as the travel time from the stop to the station. For example, among all the necessary stops of the train service 1 that is a necessary stop, there is a stop D that is passed through but not stopped at, and the nearest stop before that station B is recorded in the timetable of the train service that is a necessary stop. At this time, the departure time of the stop B is obtained from the timetable. Then, find the train timetable that records station D and the nearest stop B before station D from all the train timetables. Then find all the travel times from stop B to station D from these train timetables, and take the average value. This average value is determined as the travel time from stop B to station D.

[0104] Step S003: Based on the determined departure time of the stop before the transit stop and the determined travel time from the stop to the transit stop, determine the departure time of the transit stop.

[0105] In this embodiment, after obtaining the departure time of the nearest stop before the station and the travel time from the stop to the station through step S002, the departure time of the station is obtained by adding the travel time to the departure time.

[0106] like Figure 3As shown, the user train number identification method in the high-speed rail network perception optimization provided in this application mainly includes constructing a railway topology structure, initial screening of user-passed stations, determining user-passed stations based on the initial screening, generating candidate train numbers for the user based on the determined user-passed stations, and selecting the optimal train number for the user based on the determined candidate train numbers. The construction of the railway topology mainly includes three aspects: constructing the connection relationships between stations (which are directional); completing the necessary stations between stations based on the established connection relationships; and completing the necessary stations between stations based on the completed station information, filling in stations that are not recorded in the train timetable but are not stopped at, thus obtaining the train number corresponding to the train number that records all necessary stations for that train. The initial screening of user-passed stations is based on the distance relationship between the base station location and the stations in the signaling reported by the user's terminal device to determine the stations the user may pass through. Based on the initial screening, and using monitoring data from multiple sources, further filtering is performed on the stations that the user might pass through, thus identifying the stations the user actually traversed. This application primarily uses a pre-built station stop confidence model to filter out the stations the user actually traversed from the initially screened potential stations. For generating candidate train numbers for the user based on the identified stations, the departure time of the train at a certain station and the user's departure time at that station are considered to be relatively close to each other to determine the train the user is likely to take. The process of selecting the optimal train number for the user based on the identified candidate train numbers involves determining which train performs better in terms of both time matching and station coverage, and selecting the train with the best overall performance in both aspects as the actual train the user takes. This train number identification method only needs to use the train timetables of all trains in the railway system to automatically construct the topological relationships between stations and complete the implicit mandatory stations of the train numbers. By designing a station stop confidence model, factors such as dwell time, spatial distance, and indoor distribution occupancy are considered to determine whether a train actually stops at a station. A candidate train generation mechanism is constructed, supporting both direct train candidates and single-transfer combination candidates. A joint scoring algorithm based on time matching and station coverage is introduced to select the train most likely to be taken by the user. The entire process can be implemented entirely in software, requiring no additional hardware or frequent road testing, and possesses good scalability and real-time performance.

[0107] Based on the same inventive concept, this application provides a user train number identification system for high-speed rail network perception optimization, such as... Figure 4 As shown, the system 400 includes: The station completion module 401 is used to complete the necessary stations between any two stations for trains that appear at the same time, based on the train timetable of each train, and obtain the trains with necessary stations. The first route site determination module 402 is used to determine the sites that the user may pass through based on the distance between the base station location and the site in the signaling reported by the user's terminal. The second route station determination module 403 is used to determine the actual stations the user passes through from the possible stations the user may pass through, based on the station stop confidence model. The first train number determination module 404 is used to determine the train numbers that the user may take based on the stations the user actually passes through, from the train numbers supplemented by each necessary station. The second train number determination module 405 is used to perform spatiotemporal matching between the train numbers that the user may take and the stations that the user actually passes through, so as to determine the train number that the user actually takes from the train numbers that the user may take and the stations that the user actually passes through.

[0108] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily necessary for the embodiments of this application.

