Method for automatic generation of a list of interlocking logic parameters based on signal type

Abstract

The application provides a signal type-based interlocking logic parameter list device automatic generation method, relates to the field of rail transit signal control technology, and comprises the following steps: obtaining a signal type configuration for an interlocking logic parameter, wherein the signal type configuration comprises a signal type and a special character; analyzing the signal type configuration to determine a processing function corresponding to the signal type and a set operation rule corresponding to the special character; and based on the processing function and the set operation rule, performing dynamic traversal and set operation on physical device nodes in a preset station yard diagram to generate a target logic device set corresponding to the interlocking logic parameter. The application realizes automatic extraction of a target logic device under complex logic correlation, and significantly improves the accuracy and efficiency of data configuration.

Description

Technical Field

[0001] This invention relates to the field of rail transit signal control technology, specifically to a method for automatically generating a list of interlocking logic parameters based on signal type. Background Technology

[0002] In rail transit interlocking systems, the interlocking logic parameter list is the fundamental data source for generating Boolean algebraic logic expressions. Its core lies in configuring the mapping relationship between logic devices and parameter variables. While the generation of logic expressions has been automated by software in existing technologies, the configuration of devices in the logic parameter list still primarily relies on manual labor. Since interlocking Boolean logic data is typically created according to interlocking control zones, different interlocking zones, although functionally similar, have different physical devices, resulting in the need to repeatedly configure devices corresponding to the same parameter variables in different lists. When the project is large-scale and the number of interlocking zones is numerous, this manual configuration method is not only extremely labor-intensive and time-consuming, but also highly susceptible to data errors due to human error, making it difficult to adapt to complex station types and changing engineering requirements. Therefore, there is an urgent need for a technical solution that can automatically adapt to the characteristics of each interlocking zone and station type, and efficiently and accurately generate interlocking logic parameter lists. Summary of the Invention

[0003] To address the problems of low efficiency and error-proneness in manual configuration of interlocking logic parameter list devices in existing technologies, this application proposes an automatic generation method for interlocking logic parameter list devices based on signal type, which enables automated and accurate extraction and configuration of logic devices.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A method for automatically generating a list of interlocking logic parameters based on signal types includes: obtaining a signal type configuration for the interlocking logic parameters, the signal type configuration including signal types and special characters; parsing the signal type configuration to determine the processing function corresponding to the signal type and the set operation rule corresponding to the special characters; and, in a preset site map, dynamically traversing and performing set operations on physical device nodes based on the processing function and the set operation rule to generate a set of target logic devices corresponding to the interlocking logic parameters.

[0005] Preferably, the special characters include at least one of set union identifier, set difference identifier, and spatial range constraint identifier; the signal type configuration also includes a combined signal type formed by connecting multiple signal types with underscores; the combined signal type is used to indicate that the set of device nodes selected in the preceding order is used as the input candidate set of device nodes for subsequent order selection; the set union identifier is used to indicate that a merging operation is performed on multiple selected set of device nodes; the set difference identifier is used to indicate that device nodes that meet specific conditions are removed from the basic set of device nodes; the spatial range constraint identifier is used to indicate that the physical area range of device node selection is limited.

[0006] Preferably, when the signal type configuration includes the combined signal type, in the preset station map, based on the processing function and the set operation rules, the physical device nodes are dynamically traversed and subjected to set operations, including: performing an initial traversal and filtering in the station map according to the signal type preceding the combined signal type or the special character to obtain a first set of device nodes; using the first set of device nodes as the input candidate device set for the signal type following the combined signal type; and performing a second traversal and filtering in the input candidate device set based on the processing function corresponding to the subsequent signal type to obtain a second set of device nodes.

[0007] Preferably, the set union identifier is a comma, the set difference identifier is an exclamation mark, and the spatial range constraint identifier is a dollar sign; when parsing the signal type configuration, the signal type and the corresponding set operation rules are segmented and determined by identifying the set union identifier, the set difference identifier, and the spatial range constraint identifier.

[0008] Preferably, the signal type configuration further includes a signal type modifier, which is used to further filter the previously selected set of device nodes based on physical attributes or device orientation. When the signal type configuration includes the set difference identifier and the signal type modifier, the set operation rules include: filtering a third set of device nodes with specific physical attributes or device orientation from the initial candidate set based on the signal type modifier; removing the third set of device nodes from the initial set of device nodes corresponding to the signal type to obtain an updated set of device nodes.

[0009] Preferably, when the interlocking logic parameter list contains multiple device data columns, the signal type configuration includes a group identifier; parsing the signal type configuration includes: dividing the signal type configuration into multiple sub-signal type configurations using the group identifier; generating a target logic device set corresponding to the interlocking logic parameters includes: performing dynamic traversal and set operations corresponding to each sub-signal type configuration respectively, and mapping the resulting device node set to the corresponding device data column in the interlocking logic parameter list; when the sub-signal type configuration is empty, no device node is generated for the corresponding device data column.

[0010] Preferably, the method further includes: obtaining a preset general template for an interlocking logic parameter list, the general template for the interlocking logic parameter list including a signal type column and a logic parameter variable column; in response to detecting that the signal type configuration contains a skip flag, skipping the parsing of the signal type configuration in the current data unit, and retaining the pre-configured device data in the current data unit; generating basic configuration data based on the general template for the interlocking logic parameter list and the functional requirements of the current interlocking area, and performing the parsing of the signal type configuration and the generation of device data based on the basic configuration data.

