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Dieses Kapitel untersucht das Potenzial digitaler Planungsdokumente zur Verbesserung von Eisenbahnnetzsimulationen und Planungsprozessen. Sie führt das yaramo-Modell und die Werkzeugkette ein, die die Umwandlung digitaler Planungsdokumente in Verkehrssimulationen ermöglichen und eine frühzeitige Bewertung von Eisenbahnnetzen ermöglichen. Der Text diskutiert die Vorteile digitaler Planungsprozesse, wie reduzierte Übertragungsfehler und bessere Validierung, sowie die Herausforderungen, vor denen wir stehen, wie der Mangel an umfassender Toolunterstützung und Versionskontrollproblemen. Das Yaramo-Modell und seine drei Ebenen von Softwarekomponenten - Importeure, Prozessoren und Exporteure - sind detailliert und unterstreichen ihre Rolle bei der Konvertierung digitaler Planungsdokumente in Simulationsmodelle. In diesem Kapitel werden auch Anwendungsfälle für frühe Simulationen, Testautomatisierung der CCS-Infrastruktur und Unterstützung für Eisenbahnforschungsprojekte vorgestellt. Darüber hinaus beschreibt er den Umwandlungsprozess in ein SUMO-Modell und die Kopplung von Simulationen mit einer generischen Verriegelungslogik und demonstriert die praktischen Anwendungen der Yaramo-Werkzeugkette. Die Schlussfolgerung betont die Vorteile digitaler Planungsdokumente und die Weiterentwicklung des yaramo-Modells und der Werkzeugkette.
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Diese Zusammenfassung des Fachinhalts wurde mit Hilfe von KI generiert.
Abstract
The digitalization of the railway domain is a key enabler for more efficient railway operations matching the future needs of society. One part of this process is the digitalization of planning processes, replacing the use of paper-based plans with digital formats. Digital planning documents also open new possibilities, e.g., deriving representative simulation in early project stages. A commonly used simulator for such purposes is the Simulation of Urban Mobility (SUMO). To use the capabilities of SUMO, we are presenting a tool chain for unifying planning documents and generating simulation configurations from them. The core of this tool chain is the yaramo model, covering mainly the topology, geography, and the control command and signaling (CCS) infrastructure of the railway network. The tool chain consists of three major layers: Importers to support multiple data sources (such as PlanPro or OpenRailwayMap), processors to enrich the model, and exporters to support various consumers of the model. This leads to several applications, such as rail network performance evaluations and test automation for CSS infrastructure. Ultimately, our work aims to support the digitalization process of the railway domain, especially the digital planning and development of railway networks.
1 Introduction
A more efficient and reliable railway system is widely requested by society. Besides this, there is a shift in politics towards more passenger and freight traffic on the rails to reduce the emission of carbon dioxide. To reach these goals, one of the key enablers is the digitalization of the railway domain. This already widely affects the control command and signaling (CCS) infrastructure with open standards, like the EULYNX standard [5] and IP-based communications.
The new standards also call for digitalized planning processes. Among other things, these planning processes replace paper-based media with machine-readable documents, which ease data exchange and processing. This change leads to the advantages of digitally exchangeable documents, reduced transmission errors during scanning of paper-based plans, and better validation of the planned documents [3]. Besides these advantages, there are also several challenges with digital planning processes, like the lack of extensive tool support, version control of the files, and multiple versions of the formats themselves.
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Additionally to the planning process itself, digital planning documents are also usable for other applications. This paper focuses on taking the digital planning document as input to traffic simulations. Converting digital planning documents to traffic simulations combines the capabilities of both worlds. Digital planning documents, on the first side, have a precise model of the planned railway network which is a detailed input to the simulation. This includes the topology and details about the CCS infrastructure. The traffic simulation, on the other side, can operate the planned railway network in the early stages of the planning process. Together they support our three main use cases:
Early-Stage Simulations of Railway Plannings.
The evaluation of the railway network regarding criteria, such as bottlenecks, performance, and others.
Test Automation of CCS Infrastructure.
The testing of hardware under development by using a generic interlocking logic and hardware-in-the-loop (HiL) capabilities to trigger state changes of the hardware.
