What about Train Length and Energy Efficiency of Freight Trains in Rescheduling Models?

Toletti, Ambra; Martinis, Valerio De; Weidmann, Ulrich

doi:10.1016/j.trpro.2015.09.012

Cited by 15 publications

(9 citation statements)

References 23 publications

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“…The sketch map of intelligent TD is as shown in Figure 10. SBB has recently started the rollout of adaptive control system (from German Adaptive Lenkung, adaptive train control) on their network since 2014 [181], [182]. However, the predictive dispatching is needed to be carried out, by considering the disturbances, estimating the running times and the potential conflicts, and predicting the delay occurrence.…”

Section: ) Intelligent Tdmentioning

confidence: 99%

Train Dispatching Management With Data- Driven Approaches: A Comprehensive Review and Appraisal

Wen

Huang

et al. 2019

IEEE Access

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Train dispatching (TD) is at the forefront of all rail operations that transport passengers or goods. Recent technological advances and the explosion of digital data have introduced data-driven methods (DDMs) in rail operations. In this study, DDMs on the TD problem are briefly explored, focusing on relevant studies on delay distribution, delay propagation, and timetable rescheduling. Data-driven TD methods, including statistical methods (SM), graphical models (GM), and machine learning (ML) methods are reviewed. Then, key issues in establishing different data-driven models for the TD problem are addressed. Subsequently, ML methods are considered to be among the most promising DDMs that lead to innovative TD methods, relying on rich data obtained from train operations. This study emphasizes the potentials for designing new alternatives in the three key fields of interest and provides directions for further research on TD. Future research, including the ML-driven TD and intelligent TD, were discussed in this study. INDEX TERMS Data-driven, delay distribution, delay propagation, timetable rescheduling, train dispatching, machine learning.

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Section: ) Intelligent Tdmentioning

confidence: 99%

Train Dispatching Management With Data- Driven Approaches: A Comprehensive Review and Appraisal

Wen

Huang

et al. 2019

IEEE Access

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“…The objective function can model train delays, customer inconvenience (delays, waiting times, connections missed, cfr. Caimi et al, 2012;Toletti and Weidmann, 2016) and/or energy targets (Toletti et al, 2015). Hereinafter, we aim at minimising the sum of arrival delays at scheduled stops or at the boundaries of the area, which can be computed in the following way…”

Section: Resource Conflict Graph Model For Local Rescheduling (Rcg)mentioning

confidence: 99%

Coordinated railway traffic rescheduling with the Resource Conflict Graph model

Toletti

Laumanns²,

Weidmann

2020

Journal of Rail Transport Planning & Management

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The train rescheduling problem is quite a popular topic in the railway research community. Many approaches are available to reschedule traffic in a network partition, but very few works address the coordination of these partitions. In railway systems with very dense traffic, e.g. the Swiss one, it is not always possible to partition the network such that local rescheduling algorithms can work completely independently one from another. This paper proposes a coordination approach for adjacent local rescheduling algorithms. These algorithms are based on the Resource Conflict Graph model, which enables the representation of the interlocking system at a very fine granularity. Simulations on data from the Swiss Federal Railways show the validity of this approach to improve the consistency of decisions at the common boundaries of adjacent local rescheduling algorithms.

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“…Law 5 The load ratio η is closely related to the transportation organization under the constraints of railway network topology and transportation tasks. It involves the route optimization, the organization of passenger and freight flows, the choice of vehicle type, the organization of vehicle flows, the establishment of train plan, the operation of train formation and breakup [22], the compilation of train diagram, etc. Clearly, the operational energy efficiency improvement of all in-service trains is a complex and dynamic process integrated with the forecast of transportation tasks, the planning of transportation organization, and the actual transportation organizations.…”

Section: Station I Station I+1mentioning

confidence: 99%

Energy efficiency emergence of high-speed train operation and systematic solutions for energy efficiency improvement

Pan

Meng

2020

SN Appl. Sci.

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Different from the concept of energy consumption, the energy efficiency reflects the efficiency of using energy resource and the service-oriented business philosophy of railway transportation enterprises. The energy efficiency of high-speed train operation is mainly embodied in the operation stage of railway transportation system, but involves a number of factors during the whole life cycle of railway transportation system. Based on the above understanding, the principle of making gradual and orderly progress is followed to broaden our research vision in space and time so that the global energy efficiency of high-speed train operation can be better studied. Firstly, we describe in detail the definition of the operational energy efficiency of high-speed train. Then the energy efficiency model of high-speed train operation is established to reveal the energy efficiency emergence mechanism of high-speed train operation. The simulation is carried out to analyze the complex influence of train light-weighting, control scheme, load ratio, and different inter-station distance on the operational energy efficiency of high-speed train moving through a block section. The proportion of the braking energy consumption of high-speed train with the non-regenerative braking mode is calculated in real time so that the maximum amount of available regenerative braking energy can be known for the better design of the regenerative energy recycling system in the future. This study can help to get the systematic solutions to further improve the operational energy efficiency of all in-service high-speed trains.

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What about Train Length and Energy Efficiency of Freight Trains in Rescheduling Models?

Cited by 15 publications

References 23 publications

Train Dispatching Management With Data- Driven Approaches: A Comprehensive Review and Appraisal

Train Dispatching Management With Data- Driven Approaches: A Comprehensive Review and Appraisal

Coordinated railway traffic rescheduling with the Resource Conflict Graph model

Energy efficiency emergence of high-speed train operation and systematic solutions for energy efficiency improvement

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