Railway dispatching decision toughness evaluation method and system based on simulation driving

Abstract

A railway dispatching decision toughness evaluation method based on simulation driving comprises the steps that a system overall framework is constructed, specifically, the system overall framework including the data processing function, the simulation driving function, the toughness evaluation analysis function and the visual display function is constructed from the angle of function implementation; constructing a data processing module and mechanism: normalizing and regularizing dynamic and static data of the system, and constructing scheduling decision-related data structures and an association mapping relationship between the data structures; constructing a simulation driving module and mechanism: constructing a simulation verification mechanism and verification method of a scheduling decision based on a railway signal and a railway operation rule, inputting the scheduling decision, and outputting a verification result; constructing an evaluation analysis module and mechanism: constructing an evaluation model comprising a toughness evaluation index and a calculation method of the scheduling decision, and realizing toughness evaluation of the input scheduling decision; and the human-computer interaction and visual display module is used for displaying the toughness evaluation result of the scheduling decision in a visual mode.

Description

Technical Field

[0001] The present invention relates to a method and a system thereof, in particular to a simulation-driven railway dispatching decision resilience evaluation method and system, belonging to the field of railway communication signals. Background Art

[0002] Dispatching decision is the key to ensuring the orderly operation of trains according to the plan in railway operation. Especially under the interference of emergencies, scientific and effective dispatching decisions play a decisive role in reducing train delays. However, at present, the decision-making method of railway dispatching still mainly relies on manual experience, and the evaluation of the scientificity, effectiveness and feasibility of dispatching decisions mostly uses the actual effects after the implementation of the decisions for verification. Usually, the main indicators are the final delay degree of trains and the completion degree of various construction orders according to the plan. The final evaluation has a certain lag, and it is rarely possible to scientifically evaluate and assess dispatching decisions at the decision-making stage. Summary of the Invention

[0003] Aiming at the evaluation problem of railway dispatching decisions, the present invention proposes a simulation-driven railway dispatching decision resilience evaluation method and system. By combining simulation drive and resilience evaluation, it quickly verifies and evaluates the dispatching decisions generated by dispatchers or dispatching systems, realizes the rapid evaluation of the scientificity, effectiveness and feasibility of dispatching decisions, and assists users in decision-making. The technical solutions are as follows:

[0004] A simulation-driven railway dispatching decision resilience evaluation method, characterized in that:

[0005] Step S1: Construct the overall system architecture: From the perspective of function realization, construct an overall system architecture including functions of data processing, simulation drive, resilience evaluation analysis and visualization display;

[0006] Step S2: Construct a data processing module and mechanism: Standardize and regularize the dynamic and static data of the system, and construct the relevant data structures of dispatching decisions and the associated mapping relationships between data structures;

[0007] Step S3: Construct a simulation drive module and mechanism: Based on railway signals and railway operation rules, construct a simulation verification mechanism and method for dispatching decisions, input dispatching decisions, and output verification results;

[0008] Step S4: Construct an evaluation analysis module and mechanism: Construct an evaluation model including resilience evaluation indicators and calculation methods for dispatching decisions to realize the resilience evaluation of the input dispatching decisions;

[0009] Step S5: Human-computer interaction and visualization display module: Display the resilience evaluation results of dispatching decisions in a visual way.

[0010] The present invention discloses a non - volatile storage medium, characterized in that the non - volatile storage medium includes a stored program, wherein when the program runs, it controls the device where the non - volatile storage medium is located to execute the above - mentioned method.

[0011] The present invention also discloses a simulation - driven railway dispatching decision - making resilience evaluation system, characterized in that the system includes: a processor, a memory, a communication interface, and a bus; the processor, the memory, and the communication interface are connected through the bus and complete communication with each other; the memory stores executable program code; the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory to execute the above - mentioned method.

