Method for transforming track plans and simulation program for transformed track plans

Abstract

The invention comprises a method for transforming a track plan (GPL) of a railway infrastructure (BI) that is stored as image information, in which the track plan (GPL) is captured and analyzed using a computer. During the analysis, symbols (SBL) in the track plan (GPL) are recognized as infrastructure elements (LET, STE) and placed in the context of the railway infrastructure (BI). As a result of the transformation, data of the recognized infrastructure elements (LET, STE) are stored, and data relating to the functional relationships applicable to these infrastructure elements (LET, STE) within the railway infrastructure (BI) are stored in such a way that the functional relationships are assigned to the respective infrastructure element (LET, STE). Furthermore, the invention comprises a computer program and a computer-readable storage medium.

Description

Technical field

[0001] The invention comprises a method for transformation. Furthermore, the invention comprises a computer program product for simulation. Furthermore, the invention comprises a computer program product containing program instructions. Furthermore, the invention comprises a computer-readable storage medium containing data. Technical background

[0002] According to current best practices, in railway signaling technology, so-called PT2 documents (PT stands for plan section; PT2 for detailed design) are created manually using engineering tools, based on the experience of software and hardware engineers. This involves a significant amount of manual data entry, making it resource-intensive and prone to errors. Furthermore, the input data for the so-called PT1 documents (PT1 for basic design) is often only available in printed form, further complicating the process of accessing this information.

[0003] Document US 2017 / 286572 A1 describes a digital twin (also known as a digital twin), its creation, and its application. Using a digital twin, a simulation program could, for example, recreate rail traffic in a simulated railway system. However, this requires digitally processed data, meaning that the workload described above cannot be eliminated; rather, it is a prerequisite for creating a digital twin.

[0004] The current state of the art, as described above, presents the problem that modernization projects for railway infrastructure can only be carried out with an exceptionally high level of effort in data creation, and a certain probability of errors in this data creation must be accepted. The high personnel costs also increase the overall cost of project implementation. Summary of the invention

[0005] The object of the invention is to solve the problems described in the prior art. In particular, it is an object to provide a method for transforming planning documents for railway infrastructures, which offers improved reliability against errors and reduces the personnel effort required for the transformation. Furthermore, it is an object of the invention to provide a computer program and a computer-readable storage medium with which the improved method can be implemented.

[0006] According to a first aspect of the invention, a method for transforming a track plan of a railway infrastructure that is available as image information is described, in which the track plan is captured and analyzed using a computer.

[0007] When the invention description refers to the computer-aided acquisition of a track plan, this means that the acquisition process makes the image information available in such a way that it can be accessed for computer-aided analysis. If, for example, the track plan is available as a paper representation, optical acquisition using an image sensor is required, whereby the image information is digitized as image data. If the image information is already available digitally, then acquiring the track plan simply involves making the image data available to a processor. This latter step must, of course, also be performed if the track plan was originally only available as a paper version. The processor in question is then able to analyze the available image data. For this purpose, a suitable analysis program is executed on the processor.

[0008] A railway infrastructure provides a system that can be used for movement by rail vehicles. Within the scope of this invention, this infrastructure consists of elements. These are divided into guidance elements and control elements. Guidance elements serve to mechanically guide the rail vehicles. These include, for example, rails and switches. These are typically represented symbolically in a track plan and can therefore be identified through analysis. Control elements serve to influence the railway infrastructure and the rail vehicles on it. These can be mechanical, for example, switch drives, or perform signaling functions, for example, balises or interlocking systems. Control elements are also represented in track plans, preferably as symbols that can be identified through analysis of the track plan.It thus becomes clear that railway infrastructure depends on the functional relationships of the infrastructure elements involved, and there are precise rules governing how these interact. As already mentioned, these rules can be taken into account during analysis, thereby defining the context of the railway infrastructure.

[0009] A device is computer-aided or computer-implemented if it has a computing environment, or a method is computer-implemented if a computing environment performs at least one step of the method.

[0010] A computing environment is an IT infrastructure consisting of functional components such as processors, memory units, programs, and the data to be processed by these programs. This data is used to execute at least one application, which has a specific task to perform. Additional functional components can include sensors and actuators, which enable the computing environment to interact with the outside world. The IT infrastructure can also be organized as a network of these functional components.

[0011] Within a computing environment, computing instances form functional units that can be assigned to applications (defined, for example, by a number of program modules) and can execute them. During application execution, these functional units form self-contained systems, either physically (e.g., computer, processor) and / or virtually (e.g., program module).

[0012] Computers are electronic devices consisting of several functional components and possessing data processing capabilities. For example, computers can be clients, servers, handheld computers, communication devices, and other electronic devices for data processing, which may include processors and memory units and may also be interconnected via interfaces to form a network.

