# Theoretical background and literature review

Road safety as a scientific discipline is based on the experience of many scientific fields, such as urban planning, mathematics, and road traffic management. All this makes it an interdisciplinary field. This paper is built on the logic of the theory-empirics-model. (Jamroz, 2008) points out that there are four types of theories in road safety (stochastic, causal, systemic and behavioural). This article uses the stochastic theory, namely _random events theory_, with Bortkiewicz, who discovered that the distribution of killed in road accidents in a year is almost perfectly random and the Poisson model gives a good description of the random process (Bortkiewicz, 1898; Jamroz, 2008) as the authors investigate the accidents as random events. Bortkiewicz investigated that accidents are purely unexpected and that we do not have control over them (Elvik et al., 2009). By causal theories, it is claimed that human factors are major research problem, estimating that 90% of road accidents are connected with human factors (alcohol, training, age) (Jamroz, 2008). However, these factors were not explored in this research.

Most os the previous models predict the number of road accidents taking into account the severity of accidents, casualty count and the number of vehicles involved (Gatarić et al., 2023; Pourroostaei Ardakani et al., 2023). Previously, logistic regression and other data mining techniques and machine learning has been used as the statistical method for prediction (Ait-Mlouk et al., 2017; Mohanta et al., 2022). However, the authors of this research focus on the model predicting the number of fatal accidents on the road across the countries based on Poisson distribution, the topic which has not been studied in detail.