[0011] Furthermore, the present invention also provides an automatic device for generating a list of interlocking logic parameters based on signal types, comprising: a configuration acquisition module for acquiring signal type configurations for interlocking logic parameters, the signal type configurations including signal types and special characters; a parsing and execution module for parsing the signal type configurations, determining the processing function corresponding to the signal type, and the set operation rules corresponding to the special characters; dynamically traversing and performing set operations on physical device nodes based on the processing function and the set operation rules in a preset site map; and a device set generation module for generating a set of target logical devices corresponding to the interlocking logic parameters.

[0012] In addition, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0013] In addition, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0014] Beneficial effects: This invention transforms traditional static text matching into a dynamic equipment extraction process based on station map topology by constructing a signal type configuration that includes signal types and special characters. Utilizing set operation rules defined by special characters, complex logical operations such as cascading filtering, union set merging, difference set elimination, and spatial constraints can be implemented at the physical equipment node level, thereby accurately adapting to the differentiated needs of different interlocking zones and station types. This method not only eliminates a large amount of repetitive manual configuration work, significantly improving data generation efficiency, but also fundamentally avoids human error through a programmatic topology traversal mechanism, ensuring the accuracy and consistency of the interlocking logic parameter list data. Simultaneously, by combining a general template and a skip flag mechanism, it balances the flexibility of standardized automatic generation with personalized manual intervention, effectively reducing the implementation cost and maintenance difficulty of new projects. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for automatically generating a list of interlocking logic parameters based on signal type, according to an embodiment of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0018] Example 1 like Figure 1 As shown, this embodiment provides a method for automatically generating a list of interlocking logic parameters based on signal type. This method transforms business-level equipment requirements into executable topology traversal instructions, automatically extracting target equipment from the station map data model, thereby replacing the traditional manual search and configuration method. The method mainly includes the following steps: Step S1: Obtain the signal type configuration for the interlocking logic parameters. The signal type configuration includes the signal type and special characters.

[0019] Specifically, signal type configuration is a set of structured instructions used to drive station map traversal. In the data engineering of interlocking systems, different logical parameter variables need to be associated with physical devices having specific topological or functional attributes. To accurately express this complex association requirement, this invention defines signal type as an abstract identifier for basic filtering conditions. For example, LXH represents train signal equipment, and JFJL represents a set of equipment related to train routes. Simultaneously, to address complex scenarios where a single filtering condition cannot satisfy all needs, special characters are introduced as topology combination operators to define the logical operation relationships between equipment sets. Therefore, the obtained signal type configuration is essentially an encoded description of the distribution pattern and topological relationships of target equipment in the station map. This configuration method decouples specific business requirements from the underlying graph data structure, enabling the same set of configuration rules to adapt to the physical equipment layout of different station types and interlocking zones, providing a standardized input interface for subsequent automated processing.

[0020] Step S2: parse the signal type configuration, determine the processing function corresponding to the signal type, and the set operation rules corresponding to special characters.

[0021] Specifically, the parsing process transforms abstract configuration instructions into computer-executable graph operation semantics, rather than simple text segmentation or character matching. The system has a pre-built mapping library between signal types and graph traversal algorithms. When a specific signal type is identified, it is bound to the corresponding processing function. This processing function encapsulates the topology traversal logic for searching for specific types of nodes in the station graph. See the table below for details: For example, when parsing LXH, the FilterLXH function is called, which filters all train signal nodes in the graph data based on node attribute labels. Simultaneously, special characters in the configuration are parsed into set operation rules, such as union, difference, or spatial constraints—topological operators. This parsing step constructs a complete execution context, ensuring that subsequent device generation is no longer a static data query, but a series of ordered operations performed on the graph model based on dynamically constructed computational logic. In this way, even with extremely complex combined configurations, the system can accurately decompose them into atomic sequences of graph operations, guaranteeing the rigor and scalability of the logical execution.

[0022] Step S3: In the preset site map, based on the processing function and set operation rules, the physical device nodes are dynamically traversed and set operations are performed to generate a set of target logical devices corresponding to the interlocking logic parameters.

[0023] Specifically, the station map is modeled internally by the computer as a graph data structure containing nodes and edges. Nodes represent physical equipment entities such as signals, switches, and sections, while edges represent track connections, electrical insulation, or logical interlocking relationships between equipment. During the generation operation, the system, based on the processing function determined in step S2, initiates a graph traversal from a specified starting node or globally, searching for physical equipment nodes that meet the conditions in real time along the topological connections. During this process, set operation rules directly apply to the traversed set of node objects. For example, when encountering a union rule, the system merges the node sets returned by multiple traversal branches; when encountering a difference rule, it removes a subset of nodes that satisfy specific topological characteristics from the base result set. This dynamic traversal and operation mechanism based on graph data ensures that the generated equipment set strictly follows the actual physical topology of the station, avoiding logical loopholes caused by human memory bias or text matching errors. The final output target logical equipment set is an ordered list composed of real physical equipment node objects, which can be directly used for the automatic generation of subsequent interlocking Boolean expressions. It should be understood that although this embodiment uses a rail transit interlocking station diagram as an example for illustration, in other embodiments, this method is equally applicable to any industrial control system equipment configuration scenario with complex topological connections, as long as its underlying data can be abstracted into a graph model and there are definite logical relationships between the devices. Through the above technical solution, the present invention achieves automated and precise mapping from configuration commands to physical device sets, significantly improving the efficiency and accuracy of interlocking data configuration.

