A method, system, readable storage medium and electronic device for counting late trains at a CTC station

Abstract

This invention discloses a method, system, readable storage medium, and electronic device for statistical analysis of train delays at CTC stations. The method includes: S1, the station server periodically accessing train data files to obtain train operation data; S2, filtering the train operation data to obtain a valid train queue; S3, statistical analysis of on-time trains based on the valid train queue, including: determining whether the actual arrival time of a train is later than the planned arrival time, and whether the actual stopping time of the train is less than the planned stopping time; if the above conditions are met, the on-time time is calculated and the train information is saved; S4, statistical analysis of trains exceeding their planned stopping time based on the valid train queue, including: determining whether the actual stopping time of a train exceeds the planned stopping time; if it exceeds, the exceeding stop duration is calculated and the train information is saved to the exceeding stop train queue; S5, outputting the statistical results of on-time trains and exceeding stop trains. Its advantage is that this method can achieve automatic statistical analysis of train delay data.

Description

Technical Field

[0001] This invention relates to the field of intelligent traffic management technology, and in particular to a method, system, readable storage medium, and electronic device for calculating vehicle delays at a CTC station. Background Technology

[0002] As the core hub of the modern transportation system, railway stations are the bases for organizing transportation production activities. They not only undertake basic service functions such as passenger boarding and alighting and freight transport, but also serve as the convergence point for critical operations such as train arrival and departure, train marshalling and demarcation, locomotive and crew preparation and transfer, train inspection, and freight inspection. The orderliness and efficiency of station operations directly affect the smooth operation and transportation efficiency of the entire railway network. However, in actual operation, train punctuality is easily affected by a variety of complex factors. These influencing factors generally include technical factors (such as equipment failure and track problems), weather and environmental factors (such as extreme weather conditions such as heavy rain, heavy snow, and dense fog) and the resulting temporary speed limits, operational management factors (such as scheduling command conflicts and the ripple effects of previous train delays), and various unforeseen emergencies. These factors intertwine, making train delays a common and difficult-to-avoid phenomenon.

[0003] Against this backdrop, obtaining accurate and systematic station train delay statistics plays a practical role in station operation and management, and is of paramount importance for improving the operational management level of stations and the entire railway network. Despite the undeniable importance of this work, many stations currently rely primarily on traditional manual methods for collecting and compiling delay data. This manual collection method has revealed several limitations in practice: First, it is a highly time-consuming and labor-intensive task, especially at large hub stations handling a large number of trains daily; manual statistics require considerable manpower and are inefficient. Second, manual operations are prone to data errors, omissions, recording deviations, or untimely updates due to fatigue, negligence, or poor communication, severely impacting the accuracy and completeness of the data. Furthermore, manual statistics struggle to achieve real-time data processing and dynamic updates, leading to information delays and hindering timely and effective decision-making support for operational command. In addition, the scattered and non-standardized manual recording makes it difficult to effectively integrate and deeply analyze data from different stations and time periods, creating "information silos" that impede macro-analysis and collaborative optimization at the railway network level. Therefore, improvements to the existing data collection methods are necessary.

[0004] The statements herein provide only background information in relation to this invention and do not necessarily constitute prior art. Summary of the Invention

[0005] Based on the aforementioned technical problems, the purpose of this invention is to provide a method, system, readable storage medium, and electronic device for counting train delays at CTC stations. This method can solve the problems of low efficiency, high error rate, and insufficient accuracy in manually counting train delay data at stations. This method can realize automatic statistical analysis of train delay data and reduce the workload of station staff in manual statistics.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: A method for calculating train delays at CTC stations, comprising: S1. The station server periodically accesses the train data file to obtain train operation data; S2. Filter the train operation data to obtain the effective train queue; S3. Based on the effective train queue, perform statistics on trains rushing to catch up, including: Determine whether the actual arrival time of the train is later than the planned arrival time, and whether the actual stopping time of the train is less than the planned stopping time; If the above conditions are met, the time for this train to make its journey is calculated, and the train information is stored in the train queue for trains making their journey. S4. Based on the aforementioned effective train queue, perform statistics on trains that skip stations, including: Determine whether the actual stopping time of the train exceeds the planned stopping time; If the actual stopping time of a train exceeds the planned stopping time, the overstaying time of this train number is calculated, and the train information of this train is stored in the overstaying train queue. S5 outputs statistical results for trains that arrive on time and trains that stop at stations beyond their designated stops.

