Multi-signal train control system simulation evaluation method, system, equipment and medium

Abstract

The invention relates to the technical field of rail transit, in particular to a multi-signal train control system simulation evaluation method, system and device and a medium. A plurality of evaluation functions are integrated, and the evaluation range covers a plurality of key dimensions of train operation. Train operation efficiency and safety abnormity evaluation are closely associated and coordinated, and a complete and systematized evaluation architecture is constructed. The running situation of the train is comprehensively grasped by comprehensively considering running efficiency indexes such as morning and evening points, tracking intervals, energy consumption and key section train occupied time and safety abnormity indexes such as train allowable speed sudden change, abnormal braking, section abnormal parking, abnormal access handling and motor temperature rise alarm. Based on fusion and deep analysis of multi-source data, real-time changes of train states, such as real-time power consumption, traction operation time and the like of a train in a specific area, are comprehensively analyzed, and a powerful basis is provided for formulating an optimization strategy.

Description

Technical Field

[0001] The present disclosure relates to the technical field of rail transit, and particularly to a simulation evaluation method, system, device and medium for a multi-signal train control system. Background Art

[0002] With the continuous development of railway transportation and the increasing complexity of the railway network, the safety, efficiency and reliability of train operation have received more and more attention. After the signal system design is completed, it is necessary to perform simulation operation on the system to evaluate the train operation effect to detect the compliance of the signal system design. It is not only necessary to pay attention to the operation efficiency of the train, such as punctuality, energy consumption, etc., but also to attach importance to the train operation safety under the constraints of the signal system. With the rapid development of emerging railway forms such as high-speed railways and urban rails, higher requirements are also put forward for the accuracy, real-time performance and adaptability of train simulation operation evaluation. However, in the current field of train simulation operation evaluation, there are still many areas in the existing technologies that need to be improved and perfected: The data source is single and the integration of multi-source data is insufficient. Most simulation operation evaluation systems are mainly based on operation diagrams and operation data, lacking multi-source information such as signal system design data and ground equipment data, resulting in incomplete evaluation background information, lacking the influence and constraints of the signal system on train operation, and making it difficult to accurately calculate train operation parameters and actual tracking intervals. The limitations of the data source and the lack of integration and correlation capabilities restrict the accuracy and comprehensiveness of the evaluation system.

[0003] The evaluation functions are scattered and limited. Most simulation operation evaluation systems focus on evaluating one or two items in train operation efficiency, such as train delay and train energy consumption. The evaluation indicators are single and cannot comprehensively reflect the actual situation of train operation. Moreover, the evaluation of abnormal train operation safety such as train protection is often missing or not comprehensive enough, and a complete collaborative evaluation system has not been formed.

[0004] The compatibility is limited and it is difficult to effectively cope with the complexity and differences brought by the simulation operation evaluation of multiple types of signal system train control systems. It often cannot accurately capture the subtle differences and complex situations of train operation under various signal systems, resulting in large errors in the evaluation results.

[0005] In summary, there is an urgent need for a train operation evaluation technical solution that is more accurate, comprehensive, has higher compatibility and has deep data analysis capabilities. Summary of the Invention

[0006] In view of the above problems, the present disclosure provides a simulation evaluation method, system, device and medium for a multi-signal train control system.

[0007] In a first aspect, a simulation evaluation method for a multi-signal train control system, the method includes: Verifying the operation plan to be evaluated, and passing the verification when the operation plan meets the preset standard; Collect data on the verified operation plan and organize it into a data set; Based on the selected evaluation parameters, perform data analysis on the operation plan based on the data set and generate an evaluation result.

[0008] Furthermore, collect data on the verified operation plan and organize it into a data set, including: Extract operation plan-related data from each data source by reading signal system design data, train operation parameters, operation plan data, train dynamics simulation operation log data, and train control system device log data; Check and clean the relevant data, removing data with non-preset formats, data outside the preset range, as well as missing values or outliers; Match and merge the data from different data sources through specified identifiers to form a unified data set for analysis; the specified identifiers include: train number, line, station identifier, and time.

