Train marshalling control method, storage medium and electronic device

Abstract

A train marshalling control method, a storage medium and an electronic device, the method comprising: predicting a predicted passenger flow of a train in a future target period based on historical passenger flow data; generating a dispatch plan for the future target period according to the predicted passenger flow, wherein the dispatch plan comprises a planned departure time, a planned train identification number and a planned marshalling number; determining a marshalling number of a target train to obtain a current marshalling number, wherein if there is an actual train in a preset standby train list, the target train is the actual train; otherwise, the target train is a train in the standby train list; if the current marshalling number of the target train is different from the planned marshalling number, generating a marshalling adjustment strategy for the target train; and outputting the marshalling adjustment strategy, wherein the target train processed by the marshalling adjustment strategy is adapted to the predicted passenger flow, thereby solving the problem of capacity configuration caused by uneven time-space distribution of passenger flow in urban rail transit.

Description

Technical Field

[0001] This article relates to urban rail transit technology, and in particular to a train formation control method, storage medium, and electronic device. Background Technology

[0002] Urban rail transit systems commonly exhibit highly uneven passenger flow distribution in time and space, with peak hours seeing a high concentration of passengers, while off-peak and low-peak periods see a significant decrease. To address this issue, the current mainstream operational strategy is to adjust train intervals, shortening them during peak hours and lengthening them during off-peak hours. However, this approach has significant limitations: during off-peak hours, even with longer intervals, trains may still operate with fixed large formations, leading to a situation of "large trains carrying few passengers," resulting in substantial waste of traction energy and equipment wear and tear. During peak hours, simply shortening intervals may be limited by line capacity and cannot quickly increase the maximum capacity of a single trip, lacking flexibility to handle sudden surges in passenger flow. Therefore, achieving precise and dynamic matching between capacity allocation and passenger demand, fundamentally solving the problem of wasted or insufficient capacity, is a pressing technical issue in current urban rail transit operation and management. Summary of the Invention

[0003] This application provides a train formation control method, a storage medium, and an electronic device.

[0004] A train formation control method, comprising: Based on historical passenger flow data, predict the train passenger flow for the target period in the future; Based on the predicted passenger flow, a dispatch plan for the future target time period is generated, wherein the dispatch plan includes the planned departure time, the planned train identification number, and the planned number of train formations; Determine the number of train formations of the target train to obtain the current number of train formations. If there is an actual train in the preset reserve car list, then the target train is the actual train, which is the train whose basic formation unit TU of the target train is located at the preset time before the scheduled departure time corresponding to the planned train identifier number. Otherwise, the target train is a train in the reserve car list, which records trains that are not in operation. If the current number of train formations of the target train is different from the planned number of train formations, a train formation adjustment strategy for the target train is generated. Output the train formation adjustment strategy, wherein the target train processed by the train formation adjustment strategy is adapted to the predicted passenger flow.

[0005] A storage medium storing a computer program, wherein the computer program is configured to execute the method described above when run.

[0006] An electronic device includes a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the methods described above.

[0007] In this embodiment, based on predicted passenger flow, capacity is precisely matched to demand, avoiding both insufficient capacity during peak periods and energy waste during off-peak periods. If the current number of train formations does not match the planned number, a formation adjustment strategy is generated to meet the requirements of the dispatch plan for specific trains to perform tasks. This demonstrates a high degree of intelligence, greatly improving dispatch efficiency and response speed, reducing human error and dispatch delays, and effectively solving the capacity allocation problem caused by uneven spatial and temporal distribution of passenger flow in urban rail transit.

[0008] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application can be realized and obtained by means of the solutions described in the description and the accompanying drawings. Attached Figure Description

[0009] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0010] Figure 1 This is a flowchart illustrating the train formation control method provided in an embodiment of this application. Detailed Implementation

[0011] This application describes several embodiments, but these descriptions are exemplary and not restrictive, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0012] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application can also be combined with any conventional features or elements to form unique inventive solutions. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application can be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes can be made within the scope of the appended claims.

[0013] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0014] The solution provided in this application can automatically predict passenger flow and formulate plans before the train leaves the depot, and can intelligently judge the difference between the current vehicle status and the plan, thereby generating a systematic solution of specific and executable train formation adjustment strategy to achieve true energy saving, consumption reduction and efficiency improvement.

[0015] Figure 1 This is a flowchart illustrating the train formation control method provided in this application. This method is applied before trains are put into mainline operation and is executed in the depot or parking lot of the operation center. Through dynamic adjustment of train formations, it achieves precise matching of transport capacity and passenger flow demand. Figure 1 As shown, the method includes the following steps: Step 101: Based on historical passenger flow data, predict the passenger flow for the target period in the future.

[0016] For example, the historical passenger flow data includes, but is not limited to: passenger card swiping data at various subway stations during different time periods (e.g., at 15-minute or 1-hour intervals) over the past year or longer; passenger density data from in-car surveillance videos; and all-day passenger flow distribution data for weekdays, weekends, and holidays. This data should comprehensively cover various operational scenarios to reflect the periodic and seasonal patterns of passenger flow.

[0017] The target time period can be any of the off-peak, peak, or off-peak periods.

[0018] The purpose of predicting passenger flow is to understand in advance the capacity demand at different times in the future (such as morning peak, evening peak, off-peak, and low-peak periods), thereby providing data support for dynamically formulating train operation plans. Its advantage lies in transforming the original passive response to real-time passenger flow model into a proactive prediction and planning model, which can optimize resource allocation from a global perspective, avoid capacity waste or shortage, and lay the foundation for energy conservation, emission reduction, and improved operational efficiency.

[0019] Step 102: Based on the predicted passenger flow, generate a dispatch plan for the future target time period, wherein the dispatch plan includes the planned departure time, the planned train identification number, and the planned number of train formations.