[0007] Optionally, the station server includes a statistics server and an operation server. In step S1, the statistics server is used to periodically access the train data file, which is generated by the operation server.

[0008] Optionally, in step S2, filtering the train operation data includes: Remove duplicate data, train data outside the statistical period, and invalid train data.

[0009] Optionally, in step S2, removing invalid train data includes: Remove data for trains not registered at this station, remove data for trains that have been deleted, and remove data for trains that have not been converted to actual operation.

[0010] Optionally, in S3, the calculation method for the rush time includes: If the train arrives late but departs on time or early, the time to catch up is the difference between the actual arrival time and the planned arrival time. If a train arrives and departs late, but the actual stop time is less than the planned stop time, the time to catch up is the difference between the late arrival time and the late departure time.

[0011] Optionally, the train information stored in the punctual train queue in S3 includes: Train number, station number, actual arrival time, scheduled arrival time, actual departure time, and scheduled departure time.

[0012] Optionally, in S4, the calculation method for the over-station stop time is as follows: Excessive stop time = Actual stop time - Planned stop time.

[0013] Optionally, the train information stored in the extra-stop train queue in S4 includes: Train number, station number, and duration of extra stops.

[0014] Optionally, the station server operates using a dual-machine synchronous mechanism, where one station server can obtain train data files from the other station server based on various data transmission protocols.

[0015] Optionally, the station server can obtain train data files from another station server via SSH or FTP.

[0016] Optional, also includes: The statistical results of the queuing for trains arriving on time and the queuing for trains that stop at stations beyond the designated stops will be displayed visually.

[0017] Optionally, an automatic train delay statistics system based on a CTC system is provided for implementing the aforementioned method for statistics of train delays at CTC stations. The system includes: The data acquisition module is used to periodically access train data files and acquire train operation data; A data cleaning module, which is connected to the data acquisition module, is used to generate an effective train queue based on train operation data. The on-time statistics module is connected to the data cleaning module. The on-time statistics module is used to calculate on-time time and generate on-time train queues. An extra-stop statistics module, which is connected to the data cleaning module, is used to calculate the extra-stop duration and generate an extra-stop train queue. The result output module is connected to the on-time statistics module and the over-stop statistics module respectively, and the result output module is used to output statistical results.

[0018] Optionally, the station server operates using a dual-machine synchronous mechanism, and the data acquisition module can acquire train data files from both station servers.

[0019] Optionally, the result output module can also be used to visualize the statistical results.

[0020] Optionally, a readable storage medium stores a computer program that, when executed by a processor, implements the steps of the aforementioned method for calculating vehicle delays at CTC stations.

[0021] Optionally, an electronic device is provided, comprising: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the steps of the aforementioned method for calculating vehicle delays at CTC stations.

[0022] Compared with the prior art, the present invention has the following advantages: The present invention discloses a method, system, readable storage medium, and electronic device for statistical analysis of train delays at CTC stations. The method aims to solve the problems of low efficiency and insufficient accuracy in statistical analysis of train delay data at stations. Through innovative design, it realizes automatic statistical analysis of train delay data, reduces the workload of station staff in manual statistical analysis, significantly improves work efficiency and data accuracy, and provides strong support for optimizing station transportation operations. Attached Figure Description

[0023] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are one embodiment of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort: Figure 1 This is a simplified schematic diagram of a method for calculating vehicle delays at a CTC station according to the present invention; Figure 2 This is a visual schematic diagram of a time-tracking statistics table according to the present invention; Figure 3 This is a visual schematic diagram of a super-stop time statistics table according to the present invention. Detailed Implementation

