SIMULATION OF DRIVER’S LOCOMOTIVE-HANDLING ACTIVITY USING THE THEORY OF FUZZY GRAPHS

T. V. Butko, O. M. Horobchenko

Abstract


Purpose. The efficiency and safety of locomotive control improving is important and relevant scientific and practical problem. Every driver during the trains-handling bases on his experience and knowledge, that is why the compilation and detection the most efficient ways to control the locomotive-handling is one of the stages of measures development to reduce transportation costs. The purpose of this paper is a formalization process description of locomotive-handling and quality parameters determination of this process. Methodology. In order to achieve this goal the theory of fuzzy probabilistic graphs was used. Vertices of the graph correspond to the events start and end operations at train-handling. The graph arcs describe operations on train-handling. Graph consists of thirteen peaks corresponding to the main control actions of the engine-driver. The weighting factors of transitions between vertices are assigned by fuzzy numbers. Their values were obtained by expert estimates. Fuzzy probabilities and transition time are presented as numbers with trapezoidal membership function. Findings. Using successive merging of parallel arcs, loops and vertices elimination, the equivalent fuzzy graph of train-handling and the corresponding L-matrix were obtained. Equivalent graph takes into account separately activity of the driver during normal operation and during emergency situations. Originality. The theoretical foundations of describing process formalization in driver’s locomotive-handling activity were developed using the fuzzy probabilistic graph. The parameters characterizing the decision-making process of engineer were obtained. Practical value. With the resulting model it is possible to estimate the available reserves for the quality improvement of locomotive-handling. Reduction in the time for decision-making will lead to the approximation the current mode of control to the rational one and decrease costs of hauling operations. And reduction in the time for the emergency situations identifying will lead to the traffic safety increasing through the implementation of measures of early response to danger.


Keywords


safety movement; the locomotive crew; fuzzy graph; train, decision-making

References


Horobchenko O.M. Vyznachennia imovirnosti vynyknennia transportnoi podii v lokomotyvnomu hospodarstvi [The probability of traffic accidents determination in the locomotive facilities]. Visnyk Dnipropetrovskoho natsionalnoho universytetu zaliznychnoho transportu imeni akademika V. Lazariana [Bulletin of Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan], 2010, issue 35, pp. 48-51.

Ilman V.M., Skalozub V.V., Shynkarenko V.I. Vidtvorennia hrafiv za tekhnolohichnymy shliakhamy [The graphs reconstruction with technological ways]. Visnyk Dnipropetrovskoho natsionalnoho universytetu zaliznychnoho transportu imeni akademika V. Lazariana [Bulletin of Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan], 2007, issue 18, pp. 85-94.

Tarasov V.A., Gerasimov B.M., Levin I.A., Korneychuk V.A. Intellektualnyye sistemy podderzhki prinyatiya resheniy: teoriya, sintez, effektivnost [Intelligent systems of decision support. Theory, synthesis, efficiency]. Kyiv, MAKNS Publ., 2007. 336 p.

Zhukovytskyi I.V., Skalozub V.V., Vietrova O.V., Zinenko O.L. Modeliuvannia protsesu operatyvnoho planuvannia roboty lokomotyvnoho parku i lokomotyvnykh bryhad [Modeling of the operational planning process of working locomotives and locomotive crews]. Visnyk Dnipropetrovskoho natsionalnoho universytetu zaliznychnoho transportu imeni akademika V. Lazariana [Bulletin of Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan], 2006, issue 12, pp. 75-78.

Raskin L.G., Seraya O.V. Nechetkaya matematika [Fuzzy mathematics]. Kharkov, Parus Publ., 2008. 352 p.

Rotshteyn A.P., Shtovba S.D. Nechetkaya nadezhnost algoritmicheskikh protsessov [Fuzzy reliability of algorithmic processes]. Vinnitsa, Kontinent Publ., 1997. 142 p.

Advanced technologies and energy efficiency: fuel economy program maintained jointly by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy and the US Environmental Protection Agency. – Available at: http://www.fueleconomy.gov/FEG/atv.shtml (Accessed 29 November 2014).

Madsen A.L., Kjærulff U.B., Kalwa J., Perrier M., Sotelo M.A. Applications of Probabilistic Graphical Models to Diagnosis and Control of Autonomous Vehicles. The Second Bayesian Modeling Applications Workshop. Aalborg,AalborgUniversitet Publ., 2005. 12 p.

Bower E., Skipton-Carter A., Buchanan J. GB Rail Powertrain Efficiency Improvements. Delivering Value Through Innovation & Technology, 2012. – Available at: http://www.ricardo.com/Documents/PRs%20pdf/PRs%202012/Q 57475_DfT_GB_Rail_Diesel_Powertrain_Efficiency_Improvements_Word_FINAL_14Mar12.pdf (Accessed 27 November 2014).