[0020] The dispatch plan is the overall scheme guiding train operations for the day. Before generating the dispatch plan, complete basic data for the train operation plan needs to be compiled, including: Determining operating hours: Daily operating hours are determined based on the characteristics of urban residents' travel activities and the maintenance and repair needs of rail transit system equipment, and peak-hour operating hours are appropriately extended in response to the passenger flow characteristics during morning and evening rush hours; Departure interval setting: Based on the predicted passenger flow, set departure intervals for different time periods. During peak periods, shorten the departure interval to increase train frequency, and appropriately lengthen the departure interval during off-peak and low-peak periods to reduce operating costs. Vehicle allocation calculation: Based on the departure interval and the number of train formations, calculate the number of vehicles required each day, and appropriately increase the allocation number considering factors such as vehicle maintenance and spare parts.

[0021] The planned departure time refers to the time when the train is scheduled to depart from the originating station or depot. The interval can be flexibly adjusted according to the predicted passenger flow. For example, the interval can be shortened to 5 minutes during peak hours and extended to 10 minutes during off-peak hours.

[0022] For example, the identification number (also known as the train set number) is a unique number for a train.

[0023] The planned train formation number refers to the number of trains that should be composed of several basic train formation units (TUs) coupled together in the train allocation plan (such as 1-car formation, 2-car formation, etc.). This number is calculated and determined based on the predicted passenger flow and the train's rated passenger capacity for the corresponding time period to ensure that capacity matches demand. For example, 4-car formation trains are planned to be used during peak hours, and 2-car formation trains are planned to be used during off-peak hours.

[0024] Step 103: Determine the number of train formations of the target train to obtain the current number of train formations. If there is an actual train in the preset spare car list, then the target train is the actual train, which is the train whose basic formation unit TU of the target train is located at the preset time before the scheduled departure time corresponding to the planned train identifier number; otherwise, the target train is a train in the spare car list, wherein the spare car list records trains that are not in operation.

[0025] The standby car list refers to a list of all trains in the depot or parking lot that are not in operation (i.e., in standby status). Each standby car has its current formation status (e.g., formation 1, formation 2, etc.) and online status (online / offline). This information is obtained by querying the vehicle management database in real time.

[0026] In this context, TU refers to the smallest train unit that can be independently put into operation, consisting of a single motor car or trailer car. Each TU is assigned a globally unique fixed number (such as 1 to 16) at the time of manufacture. It is the basic unit that constitutes all double-unit trains.

[0027] The target TU is determined by querying the vehicle management system and based on the planned train identification number. This unit may exist independently or it may be part of a coupled train.

[0028] Conducting an inspection before scheduled departure (e.g., one hour in advance) allows sufficient time for any potential adjustments to the train's formation. Operations such as coupling, uncoupling, and track switching within the depot require a certain timeframe; anticipating these changes ensures the train can be deployed on time with the correct formation, preventing disruption to mainline operations.

[0029] Step 104: If the current number of train formations is different from the planned number of train formations, generate a train formation adjustment strategy for the target train.

[0030] When the system detects a deviation between the current situation (current number of train formations) and the planned requirements (planned number of train formations), it automatically triggers a decision-making operation to generate a control command (i.e., train formation adjustment strategy) that can correct the current state to the target state in the fastest and most economical way, thereby dealing with emergencies such as vehicle failures, temporary scheduling, or prediction errors.

[0031] Step 105: Output the train formation adjustment strategy, wherein the target train adjusted by the train formation adjustment strategy is adapted to the predicted passenger flow.

[0032] The method provided in this application accurately matches the demand in terms of transport capacity based on the predicted passenger flow, which avoids insufficient transport capacity during peak periods and eliminates energy waste during off-peak periods. If the current number of train formations is inconsistent with the planned number of train formations, a train formation adjustment strategy is generated to meet the requirements of the dispatch plan for specific trains to perform tasks. This reflects a high degree of intelligence, greatly improves dispatch efficiency and response speed, reduces human error and dispatch delays, and effectively solves the problem of transport capacity allocation caused by uneven spatial and temporal distribution of passenger flow in urban rail transit.

[0033] In one exemplary embodiment, the technical problem of how to achieve capacity adaptation through grouping adjustments is further defined, so as to achieve the technical effect of flexibly responding to different situations and maximizing the utilization of existing resources. Specific implementation methods include: First, compare the current number of groups with the planned number of groups, and then proceed to different strategy generation branches based on the comparison result: Branch 1: When the current number of train formations exceeds the planned number of train formations, a first strategy for uncoupling the target train is generated as the train formation adjustment strategy. In this case, the actual train formation size exceeds the planned requirement, and uncoupling operations are needed to reduce the number of train formations.

[0034] For example, suppose the plan requires the use of a 2-car train with train number 003 (i.e., planned train number = 2), but it is detected that TU number 003 is currently in a 4-car train (current train number = 4, including TUs numbered 003, 008, 010, and 015). In this case, the first strategy is generated to disassemble this 4-car train into a 2-car train (containing 003 and 008) and a 2-car train (containing 010 and 015), and then put the 2-car train containing 003 into operation.

[0035] Branch Two: When the current number of train formations is less than the planned number of train formations, a second strategy for coupling the target train is generated based on the number of train formations for each spare car in the spare car list, serving as the train formation adjustment strategy. In this case, the target train's train formation size is insufficient, and coupling operations are needed to increase the number of train formations.

[0036] If the plan requires the use of a 4-car train (planned number of cars = 4), but it is detected that TU number 003 is currently only part of a 2-car train (current number of cars = 2, including 003 and 008), then a query of the spare car list reveals an available 2-car spare car (including 010 and 015). A second strategy is generated to couple this 2-car spare car with the target train, forming a 4-car train (including 003, 008, 010, and 015) before putting it into operation.

