PROBABILISTIC MODEL FOR ASSESSING ACCIDENT RATES

Anastasia Shevtsova; Aleksandr Novikov; Sergey Evtyukov; Alexey  Marusin

doi:10.5937/jaes0-42942

Anastasia Shevtsova Belgorod State Technological University named after V.G. Shukhov, Belgorod, Russia
Aleksandr Novikov Orel State University named after I.S. Turgenev, Orel, Russia https://orcid.org/0000-0001-5496-4997
Sergey Evtyukov Saint Petersburg State University of Architecture and Civil Engineering, Saint Petersburg, Russia https://orcid.org/0000-0003-3674-643X
Alexey Marusin Saint Petersburg State University of Architecture and Civil Engineering, Saint Petersburg, Russia https://orcid.org/0000-0001-5238-2758

DOI: https://doi.org/10.5937/jaes0-42942

Keywords: accident rates, statistical databases, relative indicators, dependencies, probabilistic model, algorithm, efficiency

Abstract

When working with accident rates, a specialist has to spend quite a lot of time to establish the main places of accidents, certain conditions in which they occurred, which is extremely necessary when determining measures aimed at reducing road accidents. As a result of the research, the authors processed a large amount of data - accident rates for 2015-2021, as a result of which certain dependencies were established between the considered indicators in relative data, which made it possible to develop a probabilistic model for calculating the necessary data with the ability to determine the required conditions. Based on the results obtained, the authors developed an algorithm, according to which procedures were determined when working with accident rates and an assessment of efficiency based on the calculation of the error was carried out. The results obtained allowed us to conclude that the developed probabilistic model and algorithm are effective, in view of the minimum error.

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