Dynamic partitioning and grouping method for local decentration group train virtual reconnection

Abstract

The invention discloses a dynamic partitioning and grouping method for virtual reconnection of local decentration group trains, which is based on a local decentration structure, implements local optimization and partitions and groups a network under the principle of keeping centralized control of a train operation control system, avoids large-range train-ground large-capacity data interaction, and improves the reliability of train operation. The train handover scene is reduced; the modularity of the train operation control network is used as an overall quality evaluation index, partition decision making of the train operation control network is guided, the partition and grouping mode of the train is automatically adjusted according to real-time environment changes, task requirements and system states in the train operation process, and a dynamic partition and grouping decision scheme is adopted, so that the train operation efficiency is improved. Mobile equipment on a line is helped to adaptively adjust partitions, so that the overall load balance of a train operation control network is realized; in addition, a symmetry principle in a group theory is introduced, and a symmetric structure in the system is identified and utilized in train dispatching, so that optimization calculation is simplified and accelerated.

Description

Technical Field

[0001] The present invention relates to the field of rail transit technology, and in particular to a dynamic partitioning and grouping method for virtual reconnection of a local decentralized group of trains. Background Art

[0002] At present, my country's rail transit industry generally adopts a train operation control system based on vehicle-to-ground communication. Its characteristics are based on large-capacity vehicle-to-ground communication, relying on the ground control center to send mobile authorization to the on-board equipment to ensure the safe and efficient operation of trains on the line. In the train operation control system of the ground center, the train needs to obtain the mobile authorization of the ground control center before it can continue to move forward. Once the train fails to obtain authorization, or the authorization is not timely enough, emergency braking will be caused. For this reason, maintaining stable and continuous communication resources for trains is very important to ensure driving safety and improve operation efficiency.

[0003] The CTCS-3 level train control system of high-speed railways uses GSM-R technology to achieve continuous, two-way and safe information transmission between the ground and the train. GSM-R (Global System for Mobile Communications-Railway) is a global mobile communication system designed specifically for railway communications, ensuring high reliability and safety of communication when the train is running at high speed. The communication cells are distributed linearly along the railway, forming a stable communication network structure. This design can provide seamless communication coverage when the train passes through different cells. Each cell is equipped with a base station to support the real-time location information update of the train, the transmission of control signals, and the exchange of instructions with the train control center. The handover process refers to when the communication indicators of the communication base station cannot meet the communication needs of the train and the conditions for triggering the handover are met, the user will disconnect from the source base station and establish a new connection with the target base station to achieve the handover. The main purpose is to achieve uninterrupted communication of mobile equipment through channel switching and ensure the safe operation of the train. Generally speaking, the main reasons for triggering the handover are: the distance between the mobile equipment and the base station is far, the communication quality is poor, and the load is unbalanced within the partition.

[0004] However, when the train is running at high speed, communication interruption or timeout during the handover process will have a certain degree of impact on the safe operation of the train; for example, communication interruption or timeout during the handover process will lead to failure to switch the train control system level in time, or failure to update the location information in time. Such problems are mainly caused by abnormal radio cell reselection and location update when the train is handing over the zone, and they occur more frequently in the actual operation of high-speed railways. At present, there is no accurate positioning method. Even if the CTCS-3 level train-to-ground communication is normal in subsequent operation, such faults are still identified as radio faults.

[0005] The root cause of the above problems is that the centralized system structure itself is not suitable for implementing a large number of high-capacity train-to-ground communications, and encountering network delays has led to a decline in system performance. The existing solutions mainly focus on optimizing on-board radios and communication networks, which cannot completely solve such problems. In order to improve the problem of the train control system affecting train operation due to cross-zone switching, in addition to improving the reliability of the communication system, it is also possible to balance the load of the train operation control network from the perspective of the macro-overall signal system, optimize resource allocation and scheduling, design fault-tolerant and recovery strategies, and reduce excessive reliance on train-to-ground communications. However, there is currently no more effective solution.

[0006] In view of this, the present invention is proposed. Summary of the invention

[0007] The purpose of the present invention is to provide a dynamic partitioning and grouping method for virtual reconnection of a local decentralized group train, which supports the trains on the line to realize dynamic partitioning and grouping, adaptive resource allocation, multi-level coordination mechanism and autonomous operation control in the operating environment, and ensures the safety and efficiency of the autonomous operation of the virtual reconnection trains.

[0008] The objective of the present invention is achieved through the following technical solutions:

[0009] A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains, comprising:

[0010] Based on the concept of local decentralization, a train operation control network is constructed using trains and ground centers. Trains and ground centers are nodes in the train operation control network, called train nodes and ground control nodes. The communication connections between train nodes and ground control nodes, as well as the communication connections between trains, are all considered as edges in the train operation control network.

[0011] The modularity of the train operation control network is calculated by combining the communication connection status between different nodes, whether different nodes belong to the same community, and the total number of communication connections of the train operation control network. This is used as an overall quality evaluation indicator to guide the partitioning decision of the train operation control network. The train nodes in each community form several virtual train formations to complete the partitioning and grouping of the operation control network.

