Digital management of traffic safety improvement programs
Abstract
The article discusses the issues of digital management of road safety improvement programs (RSI). Neural networks allow for the consideration of nonlinear dependencies and complex interrelations, which can improve the accuracy of forecasts of basic indicators compared to traditional econometric models. At the macroeconomic forecasting level, artificial intelligence is used to analyze large amounts of data in order to forecast various indicators – technical, economic, and social in the field of transport infrastructure and road safety. At the same time, various levels of management are used. In 2018, the Road Safety Strategy for 2018-2024 was approved. The article discusses the results of the Strategy's implementation and methods for improving programs and their implementation in the field of road safety through digital management.
About the Authors
Eduard A. Safronov
SibADI
Russian Federation
Russian Federation
Doctor of Sciences (Technical), Professor
Ekaterina S. Semenova
SibADI
Russian Federation
Russian Federation
Candidate of Sciences (Economic), associate professor,
Anatoliy E. Semenov
OmSTU
Russian Federation
Russian Federation
student
References
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Review
Рецензент: С.М. Мочалин, д-р техн. наук, проф. ФГБОУ ВО СибАДИ
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