[0024] Example 2 In some embodiments, special characters include at least one of a set union identifier, a set difference identifier, and a spatial range constraint identifier. The signal type configuration also includes a combined signal type formed by connecting multiple signal types with underscores. The combined signal type is used to indicate that the set of device nodes selected in a previous process is used as the input candidate set of device nodes for subsequent processes. The set union identifier is used to indicate that a merging operation is performed on multiple selected sets of device nodes. The set difference identifier is used to indicate that device nodes that meet specific conditions are removed from the basic set of device nodes. The spatial range constraint identifier is used to indicate that the physical area range for device node selection is limited.

[0025] Specifically, the combined signal type is not a simple text concatenation, but rather a cascading filtering pipeline with contextual dependencies. During the topological traversal of the station map, the underline acts as a cascading identifier, its technical significance lying in altering the scope of the graph search. When the system parses a combined signal type connected by an underline, it does not perform parallel or independent searches for each signal type across the global station map, but strictly follows a left-to-right execution sequence. First, based on the leftmost preceding signal type or special character in the combined signal type, an initial traversal and filtering is performed in the preset station map to obtain the first set of equipment nodes. Subsequently, this first set of equipment nodes is directly used as the input candidate set for subsequent signal types in the combined signal type. Finally, within the subgraph defined by this input candidate set, a second traversal and filtering is performed based on the processing function corresponding to the subsequent signal type to obtain the second set of equipment nodes. For example, when configured as JFJL_SXH, the system first calls the FilterJFJL function to obtain all equipment nodes related to the train route to form a candidate set, and then only calls the FilterSXH function within this candidate set to filter the starting signal. This cascading mechanism allows subsequent filtering to utilize the topological context established by preceding filtering, avoiding repeated retrieval of irrelevant nodes in the full dataset. This ensures the accuracy of complex relationship extraction while significantly improving the computational efficiency of graph traversal.

[0026] Furthermore, to address diverse business needs that cannot be covered by a single filtering condition, this invention defines various set operation identifiers to support flexible topology calculations. Among these, the set union identifier can be represented by a comma in the specific implementation. When a comma is included in the configuration, the parser recognizes it as a union operation instruction, instructing the system to merge the sets of device nodes obtained from multiple independent filtering branches separated by commas. For example, configuring JFJL_SXH and DCJL_SXH indicates obtaining the train route starting signal and the shunting route starting signal respectively, and merging them into a unified device list. This mechanism allows the aggregation of devices from multiple sources within a single configuration unit, satisfying the configuration requirement of normalizing multi-source devices in the interlocking parameter list.

[0027] In practical implementations, the set difference identifier can be represented by an exclamation mark. This identifier is used to express exclusion logic, that is, to remove a subset that meets specific conditions from the acquired set of basic equipment. Unlike conventional filtering, the set difference operation must be based on a basic set. For example, in the scenario of configuring LXH(!YDJL_SXH), the system first obtains all train signals as the basic set, then identifies YDJL_SXH after the exclamation mark as the exclusion condition, and removes the signal node belonging to the beginning of the guiding route from the basic set. This filtering method based on set subtraction solves the problem of difficulty in accurately describing target equipment through forward enumeration in complex station types, enabling configuration personnel to quickly identify all target equipment except for specific exceptions by performing subtraction.

[0028] Spatial range constraints can be represented using dollar signs in the implementation. In the default interlocking data processing logic, to ensure data security and isolation, device filtering is typically limited to the physical boundaries of the current interlocking zone. However, some cross-site services or neighboring station interface logic require referencing device data from adjacent interlocking zones. When the parser recognizes a dollar sign at the front end of the signal type configuration, it dynamically adjusts the boundary constraints of the graph traversal, removing the default interlocking zone filtering rules and allowing the search range to extend to neighboring station areas. For example, configuring $OLROUTE_DC indicates retrieving protective route turnout equipment including both the current station and neighboring stations. This feature, through explicit spatial constraint identification, provides necessary flexibility while ensuring the default safety strategy, avoiding the lack of cross-site logic configuration due to hard-coded boundaries.

[0029] When parsing signal type configurations, the system identifies the aforementioned set union identifier, set difference identifier, and spatial range constraint identifier to segment and determine the original configuration string into independent signal type fragments and their corresponding set operation rules. This parsing process essentially compiles the text-based configuration into a structured sequence of graph operation instructions. It should be understood that although this embodiment lists commas, exclamation marks, dollar signs, and underscores as specific identifier implementations, other characters or character combinations with clear distinguishability can be used in other embodiments to carry the same semantic function, as long as they can be uniquely identified and mapped to the corresponding topology operation logic during the parsing phase. Through the collaborative work of the aforementioned combined signal types and various set operation identifiers, this invention constructs a complete system of topology device extraction expressions, enabling complex station equipment relationships to be concisely and accurately encoded and automatically executed.

[0030] Example 3 In some embodiments, the signal type configuration also includes a signal type modifier, which is used to further filter the previously selected set of device nodes based on physical attributes or device orientation. Specifically, the signal type modifier is not an independent device lookup instruction, but rather an attribute filter attached to the basic signal type. In the data model of the site map, each physical device node, in addition to its type label, carries rich physical attribute metadata, such as the device's geographical orientation, its throat area, insulation joint location, or specific functional type. The signal type modifier operates on these underlying physical attributes or topological orientation fields, not the device name string itself. When the system parses the modifier, it maps it to conditional judgment logic for the node attribute fields. This design directly anchors the directional or attribute constraints at the business level to the inherent characteristics of physical entities, ensuring that the filtering results strictly conform to the actual physical layout of the site and avoiding matching failures caused by non-standard manual naming.

