Issues on simulation of the railway rolling stock operation process – a system and literature review

Railway traffic simulation, taking into account operation and maintenance conditions, is not a new issue in the literature. External effects in such networks (eg. level crossings) were not taken into account in studies. The used models do not take into account sufficiently the process of degradation and recovery of the network. From the technical side, currently carried out simulations are made using similar approaches and techniques as in the initial stage of research. Well-established work in this area could be the basis for evaluation of new solutions. However, the progress in simulation tools during the last years, especially in performance and programming architecture, attempt to create a modern simulation tool. In the paper were presented the main assumptions for the evaluated event-based simulation method, with application to stiff-track transportation network

The Tick Formulation for deadlock detection and avoidance in railways traffic control

Wrong dispatching decisions may lead to deadlocks, where trains reciprocally block resources necessary to reach their destinations. It is crucial to develop tools to detect such potential deadlocks on time, in order to reverse the decisions previously taken by dispatchers or to take recovery actions. In this paper we present a new 0,1 linear formulation for detecting deadlocks and optimally park the involved trains to reduce congestion around the affected area. We discuss computational results on some realistic randomly generated instances to show the validity of the approach, as well as its limits.acceptedVersio

Railway operations, time-tabling and control

This paper concentrates on organising, planning and managing the train movement in a network. The three classic management levels for rail planning, i.e., strategic, tactical and operational, are introduced followed by decision support systems for rail traffic control. In addition, included in this paper are discussions on train operating forms, railway traffic control and train dispatching problems, rail yard technical schemes and performance of terminals, as well as timetable design. A description of analytical methods, simulation techniques and specific computer packages for analysing and evaluating the behaviour of rail systems and networks is also provided

Easy Cases of Deadlock Detection in Train Scheduling

A deadlock occurs when two or more trains are preventing each other from moving forward by occupying the required tracks. Deadlocks are rare but pernicious events in railroad operations and, in most cases, are caused by human errors. Recovering is a time-consuming and costly operation, producing large delays and often requiring crew rescheduling and complex switching moves. In practice, most deadlocks involve only two long trains missing their last potential meet location. In this paper, we prove that, for any network configuration, the identification of two-train deadlocks can be performed in polynomial time. This is the first exact polynomial algorithm for such a practically relevant combinatorial problem. We also develop a pseudo-polynomial but efficient oracle that allows real-time early detection and prevention of any (potential) two-train deadlock in the Union Pacific (a U.S. class 1 rail company) railroad network. A deadlock prevention module based on the work in this paper will be put in place at Union Pacific to prevent all deadlocks of this kind.acceptedVersio

Development of a multimodal port freight transportation model for estimating container throughput

Computer based simulation models have often been used to study the multimodal freight transportation system. But these studies have not been able to dynamically couple the various modes into one model; therefore, they are limited in their ability to inform on dynamic system level interactions. This research thesis is motivated by the need to dynamically couple the multimodal freight transportation system to operate at multiple spatial and temporal scales. It is part of a larger research program to develop a systems modeling framework applicable to freight transportation. This larger research program attempts to dynamically couple railroad, seaport, and highway freight transportation models. The focus of this thesis is the development of the coupled railroad and seaport models. A separate volume (Wall 2010) on the development of the highway model has been completed. The model railroad and seaport was developed using Arena® simulation software and it comprises of the Ports of Savannah, GA, Charleston, NC, Jacksonville, FL, their adjacent CSX rail terminal, and connecting CSX railroads in the southeastern U.S. However, only the simulation outputs for the Port of Savannah are discussed in this paper. It should be mentioned that the modeled port layout is only conceptual; therefore, any inferences drawn from the model's outputs do not represent actual port performance. The model was run for 26 continuous simulation days, generating 141 containership calls, 147 highway truck deliveries of containers, 900 trains, and a throughput of 28,738 containers at the Port of Savannah, GA. An analysis of each train's trajectory from origin to destination shows that trains spend between 24 - 67 percent of their travel time idle on the tracks waiting for permission to move. Train parking demand analysis on the adjacent shunting area at the multimodal terminal seems to indicate that there aren't enough containers coming from the port because the demand is due to only trains waiting to load. The simulation also shows that on average it takes containerships calling at the Port of Savannah about 3.2 days to find an available dock to berth and unload containers. The observed mean turnaround time for containerships was 4.5 days. This experiment also shows that container residence time within the port and adjacent multimodal rail terminal varies widely. Residence times within the port range from about 0.2 hours to 9 hours with a mean of 1 hour. The average residence time inside the rail terminal is about 20 minutes but observations varied from as little as 2 minutes to a high of 2.5 hours. In addition, about 85 percent of container residence time in the port is spent idle. This research thesis demonstrates that it is possible to dynamically couple the different sub-models of the multimodal freight transportation system. However, there are challenges that need to be addressed by future research. The principal challenge is the development of a more efficient train movement algorithm that can incorporate the actual Direct Traffic Control (DTC) and / or Automatic Block Signal (ABS) track segmentation. Such an algorithm would likely improve the capacity estimates of the railroad network. In addition, future research should seek to reduce the high computational cost imposed by a discrete process modeling methodology and the adoption of single container resolution level for terminal operations. A methodology combining both discrete and continuous process modeling as proposed in this study could lessen computational costs and lower computer system requirements at a cost of some of the feedback capabilities of the model This tradeoff must be carefully examined.M.S.Committee Chair: Rodgers, Michael; Committee Member: Guensler, Randall; Committee Member: Hunter, Michae