[0024] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a method, system, readable storage medium, and electronic device for calculating train delays at CTC stations, as proposed by the present invention. The advantages and features of the present invention will become clearer from the following description. It should be noted that the accompanying drawings are in a very simplified form and use non-precise proportions, used only to facilitate and clarify the illustration of the embodiments of the present invention. Please refer to the accompanying drawings to make the objectives, features, and advantages of the present invention more apparent and understandable. It should be understood that the structures, proportions, sizes, etc., depicted in the accompanying drawings are only for illustrative purposes to aid those skilled in the art and are not intended to limit the implementation conditions of the present invention. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in proportions, or adjustments to the size, without affecting the effects and objectives achieved by the present invention, should still fall within the scope of the technical content disclosed in the present invention.

[0025] As mentioned above, existing methods for manually collecting delay data have many drawbacks. In response, this invention provides a method for CTC station to count train delays. This method can automatically count train delays at the station by utilizing existing data, which helps to improve operational efficiency, enhance safety and reliability, drive data-driven decision-making, improve service experience, and control costs.

[0026] Specifically, such as Figure 1 As shown, the method for calculating train delays at CTC stations according to the present invention includes: The station servers of the S1 and CTC systems periodically access the train data files to obtain train operation data.

[0027] The CTC system (such as the existing CTC3.0 system) includes a station server with functional modules: a statistics server (svr_statistics) and an operation server (svr_twg). The statistics server (svr_statistics) periodically accesses train data files, which are generated by the operation server (svr_twg). Since the data recorded by the operation server (svr_twg) is scattered across multiple files whose content is composed of byte streams, the data acquisition module of the statistics server (svr_statistics) needs to retrieve files from multiple time periods each time it reads data. During data statistics, a data check is performed to determine if data statistics have already been completed. If they have already been counted, the statistics will not be performed again. For example, in one embodiment, the check is based on the time of the last part or the last line of a data file. If this data at that time has already been counted, it will not be counted again.

[0028] S2. Filter the train operation data to obtain valid train queues. Filtering the train operation data includes: removing duplicate data, train data outside the statistical period, and invalid train data.

[0029] Because train operation data may contain overlapping data, all data must be filtered to remove duplicates. In this embodiment, the filtering process involves establishing a valid train queue Trains[n], which includes trains T1, T2, T3, ..., T... n (where T) n The data file contains train operation data (n can be 1, 2, 3, ...). All of this train operation data is placed into the valid train queue Trains[n]. Each time a train operation data T is added... n Each of these steps requires traversing the entire valid train queue Trains[n]. When a train with the same train number T is found in the valid train queue Trains[n], the traversal is complete. n When the write time of the two is compared, the one with the most recent write time is selected and added to the valid train queue Trains[n], and the original data is deleted.

[0030] After obtaining the valid train queue Trains[n], this invention checks whether all trains in the valid train queue Trains[n] are within the statistical period. Trains outside the statistical period are removed, as are invalid vehicles (e.g., trains not stationed at this station, deleted trains, and trains not transferred to actual operation). In other words, invalid train data (e.g., data of trains not stationed at this station, data of deleted trains, and data of trains not transferred to actual operation / data not transferred to actual operation) are removed. After filtering based on the above method, the final valid train queue Trains[n] can be obtained, which is the valid train queue Trains[n] mentioned later.

[0031] On the other hand, in practical applications, the station servers of the CTC system can operate using a dual-machine synchronous mechanism. The processor used to implement the CTC station delay statistics method of this invention may only be running on one of the servers / machines. In this case, there may be a problem that the read data file is not up-to-date. Therefore, in this invention, one station server / machine can obtain the train data file from the other station server / machine based on various data transmission protocols to ensure the timeliness and completeness of the data file. For example, in some embodiments, the station server / machine can obtain the train data file from the other station server / machine via SSH or FTP. By reading the train data files from two files on the two machines respectively, the integrity, correctness, and timeliness of the train queue Trains[n] are ensured.