Support Railway Research Projects.
Operating newly developed railway systems in research projects in traffic simulations.
The following paper presents a tool chain for converting digital planning documents to traffic simulations. It has the central yaramo model and three layers of software components: Importers, processors, and exporters. Besides converting the planned network to a simulation model, yaramo has more capabilities, like the conversion of formats and the lightweight creation of planning documents.
2 Railway Planning Formats
The industry and communities, such as the OpenStreetMap community, developed formats to plan and describe railway networks and the CCS infrastructure. These formats have detailed information about the topology (e.g., points, signals, and rails) and geography (e.g., locations of components) of the system.
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One of the first developed formats is the PlanPro format – introduced by Deutsche Bahn. Development started in 2009 [1] and it is capable of planning an electronic interlocking (ESTW) [2]. It is an XML-based data format that represents the topology of the railway network with a network graph, connecting topological nodes (e.g., points) with tracks. Additional objects are available to describe the CCS equipment, such as signals or train detection systems. Deutsche Bahn offers a tool to visualize and check plannings while two commercial products are available that allow for such plannings to be created. Besides this format specific to Germany, European formats are also under development.
Digital planning formats have been designed to allow for the full planning process of the CCS equipment of a line. In contrast, data about railway infrastructure has been collected by volunteers as part of the OpenRailwayMap (ORM) [6] project. The underlying data model is also a graph, whose nodes can be enriched with arbitrary key-value pairs. For a lot of domains, conventions to represent the data have developed. This data can be queried with a query language and is accessible to the general public [4]. The data quality varies widely, but in a lot of places, there is accurate information about the topology and geography of railway lines as well as signals and other trackside devices.
3 The yaramo Pipeline
The tool chain presented in this paper uses railway network data from the mentioned formats to support the digitalization process of the railway domain. The key idea is to use digitally represented railway network models to create simulation models, perform conversions to other formats, or use the central model for data processing and parametrizing further logic.
Fig. 1.
The yaramo environment. It consists of the yaramo model and three tool chain layers: importers, processors, and exporters.
The core of the tool chain is the yaramo model, storing the topology and geography, as well as details about the CCS infrastructure. Besides the model, the tool chain is generally structured in three different layers, as also illustrated in Fig. 1: The importers read digital railway network models to create yaramo instances, processors modify these instances, and exporters write them in another format or use them as input for further tools. All these different components are implemented as separate software components as Python libraries, available on GitHub [8]. A simple example of the tool chain can be found in the repository [9]. In that code example, a PlanPro file is read by the PlanPro importer. The railway route generator, as an example of a processor, generates all possible routes through the railway network. In the end, the result is exported to a SUMO simulation model [7]. At the moment, only one importer can be used at the same time, but multiple processing engines and exporters can be applied.
3.1 The yaramo Model
The digital planning formats describe the real-world objects precisely, their focus is an interchange format that can be stored and transferred easily. However, this format is not well-suited for processing. When operating on the topology graph used by those models, common graph algorithms like DFS are useful, e.g., to find routes in the railway network. XML-based formats need further processing to allow these operations. As there is not a single model that has reached widespread adoption yet, data from multiple sources is of interest and therefore each software would need to exist in multiple flavors to allow that.
We introduce yaramo to overcome the presented issues. The model consists of a graph topology with edges and nodes as well as additional classes to represent concepts like signals and routes. Because these concepts can be found in all of the existing models, a conversion to and from them is feasible. The model is easily extensible to cover other use cases and the objects and attributes needed therefore. The yaramo model is implemented as a Python library. An extra topology class works as a wrapper class for all objects in a single yaramo instance. This topology can then be passed to other components of the pipeline.
3.2 Pipeline
This section describes the abovementioned three layers of the pipeline.
Importers. Since the yaramo model is a Python library, it is possible to create instances of the model by hand through creating the necessary objects. This is time-consuming, especially for larger models. To use existing digital planning documents (PlanPro) or ORM data, we provide libraries extracting the data from these data sources. We also created a Command Line Interface (CLI).
