Analyzing Pile-Up Crash Severity: Insights from Real-Time Traffic and Environmental Factors Using Ensemble Machine Learning and Shapley Additive Explanations Method

Analyzing Pile-Up Crash Severity: Insights from Real-Time Traffic and Environmental Factors Using Ensemble Machine Learning and Shapley Additive Explanations Method

Pile-up (PU) crashes, which involve multiple collisions between more than two vehicles within a brief timeframe, carry substantial consequences, including fatalities and significant damages. This study aims to investigate the real-time traffic, environmental, and crash characteristics and their inte...

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Bibliographic Details
Main Authors: Seyed Alireza Samerei, Kayvan Aghabayk, Alfonso Montella
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Safety
Subjects:
pile-up crash
crash severity
machine learning
SHAP method
Online Access:https://www.mdpi.com/2313-576X/10/1/22

Internet

https://www.mdpi.com/2313-576X/10/1/22

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