[0012] Beneficial effects

[0013] (1) Realize an effective evaluation of the resilience of railway dispatching decisions;

[0014] (2) Propose a flexible dispatching decision - making simulation verification mechanism, and realize an effective verification of dispatching decisions in the formulation stage;

[0015] (3) Propose a dispatching decision - making resilience evaluation method that integrates the train delay absorption ability, the train operation diagram recovery ability, and the anti - destruction ability against emergencies, enhancing the scientificity, effectiveness, and feasibility of dispatching decisions. Brief description of the drawings

[0016] Figure 1 It is a schematic diagram of the process of the simulation - driven railway dispatching decision - making resilience evaluation method and system of the present invention;

[0017] Figure 2 It is a schematic diagram of the structure of the simulation - driven railway dispatching decision - making resilience evaluation system of the present invention;

[0018] Figure 3 It is a logic diagram of the data processing module of the present invention;

[0019] Figure 4 It is a logic diagram of the simulation - driven module of the present invention;

[0020] Figure 5 It is a logic diagram of the simulation time - sequence drive of the present invention. Detailed implementation manners

[0021] The present invention proposes a simulation - driven railway dispatching decision - making resilience evaluation method, and the schematic diagram of the method process is as Figure 1 shown.

[0022] In step S1, from the perspective of system function realization, the overall structure of the system is constructed, including the following four functional modules, and their functions and the logical relationships between the modules are as Figure 2as shown

[0023] (1) A data processing module constructs corresponding data structures according to the characteristics of the data required for scheduling decision-making and operation environment simulation to standardize and regularize the data related to scheduling decision-making and simulation environment, including dynamic and static data such as train operation plans, dispatching orders, signal equipment and their states, and constructs the associated mapping relationships between different data structures, including the relationships between trains and operation plans, trains and dispatching orders, trains and signal equipment, operation plans and signal equipment, and dispatching orders and signal equipment, forming the basic data support layer for the simulation and evaluation module. The specific implementation is shown in step S2;

[0024] (2) A simulation driving module is used to construct an internal rapid simulation environment for verifying the effect of scheduling decisions, including a signal driving layer for realizing the state changes of signal equipment such as track occupancy and vacancy, signal opening and prohibition, route locking, occupancy and vacancy, and temporary speed limits on the line; an operation rule layer for constructing train operation constraints such as train tracking rules, train arrival and departure time sampling rules, train conflict determination rules, and specific station operation regulations and dispatching regulations; and a simulation driving layer for driving trains to run according to scheduling decisions in the virtual simulation environment, and finally forming scheduling decision results such as train early and late arrival information and dispatching order execution status, which are used as the input for the resilience evaluation module. The specific implementation is shown in step S3;

[0025] (3) A resilience evaluation module constructs resilience evaluation indicators and corresponding calculation methods including late arrival absorption ability, recovery ability, and anti-destruction ability in combination with the output results of the simulation driving module, and outputs the final evaluation results. The specific implementation is shown in step S4;

[0026] (4) A human-computer interaction and visualization display module displays the resilience evaluation results of scheduling decisions in a visual way such as charts, and provides a human-computer interaction interface for adjusting the rule settings of the simulation driving module and the resilience evaluation module. The specific implementation is shown in step S5.

[0027] In step S2, the associated relationships between specific data structures and dynamic and static data are constructed to form the data processing module. The main structure is as Figure 3 shown, and the specific implementation method is as follows:

[0028] (1) Signal equipment can be abstracted as a vector set containing features such as tracks, routes, block sections, and signal lights. Based on the topological relationship of the railway line, the connection association relationship between signal equipment is constructed. The block section is associated with the interval signal light it protects, the interval signal light is associated with the block sections on both sides of it, the block section in the approach section of the station is associated with the entrance and exit signal lights, the entrance and exit signal lights are associated with the routes they protect, and the routes are associated with the corresponding receiving and dispatching tracks. According to the definition rules of the train operation direction in China, the up and down attributes of train operation are added, and finally a directional topological association relationship between signal equipment is formed to support the change of the environmental state of train operation;

[0029] (2) The dispatching decision can be divided into two parts: the train operation plan and the dispatching order. Among them, the train operation plan can be abstracted as a vector set containing plan features such as train identification, current station, arrival and departure times, operation tracks, and station operation types; and based on the train plan features, the association relationship between the train plan and signal equipment is constructed, associating the train plan with the tracks and with the routes, to uniquely determine the receiving and dispatching tracks and the corresponding routes of the train, and to support the path driving in the process of train movement simulation;

[0030] (3) The dispatching order includes construction orders, speed limit orders, and skylight orders, which can be uniformly abstracted as a vector set containing features such as dispatching order identification, dispatching order type, order execution period (start time, end time), execution entity (construction personnel, trains), and execution object (corresponding turnouts, intervals, etc. signal equipment); based on the dispatching order features, the association relationship between the dispatching order object and signal equipment is constructed to support the impact of the dispatching order on the operation environment and the resulting change of the operation state during the simulation process;

[0031] (4) Taking signal equipment as the key feature link, tracing back its association relationship with the train plan and the dispatching order, constructing the association relationship between the train plan and the dispatching order, forming the correspondence between the dispatching order and the train plan, and supporting the impact of the dispatching order on the train operation state during the simulation process.

