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This research focuses on the issues of rational use of motor vehicle performance indicators to organize and manage road freight transportation efficiently. The authors examine the variability of transportation metrics and develop quantitative models that link these metrics to operational indicators. The research identifies functional relationships and distribution patterns between several randomly determined constant factors, the number of daily vehicle trips, and overall work productivity. Furthermore, the authors developed an algorithm to account for basic processes and develop mathematical models that address consumer transportation needs. Using the structure of this algorithm, initial data from multiple operators were incorporated, establishing iterative functional connections and distribution laws between these data and the operational indicators.

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Probabilistic Modeling of the Number of Trips and Performance of Vehicles During Cargo Transportation

  • 章节

  • 发表日期：

    2025年

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  • Mukhiddin N. Juraev,
  • Gaffor A. Samatov,
  • Zokirkhon Y. Yusufkhonov

摘要

This research focuses on the issues of rational use of motor vehicle performance indicators to organize and manage road freight transportation efficiently. The authors examine the variability of transportation metrics and develop quantitative models that link these metrics to operational indicators. The research identifies functional relationships and distribution patterns between several randomly determined constant factors, the number of daily vehicle trips, and overall work productivity. Furthermore, the authors developed an algorithm to account for basic processes and develop mathematical models that address consumer transportation needs. Using the structure of this algorithm, initial data from multiple operators were incorporated, establishing iterative functional connections and distribution laws between these data and the operational indicators.