Seasonal regulation of vehicle traffic on the roads of the timber industry complex

The paper touches upon one of the issues of seasonal weight restrictions on the movement of vehicles, which are established for roads of regional and local importance in the Arkhangelsk region, which negatively affect the functioning of timber transport logistics for periods of spring and autumn thaws. The relevance lies on the urgent need to introduce differentiated deadlines for weight restrictions instead of prescriptively assigned uniform deadlines for different regions. The novelty of the study lies on the fact that in the mathematical processing of empirical data on the course of air temperature, a qualitatively new approach was founded on statistical dynamics, the main tool of which is cross-spectral analysis of air temperature series. The basis for the study was an array of long-term data on daily air temperatures with a 50-year retrospective and a volume of 1800 units/year, from the archives of the Northern Administration for Hydrometeorology and Environmental Monitoring. The data was grouped into 3?50 dynamic series, with 365 daily temperature values in each series. Next, an analysis of the statistical quality of the empirical data was carried out, after which the time series were processed by cross-spectral analysis. As a result, the ability to objectively, with a high degree of accuracy and reliability, determine the dates of temperature inversions, as well as shifts in air temperature graphs in various natural and climatic conditions relatively to the accepted base weather station, was confirmed. This, in turn, serves as a starting point for the next stage of the study – correct timing of seasonal freezing and thawing of similar soils and using them as a basis for introducing and removing weight restrictions on the movement of vehicles. The authors reasonably believe that the use of this methods is also possible in the agro-industrial complex of the Russian Federation, for example, when solving problems related to the long-term variation of air temperature and requiring high reliability of the results.