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DOI: 10.23977/jvits.2020.020101 | Downloads: 22 | Views: 3825


Sergey Lyapin 1, Yulia Rizaeva 1, Dmitry Kadasev 1, Irina Kadaseva 1


1 FGBOU VO "Lipetsk State Technical University", 398055, st. Moscow, d. 30, Lipetsk, Russia

Corresponding Author

Sergey Lyapin


The article justifies the necessity to develop Russia's national road transport network and integrate it into the world economic space in order to realize its transit potential in the system of Euro-Asian international transport corridors more effectively as well as to increase the volume of transport service exports. Introducing an intelligent transport and logistics system (ITLS) it is possible to ensure road safety which will increase economic efficiency and integrated safety of transport corridors because traffic accidents (TA) have a detrimental effect on the social and economic development of any country. Drivers of vehicles (Vs) can be informed as a group or individually about the risk of an accident and the need to change the speed or location of the vehicle on the road. It is suggested that the problem can be solved online by using the parametric identification of the ITLS elements and the neural network management of the classification and regulation process. The process of training the neural network and the principles of its operation are presented.


traffic accident, intelligent transport and logistics system, probability assessment, road safety


Sergey Lyapin, Yulia Rizaeva, Dmitry Kadasev and Irina Kadaseva. THEORY OF ASSESSING ACCIDENT PROBABILITY IN INTELLIGENT TRANSPORT AND LOGISTICS SYSTEMS. Journal of Vehicle and Intelligent Transport System (2020) 2: 1-10. DOI:


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