The methodology of the study is based on the formulation and formalization of goals and objectives, the development of models, algorithmic methods, and experimental evaluation through experiments, testing, approbation and analysis of the results. In the work were used the methods of developing information systems to support the processes of collecting information, analyzing, designing and implementing such systems, the theory of algorithms for the effective formulation of subtasks and assessing the complexity of algorithms, the theory of machine learning for analyzing the behavior of drivers, generating recommendations for the driver to take measures to prevent the onset of an emergency and improve driving skills, as well as methods for developing software for the implementation of an intelligent accident prevention system. The goal of the work is to research and develop methods and algorithms for the operational control of the driver's condition, as well as the creation of a software video tracking system based on the developed algorithms. The main objectives of the work: 1) analysis of existing technologies, devices and active safety systems for the driver of a vehicle, focused on early warning and prevention of traffic accidents, as well as existing methods and algorithms for intelligent analysis of video surveillance data; 2) modeling using two classifiers and algorithms' development for improving driver real time safety; 3) development of an automated video tracking system using the proposed methods.