Development of Train Running diagram Optimization

International Journal of Applied Physics

© 2016 by SSRG - IJAP Journal

Volume 3 Issue 1

Year of Publication : 2016

Authors : Alexandre Bras, Desidéria

10.14445/23500301/IJAP-V3I2P102

How to Cite?

Alexandre Bras, Desidéria, "Development of Train Running diagram Optimization," SSRG International Journal of Applied Physics, vol. 3,  no. 1, pp. 8-12, 2016. Crossref, https://doi.org/10.14445/23500301/IJAP-V3I2P102

Abstract:

This item from aentire new viewpoint on existing lessons was categorized, from the particularconcernslectured by initial on two key matters of new train preparation plan: train running diagram and train processcorrection. Resolutions, simple ideas and investigates are argued in aspect. Between them, the train working diagram is separated into single and double pathunits and Passenger Train Running Diagram. And the train processcorrectioncontains the realtime correction, the service of train attachment and the conflict calculation. This paper announces automatic train operation transmitting system in preparation applications, and discusses the train scheduling problems and the future way of growth.

Keywords:

Train Running Diagram, Train Operation Adjustment, Train Scheduling.

References:

1. Nag, B.; Pal, M.N. Optimal design of timetables to maximize schedule reliability & minimize energyconsumption, rolling stock and crew deployment. In Proceedings of the 2nd UIC (International Union ofRailways) Energy Efficiency Conference, Paris, France, 2–4 February 2004.
2. Nasri, A.; Moghadam, M.F.; Mokhtari, H. Timetable optimization for maximum usage of regenerative energyof braking in electrical railway systems. In Proceedings of the International Symposium on Power ElectronicsElectrical Drives Automation and Motion, Pisa, Italy, 14–16 June 2010; pp. 1218–1221.
3. Peˇ na-Alcaraz, M.; Fernández, A.; Cucala, A.P.; Ramos, A.; Pecharromán, R.R. Optimal underground timetabledesign based on power flow for maximizing the use of regenerative-braking energy. Proc. Mech. Eng. Part F J. Rail Rapid Transit 2012, 226, 397–408. [CrossRef]
4. Yang, X.; Ning, B.; Li, X.; Tang, T. A two-objective timetable optimization model in subway systems.IEEE Trans. Intell. Transp. Syst. 2014, 15, 1913–1921. [CrossRef]
5. Gong, C.; Zhang, S.; Zhang, F.; Jiang, J.; Wang, X. An integrated energy-efficient operation methodology formetro systems based on a real case of shanghai metro line one. Energies 2014, 7, 7305–7329. [CrossRef]
6. Lin, F.; Liu, S.; Yang, Z.; Zhao, Y.; Yang, Z.; Sun, H. Multitrain energy saving for maximum usage ofregenerative energy by dwell time optimization in urban rail transit using genetic algorithm. Energies 2016, 9, 208. [CrossRef]
7. Yang, X.; Li, X.; Gao, Z.;Wang, H.; Tang, T. A cooperative scheduling model for timetable optimization insubway systems. IEEE Trans. Intell. Transp. Syst. 2013, 14, 438–447. [CrossRef]
8. Erofeyev, E. Calculation of Optimum Train Control Using Dynamic Programming Method; Moscow RailwayEngineering Institute: Moscow, Russia, 1967; Volume 811, pp. 16–30.
9. Ichikawa, K. Application of optimization theory for bounded state variable problems to the operation oftrain. Bull. JSME 1968, 11, 857–865. [CrossRef]
10. Figuera, J. Automatic optimal control of trains with frequent stops. Dyna 1970, 45, 263–269.