[0012] After the train operation control network is partitioned and grouped, symmetry optimization scheduling is performed based on group theory for the symmetric structure in each community; wherein the symmetric structure refers to the symmetric characteristics of the train nodes in the community in the train operation mode.

[0013] It can be seen from the technical solution provided by the present invention that, based on the local decentralized structure, local optimization is implemented under the principle of maintaining centralized control of the train operation control system, and the network is partitioned and grouped, thereby avoiding large-scale and large-capacity data interaction between the train and the ground, and reducing the train cross-zone switching scenarios; the modularity of the train operation control network is used as an overall quality evaluation indicator to guide the partitioning decision of the train operation control network, and support automatic adjustment of the train partitioning and grouping methods according to real-time environmental changes, task requirements and system status during the train operation process, so as to adapt to the complex and changeable operating environment, better respond to emergencies, and optimize the overall efficiency; and the decision-making scheme of dynamic partitioning and grouping also helps mobile equipment on the line to adaptively adjust the partition, thereby achieving overall load balancing of the train operation control network; in addition, the symmetry principle in group theory is introduced to identify and utilize the symmetric structure within the system in train scheduling, thereby simplifying and accelerating optimization calculations. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0015] Figure 1 A flowchart of a dynamic partitioning and grouping method for virtual reconnection of a local decentralized group train provided by an embodiment of the present invention;

[0016] Figure 2 A schematic diagram comparing a centralized system and a local decentralized system provided in an embodiment of the present invention;

[0017] Figure 3 A schematic diagram of the communication structure between a train and a control center of a conventional railway signal control system provided by an embodiment of the present invention;

[0018] Figure 4 A schematic diagram of the communication structure between a train and a control center after dynamic partitioning and grouping provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of the present invention.

[0020] First, the terms that may be used in this article are explained as follows:

[0021] The terms "include", "comprises", "contains", "has" or other descriptions with similar semantics should be interpreted as non-exclusive inclusion. For example, including certain technical feature elements (such as raw materials, components, ingredients, carriers, dosage forms, materials, dimensions, parts, components, mechanisms, devices, steps, procedures, methods, reaction conditions, processing conditions, parameters, algorithms, signals, data, products or products, etc.) should be interpreted as including not only certain technical feature elements explicitly listed, but also other technical feature elements known in the art that are not explicitly listed.

[0022] The term "consisting of..." means excluding any technical feature elements not explicitly listed. If this term is used in a claim, it will make the claim closed, so that it does not contain technical feature elements other than the technical feature elements explicitly listed, except for the conventional impurities related to them. If this term only appears in a clause of a claim, it only limits the elements explicitly listed in the clause, and the elements recorded in other clauses are not excluded from the overall claim.

[0023] Aiming at the problem that communication interruption caused by handover in the existing rail transit train operation control system affects driving safety, the present invention proposes a dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains, which helps mobile equipment on the line to adaptively adjust the partitions and avoid handover problems. It further supports the trains in the partition to adopt flexible grouping methods to reduce train-ground communication, shorten the tracking interval, and improve the overall transportation efficiency of multiple trains in the partition.

[0024] The following is a detailed description of a dynamic partitioning and grouping method for virtual reconnection of a local decentralized group train provided by the present invention. The contents not described in detail in the embodiments of the present invention belong to the prior art known to professional and technical personnel in this field. If no specific conditions are specified in the embodiments of the present invention, the conventional conditions in the field or the conditions recommended by the manufacturer shall be followed. The instruments used in the embodiments of the present invention, if the manufacturer is not specified, are all conventional products that can be purchased commercially.

[0025] like Figure 1 FIG. 1 is a flowchart of a method for dynamic partitioning and grouping of virtual reconnection of a local decentralized group train provided by an embodiment of the present invention, which mainly includes the following steps:

[0026] Step 1: Based on the concept of local decentralization, build a train operation control network using trains and ground centers.

[0027] In an embodiment of the present invention, based on the concept of local decentralization, a train operation control network is constructed using trains and ground centers. The trains and ground centers serve as nodes in the train operation control network, referred to as train nodes and ground control nodes. The communication connections between train nodes and ground control nodes, as well as the communication connections between trains, are all used as edges in the train operation control network.

[0028] Step 2: Use complex network algorithms to provide a fast partitioning and grouping evaluation strategy for trains running on the line.

[0029] In the embodiment of the present invention, complex network theory is used as the basis to guide the dynamic grouping and partitioning decision of multiple trains. Specifically, the modularity of the train operation control network is calculated based on the communication connection status between different nodes, whether different nodes belong to the same community, and the total number of communication connections of the train operation control network. This is used as an overall quality evaluation indicator to guide the partitioning decision of the train operation control network, and the train nodes in each community form several virtually formed train formations to complete the partitioning and grouping of the operation control network.

