DEVELOPMENT OF THE METHOD OF CLUSTERIZATION OF TRAIN SITUATIONS
DOI:
https://doi.org/10.32703/2617-9040-2021-37-18Keywords:
train, situation recognition, traffic safety, clustering, classifier.Abstract
The introduction of intelligent locomotive control systems requires better approaches to assessing and monitoring the current train situation than those used in modern traction rolling stock. Automatic detection of complex abnormal situations is currently not provided. For example, determining the inefficiency of the brakes, speeding, the presence of obstacles or people on the track, the deterioration of the traction properties of rolling stock, etc. relies solely on the driver of the locomotive. Given the important impact of these factors on traffic safety, it is proposed to include in the functions of automated and intelligent traffic control systems recognition of abnormal situations and notification of its occurrence. When driving a train, all objects of classification (train situations) are divided into a finite number of classes. A finite number of precedent objects are known and studied for each class. The task of pattern recognition is to assign a new recognizable situation to a class. The classifier or decisive rule is the rule of assigning the image of a train situation to one of the classes on the basis of its vector of features. An order of classification of train situations has been developed, which allows to allocate clusters of any complex shape, provided that different parts of such clusters are connected by chains of close to each other elements. The measure of difference is the square of the Euclidean distance.
References
ЛІТЕРАТУРА
Kuric I. et al. Research of vehicle control informative functioning capacity //IOP Conference Series: Materials Science and Engineering. – IOP Publishing, 2020. Vol. 776. №. 1. P. 012036.
Butko, T., Babanin, A., Gorobchenko, A. Rationale for the type of the membership function of fuzzy parameters of locomotive intelligent control systems //Eastern-European Journal of Enterprise Technologies. 2015. №. 3 (73). P. 4-8.
Горобченко О. М. Моделювання виникнення нештатної ситуації в ергатичній системі локомотивна бригада-поїзд //Збірник наукових праць Донецького інституту залізничного транспорту. 2014.№. 38. С. 144-147.
Горобченко О. М. Розробка методу оцінки факторів, що впливають на дії локомотивних бригад в нештатних ситуаціях //Сборник научных трудов Донецкого института железнодорожного транспорта. 2010. №. 24. С. 113-121
Kyriakidis M., Majumdar A., Ochieng W. Y. The human performance railway operational index—a novel approach to assess human performance for railway operations //Reliability engineering & system safety. 2018. Val. 170. P. 226-243.
Горобченко О., Слободянюк М., Неведров О. Формалізація поїзних ситуацій при керуванні локомотивом на основі методів нечіткої логіки. Транспортні системи і технології, № 34, С. 65-70, doi:10.32703/2617-9040-2019-34-1-5.
Gorobchenko О. et al. Study of the influence of electric transmission parameters on the efficiency of freight rolling stock of direct current. Eastern-European Journal of Enterprise Technologies, 1(3-91), 60-67. doi:10.15587/1729-4061.2018.121713.
Zhou Y. et al. Integrated optimization on train control and timetable to minimize net energy consumption of metro lines //Journal of Advanced Transportation. 2018. Vol. 2018.
Jia J. et al. Designing train-speed trajectory with energy efficiency and service quality. Engineering Optimization. 2018. Val. 50. №. 5. P. 797-818.
Фалендиш А., Гатченко В., Возненко С., Клецька, О., Барибін, M. Математичне моделювання основних параметрів в тягових розрахунках. Транспортні системи і технології, (35), С. 102-112. https://doi.org/10.32703/2617-9040-2020-35-11
Gorobchenko O. et al. Intelligent locomotive decision support system structure development and operation quality assessment //2018 IEEE 3rd International Conference on Intelligent Energy and Power Systems (IEPS). IEEE, 2018. P. 239-243.
Gorobchenko O., Nevedrov O. Development of the structure of an intelligent locomotive DSS and as-sessment of its efectiveness. Archives of Transport. 2020. Val. 56. №. 4. P. 47-58.
Holub, H., Kulbovskyi, I., Skok, P., Melnychenko, O., Kharuta, V., Bambura, O., Tretynychenko, Y. System model of information flows in networks of the electric supply system in transport infrastructure projects. Transport Means - Proceedings of the International Conference. 2020, 132-135.