[0009] Furthermore, the evaluation parameters include: Train number, selected evaluation time range, line range, evaluation dimension indicators, and calculation step size.

[0010] Furthermore, perform data analysis on the operation plan, including: Identify the speed change characteristics and energy consumption characteristics during the train operation process through data analysis.

[0011] Furthermore, perform data analysis on the operation plan, and also include: Statistically evaluate the early and late arrival situations of all trains, including: the early and late arrival times of all stations and all trains, count the number of early and late arrival trains at different stations, and compare with the preset values to generate a statistical chart of train early and late arrival times and a statistical chart of train late arrival times at each station; Take the allowed threshold and accident threshold for late arrival time statistics as evaluation indicators, evaluate the execution deviation of the planned operation diagram, count the on-time rate, late arrival rate, and accident rate of trains, and generate a statistical chart of train deviation times.

[0012] Furthermore, perform data analysis on the operation plan, and also include: Statistical evaluation of the tracking interval time between all trains, including: statistical evaluation of interval tracking, station arrival, station departure, station passing, and station arrival interval times; According to the input tracking interval calculation step value and calculation step unit, statistically evaluate the running time of trains passing through the mileage of all fixed recording point positions. The fixed recording points are the station center, the mileage positions of all block sections in the interval, the station approach signal, the approach and departure signal, the station route signal, and the fixed mileage positions calculated based on the tracking interval calculation step. Calculate the tracking interval time of fixed recording points in the train section and the statistical results of the maximum tracking interval time in the section, which are used to analyze the simulation effect evaluation of the tracking interval time in the section.

[0013] Furthermore, the data analysis of the operation plan also includes: According to the train operation simulation result data and the selected line range, calculate the running time between stations, the total running time, the total station stop time, the travel speed, and the technical speed of the selected trains.

[0014] Furthermore, the data analysis of the operation plan also includes: Evaluate and statistically analyze the section distance, running time, maximum speed, average speed, cumulative power consumption, and traction running time of the trains; According to the trains and the evaluation range, evaluate and statistically analyze the running mileage position, running time, and real-time power consumption at the calculation time step, and generate the train distance-energy consumption curve; Calculate the unit energy consumption according to the train type and traction type respectively, including: power consumption per ten thousand tons-kilometers, power consumption per kilometer, fuel consumption per ten thousand tons-kilometers, and fuel consumption per kilometer; According to the evaluation range, statistically analyze the total real-time energy consumption data of all trains and generate the total time-energy consumption data curve.

[0015] Furthermore, the data analysis of the operation plan also includes: Statistically analyze the occupancy time of train sections in the selected time period and the throat areas of the selected stations. The range is the whole process from the locking of the track section, the running of the train, to the unlocking of the track section; Calculate the utilization rate according to the idle coefficient and generate the occupancy statistical chart of the turnout track section.

[0016] Furthermore, the data analysis of the operation plan also includes: Statistically analyze the abnormal operation scenarios of the trains, which are used to analyze the reasons for the abnormal operation scenarios; Statistically analyze the number of times, time, and location of abnormal braking; Abnormal braking is an unexpected braking caused by the sudden change of the permitted speed of the train under the protection of ATP due to the signal system constraint; Statistically analyze the number of times, time, and location of abnormal stops in the section; Abnormal stops in the section are stop scenarios where the train does not need to stop in the operation plan; Statistically analyze the number of times, time, and location of abnormal non-handling of station routes; Abnormal routes are scenarios where some track sections are in the locked state and the train route cannot be handled when the train route time is triggered or the location is triggered; Statistically analyze the number of times, time, and location of motor overheating alarms.

[0017] Furthermore, the data analysis of the operation plan also includes: The traction calculation diagram is drawn according to the train number and the operation section, and is used to evaluate the traction calculation performance of the train under the current line conditions; among them, the traction calculation diagram includes: a speed-distance curve, a speed-time curve, a distance-acceleration curve, and a tracking interval time curve.