[0032] In step S3, based on the data processing layer constructed in step S2, the inherent internal logic of railway signals and the train operation logic rules are regularized, and the corresponding simulation advancement rules are set to form a train operation simulation mechanism under dispatching decision-making, and the corresponding simulation modules are constructed, as Figure 4 shown, the specific steps are as follows:

[0033] Step S3_1, first construct the operation rule layer, and the specific implementation method is as follows:

[0034] (1) Initialize the rule engine, first load the train operation regulations and station details configuration structured by data specifications for controlling the operation rules during the simulation process;

[0035] (2) Load the train sampling rules, that is, determine the arrival and departure times of trains at stations based on train speed values and signal equipment status at fixed points (station arrival and departure lines). For example, the sampling calculation method for trains with arrival and departure operations at stations can be that the moment when the train completely enters the arrival and departure line and its speed drops to 0 is the arrival point, and the moment when the train occupies the departure route and the protective signal becomes a stop signal is the departure point; the sampling calculation method for passing trains can be the average value of the moment when the train enters the arrival and departure line and the moment when it leaves the arrival and departure line; the simulation module generates the actual operation diagram through train sampling during the simulation process and outputs it as part of the simulation results;

[0036] (3) Load the train tracking rules, that is, initialize operation parameters such as the minimum running time of trains in sections, the minimum tracking interval of trains in sections, the minimum departure interval of trains, and the minimum receiving interval of trains for the coordinated operation calculation of multiple trains during the simulation process;

[0037] (4) Load the train conflict and handling rules. Since there are various adjustment methods under train conflicts, the system provides mature scheduling adjustment methods including first-come-first-served (FCFS), first-scheduled-first-served (FSFS), class priority, and heuristic algorithm-based methods in a modular way, which can be selected through human-computer interaction for train conflict resolution during the simulation process;

[0038] Step S3_2, construct the signal drive layer based on the operation rule layer, and the specific implementation method is as follows:

[0039] (1) Construct signal control rules. Based on the signal equipment status and the association relationship between signal equipment defined in step 1, combined with the mature interlocking logic of railway signals, including route locking logic, switch conversion logic, signal opening logic, conflicting route logic, etc., judge whether the interlocking conditions are met through real-time monitoring and analysis of the signal equipment status and association relationship. For example, when a certain signal is open, it must be ensured that the position of the switch ahead is correct, the track circuit is idle, and there is no conflicting route, etc. Convert these interlocking conditions into specific logical expressions and control instructions to achieve mutual restriction and coordinated work between signal equipment.

[0040] (2) Construct train operation calculation rules. Based on the mature train dynamics equation, taking a single train as the object, calculate the full-course speed curve of all trains at one time in combination with the operation plan as the basic speed curve during the simulation process. During the simulation process, when the operation environment in the section or station changes, resulting in train speed limitations (such as temporary speed limits, etc.), to improve calculation efficiency and timeliness, the method of splicing speed curves is adopted, and only the speed curves in the affected section and station subset are calculated to achieve rapid update of the train speed curve during the simulation process.

[0041] (3) Construct the signal-train interlock rule. Based on information such as the current position of the train, the status of the signal ahead, the route status, and the temporary speed limit, combined with the train operation calculation rules, calculate in real time the running time of the train in the next operation section and the signal status changes caused by the train's step-by-step movement. Then, combined with the status of the signal equipment and the interlock relationship, generate corresponding control instructions, such as the display switching of the signal machine and the conversion of the turnout, to achieve the interlock change of the signal-train status.

[0042] (4) Construct the dispatching order-signal interlock rule. Extract the time range involved in the change of the signal equipment status in the dispatching order. For example, if the dispatching order stipulates signal operations such as the blockade and temporary speed limit of a specific section within a certain time period, combined with the signal equipment control rules, generate a specific signal equipment control command queue based on time and associate it with the corresponding signal equipment as part of the driving source for the change of the signal equipment status during the simulation process.

