Integrated capacity assessment and timetabling models for dense railway networks

Mainline railways in Europe are experiencing increasing use as the worldwide demand for passenger and freight transport is growing across all transport modes. At the same time, much of the existing railway network is reaching its capacity and has become susceptible to disturbances. This thesis creates, optimizes, and evaluates railway timetables to promote more reliable, attractive and sustainable railway transport systems. In essence, we demonstrate that optimization, simulation and data analysis can be successfully applied to improving railway traffic planning and account for better infrastructure capacity use and increased level of service for passengers and freight operators.TRAIL Thesis Series no. T2017/9, the Netherlands TRAIL Research SchoolTransport and Plannin

Resilience in railway transport systems: a literature review and research agenda

Critical infrastructure networks, such as transport and power networks, are essential for the functioning of a society and economy. The rising transport demand increases the congestion in railway networks and thus they become more interdependent and more complex to operate. Also, an increasing number of disruptions due to system failures as well as climate changes can be expected in the future. As a consequence, many trains are cancelled and excessively delayed, and thus, many passengers are not reaching their destinations which compromises customers need for mobility. Currently, there is a rising need to quantify impacts of disruptions and the evolution of system performance. This review paper aims to set-up a field-specific definition of resilience in railway transport and gives a comprehensive, up-to-date review of railway resilience papers. The focus is on quantitative approaches. The review analyses peer-reviewed papers in Web of Science and Scopus from January 2008 to August 2019. The results show a steady increase of the number of published papers in recent years. The review classifies resilience metrics and approaches. It has been recognised that system-based metrics tend to better capture effects on transport services and transport demand. Also, mathematical optimization shows a great potential to assess and improve resilience of railway systems. Alternatively, data-driven approaches could be potentially used for detailed ex-post analysis of past disruptions. Finally, several rising future scientific topics are identified, spanning from learning from historical data, to considering interdependent critical systems and community resilience. Practitioners can also benefit from the review to understand a common terminology, recognise possible applications for assessing and designing resilient railway transport systems.Transport and Plannin

Estimating impacts of covid19 on transport capacity in railway networks

Due to the covid19 crisis, public transport (PT) systems are facing new challenges. Regarding restrictive measures such as physical distancing and the successive returning of passengers after the “intelligent lockdown”, significant lack of transport capacity can be expected. In this paper, the transport capacity of a PT network is assessed, using a mathematical passenger route choice and train scheduling model. By analysing the overall number of transported passengers and the resulting link and train utilization; the networks capabilities of facilitating different demands under capacity restrictions (e.g. physical distancing) are addressed. The analysis is performed on the Dutch railway network. The results show that at most 50% of the pre-covid19 demand can be transported, while most of the trains will be highly utilized reaching their maximum occupation. Thus, significantly more parts of the network are becoming highly utilized, leading to a more congested and vulnerable system than in normal conditions before covid19.Transport and Plannin

Stable and robust train routing in station areas with balanced infrastructure capacity occupation

Routing trains through busy railway station layouts is an important part of the timetabling process. For each train, a feasible route has to be determined to provide reliable operations, given the arrival and departure times at stations. In this paper, we propose a model for stable and robust train routing with the goal to minimize capacity occupation and maximize robustness. We define a multi-objective optimization problem and provide the heuristic RouteCare based on a max-plus automata model and a delay propagation model. We consider microscopic infrastructure to guarantee practical feasibility. The performance of the proposed algorithm is demonstrated on real-life instances of the Dutch railway network. The generated solutions outperformed the variants of RouteCare that independently maximize stability or robustness by 10.4% and 9.5%, respectively. In addition, RouteCare showed that even for the same number of resources used, a more robust route plan can be found that uses the station capacity more efficiently.Transport and Plannin

Passenger-centered vulnerability assessment of railway networks

The performance and behaviour of critical infrastructure in case of disruptions is an important topic and we are still lacking of insights. Due to disruptions, infrastructure becomes unavailable and may force the trains and passengers to adapt. In this paper, we introduce a problem of railway network vulnerability from the perspective of passenger flows and train operations. We propose a new Railway Network Vulnerability Model (RNVM) to assess the vulnerability of the system by finding the critical combination of links, which cause the most adverse consequences to passengers and trains. To solve this challenging problem, we present a RNVM framework, which combines two heuristics based on column and row generation with mixed integer linear programming, to efficiently model alternative passenger flows and infrastructure constraints. The developed framework provides the critical combination of links, the corresponding passenger flows, train routes and timetables. We demonstrate the performance of the RNVM framework on the real-world instance of a part of the Dutch railway network. The results show that the RNVM framework can efficiently reassign passenger flows and reroute trains during disruptions. The results also reveal that the critical links are highly demand dependent rather than a static feature of the networks topology. Finally, the computation times remain small when increasing the number of disrupted links as well as the size of the passenger demand, which allows fast and efficient network vulnerability assessment.Accepted Author ManuscriptTransport and Plannin