[0013] Processors can be, for example, converters, sensors for generating measurement signals, or electronic circuits. A processor can be a central processing unit (CPU), a microprocessor, a microcontroller, or a digital signal processor, possibly in combination with a memory unit for storing program instructions and data. The term "processor" can also refer to a virtualized processor or a soft CPU.

[0014] Storage units can be implemented on computer-readable storage devices in the form of random-access memory (RAM) or data storage devices (hard disk or data carrier).

[0015] Program modules are individual software functional units that enable a program sequence of process steps according to the invention. These software functional units can be implemented in a single computer program or in several communicating computer programs. The interfaces implemented here can be implemented in software within a single processor or in hardware if multiple processors are used.

[0016] Interfaces can be implemented using hardware, for example wired or wireless connections, or software, for example as interaction between individual program modules of one or more computer programs, and serve to exchange data, preferably in the form of digital data sets or analog signals.

[0017] To avoid misunderstandings, it should be noted that individual claim features are numbered with lowercase Latin letters, without regard to the claim numbering. This means that each letter appears only once in the entire claim set, allowing for unambiguous addressing of the relevant claim features without mentioning the claim number. Therefore, the order of the letters is irrelevant.

[0018] According to the invention, it is provided that a) During computer-aided analysis, symbols in the track plan are recognized as infrastructure elements, b) Symbols recognized during analysis are placed in the context of the railway infrastructure using computer-aided analysis, c) As a result of the transformation, data of the infrastructure elements that were recognized are stored, and for these infrastructure elements, data of these functional relationships applicable in the railway infrastructure are stored in such a way that the functional relationships are assigned to the respective infrastructure element.

[0019] In other words, the teaching according to the invention consists in the fact that the analysis goes beyond the recognition of symbols in image data, which is known per se, by placing these symbols in a knowledge-based, technically functional context. These technically functional contexts of the infrastructure elements are not inherently (or at least not solely) predetermined by the image data, i.e., they are neither represented nor defined in any way. They are preferably predefined conditions that must be met in a railway infrastructure, for example, to fulfill safety requirements for the functional safety of railway operations.

[0020] The requirements for the certification of safety-relevant applications such as railway technology are very high. According to the international standard IEC 61508, and specifically for the railway sector according to the European standard EN 50129, four Safety Integrity Levels (SILs) are distinguished for safety functions to ensure the required functional safety. Safety Integrity Level 4 represents the highest and Safety Integrity Level 1 the lowest level of safety integrity. The respective Safety Integrity Level influences the confidence interval of a measured value; the higher the Safety Integrity Level that the device must meet, the smaller the confidence interval.The dimension of functional safety for the various Safety Integrity Levels (SILs) can be clearly described by the expected frequency of a failure of the safety-relevant system, MTBF (Mean Time Between Failures), which is expressed in years (a). For SIL-1, this ranges from 10 to 100 years, for SIL-2 from 100 to 1000 years, for SIL-3 from 1000 to 10000 years, and for SIL-4 from 10000 to 100000 years.

[0021] To ensure compliance with functional safety requirements during the analysis phase, it is therefore highly advantageous to transform the image information while considering the context of the railway infrastructure. This eliminates the possibility that the transformation results in violations of these safety requirements, which would likely have arisen from an incorrect analysis of the information provided by the track plan or from a non-compliant implementation of the real railway infrastructure that served as the template for the track plan. This approach thus allows for positive influence on both the ongoing operation of the existing railway infrastructure and on planning processes, such as those for the modernization of the relevant railway infrastructure.In this context, it is also advantageous if the analysis includes the generation of an error signal, which indicates contradictions in relation to the context of the railway infrastructure that cannot be resolved by the analysis and can be output via an output device if necessary.

[0022] The terms used in this description of the invention have the following meanings. When data is mentioned, its embodiment consists in particular of one or more data sets that are in machine-readable form so that this data can be processed in a computing environment in which the method according to the invention is carried out. Infrastructure element data includes data that describe infrastructure elements of the real railway infrastructure identified during the analysis, wherein these infrastructure elements were identified in the track plan describing the railway infrastructure. Functional relationship data describes the interaction of the individual infrastructure elements. This functional relationship data serves to define a functional context for the function of the railway infrastructure as a whole.This limits the actions possible within the railway infrastructure to those that are also sensible in the actual operation of the railway infrastructure and, in particular, that meet predefined requirements for functional safety. To generate data on functional relationships, data from rules governing the function and / or interaction of infrastructure elements, as well as data on the position of infrastructure elements in the track plan, can be evaluated (more on this below).

[0023] The process results in the creation of a digital twin of the railway infrastructure. In accordance with the invention, data obtained through analysis of the track plan are combined with knowledge-based data on the functional relationships within the railway infrastructure. This advantageously results in an improved digital twin because the infrastructure elements defined by it can be more closely related to one another. These relationships enable a particularly realistic definition of the railway infrastructure, which in turn allows both control tasks and planning tasks to be performed with enhanced performance when the digital twin is taken into account.The increase in performance is reflected in reduced computing times for the simulation as well as a reduction in the number of iterations required to approximate an acceptable planning or control result.