[0043] Step S3_3, construct the simulation drive layer, and the specific implementation method is as follows:

[0044] (1) Construct a periodically triggered simulation clock: The simulation clock provides the time reference for the advancement of the simulation process, which sends trigger and time advancement signals to the dispatching decision part and the signal equipment part respectively at a fixed period. The simulation clock adopts the method of scaling and mapping based on the actual environment time, and advances the virtual simulation time by a multiple of the actual environment time to achieve the purpose of super-speed simulation. For example, can be set to 1 microsecond, that is, 1 microsecond corresponds to 1 second of actual time, and the 24-hour operation plan can be completed in 0.0864 seconds. For example, can be set to 1 microsecond, that is, 1 microsecond corresponds to 1 second of actual time, and the 24-hour operation plan can be completed in 0.0864 seconds.

[0045] (2) Dispatching decision release event: After receiving the time trigger signal of the simulation clock, the dispatching decision part releases signal events and train events respectively. The signal events are conveyed to the signal equipment, and the train events are conveyed to the train to indicate relevant operations or status changes.

[0046] (3) Signal equipment response and update: After receiving the signal events released by the dispatching decision, the signal equipment combines the status information of the train and the dispatching order information, and calls the signal control drive rules, signal-train interlock rules, and signal-dispatching order interlock rules in the signal drive layer to update its own status. At the same time, the signal equipment receives the position and speed information fed back by the train and sends this information to the dispatching decision part to update the execution status of the dispatching decision, such as calculating the actual arrival and departure points of the train according to the train timing rule.

[0047] (4) Train Response and Update: After receiving the train events issued by the dispatching decision, the train updates its own status according to the event content in combination with the train operation calculation rules, train tracking rules, and signal-train interaction rules, and calculates the conflict situation between trains based on the signal equipment status and train position information. If there is a conflict, the sequence of train operation is determined based on the conflict resolution rules, and the position and speed information of each train is fed back to the signal equipment to provide real-time train operation status data for the signal equipment and dispatching decision-making.

[0048] (5) The simulation clock continuously triggers in cycles, and the above steps are continuously repeated to achieve continuous simulation and dynamic update of the train operation status and signal equipment status based on the dispatching decision. Finally, the entire execution process of the dispatching decision is completed, and the simulation results are output.

[0049] In step S4, based on the simulation results of the dispatching decision output in step 3, combined with the total train delay time, average delay time, number of delayed trains, and delay time of each passing station, the resilience evaluation index of the dispatching decision is calculated. The specific implementation method is as follows:

[0050] (1) The resilience of the dispatching decision reflects its resistance and recovery ability in the face of interference, and to a certain extent, it is reflected in its ability to absorb train delays. Since reasonably using the redundant time reserved in the train operation diagram is an important way to resist disturbances and absorb delays, the resistance and recovery ability of the dispatching decision in the face of delays can be reflected by evaluating the actual utilization rate of the redundant time in the execution results of the dispatching decision. Therefore, the redundant time absorption rate is defined as: as:

[0051] ,

[0052] where, is the total number of stations, is the delay time of the station, is the redundant time reserved in the train operation diagram for the station, then can measure the overall ability of this dispatching decision to absorb train delays, [[ID=A]] The closer the value of is to 1, the stronger the resilience of this dispatching decision.

[0053] (2) At the same time, the resilience of the dispatching decision can also be evaluated from the aspect of the final global delay degree of the train, that is, the comprehensive ratio of the total delay time of the train at the terminal station to the planned operation time and redundant time of the train under this decision. Through this ratio, the ability of the dispatching decision to absorb train delays is reflected as a whole. Therefore, the global delay degree is defined as: :

[0054] ,

[0055] Among them is the total delay time of the train, is the planned running time of the train, is the total redundancy time of the operation diagram, , are weight coefficients, The smaller the value of , the better the resilience of the scheduling decision.

[0056] (3) The distribution of the delay time of the train at each station under this scheduling decision can be counted. For example, the standard deviation or coefficient of variation (standard deviation / mean value) of the delay time at each station can be used. If the uniformity of this value is higher, it means that the delay dispersion is better and the delay is easier to recover. Therefore, the equilibrium degree of the delay distribution is defined :

[0057] Among them is the standard deviation of the delay time at each station, is the average delay time, The larger the value of , the more uniform the distribution of the delay time, and the stronger the resilience of the scheduling decision.

