On railway lines with scarce infrastructure capacity, allocation methods allow for the assessment of the capacity requests from railway undertakings. The European Commission introduced a regulation to ensure a uniform approach to capacity allocation across all member states through socioeconomic and environmental criteria. However, relevant experiences and methods related to such criteria are hard to come by across Europe, meaning that such criteria' impact on capacity allocation is unknown. In this paper, we provide a method that applies the European criteria and can give insight into the possible impact of this new way of allocating capacity. The railway line Deventer – Bad Bentheim case study allows for the application of the method and defines its possible impacts. Compared to the current Dutch approach of distributing capacity scarcity, open-access train services have higher chances of receiving capacity access. The result shows how railway undertakings will behave more beneficially to society during capacity allocation procedures following the implementation of the method. Recommendations to improve the method are to reduce the number of assumptions, provide an inflation correction across all monetary parameters and consider using minimal frequencies.

The planning of railway operations is a very complex process, in which timetables and other logistical plans need to be both reliable and robust to effectively prevent and cope with disturbances. However, research in the robustness of initial stabling plans, designed in an earlier planning phase, during the following planning phases, has been lacking, with the models created in research in the Train Unit Shunting Problem (TUSP) being generally deterministic in nature, even though stabling plans could quickly become infeasible when the stabling demand in the form of arriving and departing trains changes.
This thesis therefore proposes a definition of the robustness of an initial stabling plan to changes in the stabling demand, such as changes in train lengths, as well as provide an assessment method of said robustness. The created Robustness Assessment Model (RAM) first generates an initial stabling demand and stabling plan, then performs a Monte Carlo simulation to generate a set of stabling plans created for variations of the initial stabling demand, based on changes in stabling demand such as train length. Finally, the RAM estimates the robustness of the initial stabling plan by analysing the differences between the initial and these generated stabling plan variations and how efficiently the initial plan is able to change to these plans to optimally facilitate the variations of the initial stabling demand.
Running this model across three locations, each with three capacity utilisation scenarios, has shown that the model is able to estimate the robustness of an initial stabling with acceptable confidence, and furthermore is able to give insight into how capable the stabling plan creation method is in generating a robust solution. Furthermore, the RAM can also be used to investigate patterns in stabling plans which could predict the robustness of said stabling plans. Current shortcomings to the RAM are its relatively long runtime, the simple stabling plan creation process used in the RAM, and that only one-sided stabling yards without servicing scheduling have been incorporated. Further research is therefore recommended for extending the RAM with other stabling yard layouts and the scheduling of services, as well as improve the stabling plan generation process to take more constraints into account.

In order to track the speed profile, a case study using a linear quadratic regulator (LQR) is addressed in this paper. A time-invariant nonlinear train motion model is constructed. To apply LQR, the quadratic term of the aerodynamic drag and the rolling mechanical resistance is linearized. Gradient resistance, curve resistance, and other environmental disturbance are not considered in this paper. An LQR algorithm with constraints is proposed to track a given reference speed profile. Maximum error and cumulative error are used in the evaluation of the tracking performance. The tracking results in plots, parameters tuning, and performance analysis are shown. The results show that the proposed LQR algorithm is able to track the given 1200 seconds speed profile, the cumulative error can be controlled within 4.7478m/s, and the maximum absolute error is 0.90839m/s. The output of the control variable u is also given.

Public transport is important for society, it provides accessibility to opportunities. Accessibility is not distributed evenly. Some inhabitants are disadvantaged, which has negative impacts on society. The distribution of accessibility between inhabitants can be measured with transport equity. The PT network should be improved in order to reduce the disadvantage of inhabitant groups. It is not defined how this could be done for regional PT networks. A six step assessment methodology is created for this purpose. The assessment method addresses what objective focus should be applied to, what improvements are possible in PT networks, what measures should be applied and what the equity effects of these measures are. Application of the assessment method yields that substantial equity improvements are possible within the Alkmaar – Den Helder railway corridor. Marginal equity improvements are achieved by changing rolling stock, significant improvements with local doubling of single track and substantial improvements when additional stations are opened. The assessment methodology is also able to identify the presence of trade-offs between inhabitants by mutual comparison.