[0030] Step 3: Achieve efficient optimization decision-making based on group theory symmetry optimization.

[0031] In an embodiment of the present invention, after the train operation control network is partitioned and grouped, symmetry optimization scheduling is performed based on group theory for the symmetric structure in each community; wherein the symmetric structure refers to the symmetric characteristics exhibited by the train nodes in the community in the train operation mode.

[0032] Based on the above scheme, a multi-level coordination mechanism for the train operation control system is also introduced. In the train operation control network, control systems at each level make decisions independently and maintain consistency through a collaborative mechanism to achieve local autonomy and global coordination.

[0033] In order to more clearly demonstrate the technical solution and technical effects provided by the present invention, the method provided by the embodiment of the present invention is described in detail with reference to specific embodiments below.

[0034] 1. The principle of local decentralization.

[0035] like Figure 2The diagram below is a comparison diagram of a centralized system and a local decentralized system. The left part is a centralized system, in which all control, decision-making and resource allocation are concentrated on one or a few central nodes, such as the RBC (radio block center) of the train operation control system. This central node usually undertakes the main functions of the system, such as management, coordination, data processing and decision-making, and all other nodes rely on this central node for operation. Its advantages are that decision-making and operation are unified, conflicts and inconsistencies are reduced, and the management of data and resources is relatively simple and easy to control. The disadvantage is that the scalability of the centralized system is limited. As the scale of the system increases, the load of the central node increases. Once the central node fails, the entire system may be paralyzed. The structure of the centralized system limits its ability to undertake large-scale and sophisticated management tasks, because once the demand increases or becomes more complex, it will inevitably fall into the choice of "sacrificing efficiency to ensure safety" and "improving efficiency and reducing safety margin".

[0036] Although advanced train operation control systems balance loads and improve efficiency by adopting a distributed structure in the control center, it mainly refers to dividing multiple partitions, each partition is managed by an RBC, and multiple RBCs are used to manage all line resources in parallel. In this way, tasks are distributed to multiple nodes, and multiple tasks can be processed simultaneously, thereby improving the overall efficiency of the system. Each node can perform some tasks independently, and these tasks can be carried out simultaneously, reducing the processing time of tasks and maintaining the centralization of control. However, the complexity of the system will continue to increase. Since the system involves multiple nodes and the interaction between them, the status, task allocation, communication protocol, etc. of each node require fine coordination and monitoring, and the complexity of managing and maintaining distributed systems has increased significantly. And as the scale of the system expands, it becomes more difficult to maintain synchronization and coordination between all nodes. Network delays, node failures, and data consistency issues may lead to a decline in system performance, and differences between nodes may lead to inconsistent updates or performance bottlenecks, and even face huge safety risks. When faced with more refined control requirements such as virtual train reconnection, the delay problems and complex life cycle management problems of existing train control systems will make it difficult to implement or limit performance.

[0037] Early Internet architectures and traditional database systems were centralized system architectures. With the changes in demand, system scalability requirements, and the emergence of new technologies, they gradually evolved into distributed architectures, and then further moved towards decentralized technology. Drawing on the development experience of other modern application fields and combining the new requirements of rail transit train operation control systems, this invention proposes a system structure based on local decentralized systems, such as Figure 2As shown in the right part. In this structure, different parts of the network show a certain degree of decentralization, and there is a certain degree of autonomy and independence between each part, but the central node or central cluster is not completely removed. It can be seen that the structure still has some centralization, but the interconnection and distribution between each sub-cluster show decentralized characteristics. This partially decentralized structure retains a certain degree of central control while allowing other parts of the system to have the ability to operate and make decisions independently. It is very suitable for implementing small-scale capacity enhancement technologies on existing train operation control systems, such as group operation control.

[0038] 2. Comparison between the traditional communication scheme and the communication scheme of the present invention.

[0039] In order to solve the problem that communication interruption or delay caused by inter-zone switching in the existing rail transit train operation control system affects driving safety, the present invention proposes a system structure based on local decentralization, and provides a fast partitioning and grouping strategy for trains running on the line by using a complex network algorithm. The concept of group theory is further abstracted, and the symmetry existing in the system is used to achieve optimal decision-making, and finally realize dynamic partitioning and grouping of multiple trains, thereby supporting the trains on the line to realize dynamic partitioning and grouping, adaptive resource allocation, multi-level coordination mechanism and autonomous operation control in the operating environment.

[0040] 1. Existing communication solutions.

[0041] like Figure 3 The figure shows the communication structure between the train and the control center of the traditional railway signal control system. In the traditional train operation control system, such as the CBTC system of urban rail transit or the CTCS-3 system of high-speed railway, all running trains communicate with the same ground center, report the running speed and position of the train to it, and request the movement authorization of the train. This structure makes the train operation dependent on the large-capacity communication channel between the train and the ground. When the train is running, it will inevitably cause cross-zone switching when moving between cellular cells, which will cause communication interruption to a certain extent, causing the ATP emergency braking of the train signal system, affecting the ride comfort, reducing the train operation efficiency, and increasing the train operation energy consumption.

