Traffic accident severity analysis in Barcelona using a binary probit and CHAID tree

Traffic accidents are still wide causation for fatalities around the globe. The set of alarm for this cause of deaths is still on, since the number of fatalities is still representing an enormous issue and a challenge for most governments. In Barcelona, similar to the rest of the world, traffic accidents are threatening lives and raising the need to lessen the number of both fatalities and severities. This study is conducted to grasp the correlations between different classification factors with accident severities and fatalities. A total of 47,153 traffic accident cases that occurred between 2016 and 2019 are utilized. Then, a binary probit model and Chi-square automatic interaction detector are exploited to grasp the impact of several risk factors. The results confirmed that males and 65 years and older injured persons are more exposed to severe or fatal injuries compared to other categories. Pedestrians and drivers are found to have higher probabilities compared to passengers in being involved in severe or fatal injuries. Weekends, afternoon, night timings all have higher odds of having severe or fatal traffic accidents. The findings of this study can help road authorities in targeting these risk factors to mitigate their impact to achieve Vision Zero.Peer ReviewedPostprint (author's final draft