Addis Ababa City Road Traffic Accident Severity Dataset

This dataset contains traffic accident records from Addis Ababa City, Ethiopia, spanning the years 2016 to 2022. The dataset includes <b>13,064 rows</b> and <b>31 features</b> related to various factors influencing road traffic accident severity. The target variable is categorized into three severity levels: <b>slight</b>, <b>serious</b>, and <b>fatal injuries</b>.The dataset aims to facilitate the analysis and prediction of road traffic accident severity using machine learning algorithms. It was initially collected by the <b>Addis Ababa Police Department</b> and contains a rich set of variables, including <b>weather conditions, collision type, driver demographics, road conditions, and time of accident</b>, among others. This comprehensive dataset serves as a foundation for developing predictive models for accident severity, which can be valuable for urban planning, traffic safety research, and policy development.Key features in the dataset include:<b>Accident Severity</b> (Target Variable): Categorical variable indicating the severity of the accident (slight, serious, fatal).<b>Weather Conditions</b>: Describes the weather at the time of the accident (e.g., clear, rainy, foggy).<b>Collision Type</b>: The type of collision (e.g., rear-end, side-impact).<b>Driver Demographics</b>: Features like <b>driver age</b>, <b>driver sex</b>, and <b>experience</b> that may affect accident outcomes.<b>Location</b>: Various aspects of the accident location, including <b>junction type</b>, <b>road type</b>, and <b>alignment</b>.<b>Temporal Features</b>: Time-related variables such as <b>day of the week</b>, <b>time of day</b>, and <b>seasonal trends</b>.<b>Vehicle Information</b>: Includes <b>vehicle type</b>, <b>vehicle defect</b>, <b>vehicle movement</b>, and the relationship between the vehicle owner and the driver.<b>Casualty Information</b>: Includes <b>age</b>, <b>sex</b>, and <b>fitness of the casualty</b>.