Microscopic Models and Network Transformations for Automated Railway Traffic Planning

This article tackles the real-world planning problem of railway operations. Improving the timetable planning process will result in more reliable product plans and a higher quality of service for passengers and freight operators. We focus on the microscopic models for computing accurate track blocking times for guaranteeing feasibility and stability of railway timetables. A conflict detection and resolution model manages feasibility by identifying conflicts and computing minimum headway times that provide conflict-free services. The timetable compression method is used for computing capacity consumption and verifying the stability according to the UIC Capacity Code 406. Furthermore, the microscopic models have been incorporated in a multilevel timetabling framework for completely automated generation of timetables. The approach is demonstrated in a real-world case study from the Dutch railway network. Practitioners can use these microscopic timetabling models as an important component in the timetabling process to improve the general quality of timetables.Transport and Plannin

Adjusting freight train paths to infrastructure possessions

This paper tackles railway timetabling with infrastructure work possessions. It introduces the integrated Passenger and Freight Train Timetable Adjustment Problem (PF-TTAP) which handles both passenger as well as freight trains. To deal with possessions, passenger trains are typically retimed, reordered or partially cancelled, while for freight trains it is important to reach their destination, possibly using an alternative path. Alternative paths for freight trains are generated using the k-shortest path algorithm. To solve the PFTTAP, a mixed integer linear programming (MILP) problem is developed to simultaneously retime, reroute and cancel trains in the network. The model aims at minimizing deviations from the original timetable and in particular selecting alternative freight paths with the least turning activities and noncommercial stops. The model was tested on the Dutch national railway network. The PF-TTAP model successfully created an alternative hour pattern satisfying all the railway stakeholders.Accepted author manuscriptTransport and Plannin

Resolving instability in railway timetabling problems

A growth of the railway transportation demand is forecasted in the next decades which needs an increase of network capacity. Where possible, infrastructure upgrading can release extra capacity, although in some cases this is not enough to satisfy the entire transportation demand unless optimised timetabling is performed. We propose a heuristic approach to develop a stable and timetable which maximise the satisfaction of transportation demand in situations where network capacity is limited. In case the demand cannot be fully satisfied, the model relaxes the given line plan and timetable design parameters. In addition, the aim is to maximize the satisfied demand by keeping as many train services as possible. We develop the mixed integer programming (MIP) model for minimizing cycle time to find an optimal stable timetable for the given line plan. The heuristic iteratively solves the MIP model and applies relaxation measures. We tested the model on the Dutch network. The results showed that the model can generate stable timetables by removing train services from the critical circuit, and also, higher transportation demand can be satisfied by additionally relaxing timetable design parameters.Transport and Plannin

Multi-objective periodic railway timetabling on dense heterogeneous railway corridors

This paper proposes a new multi-objective periodic railway timetabling (MOPRT) problem with four objectives to be minimized: train journey time, timetable regularity deviation, timetable vulnerability and the number of overtakings. The aim is to find an efficient, regular and robust timetable that utilizes the infrastructure capacity as good as possible. Based on the Periodic Event Scheduling Problem, we formulate the MOPRT problem as a Mixed Integer Linear Program (MILP). The ε-constraint method is applied to deal with the multi-objective property, and algorithms are designed to efficiently create the Pareto frontier. By solving the problem for different values of ε, the four-dimensional Pareto frontier is explored to uncover the trade-offs among the four objectives. The optimal solution is obtained from the Pareto-optimal set by using standardized Euclidean distance, while capacity utilization is used as an additional indicator to chose between close solutions. Computational experiments are performed on a theoretical instance and a real instance in one direction of a Dutch railway corridor, demonstrating the efficiency of the model and approach.Accepted Author ManuscriptTransport and Plannin

Resolving instability in railway timetabling problems

A significant growth of the railway transportation demand is forecasted in the next decades which needs an increase of network capacity. Where possible, infrastructure upgrading can provide extra capacity; although in some cases, this is not enough to satisfy the entire transportation demand even if optimised timetabling is performed. We propose a heuristic model to develop a stable timetable which maximises the satisfaction of transportation demand in situations where network capacity is limited. In case the demand cannot be fully satisfied, the model relaxes the given line plan and timetable design parameters. The aim is to keep as many train services as possible and reduce the level of service minimally. We develop a mixed integer linear programming (MILP) model for minimising the cycle time to find an optimised stable timetable for the given line plan. The heuristic iteratively solves the MILP model and applies relaxation measures. We tested the model on the Dutch network. The results showed that the model can generate stable timetables by removing train services from the critical circuit, and also, higher transportation demand can be satisfied by additionally relaxing timetable design parameters.Transport and Plannin