[0018] In a second aspect, a multi-signal train control system simulation and evaluation system includes: a pre-inspection unit, a data collection unit, and an evaluation unit; The pre-inspection unit is used to verify the operation plan to be evaluated, and the verification passes when the operation plan meets the preset standard; The data collection unit is used to collect data on the operation plan that has passed the verification and organize it into a data set; The evaluation unit is used to perform data analysis on the operation plan based on the selected evaluation parameters based on the data set and generate an evaluation result.

[0019] In a third aspect, an electronic device includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus; The memory stores a computer program; When the processor is used to execute the computer program stored on the memory, it implements the above-mentioned multi-signal train control system simulation and evaluation method.

[0020] In a fourth aspect, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned multi-signal train control system simulation and evaluation method.

[0021] The present disclosure has at least the following beneficial effects: The present disclosure realizes the diversification and comprehensiveness of data, incorporating data such as signal system design, operation diagram, train dynamics simulation operation, and train control system device logs. It delves into the interior of the train control system, and by obtaining key data such as the moving authorization, permitted speed, and braking curve of ATP, it provides a more accurate and dynamic basis for evaluation.

[0022] Integrates multiple evaluation functions, and the evaluation scope covers multiple key dimensions of train operation. It closely associates and coordinates the evaluation of train operation efficiency and safety anomalies, and constructs a complete and systematic evaluation framework. By comprehensively considering operation efficiency indicators such as arrival and departure delays, tracking intervals, energy consumption, and the time occupied by trains in key sections, as well as safety anomaly indicators such as sudden changes in train permitted speed, abnormal braking, abnormal parking in the section, abnormal route handling, and motor temperature rise alarm, it comprehensively grasps the operation situation of the train.

[0023] Achieve a comprehensive and high-precision evaluation of train operation, and be able to collect the speed and position information of the train in real time with a collection period lower than the ATP calculation period, and calculate the average speed and driving mileage of the train to reflect the train operation situation. Based on the fusion and in-depth analysis of multi-source data, it can comprehensively analyze the real-time changes in the train state, such as the real-time power consumption of the train in a specific area, the traction operation time, etc., providing a strong basis for formulating optimization strategies.

[0024] Adapt to multiple signal systems and can provide stable and reliable evaluation services for train operation under different systems. It is applicable to including CTCS-0, CTCS-1, CTCS-2, CTCS-3, CTCS-N, traditional CBTC, and the control system applicable to the virtual coupling operation of heavy-haul trains. The wide compatibility enables this system to have a wider application range in the field of rail transit and can meet the operation evaluation needs of different lines and different train types.

[0025] Other features and advantages of the present disclosure will be described in the subsequent specification, and, in part, will be obvious from the specification, or will be understood by implementing the present disclosure. The objectives and other advantages of the present disclosure can be realized and obtained through the structures pointed out in the specification and the drawings. Brief Description of the Drawings

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0027] Figure 1 It is a schematic flow diagram of the evaluation method according to the embodiment of the present disclosure; Figure 2 It is a schematic diagram of the functions of the evaluation system according to the embodiment of the present disclosure; Figure 3 It is a schematic diagram of the structure of the electronic device according to the embodiment of the present disclosure. Detailed Embodiments

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present disclosure in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are some, rather than all, of the embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present disclosure.

[0029] As an important means of transportation, the efficient and safe operation of railway transportation is of crucial importance. With the continuous expansion and complexity of the railway network, the need for accurate assessment and effective management of train operation is becoming increasingly urgent. Efficient train operation assessment is of key significance for optimizing railway operation, improving service quality, and ensuring transportation safety. The progress of data collection and transmission technology and data analysis and processing technology provides strong support for train operation assessment. Train operation assessment involves numerous parameters and factors, such as the speed, position, and energy consumption of the train. In addition to the train's own indicators, it also includes track conditions, signal systems, dispatching strategies, etc. Accurately assessing the running state of the train requires comprehensive consideration of various data and indicators.

[0030] Currently, the existing implementation schemes for train operation assessment mainly include the following: Scheme 1: A train arrival and departure delay assessment system based on the train operation diagram and simple monitoring data. This scheme judges the punctuality of the train by comparing the actual train operation time with the preset operation diagram. Train operation assessment is carried out by obtaining some operation parameters, such as speed, acceleration, etc. However, its data source is relatively limited, lacking the integration of signal system design data and ground equipment data, and it is difficult to comprehensively reflect the real situation of train operation.

