Search

The Hyperloop concept, pod speed competitions and current project developments have recently attracted much publicity. In this paper the transport technology of the vacuumed tube transport project Hyperloop is assessed through a system analysis of its principal aims, functional design, transport capacity and demand in comparison with existing commercial airlines, high-speed rail, and Maglev lines. First, the potential for high-speed long-distance travel demand for Hyperloop based on existing airline transport volumes between major airports in Germany on the one hand, and the proposed Hyperloop link from Los Angeles to San Francisco in California on the other, is assessed in general terms. Second, the technical feasibility of the proposed Hyperloop concept for vehicle design, capacity, operations, propulsion, guidance, energy supply, traffic control, safety, alignment, and construction is discussed in more detail. Third, possible environmental impacts and uncertain investment, operating and maintenance costs for implementation of a Hyperloop line are described. Finally, the risks for further Hyperloop project development and the need for more transparent research are emphasized.

Train unit routing problem determines the number of train units needed to carry out involved trips, which is a significant part of railway operation cost. In this paper, we focus on high-speed train unit routing problems, in which maintenance resource constraints both on time and distance are taken into account. Based on a connection network, this paper first proposes a general train unit routing model. Then, the general model is specialized to meet the circulation and maintenance conditions of high-speed train units in China, which is based on a special connection network with a two-day time horizon. A strategy is proposed to reduce the scale of the connection network, which improves the model’s solvability. Furthermore, an extension on multi-depot train unit routing problem is discussed. Finally, numerical experiments based on the real data of Chinese high-speed railway are carried out to verify the effectiveness and efficiency of the proposed mode and method.

Railway traffic is operated according to a detailed schedule, specifying for each train its path through the network plus arrival and departure times at its scheduled stops. During daily operations, disturbances perturb the plan and dispatchers take action in order to keep operations feasible and to limit delay propagation. This article presents a thorough assessment of the possible application of an optimization-based framework for the evaluation of different timetables and proactive railway traffic management over a large network, considering stochastic disturbances. Two types of timetables are evaluated in detail: “ regular” and “ shuttle” timetables. The former is the regular plan of operations for normal traffic conditions, while the latter plan is designed to be robust against widespread disturbances, such as adverse weather, track blockage, and other operational failures. A test case is presented on a large Dutch railway network with heavy traffic, for which we compute by microsimulation detailed t...

During real-time traffic management, the railway system suffers perturbations. The task of dispatchers is to monitor traffic flow and to compute feasible rescheduling solutions in case of perturbed operations. The main objective of the infrastructure manager is delay minimization, but the dispatchers also need to comply with the objectives of the train operating companies. This paper presents an innovative optimization framework in order to reschedule trains with different classes of priority, that can be computed statically or dynamically in order to include the needs of different stakeholders. An iterative train scheduling procedure is proposed in order to compute feasible train schedules for an ordered set of priority classes, from the highest one to the lowest one. At each step, the procedure focuses on the current priority class, preserving solution quality from the higher priority classes and neglecting lower priority classes in the optimization of train orders and times. The multi-class rescheduling problem is formulated via alternative graphs that are able to model precisely train movements at the microscopic level of block sections and block signals. Each step of the iterative train scheduling procedure is solved to optimality by a state-of-the-art branch and bound algorithm. The results show an interesting gap between single-class and multi-class rescheduling problems in terms of delay minimization. Each priority class is also evaluated in order to assess the performance of the different rescheduling solutions.

Railway traffic experiences disturbances during operations that cause conflicts between train paths or even deadlock situations. Dispatchers need actions to restore feasibility and limit spreading of delays through the network. To help them in such a task, the dispatching support tool ROMA (Railway traffic Optimization by Means of Alternative graphs) has been implemented in a laboratory environment. This paper reports on enhancements to the underlying train dispatching model as well as to the solution algorithms studied in order to tackle the increased complexity of busy stations with multiple conflicting paths and high service frequencies. Advanced train reordering and rerouting techniques are compared with straightforward rules and the current approach in the Netherlands. Extensive computational studies based on accepted statistical distributions of train delays for Utrecht Central Station assess the effectiveness of the ROMA tool in terms of solution quality and computation time.