[0031] When the signal type configuration includes a set difference identifier and a signal type modifier, the set operation rules include: filtering a set of third device nodes with specific physical attributes or device orientations from the initial candidate device set based on the signal type modifier; removing the third device node set from the initial device node set corresponding to the signal type to obtain an updated device node set. This process embodies a refined reverse exclusion mechanism. Unlike the cascade filtering described in Example 2, which approaches the target by gradually narrowing the search range, the difference modification in this example first determines an abnormal subset to be excluded and then removes it from the full or basic set. In terms of execution logic, the system first performs a graph traversal or attribute filtering independently in the current context based on the attribute conditions defined by the modifier to generate a set of third device nodes to be excluded. Subsequently, the system uses the initial device node set generated by the basic signal type as the minuend and the third device node set as the subtrahend to perform a set subtraction operation. This two-step execution strategy ensures the atomicity and accuracy of the removal operation. Even if the device pointed to by the modifier does not exist in the basic set, it will not affect the integrity of the basic set, thereby enhancing the robustness of the system.

[0032] To illustrate the above mechanism more clearly, a specific interlocking business scenario will be used for explanation below. In the configuration scenario of train signal equipment, it is usually necessary to obtain all train signals, but those starting signals used only for guiding routes must be excluded because these signals have special characteristics in interlocking logic processing. In this case, the configuration personnel can use a combination configuration including a set difference identifier and a signal type modifier. The system first obtains all train signal nodes in the entire station as the initial device node set based on the basic train signal type. Next, the system identifies the modifier combination after the set difference identifier, which defines the specific topological role of the starting point of the guiding route. Based on this, the system filters out all signal nodes with the starting point attribute of the guiding route from the candidate range, forming a third device node set. Finally, the system removes these guiding signals from the initial train signal set, and the final output target set is a clean list of ordinary train signals.

[0033] In another scenario involving equipment direction, when it is necessary to obtain the starting signal of a shunting route and it is limited to the uphill direction, the signal type modifier is used to specify the uphill physical direction attribute. After performing the basic screening of the starting signal of the shunting route, the system uses the direction judgment function corresponding to the modifier to perform a secondary filter on the result set, retaining only the equipment marked as uphill in the node attributes. It should be understood that although the above examples demonstrate the independent application of difference set elimination and attribute screening, in actual configuration, the two can also be nested or combined. For example, uphill equipment can be filtered out first by the direction modifier, and then specific types of equipment can be eliminated by the difference set identifier. This flexible combination capability allows the present invention to cover extremely complex station equipment extraction requirements with a very simple configuration syntax, avoiding the need to define a new signal type for each special screening combination, effectively controlling the expansion rate of the signal type library, and improving the maintainability and scalability of the entire interlocking data generation system.

[0034] Example 4 In some embodiments, when the interlocking logic parameter list contains multiple device data columns, the signal type configuration includes a group identifier. This feature primarily addresses the need for automated generation of complex tabular data structures in interlocking systems. In practical engineering applications, the interlocking logic parameter list is not always a single device list; many key parameter tables employ multi-dimensional data structures, meaning that multiple dimensions of device information, such as master devices, associated sections, and control buttons, need to be configured simultaneously in the same row. To adapt to this multi-dimensional tabular structure, this invention introduces a group identifier as a column separator at the configuration level. In specific implementations, the group identifier can be represented by a semicolon, but it should be understood that in other embodiments, a vertical bar or other symbols with clear separating semantics can also be used, as long as they can be uniquely identified during the parsing stage. The presence of the group identifier logically divides the originally linear signal type configuration string into multiple parallel processing channels, each corresponding to a specific data column in the table, thereby achieving a structured mapping from one-dimensional configuration instructions to two-dimensional tabular data.

[0035] The process of parsing signal type configurations specifically involves dividing the signal type configuration into multiple sub-signal type configurations using grouping identifiers. Specifically, when the system reads a configuration unit containing a grouping identifier, it first segments the original configuration string into several independent substrings based on the position index of that identifier. Each substring constitutes a sub-signal type configuration, and they are syntactically identical to the complete signal type configurations described in Examples 1 to 3. They can independently contain any legal combination of signal type, concatenation identifier, union identifier, difference identifier, or spatial range constraint identifier. This design means that grouping operations are performed at the highest priority level, defining the macroscopic skeleton of data generation, while each sub-configuration retains all the microscopic-level topology filtering and computational capabilities. Through this hierarchical parsing mechanism, the system can decouple the complex multi-column generation task into multiple standard single-column generation subtasks, simplifying the implementation complexity of the core algorithm while ensuring the isolation and independence between the generation logics of each column.

[0036] The process of generating the target logical device set corresponding to the interlocking logic parameters specifically includes performing dynamic traversal and set operations corresponding to each sub-signal type configuration, and mapping the resulting device node set to the corresponding device data column in the interlocking logic parameter list. During the execution phase, the system calls the graph traversal engine described in Example 1 sequentially or in parallel according to the order of the sub-configurations. For each sub-signal type configuration, the engine independently performs node search and set operations in the preset station map to generate a dedicated device node set. Subsequently, the system accurately writes the generated device node set into the corresponding device data column in the interlocking logic parameter list based on the sub-configuration's index number. For example, the device set generated by the first sub-configuration is filled into the first device column, the device set generated by the second sub-configuration is filled into the second device column, and so on. This strict mapping mechanism based on position indexes ensures that the automatically generated data can accurately fall into the predefined table structure, maintaining the format standardization and semantic correctness of the interlocking data file.

