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  • 1.
    Andersson, Matts
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science. WSP Analysis & Strategy Sweden.
    Berglund, Moa
    Floden, Jonas
    Persson, Christer
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
    Waidringer, Jonas
    A method for measuring and valuing transport time variability in logistics and cost benefit analysis2017In: Research in Transportation Economics, ISSN 0739-8859, E-ISSN 1875-7979, Vol. 66, p. 59-69Article in journal (Refereed)
    Abstract [en]

    The freight transport system is subject to delays and disturbances, which influence investment and planning decisions made by governments and infrastructure authorities. Traditionally relying on Cost Benefit Analysis (CBA) they are dependent on correct and up-to-date input data. So far, little success has been reached in estimating the effects of disturbances for freight. This paper aims to contribute to the understanding of disturbances in freight transport by reviewing and classifying the effects occurring due to transport time variability (TTV) and to suggest a calculation model to estimate the value of transport time variability (VTTV). In order to validate the model and its usability it was successfully tested in a case study for a large Swedish retail company. The effects of delays can be divided into four main types: System Killers, Catastrophic Events, Expected Risks, and Contingencies, of which the last two are relevant for VTTV. The model applies these in a two-step cost function with a fixed and variable part, building on previous studies of VTW for passenger transport based on the scheduling utility approach. A main theoretical result is that the estimation of VTTV is derived mathematically independently of which measure that is chosen for the quantification of TTV.

  • 2. Jiang, S.
    et al.
    Persson, Christer
    KTH, School of Architecture and the Built Environment (ABE), Transport Science.
    Malfunction in Railway System and Its Effect on Arrival Delay2016In: Current Trends in Reliability, Availability, Maintainability and Safety, Pleiades Publishing , 2016, p. 243-252Chapter in book (Refereed)
    Abstract [en]

    In this research project, we have established a set of advanced statistics models that quantify the cause-effect relation between infrastructure failures and train delay. The major model we employed in this project is called the “Wiener process model”, and we are the first researching team to implement the Wiener-process model into traffic analysis area with large scale network data in Swedish railway. The data we based our research on includes a 1) train movement record database—TFÖR 2) infrastructure error reporting system—0FELIA 3) railway facility database—BIS. For TFÖR alone, there is a 27-million data record over 5 different rail classes (from rail class 1, major railway around big city areas to rail class 5 least loaded rail) and 3 different passenger train types (x2000, regional train and commuter train). By merging the database listed above, a specified wiener process model has been estimated for the primary delay caused by system errors and the secondary delay by interaction of trains. The model also quantifies the effects of characteristics of railway system over different rail classes and operation manners. In addition, the Wiener process model also enable further research to derive the fundamental relation between capacity, speed and density (inverse function of time gap) in railway context. Switzerland.

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