[0037] The processing method provided by the above exemplary embodiments, through size relationship judgment and branch processing, can effectively cope with two completely different situations of excess and insufficient capacity, ensuring that corresponding adjustment strategies can be generated under various deviation scenarios, thereby improving the applicability and reliability of the system. By adopting the most appropriate adjustment method for different quantity differences, uncoupling operations directly reduce capacity output, while coupling operations directly increase capacity supply, ensuring that the adjusted train formation quantity is completely consistent with the planned demand, achieving precise capacity matching, and ensuring that the train formation control method can still operate reliably under various abnormal conditions, thus realizing the comprehensiveness and robustness of operational adjustments.

[0038] In one exemplary embodiment, the specific implementation of the first strategy is further defined to address the technical problem of how to adopt the most suitable decompilation scheme based on different grouping situations when decompilation operations are required, thereby achieving the technical effects of optimized operation and maximized resource utilization. The specific implementation includes: The first strategy includes the following hierarchical processing scheme: When the current number of train sets is 2, a strategy of disassembling the target train into two independent TUs is adopted. In this case, since the number of train sets is relatively small, a one-to-one complete disassembly method is the most direct and efficient.

[0039] For example, suppose the planned trainset size is 1, and the target TU (e.g., number 005) is currently in a 2-car train (numbers 005-006). The trainset adjustment strategy instructs that the 2-car train be decoupled on the depot's decoupling line, separating it into two independent 1-car units (numbers 005 and 006). Subsequently, unit number 005 is put into operation alone, while unit number 006 is returned to the reserve car list.

[0040] When the current trainset size is greater than 2, if the target train includes the target TU, then the target train is de-trained according to the position of the target TU in the trainset; otherwise, the target train is de-trained according to the planned trainset size. Specific details are as follows: When the target train includes the target TU, the specific location of the target unit in the train needs to be considered to determine the optimal decoupling scheme; when the target train does not include the target TU, the decoupling operation only needs to satisfy that the number of trains in the formation is the planned number of trains.

[0041] For example, assuming the planned number of train sets is 2, the target TU (number 003) is currently in a 4-car train (numbers 001-002-003-004).

[0042] If train number 003 is located at one end of the train formation (e.g., the third position): the formation adjustment strategy instructs that trains be decoupled between 003 and 004, dividing the train into a 3-car train (numbered 001-002-003) and a 1-car unit (numbered 004). Since the resulting 3-car train is still greater than the planned number (2), 001-002-003 needs to be further decoupled into 001-002 (2-car train) and 003 (1-car train). Finally, the 2-car train (001-002) containing the target unit will be put into operation.

[0043] If train number 003 is located in the middle of the train formation (e.g., the second position): the formation adjustment strategy will evaluate the economy of different decoupling schemes. The optimal solution may be to decouple twice, once between 001 and 002 and again between 003 and 004, directly dividing the train into three parts: 001, 002-003, and 004. Subsequently, the two-train formation (002-003) containing the target unit will be put into operation.

[0044] The reasons for determining whether to de-assemble or de-assemble the target TU based on its position in the target train include: Ensuring the participation of the target TU in operation: The ultimate goal of the decoupling operation is not simply to reduce the number of cars, but to ensure that the target TU designated in the plan (such as number 003) is included in the trains that are eventually put into operation. Location information directly determines which couplers need to be decoupled to release them.

[0045] Pursuing operational economy (principle of minimum variation): The choice of disassembly / reassembly location directly affects operational costs, including: Minimum number of operations: Disassembly / reassembly from the end of the train usually requires only one operation to separate the part containing the target unit (although this part may still need further disassembly / reassembly). Disassembly / reassembly from the middle may not be able to directly obtain the required trainset in one operation, requiring multiple operations and taking longer; Maximum resource utilization: A reasonable disassembly / reassembly location allows the other parts generated after disassembly / reassembly (such as 001-002 or 004 in the example above) to form reasonable trainsets (such as 2-carset or 3-carset), so that they can be used immediately as spare cars, avoiding the generation of a large number of invalid 1-carset units and maximizing the utilization of vehicle resources.

[0046] The above exemplary embodiments, through differentiated decoupling schemes, can accurately adjust overstaffed trains to the planned required number of formations, satisfying capacity demands while avoiding resource waste caused by excessive decoupling. Employing the most suitable decoupling method for different formation sizes and unit positions reduces unnecessary operational steps, improves shunting efficiency, and shortens train departure preparation time. Each decoupling unit can be re-entered into the spare car list, providing more available resource options for subsequent capacity adjustments, improving the overall utilization rate of vehicle resources, and ensuring optimal decoupling operations under various formation conditions, thereby maximizing the utilization of operational resources and significantly improving operational efficiency.

[0047] In one exemplary embodiment, the specific method of performing the ungrouping operation based on the target TU position is further defined to address the technical problem of how to formulate the optimal ungrouping scheme for different grouping positions, achieving the technical effect of most economical operation and minimal impact on operations. Specific implementation methods include: Scenario 1: When the formation position of the target TU is at one end of the target train, the target train is disassembled into two independent first formation structures, including the formation number of the target TU formation structure being the planned formation number.

[0048] For example, suppose the planned trainset size is 2, the target TU number is 008, and it is currently in a 4-car train with the train formation sequence 008-005-012-009 (008 is at the front of the train). The trainset adjustment strategy instructs a decoupling operation between 008 and 005, dividing the train into two independent parts: a 1-car unit (number 008) and a 3-car train (number 005-012-009). Since a 2-car train is planned, the system will further decouple the 3-car train 005-012-009 into 005-012 (2-car) and 009 (1-car). Finally, the 2-car train 005-012 containing the target unit will be put into operation, and units 008 and 009 will be returned to the spare car list.

[0049] Scenario 2: The formation position of the target TU is not at one end of the target train. Sub-case A: When the number of train formations between the target unit and one end of the train formation meets the planned number of train formations, the target train is decomposed into two independent second formation structures, including the second formation structure of the target TU having the number of train formations equal to the planned number of train formations.