Processors. Having a yaramo instance, some common operations are usually necessary to enrich the model for further processing. Therefore, processors are taking the model as input and enrich it with their purpose. Currently, fully implemented is the railway route generator, which uses a depth-first search on the topology graph to find all possible routes in the topology.
Exporters. After enriching the instance, it can be converted to different output formats. The resulting files can be used for further processing by other tools. Currently, the export to PlanPro files and SUMO simulation configurations are possible. Besides this, a yaramo instance can also be used as input for other tools, such as an generic interlocking logic, by parametrizing them with the model.
4 Early-Stage Simulations of Digital Planning Documents
The introduction mentioned several applications of traffic simulations parameterized with digital railway planning documents. We are using Simulation of Urban Mobility (SUMO) as the traffic simulator, which is commonly used in the area of traffic simulation. SUMO contains several models for the movement of vehicles but needs a simulation model as input. This model mainly consists of a network and routes through this network.
Fig. 2.
The pipeline to convert yaramo instances to SUMO simulations. The grey boxes are provided by the SUMO tool chain, the bold boxes were developed as the exporter.
Conversion to a SUMO Model. The conversion of a yaramo instance to a SUMO simulation model follows a pipeline shown in Fig. 2 and is implemented in the SUMO exporter. First, files are created in the SUMO-Plain-XML format as the main conversion step. Hence, all points, track ends, as well as signals, must be converted to nodes via a graph transformation. Next, the SUMO tool netconvert transforms the plain-XML files to the SUMO network. The SUMO simulation configuration created afterward links the network file to a route file, containing the routes from the yaramo model. These routes were either planned in the PlanPro file or generated by the railway route generator. This completes the model for the simulation.
Coupling the Simulation with a Generic Interlocking Logic. To run the simulation, we developed a basic interlocking logic managing the railway network and its CCS architecture. This logic is parametrized with a yarmao instance. It offers an interface to set, free, and reset routes for trains. If a route for a train is set, the interlocking logic verifies that the required elements are not reserved by any other train and reserves them afterward. It also moves the points to the necessary position and sets signal aspects. Reserving overlaps, basic support for flank protection, and other operations are also supported.
Implemented as a library, the logic itself is not limited to SUMO. When instantiating the interlocking logic, it is necessary to pass infrastructure providers (IPs), that couple the logic with any kind of infrastructure. The IPs get called by the logic when moving a point or setting a signal. To couple the interlocking logic with SUMO, a SUMO IP is necessary. This passes the required states to TraCI (a SUMO interface) and affects the state of the simulation. We also developed an IP moving hardware points, proving the possibility of HiL simulations.
During the execution, the SUMO simulation determines the train positions and returns that position via the SUMO infrastructure provider to the interlocking logic. That mechanism is closely related to a train detection system realized by axle counters. To simulate train movements, a test driver needs to create trains in SUMO and set routes for these trains in the interlocking logic. This is the responsibility of the test developer, having the mentioned use cases in mind.
5 Conclusion
Digital planning documents of railway networks and their CCS infrastructure, such as documents in the PlanPro format, offer a variety of new applications for detailed data about the planned networks. The yaramo model and the related tool chain offer a lightweight framework to read and process PlanPro files and create SUMO simulation models based on the planning documents. These simulations can be used to experimentally evaluate the planned network in the early stages of development, e.g., regarding the performance. Other applications, like test automation of hardware prototypes, are possible as well since the simulation supports HiL experiments. Besides the simulation-based applications, also the transformation of publicly available data in ORM to digital planning documents or the lightweight creation of PlanPro files are further use cases of this model and tool chain. Both support the digitalization of existing railway networks.
In the near future, several more features will be added to the model and the tool chain. One major point of the ongoing development is the extension of the model while keeping it lightweight at the same time. We only add features, that are necessary for our use cases. Now, especially the support of level crossings and axle counters are in our focus. Another useful feature would be the functionality to merge multiple instances to combine largely available ORM data with a precise PlanPro model. Finally, the tool chain would benefit from a visualization of a model to make it easier to understand an instance.
In summary, the presented model and tool chain support the digitalization of the railway domain to increase the performance and reliability of the whole railway system.
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