Analysis of Data in Solving the Problem of Reducing the Accident Rate Through the Use of Special Means on Public Roads

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 1 June 2022 through 4 June 2022; 180242; 180242

Год издания: 2022

Идентификатор DOI: 10.1109/IEMTRONICS55184.2022.9795842

Ключевые слова: public roads, road accidents, statistical data, traffic

Аннотация: The purpose of this study is to conduct a statistical analysis of road accidents in the Russian Federation. The article considers ways to reduce accidents and are effective and efficient, as well as statistics given in the period from 1991 to 2019. The main causes of accidents have been identified, which is an essential aspect for Показать полностьюreducing the accident rate. The analysis of statistical data on the number of accidents, population, length of roads, number of vehicles other than motorcycles and the general road situation available at the moment and several years ago, as well as the main causes of accidents and measures to reduce accidents. This analysis has led to correct and effective results and solutions to improve the situation on the roads. At the same time, the integrated measures implemented and being implemented at the moment, such as federal targeted, regional and local programs, as well as road safety strategies, are more likely to reduce road accidents. Statistical data and methods used are taken into account, the effectiveness of which is decreasing. Development of methods appropriate to the current situation is a necessity. © 2022 IEEE.

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Издание

Журнал: 2022 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2022

Издатель: 2022 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2022

Персоны

  • Kukartsev V. (Department of Information Economic Systems, Reshetnev Siberian State University of Science and Technology, Russian Federation, Siberian Federal University, Department of Informatics, Krasnoyarsk, Russian Federation, Bauman Moscow State Technical University, Digital Material Science: New Materials and Technologie, Krasnoyarsk, Russian Federation)
  • Mikhalev A. (Siberian Federal University, Department of Informatics, Krasnoyarsk, Russian Federation)
  • Stashkevich A. (Reshetnev Siberian State University of Science and Technology, Department of System Analysis, Krasnoyarsk, Russian Federation)
  • Moiseeva K. (Reshetnev Siberian State University of Science and Technology, Information Control Systems Department, Krasnoyarsk, Russian Federation)
  • Kauts I. (Reshetnev Siberian State University of Science and Technology, Department of System Analysis, Krasnoyarsk, Russian Federation)

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