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Severity Analysis of Vehicle Traffic Accidents Based on XGBoost and SHAP
CHEN Kailiang
2023, 48(4):
179-185.
DOI: 10.16638/j.cnki.1671-7988.2023.04.036
In order to study the significant factors affecting the severity of four-wheeled vehicle
traffic accidents, and to grasp their occurrence characteristics and regularities, 2 966 four-wheeled
vehicle accidents in the China in-depth acciddent study (CIDAS) database are modeled to include
the 19 factors including people-vehicle-road- environment are used as input and the accident result
is used as output. In the research, an evaluation system including accuracy, precision, recall, F-1
score are introduced, and the XGBoost model is compared with LightGBM, random forest and
CatBoost models side by side, which proved its excellent classification performance. In addition,
SHAP is used to visually analyze the model to explore the influence of various factors on the
severity of the accident. The results show that, for minor injury/serious injury/death, the most critical influencing factors are collision type, personnel category, and collision type. In order to
avoid the occurrence of fatal accidents, we can pay more attention to and prevent unilateral
collisions of passengers/trucks, and the accident is characterized by starting, running off course
under the high speed limit road, colliding with the target vehicle, or hitting an obstacle. And should
pay attention to the slack psychology of drivers who drive on the 30~60 km/h speed limit road.
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