[0024] According to a further aspect of the invention, a computer program product for simulation is described, which is designed to simulate the operational behavior of infrastructure elements of a railway infrastructure.

[0025] According to this aspect, the invention provides that the computer program product has a data interface for reading in the result generated as described above from the transformation of a track plan of the railway infrastructure, which is available as image information.

[0026] In other words, the invention provides for the simulation of the operational behavior of a railway infrastructure consisting of infrastructure elements. This operational behavior can be described by at least one functional relationship (defined in particular by the rules already mentioned) or its virtual representation. According to the invention, the simulation program product is configured to perform a simulation method according to one of the aspects of the invention and its variants outlined above.

[0027] The simulation software (hereinafter also referred to as the simulation software) may include a logic module designed to determine, based on the data of the infrastructure elements in which the topology of the railway infrastructure can be at least partially replicated, and the functional relationships (defined by the data of the functional relationships) or their virtual representation. The virtual representation of the railway infrastructure corresponds to the aforementioned data in which its functionality can be at least partially replicated. The simulation software may be designed as a digital twin of the underlying railway infrastructure. In particular, the simulation software may be designed as a digital twin in accordance with US 2017 / 286572 A1. The disclosure content of US 2017 / 286572 A1 is incorporated into the present application by reference.

[0028] The invention is based, among other things, on the understanding that a railway infrastructure described by means of a digitized track plan is particularly suitable for simulation and can be reproduced with increased realism by the simulation software. The simulation software can be configured to monitor the operation of the railway infrastructure defined by the digitized track plan. The advantages associated with this aspect of the invention have already been explained above, and reference is made to these advantages.

[0029] According to a further aspect of the invention, a computer program product is described, containing program instructions that can be executed by a computing environment. According to this aspect, the invention provides that at least the aforementioned steps a), b), and c) are executed.

[0030] According to the invention, a computer program product or simulation program product containing program modules is described with program instructions, wherein the program modules can run in the same computing instance or in several computing instances of the computing environment. The computer program product, which can comprise one or more computer programs, can be used to execute the method according to the invention and / or its exemplary embodiments, and the advantages described above are achieved through its execution.

[0031] According to a further aspect of the invention, a computer-readable storage medium containing data, which is stored as data records on the storage medium, is described. According to this aspect, the invention provides that the data records make the computer program products described above executable.

[0032] Furthermore, a provisioning device for storing and / or providing the relevant computer program in the form of a computer-readable storage medium is described. The provisioning device is, for example, a storage unit that stores the computer program and makes it available for retrieval. Alternatively or additionally, the provisioning device is a network service, a computer system, a server system, in particular a distributed computer system, such as a cloud-based system or virtual computer system, which stores the computer program on a computer-readable storage medium and preferably makes it available in the form of a data stream.

[0033] The provision of the computer program product takes the form of program modules describing program data sets as a file, in particular as a download file, or as a data stream, in particular as a download data stream. The computer program product is transferred, for example, using the provisioning device to a computing environment so that the method according to the invention can be executed in one or more computing instances of this computing environment. Embodiments of the invention

[0034] Further developments of the invention, describing variants, are explained below without limiting the basic idea of ​​the invention.

[0035] According to one variant, the aspects of the invention explained above are determined by the fact that d) the analysis uses stored data of rules for the function and / or interaction of the infrastructure elements, e) these rules are taken into account when creating the data of the functional relationships.

[0036] As mentioned previously, the stored data consists of datasets that can be read into the process to evaluate the rules governing the function and / or interaction of the infrastructure elements. As already described, these rules, as the evaluation results, are then available for the execution of the process, in that they can be provided as data on the functional relationships for consideration. These are also datasets that are evaluated during the process. The point at which the data on the functional relationships must be considered in the process flow is determined by the fact that the data on the functional relationships is linked to the data on the infrastructure elements.

[0037] One advantage of this approach is that the aforementioned data is generally applicable to the operation of railway infrastructure and is preferably defined in operating permits, standards, and the like. This makes it an easily accessible source from which data on functional relationships can be readily generated, even if these relationships are not explicitly stated in the track plan itself. In particular, a database can be established that can be used comprehensively for creating digital twins based on track plans, and whose multiple uses advantageously reduce the effort involved in implementing the inventive method.

[0038] According to one variant, the aspects of the invention explained above are determined by the fact that f) of identified infrastructure elements whose position in the track plan is determined, g) data of the position are stored in such a way that the position is assigned to the relevant infrastructure element.