Despite advanced communication, monitoring, and control facilities, train operations are still subject to uncertainties that can disturb train services, cause delay to multiple trains, and propagate through the network. One option is to mitigate delay propagation in the timetable design by adding buffer time to the minimum difference between the time two successive train of either direction enter a section. It is still common practice to design buffer times based on a deterministic value, decreasing operational capacity and requiring large amount of manual checking by planners. Existing approaches to effectively allocate buffer time in timetables lack flexibility and require an initial timetable. In this paper, a data-driven approach for determination of buffer time planning rules suitable for usage in an initial timetable is presented. These planning rules are not necessarily generic, but rather depend on timetable characteristic. Two metrics that describe delay propagation, mean secondary delay and hindrance percentage, are extracted from literature and predicted in a regression analysis with the use of timetable characteristics related to headway situations of two succeeding trains. The results of the regression analysis on a case study of the Dutch railway network between Haarlem, Leiden Centraal and Schiphol Airport are used to determine the amount of scheduled buffer time that would ensure a certain amount of hindrance percentage given a specific headway situation. The results show that the mean secondary delay and hindrance percentage for various headway situations can both be predicted with an accuracy of 90.7\% based on timetable characteristics and is quite heterogeneous. Mean secondary delay appeared not significantly impacted by the scheduled buffer time, contrary to hindrance percentage which is significantly influenced by the scheduled buffer time.

Moving block signalling promises a significant reduction of the infrastructure occupation compared to a fixed block system, such as NS’54/ATB. This is mainly caused by a strong reduction of the approach and running time. However, to assess the capacity gains track occupation data, such as blocking times are needed. ETCS L3 Moving Block is still in development, so gathering data out of daily operations is not possible. Also gathering moving block data out of simulation isn’t always a convenient solution. For example, in simulation software FRISO, used at ProRail, ETCS L3 Moving Block is not (yet) implemented.
With infrastructure data, rolling stock parameters and planned time-distance data, blocking times for a moving block signalling system can be estimated. The model presented in this thesis has an average error of 0.87s to the blocking time. In 95% of the cases the error is within a range of (-3,3) seconds. Given that ProRail plans with a precision of 6 seconds, it can be concluded that the model both precise as accurate. With the blocking times of all trains, bottlenecks in both railway corridors and complex nodes can be identified. One could sum all blocking times per block and consider blocks with the highest summed blocking times as bottleneck. However, this can only be applied for homogeneous traffic situations. Another approach is identifying bottlenecks by the shortest buffer time between two trains, also called a critical block. This can be applied for both homogeneous as heterogeneous traffic situations. An advantage is that it is not needed to split corridors into line sections. One could analyse a whole network at once and identify bottleneck at a microscopic level. By keeping the same timetable, the buffer time between two trains increases on average by 75 seconds (60%) using moving block over NS’54.

Due to the continuous expansion of the urban scale, the urban metro transportation system also needs to be constantly updated, especially those cities that need to carry mega-events. Larger carrying capacity, better collaboration mode and more optimized operation mode are required to handle the sudden increase in travel demand. The ever-growing micromobility system and the multimodal transport system of micromobility and other public transportation methods can well meet this trend.

This thesis aims to develop a multimodal transport optimization model that takes full advantage of the micromobility mode. This thesis, from the perspective of the traffic system administrator, explores the influence of micromobility on the cost of the entire traffic system under the premise of maintaining the normal operation of the metro system after micromobility joins the traffic system at the same level as the metro.

Firstly, through literature review, the research object is determined to be a representative shared bike in micromobility mode. The way to deal with the excessive travel demand brought by mega-events is to add shared bikes to the transportation system with the same status as the metro on the basis of maintaining the normal operation of the metro system, and cooperate with the metro system to meet the demand.

Secondly, the research methods are qualitative research and quantitative research. In the qualitative research, model design, adjustment and optimization are carried out in combination with actual experience to realize the design of the multimodal transport system of shared bike and urban metro system. In quantitative research, this thesis describes a case study area based on real condition and proposes six scenarios. And through demand forecasting and parameter changes, this thesis explores the situation that only metro participates in the transportation system, and micromobility mode participates in the transportation system with metro with different parameters, etc., under the premise of meeting the excessive travel demand brought by mega-events, impact on total travel costs.

Through model optimization and scenario verification, it is concluded that when the micromobility mode participates in the transportation system in a reasonable way, the multimodal transport system will be able to reduce the total cost, and the degree of reduction is related to the characteristics and parameters of the mode.

