The Application of Machine Learning for Risk Management of Traffic Collision

At the moment, machine learning is increasingly being used in risk management of road traffic accidents in logistics systems. This is primarily due to the large amount of information that appears every second in the individual links of the logistics system and subsequently continuously circulates through the logistics channels. Besides, An important fact is the development of Internet of things technologies in the transport industry, which generates huge amounts of data about movements, transactions, behavior, and other various operational procedures. The fundamental goal of this final qualification paper is to compare the various machine learning methods and procedures used to model the risks of an accident. The relevance of the work is the fact that in modern logistics circles there is practically no comprehensive analysis of various machine learning methods that can be effectively used not only to model conventional operational types of logistics activities, but also manage risks, including road traffic accidents The main methods that appear in the current final qualification work are: theoretical analysis of the literature based on the study and collection of various information, comparative analysis and mathematical modeling through machine learning.