[0039] Data relating to the position of infrastructure elements thus pertains to their positioning in the track plan. If the track plan is a scaled representation of the railway infrastructure, it can be assumed that these elements are located in the same place (geographical position) in the actual railway infrastructure (at least if the track plan is error-free). However, it is also possible that the track plan only depicts the topology of the railway infrastructure, i.e., it does not contain a scaled representation of the actual railway infrastructure. This is advantageous, for example, to be able to enlarge and thus clearly display areas with a high density of infrastructure elements, and to compress and thus save space in areas with a low density of infrastructure elements.However, even track plans that are not to scale can reveal certain relationships between the infrastructure elements, such as their order of arrangement, depending on their positioning (just not to scale).

[0040] One advantage of this approach is that relationships (whether to scale or not) between infrastructure elements can be derived solely from the representation in the track plan. Deriving these relationships does not require evaluating the aforementioned data from rules. This data is additional information that can be extracted from the track plan. This information is preferably specific to the railway infrastructure in question and therefore not included in generally applicable rules for the infrastructure elements.

[0041] Including positional data makes the created digital twin more realistic and consequently enables better simulation of processes that can be carried out in the railway infrastructure. This also allows for higher performance when operating the digital twin, further contributing to the advantages already explained above.

[0042] According to one variant, the aspects of the invention explained above are determined by the fact that the recognition of symbols in a large number of track plans is trained using machine learning.

[0043] One advantage of this approach is that the artificial intelligence used can be trained to apply the learned method more efficiently and reliably to new projects, enabling greater accuracy in recognizing track plans. Ideally, track plans that are already digitized can be used, as their contents are known and can be directly compared with the results obtained by the artificial intelligence. This allows for easy feedback during machine learning to evaluate the training results. Furthermore, this approach expands the database of datasets available for training.

[0044] Artificial intelligence (AI) is, in the context of this invention, understood more narrowly as the capability of computer-based machine learning (ML). This involves the statistical learning of algorithm parameterization, preferably for highly complex applications. Using ML, the system recognizes and learns patterns and regularities in the acquired process data based on previously inputted training data. With the aid of suitable algorithms, ML can independently find solutions to emerging problems. ML is divided into three areas: supervised learning, unsupervised learning, and reinforcement learning, with more specific applications such as regression and classification, structure recognition and prediction, data generation (sampling), and autonomous action.

[0045] In supervised learning, the system is trained by observing the relationship between input and corresponding output of known data, thereby learning approximate functional relationships. The availability of suitable and sufficient data is crucial, because if the system is trained with unsuitable (e.g., non-representative) data, it will learn incorrect functional relationships. In unsupervised learning, the system is also trained with example data, but only with input data and without a connection to a known output. It learns how to form and extend data groups, what is typical for the respective use case, and where deviations or anomalies occur. This allows use cases to be described and errors to be detected.In reinforcement learning, the system learns through trial and error by proposing solutions to given problems and receiving positive or negative feedback on these proposals. Depending on the reward mechanism, the AI ​​system learns to perform corresponding functions.

[0046] According to one variant, the aspects of the invention explained above are determined by the fact that h) the above steps a), b) and c) are applied to several track plans of the same railway infrastructure, i) the results of the transformation are compared with each other in such a way that infrastructure elements are identified in track plans that denote one and the same infrastructure element in the railway infrastructure.

[0047] One advantage of this variant is that it increases the probability of generating largely accurate results from the transformation according to the invention. In reality, multiple documentations of railway infrastructure often exist, which can be explained by the long operating life of railway infrastructure systems and their necessary repairs or adaptations to current requirements. These documentations, particularly in the form of track diagrams, represent the railway infrastructure at least partially or at least accurately. By comparing the transformation results, potential discrepancies can therefore be identified and, for example, checked manually by the project team during the planning of changes to the railway infrastructure, and, if necessary, verified or corrected.

[0048] The same railway infrastructure within the meaning of the invention is thus understood to be a section of the entire track network (which constitutes the railway infrastructure) that is at least partially represented in at least two different track diagrams. In other words, there must be at least some overlap in the track diagrams, and this overlap represents the common railway infrastructure because it can be verified by comparing the results of the transformation according to this variant of the invention.

[0049] According to one variant, the aspects of the invention explained above are determined by the fact that j) a message indicating an inconsistency is generated and output if an infrastructure element cannot be identified in all track plans, k) a message identifying the infrastructure element in question is generated.

[0050] One advantage of this approach is that the detection of inconsistencies in track plans representing the same railway infrastructure can be automated. A project team is then notified via messages indicating which details of the transformation result require particular attention and in which direction the review should proceed.

[0051] The message indicating an inconsistency consists of data that can be evaluated by a computing environment to confirm the existence of an inconsistency. This message can consist of one or more data records. The message identifying the relevant infrastructure element consists of data relating to an infrastructure element identified in the track plan, for which the inconsistency has been determined across multiple track plans. This message can also consist of one or more data records. The message indicating an inconsistency and the message identifying the infrastructure element can also be the same message. In this case, the data are transmitted together in one or more data records.

[0052] According to one variant, the aspects of the invention explained above are determined by the simulation of railway infrastructure functions, wherein l) the data of the identified infrastructure elements are used in the simulation, m) the data of the functional relationships are taken into account in the simulation, n) data of a simulation result are generated.

