Forecasting the volume of urban freight traffic

The efficient development of transportation vehicles in conditions of stiff competition and global digitalization depends on the correct methodology and forecasting of freight transportation. A review of scientific literature showed that all studies are directed towards the railway mode of transportation. The research conducted in this work focuses on freight transportation by road transport in the city of Almaty, where trucks remain the sole means of delivering goods from one point to another at the local transportation level. The main goal of the research presented in this article is to analyze statistical indicators of transportation volumes and freight turnover by road transport and develop software aimed at forecasting the expected volume of freight transportation. In logistics planning and management, the moving average method is employed to predict truckload volumes and freight turnover for the next year. This method works by averaging data points to smooth out random fluctuations, thereby providing a more stable forecast. This phenomenon arises from replacing the original levels of the time series with arithmetic means calculated for certain time intervals. To facilitate transportation volume planning and substantiate the optimality of freight transportation, it is necessary to have up-to-date statistical data. These statistic data serve as the basis for constructing a dynamic representation of automobile traffic volumes and freight turnover in the city of Almaty. The growth rates of indicators are calculated to assess dynamics. The forecasting aspect of freight transportation volume is addressed by developing an algorithm based on the moving average method.

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Publication Details

Journal
Bulletin of Turan University
Published
2024-10-04
DOI
https://doi.org/10.46914/1562-2959-2024-1-3-35-53-67
Primary Topic
Transportation Systems and Logistics
Type
article
Field-Weighted Citation Impact
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article

Forecasting the volume of urban freight traffic

Yekaterina Kim, Saule Belginova, Zhanar Bimurat, R. T. Ismailova
Bulletin of Turan University
Transportation Systems and Logistics
article

Forecasting the volume of urban freight traffic

Yekaterina Kim, Saule Belginova, Zhanar Bimurat, R. T. Ismailova
article en

Abstract

The efficient development of transportation vehicles in conditions of stiff competition and global digitalization depends on the correct methodology and forecasting of freight transportation. A review of scientific literature showed that all studies are directed towards the railway mode of transportation. The research conducted in this work focuses on freight transportation by road transport in the city of Almaty, where trucks remain the sole means of delivering goods from one point to another at the local transportation level. The main goal of the research presented in this article is to analyze statistical indicators of transportation volumes and freight turnover by road transport and develop software aimed at forecasting the expected volume of freight transportation. In logistics planning and management, the moving average method is employed to predict truckload volumes and freight turnover for the next year. This method works by averaging data points to smooth out random fluctuations, thereby providing a more stable forecast. This phenomenon arises from replacing the original levels of the time series with arithmetic means calculated for certain time intervals. To facilitate transportation volume planning and substantiate the optimality of freight transportation, it is necessary to have up-to-date statistical data. These statistic data serve as the basis for constructing a dynamic representation of automobile traffic volumes and freight turnover in the city of Almaty. The growth rates of indicators are calculated to assess dynamics. The forecasting aspect of freight transportation volume is addressed by developing an algorithm based on the moving average method.

Bulletin of Turan University(3)
Turan University (KZ), Mining Institute (RU)
Sustainable cities and communities
Openalex Percentile: Top 80%
Transportation Systems and Logistics
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