Abstract

This study aims to investigate the possible relationships of risk factors related to traffic accidents playing important roles in increasing the likelihood of accidents. In the previous studies, parametric models are mostly used to investigate the causes of traffic accidents. As a non-parametric data mining model with its increasing usage in recent years; association rule mining was employed in this study to analyse the traffic accident data for the period of 2015 and 2020 in the city of Sakarya, Turkey. The analysis of the data studied revealed the relationships among the external/environmental, driver, road, vehicle and nature of accident factors. Some important rules regarding accidents occurring on daylight came into prominence within the scope of this study. In addition, the correlations between the driver casualties and their education level and ages are established to be related. The findings are beneficial for transportation authorities to apply effective operational strategies and campaigns to increase the road safety.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.