[0032] In practical applications, various situations arise regarding delayed trains. For each situation, statistics on trains arriving on time and delayed trains exceeding their scheduled stop time can be performed. Specifically, in the following scenarios 1 and 2, statistics on trains arriving on time can be performed: 1) Scenario 1 (Scheduled arrival / departure): The train arrives late but departs early or on time (insufficient stopping time); 2) Scenario 2: The train arrives late and departs late, but the actual stop time is less than the planned stop time. On the other hand, for arriving / departure trains whose actual stop time is greater than the scheduled stop time (Scenario 3), statistics on trains exceeding their scheduled stop time can be performed.

[0033] Based on the above, the CTC station's method for counting train delays according to the present invention further includes: S3. Based on the effective train queue, perform on-time train statistics, including: determining whether the actual arrival time of a train is later than the planned arrival time, and whether the actual stopping time of the train is less than the planned stopping time; if the above conditions are met, calculate the on-time time of this train number, and store the train information of this train in the on-time train queue Hurry Train[m]. The train information stored in the on-time train queue Hurry Train[m] includes: train number, station number, actual arrival time, planned arrival time, actual departure time, and planned departure time.

[0034] After the initial data processing in S2, the final valid train queue Trains[n] can be obtained. Based on this valid train queue Trains[n], it is necessary to perform data statistics on punctual trains. In practice, a punctual train queue Hurry Train[m] can be created to store punctual trains during the statistical process.

[0035] In practical applications, it is necessary to iterate through each train operation data T in the valid train queue Trains[n]. n A train operation data T n It contains the operation data of a train at various stations, and each train operation data T n It may contain multiple Records, each Record being a node, and each Record represents the train's operation data at a station. In practical applications, the target station for statistics may be single or multiple stations, requiring iteration through each Record to obtain the train's operation data at the target station.

[0036] During the traversal, after obtaining train operation data T1, the first step is to obtain the RecordCount, which represents the number of records in T1, indicating how many stations the train has operation data at. Then, each Record in T1 is traversed. For each Record read, it is determined whether it meets the requirements of the current station's StaNo, i.e., whether the station corresponding to the Record is within the target station. If it is, subsequent checks and calculations continue; if it is outside the target station, meaning the train's operation data at that station does not need to be counted, the Record is discarded. Simultaneously, based on the information in the Record, it is necessary to determine whether the train is a through train (a through train is one whose arrival and departure times are the same at that station). If it is a through train, it needs to be discarded; this invention only counts trains other than through trains.

[0037] Furthermore, it checks whether the actual arrival time (Arrive) of the Record is later than the planned arrival time (Arrive_plan), and whether the actual stop time (Real_time) is less than the planned stop time (Plan_time). If both conditions are met, the train information of the Record, including train number, station number, actual arrival time, planned arrival time, actual departure time, and planned departure time, is added to the on-time train queue (HurryTrain[m]), and the data statistics and calculations for on-time trains are performed. Then, the process continues until the last Record in the valid train queue (Trains[n]) is reached.

[0038] In this invention, the method for calculating the time to catch up includes: if the train arrives late but departs on time or early, the time to catch up is the difference between the actual arrival time and the planned arrival time; if the train arrives late and departs late, but the actual stop time is less than the planned stop time, the time to catch up is the difference between the late arrival time and the late departure time.

[0039] The following will provide a detailed explanation using scenarios 1 and 2: 1) Scenario 1 (from fixed to open) Prerequisite: The train arrives late and departs early or on time (insufficient stopping time).

[0040] Calculation rule: If the scheduled arrival time of the train is t1 and the actual arrival time is t2, then the time to catch up is t2-t1.

[0041] For example, in one embodiment, the scheduled arrival time of the train is 10:00 and the scheduled departure time is 10:20. A delay of 5 minutes (10:05) means that the train is 5 minutes late. Whether the train departs at or before 10:20, it is considered to be 5 minutes late.

[0042] 2) Scenario 2 Prerequisite: The train arrives late and departs late, but the actual station stop time is less than the planned station stop time.

[0043] Calculation rules: If the train's scheduled arrival time is t1 and the actual arrival time is t2, the delay time is t2-t1; if the train's scheduled departure time is t3 and the actual departure time is t4, the delay time is t4-t3. The time to catch up is (t2-t1)-(t4-t3).

