Performability evaluation of the ERTMS/ETCS – Level 3

Level 3 of the ERTMS/ETCS improves the capacity of railways by replacing fixed-block signalling, which prevents a train to enter a block occupied by another train, with moving block signalling, which allows a train to proceed as long as it receives radio messages ensuring that the track ahead is clear of other trains. If messages are lost, a train must stop for safety reasons within a given deadline, even though the track ahead is clear, making the availability of the communication link crucial for successful operation.We combine analytic evaluation of failures due to burst noise and connection losses with numerical solution of a non-Markovian model representing also failures due to handovers between radio stations. In so doing, we show that handovers experienced by a pair of chasing trains periodically affect the availability of the radio link, making behavior of the overall communication system recurrent over the hyper-period of periodic message releases and periodic arrivals at cell borders. As a notable aspect, non-Markovian transient analysis within two hyper-periods is sufficient to derive an upper bound on the first-passage time distribution to an emergency brake, permitting to achieve a trade-off between railway throughput and stop probability. A sensitivity analysis is performed with respect to train speed and headway distance, permitting to gain insight into the consequences of system-level design choices.     

Conflict Resolution through Negotiation in a Railway Open Access Market: a Multi-agent System Approach

Abstract

Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.     

Optimizing train stopping patterns and schedules for high-speed passenger rail corridors

High-speed railway (HSR) systems have been developing rapidly in China and various other countries throughout the past decade; as a result, the question of how to efficiently operate such large-scale systems is posing a new challenge to the railway industry. A high-quality train timetable should take full advantage of the system’s capacity to meet transportation demands. This paper presents a mathematical model for optimizing a train timetable for an HSR system. We propose an innovative methodology using a column-generation-based heuristic algorithm to simultaneously account for both passenger service demands and train scheduling. First, we transform a mathematical model into a simple linear programming problem using a Lagrangian relaxation method. Second, we search for the optimal solution by updating the restricted master problem (RMP) and the sub-problems in an iterative process using the column-generation-based algorithm. Finally, we consider the Beijing–Shanghai HSR line as a real-world application of the methodology; the results show that the optimization model and algorithm can improve the defined profit function by approximately 30% and increase the line capacity by approximately 27%. This methodology has the potential to improve the service level and capacity of HSR lines with no additional high-cost capital investment (e.g., the addition of new tracks, bridges and tunnels on the mainline and/or at stations).     

An optimization model for integrated planning of railway traffic and network maintenance

Railway transportation systems are important for society and have many challenging and important planning problems. Train services as well as maintenance of a railway network need to be scheduled efficiently, but have mostly been treated as two separate planning problems. Since these activities are mutually exclusive they must be coordinated and should ideally be planned together. In this paper we present a mixed integer programming model for solving an integrated railway traffic and network maintenance problem. The aim is to find a long term tactical plan that optimally schedules train free windows sufficient for a given volume of regular maintenance together with the wanted train traffic. A spatial and temporal aggregation is used for controlling the available network capacity. The properties of the proposed model are analyzed and computational experiments on various synthetic problem instances are reported. Model extensions and possible modifications are discussed as well as future research directions.     

A tabu search algorithm to solve the integrated planning of container on an inter-terminal network connected with a hinterland rail network

Transport demand for containers has been increasing for decades, which places pressure on road transport. As a result, rail transport is stimulated to provide better intermodal freight transport services. This paper investigates mathematical models for the planning of container movements in a port area, integrating the inter-terminal transport of containers (ITT, within the port area) with the rail freight formation and transport process (towards the hinterland). An integer linear programming model is used to formulate the container transport across operations at container terminals, the network interconnecting them, railway yards and the railway networks towards the hinterland. A tabu search algorithm is proposed to solve the problem. The practical applicability of the algorithm is tested in a realistic infrastructure case and different demand scenarios. Our results show the degree by which internal (ITT) and external (hinterland) transport processes interact, and the potential for improvement of overall operations when the integrated optimization proposed is used. Instead, if the planning of containers in the ITT system is optimized as a stand-alone problem, the railway terminals may suffer from longer delay times or additional train cancellations. When planning the transport of 4060 TEU containers within one day, the benefits of the ITT planning without considering railway operations account for 17% ITT cost reduction but 93% railway operational cost growth, while the benefits of integrating ITT and railway account for a reduction of 20% in ITT cost and 44% in railway operational costs.     