[0037] Specifically, when a sub-signal type configuration is empty, no device node is generated in the corresponding device data column. In multidimensional table configuration scenarios, not every column needs to generate devices automatically. Some columns may need to retain manually pre-configured special data, or may not need to be filled at all under the current interlocking zone function. When the parser detects that there are no valid characters between two adjacent group identifiers, or that the group identifier is at the beginning or end of the configuration string and there are no characters adjacent to it, it will identify that position as an empty sub-signal type configuration. At this time, the system will not report an error or attempt to fill in the default value, but will explicitly skip the automatic generation operation for that column, keeping the original state of the cell content or an empty value. For example, if the configuration content is A;;B, where A and B are valid signal type configurations separated by two consecutive semicolons, the system will generate three sub-configurations, with the second sub-configuration being empty. The execution result is that the first column is filled with the device corresponding to A, the third column is filled with the device corresponding to B, and the second column is not automatically written. This explicit white space mechanism gives configuration personnel great flexibility, allowing the same set of automatically generated rules to handle fully automated scenarios as well as seamlessly compatible with hybrid configuration modes involving human-machine collaboration, effectively avoiding the risk of human-specific configurations being accidentally overwritten due to excessive automation.

[0038] To more clearly illustrate the technical solution of this embodiment, a specific scenario of generating a cross-station turnout parameter table is used as an example. Assume that an interlocking logic parameter table contains two columns of equipment data: local turnouts and neighboring turnouts. The configuration personnel can enter $OLROUTE_DC;KZQD_DC in the signal type configuration cell. In this configuration, the semicolon acts as a grouping identifier, dividing the entire string into two sub-signal type configurations. The first sub-configuration, $OLROUTE_DC, contains a spatial range constraint identifier, instructing the system to remove interlocking zone boundary restrictions when traversing protected route turnouts, obtain all turnout equipment including those from neighboring stations, and map the results to the first column. However, since business requirements only require displaying local turnouts in the first column, this is only to demonstrate the syntax of spatial constraints; in actual applications, it can be used in conjunction with a difference set identifier to exclude neighboring station equipment. The second sub-configuration, KZQD_DC, is specifically used to obtain turnout equipment related to cross-station sections and map it to the second column.

[0039] Example 5 In some embodiments, to balance the efficiency of automated generation with the specific needs of the engineering site, the present invention also provides a mechanism for manual intervention compatibility and template reuse. Specifically, the method further includes obtaining a preset general template for the interlocking logic parameter list, which includes a signal type column and a logic parameter variable column. Simultaneously, in response to detecting a skip flag in the signal type configuration, the parsing of the signal type configuration in the current data unit is skipped, and the pre-configured device data in the current data unit is retained. Furthermore, based on the general template for the interlocking logic parameter list and the functional requirements of the current interlocking area, basic configuration data is generated, and the parsing of the signal type configuration and the generation of device data are performed based on the basic configuration data.

[0040] Specifically, the skip flag acts as a circuit breaker and safety valve in the parsing process. In a fully automated equipment generation process, although most logical devices can be automatically obtained through signal type configuration in the site diagram, in actual engineering implementation, there will always be a small number of special cases that cannot be described by general topology rules, or specific data that has been manually entered by configuration personnel based on on-site debugging experience. If automated parsing is forced, these valuable manual configurations will be overwritten. To solve this problem, this invention defines a skip flag. When the parsing engine reads the signal type configuration of a data unit, if it recognizes the presence of this flag, it will immediately terminate all subsequent graph traversal and set operation steps for that unit, no longer attempting to map it to a processing function, but directly retaining the existing text content in the current cell as the final result. For example, in a specific implementation, the skip flag can be represented by an asterisk or other agreed-upon special symbols. This mechanism allows the same parameter list to contain both standardized equipment data automatically generated by the system and personalized data carefully configured by humans, achieving a seamless integration of machine intelligence and expert experience, and greatly improving the system's adaptability in complex non-standard scenarios.

[0041] The general template for interlocking logic parameter lists is essentially a standardized carrier that decouples interlocking control logic from specific physical equipment. Due to the high functional similarity of rail transit interlocking systems, although the physical equipment layouts differ between stations or interlocking zones, the underlying logical structures for route control, signal opening, and section locking are essentially the same. The general template extracts this unchanging logical structure, retaining only the signal type column and the logic parameter variable column, while removing specific equipment name data. When a new interlocking zone data configuration task is initiated, the system first loads the general template matching the station type and instantiates it according to the actual functional requirements of the current interlocking zone, generating basic configuration data containing complete signal type configurations. This basic configuration data forms the baseline skeleton for subsequent automated generation. Based on this, the system then calls the parsing and traversal mechanism described in the aforementioned embodiments to generate the actual physical equipment nodes in the current station map. In this way, configuration personnel do not need to write complex signal type combinations line by line from scratch; they can complete most of the work by reusing mature templates and making a few targeted adjustments. This not only improves data configuration efficiency several times over, but more importantly, it inherits proven standard logic, reducing the risk of logical errors introduced by human reconfiguration from the source, and ensuring the consistency and reliability of interlocking data quality between different projects.

[0042] Example 6 This embodiment provides an automatic device for generating a list of interlocking logic parameters based on signal types. This device is a specific architectural implementation of the methods described in embodiments 1 to 5 at the software product level, aiming to solidify abstract method processes into reusable and maintainable engineering components through modular structural design. The device mainly includes a configuration acquisition module, a parsing and execution module, and a device set generation module.