[0044] For example, in one embodiment, the train's scheduled arrival time is 10:00, and its scheduled departure time is 10:20. It is 5 minutes late (10:05), and the train departs at 10:22, with a 3-minute head start time.

[0045] S4. Based on the effective train queue Trains[n], perform over-stop train statistics, i.e., over-stop and delayed train statistics, including: determining whether the actual stopping time of a train exceeds the planned stopping time; if the actual stopping time exceeds the planned stopping time, calculate the over-stop duration of this train and store the train information of this train in the over-stop train queue OverTrain[j]. The train information stored in the over-stop train queue OverTrain[j] includes: train number, station number, and over-stop duration.

[0046] After the initial data processing in S2, the final valid train queue Trains[n] can be obtained. Based on this valid train queue Trains[n], it is necessary to perform data statistics on trains that skip stops. In practice, an over-stop train queue Over Train[j] can be created to store trains that are rushing to catch up during the statistical process.

[0047] In practical applications, it is necessary to iterate through each train operation data T in the valid train queue Trains[n]. n A train operation data T n It contains the operation data of a train at various stations, and each train operation data T n It may contain multiple Records, each Record being a node, and each Record representing the train's operation data at a station. In practical applications, the target station may be single or multiple, requiring iteration through each Record to obtain the train's operation data at the target station.

[0048] During the traversal, after obtaining train operation data T1, the first step is to obtain the RecordCount (i.e., the number of records) in the train operation data T1, which indicates how many stations the train has operation data at. Then, each Record in the train operation data T1 is traversed. For each Record read, it is necessary to determine whether it meets the requirements of the current station's StaNo, i.e., whether the station corresponding to the Record is within the target station. If it is within the target station, subsequent judgments and calculations continue; if it is outside the target station, meaning the train's operation data at that station does not need to be counted, the Record is discarded. Simultaneously, based on the information in the Record, it is also necessary to determine whether the train is a through train (a through train is one whose arrival and departure times are the same at that station). If it is a through train, it needs to be discarded; this invention only counts trains other than through trains.

[0049] Furthermore, it is determined whether the actual stop time Real_time of the Record is longer than the planned stop time Plan_time. If so, the train information of the Record, such as train number, station number, and overstay time Over_time, is added to the overstay train queue Over Train[j], and the data statistics and calculations for overstay trains are performed. Then, the process continues to traverse until the last Record in the valid train queue Trains[n].

[0050] In this invention, the overstaying stop time is calculated as follows: Overstaying stop time = Actual stop time - Planned stop time. The following is a detailed explanation using scenario 3: Scene 3: Prerequisite: The actual station dwell time of the train is greater than the scheduled station dwell time.

[0051] Calculation rule: For arriving and departing trains whose actual stop time is longer than the scheduled stop time, calculate the difference between the scheduled stop time and the actual stop time.

[0052] For example, in one embodiment, the train is scheduled to arrive at 10:00 and depart at 10:10 (scheduled stop at the station for 10 minutes), but actually arrives at 10:01 and departs at 10:15 (actual stop at the station for 14 minutes). In this embodiment, the over-stop time is 4 minutes.

[0053] S5. Output the statistical results of on-time trains and trains that stop beyond their designated stops. The statistical results include train information and the corresponding on-time time or the duration of the extra stop.

[0054] As described above, the CTC station train delay statistics method of the present invention obtains train operation data by periodically accessing the train data file of the station server, processes the train operation data to obtain the effective train queue Trains[n], and then performs statistics on on-time trains and trains that skip stops based on this data. This method can realize automatic statistical analysis of train delay data, reduce the workload of station staff in manual statistics, avoid the omissions caused by manual judgment, and ensure real-time updates of statistical results, significantly improving work efficiency and data accuracy, and providing strong support for optimizing station transportation operations.

[0055] Furthermore, this invention is based on system collaboration and data integration. Relying on the existing CTC3.0 system, it does not require large-scale addition of hardware. By optimizing the data transmission path, it breaks down data barriers within the system, realizes automatic statistics of vehicle delay information, makes full use of existing resources, and reduces implementation costs.