[0050] For example, the planned trainset size is 2, the target unit number is 012, and it is currently in a 4-car train 005-008-012-009 (012 is the third car). Checking the trainset size from 012 to the nearest end (009 end): 012-009 is a 2-car train, which exactly meets the planned requirement. The trainset adjustment strategy instructs to de-coupling between 008 and 012, dividing the train into two parts: 005-008 (2-car train) and 012-009 (2-car train). Subsequently, the 2-car train 012-009, containing the target unit, will be put into operation.

[0051] Sub-case B: The number of train formations between the target unit and the end of any train does not meet the planned requirements. The target train is then split into two independent third formations, where the number of formations in the third formations excluding the target TU is the planned number of formations.

[0052] For example, the planned train formation is 1, the target unit number is 008, and it is currently in a 4-car train 005-008-012-009 (008 is in the second position). Checking 008 to both ends: 005-008 is a 2-car formation (greater than 1), and 008-012-009 is a 3-car formation (greater than 1), neither of which meets the planned requirements. The train formation adjustment strategy instructs a decoupling: first, decoupling is performed between 005 and 008, resulting in 005 (1 car formation) and 008-012-009 (3 car formations). Train 005 is then put into operation as a 1-car formation train.

[0053] The above exemplary embodiments refine the disassembly and reassembly strategy based on positional relationships, customize the disassembly and reassembly scheme according to the specific position of the target TU, and ensure that the train containing the target unit and conforming to the planned number of trains is accurately obtained under the premise of minimizing the impact of operation; by judging the positional relationships, other parts generated by disassembly and reassembly are made into reasonable formations (such as 2-car trains or 3-car trains) as much as possible, which can be directly converted into spare cars and avoid generating too many invalid 1-car train units.

[0054] In one exemplary embodiment, the specific implementation of the second strategy is further defined to address the technical problem of how to intelligently select a linkage scheme when the number of groups needs to be increased, thereby achieving the technical effect of quickly matching requirements and optimizing resource allocation. Specific implementation methods include: Step 1: Calculate the required number of additional groups Calculate the difference between the planned number of train sets and the current number of train sets to determine the number of additional train sets needed. For example, if the planned number of train sets is 4, and the target train has 2 sets, then the required number of additional train sets is 2.

[0055] Step 2: Identification of the target backup vehicle and generation of the coupling strategy The system then searches the list of available spare vehicles to obtain the target spare vehicle, thereby generating a coupling strategy, including the following situations: Scenario A: There is a standby vehicle with a single matching line. If there are spare cars in the spare car list with a number of train sets that exactly equals the number of train sets to be added, then the spare car will be used as the target spare car and coupled to the target train.

[0056] For example, if the planned trainset size is 4, and the target train is a 2-carset (007-008), then 2 more carsets need to be added. The system finds an available 2-carset train (numbered 010-011) in the spare car list. The trainset adjustment strategy instructs that the two 2-carset trains 007-008 and 010-011 be coupled together to form a 4-carset train (007-008-010-011) for operation.

[0057] Scenario B: There are multiple matching combinations of spare cars. If there is no single spare car to match, but there are multiple spare cars whose total number of trains equals the required number of additional trains, then these spare cars will be coupled to the target train.

[0058] For example, if the planned trainset size is 3, and the target train is 1 set, then 2 sets need to be added. The system does not find any available 2-set trains in the spare car list, but it does find two available 1-set trains (numbered 015 and 016). The trainset adjustment strategy instructs that 015 and 016 be coupled together to form a 2-set unit, and then this newly formed 2-set unit be coupled together with 005 to form a 3-set train (005-015-016) for operation.

[0059] The exemplary embodiments described above, by calculating the precise number of additional train formations required, ensure that the train formations after coupling are completely consistent with the planned requirements, achieving a precise match between transport capacity supply and passenger demand. Intelligent matching based on the key parameter of train formation number prioritizes the coupling scheme with the fewest operations and highest efficiency, significantly improving vehicle utilization and scheduling efficiency. It provides two paths: single-train matching and multi-train combination, enhancing adaptability to different vehicle resource conditions. In the case of multi-train combinations, intelligent selection and sequencing ensure the economy and feasibility of coupling operations.

[0060] In summary, this embodiment provides an efficient, economical, and reliable capacity increase solution through the aforementioned intelligent coupling strategy generation method. It ensures that operational needs can still be met through flexible grouping adjustments when direct replacement is not possible, greatly enhancing the applicability and robustness of the grouping control method.

[0061] In one exemplary embodiment, the processing method when there is no readily available standby vehicle is further defined to address the technical problem of how to obtain the required standby vehicle through a decoupling operation in the event of resource mismatch, thereby achieving the technical effects of maximizing resource utilization and ensuring the execution of the operation plan. Specific implementation methods include: If the target backup vehicle is not found in the backup vehicle list, the system performs the following steps: Finding available spare cars for decomposition: The system searches the spare car list for spare cars with a number of train sets greater than the required number. Although the number of train sets of these spare cars does not match, they can be decompositioned to obtain train units that meet the requirements.

[0062] Perform the ungrouping operation: Perform the ungrouping operation on the found spare cars to obtain the target spare cars that meet the grouping requirements.

[0063] For example, if a target train (train number 006) with a 1-car formation needs to be coupled with a 2-car formation unit to make it a 3-car formation train, but there are no available 2-car formation trains in the spare car list, but there is one available 4-car formation train (train number 012-013-014-015), then the system will perform the following operations: Select the 4-car train 012-013-014-015 as the decoupling object; Perform a decoupling operation between 013 and 014, dividing them into two 2-car trains: 012-013 (2-car train) and 014-015 (2-car train). Use one of the 2-car trains (such as 012-013) as the target spare car, and couple 012-013 with the target train 006 to form a 3-car train 006-012-013.