Wierzchoń S. T., Kłopotek M. A. Modern algorithms of cluster analysis. Springer, 2018. 421 p.
Anderberg M. R. Cluster analysis for applications: probability and mathematical statistics: a series of monographs and textbooks. – Academic press, 2014. Vol. 19.
REFERENCES
Kuric, I., Gorobchenko, O., Litikova, O., Gritsuk, I., Mateichyk, V., Bulgakov, M., & Klackova, I. (2020). Research of vehicle control informative functioning capacity. Paper presented at the IOP Conference Series: Materials Science and Engineering, 776(1) doi:10.1088/1757-899X/776/1/012036.
Butko, T., Babanin, A. & Gorobchenko, A. (2015). Rationale for the type of the membership function of fuzzy parameters of locomotive intelligent control systems. Eastern-European Journal of Enterprise Technologies, 1(3), 4-8. doi:10.15587/1729-4061.2015.35996.
Горобченко, О. М. (2014) Моделювання виникнення нештатної ситуації в ергатичній системі локомотивна бригада-поїзд. Збірник наукових праць Донецького інституту залізничного транспорту (38). C. 144-147.
Горобченко, О. М. (2010). Розробка методу оцінки факторів, що впливають на дії локомотивних бригад в нештатних ситуаціях. Збірник наукових праць Донецького інституту залізничного транспорту, (24). С. 113-121.
Kyriakidis, M., Majumdar, A., & Ochieng, W. Y. (2018). The human performance railway operational index—a novel approach to assess human performance for railway operations. Reliability engineering & system safety, 170, 226-243.
Gorobchenko, O., Slobodianiuk, M., & Nevedrov, O. (2019). Formalization situations at train locomotive management on the basis of fuzzy logic. Transport Systems and Technologies, (34), 65-70. https://doi.org/10.32703/2617-9040-2019-34-1-5
Gorobchenko, O., Fomin, O., Fomin, V., & Kovalenko, V. (2018). Study of the influence of electric transmission parameters on the efficiency of freight rolling stock of direct current. Eastern-European Journal of Enterprise Technologies, 1(3-91), 60-67. doi:10.15587/1729-4061.2018.121713.
Zhou, Y., Bai, Y., Li, J., Mao, B., & Li, T. (2018). Integrated optimization on train control and timetable to minimize net energy consumption of metro lines. Journal of Advanced Transportation, 2018.
Jia, J., Yang, K., Yang, L., Gao, Y., & Li, S. (2018). Designing train-speed trajectory with energy efficiency and service quality. Engineering Optimization, 50(5), 797-818.
Falendish, A., Hatchenko, V., Voznenko, S., Kletska, O., & Barybin, M. (2020). Математичне моделювання основних параметрів в тягових розрахунках. Транспортні системи і технології, (35), 102-112. https://doi.org/10.32703/2617-9040-2020-35-11
Gorobchenko, O., Fomin, O., Gritsuk, I., Saravas, V., Grytsuk, Y., Bulgakov, M., . . . Zinchenko, D. (2018). Intelligent locomotive decision support system structure development and operation quality assessment. Paper presented at the 2018 IEEE 3rd International Conference on Intelligent Energy and Power Systems, IEPS 2018 - Proceedings, 2018-January 239-243. doi:10.1109/IEPS.2018.8559487.
Gorobchenko, O., Nevedrov, O., (2020). Development of the structure of an intelligent locomotive DSS and assessment of its efectiveness. Archives of Transport, 56(4), 47- 58. DOI: https://doi.org/10.5604/01.3001.0014.5517.
Holub, H., Kulbovskyi, I., Skok, P., Melnychenko, O., Kharuta, V., Bambura, O., & Tretynychenko, Y. (2020). System model of information flows in networks of the electric supply system in transport infrastructure projects. Paper presented at the Transport Means - Proceedings of the International Conference, 132-135.
Wierzchoń, S. T., & Kłopotek, M. (2018). Modern algorithms of cluster analysis (421 p.). Berlin, Germany: Springer.
Anderberg, M. R. (2014). Cluster analysis for applications: probability and mathematical statistics: a series of monographs and textbooks (Vol. 19). Academic press.
Downloads
Published
How to Cite
Issue
Section
License
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