[0109] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0110] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0114] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0115] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0116] The above provides a detailed description of a user train number identification method in high-speed rail network perception optimization provided by this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A user train number identification method in high-speed rail network perception optimization, characterized in that, The method includes: Based on the train timetable for each train, for any two trains that appear at the same time, complete the necessary stations between those two stations to obtain the trains with the necessary stations. Based on the distance between the base station location and the site in the signaling reported by the user's terminal, the sites that the user may pass through are determined. Based on the station stop confidence model, the stations that the user actually passed through are determined from the stations that the user may have passed through. Based on the stations the user actually passes through, the train schedules that the user may take are determined from the complete train schedules of each necessary station. The complete train schedules of the stations the user may pass through are spatiotemporally matched with the stations the user actually passes through, so as to determine the train the user actually takes from the complete train schedules of the stations the user may pass through.

2. The user train number identification method in high-speed rail network perception optimization according to claim 1, characterized in that, After determining the actual train numbers taken by each of the multiple users, the method further includes: Based on each user's actual train number, identify all users who took the same train number; All users traveling on the same train are grouped into one terminal group, and the wireless network quality of the terminal group is analyzed. Based on the spatiotemporal information of each user for each train, the intersecting trains are determined; For trains that intersect, during the corresponding intersecting time period, perform wireless network quality analysis on all terminal combinations of the intersecting trains.

3. The user train number identification method in high-speed rail network perception optimization according to claim 1, characterized in that, Based on the train timetables for each train, for any two trains that appear at the same station, complete the necessary stops between those two stations to obtain the complete train numbers with necessary stops, including: Based on the train timetables for each train, determine the connection between any two stations; For the first station and the second station, traverse all trains and determine the initial directed path between the first station and the second station based on the train timetable of trains that appear at both the first station and the second station. For the initial directed path between the first station and the second station, if the connection relationship between the first station and the second station is not an adjacent relationship, and the first station and the second station have one and only one common adjacent station, the common adjacent station is determined as a necessary station of the initial directed path between the first station and the second station. The initial directed path between the first station and the second station is completed by using the necessary stops to obtain the necessary stop completion train numbers for any two stations that appear at the same time.

4. The user train number identification method in high-speed rail network perception optimization according to claim 3, characterized in that, Based on the train timetables for each train, determine the connection between any two stations, including: Iterate through all train services, add every two stations in the same train service to the direct train service list, and mark whether each pair of added stations is directly adjacent and which train service they belong to. Iterate through any two stations in the direct train list. If the two stations currently iterated through satisfy the condition that they are directly adjacent in all trains that appear at the same time, determine the connection relationship between the two stations currently iterated through as an adjacent relationship. If the two stations currently visited do not meet the condition that they are directly adjacent in all simultaneous train services, the connection relationship between the two stations currently visited is determined to be a direct relationship for the same train service. If the first station and the second station do not appear in the same data entry in the same direct train list, and there is a third station that is directly connected to the first station and the second station respectively, then the connection relationship between the first station and the second station is determined to be a one-transfer reachable relationship. If there is no direct train connection or a single transfer between the two stations currently being traversed, then the relationship between the two stations is determined to be unreachable.

5. The user train number identification method in high-speed rail network perception optimization according to claim 3, characterized in that, The initial directed path between the first station and the second station is completed using the necessary stops to obtain the necessary stop-complete train numbers for any two stations that appear simultaneously, including: By using the necessary stations, the initial directed path between the first station and the second station is completed, resulting in multiple completed directed paths between the first station and the second station; Based on whether the multiple completed directed paths between the first site and the second site are completely contained among each other, the multiple completed directed paths between the first site and the second site are aggregated. If the path obtained after aggregation is a single path, then that path shall be taken as the final path between the first site and the second site. If the path obtained after aggregation is multiple paths, then the shortest path among these multiple paths shall be taken as the final path between the first station and the second station. The stations on the final path between the first station and the second station are taken as the necessary stations for trains that appear simultaneously at the first station and the second station, and the necessary stations are supplemented for the trains to obtain the trains with the necessary stations for the trains that appear simultaneously at the first station and the second station.