[0053] One advantage of this approach is that the relatively high degree of realism of the digital twin, represented by the transformation result, is suitable for simulating processes within the railway infrastructure. This simulation can be used to advantage for various purposes. Firstly, the simulation allows for statements about current or planned railway operations within the infrastructure. Secondly, the simulation can be used to verify and / or understand the functionality of the railway infrastructure. This will be explained in more detail below.

[0054] According to one variant, the aspects of the invention explained above are determined by the fact that the data from the simulation result are used to control the railway infrastructure.

[0055] One advantage of this approach is that the digital twin can be used to optimize railway operations. In particular, it allows for a response to unforeseen incidents in railway operations, enabling the simulation of alternative scenarios that promise the smoothest possible operation by taking the unforeseen incident into account. Because the digital twin, as mentioned earlier, offers high performance, a large number of alternative scenarios can be simulated in a relatively short time, allowing for the optimization of the planned alternative operating regime for the railway infrastructure.

[0056] According to one variant, the aspects of the invention explained above are determined by the fact that the data from the simulation result are used to check whether rules for the function and / or interaction of the infrastructure elements are violated.

[0057] One advantage of this approach is that it allows for the verification of the functionality of infrastructure elements captured in the digital twin, even without actual operation of the railway infrastructure, by simulating their operation under specific conditions. This relies on the understanding that typical situations requiring infrastructure elements to be handled can be recreated even without real-world railway operations. With such modeled functional relationships, it is easy to predict the correct response of the infrastructure elements to the simulated conditions. Therefore, simulation can be used to verify whether the mapping of the railway infrastructure based on the track plan was successful, at least with regard to the consistency of the railway infrastructure captured as a digital twin.

[0058] According to one variant, the aspects of the invention explained above are determined by the fact that the computer program product is designed to simulate functions of the railway infrastructure as described above.

[0059] One advantage of this variant is that a computer program product can be offered which is suitable for carrying out the method according to the invention. The user of this computer program product can thus benefit from the advantages of the invention without having to program the functionalities individually. However, an adjustment of the parameters of the computer program product is necessary so that an artificial intelligence implemented by the computer program product can be trained. The details of this have already been described above. Exemplary embodiments of the drawing

[0060] Further details of the invention are described below with reference to the drawing. Identical or corresponding drawing elements are provided with the same reference numerals in each figure and are only explained more than once to the extent that differences arise between the individual figures.

[0061] The exemplary embodiments described below are preferred embodiments of the invention. In these exemplary embodiments, the described components each represent individual variants of the invention, which can be considered independently of one another. Each of these variants further develops the invention independently and can therefore be regarded as part of the invention individually or in a combination other than that shown. Furthermore, the described components can also be combined with the variants of the invention described above. Figure 1schematically shows an exemplary embodiment of a railway environment as part of a railway infrastructure with its interrelationships between the functional components used. Figure 2 shows an exemplary embodiment of a computing environment for the device according to Figure 1 as a block diagram of the individual functional components and further functional components and the interfaces formed between them, wherein individual computing instances execute program modules which can each run in one or more of the exemplary processors shown and wherein the interfaces shown can accordingly be implemented in software in one of the processors or in hardware between different processors. Figure 3 shows an example of a scale track plan and Figure 4 An example of a track plan that is not to scale, where the track plans are according to Figure 3 and Figure 4can serve as input for the inventive method for transforming track plans, and wherein the exemplary embodiments of the track plans represent a railway environment according to Figure 1 represent. Figure 5 shows, as a possible result of the transformation, a graphical representation of an exemplary functional relationship of the orbital environment according to Figure 1 . Figure 6 An embodiment of the method according to the invention is shown as a flowchart, wherein the process steps shown can be implemented individually or in groups by program modules, and wherein the computing instances and interfaces are defined according to Figure 2 are indicated by example. Detailed description of the exemplary implementations

[0062] Regardless of the grammatical gender of terms, persons with male, female or other gender identities are equally included.

[0063] In Figure 1A railway environment (BU) can be seen as part of a railway infrastructure in which the inventive method takes place. This involves a Figure 2 The depicted computing environment RU is used. Figure 1The diagram depicts a track-guided vehicle (FZ) traveling in one direction (FR) on a first track (GL1). There is also a second track (GL2) and a connecting track (VGL) linking these two tracks, which serve as so-called control elements (LET) of the railway environment. Along the track formed by the rail system, a signal box (STW) is provided as a control element (STE). This signal box controls functional components of the railway environment (BU), such as a first signal (SG1), a second signal (SG2) (referring to light signals), a first point motor (WA1) of a first point (W1), or a second point motor (WA2) of a second point (W2), as further control elements (STE). Additionally, a first axle counter (AZ1), a second axle counter (AZ2), a third axle counter (AZ3), a fourth axle counter (AZ4), a fifth axle counter (AZ5), and a sixth axle counter (AZ6), as well as a balise (BL), are provided.Functional components of the first track GL1 can also be controlled by a first controller CRL1, and functional components of the second track GL2 can also be controlled by a second controller CRL2. In the example according to... Figure 1 These are the axle counters in question.

