Stochastic delay propagation in railway networks and phase-type distributions

Meester, Ludolf Erwin; Muns, Sander

doi:10.1016/j.trb.2006.02.007

Cited by 92 publications

(56 citation statements)

References 4 publications

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“…Yuan and Hansen [4] and Meester and Muns [5] have both emphasised the lack of queuing models to consider timetables, since they are reliant on probability distributions for inter-arrival times. Moreover, fixed arrival and departure times were also not considered, and the impact of speed variations was [3] instead suggested a way to capture speed variances among different train types by ignoring block (signalling) sections in a section between stations.…”

Section: Queuing Modelsmentioning

confidence: 99%

Mathematical and Simulation Tecniques for Modelling Urban Train Networks

Wilson

Fourie

Delmistro³

2016

SAJIE

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Railway systems can pose complex problems for the scheduling and operation of trains. A passenger rail service's first priority is to provide a punctual and safe transport service to its customers. But doing so is a major challenge for rail network operators, as disruptions are inevitable, especially in densely-populated networks. Disruptions can be caused not only by infrastructure or rolling stock breakdowns, but also by maintenance activities, new rolling stock, or new train services. Managing these disruptions and predicting the extent of its effects is a crucial part of rail network operation. Mathematical models and simulation can be applied to these problems. This paper will review the literature concerning the modelling of train networks. OPSOMMINGSpoorwegstelsels skep soms komplekse probleme met betrekking tot die skedulering en die bedryf van treine. 'n Passasiers-spoordiens se eerste prioriteit is om stiptelike en veilige vervoer te verskaf aan sy gebruikers. Om 'n stiptelike en betroubare diens te lewer is 'n groot uitdaging vir netwerk operateurs, aangesien trein dienste maklik ontwrig word in digbevolkte netwerke. Ontwrigtinge word nie net deur infrastruktuur en rollende materiaal falings veroorsaak nie, maar ook deur infrastruktuur onderhoud, nuwe rollende materiaal, en nuwe treindienste wat ingestel kan word. Die bestuur van dié ontwrigtinge en die akkurate vooruitskatting van die effek op die res van die netwerk is 'n kritiese komponent van die bedryf van 'n trein netwerk. Wiskundige modelle en simulasie metodes kan toegepas word op dié tipe probleme. Hierdie artikel bespreek die literatuur wat oor die modellering van trein netwerke handel. INTRODUCTIONRailway network companies often need to model and simulate the operation of their trains. This need usually arises with the expansion or maintenance of infrastructure, or the addition of new rolling stock and services. Infrastructure expansion entails adding new links, stations, or additional lines on a specific route. Furthermore, perway, electrical, and signals maintenance all contributes to train operations being disrupted to some extent. And adding train services or new rolling stock requires major operations planning and rescheduling. Forecasting the effect on the operation of the network before the implementation of such changes is a crucial component of planning. Bottlenecks, line capacities, demand satisfaction, and delay propagations are all areas that need to be identified and calculated before large capital amounts are spent. This can be done through the use of mathematical models and simulation. The optimisation of existing operations can also be done using these tools. OBJECTIVEThe objective of this paper is to review the literature on the different modelling techniques that are used to describe the operation of train networks. This will lay the groundwork for developing

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Section: Queuing Modelsmentioning

confidence: 99%

Mathematical and Simulation Tecniques for Modelling Urban Train Networks

Wilson

Fourie

Delmistro³

2016

SAJIE

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“…In 2007, Meester and Muns [5] formalized a model to quantify the running time propagation of delays which determines the secondary delay (caused) from the distribution of the primary delays (generators).…”

Section: Introductionmentioning

confidence: 99%

A model to analyze railway delay to support the “performance regime” evaluation

Guida¹,

Libardo²,

Salerno³

2012

WIT Transactions on the Built Environment

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This research tries to improve an existing model of the authors concerning "performance regime": it showed an innovative methodology to check rail operations and to attribute delay responsibilities to every event and every train. This paper also considers other features of the infrastructure management dimension as: (a) railway company and external; (b) delay causes. A programming language has been used to set and define an algorithm that has been used in a key role in the "Perseo" project of the Italian railway manager (Rfi).

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“…most stochastic models to analyse propagation of delays focused on single-track sections or on simple junctions. classical stochastic models for the propagation of delays had been studied intensively, most importantly in refs [6,7]. The papers proposed the approximation of delay distributions to reduce the computational effort.…”

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confidence: 99%

“…The papers proposed the approximation of delay distributions to reduce the computational effort. The paper [7] represents train traffic in a form of occupying an intermediate position between the macro-models and the models with very detailed description of the process, i.e. micro-models.…”

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Stochastic model for the real-time train rescheduling

Davydov¹,

Chebotarev²,

Kablukova³

2017

Int. J. TDI

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The article explores the problem of train rescheduling based on the actual situation. The proposed stochastic model uses specific distributions of operating times which are dependent on the current traffic conditions. The arrival time distribution is considered as a result of adjusting the train trajectory by speed control. The results of modelled arrival distributions correspond well with the experimental data received at the russian railways. The proposed model is used for prevention of sequence-of-trains conflicts and violations of connections. The basis of deviation prediction is two-train model of mesalevel which uses actual features of scattering of the operation times both at sites and at stations. The article also proposed a new measure of arrival delay which considers the share of satisfied passengers.

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Stochastic delay propagation in railway networks and phase-type distributions

Cited by 92 publications

References 4 publications

Mathematical and Simulation Tecniques for Modelling Urban Train Networks

Mathematical and Simulation Tecniques for Modelling Urban Train Networks

A model to analyze railway delay to support the “performance regime” evaluation

Stochastic model for the real-time train rescheduling

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