[0043] The configuration acquisition module is used to obtain signal type configurations for interlocking logic parameters. These configurations include signal types and special characters. Specifically, as the data input interface for the entire device, its responsibilities extend beyond reading text files; it also includes preprocessing and validating the raw configuration data. In actual engineering deployments, this module can interface with graphical configuration interfaces, Excel parameter tables, or database storage systems, uniformly converting user-entered device extraction requirements in different formats into a standardized internal data structure. For example, when importing a CSV file containing thousands of configuration lines from an external source, the configuration acquisition module scans the signal type column line by line, removing blank and comment lines, and encapsulates valid configuration strings into a task queue to be processed before passing them to downstream modules. This design decouples the data source format from the core processing logic, enabling the device to flexibly adapt to different project data delivery specifications without modifying the core algorithm code.

[0044] The parsing and execution module parses signal type configurations, determines the corresponding processing functions for each signal type, and identifies set operation rules for special characters. Based on the pre-defined site map, it dynamically traverses and performs set operations on physical device nodes according to the processing functions and set operation rules. Specifically, this module is the core computing engine of the device. Internally, it is not a simple serial processing pipeline, but a tightly coupled runtime environment integrating syntax analysis and graph traversal execution. Upon receiving the standardized configuration from the configuration acquisition module, the parsing and execution module first identifies the signal type identifier and topology combination operator using its built-in lexical analyzer and immediately binds them to the pre-defined processing function library and set operation operator library. Subsequently, the graph traversal engine within the module, based on the execution plan generated by parsing, directly initiates node searches and set operations on the site map data model loaded in memory. For example, when parsing a combination configuration containing cascading identifiers, the execution engine automatically constructs a context pipeline, directly injecting the node set obtained from the preceding filtering into the input parameters of the subsequent filtering function. The entire process requires no intermediate result serialization or deserialization overhead. This integrated parsing and execution architecture ensures that complex topology operation logic can be executed efficiently and atomically, avoiding performance bottlenecks and state inconsistencies caused by frequent data exchanges between modules.

[0045] The device set generation module generates the target logical device set corresponding to the interlocking logic parameters. Specifically, this module is responsible for converting the memory-level node objects output by the parsing and execution module into a final delivery format that conforms to the interlocking data specification. After traversal and computation, the device set generation module performs deduplication, sorting, and attribute extraction operations on the physical device nodes in the result set, and fills the device name, number, or associated attributes into the specified data columns according to the target structure requirements of the interlocking logic parameter list. For example, when processing multi-column grouped configurations, this module accurately maps the device sets generated by different subtasks to the corresponding output fields based on the mapping relationship established by the group identifier, while correctly handling the blanking logic of empty configuration columns. In addition, this module is also responsible for exception capture and logging. When a configuration unit fails to generate due to missing site map data or syntax errors, it can generate detailed diagnostic information without interrupting the overall batch processing flow, thereby ensuring the robustness and observability of the device in large-scale engineering applications.

[0046] Through the aforementioned modular architecture, this invention encapsulates the signal type-based automatic device generation method into an independent software device. The modules collaborate through clearly defined data interfaces, ensuring both the encapsulation and security of the core topology traversal logic and providing sufficient external scalability to adapt to diverse engineering integration needs. It should be understood that although this embodiment describes three main functional modules, in actual software development, these modules can be further broken down into finer-grained microservice components or merged into a single high-performance processing unit. As long as their overall functionality covers the complete technical chain of configuration acquisition, parsing and execution, and result generation, they fall within the protection scope of this invention.

[0047] Example 7 This embodiment provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described in any of the above embodiments. Specifically, this electronic device is a physical entity that carries and runs the aforementioned automatic generation method for interlocking logic parameter list devices. In practical engineering applications, the specific form of this electronic device is not limited. It can be a rack-mounted server or workstation deployed in a data center or computer room, a laptop, tablet, or dedicated handheld debugging terminal used by engineers on-site, or even an industrial control computer or embedded computing board embedded inside an interlocking cabinet. The memory can include high-speed random access memory and non-volatile memory, such as one or more disk storage devices, flash memory devices, or other solid-state storage devices, for persistently storing program instructions for implementing the method of this invention, as well as intermediate or result data such as station map data and signal type configuration libraries. The processor can be a general-purpose central processing unit, network processor, digital signal processor, or application-specific integrated circuit. It communicates with the memory through a system bus, reads and interprets the computer program instruction sequence stored therein, thereby driving hardware resources to complete the dynamic traversal and set operation of the station map. Through this hardware and software combined architecture, the present invention transforms abstract data processing logic into concrete machine behavior, making the technical solution have clear industrial applicability and manufacturability.

[0048] This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the methods described in any of the above embodiments. Specifically, a computer-readable storage medium is another product form that exists independently of a specific hardware carrier. This medium can be a tangible, non-transitory storage medium, including but not limited to read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, magnetic storage media such as floppy disks or hard disks, optical storage media such as CD-ROMs or DVDs, and various semiconductor storage chips such as USB flash drives or SD cards. It should be understood that although this embodiment lists various specific media types, this is merely an exemplary description for full disclosure and is not a limitation on the scope of protection of this invention. Any medium capable of storing data electronically, magnetically, optically, electromagnetically, infraredly, or semiconductorally, and capable of being read by a computer system to execute corresponding instructions, falls within the scope of this invention. Furthermore, the computer program stored on the medium is a collection of instruction code, which can take various forms such as source code, object code, assembly code, or machine code, and can also be compiled, linked, or encrypted, as long as it can substantially reproduce the method flow described in this invention when executed. By embedding the method in a storage medium, this invention enables convenient distribution, backup, and version management of the technical solution. It also provides direct legal protection for the circulation of software products, further improving the comprehensive and multi-dimensional protection layout from method to device to product.