[0064] The technical advantages of the above embodiments include: Resource activation and conversion: Large-formation spare cars that were originally unusable can be converted into smaller-formation units that meet the requirements through decomposition operations, which greatly improves the utilization efficiency and flexibility of vehicle resources.

[0065] Ensuring operational continuity: Even when backup vehicle resources are not perfectly matched, internal adjustments can still ensure the execution of the operational plan, avoiding the cancellation of services or reduction of service standards due to insufficient vehicle resources.

[0066] Operational economy: Compared with other emergency solutions (such as temporarily relocating vehicles from other lines), resource adjustments within the depot are less costly, more efficient, and do not affect the overall operating network.

[0067] The system's intelligence is demonstrated by its ability to make intelligent decisions in resource scheduling. It can not only perform simple matching, but also proactively create conditions to meet the needs when resources are insufficient.

[0068] In summary, this embodiment provides an innovative solution for resource-constrained situations by introducing a spare car de-staging mechanism, ensuring that the grouping control method can still operate efficiently under various extreme conditions, demonstrating the completeness and robustness of the system design.

[0069] In an exemplary embodiment, in a preferred embodiment of the present invention, an intelligent processing scheme is provided when the target train is not in the list of standby trains, and the specific implementation is as follows: S301: Candidate Backup Vehicle Inspection When the system detects that the target train is not in the preset list of spare cars, it automatically initiates the candidate spare car search process. The system traverses the spare car list and selects all available spare cars with the same number of formations as the planned number of formations as the candidate set.

[0070] S302: Direct Replacement Strategy If a suitable standby train exists in the candidate set, the system performs an identifier replacement operation: automatically replacing the identifier of the original scheduled train in the dispatch plan with the identifier of the candidate standby train to update the dispatch plan, and generating a dispatch instruction: "Scheduled train T008 has been replaced by standby train B012 to perform the operation task." Application Example: A 4-car train T008 is planned to be used, but it is unavailable. The system finds an available 4-car spare train B012 in the spare car list, automatically replaces its identification number, and ensures the smooth execution of the operation plan.

[0071] S303: Intelligent grouping processing strategy When no candidate spare cars with a matching number of trains are available, the system initiates intelligent train formation processing: S303.1: Handling of spare vehicles in small groups Multiple spare cars with a smaller number of formations than planned can be coupled together: Calculate the required increase in group size: ΔN = Np - Nr Select spare cars for small groups (such as 1-car or 2-car units). Generate the optimal linkage scheme so that the total number of linked groups meets the planned requirements.

[0072] Application example: A 4-car train is needed, but there are no available 4-car spare cars. The system selects two 2-car spare cars (B006-B007 and B008-B009) to couple together to form a 4-car train for operation.

[0073] S303.2: Disassembly and assembly of spare cars in large formations Perform de-grouping operations on spare cars whose number of formations exceeds the planned number of formations: Select a suitable large-formation spare car (such as a 4-car or 3-car formation). Perform the decomposition operation to obtain train units that meet the planned number of train formations. The deassembled train units will be put into operation. Application Example: A 2-car train is needed, but no 2-car spare cars are available. The system selects 4 spare cars B010-B011-B012-B013 and decouples them into two 2-car trains (B010-B011 and B012-B013), one of which is used for operational tasks.

[0074] This implementation method employs a multi-level spare car handling strategy, utilizing both small-group coupling and large-group decoupling to fully leverage the potential of existing spare car resources and improve vehicle utilization. Even when the primary spare car is unavailable, intelligent train formation processing ensures the execution of the operational plan and avoids service interruptions. It automatically selects the lowest-cost handling solution, prioritizing direct replacement and then considering train formation processing to minimize operating costs. This ensures the reliable operation of the dynamic train formation adjustment system under various resource conditions, providing strong technical support for urban rail transit operations.

[0075] In an exemplary embodiment, the process of generating the train formation adjustment strategy for the target train does not involve generating a single solution, but rather constructing a strategy set containing multiple feasible solutions, and selecting the optimal solution from these solutions based on principles of economy and efficiency. Specifically, this includes the following steps: S701: Multiple Scheme Generation. Based on the current vehicle resource status (including the current formation of the target train, the number of formations and status of each spare car in the spare car list), the system generates at least two feasible formation adjustment methods for the same target train. For example, to adjust a target train currently in formation 1 (number 005) to formation 3, the system may generate the following two adjustment methods in parallel: Method 1 (Coupling Scheme): Find a 2-car train (such as number 010-011) from the spare car list and directly couple it with the target train (005) to form a 3-car train (005-010-011).

[0076] Method 2 (Decoupling-Coupling Combination Scheme): There are no suitable 2-car trains in the spare car list, but there is a 4-car train (numbered 012-013-014-015). The system generates a scheme: first, decoupling the 4-car train into two 2-car trains (012-013 and 014-015), then taking one of them (such as 012-013) and coupling it with the target train (005) to form a 3-car train (005-012-013).

[0077] S702: Quantitative Evaluation of Solutions. For each generated adjustment method, the system estimates its key execution parameters: Number of operations (O): The total number of linking and delinking operations required to complete this adjustment. For example, Method 1 requires only 1 linking operation (O=1); Method 2 requires 1 delinking and 1 linking operation (O=2).

[0078] Execution time (T): The total time required to complete all operations, estimated based on historical data or models. Decompilation and coupling operations each have their standard execution times; the second method typically takes longer than the first.

[0079] S703: Optimal Strategy Determination. Based on preset optimization objectives (such as "shortest adjustment time" or "fewest operations"), the system compares the evaluation parameters of each method to determine the final grouping adjustment strategy. Its decision logic can be expressed as: Optimal strategy = min( Wi * Oi + Wt * Ti ) Where Oi and Ti are the number of operations and execution time of the i-th method, respectively, and Wi and Wt are the corresponding weighting coefficients, which can be adjusted according to the actual operation strategy. By default, the scheme with the shortest execution time can be selected first to ensure that the train can leave the depot on time. Continuing the example above, the system will prioritize the first method as the final output train formation adjustment strategy.

