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Aug 30, 2023

Research on the Influencing Factors of Traffic Crash Severity during the Initial Period of COVID-19 and COVID-19 Pandemic Based on CatBoost and SHAP Algorithm: A Case Study in Texas

ABSTRACT

After the outbreak of COVID-19, traffic patterns and traffic composition have significantly changed. This paper explores the leading causes of traffic crashes and the impact of COVID-19 on traffic crashes. In this paper, the CatBoost algorithm is used to build a classification model of the causes of traffic crashes, and the accuracy of the model is tested by confusion matrix, f1-score, accuracy, recall, and precision. The influence degree of crash characteristics of the model that has passed the accuracy test is ranked by the importance degree using the SHAP algorithm. The different causes of traffic crashes during the initial stage and the pandemic stage are analyzed. Through the analysis, it is found that the speed limit, COVID-19, and the percentage of trucks in the average daily traffic volume significantly impact the severity of the crash, and the factor of COVID-19 also has a particular interaction with other crash characteristics.

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Go to CICTP 2023
CICTP 2023
Pages: 1006 - 1016

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Published online: Aug 30, 2023

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Tianyang Cui [email protected]
1School of Transportation, Southeast Univ., Jiangning District, Nanjing, China. Email: [email protected]
Weihan Chen [email protected]
2School of Transportation, Southeast Univ., Jiangning District, Nanjing, China. Email: [email protected]

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