Gentle J.E. Matrix Algebra: Theory, Computations, and Applications in Statistics.New York, Springer Science & Business Media Publ., 2007. 552 p.

NaumannU., Schenk O. Combinatorial Scientific Computing.London, CRC Press Publ., 2012. 600 p.

Okorokov А.М. Strategic management of transport cargo complex. Nauka ta prohres transportu. Visnyk Dnipropetrovskoho natsionalnoho universytetu zaliznychnoho transportu − Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, 2014, no. 4 (52), pp. 101-110.

Wang Z., Li-min J. The Theory and Methods of Design and Optimization for Railway Intelligent Transportation Systems (RITS). Beijing, China, Bentham Science Publishers Ltd. Publ., 2011. 149 p.


GOST Style Citations


  1. Горобченко, О. М. Визначення імовірності виникнення транспортної події в локомотивному господарстві / О. М. Горобченко // Вісн. Дніпропетр. нац. ун-ту залізн. трансп. ім. акад. В. Лазаряна. – Дніпропетровськ, 2010. – Вип. 35. – С. 48–51.
  2. Ільман, В. М. Відтворення графів за технологічними шляхами / В. М. Ільман, В. В. Скалозуб, В. І. Шинкаренко // Вісн. Дніпропетр. нац. ун-ту залізн. трансп. ім. акад. В. Лазаряна. – Дніпропетровськ, 2007. – Вип. 18. – С. 85–94.
  3. Интеллектуальные системы поддержки принятия решений: теория, синтез, эффективность / В. А. Тарасов, Б. М. Герасимов, И. А. Левин, В. А. Корнейчук. – Киев : МАКНС, 2007. – 336 с.
  4. Моделювання процесу оперативного планування роботи локомотивного парку і локомотивних бригад / І. В. уковицький, В. В. Скалозуб, О. В. Вєтрова, О. Л. Зіненко // Вісн. Дніпропетр. нац. ун-ту залізн. трансп. ім. акад. В. Лазаряна. – Дніпропетровськ, 2006. – Вип. 12. – С. 75–78.
  5. Раскин, Л. Г. Нечеткая математика : моногр. / Л. Г. Раскин, О. В. Серая. – Харьков : Парус, 2008. – 352 с.
  6. Ротштейн, А. П. Нечеткая надежность алгоритмических процессов / А. П. Ротштейн, С. Д. Штовба. – Винница : Континент, 1997. – 142 с.
  7. Advanced technologies and energy efficiency: fuel economy program maintained jointly by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy and
    the US Environmental Protection Agency [Електронний ресурс]. – Режим доступу: http://www.fueleconomy.gov/FEG/atv.shtml. – Назва з екрана. – Перевірено : 29.11.2014.
  8. Applications of Probabilistic Graphical Models to Diagnosis and Control of Autonomous Vehicles / A. L. Madsen, U. B. Kjærulff, J. Kalwa [et al.] // The Second Bayesian Modeling Applications Workshop. – Aalborg :AalborgUniversitet, 2005. – 12 p.
  9. Bower, E. GB Rail Powertrain Efficiency Impro-vements. Delivering Value through Innovation & Technology [Електронний ресурс] / E. Bower, A. Skipton-Carter, J. Buchanan. – Режим доступу: http://www.ricardo.com/Docu-ments/PRs%20-pdf/PRs%202012/Q57475_DfT_GB_Rail_Diesel_Powertrain_Efficiency_Improvements_Word_FINAL_14Mar12.pdf. – Назва з екрана. – Пере-вірено : 27.11. 2014.
  10. Gentle, J. E. Matrix Algebra: Theory, Computations, and Applications in Statistics / J. E. Gentle. – New York : Springer Science & Business Media, 2007. – 552 p. doi: 10.1007/978-0-387-70873-7.
  11. Naumann, U. Combinatorial Scientific Computing / U. Naumann, O. Schenk. –London: CRC Press, 2012. – 600 p.
  12. Okorokov, А. М. Strategic management of trans-port cargo complex / А. М. Okorokov // Наука та прогрес трансп. Вісн. Дніпропетр. нац. ун-ту залізн. трансп. – 2014. – № 4 (52). – С. 101–110. doi: 10.15802/stp2014/27320.
  13. Wang, Z. The Theory and Methods of Design and Optimization for Railway Intelligent Trans-portation Systems (RITS) / Z.Wang, J. Li-min. – Beijing, China : Bentham Science Publishers Ltd., 2011. – 149 p. doi: 10.2174/978160805138011-10101.


DOI: https://doi.org/10.15802/stp2015/42164

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

 

ISSN 2307–3489 (Print)
ІSSN 2307–6666 (Online)