[0042] 2. The communication scheme of the present invention.

[0043] like Figure 4As shown, it is a schematic diagram of the communication structure between the train and the control center after dynamic partitioning and grouping provided by the present invention. The train operation control network proposed by the present invention regards the trains running on the line and the ground center as multiple nodes in a complex network, and the communication connections between the train and the ground, and between the train and the train are regarded as the edges of the complex network. Based on the concept of "local decentralization", the quality function (overall quality evaluation index) is optimized on the possible divisions of the network to form a characteristic matrix vector of the network, and a method for partition detection and evaluation is formed through vector expression, thereby obtaining high-quality detection results. Further, the dynamic grouping and partitioning decision of multiple trains is guided according to the detection results of the complex network (such as Figure 4 Trains in a zone can maintain “full train-to-ground communication connection” with the ground center (as shown in Figure 4 Each train communicates with the ground center and can also maintain a "chain connection" (as shown in the middle partition 1). Figure 4 The pilot car is determined through the election negotiation strategy, and the pilot car implements the vehicle-to-ground communication connection. Other trains maintain a virtual coupling formation with the pilot car through vehicle-to-vehicle communication and autonomously negotiate line resources in a small range.

[0044] From the above comparison, it can be seen that the present invention aims to solve the problem that in the existing train operation control system, communication interruption caused by train inter-zone switching leads to train braking, and data transmission security affects driving safety. By dividing the characteristic matrix vector after optimizing the quality function of the train operation control network, a partition detection and evaluation scheme is formed to guide multiple trains to dynamically group and partition during operation, thereby avoiding train inter-zone switching scenarios.

[0045] In summary, the present invention aims to solve the problem of train braking caused by communication interruption caused by train cross-zone switching in the existing train operation control system, and the problem of data transmission security affecting driving safety. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains is proposed. By dividing the characteristic matrix vector after the complex network optimization quality function, a partition detection and evaluation method is formed to guide the dynamic grouping and partitioning of multiple trains during operation, and further based on the conceptual abstraction problem of group theory, efficient optimization decision-making is achieved according to the symmetry of the system. Through this method, the train group can actively optimize the partitioning and grouping during operation, avoid or reduce the train cross-zone switching scenarios as much as possible, and further support the trains in the partition to adopt a small formation based on vehicle-to-vehicle communication to reduce the tracking interval, thereby improving the overall transportation efficiency of multiple trains in the partition.

[0046] 3. Introduction of the solution of the present invention.

[0047] 1. Introduction to train operation control network.

[0048] In an embodiment of the present invention, the train operation control network is composed of train nodes, ground control nodes and communication connections between nodes, wherein the nodes represent the physical control devices in the real train control system, and the edges represent the communication connections between these physical control devices. The number of edges contained in the shortest path between two nodes represents the network distance (non-track distance) between the two train nodes. The average value of the network distance between any two nodes in the train operation control network is the average path length of the network, which represents the degree of separation between nodes in the entire train control network and reflects the global characteristics of the train control network. The total number of edges between a train node and other nodes is the degree of the train node. The degree values ​​of the train nodes in the network are sorted from small to large, and the proportion of nodes with a degree of k to the total number of nodes in the network is statistically obtained. P(k), which is the degree distribution of the network. From a probability perspective, P(k) is the probability of randomly selecting a node in the network with a degree of k.

[0049] 2. Zoning and grouping decision-making plan.

[0050] In order to achieve the overall load balance of the train operation control network, it is necessary to divide it into multiple communities. Not only should there be almost no edges between communities, but the trains in the partition should also have specific performance as much as possible to further realize the virtual coupling of trains. To achieve this effect, simply counting the edges is not a good way to intuitively quantify the community structure, because most of the time there are no edges between communities just because the number of edges between groups is less than expected. Since the real community structure in the train control network corresponds to the statistical edge arrangement, it can be quantitatively evaluated and guide the final decision by using modularity metrics. The value of modularity can be positive or negative, and a positive value indicates that a reasonable partition structure may exist. The specific scheme is as follows:

[0051] Use A ij Indicates the communication connection between node i and node j, A ij If it is 0, it means that there is no communication connection between node i and node j. ij If it is not 0, it means that there is a communication connection between node i and node j; in a one-dimensional network scale, if there is a communication connection between node i and node j, then A ij =1, in the case of multi-dimensional network superposition A ij Larger values ​​are possible; in fact, A ij That is, the elements of the train operation control network adjacency matrix are used Indicates the total number of communication connections in the train operation control network; C i , C j Correspondingly, it represents the community where node i and node j are located. If node i and node j belong to the same community, then δ(C i ,C j )=1, otherwise δ(C i ,Cj )=0.

