Road traffic accidents, especially occurring on road sections outside of populated areas, are characterized by high severity of consequences and, therefore, are one of the main safety problems of the technosphere. Studies of many authors confirm the importance of the influence of meteorological parameters on the accident rate. However, most results don’t contain quantitative data demonstrating how risk of occurring a car accident depends on weather conditions. Research of this article assesses the impact of five main meteorological parameters on the accident rate using as example one of the Russian Federal roads. Nonlinear dependences of weather conditions and road accident risk were obtained by means of calculation of frequencies. The results are presented in the form of graphical dependencies. As a result of approximation there were found formulas that describe the relationship between values of meteorological parameters and the variation of a car accident risk. According to probability theory, the mathematical model can be based on the multiplication of risks caused by each meteorological parameter.

Introduction. Reducing the number of road traffic fatalities and aiming for zero deaths by 2030 is a key road safety government goal. The prevention of especially serious road accidents is one of the elements of achieving this goal. Analysis of the main factors contributing to the especially serious road accidents occurrence is the basis of an effective system for their prevention. A review of the scientific literature reveals a lack of knowledge in this area.Materials and methods. The study was performed on the basis of especially serious road accidents sample. The accidents that occurred in the regions of the Siberian Federal District in the period from 2017 to 2020 were analyzed. The following parameters were analyzed: the number of dead and injured, the type of accident, the period of the day, the day of the week, the month of the year, the weather conditions and the condition of roadway. The study is based on a multidimensional frequency distribution. The calculations and graphs were made using MS Excel and Statistica.Results. The results are presented using 2D and 3D histograms and cross tables. An analysis of the especially serious road accidents structure made it possible to distinguish two groups of accidents that differ in the number of the injured and dead. The influence of the analysed factors contributing to the especially serious road accidents occurrence is determined.Practical importance. Knowledge of the factors influence on the frequency of especially serious road accidents occurrence will allow public services to effectively plan measures to prevent such accidents and respond to them. This will reduce the number of road accidents deaths.Originality. Two groups of road accidents with especially serious consequences are identified and substantiated. It was found that the factors have different effects on the distribution of accidents in these groups. The study contains new knowledge of the factors contributing to the especially serious road accidents occurrence.

The use of neural networks promotes flexible non-linear modelling. Also, it is the perspective direction. The article investigates the influence of the main road characteristics on the accident rate. Twelve variables are selected as the main road characteristics. The result of modelling is the two-layer feed-forward neural network with hidden sigmoid nodes and linear output nodes. The operability of the model is estimated by calculating the index of regression by training, validation and testing. The results are acceptable for the intended purpose. The resulting model can be used for assessing and forecasting the safety rate on the two-lane roads with the intensity of 120 to 340 cars/hour. These include a significant part of the streets of CIS countries and other states. Besides, the neural network model can become the basis for the development of software products for assessing the accident rate based on road characteristics or can be implemented in existing software.

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Introduction. Road safety is one of the state targets. One of the indicators of the state of road traffic accidents in state programs is the number of traffic accident-prone section. Reducing their number will lead to a significant increase in the level of security. This is due to the fact that a large number of accidents, deaths and injuries are concentrated in these sections. Therefore, the task of determining the factors of the formation of traffic accidentprone section is relevant.Materials and methods. The study is based on data on accidents that occurred on the federal motorways of the Altai Territory in the period from 2018 to 2021. The procedure for performing the work included three stages. At the first stage, traffic accident-prone section was identified based on the data for 2021. At the second stage, the features of accidents in these sections in previous years were determined. At the third stage, the main factors of accident formation were determined by analyzing the layout of traffic management tools, video material on roads (road shooting).Results. A comprehensive analysis of traffic accident-prone section of federal roads in the Altai Territory allowed to identify a number of typical conditions that contribute to the formation of increased accident risk. Among them: a significant change in the speed limit, proximity to the city, the presence of a large number of conflict points, road works.The scope of the study / the possibility of subsequent use of the results of scientific work. The results of the work can be used in the work on the comprehensive study of the factors of occurrence of traffic accident-prone section on federal motorways, modelling various road conditions and environmental conditions on the degree of accident of a road section.Practical importance. Knowledge about the main factors and conditions of the formation of traffic accidentprone section will allow responsible services to reduce the degree of danger of similar sections by preventing the simultaneous action of all selected conditions.Originality. For the first time, the study identifies and substantiates specific conditions that collectively contribute to the formation of traffic accident-prone section on federal roads.