Many railway networks suffer from high capacity utilisation. For scheduling all services, adjustments to the desired slots are often needed. Such adjustments might lead to longer travel times, crowded trains, longer waiting times for boarding and for transfers. All of this has an important socio-economic impact on both travellers and train operators. This raises the question of the socio-economic assessment of changes in commuter train timetables including transfers. Thus, the aim of this study is to evaluate the effects of adjustments of commuter train timetables on the traveller (i.e. consumer costs) and the train operator (i.e. producer costs). These costs are estimated based on all train trips and operations in the network. In a case study, the effect of changes in departure times (resulting in non-regular interval timetables) is analysed. Further, the price of cancelling a two-way service during different times of the day is compared. The results show that changing departure times can both decrease and increase the total costs, and that regularity for parallel services might not be as important as expected if it is kept for each separate service. For the second study, waiting times for transfers were indicated to have a (too) large impact which can lead to misleading results and might be adjusted in future work. The model is adequate for such kind of questions but needs some more adjustments. For railway networks with dense and heterogeneous traffic (as is the case in Sweden), the contributions of this model are useful for making the challenging timetabling process easier and commuter train services less costly.

On highly used railway lines with heterogeneous traffic, timetabling is challenging. In particular, the limited existing capacity means that to guarantee an acceptable level of quality, the infrastructure manager must cancel some train services on the expense of others. In this article, we study the conflict between commercial long-distance trains and subsidized commuter trains with a socio-economic perspective (i.e. travelers and train operators). The study attempts to answer the following question: What is the socio-economic effect of modifying the timetable of a commuter service?The case study treats the commuter train services in Stockholm. Trip data was collected from the local commuter train operator. An entropy maximization-based model was implemented to estimate the dynamic network Origin-Destination (OD) matrix. This dynamic matrix, of one full working day, was then used to estimate the number of travelers per train, and further converted for use in the microscopic simulation tool RailSys. Travel and waiting time are estimated for each OD pair and with that the generalized costs for the travelers and operators. The effect of crowding in the trains is included in the estimation. The article can be considered as an initiation to a novel method to calculate effects of changes in commuter train timetables. This novel approach enables to price commercial train slots in the capacity allocation process such as in an auction. It provides a new way to estimate the local train operator´s valuation of the different parameters (i.e. waiting, travel time and interchanges). Using RailSys for the estimation of times makes it possible to include capacity aspects that normally are difficult to reveal.