Mixed traffic with large speed differences between fast and slower trains consumesmore capacity and makes the system sensitive to disruptions. This article focuses onadequate train configuration for increasing the top speed for express trains like theGreen Train and how that affects capacity on lines with heterogeneous traffic.Microscopic simulation of a future timetable selected by criteria revealed by analyticaltimetable analysis for a chosen structure of services combines the advantages of twomethods and makes it possible to reveal relevant characteristics for different alternatives.Punctual short stops through better train layout and skip-stop operation forregional trains are a few of the measures that are shown to have compensating effectsfor the increase in capacity utilisation and can reduce disruptions. Although it ispossible to reduce the perturbations by means of different measures, the basic problemwith mixing fast and slower trains on the same line still remains.

Capacity shortfalls on railway lines often lead to disturbances in operation and limited possibilities for traffic increase. Static and dynamic characteristics describing the capacity are an important input for cost-benefit analysis. However, they are rarely used in economics. At the same time, economic parameters are hardly ever included in capacity studies.

This paper focuses on measurements of dynamic timetable and capacity characteristics. The purpose is to identify the determining variables that influence capacity and by the railway users. Is simulation a useful method to reveal the decisive parameters? A structure for economic evaluation of the identified characteristics is to be developed.

Using mixed methods data analysis, relevant capacity characteristics are retrieved and relationships between these, static criteria and socio-economic impacts identified. The study is mainly based on passenger rail traffic between Stockholm and Gothenburg in Sweden and the focus is on long-distance passenger traffic. Simulation is shown to be advantageous as future scenarios can be evaluated concerning operational parameters – which according to the results of this paper are important to travelers. A structure for a future model where timetable analysis and microscopic simulation are used to reveal relevant capacity characteristics based on the findings is presented.

Assessment of capacity for highly-used railways is an important and challenging task. This paper describes a method for evaluation of timetables based on capacity and economic assessment. Common methods from both fields are combined. For developing and analysing purposes, the model is first tested with historical delay data for express trains on a double-track line with dense, mixed traffic in Sweden. An assessment aiming to compare the departures is made by combining common weights for different variables. Differences in the results based on the model structure are discussed. In the second step, microscopic simulation is used to reveal delay characteristics of timetable alternatives that are then compared and discussed in a similar way to step 1.

The presented method using simulation makes it possible to reveal and evaluate characteristics that are important for both timetable planning and economic analysis, for example evaluation of strategies. Timetable and delay times are important input variables that affect the travellers' choice. Using simulation and other methods from capacity planning gives the opportunity to find characteristics for analysing alternatives and improve economic evaluation, at the same time as the use of economic parameters provides more possibilities to make a relevant capacity analysis.

On deregulated railway markets, efficient capacity allocation is important. We study the case where commercial trains and publicly controlled traffic (“commuter trains”) use the same railway infrastructure and hence compete for capacity. We develop a method that can be used by an infrastructure manager trying to allocate capacity in a socially efficient way. The method calculates the loss of societal benefits incurred by changing the commuter train timetable to accommodate a commercial train path request, and based on this calculates a reservation price for the train path request. If the commercial operator's willingness-to-pay for the train path exceeds the loss of societal benefits, its request is approved. The calculation of these benefits takes into account changes in commuter train passengers’ travel times, waiting times, transfers and crowding, and changes in operating costs for the commuter train operator(s). The method is implemented in a microscopic simulation program, which makes it possible to test the robustness and feasibility of timetable alternatives. We show that the method is possible to apply in practice by demonstrating it in a case study from Stockholm, illustrating the magnitudes of the resulting commercial train path prices. We conclude that marginal societal costs of railway capacity in Stockholm are considerably higher than the current track access charges.

In Sweden and other countries it is not an uncommon practice that freight trains depart more or less on-demand instead of strictly following a pre-planned timetable. However, the systematic effects of freight trains departing late or (in particular) early has long been a contested issue. Although some microscopic simulation tools currently have the capability to evaluate the effect of freight trains departing before schedule, it has yet not been established how macroscopic simulation tools, capable of fast simulation of nation-wide networks, can manage such tasks. This paper uses a case study on a line between two large freight yards in Sweden to investigate how the results of microscopic and macroscopic simulation, represented by two modern simulation tools, differ when it comes to this particular problem. The main findings are that both the microscopic and the macroscopic tools replicated the empirical punctuality fairly well. Furthermore, allowing early departures of freight trains increased overall freight train punctuality while the passenger train punctuality decreased slightly, as determined by both tools. The results are encouraging, but further studies are needed to determine if macroscopic simulation is on-par with microscopic simulation.

Allocating train runs usually focuses on avoiding conflicts while adjusting requested paths as little as possible. However, a conflict-free timetable is not a guarantee for high reliability. The aim of this article is (1) to estimate the efficiency of alternative timetable slots by comparing different, but similar express train departures as if they were alternative slots and (2) to analyse effects of changes in a timetable with long and short-distance services competing for capacity. For this purpose, timetable performance indices are proposed considering timetable and reliability criteria with demand. These indices were computed based on empirical and simulated data. The methodology is applied in case studies for the Swedish Western and Southern Main Lines and is shown to be relevant to capacity allocation and helpful in the timetabling process, especially when passenger demand is known. Simulation with the microscopic tool RailSys and the macroscopic PROTON is used to estimate how timetables on double track lines with dense, heterogenous traffic react to disturbances. With the suggested model configuration, estimated delay and travel demand have larger impact on the goodness of a timetable than travel times. Both the micro and macroscopic simulation tools are shown to be useful, but the more detailed RailSys is more adequate for estimating the goodness of a timetable focusing on train slots and small changes.