[0056] Furthermore, the data and information required for statistics in this invention are all derived from real CTC system operation data, which can ensure the objectivity and timeliness of the data, and can effectively reflect the actual situation of train operation at the station, providing a reliable basis for transportation operation adjustments.

[0057] Furthermore, the method for calculating train delays at CTC stations according to the present invention also includes: visualizing the statistical results of on-time trains and trains that skip stops (see [link to documentation]). Figure 2 and Figure 3 In practical applications, a visual interactive design, i.e., a visual display interface, can be adopted to present complex delay data in the form of intuitive charts or lists, so that staff can quickly obtain key information, reduce the difficulty of operation, and thus improve the user experience.

[0058] Based on the same inventive concept, this invention also provides an automatic train delay statistics system for stations based on a CTC system. This system is used to implement the aforementioned method for statistics of train delays at CTC stations. Specifically, the system includes a data acquisition module, a data cleaning module, a punctuality statistics module, an over-stop statistics module, and a result output module. The data acquisition module is used to periodically access train data files and acquire train operation data. The data cleaning module is connected to the data acquisition module and is used to generate an effective train queue based on the train operation data. The punctuality statistics module is connected to the data cleaning module and is used to calculate punctuality time and generate a punctuality train queue. The over-stop statistics module is connected to the data cleaning module and is used to calculate over-stop duration and generate an over-stop train queue. The result output module is connected to both the punctuality statistics module and the over-stop statistics module and is used to output the statistical results.

[0059] As described above, the automatic train delay statistics system based on the CTC system of this invention combines a data acquisition module, a data cleaning module, a punctuality statistics module, an over-stop statistics module, and a result output module. By periodically and automatically accessing train data files and filtering valid data, it completely replaces the traditional manual recording method, significantly improving data collection efficiency. Therefore, this system can process large amounts of train operation data in a short time, avoiding the time-consuming and labor-intensive problem of manual statistics. This method is particularly suitable for high-density traffic scenarios in large hub stations. Thus, the automatic train delay statistics system based on the CTC system of this invention, with its automated statistics function, greatly reduces the manual input of station staff in delay data statistics, allowing staff to devote more energy to core tasks such as train scheduling and operational coordination, thereby improving overall work efficiency.

[0060] Furthermore, in this invention, the station server operates using a dual-machine synchronous mechanism. Even if the data acquisition module is only installed on one of the station servers, it can still acquire train data files from both station servers. In practical applications, the data acquisition module on one station server / machine can obtain train data files from the other station server / machine via SSH or FTP. By reading the train data files from the two files on the two machines respectively, the integrity, correctness, and timeliness of the data can be guaranteed.

[0061] Furthermore, in this invention, the result output module can also be used to visualize the statistical results (see [link to related documentation]). Figure 2 and Figure 3 In practical applications, the results output module can adopt a visual interactive design (such as a user-friendly visual display interface) to present complex delay data in the form of intuitive charts, clear lists, etc., so that staff can quickly obtain key information, reduce the difficulty of operation, and thus improve the user experience.

[0062] Based on the same inventive concept, the present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned method for calculating vehicle delays at CTC stations.

[0063] Based on the same inventive concept, the present invention also provides an electronic device, the electronic device comprising: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the aforementioned steps of CTC station counting vehicle delays.

[0064] In summary, the present invention provides a method, system, readable storage medium, and electronic device for calculating train delays at a CTC station. This method obtains train operation data by periodically accessing train data files on a station server, processes the train operation data to obtain valid train queues (Trains[n]), and then performs statistics on on-time trains and trains that skip stops. This approach enables automatic statistical analysis of train delay data, reduces the workload of manual statistics by station staff, avoids omissions due to manual judgment, and ensures real-time updates of statistical results, significantly improving work efficiency and data accuracy, and providing strong support for optimizing station transportation operations.

