The demand for transportation by railway has never been this high, and still rising. Making space for everyone who wants to use the tracks is a considerable challenge hence it’s important to have a consistent way of measuring the capacity and availability of the tracks in the system (Trafikverket, 2021). Capacity utilization is a general way of talking about the performance of the system. A good understanding of the capacity in strategic railway planning can be a helpful tool for decision support to evaluate the investment impact for a range of options (Liao et al., 2021). Capacity can be seen as a way of measuring how much of a certain infrastructure is used under a predefined amount of time. 

In railways, single track lines require more planning details compared to double-track lines. A single-track line section is generally a section of the line with bidirectional traffic where two trains cannot be at the same time, divided by passing loops. In 2022, approximately 80% of the Swedish railway network consisted of single tracks.

Various methods can be used to measure the capacity. The guidelines from the International Union of Railways (UIC) in their capacity leaflet 406 are one of the most widely used methods for capacity calculation and suggests a compression method where, for single tracks, the line is divided into sections and then the occupation time for each train between the passing loops is compressed and measured, in other words, a summary of the total run time. Landex (2009) applies the UIC406 method to a Danish context and adds dummy trains to the timetable to find out by which crossing stations the line should be divided into sections. Jamili (2018) extends the Landex approach but puts focus on the buffer times to find practical capacity. 

Swedish Transport Administration (Trafikverket) uses an analytical adaption of the UIC406 compression method to compute the capacity utilization for lines in Sweden including parameters such as number of trains, runtime, time for meetings and time depending on signaling system for critical sections of a line. This means that the calculations are quite general, not considering the order of the trains or where/if crossings occur. 

Weik et al. (2020) introduce a Matlab-based model to make timetable-dependent and -independent compression analyses for stations and double tracks. The suggested method is a hybrid simulation-timetable compression framework for capacity analysis based on the UIC 406 method where the analysis is performed on a microscopic level of detail to better account for dependencies between trains. The model uses infrastructure and timetable data imported from RailSys and checks for conflicts between trains assigned to the same block sections. 

With this study, we aim to continue developing the model from Weik et al. (2020) and explore the possibility of measuring capacity utilization for single-track sections using the planned timetable with the consideration of planned crossovers at passing loops. The results are compared with the output from the method that Trafikverket uses as well as UIC method. We also study the effect of having simultaneous entry at the passing loop or not.   

The model has been modified and given both a more overall compression design compared to the previous one by solving conflicts and compressing all trains at the same time but also more detailed to deal with partial releases of block sections as the train successively releases the block sections after passing by instead of, model-wise, occupying the full block section the whole time making the train crossovers possible in the model. Data is retrieved from Trafikverket’s RailSys model of 2022 as simulation logfiles and infrastructure information. 

The preliminary results from the case study so far show that the capacity utilization for the critical section of a single-track line in Sweden is slightly over-estimated by Trafikverket’s estimation using the analytical calculation and slightly underestimated compared to UIC method, in comparison to the timetable-based compression method developed in this work. We can also see the difference in using simultaneous entry at passing loops at single tracks. 

References

Jamili, A., (2018). Computation of practical capacity in single-track railway lines based on computing the minimum buffer times. J. Rail Transp. Plan. Manag. 8, 91–102. https://doi.org/10.1016/j.jrtpm.2018.03.002

Landex, A., (2009). Evaluation of Railway Networks with Single Track Operation Using the UIC 406 Capacity Method. Netw. Spat. Econ. 9, 7–23. https://doi.org/10.1007/s11067-008-9090-7 

Liao, Z., Li, H., Miao, J., Corman, F., 2021. Railway capacity estimation considering vehicle circulation: Integrated timetable and vehicles scheduling on hybrid time-space networks. Transp. Res. Part C Emerg. Technol. 124, 102961. https://doi.org/10.1016/j.trc.2020.102961

Weik, N., Warg, J., Johansson, I., Bohlin, M. and Nießen, N., 2020. “Extending UIC 406-based capacity analysis – New approaches for railway nodes and network effects”, Journal of Rail Transport Planning & Management, vol. 15, pp. 1—15. https://dx.doi.org/10.1016/j.jrtpm.2020.100199.