[0080] This embodiment avoids the limitations of a single solution by introducing a multi-scheme generation and comparison mechanism. It can intelligently select the most efficient and economical grouping adjustment path under complex resource conditions, further improving the intelligence level and operational efficiency of the scheduling system and ensuring the practicality and optimization of the adjustment strategy.

[0081] In one exemplary embodiment, the rules for determining the planned train identification number are further defined to address the technical issues of uniqueness and consistency of multi-train identification, thereby simplifying system management and ensuring scheduling accuracy. Specific implementation methods include: The planned train identification number and the adjusted actual planned train identification number are both determined according to the following rules: The minimum value among all the fixed numbers of the TUs included in the train is taken as the unique identifier of the train.

[0082] For example, the identification of a newly formed train is determined: Suppose that three TUs numbered 002, 005, and 009 need to be coupled together to form a new 3-car train. The system takes the minimum value of the three numbers, 002, so the identification number of this newly formed planned train is 002.

[0083] For example, the markings on the trains after decommissioning are updated: A 4-car train originally had the identification number 001 (composed of numbers 001-004-006-008). After decoupling, if two 2-car trains are obtained, 001-004 and 006-008 respectively: The identification number for trains 001-004 is min(001,004)=001; The identification number for trains 006-008 is min(006,008)=006.

[0084] For example, the identification of the trains after coupling is determined: There is a 1-car train 002 that needs to be coupled with a 2-car train 005-007: Before coupling: Train 002 (identification number 002), Train 005-007 (identification number 005); After coupling, they form a 3-car train 002-005-007, with the identification number min(002,005,007)=002.

[0085] In the above exemplary embodiment, after the identification number of the target train changes after being processed by the grouping adjustment strategy, the planned train identification number in the dispatch plan is updated.

[0086] To ensure the accuracy of dispatch instructions and the feasibility of operational plans, after the grouping adjustment strategy is implemented, the system also includes a crucial process for updating identifiers and synchronizing shift plans, as detailed below: S901: Identifier number change judgment.

[0087] After the train formation adjustment strategy (such as decoupling or coupling operations) is executed, the system will recalculate the target train's identification number. The calculation rule is as described above: the minimum value among the fixed numbers of all TUs included in the train is taken. The system compares the newly calculated identification number with the original "planned train identification number" in the dispatch plan. If they match, no action is required; if they do not match, it is determined that the target train's identification number has changed, triggering the next update process.

[0088] S902: Dispatch plan update. Once the identification number is determined to have changed, the system will automatically perform a dispatch plan update operation, that is, replace the "planned train identification number" of the train in the dispatch plan with the newly calculated identification number.

[0089] S903: Update Confirmation and Synchronization. After the update is completed, the system sends a confirmation message to the dispatcher (such as "The planned train identification number has been updated from XXX to YYY"), and synchronizes the updated dispatch plan to the Automatic Train Control (ATS), vehicle management and other related systems to ensure that the entire operation system dispatches and tracks trains based on the latest and most accurate train identification information.

[0090] For example, suppose the dispatch plan requires a 3-car train with the identifier "003" to perform a certain operation. However, upon inspection, the TU currently with the identifier 003 is in a 4-car train (numbered 001-002-003-004, identifier min(001,002,003,004)=001). To satisfy the 3-car plan, the system generates a disassembly strategy, disassembling the 4-car train into a 3-car train (001-002-003, new identifier min(001,002,003)=001) and a 1-car train (004).

[0091] Before decommissioning: The train identification number in the dispatch plan is 003.

[0092] After decompilation: The identification number of the target train actually put into operation becomes 001.

[0093] At this point, the system detects that the identification number has changed from "003" to "001" and automatically updates the "planned train identification number" in the dispatch plan to "001". In this way, the ATS system will correctly track the train with identification number "001" to perform the task, avoiding "train loss" or dispatch instruction errors caused by identification number mismatch.

[0094] This embodiment effectively solves the problem of dynamic changes in train identity caused by flexible train formation through the aforementioned automated identification number update mechanism, ensuring the consistency between operational plan data and actual vehicle status. This is a key link in ensuring the reliable and accurate operation of the entire dynamic train formation control system. The technical advantages of this embodiment are that, regardless of how trains are formed or deformed, this rule ensures that each train has a unique and definite identification number, avoiding identification conflicts and management confusion; this rule is perfectly compatible with the traditional fixed numbering method, supporting both single-formation trains (where the identification number is its own number) and multi-formation trains, achieving a unified numbering system; and it is easy to calculate, facilitating both automatic system processing and manual identification and verification, reducing operational complexity.

[0095] In summary, by introducing a minimum-number-based identification rule, a simple yet effective train identification management scheme is provided. This ensures the uniqueness and consistency of train identification under various formation adjustments, laying a solid foundation for the reliable operation of the entire formation control system. This design embodies the technical wisdom of solving key problems in complex systems through simple rules.

[0096] Let's take a specific application scenario as an example to illustrate: Route configuration: The route uses a connection from station A to station B and then to station C, utilizing a turnaround before station A and a turnaround after station B. Vehicle configuration: A total of 20 cars are configured, including 3 two-car trains, 3 four-car trains and 2 one-car spare cars, supporting up to 4 dispatch plans to operate online at the same time.

[0097] Linkage capability: All vehicles support single-sided operation or multi-vehicle linkage, with a maximum linkage of 4 vehicles.

[0098] Taking the above application scenario as an example, the following explanation addresses the situation where the actual train formation data exceeds the planned formation number, when the target train includes the target TU: Application Scenario 1-1: The current number of groups is 2.