[0065] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0066] In the description of this invention, it should be understood that the terms "center," "height," "thickness," "upper," "lower," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0067] In the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0068] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0069] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method of CTC station tallying vehicle delays, characterized by, Include: S1. The station server periodically accesses the train data file to obtain train operation data; S2. Filter the train operation data to obtain the effective train queue; S3. Based on the effective train queue, perform statistics on trains rushing to catch up, including: Determine whether the actual arrival time of the train is later than the planned arrival time, and whether the actual stopping time of the train is less than the planned stopping time; If the above conditions are met, the time for this train to make its journey is calculated, and the train information is stored in the train queue for trains making their journey. S4. Based on the aforementioned effective train queue, perform statistics on trains that skip stations, including: Determine whether the actual stopping time of the train exceeds the planned stopping time; If the actual stopping time of a train exceeds the planned stopping time, the overstaying time of this train number is calculated, and the train information of this train is stored in the overstaying train queue. S5. Output the statistical results of on-time trains and trains that stop beyond their designated stops; The station server includes a statistics server and an operation server. In step S1, the statistics server is used to periodically access the train data file, which is generated by the operation server. In S3, the calculation method for the time required to make the trip includes: If the train arrives late but departs on time or early, the time to catch up is the difference between the actual arrival time and the planned arrival time. If a train arrives and departs late, but the actual stop time is less than the planned stop time, the time to catch up is the difference between the late arrival time and the late departure time.

2. The method for CTC station to count train delay of claim 1, wherein, In step S2, filtering the train operation data includes: Remove duplicate data, train data outside the statistical period, and invalid train data.

3. The method of claim 2, wherein the CTC station counts the vehicle as late, and In step S2, removing invalid train data includes: Remove data for trains not registered at this station, remove data for trains that have been deleted, and remove data for trains that have not been converted to actual operation.

4. The method of claim 1, wherein the CTC station counts the vehicle as late, and The train information stored in the punctual train queue in S3 includes: Train number, station number, actual arrival time, scheduled arrival time, actual departure time, and scheduled departure time.

5. The method for CTC station to count train delays of claim 1, wherein, In S4, the method for calculating the over-station stop time is as follows: Excessive stop time = Actual stop time - Planned stop time.

6. The method for calculating train delays at CTC stations as described in claim 1, characterized in that, The train information stored in the S4 extra-stop train queue includes: Train number, station number, and duration of extra stops.

7. The method for calculating train delays at CTC stations as described in claim 1, characterized in that, The station server operates using a dual-machine synchronous mechanism, where one station server can obtain train data files from the other station server based on various data transmission protocols.

8. The method for calculating train delays at CTC stations as described in claim 7, characterized in that, The station server can obtain train data files from another station server via SSH or FTP.

9. The method for calculating train delays at CTC stations as described in claim 1, characterized in that, Also includes: The statistical results of the queuing for trains arriving on time and the queuing for trains that stop at stations beyond the designated stops will be displayed visually.

10. A CTC system-based automatic station train delay statistics system, characterized in that, It is used to implement the method for calculating train delays at CTC stations as described in any one of claims 1 to 9, the system comprising: The data acquisition module is used to periodically access train data files and acquire train operation data; A data cleaning module, which is connected to the data acquisition module, is used to generate an effective train queue based on train operation data. The on-time statistics module is connected to the data cleaning module. The on-time statistics module is used to calculate on-time time and generate on-time train queues. An extra-stop statistics module, which is connected to the data cleaning module, is used to calculate the extra-stop duration and generate an extra-stop train queue. The result output module is connected to the on-time statistics module and the over-stop statistics module respectively, and the result output module is used to output statistical results.

11. The automatic train delay statistics system based on the CTC system as described in claim 10, characterized in that, The station server operates using a dual-machine synchronous mechanism, and the data acquisition module can acquire train data files from both station servers.

12. The automatic train delay statistics system based on the CTC system as described in claim 10, characterized in that, The result output module can also be used to visualize the statistical results.

13. A readable storage medium, characterized by, The readable storage medium stores a computer program that, when executed by a processor, implements the steps of the CTC station vehicle delay statistics method as described in any one of claims 1 to 9.

14. An electronic device, comprising: The electronic device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the steps of the method for calculating vehicle delays at a CTC station as described in any one of claims 1 to 9.

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