[0058] (4) The influence range of the scheduling decision can be reflected by calculating the ratio of the number of delayed trains to the total number of trains. The ratio of affected trains is defined :

[0059] Among them is the number of delayed trains, is the total number of trains, The larger the value of , the fewer the number of delayed trains, and the stronger the resilience of the scheduling decision.

[0060] (5) Considering the above indicators comprehensively, the comprehensive resilience evaluation index of the scheduling decision can be formed :

[0061] ,

[0062] Among them are weights, normalized to the interval [0,1], . Therefore can be used as the comprehensive resilience evaluation index of the scheduling decision, and the larger its value, the better the resilience of the decision.

[0063] In step S5, different visualization methods are adopted as needed to display the train operation results and the resilience evaluation results of the decision-making under this scheduling decision. For example, the final train operation results are displayed using an operation diagram, the train delay areas, the influence degree and scope are displayed using a heat map, and the distribution balance degree of the delays is displayed using a scatter plot, etc. Mature human-computer interaction methods such as mouse clicking can be used to realize the switching settings of different simulation rules and evaluation rules built in the system.

[0064] The present invention also discloses a simulation-driven railway scheduling decision-making resilience evaluation system, which is characterized in that the system includes: a processor, a memory, a communication interface and a bus; the processor, the memory and the communication interface are connected through the bus and complete communication with each other; the memory stores executable program codes; the processor runs a program corresponding to the executable program codes by reading the executable program codes stored in the memory, so as to execute the above method.

[0065] The above has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection required by the present invention is defined by the appended claims and their equivalents.

Claims

1. A simulation-driven resilience evaluation method for railway dispatching decisions, characterized by: Step S1. Construct the overall system architecture: From the perspective of function implementation, construct an overall system architecture that includes data processing, simulation-driven, resilience evaluation analysis, and visualization display functions; Step S2. Construct the data processing module and mechanism: Standardize and regularize the dynamic and static data of the system, and construct the correlation mapping relationship between the data structures related to dispatching decisions and between data structures; Step S3. Construct the simulation-driven module and mechanism: Based on railway signals and railway operation rules, construct a simulation verification mechanism and verification method for dispatching decisions, input the dispatching decision, and output the verification result; Step S4. Construct the evaluation analysis module and mechanism: Construct an evaluation model that includes resilience evaluation indicators and calculation methods for dispatching decisions to achieve the resilience evaluation of the input dispatching decision; Step S5. Human-computer interaction and visualization display module: Display the resilience evaluation result of the dispatching decision in a visual way.

2. The simulation-driven method for evaluating the resilience of railway dispatching decisions according to claim 1, wherein The said step 1 includes the following contents: The overall architecture includes the following four functional modules: (1) Data processing module. According to the characteristics of the data required for dispatching decisions and operation environment simulation, construct corresponding data structures to standardize and regularize the data related to dispatching decisions and simulation environment, and construct the correlation mapping relationship between different data structures to form the basic data support layer for the simulation and evaluation modules; (2) Simulation-driven module. Used to construct an internal rapid simulation environment for verifying the effect of dispatching decisions; a simulation-driven layer for driving trains to run according to dispatching decisions in a virtual simulation environment, and finally form train arrival and departure delay information, the execution situation of dispatching commands, and dispatching decision results, as the input of the resilience evaluation module; (3) Resilience evaluation module. Combining the output results of the simulation-driven module, construct resilience evaluation indicators including delay absorption ability, recovery ability, and anti-destruction ability and corresponding calculation methods, and output the final evaluation result; (4) Human-computer interaction and visualization display module. Through visualization, display the resilience evaluation result of the dispatching decision, and provide a human-computer interaction interface for adjusting the rule settings of the simulation-driven module and the resilience evaluation module.