Freight Train Optimization and Simulation

Train scheduling has already received a lot of attention, whether for passenger or freight trains. While the volume of goods transport has increased over the years, extensions of railway systems are very rare because they represent major investments for railway companies or governments. Accordingly, the railway companies are often operating freight trains in a system that is close to saturation. It follows that a very effective planning and optimization of the rail network is needed. While passenger train schedules are relatively static and cyclic, and can be planned months ahead, freight train schedules are designed with a much shorter planning time period, sometimes even one day or few hours before train departures. Moreover, passenger train schedules must obey some strict time window constraints as trains must arrive and depart from stations in order for passengers to get off/on the trains according to the posted schedule. On the opposite, the schedule of the freight trains may vary according to the train lengths or loads, i.e., freight trains have a much greater variability in their average speed. Lastly, the track configuration of the freight trains does not have a dedicated direction as it is often the case for passenger trains. For all those reasons, the scheduling of freight trains is more complex than for passenger trains. In this thesis, we propose a new dynamic row/column management algorithm for the schedule of freight trains in a single/double track railway mesh network system. While many works have already been devoted to train scheduling, previously published optimization models all suffer from scalability issues. Moreover, very few of them take into account the number of alternate tracks in the railway stations or in the sidings for train meets, as well as the delay incurred by trains that take sidings. We propose a non time-indexed model, which takes into account such constraints, and we design an original solution scheme with iterative additions/removals of constraints/variables in order to remain with a manageable sized mixed integer linear program, while still ensuring convergence to an optimal solution. Numerical results are presented on several data instances of CPR (Canada Pacific Railway) on the Vancouver-Calgary corridor, one of the busiest corridors in their railway system. In addition, we developed a simulation tool within the Arena framework, for the scheduling of freight trains. Comparisons of the simulation and optimization tools are made, together with a review of the pros and cons of simulation against optimization tools

Models and methods for operational planning in freight railroads

textRailroads are facing increasing demand for freight transportation. Effective planning and scheduling are crucial to improve the utilization of expensive resources (such as crew and track), reduce operational costs, and provide on-time service. This dissertation focuses on problem modeling and solution method development for real planning problems faced by railroads. It consists of three chapters that study two important planning problems in the daily operations of U.S. freight railroads: crew assignment and train movement planning. Chapter 2 proposes an optimization model to decide crew-to-train assignments and deadheads for double-ended crew districts. We develop an effective solution approach, combining optimization and a standalone heuristic, that generates optimal solutions in minutes. The excellent performance of this solution approach makes it well-suited for implementation within a real-time decision support tool for crew dispatchers. Chapter 3 discusses crew repositioning given the uncertainty in trains’ arrival and departure times. We propose models that minimize the expected crew holding, train delay, and deadheading cost, and develop both exact and heuristic solution methods to provide insights for crew planning under train schedule uncertainty. The last chapter studies the movement planning problem for trains traveling in a territory with multiple through tracks (mainlines) and various junctions. We explore a number of heuristic algorithms to obtain good solutions within a reasonable amount of time. The contributions of this dissertation include modeling enhancements, algorithmic development, implementation and computational testing, and validation using real data.Operations Research and Industrial Engineerin

