S. V. Gerus, V. V. Dementienko, V. I. Mirgorodskiy
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引用次数: 0
Abstract
Based on an analysis of statistical data on railway and road traffic, as well as laboratory studies, mathematical models are developed that describe the “human–monitoring system–vehicle–traffic system” system. The issues of classifying operators according to their tendency to fall asleep and create emergency situations are explored. A statistical analysis of the accident rate of vehicle drivers was carried out based on their susceptibility to accidents. The degree of effectiveness and safety of monitoring systems is taken into account, as well as the influence of psychological factors caused by drivers excessive trust in the monitoring system. The risks associated with system malfunctions and insufficient efficiency of its operation are calculated. The use of an ineffective driver monitoring system does not reduce, but increases the likelihood of an accident. The design and principles of operation of a driver vigilance telemechanical control system (DVTCS) are described. The device is designed for continuous monitoring of the drivers vigilance and attentiveness while driving rolling stock. The work of DVTCS is based on scientific results according to which episodic changes in skin resistance reflect the level of alertness and wakefulness. It has been shown that due to more reliable, continuous, and nondistracting monitoring of the drivers physiological state the DVTCS provides a higher level of traffic safety than its “Safety Handle” counterpart. Statistical data from operational and laboratory data have been analyzed, indicating a high level of operational safety of the DVTCS. A comparison of Russian and international requirements for the safety level of DVTCS has been carried out. Methods for further improvement of the device are noted.
期刊介绍：
The purpose of the journal is to publish high-quality peer-reviewed scientific and technical materials that present the results of fundamental and applied scientific research in the field of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The policy of the journal provides for the rapid publication of original scientific articles, analytical reviews, articles of the world''s leading scientists and specialists on the subject of the journal solicited by the editorial board, special thematic issues, proceedings of the world''s leading scientific conferences and seminars, as well as short reports containing new results of fundamental and applied research in the field of mathematical theory and methodology of image analysis, mathematical theory and methodology of image recognition, and mathematical foundations and methodology of artificial intelligence. The journal also publishes articles on the use of the apparatus and methods of the mathematical theory of image analysis and the mathematical theory of image recognition for the development of new information technologies and their supporting software and algorithmic complexes and systems for solving complex and particularly important applied problems. The main scientific areas are the mathematical theory of image analysis and the mathematical theory of pattern recognition. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. Articles can be submitted either in English or Russian. The English language is preferable. Pattern Recognition and Image Analysis is a hybrid journal that publishes mostly subscription articles that are free of charge for the authors, but also accepts Open Access articles with article processing charges. The journal is one of the top 10 global periodicals on image analysis and pattern recognition and is the only publication on this topic in the Russian Federation, Central and Eastern Europe.
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