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Tytuł pozycji:

Forecasting the number of road accidents in Poland using weather-dependent trend models

Tytuł:
Forecasting the number of road accidents in Poland using weather-dependent trend models
Autorzy:
Gorzelańczyk, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/2203615.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Tematy:
traffic accident
forecasting
trend model
weather conditions
Źródło:
Technical Sciences / University of Warmia and Mazury in Olsztyn; 2023, 26(1); 57--76
1505-4675
2083-4527
Język:
angielski
Prawa:
CC BY: Creative Commons Uznanie autorstwa 3.0 PL
Dostawca treści:
Biblioteka Nauki
Artykuł
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Every year a very large number of people die on the roads. From year to year, the value decreases, there are still a very high number of them. The pandemic has reduced the number of road accidents, but the value is still very high. For this reason, it is necessary to know under which weather conditions the highest number of road accidents occur, and to know the forecast of accidents according to the prevailing weather conditions for the coming years, in order to be able to do everything possible to minimize the number of road accidents. The purpose of the article is to make a forecast of the number of road accidents in Poland depending on the prevailing weather conditions. The research was divided into two parts. The first was the analysis of annual data from the Police statistics on the number of road accidents in Poland in 2001-2021, and on this basis the forecast of the number of road accidents for 2022-2031 was determined. The second part of the research, dealt with monthly data from 2007-2021. Again, the analyzed forecast for the period January 2022-December 2023 was determined. The results of the study indicate that we can still expect a decline in the number of accidents in the coming years, which is particularly evident when analyzing annual data. It is worth noting that the prevailing pandemic distorts the results obtained. The research was conducted in MS Excel, using selected trend models.

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