6. The user train number identification method in high-speed rail network perception optimization according to claim 1, characterized in that, Based on the site stop confidence model, the actual sites visited by the user are determined from among the possible sites the user may have visited, including: Based on the signaling reported by the user's terminal, determine the dwell time of each station the user may pass through, whether the indoor distribution cell of the railway station is occupied, and the distance between the user's terminal and each station the user may pass through; Based on the dwell time threshold, the dwell time of each station the user may pass through, whether the indoor distribution cell of the railway station is occupied, the distance threshold, and the distance between the user's terminal and each station the user may pass through, the confidence level of each station the user may pass through is determined by the station dwell confidence model. From the various stations that the user may pass through, stations with a confidence level greater than the confidence level threshold are selected as high-confidence stopping stations; The high-confidence stops, and the stops that have a direct train connection with the high-confidence stops among the various stops the user may pass through, are identified as the stops the user actually passes through.

7. The user train number identification method in high-speed rail network perception optimization according to claim 1, characterized in that, Based on the stations the user actually passes through, the train schedules that the user might take are determined from the complete list of train schedules for each necessary stop, including: When the number of high-confidence stops is one, for each stop the user actually passes through, determine the difference between all departure times of each supplementary train at each necessary stop and the latest departure time of that stop. Supplementary trains at necessary stops whose difference is less than the difference threshold and which stop at that stop are considered as supplementary trains at necessary stops that the user may take.

8. The user train number identification method in high-speed rail network perception optimization according to claim 1, characterized in that, Based on the stations the user actually passes through, the train schedules that the user might take are determined from the complete list of train schedules for each necessary stop, including: If the number of high-confidence stops is greater than one, each stop actually traversed by the user is considered a transfer station. All combinations of transfer trains are queried, and the trains in the queried combinations are used as necessary stops that the user may take to complete the train schedule. The queried combinations of transfer trains include a first necessary stop complete train schedule and a second necessary stop complete train schedule. The transfer station and the first stop actually traversed by the user appear in the first necessary stop complete train schedule, and the transfer station and the second stop actually traversed by the user appear in the second necessary stop complete train schedule.

9. A user train number identification method in high-speed rail network perception optimization according to claim 1, characterized in that, The system performs spatiotemporal matching between the train schedules that the user might take, which include the necessary stops along the route, and the actual trains the user takes. This process involves determining the actual train number the user takes from the train schedules that the user might take, including: For each station that the user actually passes through, the departure time of that station is supplemented in the train schedule based on the latest departure time of that station and the departure time of that station in the train schedule that the user may pass through, and the corresponding time matching degree is determined. Based on the number of stations the user actually passes through, and the number of stations in the supplementary train schedule that the user may take that intersect with the stations the user actually passes through, the corresponding station coverage is determined. Based on the time matching degree and station coverage of the complete train schedules at each necessary stop the user may take, the confidence level of the complete train schedules at each necessary stop the user may take is determined. Arranged in descending order of confidence level, the train numbers are supplemented from all possible stops the user might pass through to determine the actual train number the user took.

10. A user train number identification method in high-speed rail network perception optimization according to claim 9, characterized in that, Determine the departure times of the necessary stops for the train service, including: If the station is a necessary stop for completing a train journey, the departure time of the stop is determined by the time information recorded in the corresponding train timetable. If the station is a necessary stop and a stop that is supplemented in the train schedule, determine the departure time of the stop that is located before the stop in the corresponding train timetable, and determine the travel time from the stop to the stop through the target train through the train timetable. The target train is the train that records the stop and the stop in its own train timetable. The departure time of the transit station is determined based on the departure time of the stop preceding the transit station and the travel time from the stop to the transit station.

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