[0052] During operation, each node randomly communicates (including vehicle-to-vehicle communication and vehicle-to-ground communication). The expected number of connections between node i and node j can be expressed as To indicate that k i and k j is the degree of the node (meaning that the node has point-to-point direct communication with several nodes in the area), expressed in k i For example: A il is the communication connection status between node i and node l.

[0053] Finally, the calculation method of the modularity Q of the train operation control network is expressed as:

[0054]

[0055] The modularity Q of the train control network is a new attribute after the network definition of the train operation control system. It can evaluate the overall quality of the train operation control network after it is divided into multiple small communities, and can quantitatively evaluate whether the division is reasonable. From the above calculation method, it can be concluded that the physical meaning of the modularity function of the train control network is the expected value of the proportion of edges within the community in the network minus the proportion of edges randomly connecting nodes under the same community structure. Therefore, the larger the Q value, the more obvious the community structure of the network. In a network with better modularity, there are many edges within the community, and only a few edges between communities. This ensures that the trains within the community will not have communication delays or interruptions due to cross-community communication. It also means that the trains within the community have a certain degree of performance that can implement virtual coupling.

[0056] During the operation of the train, various operation data (for example, speed, position, acceleration, etc.) of each train node are taken as data blocks, and the data blocks are organized to form a data block sequence; the Merkle tree is constructed for the data block sequence to obtain a hash value of the root node; if any data block changes, the entire Merkle tree structure will change, and the hash value of the root node will also change accordingly. Whenever each node receives train operation data from other train nodes, it verifies whether the data has been tampered with or damaged by comparing the hash value of the root node. This Merkle tree structure can quickly and accurately verify the integrity and correctness of the data, and ensure the security and reliability of the train operation control network. On this basis, the entire train operation control network can be divided into communities in the framework of a tree structure (i.e., the aforementioned Merkle tree structure), the leaves of the tree structure are the various ground control nodes, and the internal connections of the tree correspond to the communication connections between the ground control nodes.

[0057] Based on the above method, the adjacency matrix of the tree structure formed by the ground control nodes and their communication connections in the train operation control network can be stored as an integer array. The community is dynamically divided, and pairs of rows and columns are repeatedly merged when merging corresponding communities. The calculation method of the modularity Q of the train operation control network is converted into a matrix form, which is expressed as:

[0058]

[0059] Among them, S represents an n*R matrix, and its i-th row and r-th column element is denoted by S ir , S ir =1 means that the i-th node belongs to the r-th community, n is the number of nodes, R is the number of communities, Tr() is the trace of the calculation matrix, and T is the matrix transpose symbol; the modularity matrix B reflects the deviation between the actual connection situation in the network and the connection expectation value, which is used to determine whether the community structure in the network is significant. ij is the element in the i-th row and j-th column of matrix B.

[0060] The modularity matrix B of the train operation control network is a matrix that encodes the network connection structure. It can effectively describe the network structure, guide train partitioning and grouping decisions, and ensure the overall load balance of the network.

[0061] Each community contains multiple train nodes. The train nodes in the community are grouped to form several virtually-formed train formations. The train nodes select a lead car through election and negotiation, and the others serve as follower cars. The follower cars maintain a virtually connected small formation with the lead car through vehicle-to-vehicle communication to complete the grouping. This part of the process can refer to conventional technology and will not be elaborated in the present invention.

[0062] 3. Symmetry optimization based on group theory.

[0063] Local decentralized systems usually have certain symmetries, such as repeated paths, similar scheduling rules or patterns when trains are running. Group theory can help identify these symmetries and transform them into mathematical group structures. These symmetries can be used to reduce redundant calculations, reduce the complexity of calculations, and form standardized decision-making patterns in the system. For example, if some train operation modes have the same symmetric characteristics, they can be classified into the same category, and effective grouping and path planning can be constructed based on these relationships to simplify the design of scheduling and control strategies. If the itineraries of some trains are periodic or symmetrical within a certain period of time, these characteristics can be used to optimize scheduling and resource allocation, making the overall operation of the system smoother and more efficient. Through the representation theory of groups, complex optimization problems can be transformed into simpler linear representations, thereby speeding up calculations. For train control systems that require real-time scheduling and control, this optimization can significantly improve the system's response speed and decision-making efficiency. In addition, through group theory, the system can identify invariants and symmetric operations, which is particularly important when dealing with unexpected situations. For example, in certain emergency situations, group theory can help identify elements in the system that can remain unchanged, thereby providing a theoretical basis for the system's emergency handling and improving the robustness of the system.

[0064] Suppose a local decentralized train network consists of multiple areas, each area has multiple train nodes, and these nodes are arranged according to a certain symmetrical structure. Specifically, the symmetrical structure refers to the symmetrical characteristics of the train nodes in the community in the train operation mode, for example, there is a symmetrical regularity in the train paths or scheduling schemes in certain areas.

[0065] In the embodiments of the present invention, the region mainly refers to the physical region in which the train is running, and the aforementioned community is usually used to describe the topological structure in the train network, that is, the group identified by the connection and interaction between nodes. In some cases, there may be overlap between the two, for example, the train nodes in a physical region can constitute a community in a topological sense.