[0049] Example 8 This embodiment provides a comprehensive application scenario for the automatic generation of interlocking zone logic parameter lists. It aims to fully demonstrate, through a real-world rail transit signaling engineering case, the collaborative operation of the various technical features described in the aforementioned embodiments in a practical production environment, and to verify the significant advantages of this invention in efficiency and accuracy compared to traditional manual configuration methods. It should be understood that the following examples are merely illustrative and not intended to limit the scope of this invention. In actual engineering projects, configuration personnel can flexibly combine various signal types and topology combination operators according to specific station types and interlocking functional requirements.

[0050] In the first typical application scenario, addressing the need for automatic generation of train route starting signal equipment, the system demonstrates a collaborative working mechanism of combined signal types and set union identifiers. In traditional interlocking data configuration, train route starting signals, shunting route starting signals, and virtual signals are often scattered across different logical contexts. Manual configuration requires consulting drawings and entering data one by one, which is prone to omissions or mismatches. Using the method of this invention, configuration personnel only need to input a composite configuration command consisting of cascading identifiers and union identifiers in the signal type configuration cell of the interlocking logic parameter list. Specifically, this configuration command first concatenates the train route-related equipment screening conditions with the starting signal screening conditions through the cascading identifier, instructing the system to first traverse and obtain the set of all physical equipment nodes associated with the train route in the preset station map, and then use this set as the input candidate equipment set for a second traversal, thereby accurately extracting the starting signal nodes belonging to the train route. Similarly, the system executes the cascading screening process for shunting route starting signals in parallel. Subsequently, the parser identifies the union identifier in the configuration and performs a merging operation on the device node sets obtained from the two independent filtering branches and the node set obtained directly through the virtual signal machine signal type, ultimately generating a unified target logical device set containing the three types of devices. This process transforms the complex cognitive task that originally required repeated manual comparisons and multiple searches into a standardized graph traversal and set operation sequence that can be automatically executed by a computer. This not only reduces the configuration time for a single line of data from minutes to milliseconds, but more importantly, it eliminates the risk of missing device configurations due to human distraction, ensuring the integrity of the route control logic.

[0051] In the second typical application scenario, addressing the need for refined filtering of the list of ordinary train signal controllers, excluding the starting signal of the guiding route, the system demonstrates a mechanism for the combined use of set difference identifiers and signal type modifiers. In interlocking logic design, although the starting signal of the guiding route is physically a train signal, its interlocking control logic is unique and cannot be mixed into the processing flow of ordinary train signals. If manual configuration is used, the configuration personnel must memorize the numbers of all guiding signals in the entire station and manually avoid them, a task that is almost impossible to complete accurately in large hub stations. When applying this invention, the configuration personnel first specify the basic train signal type in the signal type configuration to obtain the full candidate set, and then configure the set difference identifier and subsequent combination of modifiers for the starting signal of the guiding route. During execution, the system first iterates through the station map based on the basic signal type to obtain an initial set of equipment nodes. Next, based on the topological role attributes defined by modifiers, it dynamically filters out all third-party equipment nodes with the guiding route start attribute from the candidate range. Finally, it strictly performs set subtraction to remove the third-party equipment node sets from the initial set, outputting a clean list of ordinary train signals. This reverse exclusion mechanism based on physical attributes and topological relationships gives the configuration rules adaptive capabilities. Even if new guiding signals are added during station renovations, as long as their node attributes are correctly labeled, the system can automatically include them in the exclusion range without manual configuration modification, fundamentally ensuring the security and timeliness of interlocking data.

[0052] In the third typical application scenario, addressing the multi-dimensional data generation requirements of cross-station turnout parameter tables, the system demonstrated its comprehensive application capabilities of spatial range constraint identifiers, multi-column grouping identifiers, and skip identifiers. Cross-station interlocking logic typically requires referencing turnout equipment from both the local and neighboring stations simultaneously, and the parameter table structure often includes multiple dimensions such as local turnout columns, neighboring station turnout columns, and related button columns. In this case, the configuration personnel entered a three-segment composite configuration separated by grouping identifiers within the same cell. The first segment of the configuration pre-sets the spatial range constraint identifier, instructing the system to remove the default interlocking zone boundary filtering rules when traversing protected route turnouts, allowing the search range to extend to the neighboring station area, thereby obtaining a complete set of turnout equipment including both the local and neighboring stations, and mapping the result to the first data column of the parameter table. The second segment of the configuration is specifically used to obtain the turnout equipment related to the cross-station section and accurately fills the second data column through the mapping relationship established by the grouping identifiers. The third segment of the configuration uses a skip identifier, instructing the system not to perform any automatic parsing and generation operations on this column, fully preserving the special button data manually entered by the configuration personnel based on on-site debugging experience. Through this compact configuration command, the system simultaneously completes three complex tasks—cross-domain data extraction, multi-dimensional structure mapping, and human-machine collaboration compatibility—within an atomic processing flow. This not only solves the cumbersome problem of manually exporting and splicing cross-site devices separately in traditional methods, but also avoids the automatic process from erroneously overwriting expert experience through an explicit whitespace mechanism, fully demonstrating the flexibility and robustness of this invention in dealing with complex engineering scenarios.

