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Forecasting the number of road accidents caused by pedestrians in Poland using neural networks

Author

Listed:
  • Piotr Gorzelańczyk

    (Stanislaw Staszic State University of Applied Sciences in Piła)

Abstract

Every year, fewer traffic accidents occur in Poland and throughout the world. Pandemics have recently impacted this number, but it is still relatively high. All efforts should be made to lower this figure. The article's main goal is to project the number of pedestrian-related traffic accidents in Poland based on yearly statistics. from 2001. A projection for the years 2024–2030 was created using police data. Various neural network models were employed to predict the number of incidents. The findings indicate that a stabilisation in traffic accidents is yet to be expected. One way to look at this is as a result of both Poland’s population reduction and the growing number of cars on the road. The number of random samples (training, test, and validation) selected has little effect on the outcomes.

Suggested Citation

  • Piotr Gorzelańczyk, 2024. "Forecasting the number of road accidents caused by pedestrians in Poland using neural networks," Cognitive Sustainability, Cognitive Sustainability Ltd., vol. 3(4), pages 5-14, December.
    • Handle: RePEc:bcy:issued:cognitivesustainability:v:3:y:2024:i:4:p:5-14
    DOI: 10.55343/CogSust.102
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    More about this item

    Keywords

    road accident; pandemic; forecasting; neural networks; pedestrian;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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