[0099] When the planned number of train sets is 1, the target train will be decoupled in a 1-1 manner. The target train set will be retained, and the other single train set will be stored in the spare car list.

[0100] Application Scenario 1-2: Actual grouping data volume is 3 1-2-A, The planned number of formations is 1 (1) The target TU is located at one end of the target train in the train formation; If the target TU is located at the left end of the target train, the target train will be decoupled in the form of 1-2. The target TU will be retained, and the other 2 train sets will be stored in the spare car list.

[0101] If the target TU is located at the right end of the target train, the target train will be decoupled in a 2-1 manner, retaining the target TU and storing the other 2 train sets in the spare car list.

[0102] (2) The target TU is not located at one end of the target train in the train formation; Since the train formation data between the target TU and one end of the train formation does not meet the planned formation quantity, if the target TU is to be retained, it needs to be de-formed twice, which is uneconomical. Therefore, this application proposes an improved method, namely, de-forming once, performing de-formation form 1-2, replacing the dispatch plan train with a single-formation train, and storing the other two train formations in the spare car list.

[0103] 1-2-B, The planned number of formations is 2 (1) The target TU is located at one end of the target train in the train formation; If the target TU is located at the left end of the target train, the target train will be decoupled in a 2-1 manner, retaining the target TU and storing the other 1 trainset in the spare car list.

[0104] If the target TU is located at the right end of the target train, the target train will be decoupled in the form of 1-2. The target TU will be retained, and the other train group will be stored in the spare car list.

[0105] (2) The target TU is not located at one end of the target train in the train formation; Since the train formation data between the target TU and one end of the train formation meets the planned number of formations, the target train is deformed in a 2-1 manner. The formation structure including the target TU is retained, and the other 1 formation is stored in the spare car list.

[0106] Application scenarios 1-3: The current number of groups is 4 1-3-A, The planned number of formations is 1 (1) The target TU is located at one end of the target train in the train formation; If the target TU is located at the left end of the target train, the target train will be decoupled in the form of 1-3. The target TU will be retained, and the other 3 train sets will be stored in the spare car list.

[0107] If the target TU is located at the right end of the target train, the target train will be decoupled in a 3-1 manner, retaining the target TU and storing the other 3 train sets in the spare car list.

[0108] (2) The target TU is not located at one end of the target train in the train formation; If the target TU is to be retained, it needs to be decoupled twice, which is uneconomical. Therefore, this application proposes an improved method, namely, decoupling once, performing decoupling forms 1-3, replacing the dispatch plan train with a single-unit train, and storing the other 3-unit train in the spare car list.

[0109] 1-3-B, The planned number of formations is 2 (1) The target TU is located at one end of the target train in the train formation; The target train is decoupled in a 2-2 configuration, retaining the train formation including the target TU and storing the other two trains in the spare car list.

[0110] (2) The target TU is not located at one end of the target train in the train formation; Since the train formation data between the target TU and one end of the train formation meets the planned number of formations, the target train is deformed in a 2-2 manner. The formation structure including the target TU is retained, and the other two formations are stored in the spare car list.

[0111] 1-3-C, The planned number of formations is 3 The target train is decoupled and reassembled in either a 3-1 or 1-3 configuration. This includes setting the target TU's train formation data to 3 and storing the remaining train formation in the spare car list.

[0112] Continuing with the above application scenario as an example, let's explain the situation where the actual train formation data is less than the planned formation number when the target train includes the target TU: Application Scenario 2-1: Current group size is 1 When the planned number of train sets is 2, if there is 1 train set in the spare car list, the target train will be combined with the 1 train set, and the combination will be 1+1.

[0113] When the planned number of train sets is 3, and there are 2 train sets in the spare car list, the target train will be combined with 1 train set, and the combination will be 2+1.

[0114] When the planned number of train sets is 4, and there are 2 train sets in the spare car list, the target train will be combined with 1 train set, and the combination will be 3+1.

[0115] Application Scenario 2-2: Current group size is 2 When the planned number of train sets is 3, if there is 1 train set in the spare car list, the target train will be combined with the 1 train set, and the combination will be 1+2.

[0116] When the planned number of train sets is 4, and there are 2 train sets in the spare car list, the target train will be combined with 1 train set, and the combination will be 2+2.

[0117] Application Scenario 2-3: Current group size is 3 When the planned number of train sets is 4, if there is 1 train set in the spare car list, the target train will be combined with the 1 train set, and the combination will be 3+1.

[0118] When performing train formation processing with the target train, if the required spare car cannot be found, a spare car with a formation quantity greater than the required formation quantity is searched for; if found, the found spare car is deformed to obtain a spare car that can be coupled and has a formation quantity equal to the required increase in formation quantity, which is then used as the target spare car.

[0119] For example, if the current trainset size is 3 and the planned trainset size is 1, and there is no 1-car train in the spare train list, then a spare 2-car train is searched for. If found, it is disassembled (disassembly method 1-1), and then the disassembled 1-car train is combined with the current 3-car train to form a 3+1 formation. If no spare 2-car train is found, then a spare 3-car train is searched for. If a 3-car train is found, it is disassembled (disassembly method 2-1), and then the disassembled 1-car train is combined with the target train to form a 3+1 formation. If no spare 3-car train is found, a message is displayed indicating that no suitable spare train was found, and neither the trainset / disassembly scheme is suitable. The dispatcher will intervene, or the 3-car train will be dispatched by default.

[0120] In summary, to improve operational efficiency and reduce the number of train coupling and decoupling operations, a flexible train formation processing method is proposed, and a recommended train formation scheme is provided. The input data is the required dispatch plan, and the output data is the available train formations that adapt to the dispatch plan. Furthermore, following the principle of minimal change, the dispatch train formations are modified or the dispatch plan trains are replaced to save time and costs.

