THE TRAFFIC INTENSITY AND THE NUMBER OF TRAFFIC ACCIDENTS BASED ON PROBABILITY THEORY AND MATHEMATICAL STATISTIC FORECASTING

  • Liliya Kushchenko Belgorod State Technological University named after V.G. Shukhov, Transport and technological institute, Department of operation and organization of vehicle traffic, Belgorod, Russia
  • Sergey Kushchenko Belgorod State Technological University named after V.G. Shukhov, Transport and technological institute, Department of operation and organization of vehicle traffic, Belgorod, Russia
  • Alexander Novikov Orel State University named after I.S. Turgenev, Polytechnic Institute, Department of service and machines' repair, Orel, Russia
  • Sergey Eremin Orel State University named after I.S. Turgenev, Polytechnic Institute, Department of service and machines' repair, Orel, Russia
Keywords: traffic intensity, traffic accident, vehicle, probability theory and mathematical statistics, forecasting, mathematical trend, Weibull distribution law, confidence intervals.

Abstract


Based on the collected experimental data on the number of vehicles moving along the street and road network of the urban agglomeration, a theoretical approach to predicting the number of vehicles based on mathematical statistics and probability theory is developed in the article. The obtained results of the intensity of vehicle traffic forecasting, together with the processed statistical data on the number of traffic accidents, make it possible to identify places with increased traffic accident rates for predicting the number of traffic accidents. The results of the predicted values of seasonal vehicle traffic intensity are given in the text (Table 1). The forecast results are within the confidence interval, which theoretically confirms the correctness of the obtained values. The theoretical approach to predicting the number of traffic accidents was obtained on the basis of the two-parameter Weibull distribution law. The results of the obtained numerical parameters of the statistical and theoretical distribution law λ(t) characteristics are shown in Table 3. An additional assessment was carried out when choosing the distribution curve λ(t), which makes it possible to implement the K. Pearson agreement criterion and its properties χ2. The theoretical approach allows you to assess the road traffic situation in an urban agglomeration with the subsequent implementation and implementation of organizational and technical measures to reduce road deaths.

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Published
2025/12/02
Section
Original Scientific Paper