[0031] Scheme 2: An assessment system only for specific indicators. For example, some systems focus on the energy consumption assessment of the train or only analyze the train tracking interval, and do not form a comprehensive assessment system for operation efficiency and safety anomalies.

[0032] In summary, the existing train operation assessment schemes need to be further improved and perfected in terms of data comprehensiveness, analysis depth, function integration, and the ability to handle abnormal situations, etc., to meet the growing railway transportation needs.

[0033] Therefore, as Figure 1 shown, the present disclosure provides a multi-signal train control system simulation assessment method, and the method includes: Verifying the operation plan to be evaluated, and the verification passes when the operation plan meets the preset standard; Collecting data for the verified operation plan and organizing it into a data set; Based on the selected evaluation parameters, performing data analysis on the operation plan based on the data set and generating an evaluation result.

[0034] When specifically implemented, it is introduced as follows: As Figure 1 shown, the processing flow of the multi-type signal system train control system simulation operation assessment system is described as follows: The system starts to load the configuration file and establish a database connection.

[0035] Obtain the list of operation plans, and the user selects the operation plans to be evaluated according to the plan status. After selecting the operation plan, the system verifies the operation plan to ensure the legality and effectiveness of the selected plan and whether it meets the evaluation conditions.

[0036] By reading the signal system design data, train operation parameters, operation plan data, train dynamics simulation operation log data, and train control system equipment log data, relevant data is extracted from each data source for temporary caching.

[0037] The system checks and cleans the data, checking whether the data format is correct, whether the data values are within a reasonable range, whether there are missing values or outliers, etc.

[0038] Match and merge the data from different data sources through specified identifiers (such as train numbers, line / station identifiers, time, etc.) to form a unified data set for subsequent analysis.

[0039] Identify key performance indicators during the train operation process through data analysis, such as speed change characteristics, energy consumption characteristics, etc.

[0040] The user selects the evaluation function through the interface switch.

[0041] The user selects the train, selects the evaluation time range or line range, sets evaluation indicators, calculation step size and other parameters through the interface.

[0042] The system generates the evaluation results through calculation and displays the evaluation results to the user in an intuitive way, such as generating operation diagrams and statistical charts.

[0043] The evaluation process ends.

[0044] As Figure 2 shown, the multi-type signal system train control system simulation operation evaluation system provides a more accurate, comprehensive, higher compatibility and in-depth data analysis ability train operation evaluation system and method. The system is divided into a client and a server, and the http protocol is used for communication between the client and the server to achieve interactive data processing during the design process. The client is developed using the vue lightweight framework and is responsible for visual display of evaluation results; the server uses the SpringCloud microservice architecture and is responsible for data collection and processing; The functions of the multi-type signal system train control system simulation operation evaluation system mainly include seven evaluation functions: train operation diagram evaluation, train tracking interval time evaluation, train operation index evaluation, train operation energy consumption evaluation, train operation data statistics, abnormal scenario statistics, and train traction calculation diagram drawing.

[0045] Train operation diagram evaluation: Evaluate the arrival and departure delays of all trains, including the arrival and departure delay times of all stations and all trains, and the number of trains with arrival and departure delays at different stations; generate statistical charts of train arrival and departure delay times and statistical charts of train arrival and departure delay times at each station.

[0046] Using the allowable threshold and accident threshold for delay time statistics as evaluation indicators, automatically evaluate the execution deviation of the planned train operation diagram, count the on-time rate, delay rate and accident rate of trains, and generate a statistical chart of train deviation time; retrieve the train operation diagram and base map after the train operation simulation calculation is completed to visually analyze the simulation effect of the operation diagram.

[0047] Train tracking interval time evaluation: Statistical evaluation of the tracking interval time between all trains, mainly including statistical evaluation of interval tracking, station arrival, station departure, station passing and station arrival interval times.