[0066] Let G be a group that acts on a set of train nodes X. The orbital Orb of each train node x∈X G (x) represents all the locations that the train node x can reach under the action of group G:

[0067] Orb G (x) = {g·x|g∈G}

[0068] Here, g is an element in the group G, representing an operation or transformation.

[0069] Those skilled in the art can understand that a group is a structured set in mathematics, which usually needs to satisfy the properties of closure, associativity, identity element, and inverse element; in the train control network described in the embodiment of the present invention, the group G represents a set of operations or transformations on the operating mode of the train nodes, such as: different choices or symmetric transformations of train paths; scheduling or switching of train positions; certain structured arrangements or groupings between train nodes. These operations satisfy the algebraic properties of the group and represent symmetry or structured transformations in train scheduling. By utilizing the characteristics of the group structure, it is possible to more effectively manage train paths, allocate resources, simplify scheduling, and maintain the consistency and stability of the system.

[0070] In train scheduling, if different train nodes need to pass through the same track section under the action of the group, they can be regarded as symmetrical and a group, and the scheduling strategies can be the same.

[0071] In group action, the stable subgroup Stab G (x) is the set of group elements that keep node x unchanged:

[0072] Stab G (x) = {g∈G | g·x = x}

[0073] Stable subgroups indicate which operations do not change the state of the system under symmetry. This property can be used to identify invariant paths in path planning, thereby simplifying scheduling.

[0074] Exemplarily, it can be assumed that the path of the train operation has a symmetrical structure. For example, assuming that the train arrives at path p2 from path p1, the symmetry of the path is controlled by group G. In path selection, the symmetry of the path can be analyzed through group action, and the optimal path can be selected.

[0075] Based on this, when two train operation modes (for example, paths p1 and p2) have symmetric characteristics under the action of group G, the optimal solution of one of the train operation modes is calculated, and the optimal solution of the other train operation mode is obtained by performing symmetry operation on the optimal solution, which is expressed as:

[0076] p2=g·p1

[0077] Among them, p1 is the optimal solution of one train operation mode (for example, path p1), p2 is the optimal solution of another train operation mode (for example, path p2), and g∈G. The optimal solution refers to the best solution to achieve the set optimal goal under given constraints. For example, the optimal goal can be to meet the optimization goals such as time optimization, resource optimization, load balance optimization, safety optimization, and symmetry optimization.

[0078] The set of train operation modes is denoted as P. The set P is divided into different equivalence classes (for example, the same track) by the action of group G on the set P, which can be expressed as: P / G = {Orb G (p)|p∈P}; where P / G represents the result of partitioning the set P by the group G, p is a single train operation mode in the set P, and Orb G (p) is all the locations that can be reached by the train operation mode p, that is, Orb G (p) = {g·p|g∈G}; Although the train operation mode p here is different from the train node x mentioned above, these two different types of independent variables can be processed within the framework of group action. This processing method is consistent with the application logic of group theory and also meets the needs of train control systems at different levels.

[0079] In this way, only one scheduling calculation is needed for each equivalence class, which greatly reduces the amount of calculation. The final scheduling scheme can generate scheduling plans for all train operation modes through symmetric operations.

[0080] The optimal goal of the scheduling scheme is to minimize the objective function f(p). Based on group theory, the symmetric optimization scheduling is performed and the optimal solution is expressed as:

[0081] min p∈P f(p)=min p∈P / G f(p).

[0082] In the embodiment of the present invention, the optimal goal may be the various optimization goals provided above, and the objective functions corresponding to the various optimization goals may be implemented with reference to conventional technologies, which will not be elaborated in the present invention.

[0083] It can be seen that the computational complexity is greatly reduced by only optimizing the representative path of the equivalence class under the action of the group.

[0084] 4. Implement a multi-level coordination mechanism for the train operation control system.

[0085] Based on the above scheme of the embodiment of the present invention, in the local decentralized structure, train control systems at different levels, including regional control centers, trackside control units, on-board autonomous control devices, etc., cooperate through the above partitioning and grouping method to achieve efficient and stable operation of the overall system; the ground equipment involved in the train control systems at different levels is used as a ground control node, and the on-board autonomous control devices on the train involved are used as train nodes; that is, the above regional control center, trackside control unit, etc. can be regarded as ground control nodes in a broad sense, responsible for different levels of ground control tasks, and the on-board autonomous control devices are train nodes, responsible for the autonomous operation and micro-control of the train. Under this mechanism, the control units at all levels form a synergy through communication and data sharing to achieve the goal of global optimization. For the operation control of train groups, the regional control center can issue regional-level macro instructions to the on-board system, and the on-board system makes micro-adjustments at the train level according to local conditions. The control systems at all levels make decisions independently under certain rules and maintain consistency through a collaborative mechanism. This collaborative mechanism retains the flexibility of local autonomy and ensures global coordination. In fact, for a fully autonomous train system, unmanned driving is the ultimate goal, and all control and decision-making in the system are done automatically by the system.

