The Effect of Age and Experience on the Risk of a Traffic Accident

Abstract

Road traffic accidents are a major societal problem that has serious economic, social and health impacts on the population, and their causes can be linked to a number of factors including the age and experience of drivers. These variables make it possible not only to identify risk groups but also to design targeted measures aimed at effectively improving road safety. The aim of this study was to evaluate the relationship between demographic factors such as age and experience of drivers and the causes of road accidents in the Czech Republic in the period from 1 January 2014 to 31 December 2023. Correlation and graphical methods were used in this analysis, which provided a detailed overview of the relationships between the variables studied. The data obtained showed a strong linear dependency between the total number of crashes and the age categories of drivers, namely 18-34 years, 35-64 years and 65 years and over, as well as between their length of experience, where the most significant values were identified for drivers with 1-3 years of experience and 7 years and over, and different types of crashes, such as collisions with a moving non-road vehicle, a parked vehicle and a fixed obstacle. The results confirmed the existence of a positive linear relationship between all the variables studied, while the graphical analysis made it possible to visualize the trends in the frequency of crashes during the study period. The highest numbers of accidents were recorded in 2016-2019, while the lowest in 2023, suggesting a possible influence not only of demographic factors, but also of changes in legislation, infrastructure development and education programmes on driver behaviour. The identification of key risk factors is a major contribution of this work, as the results can serve as a basis for the design of preventive measures targeting specific age and experience groups of drivers. The most significant limitation of the work remains the distribution and nature of the secondary data, which may bias the accuracy of the conclusions and provides scope for further research aimed at more detailed data collection and analysis.