3. The method for evaluating the resilience of railway dispatching decision-making based on simulation-driven according to claim 1, wherein The said step 2 includes the following contents: (1) Based on the topological relationship of railway lines, construct the connection correlation relationship between signal devices, associate the block section with the interval signal machine it protects, associate the interval signal machine with the block sections on both sides of it, associate the block section in the approach section of the station with the entry and exit signal machines, associate the entry and exit signal machines with the routes they protect, associate the routes with the corresponding receiving and dispatching tracks, and add the up and down attributes of train operation according to the definition rules of train operation directions in China, and finally form a directional topological correlation relationship between signal devices to support the change of the environmental state of train operation; (2) The dispatching decision can be divided into two parts: the train operation plan and the dispatching order. Based on the characteristics of the train plan, the association relationship between the train plan and the signal equipment is constructed, and the train plan is associated with the track and the route, which is used to uniquely determine the receiving and dispatching tracks and the corresponding routes of the train, and to support the path driving in the train movement simulation process. The dispatching order is uniformly abstracted into a vector set containing the characteristics of the dispatching order identifier, dispatching order type, command execution period, execution subject, and execution object. Based on the characteristics of the dispatching order, the association relationship between the dispatching order object and the signal equipment is constructed to support the impact of the dispatching order on the operation environment and the resulting changes in the operation state during the simulation process. (3) Taking the signal equipment as the key characteristic link, tracing its association relationship with the train plan and the dispatching order, constructing the association relationship between the train plan and the dispatching order, forming the correspondence between the dispatching order and the train plan, and supporting the impact of the dispatching order on the train operation state during the simulation process.

4. The method for evaluating the resilience of railway dispatching decision-making based on simulation drive according to claim 1, characterized in that the step 3 includes the following contents: Step S3_1, first construct the operation rule layer. Step S3_2, construct the signal drive layer on the basis of the operation rule layer. Step S3_3, construct the simulation drive layer.

5. The method for evaluating the resilience of railway dispatching decisions based on simulation-driven according to claim 4, characterized in that The step S3_1 includes the following contents: (1) Initialize the rule engine. First, load the train operation regulations and station details configuration structured by data specifications for controlling the operation rules during the simulation process. (2) Load the train sampling rules, that is, determine the arrival and departure times of the train at the station based on the train speed value and the signal equipment status on the arrival and departure lines of the station. For example, the sampling calculation method for the arrival and departure of trains with arrival and departure operations at the station is that the moment when the train completely enters the arrival and departure line and the speed drops to 0 is the arrival point, and the moment when the train occupies the departure route and the protecting signal changes to the stop signal is the departure point. The average value of the arrival and departure times of the train entering and leaving the arrival and departure line can be obtained through the train sampling calculation method. The simulation module generates the actual operation diagram through the train sampling during the simulation process and outputs it as part of the simulation results. (3) Load the train tracking rules, that is, initialize the minimum running time of the train in the section, the minimum tracking interval of the train in the section, the minimum departure interval of the train, and the minimum receiving interval of the train, which are used for the coordinated operation calculation of multiple trains during the simulation process. (4) Load the train conflict and handling rules. Since there are various adjustment methods under train conflicts, the system provides, in a modular way, dispatching adjustment methods including first come first served (FCFS), first scheduled first served (FSFS), priority based on rank, and heuristic algorithm based scheduling adjustment methods, which are selected through human-computer interaction for resolving train conflicts during the simulation process. The step S3_2 includes the following contents:

6. The method for evaluating the resilience of railway dispatching decisions based on simulation-driven according to claim 4, characterized in that, (1) Construct the signal control rules. Based on the signal equipment status and the association relationship between signal equipment defined in step 1, combined with the real-time monitoring and analysis of the signal equipment status and association relationship by the mature interlocking logic of railway signals, judge whether the interlocking conditions are met. ​ (2)Construct train operation calculation rules: Based on mature train dynamics equations, taking a single train as the object, calculate the full-course speed curves of all trains at one time in combination with the operation plan, which are used as the basic speed curves during the simulation process; during the simulation process, when the operation environment in the section or station changes, resulting in limited train operation speed, to improve the calculation efficiency and timeliness, the method of splicing speed curves is adopted, and only the speed curves within the affected section and station subset are calculated to achieve the rapid update of the train speed curves during the simulation process; (3)Construct signal-train linkage rules: According to the current position of the train, the status of the signal lights ahead, the route status, and the temporary speed limit information, combined with the train operation calculation rules, calculate in real time the running time of the train in the next operation section and the signal status changes caused by the train's step-by-step movement, and generate corresponding control commands in combination with the status and interlocking relationship of the signal equipment; (4)Construct dispatching order-signal linkage rules: Extract the time range involving the change of the signal equipment status in the dispatching order, and generate a specific signal equipment control command queue based on time in combination with the signal equipment control rules, and associate it with the corresponding signal equipment as part of the driving source for the change of the signal equipment status during the simulation process.