[0048] Compatible with different records of on-vehicle operation control of different trains, calculate the step value and step unit according to the input tracking interval, and count the running time of the train passing through the mileage of all fixed record points. The fixed record points are the center of the station, the mileage of all block sections in the interval, the approach signal of the station, the approach and departure signals of the station, the route signal of the station and the fixed mileage position calculated by the step of the tracking interval input by the user.

[0049] Calculate the statistical results of the train interval fixed record point tracking interval time and the maximum interval tracking time in the interval, which are used to analyze the simulation effect evaluation of the interval tracking interval time.

[0050] Train operation index evaluation: Be able to automatically calculate the running time between stations, total running time, total station stop time, travel speed and technical speed of the selected trains according to the train operation simulation result data and the selected line range.

[0051] Train operation energy consumption evaluation: Evaluate and count the interval distance, running time, maximum speed, average speed, cumulative power consumption and traction running time of the selected trains; Evaluate and count the running mileage position, running time and real-time power consumption according to the selected trains and evaluation range at the calculation time step, and generate a train distance-energy consumption curve.

[0052] Calculate the unit energy consumption according to the train type and traction type, including the power consumption per ten thousand tons per kilometer, the power consumption per kilometer, the fuel consumption per ten thousand tons per kilometer and the fuel consumption per kilometer.

[0053] Automatically count the total real-time energy consumption data of all trains according to the selected evaluation range and multiple trains, and generate a total energy consumption data curve according to needs.

[0054] Train operation data statistics: Statistical analysis is carried out on the train occupancy time of the track sections in the selected time period and the selected station throat. The range is the whole process from track section locking → train operation → track section unlocking. Calculate the utilization rate according to the determined idle coefficient, and generate the occupancy statistical chart of the turnout track section.

[0055] Abnormal operation scenario statistics: Statistical analysis is carried out on the abnormal operation scenarios of trains to facilitate users to analyze the reasons for abnormal operation scenarios.

[0056] Statistical analysis is carried out on the number of times, time and location of abnormal braking. Abnormal braking is an unexpected braking caused by a sudden change in the allowable speed of the train under the protection of ATP, which is restricted by the signal system.

[0057] Statistical analysis is carried out on the number of times, time and location of abnormal stops in the section. An abnormal stop in the section is a scenario where the train stops at a location where it is not required to stop in the operation plan. The system records the time from the start of the abnormal stop to the start of the abnormal stopped train.

[0058] Statistical analysis is carried out on the number of times, time and location of abnormal non - handling of station routes; an abnormal route is a scenario where certain track sections cannot handle the train route in the locked state when the train route time or location is triggered.

[0059] Statistical analysis is carried out on the number of times, time and location of motor over - temperature alarms. For example, when a locomotive - hauled train runs at the maximum handle position (or handle coefficient) and the cumulative time of continuously running at a speed lower than the "minimum calculated speed" of the current locomotive configuration in the locomotive depot exceeds the set value of the "motor temperature rise alarm time" in the "train operation simulation parameters", an alarm of motor over - temperature is determined.

[0060] Train traction calculation diagram drawing: Draw the traction calculation diagram according to the train number and operation section selected by the user, mainly including speed - distance curve, speed - time curve, distance - acceleration curve and following interval time curve. It is used to evaluate the traction calculation performance of the train under the current line conditions.

[0061] This disclosure uses multi-source data input: multiple types of data such as signal system design data, train operation parameters, operation plan data, train dynamic simulation operation data, and train control system equipment data are used as input for train operation evaluation and analysis. Comprehensive evaluation by loading train control system equipment data: It can conduct comprehensive operation evaluation based on train control system equipment data, such as ATP movement authorization, permitted speed, braking curve, and analyze the train operation status according to the real-time state changes of the train control system. Compatible with multiple types of systems: It is compatible with multiple types of signal systems and supports the evaluation of multi-train tracking operation, and supports the selection of evaluation trains and evaluation scopes. Integration of multiple evaluation functions: The evaluation scope includes train operation efficiency evaluation (early or late arrival, tracking interval, energy consumption, time of train occupying turnout track section) and safety anomaly evaluation (abnormal braking, abnormal parking in the section, abnormal route handling, motor overheating alarm). They are interrelated and collaborative to form a complete train operation evaluation system.