Models and Methods for Multi-Actor Systems

2010/2011The study of the models and methods to apply to multi-actor systems is a widely discussed research topic in the related scientific literature. The multi-actor systems are defined as systems that are characterized by the presence of several autonomous elements, of different decision makers and of complex rules that allow the communication, the coordination and the connection of the components of such systems. Commonly, the study of Multi-Actor System, MAS, recalls the well-known issues concerning the multi-agent systems. The research topic related to the multi-agent system firstly started to appear in scientific literature in 1980s, mainly in relation to the computer science and artificial intelligence. In this dissertation, in particular, the study of the multi-agent systems, and specifically of the multi-actor systems, is taken into account merely in relation to the distinctive features of complexity that characterize such systems and not to the issues concerning the agent-oriented software engineering. Therefore, the research results presented in this thesis are focused on the development and on the realization of innovative models and methodologies to face the management and the decision making mechanisms applied to complex multi-actor systems. This dissertation especially focuses on two different examples of multi-actor systems in two very diverse perspectives. The former deals with the research problem related to intermodal transportation networks, while the latter with the so called consensus problem in distributed networks of agents. Concerning the research problem related to the intermodal logistic systems, the research activity addresses the management of their more and more increasing complexity by the applications of the modern Information and Communication Technologies (ICT) tools that are key solutions to achieve the efficiency and to enhance logistics competitiveness. The related scientific literature still seems lacking in addressing with adequate attention the impact of these new techniques on the management of these complex systems and, moreover, there is an apparent lack of a systematic and general methodology to describe in detail the multiplicity of elements that can influence the dynamics and the corresponding information and decision making structure of intermodal transportation systems. The innovative results presented in this dissertation are focused on the development of an Integrated System, IS, devoted to manage intermodal transportation networks at the tactical as well as operational decision level to be used by decision makers both in off-line planning and real time management. To specify the Integrated System, a reference model is developed relying on a top-down metamodeling procedure. These innovative research results are a contribution to bridge the gap and to propose not only a systematic modeling approach devoted to describe a generic multi-actor logistic system, but also a management technique based on a closed loop strategy. The second example of application is focused on a topic that is widely discussed in scientific literature related to the study of the multi-actor collective behaviors in a distributed network. The interaction protocols that allow the agents to reach the convergence to a common value is called consensus or agreement problem. This research problem is particularly studied in the context of cooperative control of multi-agent systems because the agents are autonomous, independent and have to interact in a distributed network. The presented research results address the investigation of new and fast alignment protocols that enhance the performances of the standard iteration protocols for particular topologies of digraphs on the basis of a triangular splitting of the standard iteration matrix. The examined examples, the models and the methodologies applied to analyze them, are very different in the two cases and this testifies the large extent of research problems related to the multi-actor systems.L’analisi di modelli e metodi da sviluppare e da applicare nel contesto dei sistemi multi-attoriali costituisce un tema molto variegato e discusso nella letteratura scientifica internazionale. I sistemi multi-attoriali sono sistemi che si contraddistinguono per la presenza di molti elementi autonomi diversi tra loro, di molteplici decisori e di complesse regole che determinano la comunicazione, il coordinamento e la connessione all'interno di tali sistemi. Frequentemente, facendo riferimento a sistemi multi-attoriali, Multi-Actor Systems, si richiama il tema molto attuale dei sistemi multi agente, Multi-Agent Systems. Diffusisi a partire dal 1980, i sistemi multi agente sono spesso studiati in relazione alle metodologie di sviluppo dell'ingegneria