[0064] Furthermore, a control center (LZ) is planned, in which, for example, adherence to a timetable can be monitored by vehicles (FZ) operating in the railway environment (BU). The signal box (STW), the control center (LZ), and the vehicle (FZ) are equipped with antennas (AT), enabling radio-based communication between these units.

[0065] The computing environment RU, in which the inventive method takes place, can be considered jointly by Figure 1 and Figure 2 The data can be extracted. The computing instances and functional components used interact with each other via S22 interfaces.

[0066] According to Figure 2The computers forming the respective computing instances are described in more detail. In the first computer CP1 of the control center LZ, a first processor PR1 is connected to a first memory unit SE1 via an eleventh interface S11. In the second computer CP2 of a service provider DL for simulation calculations, a second processor PR2 is connected to a second memory unit SE2 via a twelfth interface S12. In the third computer CP3 of the signal box STW, a third processor PR3 is connected to a third memory unit SE3 via a thirteenth interface S13. In the fourth computer CP4 of a project planning environment PU, a fourth processor PR4 is connected to a fourth memory unit SE4 via a fourteenth interface S14.If, within the scope of this invention description, only computers, processors, memory units, signals, switches, switch drives, axle counters or interfaces S22 are mentioned, the information generally refers to all of the computers, processors, memory units and other functional components named above in detail, which, connected by the interfaces, contribute to the formation of the computing environment RU.

[0067] The aforementioned project environment PU can, for example, be a computer infrastructure for a project team to improve the performance of the railway infrastructure BI. The service provider DL can be a data center that offers applications for creating and training algorithms using artificial intelligence, as well as simulations, as a service DL. These services require a high level of computing capacity but can alternatively also be performed in the project environment PU. The fourth processor PR4 is connected to the second processor PR2 via interface S21. The fourth processor PR4 is connected to the first processor PR1 via interface S22. The fourth processor PR4 is connected to the third processor PR3 via interface S23. The first processor PR1 is connected to the third processor PR3 via interface S24.The S22 interfaces allow the work of the PU project planning environment to be coordinated with the work of the service provider DL. Furthermore, data from the LZ control center regarding real-world rail traffic and from the STW interlocking system regarding the real-world conditions of the BU railway environment can be transferred.

[0068] Through a first interface S1 according to Figure 1The signal box STW and the second signal SG2 are connected via a second interface S2. The signal box STW and the first signal SG1 are connected via a third interface S3. The signal box STW and the first point motor WA1 are connected via a fourth interface S4. The signal box STW and the second point motor WA2 are connected via a fourth interface S4. The first controller CRL1 and the first axle counter AZ1 are connected via a fifth interface S5. The first controller CRL1 and the second axle counter AZ2 are connected via a sixth interface S6. The first controller CRL1 and the third axle counter AZ3 are connected via a seventh interface S7. The second controller CRL2 and the fourth axle counter AZ4 are connected via an eighth interface S8. The second controller CRL2 and the fifth axle counter AZ5 are connected via a ninth interface S9.The second controller CRL2 and the sixth axle counter AZ6 are connected via a tenth interface S10.

[0069] In the Figures 3 and 4 Examples of GPL track plans are shown, as they are typically created, for example, in paper form. These GPL track plans correspond to a representation of the railway environment according to BU. Figure 1 and are therefore greatly simplified. In reality, more complex railway environments (BU) are usually depicted.

[0070] During the track plan GPL according to Figure 3 The track plan, which includes a scale representation, is in accordance with... Figure 4 a schematic representation from which only the relationship between the arrangement of the individual functional components can be deduced. The individual functional elements are labelled with the same reference symbols as in Figure 1, so that a detailed explanation is not necessary. For the purpose of the transformation according to the invention, the track plans GPL can be transformed according to the Figures 3 and 4 for example, they can be scanned so that digital image data is available which can then be evaluated and compared according to the invention.

[0071] According to Figure 5 One result of this evaluation using the method according to the invention is graphically represented. This is a network representation with nodes KN, which are connected to each other by lines LN, whereby the logical relationships between the individual functional components of the railway environment BU are shown. Also according to Figure 5 The same reference symbols will be used as according to Figure 1 used so that their assignment to the railway environment BU according to Figure 1 is easily possible.

[0072] The graphical representation contains a graph of the logical relationships that arise when the in Figure 1 The depicted vehicle FZ, traveling in the direction FR, changes track, i.e., it travels from the first track GL1 via the connecting track VGL to the second track GL2. The first switch W1 and the second switch W2 are set in such a way that a change between the first track GL1 and the second track GL2 is possible.