Railways in Europe need to reduce CO₂ emissions and energy usage to contribute to sustainability. One of the measures that railway undertakings can apply with low investment cost and both high reductions in CO₂ emission and energy consumption, is energy-efficient train trajectory optimization. Another efficient measure is incorporating energy-efficiency in the timetable design. The aim of this thesis is to incorporate energy-efficient train trajectory optimization in the timetable design in order to improve the potential for energy-efficiency of railways. The thesis develops and applies models for the energy-efficient train
control problem for a single train over (multiple) stops with both mechanical and regenerative braking behavior. In addition, energy-efficient train trajectory optimization is incorporated in timetabling by formulating and developing algorithms for a multiple-objective optimization problem applied on a corridor with multiple interacting trains.@en

To better govern inventory control of spare parts in tandem with scheduling of maintenance operations in a railway setting, a Railway Spare Inventory & Maintenance Scheduling (R-SIMS) model is developed. To suit the railway industry setting the model includes an inventory control strategy which envokes continuous monitoring and a reorder level as well as an order up-to level. Moreover a condition based maintenance (CBM) strategy is used with periodical inspections. These strategies are combined in a simulation model which assumes stochastic step-wise deterioration of parts as well as stochastic lifetime lengths to predict the expected cost per part per period. The three maintenance scheduling and spare inventory decisions to be minimised in terms of their resulting costs are 1) when to replace parts based on their condition, 2) when to buy new spare parts and 3) how many spare parts to procure at each order. These decisions are represented by values of the three decision variables: the CBM threshold L_p, the reorder level s and the order up-to level S. The minimisation of these decision variables is performed through surrogate modelling, a branch of machine learning optimisation techniques which deals with complex black-box functions. It does so by running experiments and estimating a surrogate function which in turn is optimised mathematically. Multiple surrogate modelling methods are compared in experiments to test their performance, speed and stability. These experiments showed that the Tree-structured Parzen Estimator algorithm as used in the HyperOpt Python library was one of the best performing methods (only rivaled by the MVRSM algorithm), moreover it was shown to be the fastest as well as the most stable of the tested algorithms for this particular problem application. This research contributes to the existing theory by creating a modelling framework for the joint optimisation of spare inventory and maintenance scheduling decisions which is specifically tailored to the railway context and includes possibilities for minimal maintenance. In practice this model can be used by maintenance providers to increase the financial success of their maintenance operations and by infrastructure managers to increase insight into their maintenance providers' operations.

In busy passenger railway networks, a large amount of trains have to be parked in shunting yards off the mainline every night, where they will be cleaned, maintained, sorted and parked. This problem is known as the Train Unit Shunting Problem (TUSP), which is a hard combinatorial optimization problem faced by railway operators. The TUSP is currently solved using human heuristics, which is difficult and time-consuming. Reinforcement learning approaches have been developed in the last few years to efficiently approach this problem. In this research we develop, in a multi-agent deep reinforcement learning framework, an heuristic for random exploration to efficiently search the state-action space and two heuristics for train routing strategies, which aim at improving the performance and quality of the produced route plans. On one hand, we develop the Type-Based Routing Strategy, based on the idea of parking trains of the same rolling stock type on the same tracks. On the other hand, we develop the In-Residence Time Routing Strategy, based on parking trains ordered according to their departure time. Both routing strategies consists of four components: (1) standard parking rules, (2) combination and split rules, (3) conflict resolution rules and (4) unnecessary movements rules. The goal is to incorporate information from the logistics side of the problem into the framework. We demonstrated the performance of the heuristics developed in two real-life cases in the Dutch railway network. The results of the experiments carried out demonstrate the potential of the resulting framework to produce more efficient route plans and to adapt to different problems designs such as different matching problems types and different shunting yards.

Technological innovations in the Dutch railway sector, such as ERTMS and the 3kV power supply system make it possible to increase the efficiency, effectivity and speed of the railway system in the upcoming decades. The implementation of systems such as ERTMS and 3kV is a lengthy process. The new systems will therefore operate alongside the old systems (ATB-EG and 1.5kV) for a long period of time. Between the old and the new system, operational transitions are required. The number of operational will therefore increase in the coming years. Some of these transitions from one system to another system turn out to be prone to failures and disruptions. When an operational transition fails, this can cause considerable delays on the railway network. Especially when multiple operational transitions are close together and occur nearly simultaneously, the risk of failures in one of these transitions is present. When operational transitions are combined, a failure in one transition can have large effects on another operational transition that is about to take place. Operational transitions are defined by two characteristics. Firstly, they are physical locations in the rail infrastructure. Secondly, operational transition require the driver to switch between two systems, or to change his/her behaviour significantly. The aim of this thesis is to investigate the effect of operational transitions on the reliability of train operations. The magnitude of the impact of operational transitions on the reliability of train operations is often unclear. This thesis contributes to scientific literature by examining a sizable number of operational transition types and providing an initial insight into the effect of these transitions on railway operations. For society in general and for ProRail in particular, the findings of this research can contribute to a better understanding of operational transitions. Using the acquired knowledge, ProRail can take measures that increase the reliability of operational transition passages, thereby increasing the punctuality of train services.

