Forecasting the Number of Road Accidents in Poland and Hungary Using Neural Networks

The incidence of road accidents in Poland and Hungary has been on a downward trend annually, a pattern that is also evident globally. Although the recent pandemic has impacted these statistics, the total remains alarmingly high. Consequently, it is crucial to implement all possible strategies to reduce this figure further. This article aims to project future road accidents in Poland and Hungary. To achieve this, we analysed yearly statistics regarding road accidents in the two nations. Utilising data from the Polish Police and the Hungarian Central Statistical Office, we made forecasts from 2024 to 2030. Several selected neural network models were employed for this predictive analysis. The findings indicate that we can anticipate a continued stabilisation in the number of road accidents. Several factors, including the rising number of vehicles on the roads and the development of new highways, influence this trend. Additionally, the chosen sizes for the sample sets (learning, testing, and validation) play a significant role in the results obtained.

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Publication Details

Journal
Periodica Polytechnica Civil Engineering
Published
2025-08-12
DOI
https://doi.org/10.3311/ppci.41167
Citations
1
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
1.30
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article

Forecasting the Number of Road Accidents in Poland and Hungary Using Neural Networks

Piotr Gorzelańczyk, Viktoria Ötvös
1 citations
Periodica Polytechnica Civil Engineering
Traffic and Road Safety
1.30
article

Forecasting the Number of Road Accidents in Poland and Hungary Using Neural Networks

Piotr Gorzelańczyk, Viktoria Ötvös
article en
1 citations

Abstract

The incidence of road accidents in Poland and Hungary has been on a downward trend annually, a pattern that is also evident globally. Although the recent pandemic has impacted these statistics, the total remains alarmingly high. Consequently, it is crucial to implement all possible strategies to reduce this figure further. This article aims to project future road accidents in Poland and Hungary. To achieve this, we analysed yearly statistics regarding road accidents in the two nations. Utilising data from the Polish Police and the Hungarian Central Statistical Office, we made forecasts from 2024 to 2030. Several selected neural network models were employed for this predictive analysis. The findings indicate that we can anticipate a continued stabilisation in the number of road accidents. Several factors, including the rising number of vehicles on the roads and the development of new highways, influence this trend. Additionally, the chosen sizes for the sample sets (learning, testing, and validation) play a significant role in the results obtained.

Periodica Polytechnica Civil EngineeringVol. 69(3)
Budapest University of Technology and Economics (HU), Institute for Transport Sciences (HU), Stanisław Staszic University of Applied Sciences in Piła (PL)
Good health and well-being
Openalex Percentile: Top 18%
Traffic and Road Safety
1.30
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Forecasting the Number of Road Accidents in Poland and Hungary Using Neural Networks — Piotr Gorzelańczyk, Viktoria Ötvös · Periodica Polytechnica Civil Engineering (2025) | TGRS Research Map | TGRS