On particulate emissions from moving trains in a tunnel environment

Increasing attention is being paid to airborne particles in railway environments because of their potential to adversely affect health. In this study, we investigate the contribution of moving trains to both the concentration and size distribution of particles in tunnel environments. Real-time measurements were taken with high time-resolution instruments at a railway station platform in a tunnel in Stockholm in January 2013. The results show that individual trains stopping and starting at the platform substantially elevate the particulate concentrations with a mobility diameter greater than 100 nm. Two size modes of the particulate number concentrations were obtained. A mode of around 170 nm occurs when a train moves, while the other mode peaks at about 30 nm when there is no train in the station. By using principal component analysis (PCA), three contributing sources were identified on the basis of the classification of the sizes of the particles, namely railway-related mechanical wear, suspension due to the movement of trains and sparking of electric-powered components. It is concluded that the particulate matter released by individual moving trains is a key contributor to fine particles (100–500 nm) on the railway platform in a tunnel.     

Prediction of ground vibration amplitudes due to urban railway traffic using quantitative and qualitative field data

The growth of railway transport in urban areas has lead to an increase in ground vibrations enhancing their negative environmental impact. Therefore is mandatory to predict and control ground vibrations. This work presents a methodology for the determination of prediction models of ground vibration amplitudes due to railway train circulation in urban environments. Using quantitative predictors (train speed and distance) and qualitative predictors (railway track type, dominant geology and building type), being the use of the latter predictors justified by the fact that, most frequently, quantitative parameters are very difficult to obtain in the urban environment due to their characterization. Thus, a detailed statistical study based on the proposal and validation of multiple linear regression models, is successfully applied in order to predict vibration amplitudes produced by railway train circulation, in the considered domain, as function of quantitative and qualitative predictors, easily obtained in field work. A multiple linear regression model for ground vibration prediction due to underground railway traffic has been presented for the Lisbon area.     

A fault tolerance approach for railway scheduling and train control

This paper makes two contributions. It firstly proposes the use of a fault tolerance approach for railway operations and secondly it develops a minimum time gap matrix model for capacity computation and the study of perturbation effects through the generation of a compressed timetable. A fault tolerance approach is proposed to improve the operational efficiency of the railway network in terms of the network capacity and the robustness of train timetables. The term fault tolerance is used in a broad sense, to represent any abnormalities or unexpected events in operations or equipment. Enhanced fault tolerance capability provides safety assurance so that, in normal operating conditions, trains can adopt much faster speed profiles when approaching a ‘to-be-cleared’ signal block at stations and junctions than those currently permitted, effectively turning the status of ‘be ready to stop’ to that of ‘proceed with caution’. In the rare event of a ‘fault’ in the system, e.g. if a conflicting train fails to move out of a signalling block as expected or a switch fails to operate as required, the train would be re-routed to take an alternative path. In this study, the new approach is developed on three scenarios i.e., a standard classic right turn junction, a terminus station, and a small network combining both of these elements to demonstrate the performance gains, but the concept can be readily extended for other types of junctions/stations. Results so far show great potential in the proposed fault tolerance approach to increase the capacity and enhance operational robustness to perturbations at such locations. A novel method for capacity computation called minimum time gap matrix model is also introduced that has capability to produce compressed timetables directly from a given train sequence.     

Recent success stories on integrated optimization of railway systems

Planning and operating railway transportation systems is an extremely hard task due to the combinatorial complexity of the underlying discrete optimization problems, the technical intricacies, and the immense size of the problem instances. Because of that, however, mathematical models and optimization techniques can result in large gains for both railway customers and operators, e.g., in terms of cost reductions or service quality improvements. In the last years a large and growing group of researchers in the OR community have devoted their attention to this domain developing mathematical models and optimization approaches to tackle many of the relevant problems in the railway planning process. However, there is still a gap to bridge between theory and practice (e.g. Cacchiani et al., 2014; Borndörfer et al., 2010), with a few notable exceptions. In this paper we address three individual success stories, namely, long-term freight train routing (part I), mid-term rolling stock rotation planning (part II), and real-time train dispatching (part III). In each case, we describe real-life, successful implementations. We will discuss the individual problem setting, survey the optimization literature, and focus on particular aspects addressed by the mathematical models. We demonstrate on concrete applications how mathematical optimization can support railway planning and operations. This gives proof that mathematical optimization can support the planning of railway resources. Thus, mathematical models and optimization can lead to a greater efficiency of railway operations and will serve as a powerful and innovative tool to meet recent challenges of the railway industry.     

