An Efficient Method to Schedule New Trains on a Heavily Loaded Railway Network

Ingolotti, L.; Barber, Federico; Tormos, Pilar; Lova, Antonio; Salido, Miguel Á.; Abril, M.

doi:10.1007/978-3-540-30498-2_17

Cited by 15 publications

(16 citation statements)

References 6 publications

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“…Afterwards, it transforms the problem into mathematical models, applies advanced algorithmic techniques and heuristic criteria , Barber et al (2006b), Ingolotti et al (2004), ) and automatically obtains optimized, robust, reactive and flexible railway timetables. The MOM system do the following: it can optimize existing running maps; schedule new periodic and/or not periodic trains, making them compatible with the existing scheduled trains; validate and perform theoretical and practical capacity analyses; simulate the effects of delays or incidences; measure robustness of timetables; and reschedule running maps according to incidences and delays.…”

Section: General System Architecturementioning

confidence: 99%

An assessment of railway capacity

Abril¹,

Barber²,

Ingolotti³

et al. 2008

Transportation Research Part E: Logistics and Transportation Re

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283

183

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In this paper, we review the main concepts and methods to perform capacity analyses, and we present an automated tool that is able to perform several capacity analyses. Capacity is extremely dependent on infrastructure, traffic, and operating parameters. Therefore, an in-depth study of the main factors that influence railway capacity is performed on several Spanish railway infrastructures. The results show how the capacity varies according to factors such as train speed, commercial stops, train heterogeneity, distance between railway signals, and timetable robustness.

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Section: General System Architecturementioning

confidence: 99%

An assessment of railway capacity

Abril¹,

Barber²,

Ingolotti³

et al. 2008

Transportation Research Part E: Logistics and Transportation Re

Self Cite

283

183

View full text Add to dashboard Cite

show abstract

“…In this case, the problem is typically formulated as a multicommodity flow problem Schlechte, 2007, 2008;Caprara et al, 2001Caprara et al, , 2002Caprara et al, , 2006. Further papers deal with a different but related problem, i.e., the problem of inserting additional trains in an existing timetable (Burdett and Kozan, 2009;Cacchiani et al, 2010;Flier et al, 2009;Ingolotti et al, 2004;Lova et al, 2007;Tormos et al, 2008), mostly for scheduling additional freight trains. In this case, the timetable already established for passenger trains is not modifiable, and freight train operators indicate their requests to the infrastructure manager in terms of an ideal timetable.…”

Section: Rail Transportationmentioning

confidence: 99%

Single European Sky and Single European Railway Area: A system level analysis of air and rail transportation

Pellegrini

Rodríguez

2013

Transportation Research Part A: Policy and Practice

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Air and rail transportation systems are characterized by important common features: they serve a significant share of passenger traffic in Europe; their functioning relies on the cooperation of many stakeholders operating a fixed timetable, often with competing objectives; and they have been characterized by quite a fragmented development following national borders. For these systems, the European Commission envisages a common future in terms of an increase of efficiency and elimination of national borders. In this paper, we analyze the two systems in the perspective of their common development and we underline the main existing differences linked to the management of the infrastructure. These differences concern the processes implemented for specifying and allocating capacity, both in strategic planning and in real-time intervention. Our analysis suggests that the air transportation system is moving in the direction indicated by the European Commission, as well as the rail transportation system for what concerns international train paths (typically high-speed trains). However, a substantial separation still exists between conventional rail transportation systems of different countries.

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“…The reason why only average velocities are used is that it is common to model train time table planning programs [66]- [71] such that you know when and where the trains starts and stops -but nothing more. Obviously, only average train velocities can be used, and variations of the velocity between two train stops has to be unconsidered.…”

Section: Output: the Fastest Possible Average Velocity Of An Addedmentioning

confidence: 99%

Fast Estimation of Relations Between Aggregated Train Power System Data and Traffic Performance

Abrahamsson

Söder

2011

IEEE Trans. Veh. Technol.

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Abstract-Transports on rail are increasing and major railway infrastructure investments are expected. An important part of this infrastructure is the railway power supply system. The future railway power demands are not known. The more distant the uncertain future, the greater the number of scenarios that have to be considered. Large numbers of scenarios make time demanding (some minutes, each) full simulations of electric railway power systems less attractive and simplifications more so.The aim, and main contribution, of this paper is to propose a fast approximator, that uses aggregated traction system information as inputs and outputs. This approximator can be used as an investment planning constraint in the optimization. It considers that there is a limit on the intensity of the train traffic, depending on the strength of the power system. This approximator approach is not encountered before in the literature.In the numerical example of this paper, the approximator inputs are the power system configuration; the distance between a connection from contact line to the public grid, to another connection, or to the end of the contact line; the average values and the standard deviations of the inclinations of the railway; the average number of trains; and the average velocity of them, for that distance. The output is the maximal attainable average velocity of an added train for the by the inputs described railway power system section.The approximator facilitates studies of many future railway power system loading scenarios, combined with different power system configurations, for investment planning analysis. The approximator is based on neural networks.An additional value of the approximator is that it provides an understanding of the relations between power system configuration and train traffic performance.

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An Efficient Method to Schedule New Trains on a Heavily Loaded Railway Network

Cited by 15 publications

References 6 publications

An assessment of railway capacity

An assessment of railway capacity

Single European Sky and Single European Railway Area: A system level analysis of air and rail transportation

Fast Estimation of Relations Between Aggregated Train Power System Data and Traffic Performance

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