[0073] To prepare for the vehicle FZ to change tracks, the track sections between the second axle counter AZ2 and the third axle counter AZ3, as well as between the fourth axle counter AZ4 and the fifth axle counter AZ5, are first checked simultaneously to ensure they are clear, meaning no vehicles FZ are currently traveling on these sections. Then, the first signal SG1 and the second signal SG2 are simultaneously set to "red," preventing the vehicle from proceeding if these sections are occupied. Next, the track sections between the first axle counter AZ1 and the second axle counter AZ2, as well as between the fifth axle counter AZ5 and the sixth axle counter AZ6, are checked simultaneously to ensure they are clear. If so, the first switch W1 and the second switch W2 are simultaneously set so that the following Figure 1The vehicle FZ, as shown, can switch from the first track GL1 to the second track GL2 via the connecting track VGL. Subsequently, the system monitors the first axle counter AZ1, the second axle counter AZ2, the fifth axle counter AZ5, and the sixth axle counter AZ6 to ensure that the vehicle FZ follows the prescribed route and clears the track sections defined by the latter axle counters in succession. Afterward, the vehicle FZ leaves the track environment BU on the second track GL2.

[0074] This is merely an example of a functionality of the railway environment BU. This functionality can be simulated, for example, to verify the function of the functional components recognized in the track plans GPL. The simulation can also be performed to ensure that the aforementioned functional components are implemented in the real railway environment BU according to the specifications. Figure 1 according to Figure 5The logic shown can be followed by control via the STW interlocking system. In other words, the model, which is generated by analyzing the GPL track plans according to Figure 3 and Figure 4 It was created as a digital twin, first tested for its functionality through simulation, and then used to increase the performance of a control system for the railway environment (BU) in real train traffic.

[0075] The following describes the method according to the invention by way of example, as shown in the flowchart according to Figure 6 will be presented and explained step by step. Figure 3 Furthermore, the boxes provide an example of how functional components and computing instances are contained within them. Figure 1 and 2The individual steps can be carried out. Computer-aided steps take place in the processors, which are not shown in detail. The reading and saving of data to the storage units is shown as an example. Insofar as the S22 interfaces are used in this context, Figure 1 and 2 These can also be used in Figure 3 marked.

[0076] In the first step 1, the process is started (abbreviated: START).

[0077] In a second step, analog image information in the form of a track plan (GPL, abbreviated SCN) is scanned. If the information is already available digitally, the scanning step is omitted. However, digital image information must still be made available to the process.

[0078] In a third step, the acquired digital image information (ANL) is analyzed. During the analysis, symbols represented by the image information are identified, for example, and assigned to specific functional elements of the railway infrastructure (BI).

[0079] In a fourth step, the railway context is taken into account with regard to the identified infrastructure elements LET and STE in the aforementioned image information (abbreviated: CNT). Rules transferred from the fourth storage unit SE4 can be considered here, defining the context to be taken into account.

[0080] In a fifth step, the position of the identified infrastructure elements LET and STE is considered, taking into account the track plan GPL as a whole and the topology and / or topography of the infrastructure elements LET and STE within the track plan GPL (abbreviated POS). In this context, topology refers to the interaction of the individual infrastructure elements LET and STE and their functional relationships to one another. Logical functional relationships must be considered. Topography refers to the spatial relationship between the infrastructure elements LET and STE. This information can be obtained from track plans GPL that include a scaled representation of the railway infrastructure BI.

[0081] In a sixth step, data from the identified infrastructure elements LET and STE are stored together with the functional relationships applicable to these infrastructure elements within the railway infrastructure BI, such that the functional relationships are assigned to the respective infrastructure element LET or STE (abbreviated as SVE). These functional relationships between the infrastructure elements LET and STE constitute the functional context and thus a digital twin of the railway infrastructure BI.

[0082] In a seventh step (SIM), a simulation step is performed. The aim of this step is to test basic functions of the railway infrastructure BI, which was created as a digital twin of the railway infrastructure BI through the preceding steps. The contextual information from the fourth storage unit SE4 can be used for this purpose, as mentioned above.

[0083] In the eighth step (8), the simulation result undergoes plausibility checks (PLS). Based on the contextual information, it can be verified whether the created digital twin behaves as expected under specific operational conditions within a simulated operating scenario. If so, the process continues to the ninth step (9). If not, the process recursively returns to the second step (2). Additional planning documents or the available planning documents must then be rescanned (to avoid scanning errors), or, if this step is omitted, at least the analysis according to the third step (3) must be repeated (to correct analysis errors).

[0084] In a ninth step, a further simulation is performed, this time under the underlying real-world operating conditions of the railway infrastructure BI, which is described by the digital twin (SIM). Data from the first storage unit SE1 and the second storage unit SE2 can be taken into account here, relating to current train traffic and the current status information of the individual infrastructure elements LET, STE of the railway infrastructure BI.