[0062] Compared with the train early or late arrival evaluation system based on operation diagrams and simple monitoring data, this disclosure adds signal system design data, train operation parameters, and train control system equipment log data as input, which can provide more comprehensive background information for evaluation and calculate the train operation time and tracking interval more accurately. In case of anomalies, it can assist in quickly locating the fault point.

[0063] Compared with the evaluation system for specific indicators, this disclosure conducts integrated evaluation of evaluation functions. The evaluation scope includes train operation efficiency evaluation and safety anomaly evaluation and is compatible with multiple types of signal systems, comprehensively evaluating the train operation status under different signal system controls to form a complete train operation evaluation system.

[0064] This disclosure is designed based on the C / S architecture, uses the vue lightweight framework to develop desktop applications, and uses the SpringCloud microservice architecture for service development. In specific implementation, other frameworks can be used for the client and the server.

[0065] A multi-signal train control system simulation evaluation system includes: a pre-inspection unit, a data collection unit, and an evaluation unit; The pre-inspection unit is used to verify the operation plan to be evaluated, and the verification passes when the operation plan meets the preset standard; The data collection unit is used to collect data for the verified operation plan and organize it into a data set; The evaluation unit is used to conduct data analysis on the operation plan based on the selected evaluation parameters and the data set, and generate an evaluation result.

[0066] Such as Figure 3As shown, the present disclosure provides an electronic device, including a processor 301, a communication interface 302, a memory 303, and a communication bus 304. Among them, the processor 301, the communication interface 302, and the memory 303 complete communication with each other through the communication bus 304; The memory 303 stores a computer program; The processor 301 is configured to implement the above method when executing the computer program stored on the memory 303.

[0067] The present disclosure provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0068] The computer-readable storage medium may be included in the device / device described in the above embodiments; it may also exist alone without being assembled into the device / device. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiments of the present disclosure is implemented.

[0069] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or device.

[0070] Although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A simulation evaluation method for a multi-signal train control system, characterized in that, The method includes: Verifying the operation plan to be evaluated, and passing the verification when the operation plan meets the preset standard; Collecting data on the operation plan that has passed the verification and organizing it into a data set; Based on the selected evaluation parameters, performing data analysis on the operation plan based on the data set and generating an evaluation result.

2. The multi-signal train control system simulation evaluation method according to claim 1, wherein Collecting data on the operation plan that has passed the verification and organizing it into a data set includes: Extracting operation plan-related data from each data source by reading signal system design data, train operation parameters, operation plan data, train dynamics simulation operation log data, and train control system device log data; Checking and cleaning the relevant data to remove data with non-preset formats, data outside the preset range, as well as missing values or outliers; Matching and merging the data from different data sources through a specified identifier to form a unified data set for analysis; the specified identifier includes: train number, line, station identifier, and time.

3. The multi-signal train control system simulation evaluation method according to claim 1, wherein The evaluation parameters include: Train number, selected evaluation time range, line range, evaluation dimension index, and calculation step size.

4. The multi-signal train control system simulation evaluation method according to claim 1, wherein Performing data analysis on the operation plan includes: Identifying the speed change characteristics and energy consumption characteristics during the train operation process through data analysis.

5. The multi-signal train control system simulation evaluation method according to claim 1, wherein Performing data analysis on the operation plan further includes: Statistical evaluation of the early and late arrival situations of all trains, including: the early and late arrival times of all stations and all trains, counting the number of early and late arrival trains at different stations, and comparing with the preset value to generate a statistical chart of train early and late arrival times and a statistical chart of train late arrival times at each station; Using the allowable threshold and accident threshold of late arrival time statistics as evaluation indicators, evaluating the execution deviation of the planned operation diagram, counting the on-time rate, late arrival rate, and accident rate of trains, and generating a statistical chart of train deviation times.