Multiple-phase train trajectory optimization with signalling and operational constraints

The train trajectory optimization problem aims at finding the optimal speed profiles and control regimes for a safe, punctual, comfortable, and energy-efficient train operation. This paper studies the train trajectory optimization problem with consideration of general operational constraints as well as signalling constraints. Operational constraints refer to time and speed restrictions from the actual timetable, while signalling constraints refer to the influences of signal aspects and automatic train protection on train operation. A railway timetable provides each train with a train path envelope, which consists of a set of positions on the route with a specified target time and speed point or window. The train trajectory optimization problem is formulated as a multiple-phase optimal control model and solved by a pseudospectral method. This model is able to capture varying gradients and speed limits, as well as time and speed constraints from the train path envelope. Train trajectory calculation methods under delay and no-delay situations are discussed. When the train follows the planned timetable, the train trajectory calculation aims at minimizing energy consumption, whereas in the case of delays the train trajectory is re-calculated to track the possibly adjusted timetable with the aim of minimizing delays as well as energy consumption. Moreover, the train operation could be affected by yellow or red signals, which is taken into account in the train speed regulation. For this purpose, two optimization policies are developed with either limited or full information of the train ahead. A local signal response policy ensures that the train makes correct and quick responses to different signalling aspects, while a global green wave policy aims at avoiding yellow signals and thus proceed with all green signals. The method is applied in a case study of two successive trains running on a corridor with various delays showing the benefit of accurate predictive information of the leading train on energy consumption and train delay of the following train.     

An improved car‐following model for railway traffic

In this paper, we propose an improved traffic model for simulating train movement in railway traffic. The proposed model is based on optimal velocity car‐following model. In order to test the proposed model, we use it to simulate the train movement with fixed‐block system. In simulations, we analyze and discuss the space–time diagram of railway traffic flow and the trajectories of train movement. Simulation results demonstrate that the proposed model can be successfully used for simulating the train movement in railway traffic. From the space–time diagram, we find some complex phenomena of train flow, which are observed in real railway traffic, such as train delays. By analyzing the trajectories of train movement, some dynamic characteristics of trains can be reproduced. Copyright © 2011 John Wiley & Sons, Ltd.     

Integrating robust timetabling in line plan optimization for railway systems

We propose a heuristic algorithm to build a railway line plan from scratch that minimizes passenger travel time and operator cost and for which a feasible and robust timetable exists. A line planning module and a timetabling module work iteratively and interactively. The line planning module creates an initial line plan. The timetabling module evaluates the line plan and identifies a critical line based on minimum buffer times between train pairs. The line planning module proposes a new line plan in which the time length of the critical line is modified in order to provide more flexibility in the schedule. This flexibility is used during timetabling to improve the robustness of the railway system. The algorithm is validated on the DSB S-tog network of Copenhagen, which is a high frequency railway system, where overtakings are not allowed. This network has a rather simple structure, but is constrained by limited shunt capacity. While the operator and passenger cost remain close to those of the initially and (for these costs) optimally built line plan, the timetable corresponding to the finally developed robust line plan significantly improves the minimum buffer time, and thus the robustness, in eight out of ten studied cases.     

Macroscopic multiple-station short-turning model in case of complete railway blockages

In case of railway disruptions, traffic controllers are responsible for dealing with disrupted traffic and reduce the negative impact for the rest of the network. In case of a complete blockage when no train can use an entire track, a common practice is to short-turn trains. Trains approaching the blockage cannot proceed according to their original plans and have to short-turn at a station close to the disruption on both sides. This paper presents a Mixed Integer Linear Program that computes the optimal station and times for short-turning the affected train services during the three phases of a disruption. The proposed solution approach takes into account the interaction of the traffic between both sides of the blockage before and after the disruption. The model is applied to a busy corridor of the Dutch railway network. The computation time meets the real-time solution requirement. The case study gives insight into the importance of the disruption period in computing the optimal solution. It is concluded that different optimal short-turning solutions may exist depending on the start time of the disruption and the disruption length. For periodic timetables, the optimal short-turning choices repeat due to the periodicity of the timetable. In addition, it is observed that a minor extension of the disruption length may result in less delay propagation at the cost of more cancellations.     

Development of hybrid optimization of train schedules model for N-track rail corridors

From a capacity perspective, efficient utilization of a railway corridor has two main objectives; avoidance of schedule conflicts, and finding a proper balance between capacity utilization and level of service (LOS). There are several timetable tools and commercial rail simulation packages available to assist in reaching these objectives, but few of them offer both automatic train conflict resolution and automatic timetable management features for the different types of corridor configurations. This research presents a new rescheduling model to address some of the current limitations. The multi-objective linear programming (LP) model is called “Hybrid Optimization of Train Schedules” (HOTS), and it works together with commercial rail simulation tools to improve capacity utilization or LOS metrics. The HOTS model uses both conflict resolution and timetable compression techniques and is applicable to single-, double-, and multiple-track corridors (N-track networks), using both directional and bi-directional operations. This paper presents the approach, formulation and data requirements for the HOTS model. Single and multi-track case studies test and demonstrate the model’s train conflict resolution and timetable compression capabilities, and the model’s results are validated by using RailSys simulation package. The HOTS model performs well in each tested scenario, providing comparable results (either improved or similar) to the commercial packages.     