This paper describes how knowing the source of delays is crucial information to railway infrastructure managers and train operators but assigning a given delay to its causes is very difficult. Actual delays at stations are monitored online using train describer systems and timetable databases, but it is unknown whether for instance a delay has been caused by a slow running train or by a route conflict where a driver had to slow down due to a restricted signal. In particular, delays due to route conflicts are hard to recognize afterwards, although their identification is crucial to assess and optimize the quality of infrastructure capacity allocation. This paper presents the software tool TNV-Conflict that identifies automatically all signaled route conflicts including the critical sections and conflicting trains. The developed tool can be used offline using train describer logfiles containing chronological infrastructure and train description messages. The object-oriented approach already anticipates an online implementation based on real-time messages. The resulting information is used to analyze the number of route conflicts and their effect on capacity consumption and punctuality, to assign knock-on delays to conflicting trains in a non-discriminatory way, and to identify structural route conflicts corresponding to timetable flaws (e.g. infeasible minimum headways, late trains due to preceding bottlenecks, and early trains due to excessive running time supplements). TNV-Conflict provides essential information to improve capacity allocation and construct reliable train paths. An example application on a railway corridor in the Netherlands illustrates the potential of the tool.

In the last years, real-time railway traffic optimization experienced an increasing interest due to the expected growth of traffic and the limited possibilities of enhancing the infrastructure, which ask for a more efficient use of resources and the application of more advanced decision support tools. This paper presents a computerized train dispatching system, called ROMA (Railway traffic Optimization by Means of Alternative graphs), for supporting railway traffic controllers during operations. Innovative scheduling and rerouting algorithms have been developed in order to globally optimize disturbed railway traffic conditions. ROMA can anticipate the evolution of traffic, including the propagation of delays in a regional railway network, and can estimate the effects of different dispatching measures during a period of about 15 minutes ahead. Therefore, ROMA would enable traffic controllers to frequently perform incremental changes to the actual timetable to accommodate changes in traffic patterns due to disturbances, such as train delays and blocked tracks. An extensive computational study is carried out, based on a dispatching area of the Dutch railway network, to show the high potential of our train dispatching system as a support tool to improve punctuality.

This paper evaluates several commonly applied probability distribution models for stochastic train process times, which are based on empirical data recorded in a Dutch railway station, The Hague Holland Spoor. An initial guess of model parameters is obtained by the Maximum Likelihood Estimator (MLE). An iterative procedure is then followed, where large delays are omitted one by one and the distribution parameters are estimated correspondingly using the MLE method. The parameter estimation is improved by minimizing the Kolmogorov-Smirnov (K-S) statistic where of course the empirical distribution is still based on the complete data set. A local search is finally performed in the neighborhood of the improved model parameters to further optimize the estimation. To evaluate the distribution models, we compare the K-S statistic among the fitted distributions with optimized parameters using the one-sample K-S goodness-of-fit test at a commonly adopted significance level of α = 0.05. It has been found that the log-normal distribution can be generally considered as the best approximate model among the candidate distributions for both the arrival times of trains at the platform and at the approach signal of the station. The Weibull distribution can generally be considered as the best approximate distribution model for non-negative arrival delays, departure delays and the free dwell times of late arriving trains. The shape parameter of the fitted distribution is generally smaller than 1.0 in the first two cases, whereas it is always larger than 1.0 in the last case. These distribution evaluation results for train process times can be used for accurately predicting the propagation of train delays and supporting timetable design and rescheduling particularly in case of lack of empirical data.

The hinder of approaching trains at railway junctions and in stations due to delayed trains still occupying the route can be minimized by the use of on-board processors that automatically determine the speed and travel time needed until the next main signal that protects the route of a conflicting train. The actual location, speed and distance of the trains to the conflict point are continuously recorded by on-board processors and communicated via GSM-R to other trains in the same area. A decision support system for traffic control identifies in time route conflicts between approaching trains automatically, estimates the remaining travel times and indicates the suitable speed to follow by each of the trains in order to assure seamless merging or crossing. The individual acceleration, braking and speed instructions are transmitted to each train and automatically applied by the on-board processor. The automatic piloting of trains enables maximal use of available track capacity, while guaranteeing minimal train delays.

Incidents and waiting for train connections are registered by dispatchers as sources of train delays, but route and headway conflicts are not always clearly recognized. Moreover, traffic management and route setting are the primary task of dispatchers and signallers, whilst monitoring and incident registration is not allowed to take up too much of their time. This paper describes a tool that automatically and without discrimination identifies route conflicts and the train numbers involved. It is based on standard train describer and infrastructure messages recorded on the Dutch railway network. The logic of these messages is captured in a coloured Petri net (CPN) model on which a prototype tool for route conflict identification and estimation of knock-on delay has been developed.

The paper applies principles of dynamic traffic management to solve the train re-scheduling problem faced by railway infrastructure managers during operations. When train operations are perturbed conflicts arise with respect to the scheduled train paths. A detailed mathematical formulation and dispatching algorithms are adopted to re-compute a new timetable of feasible arrival and departure times. The system generates a conflict free schedule with admissible train dynamics and with observance of minimum safety headway distances. Computational experiments on a part of the Dutch rail network show that the adopted rescheduling support system provides better solutions when compared to simple dispatching rules.