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T-Comm_Article 4_2_2022

ABOUT METHODS FOR COLLECTING AND ANALYZING TRAFFIC FLOW CHARACTERISTICS

Marina S. Moseva, Moscow Technical University of Communications and Informatics, Moscow, Russia, m.s.moseva@mtuci.ru

Abstract
The ever-increasing motorization leads to the need to solve problems related to the optimal movement of transport, ensuring its safety and improving the environmental situation. According to Rosstat statistics, the number of own cars in the constituent entities of the Russian Federation (per 1,000 people) is increasing every year. The issues of optimal control of the movement of vehicles remain topical. Modeling of traffic flows allows you to determine the “bottlenecks” of the existing road network. In most situations, the best solution to the above problems is to improve the existing transport system. This approach is quite expensive. In this regard, studies related to the development and application of modern and promising technologies in the creation of intelligent transport systems of various levels and purposes are relevant both today and in the future. The collection and analysis of data on traffic flows allows you to verify the models, as well as make decisions about the further management of the movement of vehicles. With the development of computer technology and information technology, methods for accumulating and processing information about traffic flows have been improved. Today it becomes possible to receive, process data and make decisions in real time. This study is devoted to an overview of existing methods for monitoring and collecting characteristics about the state of traffic flows. A review of modern technologies and sensors used to collect traffic information is made. The method for collecting data on road users is described. An algorithm for classifying vehicles depending on the brand of the vehicle has been developed. The description of the vehicle tracking algorithm is given. The method for calculating the main characteristics of the traffic flow (speed, density, intensity) based on data from the video sequence is described.

Keywords: traffic flow monitoring, vehicle classification, neural network algorithm, calculation of traffic flow characteristics.

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Information about author:

Marina S. Moseva, Department of Mathematical Cybernetics and Information Technologies, Moscow Technical University of Communications and Informatics, Moscow, Russia