In this article, the authors reviewed the existing system of weight control of heavy vehicles in the Russian Federation. In this research, the main shortcomings of the system, which prevent its effective functioning in relation to the use of road infrastructure, were determined. To solve these problems, we developed a model of the functionality of a telematic automated system of weight control of heavy vehicles, as well as defining the optimization tasks of the transportation process. Mathematical modeling of the operational factors that influence the system of weight control of heavy vehicles on roads was carried out. As a result of the research, the most significant parameters that have the greatest impact on the efficiency of the road were determined. By means of these parameters, it is feasible to choose suitable hardware and equipment for a weight control system. The methodology of developing automatic points for the weight control of heavy loads during road transportation was formulated. As a result of the study, it was concluded that the introduction of a telematic automated system of weight control of heavy vehicles would increase the efficiency of road transport on the highway by positively affecting its basic transport and performance indicators.

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The article discusses a new method of automatic vehicle identification system (AVIS) based on the developed system of vehicle traffic control using matrix QR-code, which solves the problem of segmentation of license plates and signs of different formats (signs of the QR-code type with a different number of characters). The system has been created in order to recognize segmented characters from the same input sets that have the same size without overlapping letters and sets of numbers. It is proposed to apply a method for recognizing non-standard characters, based on the use of a mixed pattern method, the degree of compliance. Based on testing of 100 samples of templates and signs, experiments and images taken in real conditions of vehicle operation, it can be stated, that this method provides a recognition accuracy of 80.4%., for the mixed pattern method, it takes 1.7 seconds, and for the compliance templates it takes 0.75 second to perform the recognition operation when determining the adequacy of the application of the mixed method.

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