[0085] In a tenth step, the real railway infrastructure BI is controlled, for example, by the signal box STW or the controllers CRL1, CRL2 (abbreviated: CRL). The simulation result is used, at least as a supporting tool, for this control process.

[0086] In step 11, the process is terminated (abbreviated: STOP). Reference symbol list

[0087] BU Railway environment RUR Computer environment FZ Vehicle FR Direction of travel GL1 First track GL2 Second track VGL Connecting track LET Control element STE Control element STW Interlocking system SG1 First signal SG2 Second signal WA1 First point motor W1 First point WA2 Second point motor W2 Second point AZ1 First axle counter AZ2 Second axle counter AZ3 Third axle counter AZ4 Fourth axle counter AZ5 Fifth axle counter AZ6 Sixth axle counter BLB Alignment CRL1 First controller CRL2 Second controller LZ Control center ATA Antennas S2222. Interface CP1 First computer PR1 First processor SE1 First memory unit S11 Eleventh interface CP2 Second computer DL Service provider PR2 Second processor SE2 Second memory unit S12 Twelfth interface CP3 Third computer PU Project environment PR3 Third processor SE3 Third memory unit S1313. CP4 interface (fourth computer), PR4 (fourth processor), SE4 (fourth storage unit), S1414 interface (railway infrastructure), S2121 interface, S2323 interface, S2424 interface.Interface S1 first interface S2 second interface S3 third interface S4 fourth interface S5 fifth interface S6 sixth interface S7 seventh interface S8 eighth interface S9 ninth interface S10 tenth interface GPLGleisplan KNKnoten LNLinien SBLSymbole LET, STEInfrastructure element.

Claims

1. Method for transforming a track plan (GPL) of a railway infrastructure (BI) that is available as image information, in which the track plan (GPL) is captured and analyzed using computer-aided methods, characterized by the fact that a) During computer-aided analysis, symbols (SBL) in the track plan (GPL) are recognized as infrastructure elements (LET, STE), b) Symbols (SBL) recognized during analysis are placed in the context of the railway infrastructure (BI) using computer-aided analysis, c) As a result of the transformation, data of the infrastructure elements (LET, STE) that were recognized are stored, and for these infrastructure elements (LET, STE), data of these functional relationships applicable in the railway infrastructure (BI) are stored in such a way that the functional relationships are assigned to the respective infrastructure element (LET, STE).

2. Method according to claim 1, characterized by the fact thatd) the analysis accesses stored data of rules for the function and / or interaction of the infrastructure elements (LET, STE), e) these rules are taken into account when creating the data of the functional relationships.

3. Method according to claim 1 or 2, characterized by the fact that f) of identified infrastructure elements (LET, STE) whose position in the track plan (GPL) is determined, g) data of the position are stored in such a way that the position is assigned to the relevant infrastructure element (LET, STE).

4. Method according to any one of the preceding claims, characterized by the fact that The recognition of symbols (SBL) in a variety of track plans (GPL) is trained using machine learning.

5. Method according to any one of the preceding claims, characterized by the fact thath) the steps a), b) and c) according to claim 1 are applied to several track plans (GPL) of the same railway infrastructure (BI), i) the results of the transformation are compared with each other in such a way that infrastructure elements (LET, STE) are identified in track plans (GPL) that denote one and the same infrastructure element (LET, STE) in the railway infrastructure (BI).

6. Method according to claim 5, characterized by the fact that j) a message indicating an inconsistency is generated and output if an infrastructure element (LET, STE) cannot be identified in all track plans (GPL), k) a message identifying the infrastructure element (LET, STE) in question is generated.

7. Method according to any one of the preceding claims 2 to 6, characterized by the fact thatFunctions of the railway infrastructure (BI) are simulated, wherein l) the data of the identified infrastructure elements (LET, STE) are used in the simulation, m) the data of the functional relationships are taken into account in the simulation, n) data of a simulation result are generated.

8. Method according to claim 7, characterized by the fact that The data from the simulation results will be used to control the railway infrastructure (BI).

9. Method according to claim 7, characterized by the fact that The data from the simulation result will be used to check whether rules for the function and / or interaction of the infrastructure elements (LET, STE) are violated.

10. Computer program product for simulation, designed to simulate the operational behavior of infrastructure elements (LET, STE) of a railway infrastructure (BI), characterized by the fact thatThe computer program product has a data interface for reading in a result of transforming a track plan (GPL) of the railway infrastructure (BI) that is available as image information, generated according to one of the preceding claims.

11. Computer program product according to claim 10, characterized by the fact that the computer program product is designed to simulate functions of the railway infrastructure (BI) according to claim 7.

12. Computer program product containing program instructions executable by a computing environment (RU) such that at least steps a), b) and c) of the method according to any one of claims 1 - 9 are executed.

13. Computer-readable storage medium containing data which are stored as data records on the storage medium, such that the data records make the computer program product according to one of claims 10 to 12 executable.

Images