[0086] The above solution provided by the embodiment of the present invention mainly achieves the following beneficial effects:

[0087] 1. Help trains avoid communication interruptions and delays during inter-zone handover by optimizing the system structure.

[0088] Existing train operation control systems are all based on a centralized structure, with zones defined by physical distance, which will cause communication interruption problems when the train switches between zones. The method described in the present invention proposes a local decentralized system structure, which implements local optimization under the principle of maintaining centralized control of the train operation control system, and enables trains in the zone to autonomously choose "full train-to-ground communication connection" or "chain connection" through zoning and grouping. In this way, large-scale and large-capacity data interaction between the train and the ground is avoided, and the train switching between zones is reduced.

[0089] 2. Increase system flexibility through dynamic partitioning and grouping.

[0090] The above scheme of the present invention supports automatic adjustment of the partitioning and grouping of trains according to real-time environmental changes, task requirements and system status during train operation. In traditional systems, the partitioning and grouping of trains are usually pre-set, but in a complex and changeable operating environment, the static partitioning and grouping method cannot cope with emergencies or optimize overall efficiency. The technology proposed in the present invention divides the characteristic matrix vector after the complex network optimization quality function to form a partition detection and evaluation method, which guides the dynamic grouping and partitioning decision of multiple trains during operation, and can improve the above problems.

[0091] 3. Realize the overall load balance of the train operation control network.

[0092] The reason for triggering the train to brake without reason is sometimes the problem of unbalanced network load, that is, multiple trains are congested in a certain area at a certain time, causing communication delays and triggering emergency braking of the train. From the perspective of the signal control system, the present invention proposes a decision method for dynamically partitioning and grouping trains during operation, which helps mobile equipment on the line to adaptively adjust partitions, thereby achieving overall load balance of the train operation control network.

[0093] 4. Realize optimized dispatching decisions for train groups.

[0094] The method of the present invention can realize the function of dynamically adjusting demand and allocating resources. Here, resources mainly refer to the basic elements required in the train operation process, such as the occupation of track sections, traction power supply, and communication bandwidth. In traditional systems, resource allocation is often fixed, and it is difficult to flexibly respond to sudden changes. The partitioning and grouping technology proposed in the present invention introduces the division and collaboration of different communities and nodes, as well as the coordination mechanism (control units at all levels coordinate through communication and data sharing), which can realize the adaptive resource allocation function, allowing the system to respond quickly in real time to ensure efficient use of resources. In large-scale train operation control networks, the symmetry principle in group theory is used to identify and utilize the symmetric structure within the system in train scheduling, thereby simplifying and accelerating optimization calculations. For example, the transportation demand and track section usage of some trains are equivalent in symmetry (such as having similar paths and timetable plans), so these equivalent problems can be combined into one problem for solution, that is, it is considered to be a group of super-long trains. This method greatly reduces redundant calculations, thereby improving the overall calculation efficiency, effectively shortening the time of scheduling decisions, and showing significant advantages in real-time systems.

[0095] 5. Realize the multi-level coordination mechanism of train operation control system.

[0096] The method described in the present invention can realize a multi-level coordination mechanism, which not only retains the flexibility of local autonomy, but also ensures global coordination, enhances the synergy effect of the system, and supports hierarchical management and maintenance. The multi-level coordination mechanism achieves a stronger synergy effect through the mutual cooperation of different levels. For example, when the boundary between regions is handed over, the control systems of different regions can achieve smooth train transfers through a coordination mechanism to avoid scheduling conflicts when trains enter new areas. At the same time, the system can realize cross-regional scheduling of resources through a coordination mechanism, such as temporarily adjusting the flow of trains between regions to balance the load. In addition, the multi-level coordination mechanism makes the management and maintenance of the system more modular and hierarchical. Different control levels can be updated, maintained and managed independently without direct impact on other levels.

[0097] 6. Introduce data analysis technology applications for train operation control systems.

[0098] The network modularity calculation and group theory symmetry optimization methods proposed in this paper further apply data analysis technology to the train operation control system, assist in the digital transformation of railway communication signal systems, and support the implementation and application of digital twin technology for train operation control systems. Redefine the train operation control system from the perspective of networking, digitization, and intelligence.

[0099] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above embodiments can be implemented by software, or by means of software plus necessary general hardware platforms. Based on such understanding, the technical solutions of the above embodiments can be embodied in the form of software products, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0100] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains, characterized in that: include: Based on the concept of local decentralization, a train operation control network is constructed using trains and ground centers. Trains and ground centers are nodes in the train operation control network, called train nodes and ground control nodes. The communication connections between train nodes and ground control nodes, as well as the communication connections between trains, are all considered as edges in the train operation control network. The modularity of the train operation control network is calculated by combining the communication connection status between different nodes, whether different nodes belong to the same community, and the total number of communication connections of the train operation control network. This is used as an overall quality evaluation indicator to guide the partitioning decision of the train operation control network. The train nodes in each community form several virtual train formations to complete the partitioning and grouping of the operation control network. After the train operation control network is partitioned and grouped, symmetry optimization scheduling is performed based on group theory for the symmetric structure in each community; wherein the symmetric structure refers to the symmetric characteristics of the train nodes in the community in the train operation mode.

2. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 1, characterized in that: The method of calculating the modularity of the train operation control network by combining the communication connection status between different nodes, whether different nodes belong to the same community, and the total number of communication connections of the train operation control network includes: Use A ij Indicates the communication connection between node i and node j, A ij If it is 0, it means that there is no communication connection between node i and node j. ij If it is not 0, it means that there is a communication connection between node i and node j; use Indicates the total number of communication connections in the train operation control network; C i , C j Correspondingly, it represents the community where node i and node j are located. If node i and node j belong to the same community, then δ(C i ,C j )=1, otherwise δ(C i ,C j )=0; The calculation method of the modularity Q of the train operation control network is: Among them, k i , k j Correspondingly, they represent the degrees of node i and node j.

3. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 2, characterized in that: During the operation of the train, various operation data of each train node are taken as data blocks, and the data blocks are organized into a data block sequence; a Merkle tree is constructed for the data block sequence to obtain a hash value of a root node; Whenever train operation data is received from a train node, it is verified whether the data has been tampered with or damaged by comparing the hash value of the root node.

4. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 3, characterized in that: The entire train operation control network is divided into communities using the framework of a Merkle tree structure. The leaves of the tree structure are the ground control nodes, and the internal connections of the tree correspond to the communication connections between the ground control nodes.

5. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 4, characterized in that: The adjacency matrix of the Merkle tree structure is stored as an integer array, and pairs of rows and columns are repeatedly merged when merging corresponding communities. The calculation method of the modularity Q of the train operation control network is converted into a matrix form, which is expressed as: Among them, S represents an n*R matrix, and its i-th row and r-th column element is denoted by S ir , S ir =1 means that the i-th node belongs to the r-th community, n is the number of nodes, R is the number of communities, Tr( ) is the trace of the calculation matrix, and T is the matrix transpose symbol; the modularity matrix B reflects the deviation between the actual connection situation and the connection expectation value, which is used to determine whether the community structure in the network is significant, B ij is the element in the i-th row and j-th column of matrix B.

6. A method for dynamic partitioning and grouping of virtual reconnection of local decentralized group trains according to any one of claims 1 to 7, characterized in that: After the train operation control network is partitioned, the train nodes in the community maintain complete train-to-ground communication connection with the ground control nodes, and each train node communicates with the ground control node; alternatively, the trains in the community maintain a chain connection, and autonomously decide on the lead car through an election negotiation strategy. The lead car communicates with the ground control node, and other train nodes maintain a virtual coupling formation with the lead car through train-to-train communication and autonomously negotiate line resources.

7. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 1, characterized in that: For the symmetric structures in each community, the symmetric optimization scheduling based on group theory includes: Let G be a group that acts on a set of train nodes. When two train operation modes have symmetric characteristics under the action of group G, the optimal solution of one of the train operation modes is calculated, and the optimal solution of the other train operation mode is obtained by performing symmetry operations on the optimal solution.

8. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 7, characterized in that: The optimal solution of another train operation mode obtained by performing symmetric operation on the optimal solution is expressed as: p2=g·p1 Among them, p1 is the optimal solution of one of the train operation modes, p2 is the optimal solution of the other train operation mode, g∈G, g is an element in the group G, and the optimal solution refers to the best solution to achieve the set optimal goal under given constraints.

9. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 7 or 8, characterized in that: Also includes: The set of train operation modes is P, and the group G is used to divide the set P into different equivalence classes, expressed as: P / G = {Orb G (p)|p∈P}; Among them, P / G represents the result of dividing the set P by the group G, p is a single train operation mode in the set P, and Orb G (p) is all the locations that can be reached by the train operation mode p, Orb G (p) = {g·p|g∈G}, where g is an element of the group G, representing an operation or transformation; A scheduling calculation is performed for each equivalence class. The final scheduling scheme generates a scheduling plan for all train operation modes through symmetric operations. The optimal goal of the scheduling scheme is defined as minimizing the objective function f(p). Based on group theory, symmetric optimization scheduling is performed, and the optimal solution is expressed as: min p∈P f(p)=min p∈P / G f(p)。 10. A dynamic partitioning and grouping method for virtual reconnection of local decentralized group trains according to claim 1, characterized in that: Also includes: A multi-level coordination mechanism for the train operation control system is introduced. In the train operation control network, control systems at each level make decisions independently and maintain consistency through a collaborative mechanism to achieve local autonomy and global coordination. Among them, the ground equipment involved in the train control systems at different levels serves as the ground control nodes, and the on-board autonomous control equipment on the trains involved serves as the train nodes.

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