del software. Nel presente lavoro di tesi, il tema dei sistemi multi-agente, ed in particolare di quelli multi-attoriali, non viene analizzato in questo contesto, ma in relazione alle tecniche decisionali da adottare per gestire sistemi caratterizzati da un alto livello di complessità. In tale ambito, i risultati presentati all'interno di questa dissertazione sono focalizzati sullo sviluppo e sulla realizzazione di nuovi metodi e di nuove metodologie, in grado di affrontare la gestione della complessità dei sistemi multi-attoriali. Vengono in particolare esaminate due diverse problematiche, in due contesti completamente diversi e con tecniche differenti, a testimoniare le vaste applicazioni che riguardano i sistemi multi-attoriali. I problemi analizzati sono incentrati, in primo luogo, su un'applicazione inerente la gestione di sistemi logistici intermodali ed, in secondo luogo, sullo studio delle regole o protocolli di interazione in una rete distribuita di agenti autonomi. Per quanto riguarda l'aspetto legato ai sistemi intermodali di trasporto, un tema molto discusso nella letteratura scientifica recente, l'analisi si focalizza sulla gestione della loro sempre crescente complessità, tramite l'utilizzo di sistemi dell'Information and Communication Technology, ICT. Questi strumenti richiedono metodi e modelli che sono innovativi rispetto a quanto è presente nella letteratura scientifica, all'interno della quale è stata riscontrata la mancanza di un approccio sistematico e sufficientemente ad alto livello per la realizzazione di una metodologia in grado di descrivere allo stesso tempo sia la molteplicità di elementi che influenzano le dinamiche e le informazioni, sia le strutture decisionali dei sistemi intermodali. L'innovazione dei risultati presentati in questa tesi si focalizza proprio sull'esigenza di proporre un sistema integrato, Integrated System (IS), basato su un metamodello delle reti intermodali di trasporto, che fornisca un valido supporto ai decisori sia a livello tattico che operativo. Il secondo aspetto affrontato in questa tesi riguarda un altro argomento di largo ed attuale interesse nella letteratura scientifica, che viene comunemente chiamato problema del consenso. Questo problema affronta lo studio di come diversi agenti autonomi collocati su una rete distribuita siano in grado di comunicare e di accordarsi su un valore comune, senza la presenza di un decisore centrale. A questo scopo ci sono degli algoritmi che specificano le regole o protocolli di interazione tra i diversi agenti. In tale contesto, i risultati proposti si focalizzano su alcune problematiche rappresentate dal protocollo classico del consenso e soprattutto sulla sua scarsa efficienza in particolari conformazioni delle reti di agenti. Il lavoro di tesi propone, quindi, un approccio di suddivisione, splitting, della matrice standard di iterazione, di tipo triangolare, che presenta notevoli vantaggi in termini di performance rispetto all'algoritmo classico. Lo studio di problemi multi-attoriali, pertanto, richiede lo sviluppo di innovative metodologie decisionali e di nuovi metodi di gestione delle comunicazioni, per rispondere al livello sempre crescente di complessità, offrendo in questo modo alcuni spunti molto interessanti per la ricerca.XXIV Ciclo198

Intelligent real-time train rescheduling management for railway system

The issue of managing a large and complex railway system with continuous traffic flows and mixed train services in a safe and punctual manner is very important, especially after disruptive events. In the first part of this thesis an analysis method is introduced which allows the visualisation and measurement of the propagation of delays in the railway network. The BRaVE simulator and the University of Birmingham Single Train Simulator (STS) are also introduced and a train running estimation using STS is described. A practical single junction rescheduling problem is then defined and it investigates how different levels of delays and numbers of constraints may affect the performance of algorithms for network-wide rescheduling in terms of quality of solution and computation time. In order to deal with operational dynamics, a methodology using performance-based supervisory control is proposed to provide rescheduling decisions over a wider area through the application of different rescheduling strategies in appropriate sequences. Finally, an architecture for a real-time train rescheduling framework, based on the distributed artificial intelligence system, is designed in order to handle railway traffic in a large-scale network intelligently. A case study based on part of the East Coast Main Line is followed up to demonstrate the effectiveness of adopting supervisory control to provide the rescheduling options in the dynamic situation