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  • 1.
    Joborn, Martin
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering. Branschprogram Kapacitet i Järnvägstrafiken, KAJT.
    KAJT Projektkatalog 2022-03-312022Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Sammanställning av aktuella projekt inom Branschprogram Kapacitet i järnvägstrafiken (KAJT).

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    KAJT Projektkatalog 2022-03-31
  • 2.
    Joborn, Martin
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering. RISE Res Inst Sweden, Sweden.
    Ranjbar, Zohreh
    RISE Res Inst Sweden, Sweden.
    Understanding causes of unpunctual trains: Delay contribution and critical disturbances2022In: Journal of Rail Transport Planning & Management, ISSN 2210-9706, E-ISSN 2210-9714, Vol. 23, article id 100339Article in journal (Refereed)
    Abstract [en]

    In this paper we define new concepts and metrics for improved understanding of causes to un-punctual trains. The metrics are denoted delay contribution and critical disturbance. Delay contribution can be interpreted as how much a specific disturbance contributes to the delay of a train and the critical disturbances can be interpreted as the disturbances that made the train become unpunctual. The metrics are applied in a test case with trains in southern Sweden. The results show that the metrics can provide a complementary view regarding causes to unpunctu-ality compared to standard methods and are able to pinpoint disturbances that made trains become unpunctual and separate them from disturbances that have less impact on the punctu-ality. The methods are useable in the continuous work to improve railway performance e.g., by prioritizing maintenance work that give best impact on punctuality.

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    fulltext
  • 3.
    Peterson, Anders
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Bohlin, Markus
    KTH Royal Inst Technol, Sweden; Malardalen Univ, Sweden.
    Joborn, Martin
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering. RISE Res Inst Sweden, Sweden.
    Guest editorial for the best papers of RailNorrkoping 20192020In: Journal of Rail Transport Planning & Management, ISSN 2210-9706, E-ISSN 2210-9714, Vol. 15, article id 100204Article in journal (Other academic)
    Abstract [en]

    n/a

  • 4.
    Lidén, Tomas
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Joborn, Martin
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    An optimization model for integrated planning of railway traffic and network maintenance2017In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 74, p. 327-347Article in journal (Refereed)
    Abstract [en]

    Abstract Railway transportation systems are important for society and have many challenging and important planning problems. Train services as well as maintenance of a railway network need to be scheduled efficiently, but have mostly been treated as two separate planning problems. Since these activities are mutually exclusive they must be coordinated and should ideally be planned together. In this paper we present a mixed integer programming model for solving an integrated railway traffic and network maintenance problem. The aim is to find a long term tactical plan that optimally schedules train free windows sufficient for a given volume of regular maintenance together with the wanted train traffic. A spatial and temporal aggregation is used for controlling the available network capacity. The properties of the proposed model are analyzed and computational experiments on various synthetic problem instances are reported. Model extensions and possible modifications are discussed as well as future research directions.

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    An optimization model for integrated planning of railway traffic and network maintenance
  • 5.
    Svedberg, Victoria
    et al.
    Linköping University, Department of Science and Technology. Linköping University, Faculty of Science & Engineering. SICS Swedish ICT AB, Sweden.
    Aronsson, Martin
    SICS Swedish ICT AB, Sweden.
    Joborn, Martin
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering. SICS Swedish ICT AB, Sweden.
    Railway Timetabling Based on Cost-Benefit Analysis2017In: 19TH EURO WORKING GROUP ON TRANSPORTATION MEETING (EWGT2016), ELSEVIER SCIENCE BV , 2017, Vol. 22, p. 345-354Conference paper (Refereed)
    Abstract [en]

    The congestion on the tracks are increasing and to plan all requested trains on the tracks become harder. The infrastructure manager must have good methods for ruling out which operator gets its requested timetable. These methods must maximise the welfare and the decision must also be fully transparent the operators. The aim of this paper is to develop and evaluate an optimization model for welfare cost. The welfare cost is minimised while considering the detailed constraints of the railway infrastructure. The resulting welfare cost can be used to perform a cost-benefit analysis to provide a value of possible future traffic. The cost-benefit analysis can be the base for several kinds of analyses, like finding the optimal number of departures or the best departure times, finding the economic value of a certain timetable, which are exemplified. The optimisation model is tested on a part of the Swedish railway network covering the entire area operated by the regional train operator Ostgotatrafiken. (C) 2016 The Authors. Published by Elsevier B.V.

  • 6.
    Lidén, Tomas
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Joborn, Martin
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Dimensioning windows for railway infrastructure maintenance: Cost efficiency versus traffic impact2016In: Journal of Rail Transport Planning & Management, ISSN 2210-9706, E-ISSN 2210-9714, Vol. 6, no 1, p. 32-47Article in journal (Refereed)
    Abstract [en]

    The Swedish Transport Administration is introducing a new regime, called maintenance windows, for allocating train free slots reserved for maintenance tasks on the railway infrastructure. In this paper, a model for the assessment and the dimensioning of such maintenance windows is presented, which considers marginal effects on both the maintenance cost and the expected train traffic demand. The aim is to establish quantitative measures that can be used for comparing conflicting capacity requests from infrastructure maintenance and traffic operations on railway networks. The model is demonstrated in a cost benefit analysis for a real life case study on the Swedish Northern Main Line.

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    fulltext
  • 7.
    Kecman, Pavle
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Corman, Francesco
    Delft University of Technology, The Netherlands.
    Peterson, Anders
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Joborn, Martin
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Stochastic prediction of train delays in real-time using Bayesian networks2015In: Conference on Advanced Systems in Public Transport: CASPT2015, ETH Zurich, 2015Conference paper (Refereed)
    Abstract [en]

    In this paper we present a stochastic model for predicting the propagation of train delays based on Bayesian networks. This method can eciently represent and compute the complex stochastic inference between random variables. Moreover, it allows updating the probability distributions and reducing the uncertainty of future train delays in real time under the assumption that more information continuously becomes available from the monitoring system. The dynamics of a train delay over time and space is presented as a stochastic process that describes the evolution of the time-dependent random variable. This approach is further extended by modelling the interdependence between trains that share the same infrastructure of have a scheduled passenger transfer. The model is applied on a set of historical trac realisation data from the part of a busy corridor in Sweden.We present the initial results and analyse the accuracy of predictions as well as the evolution of probability distributions of event delays over time. The presented method is important for making better predictions for train trac, that are not only based on static, oine collected data, but are able to positively include the dynamic characteristics of the continuously changing delays.

  • 8.
    Joborn, Martin
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems.
    Leander, Per
    Transrail Sweden AB.
    Lidén, Tomas
    Transrail Sweden AB.
    Nordmark, Thomas
    LKAB.
    Energy efficiency and on-time performance for heavy haul trains2011In: International Heavy Haul Association Conference, Conference Proceedings, 2011Conference paper (Refereed)
    Abstract [en]

    The driving advisory system CATO has been installed at iron ore trains at LKAB, Sweden. CATO uses radio communication to communicate, e.g., the operational timetable and train status between the train control center and the trains. The advisories both enable the drivers to keep the operational timetable with very high precision and reduce the energy consumption by 20-25 percent. CATO’s speed advisories are easy to follow, and can easily be adapted to be relevant for heavy haul driving under extreme conditions.

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