Methodology for Optimizing Factors Affecting Road Accidents in Poland

Piotr Gorzelanczyk () and Henryk Tylicki
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Piotr Gorzelanczyk: Transport Department, Stanislaw Staszic State University of Applied Sciences in Pila, ul. Podchorazych 10, 64-920 Pila, Poland
Henryk Tylicki: Transport Department, Stanislaw Staszic State University of Applied Sciences in Pila, ul. Podchorazych 10, 64-920 Pila, Poland

Forecasting, 2023, vol. 5, issue 1, 1-15

Abstract: With the rapid increase in the number of vehicles on the road, traffic accidents have become a rapidly growing threat, causing the loss of human life and economic assets. The reason for this is the rapid growth of the human population and the development of motorization. The main challenge in predicting and analyzing traffic accident data is the small size of the dataset that can be used for analysis in this regard. While traffic accidents cause, globally, millions of deaths and injuries each year, their density in time and space is low. The purpose of this article is to present a methodology for determining the role of factors influencing road accidents in Poland. For this purpose, multi-criteria optimization methods were used. The results obtained allow us to conclude that the proposed solution can be used to search for the best solution for the selection of factors affecting traffic accidents. Furthermore, based on the study, it can be concluded that the factors primarily influencing traffic accidents are weather conditions (fog, smoke, rainfall, snowfall, hail, or cloud cover), province (Lower Silesian, Lubelskie, Lodzkie, Malopolskie, Mazovian, Opolskie, Podkarpackie, Pomeranian, Silesian, Warmian-Masurian, and Greater Poland), and type of road (with two one-way carriageways; two-way, single carriageway road). Noteworthy is the fact that all days of the week also affect the number of vehicle accidents, although most of them occur on Fridays.

Keywords: multi-criteria optimization; traffic accident; factors affecting traffic accidents (search for similar items in EconPapers)
JEL-codes: A1 B4 C0 C1 C2 C3 C4 C5 C8 M0 Q2 Q3 Q4 (search for similar items in EconPapers)
Date: 2023
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