scholarly journals Corrigendum

2021 ◽  
Vol 49 (3) ◽  
pp. 308
Author(s):  
Periodica Polytechnica Transportation Engineering
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Online Version ◽  
Correct Version ◽  
Modeling And Optimization ◽  
Railway Traffic ◽  
Management Problems

László Lindenmaier, István Ferenc Lövétei, Gábor Lukács, Szilárd Aradi "Infrastructure Modeling and Optimization to Solve Real-time Railway Traffic Management Problems", 49(3), pp. 270–282, 2021. (in this issue)https://doi.org/10.3311/PPtr.18582When the above article was first published online some symbols in the text on pages 274–276, Table 7 on page 277, furthermore the subscript of the symbol bs in Eqs. (10), (11) and in the text on page 277 were incorrect. This has now been corrected in the online version. The correct version of some symbols in the text on pages 274–276, Table 7 on page 277, furthermore the subscript of the symbol bs in Eqs. (10), (11) and in the text on page 277 were published in this paper.

scholarly journals Infrastructure Modeling and Optimization to Solve Real-time Railway Traffic Management Problems

2021 ◽  
Vol 49 (3) ◽  
pp. 270-282
Author(s):  
László Lindenmaier ◽  
István Ferenc Lövétei ◽  
Gábor Lukács ◽  
Szilárd Aradi
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Global Climate ◽  
Research Result ◽  
Mixed Integer ◽  
Programming Approach ◽  
Railway Traffic ◽  
Real Time Traffic ◽  
Management Problems ◽  
Mean Cost

Rail transportation helps to reach the global climate targets because it is characterized by low emission. The passenger and freight volumes on the railway increase yearly in line with EU targets. However, delays of passenger and freight trains decrease the punctuality and the reliability of the railway sector and the development of the infrastructure is not enough to increase the average speed of trains. Delays mean cost to the passengers, railway operators, infrastructure managers, and all railway undertakers. Therefore, the reason for the most significant optimization target is to minimize delays. In this paper, a possible solution has been described to solve the real-time railway traffic management problems by applying a mixed-integer linear programming approach. For validation of the research result, one simplified case study has been presented. Based on the result, the presented solution can provide effective support to dispatchers in solving real-time traffic management problems.

scholarly journals Distributed optimization for real-time railway traffic management

2018 ◽  
Vol 51 (9) ◽  
pp. 106-111 ◽  
Author(s):  
Xiaojie Luan ◽  
Bart De Schutter ◽  
Ton van den Boom ◽  
Francesco Corman ◽  
Gabriel Lodewijks
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Distributed Optimization ◽  
Railway Traffic

scholarly journals A Routing Filter for the Real-time Railway Traffic Management Problem Based on Ant Colony Optimization

2015 ◽  
Vol 10 ◽  
pp. 534-543 ◽  
Author(s):  
Marcella Sama‘ ◽  
Paola Pellegrini ◽  
Andrea D’Ariano ◽  
Joaquin Rodriguez ◽  
Dario Pacciarelli
Keyword(s):  
Ant Colony Optimization ◽  
Real Time ◽  
Traffic Management ◽  
Ant Colony ◽  
Management Problem ◽  
The Real ◽  
Railway Traffic

scholarly journals A Conditional Time-Intervals formulation of the real-time Railway Traffic Management Problem

2021 ◽  
Vol 54 (2) ◽  
pp. 187-194
Author(s):  
Grégory Marlière ◽  
Sonia Sobieraj Richard ◽  
Paola Pellegrini ◽  
Joaquin Rodriguez
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management Problem ◽  
Time Intervals ◽  
The Real ◽  
Railway Traffic ◽  
Conditional Time

scholarly journals MCTS Based Approach for Solving Real-time Railway Rescheduling Problem

2021 ◽  
Author(s):  
István Ferenc Lövétei ◽  
Bálint Kővári ◽  
Tamás Bécsi
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Critical Factor ◽  
Management Problem ◽  
Traffic Situation ◽  
Railway Company ◽  
Railway Traffic ◽  
Human Decision ◽  
Human Operators ◽  
Abstraction Levels

Solving a real-time Railway Traffic Management Problem (rtRTMP) is a challenging task for human operators. To solve the traffic situation, many factors need to be considered. Traditionally, the most critical factor is the availability of the possible routes and the relative position of the vehicles to each other. Besides, additional constraints can be found, such as the velocity, the length, and railway company regulations. The human decision-making process is essential in case of any disturbance (deviation from the pre-planned timetable). The human operator may solve this situation, but generally, the solution is not optimal. In this paper, the authors present a new method, where they consider an MCTS based algorithm to solve the traffic situation in a fast way in a given station. The performance of the algorithm is examined in two abstraction levels. The main purpose is to execute an experimental study to examine the efficiency of the MCTS based algorithms to solve railway traffic situations.

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