RailML application for description of railway interlocking systems

Ciszewski, Tomasz; Kornaszewski, M.; Nowakowski, Waldemar

doi:10.24136/atest.2018.415

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…The priorities of its elements ([vi,eu,q], vi∈V(G), q∈R0 + , eu∈E(G), vi∈φ(eu), are determined by the q-component value (the element priority is the higher the lower the value of its distance mark q). ▪ The track infrastructure can be defined within a specific configuration file (in XML format), which uses templates inspired by the railML standard [35,36]. The infrastructure models can be constructed (e.g., for the MesoRail simulator [4]), within the TrackEd simulator [37] for instance.…”

Section: B Model Properties and Implementation Commentsmentioning

confidence: 99%

Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Kavička

Diviš

2022

IEEE Access

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Computer simulations are frequently used for rail traffic optimization. This approach, referred to as simulation-based optimization, typically employs simulation toolssimulators that are designed to examine railway systems at various levels of detail. Microscopic rail traffic simulators find use when examining rail traffic and the rail infrastructure in great detail. Such simulators typically serve to follow the positions and motions of rail vehicles (trains, locomotives, train cars) and their relocation as well as segments of the rail infrastructure (tracks, switches, track crossings). One of the typical problems to be solved by microscopic simulators within a simulation experiment is to determine the realistic train and shunting routes (within the currently occupied infrastructure) along which the rail vehicles are moved. This requires a suitable rail infrastructure model, associated with algorithms that seek admissible routes for the transfer of the relocation objects. This paper describes novel dynamic route searching algorithms applicable to the relocation of rail vehicles within track infrastructure of railway systems. The infrastructure model is represented by a specific edge-weighted undirected graph. The routes computed by the algorithms coincide with specific shortest walks in the graph, taking into account the particular relocation object lengths. The use of the algorithms within the simulation tools (working at the microscopic level of detail) extends the modelling possibilities when searching for realistic track routes (especially for complicated shunting operations), which contributes to better modelling of complex railway traffic (than in the relevant existing rail traffic simulators) and thus to better application of the results of traffic simulations in practice.INDEX TERMS rail traffic, simulation-based optimizations, single-train shortest routes

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Section: B Model Properties and Implementation Commentsmentioning

confidence: 99%

Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Kavička

Diviš

2022

IEEE Access

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“…A standard exists for this purpose, viz. railML [27,28] (open-source railway markup language). is standard defines a recommended format of the files for the exchange of data for railway applications.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(ii) e configuration of the railway infrastructure can be specified for the needs of the MesoRail simulator [20], for example, within the TrackEd editor [24]. is editor stores infrastructure description in the XML format, which uses templates inspired by the railML standard [27,28]. is, in fact, means that the relocation object (whose length is L) is located "precisely" at the end of the respective track both at the beginning and at the end of the relocation operation.…”

Section: Basic Algorithmmentioning

confidence: 99%

“…for each j v y ∈ F V do (28) Get_Indexes(↓ j v y , ↑j, ↑y) (29) if (x � y and i ≠ j) then (30) okay ← false // inadmissible combination of the start and finish vertices (31) exit (32) end (33) if (ω (a) trajectory to the points representing the input ends of the edges/tracks reached. e total length of the train's trajectory during the relocation is 470 m. e value for the last member of the walk is additionally increased by L � 120 due to the fact that the relocation operation must be finished by a partial transfer of the whole object to the finish track (edge).…”

Section: Basic Algorithmmentioning

confidence: 99%

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Dynamic Automated Search of Shunting Routes within Mesoscopic Rail-Traffic Simulators

Kavička

Krýže

2021

Journal of Advanced Transportation

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Software tools using computer simulations are frequently used in the research and optimization of railway transport systems. Such simulations serve to examine different railway traffic scenarios (which typically reflect different timetables and railway infrastructure configurations). During the simulation experiments, it is necessary, among other things, to solve tasks related to the determination of track routes along which individual trains or parts of train sets are moved. Many simulation tools require the basic and alternative permissible track routes to be manually specified before starting the simulations, which is a relatively tedious and time-consuming process. Classical graph algorithms cannot be applied to solve the problem of automatic calculation of the routes because they are unable to take into account the length of the object being moved or recognise changes in the direction of its movement. This article presents original innovative algorithms focused on automated dynamic search of track routes (applying an appropriate optimization criterion), which is performed during simulation experiments within simulators working at the mesoscopic level of detail. The algorithms are based on a mathematical model (represented by a specifically designed weighted digraph) that appropriately reflects the actual track infrastructure. The dynamic calculation of each specific track route for a train or a group of railway vehicles considers both the total train set length and the current railway infrastructure occupancy, including blocked parts of the infrastructure due to intervention of the interlocking system. In addition, the places where the train set movement direction is changed can be identified on each route found. Applications of the algorithms and of the mathematical model of the track layout are demonstrated on a model track infrastructure.

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Digital Modelling in the Railways

Lecomte¹

2021

Leveraging Applications of Formal Methods, Verification and Validation: Tools and Trends

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RailML application for description of railway interlocking systems

Cited by 3 publications

References 7 publications

Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Dynamic Automated Search of Shunting Routes within Mesoscopic Rail-Traffic Simulators

Digital Modelling in the Railways

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