An integrated sea–land transportation system model and its theory

To enhance the efficiency of intermodal transportation for large quantities of goods, the current sea–land transportation system has been reviewed and systematically analyzed, and a bottleneck is pinpointed in the linkage or goods transfer between the waterway and railway. The bottleneck impacts the efficiency of the goods through transportation combining the two modes. To eliminate the existing bottleneck and inefficiency towards intermodality, a new type of flexible double-rail track has recently been invented together with innovations both in trestle bridges and in train ferries. The outcomes of the research in progress show that the flexible double-rail track is feasible from the viewpoints of both geometry and engineering mechanics, it can be used to improve the compatibility of a trestle bridge with various types of train ferries and hence it can support the development of train ferries on a large scale. Based on the innovations, an integrated sea–land transportation system model is proposed as a systematic solution, which is expected to effectively overcome the existing bottleneck and to enhance the efficiency of the whole sea–land combined transportation. Further research on this system model and its major components is also addressed in the paper.     

Modelling route choice behaviour in multi-modal transport networks

The paper presents new findings on the influence of multi-modal trip attributes on the quality and competitiveness of inter-urban multi-modal train alternatives. The analysis covers the entire trip from origin to destination, including access and egress legs to and from the train network. The focus is on preferences for different feeder modes, railway station types and train service types as well as on the relative influence of time elements and transfer penalties. Data from dedicated surveys are used including individual objective choice sets of 235 multi-modal homebound trips in which train is the main transport mode. The observed trips have origins and destinations within the Rotterdam–Dordrecht region in The Netherlands with an average total trip time of 50 minutes. Hierarchical Nested Logit models are estimated to take account of unobserved similarities between alternatives at the home-end and the activity-end of the trip respectively, resulting in two-level nesting structures which differentiate between intercity (IC) and non-intercity railway station types at the upper level and between transit and private access modes at the lower level. In order to reflect the multi-dimensional structure of the data a more advanced so-called Multi-Nested GEV model according to the Principles of Differentiation has been estimated which significantly improves the explanatory power and stresses the importance of the home-end of the multi-modal trip.     

从数字看中国铁路隧道的建设

根据收集到的有关中国铁路隧道建设比较全面、可靠的统计资料,按年代和铁路线归纳整理列出的,并用数字来阐述截至2005年末中国铁路隧道建设的基本情况与发展历程；同时对隧道命名与隧道长度计算的统一等问题提出建议。     

Integrating capacity analysis with high-speed railway timetabling: A minimum cycle time calculation model with flexible overtaking constraints and intelligent enumeration

Compared with most optimization methods for capacity evaluation, integrating capacity analysis with timetabling can reveal the types of train line plans and operating rules that have a positive influence on improving capacity utilization as well as yielding more accurate analyses. For most capacity analyses and cyclic timetabling methods, the cycle time is a constant (e.g., one or two hours). In this paper, we propose a minimum cycle time calculation (MCTC) model based on the periodic event scheduling problem (PESP) for a given train line plan, which is promising for macroscopic train timetabling and capacity analysis. In accordance with train operating rules, a non-collision constraint and a series of flexible overtaking constraints (FOCs) are constructed based on variations of the original binary variables in the PESP. Because of the complexity of the PESP, an iterative approximation (IA) method for integration with the CPLEX solver is proposed. Finally, two hypothetical cases are considered to analyze railway capacity, and several influencing factors are studied, including train regularity, train speed, line plan specifications (train stops), overtaking and train heterogeneity. The MCTC model and IA method are used to test a real-world case involving the timetable of the Beijing–Shanghai high-speed railway in China.     

Non-discriminatory train dispatching in a rail transport market with multiple competing and collaborative train operating companies

Train dispatching is vital for the punctuality of train services, which is critical for a train operating company (TOC) to maintain its competitiveness. Due to the introduction of competition in the railway transport market, the issue of discrimination is attracting more and more attention. This paper focuses on delivering non-discriminatory train dispatching solutions while multiple TOCs are competing in a rail transport market, and investigating impacting factors of the inequity of train dispatching solutions. A mixed integer linear programming (MILP) model is first proposed, in which the inequity of competitors (i.e., trains and TOCs) is formalized by a set of constraints. In order to provide a more flexible framework, a model is further reformulated where the inequity of competitors is formalized as the maximum individual deviation of competitors’ delay cost from average delay cost in the objective function. Complex infrastructure capacity constraints are considered and modelled through a big M-based approach. The proposed models are solved by a standard MILP solver. A set of comprehensive experiments is conducted on a real-world dataset adapted from the Dutch railway network to test the efficiency, effectiveness, and applicability of the proposed models, as well as determine the trade-off between train delays and delay equity.