7. The simulation-driven railway dispatching decision-making resilience evaluation method according to claim 4, characterized in that The step S3_3 includes the following contents: (1) Construct a periodically triggered simulation clock: The simulation clock provides the time reference for the advancement of the simulation process. It sends trigger and time advancement signals to the scheduling decision part and the signal device part respectively at a fixed period ; The simulation clock adopts a method of scaling and mapping based on the actual environmental time to advance the virtual simulation time by multiples of of the actual environmental time to achieve the purpose of over-speed simulation. Among them, simu_cycle and T together represent the fixed period T simu_cycle ; (2)Dispatching decision release event: After the dispatching decision part receives the time trigger signal of the simulation clock, it releases the signal event and the train event respectively; (3)Signal equipment response and update: After the signal equipment receives the signal event released by the dispatching decision, it combines the status information of the train and the dispatching order information, and calls the signal control driving rules, signal-train linkage rules and signal-dispatching order linkage rules in the signal driving layer to update its own status; at the same time, the signal equipment receives the position and speed information fed back by the train and sends this information to the dispatching decision part to update the execution status of the dispatching decision, such as calculating the actual arrival and departure points of the train according to the train arrival and departure rules; (4)Train response and update: After the train receives the train event released by the dispatching decision, it updates its own status according to the event content in combination with the train operation calculation rules, train tracking rules and signal-train linkage rules, and calculates the conflict situation between trains according to the signal equipment status and train position information. If there is a conflict, determine the sequence of train operation based on the conflict handling rules, and feedback the position and speed information of each train to the signal equipment to provide the real-time operation status data of the train for the signal equipment and the dispatching decision; (5)The simulation clock triggers continuously in a cycle, and the above steps are continuously looped to achieve the continuous simulation and dynamic update of the train operation status and signal equipment status based on the dispatching decision, and finally complete the entire execution process of the dispatching decision and output the simulation results.

8. The simulation-driven railway dispatching decision-making resilience evaluation method according to claim 4, characterized in that The step S4 includes the following contents: (1) By evaluating the actual utilization rate of redundant time for the execution result of the scheduling decision, the resistance and recovery capabilities of the scheduling decision in the face of delays are reflected. Therefore, the redundant time absorption rate is defined as: , Among them, is the total number of stations, is the delay time of the th station, is the redundant time reserved in the train operation diagram of the th station. Then can measure the overall absorption ability of the scheduling decision on train delays. The closer the value is to 1, the stronger the resilience of the scheduling decision. (2)The resilience of the scheduling decision can be evaluated from the aspect of the final global delay degree of the train, that is, under the condition of adopting this decision, the comprehensive ratio of the total delay time of the train at the terminal station to the planned running time and redundant time of the train. Through this ratio, the absorption ability of the scheduling decision to train delays is reflected as a whole. Therefore, the global delay degree is defined : ， Among them, is the total delay time of the train, is the planned running time of the train, is the total redundancy time of the operation diagram, and are the weight coefficients, The smaller the value of , the better the resilience of the scheduling decision; (3) By statistically analyzing the distribution of the train's delay time at each station under this scheduling decision, such as using the standard deviation or coefficient of variation of the delay time at each station, if the uniformity of this value is higher, it indicates that the delay dispersion is better and the delay is easier to recover. Therefore, the equilibrium degree of the delay distribution is defined. : , where is the standard deviation of the delay time of each station, is the average delay time, The larger the [[value]] is, the more uniform the distribution of the delay time is, and the stronger the resilience of the scheduling decision is; (4) The influence scope of the dispatching decision can be reflected by calculating the ratio of the number of late trains to the total number of trains, and the proportion of affected trains is defined. : , where is the number of late trains, is the total number of trains, The larger the value, the fewer the number of late trains, and the stronger the resilience of the dispatching decision; (5) Considering the above indicators comprehensively, a comprehensive resilience evaluation index for scheduling decisions can be formed : ， Among them is the weight, normalized to the interval [0, 1] ; therefore can be used as a comprehensive resilience evaluation index for scheduling decisions. The larger its value, the better the resilience of the decision 9. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein the program, when running, controls the device where the non-volatile storage medium is located to execute the method described in any one of claims 1 to 8.

10. A simulation-driven railway dispatching decision-making resilience evaluation system, characterized in that, The system includes: a processor, a memory, a communication interface, and a bus; the processor, the memory, and the communication interface are connected through the bus and complete communication with each other; the memory stores executable program codes; the processor runs a program corresponding to the executable program codes by reading the executable program codes stored in the memory, so as to execute the method described in any one of claims 1-8 above.

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