Prediction and analysis of the severity of road traffic accidents at traffic signs under rainstorm conditions

Yao Ge; Heyi Zhao; Tong Liu

doi:10.1117/12.3051342

20 January 2025 Prediction and analysis of the severity of road traffic accidents at traffic signs under rainstorm conditions

Yao Ge, Heyi Zhao, Tong Liu

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 134221J (2025) https://doi.org/10.1117/12.3051342
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

The road driving environment is an important factor affecting the severity of traffic accidents. In this paper, the traffic accident at traffic signs under the condition of a rainstorm is taken as the research object to explore the causes and influencing factors of the accident. Based on the traffic accident cases in the US Accidents (2016–2023) database, this paper analyzes the distribution characteristics of the accident data, uses SMOTE technology to form a balanced dataset, and then uses XGBoost machine learning method to build a traffic accident prediction model. Finally, combined with SHAP interpretable analysis, the relationship between various factors and the severity of traffic accidents is further revealed. The results show that traffic jam distance, climatic conditions (temperature, air pressure, humidity), and road conditions are the important factors that cause traffic accidents under these conditions. According to the research results, this paper puts forward some suggestions to reduce accidents from the perspective of traffic management, which provides a new perspective and information for accurate accident prevention and control.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yao Ge, Heyi Zhao, and Tong Liu "Prediction and analysis of the severity of road traffic accidents at traffic signs under rainstorm conditions", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 134221J (20 January 2025); https://doi.org/10.1117/12.3051342

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