OpenTrack simulation model files and output dataset for a copenhagen suburban railway

Harrod, Steven; Cerreto, Fabrizio; Nielsen, Otto Anker

doi:10.1016/j.dib.2019.103952

Cited by 8 publications

(7 citation statements)

References 1 publication

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“…The above-mentioned rail traffic simulations can be applied in conjunction with various specialized simulation tools, which can employ different rail infrastructure submodels [1,15,16,22]. Examples of relevant simulation tools used for such simulations include OpenTrack [23,24], RailSys [25,26,27], Villon [28], MesoRail [4], NEMO [29], PULSim [30], Simarail [31] etc. Such tools apply the same level of detail of investigation (microscopic, mesoscopic, or macroscopic) within one simulation model.…”

Section: Related Literaturementioning

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: Related Literaturementioning

confidence: 99%

Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Kavička

Diviš

2022

IEEE Access

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“…is is a widely used software enabling discrete and continuous approaches to simulation to be combined [8]. It can be used in the modeling of both high-speed lines [9] and conventional lines [10] as well as suburban lines [11,12].…”

Section: State-of-the-artmentioning

confidence: 99%

Impact Assessment of Interlocking Systems on Single-Track Railway Lines as a Measure Leading to Resilient Railway System

Bažant

Bulíček

2022

Journal of Advanced Transportation

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Railway systems should be resilient to play a key role in creating sustainable development. Single-track railway lines are seen as potential bottlenecks due to limited capacity. More advanced railway interlocking systems (such as ETCS or satellite-based control systems) are being developed. On the other hand, the installation of these interlocking systems is a complex and time-consuming and costly task. For this reason, it is necessary to recognize the impact of potentially installed system with capacity, stability of timetable, quality, and other associated effects. The assessment is based on a set of simulation experiments using stochastic microscopic simulation model in the OpenTrack software tool. The focus is on railway operation with automatic block and automatic line blocking systems. If these two systems will have positive capacity effects, it is a basic presumption also for systems such as moving block (e.g., ETCS L3) to be effective. Research has shown that the significance of such measures can be best supported by linking to a matching timetable concept that will make full use of the benefits offered by these interlocking systems. The results reached in this research should be potentially applied, for example, by prioritizing of single-track railway lines for possible installation of such interlocking system. It can be achieved based on the capacity and operational effects examined.

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“…Dataset [27] contains data on four small case scenarios for the timetable scheduling fairness problem. Dataset [28] contains simulation data for the evaluation of performance and delays of a suburban railway line and was published in delay propagation study [29]. The OpenTrack model simulates train departures according to a timetable and calculates speed and positioning of trains while taking into consideration safety rules, signaling and railway line constraints.…”

Section: Passenger Transportmentioning

confidence: 99%

A Systematic Review of Artificial Intelligence Public Datasets for Railway Applications

et al. 2021

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The aim of this paper is to review existing publicly available and open artificial intelligence (AI) oriented datasets in different domains and subdomains of the railway sector. The contribution of this paper is an overview of AI-oriented railway data published under Creative Commons (CC) or any other copyright type that entails public availability and freedom of use. These data are of great value for open research and publications related to the application of AI in the railway sector. This paper includes insights on the public railway data: we distinguish different subdomains, including maintenance and inspection, traffic planning and management, safety and security and type of data including numerical, string, image and other. The datasets reviewed cover the last three decades, from January 1990 to January 2021. The study revealed that the number of open datasets is very small in comparison with the available literature related to AI applications in the railway industry. Another shortcoming is the lack of documentation and metadata on public datasets, including information related to missing data, collection schemes and other limitations. This study also presents quantitative data, such as the number of available open datasets divided by railway application, type of data and year of publication. This review also reveals that there are openly available APIs—maintained by government organizations and train operating companies (TOCs)—that can be of great use for data harvesting and can facilitate the creation of large public datasets. These data are usually well-curated real-time data that can greatly contribute to the accuracy of AI models. Furthermore, we conclude that the extension of AI applications in the railway sector merits a centralized hub for publicly available datasets and open APIs.

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OpenTrack simulation model files and output dataset for a copenhagen suburban railway

Cited by 8 publications

References 1 publication

Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Impact Assessment of Interlocking Systems on Single-Track Railway Lines as a Measure Leading to Resilient Railway System

A Systematic Review of Artificial Intelligence Public Datasets for Railway Applications

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