Computers are preferred above humans when dealing with information processing because of the great memory and fast computing times. The use of algorithms within complex planning processes is an interesting research field. These algorithms should help human planners with the planning process and therefore are called Planning Assistance Tools (PAT). However, the implementation of a PAT often fails because of the lack of acceptance by human planners. The lack of acceptance is often linked to the fact of human aspects that are missing within the PAT. This research provides a methodology to identify the missing aspects using a developed PAT, real-life planning assignments and experienced planners within the railway node planning. Based upon empirical experiments, a list of aspects is formulated that are translated to extensions that are implemented in the PAT. The application of such a method to a real-life case has not yet been mentioned in literature before. The research proves that the implementations have a positive effect on the quality of the solution provided by the PAT, while not harming the performance of the solution. Planners seem to better understand the solution of the PAT and the decisions made by the PAT, which increases the level of trust and the level of acceptance. The method used to identify aspects and implement them might be applicable within the industry for planning tools that are already developed, but not yet implemented because of missing acceptance of human planners.

Block signalling and Automatic Train Protection are two of the main railway safety systems to control the risk of train accidents. The combination of the existing Dutch block signalling system NS’54 and ATP-system ATB-EG is functioning well, but has some drawbacks. The systems have been designed over 60 years ago with proven technology of that time. Components are old and will have to be replaced in the near future. The safety functionality of the legacy systems is limited. Moreover, the capacity of the Dutch railway network with NS’54/ATB-EG is almost fully used while demand grows. Solutions are required to match the demand growth. The European Rail Traffic Managements System (ERTMS) is proposed to be the new standard European safety system. Train control is included in the European Train Control System (ETCS). It offers benefits in the form of interoperability, increased safety, speed, capacity and/or reliability over the national system. ERTMS/ETCS Hybrid Level 3 is an integrated cab-signalling and train protection system that combines train position information, onboard train integrity confirmation and trackside train detection. Compared to the legacy system NS'54/ATB-EG and the proposed system ERTMS/ETCS Level 2 it offers more railway capacity and allows for a reduction in trackside train detection. This thesis shows that the infrastructure occupation can drop from 84% to 66,7% when implementing ERTMS/ETCS Hybrid Level 3. Reducing the amount of trackside train detection to the minimum and transitioning from track circuits to axle counters can result in a decrease of track unavailability related to train protection systems of over 40% compared to the existing configuration.

Railway systems are vulnerable to unexpected disruptions, which usually result in track blockages for a few hours. In practice, disruptions are handled manually and the resulting impact to passengers is rarely considered. To enable disruption management more efficiently, operator-friendly and passenger-friendly, this thesis develops mathematical models and solution methods for dynamic passenger assignment, timetable rescheduling, and the integrated passenger assignment with timetable rescheduling during disruptions. @en

Railways are facing the challenge to simultaneously increase the capacity and the operational performance of their network. Automatic train operation (ATO) can be one of the technologies to increase the capacity of the railway network. The specifications for ATO over the European Train Control System (ETCS) automatic train protection system have been defined. However, testing is taking place over legacy automatic train protection systems , such as ATBNG, as well. ATO requires information from the automatic train protection system. The goal of this master thesis is to determine the data gap between ETCS and ATBNG in relation to ATO. First a generic ATO model is developed from literature. This model presents the information required and produced by ATO. The model is used as a framework for the analysis of ATO over ETCS and ATO over ATBNG. This analysis resulted in a conceptual model of both ATO over ETCS and ATO over ATBNG. The conceptual model shows that ATBNG can provide the required information if the ATBNG operational envelope is used as the relevant safety envelope. However, currently the operational envelope of the NS’54 signalling system is the relevant safety envelope. Additional information is required to allow ATO to determine the NS’54 operational envelope. Furthermore, ATBNG is not capable of presenting ATO information to the train driver. A new ATO DMI is required. Moreover, the ProRail traffic management system is not yet capable of providing ATO with the required information for both ATO over ETCS and ATO over ATBNG. To validate the conceptual ATO over ATBNG model three case studies have been worked out. The study performed for this master thesis is an exploratory study, therefore validation of the findings and assumptions is required.

Even though rail is more energy efficient than most other transport modes, the enhancement of energy efficiency is an important issue for railways to reduce their contributions to climate change further as well as to save costs and enlarge competition advantages involved. This thesis is motivated by the challenges in improving energy efficiency of train operations. The main objectives are to develop the modelling and solution methods for the train trajectory optimization problem to improve the model accuracy and the computation time, to apply the methods in a train driver advisory system development, and to develop a multi-train trajectory optimization method to solve the delay recovery and the energy-efficient timetabling problem. @en