6. The multi-signal train control system simulation evaluation method according to claim 1, wherein Performing data analysis on the operation plan further includes: Statistical evaluation of the tracking interval time between all trains, including: statistical evaluation of interval tracking, station arrival, station departure, station passing, and station arrival intervals; According to the input tracking interval calculation step value and calculation step unit, statistically calculating the running time of the train passing through the mileage positions of all fixed recording points, where the fixed recording points are the station center, the mileage positions of all block sections in the interval, the station approach signal, the approach and departure signal, the station route signal, and the fixed mileage positions calculated by the tracking interval calculation step; Calculating the statistical results of the train interval fixed recording point tracking interval time and the interval maximum tracking interval time for analyzing the simulation effect evaluation of the interval tracking interval time.

7. The multi-signal train control system simulation evaluation method according to claim 1, wherein Performing data analysis on the operation plan further includes: Calculate the running time between stations, total running time, total station stop time, travel speed, and technical speed of the selected train based on the train operation simulation result data and the selected line range.

8. A multi-signal train control system simulation evaluation method according to claim 1, characterized in that Performing data analysis on the operation plan further includes: Evaluating and statistically analyzing the section distance, running time, maximum speed, average speed, cumulative power consumption, and traction running time of the train; Evaluating and statistically analyzing the running mileage position, running time, and real-time power consumption according to the train and the evaluation range at the calculation time step, and generating a train distance-energy consumption curve; Calculating the unit energy consumption respectively according to the train type and traction type, including: power consumption per ten thousand tons per kilometer, power consumption per kilometer, fuel consumption per ten thousand tons per kilometer, and fuel consumption per kilometer; According to the evaluation range, statistically analyze the total real-time energy consumption data of all trains and generate a total time-energy consumption data curve.

9. A multi-signal train control system simulation evaluation method according to claim 1, characterized in that Performing data analysis on the operation plan further includes: Statistically analyzing the occupancy time of the train on the track section of the selected throat of the selected station within the selected time period, and the range is the whole process from the locking of the track section, the running of the train, to the unlocking of the track section; Calculate the utilization rate according to the idle factor and generate a statistical chart of the occupancy of the turnout track section.

10. A multi-signal train control system simulation evaluation method according to claim 1, characterized in that Performing data analysis on the operation plan further includes: Statistically analyzing the abnormal operation scenarios of the train for analyzing the reasons for the abnormal operation scenarios; Statistically analyzing the number of times, time, and position of abnormal braking; abnormal braking is an unexpected braking caused by the sudden change of the allowable speed of the train under the protection of ATP due to the signal system constraint; Statistically analyzing the number of times, time, and position of abnormal stops in the section; abnormal stops in the section are stop scenarios where the train does not need to stop in the operation plan; Statistically analyzing the number of times, time, and position of abnormal non-handling of station routes; abnormal routes are scenarios where certain track sections are in a locked state and the train route cannot be handled when the train route time is triggered or the location is triggered; Statistically analyzing the number of times, time, and position of motor overheating alarms.

11. A multi-signal train control system simulation evaluation method according to claim 1, characterized in that Performing data analysis on the operation plan further includes: Drawing a traction calculation diagram according to the train number and operation section for evaluating the traction calculation performance of the train under the current line conditions; wherein, the traction calculation diagram includes: speed-distance curve, speed-time curve, distance-acceleration curve, and tracking interval time curve.

12. A multi-signal train control system simulation and evaluation system, characterized in that, Including: A pre-inspection unit, a data collection unit, and an evaluation unit; The pre-inspection unit is used to verify the operation plan to be evaluated, and the verification passes when the operation plan meets the preset standard; The data collection unit is used to collect data on the operation plan that has passed the verification and organize it into a data set; The evaluation unit is used to perform data analysis on the operation plan based on the data set according to the selected evaluation parameters and generate an evaluation result.

13. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete their mutual communication through the communication bus; The memory stores a computer program; The processor is used to implement a multi-signal train control system simulation evaluation method described in any one of claims 1-11 when executing the computer program stored on the memory.

14. A computer-readable storage medium stores a computer program, characterized in that, When the computer program is executed by the processor, it implements a multi-signal train control system simulation evaluation method described in any one of claims 1-11.

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