Abstract
As the number of vehicles on the road increases, traffic accidents are becoming more destructive, causing loss of life and work. This is due to rapid population growth and the development of motorization. The most important challenge in estimating and studying information about street twists of fate is the small amount of facts available for this analysis. Although car accidents kill and injure millions of people around the world each year, they are rare in time and space. The motive of this article is to advise an effective approach to estimating the number of accidents on Poland’s roads, based primarily on a combination of factors affecting such layered situations. The methodology presented in this paper for the use of multi-criteria optimization procedures using a multi-criteria optimization model (a set of forecasting methods, sub-criteria of the criterion function, and elements of the dominance relationship) allows us to conclude that the above methodology can be used to optimize methods for forecasting road accidents in Poland.
Publisher
Highlights of Science, S.L.
Reference45 articles.
1. World Health Organization. (2020). Global status report on road safety 2020. https://www.who.int/violence_injury_prevention/road_safety_status/report/en (accessed 10 May 2022).
2. European Union. (2022). Eurostat Statistics. https://ec.europa.eu/eurostat (accessed 10 May 2022).
3. Statystyka. (2022). Police Statistics. https://statystyka.policja.pl (accessed 10 May 2022).
4. Tambouratzis, T., Souliou, D., Chalikias, M., & Gregoriades, A. (2014). Maximising accuracy and efficiency of traffic accident prediction combining information mining with computational intelligence approaches and decision trees. Journal of Artificial Intelligence and Soft Computing Research, 4(1), 31–42. https://doi.org/10.2478/jaiscr-2014-0023
5. Zhu, L., Lu, L., Zhang, W., Zhao, Y., & Song, M. (2019). Analysis of accident severity for curved roadways based on Bayesian networks. Sustainability, 11(8), 2223. https://doi.org/10.3390/su11082223