[0053] In summary, through the above comprehensive application scenarios, it can be seen that this invention constructs a complete system of device extraction expressions by combining discrete signal types and topology operators, and achieves dynamic execution within the station map data model. Compared to the static configuration methods in existing technologies that rely on manual memory and text matching, this invention, through a programmatic graph traversal and set operation mechanism, deeply binds business logic with physical topology. This not only significantly improves the efficiency of generating interlocking logic parameter lists but also ensures the accuracy and consistency of device relationships at the underlying data structure level, providing a reliable data foundation for the subsequent automatic generation of interlocking Boolean expressions.

[0054] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for automatically generating a list of interlocking logic parameters for a device based on signal type, characterized in that, include: Obtain the signal type configuration for the interlocking logic parameters, wherein the signal type configuration includes the signal type and special characters; The signal type configuration is parsed to determine the processing function corresponding to the signal type and the set operation rules corresponding to the special characters; In the preset site map, based on the processing function and the set operation rules, the physical device nodes are dynamically traversed and set operations are performed to generate a target logical device set corresponding to the interlocking logic parameters.

2. The method for automatically generating a list of interlocking logic parameters based on signal type according to claim 1, characterized in that, The special characters include at least one of set union identifier, set difference identifier, and spatial range constraint identifier; the signal type configuration also includes a combined signal type formed by connecting multiple signal types with underscores; The combined signal type is used to indicate that the set of device nodes selected in the previous step is used as the set of input candidate devices for the subsequent step. The set union identifier is used to indicate that a merge operation is performed on multiple selected sets of device nodes; The set difference identifier is used to indicate the removal of device nodes that meet specific conditions from the set of basic device nodes; The spatial range constraint identifier is used to indicate the physical area range that limits the selection of device nodes.

3. The method for automatically generating a list of interlocking logic parameters based on signal type according to claim 2, characterized in that, When the signal type configuration includes the combined signal type, in the preset site map, based on the processing function and the set operation rules, dynamic traversal and set operations are performed on the physical device nodes, including: Based on the signal type or special character preceding the combined signal type, the first traversal and filtering is performed on the station map to obtain the first set of equipment nodes; The first set of device nodes is used as the input candidate device set for the signal type following the combined signal type; In the set of input candidate devices, a second traversal and filtering is performed based on the processing function corresponding to the subsequent signal type to obtain a second set of device nodes.

4. The method for automatically generating a list of interlocking logic parameters based on signal type according to claim 3, characterized in that, The union of sets is identified by a comma, the difference of sets is identified by an exclamation mark, and the spatial range constraint is identified by a dollar sign; When parsing the signal type configuration, the signal type and the corresponding set operation rules are segmented and determined by identifying the set union identifier, the set difference identifier, and the spatial range constraint identifier.

5. The method for automatically generating a list of interlocking logic parameters based on signal type according to claim 2, characterized in that, The signal type configuration also includes a signal type modifier, which is used to further filter the previously selected set of device nodes by physical attributes or device orientation. When the signal type configuration includes the set difference identifier and the signal type modifier, the set operation rules include: Based on the signal type modifier, a third set of device nodes with specific physical attributes or device orientations is selected from the initial candidate device set; The third set of device nodes is removed from the initial set of device nodes corresponding to the signal type to obtain the updated set of device nodes.

6. The method for automatically generating a list of interlocking logic parameters based on signal type according to claim 1, characterized in that, When the interlocking logic parameter list contains multiple device data columns, the signal type configuration includes a group identifier; Parsing the signal type configuration includes: dividing the signal type configuration into multiple sub-signal type configurations using the group identifier; Generating a set of target logic devices corresponding to the interlocking logic parameters includes: performing dynamic traversal and set operations corresponding to each of the sub-signal type configurations, and mapping the resulting set of device nodes to the corresponding device data column in the interlocking logic parameter list; when the sub-signal type configuration is empty, no device nodes are generated in the corresponding device data column.

7. The method for automatically generating a list of interlocking logic parameters based on signal type according to claim 1, characterized in that, The method further includes: Obtain a preset general template for the interlocking logic parameter list, which includes a signal type column and a logic parameter variable column; In response to detecting that the signal type configuration contains a skip flag, the parsing of the signal type configuration in the current data unit is skipped, and the pre-configured device data in the current data unit is retained; Based on the general template of the interlocking logic parameter list and the functional requirements of the current interlocking area, basic configuration data is generated, and based on the basic configuration data, the parsing of the signal type configuration and the generation of device data are performed.

8. An automatic device for generating interlocking logic parameter lists based on signal types, applicable to the automatic generation method for generating interlocking logic parameter lists based on signal types as described in any one of claims 1-7, characterized in that, include: The configuration acquisition module is used to acquire the signal type configuration for the interlocking logic parameters. The signal type configuration includes the signal type and special characters. The parsing and execution module is used to parse the signal type configuration, determine the processing function corresponding to the signal type, and the set operation rules corresponding to the special characters; and perform dynamic traversal and set operations on physical device nodes based on the processing function and the set operation rules in the preset station map. The device set generation module is used to generate a target logic device set corresponding to the interlocking logic parameters.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the automatic generation method for the interlocking logic parameter list device based on signal type, as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the automatic generation method for the interlocking logic parameter list device based on signal type, as described in any one of claims 1 to 7.

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