[0121] This solution can be widely applied to the following urban rail transit operation scenarios: Daily peak passenger flow scheduling: During morning and evening rush hours, passenger flow exhibits a clear tidal pattern. The system automatically predicts peak passenger flow and adjusts smaller train sets to larger ones. For example, during the morning peak from 7:00 to 9:00, 2-car trains are dynamically adjusted to 4-car train sets to improve one-way transport capacity.

[0122] Emergency Response to Special Events: During special periods such as sporting events and large-scale activities, the system can quickly adjust train formation plans to cope with sudden surges in passenger flow. For example, during events held at the stadium station, the number of train formations on surrounding lines can be temporarily increased to quickly evacuate spectators.

[0123] Train Disruption Replacement: When a scheduled train malfunctions, the system automatically activates the backup train replacement mechanism to ensure operational continuity. For example, if a scheduled train experiences a sudden malfunction, the system will automatically dispatch a backup train within 5 minutes to avoid operational interruption.

[0124] Energy-saving off-peak operation: During off-peak periods or at night when passenger traffic is low, the system automatically reduces train formations to lower energy consumption. For example, after 11:00 PM, 4-car trains will be reduced to 2-car trains to reduce energy consumption.

[0125] Transitional period after new line opening: In the initial stage of a new line's operation, passenger flow is unstable, and the system dynamically adjusts the number of train sets to adapt to changes in passenger flow. For example, in the first month of a new line's operation, the number of train sets is dynamically adjusted based on actual passenger flow to gradually optimize capacity allocation.

[0126] This application embodiment also provides a storage medium storing a computer program, wherein the computer program is configured to execute the method described above when running.

[0127] An electronic device includes a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the methods described above.

[0128] This electronic device can be deployed in the server cluster of the rail transit control center.

[0129] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

Claims

1. A train formation control method, characterized in that, include: Based on historical passenger flow data, predict the train passenger flow for the target period in the future; Based on the predicted passenger flow, a dispatch plan for the future target time period is generated, wherein the dispatch plan includes the planned departure time, the planned train identification number, and the planned number of train formations; Determine the number of train formations of the target train to obtain the current number of train formations. If there is an actual train in the preset reserve car list, then the target train is the actual train, which is the train whose basic formation unit TU of the target train is located at the preset time before the scheduled departure time corresponding to the planned train identifier number. Otherwise, the target train is a train in the reserve car list, which records trains that are not in operation. If the current number of train formations differs from the planned number of train formations, a train formation adjustment strategy for the target train is generated. Output the train formation adjustment strategy, wherein the target train processed by the train formation adjustment strategy is adapted to the predicted passenger flow. The train formation adjustment strategy for generating the target train includes: When the current number of train formations is greater than the planned number of train formations, a first strategy for unforming the target train is generated as the train formation adjustment strategy. When the current number of train sets is less than the planned number of train sets, a second strategy for coupling the target train is generated based on the number of train sets of each spare car in the spare car list as the train set adjustment strategy. The number of train formations of the target train after processing by the formation adjustment strategy is the planned number of train formations. The first strategy includes: When the current train formation size is 2, the target train is deformed into two independent TUs; When the current number of train formations is greater than 2, if the target train includes a target TU, the target train is de-formed according to the formation position of the target TU in the target train; otherwise, the target train is de-formed according to the planned number of train formations.

2. The method according to claim 1, characterized in that, The step of performing the de-staging operation on the target train according to the formation position of the target TU on the target train includes: When the formation position of the target TU is at one end of the target train, the target train is disassembled into two independent first formation structures, wherein the number of formations in the first formation structure of the target TU is the planned number of formations; When the formation position of the target TU is not at one end of the target train, if the formation data between the target TU and one end of the train formation in the target train meets the planned formation number, then the target train is decomposed into two independent second formation structures, including the second formation structure of the target TU, whose formation number is the planned formation number; otherwise, the target train is decomposed into two independent third formation structures, wherein the formation number of the third formation structure excluding the target TU is the planned formation number.

3. The method according to claim 1, characterized in that, Based on the number of spare cars in the spare car list, a coupling strategy for the target train is generated as the train formation adjustment strategy, including: Calculate the required number of additional formations based on the current number of formations and the planned number of formations; If a target spare car exists in the spare car list, the coupling strategy is generated based on the target spare car, wherein the target spare car is a spare car that can be coupled and whose grouping quantity is the required number of additional groups, or multiple spare cars whose quantity is the required number of additional groups.

4. The method according to claim 3, characterized in that, The method further includes: If the target spare car is not found in the spare car list, then find a spare car with a train number greater than the required train number. If found, the found spare car is decoupled to obtain a spare car that can be coupled and has the required number of additional train formations, which is then used as the target spare car.

5. The method according to claim 1, characterized in that, The train formation adjustment strategy for generating the target train includes: Generate at least two train formation adjustment methods corresponding to the target train, wherein each train formation adjustment method has its own number of operations and execution time; The grouping adjustment strategy is determined based on the number of operations and execution time of each grouping adjustment method.

6. The method according to claim 1, characterized in that, The methods for selecting the target train as one of the trains in the list of spare trains include: If there are candidate spare cars in the spare car list, the candidate spare car is selected as the target train, wherein the number of trains in the candidate spare car is the same as the planned number of trains; otherwise, any train in the spare car list is selected as the target train.

7. The method according to any one of claims 1 to 6, characterized in that: The identification number is determined based on the minimum value among all the identification numbers of the TUs included in the train; When the number of TUs in any train, including the spare car and the target train after the formation adjustment strategy, changes, the identification number of each train is redefined. Specifically, after the identification number of the target train changes after being processed by the aforementioned train formation adjustment strategy, the planned train identification number in the dispatch plan is updated.

8. A storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the method described in any one of claims 1 to 7 when it is run.

9. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the method as described in any one of claims 1 to 7.

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