A literature review of machine learning algorithms for crash injury severity prediction
Introduction: Road traffic crashes represent a major public health concern, so it is of
significant importance to understand the factors associated with the increase of injury …
significant importance to understand the factors associated with the increase of injury …
[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review
Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and developing effective road safety …
are a prerequisite for devising countermeasures and developing effective road safety …
Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis
Detecting traffic accidents as rapidly as possible is essential for traffic safety. In this study, we
use eXtreme Gradient Boosting (XGBoost)—a Machine Learning (ML) technique—to detect …
use eXtreme Gradient Boosting (XGBoost)—a Machine Learning (ML) technique—to detect …
The application of XGBoost and SHAP to examining the factors in freight truck-related crashes: An exploratory analysis
Due to the burgeoning demand for freight movement, freight related road safety threats have
been growing substantially. In spite of some research on the factors influencing freight truck …
been growing substantially. In spite of some research on the factors influencing freight truck …
[HTML][HTML] A study on road accident prediction and contributing factors using explainable machine learning models: analysis and performance
Road accidents are increasing worldwide and are causing millions of deaths each year.
They impose significant financial and economic expenses on society. Existing research has …
They impose significant financial and economic expenses on society. Existing research has …
Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study
A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …
prediction and effective implementation of appropriate mitigation strategies. Traditional …
Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model
A Hosseinzadeh, A Moeinaddini… - Journal of safety …, 2021 - Elsevier
Introduction: Reducing the severity of crashes is a top priority for safety researchers due to
its impact on saving human lives. Because of safety concerns posed by large trucks and the …
its impact on saving human lives. Because of safety concerns posed by large trucks and the …
Handling imbalanced data in road crash severity prediction by machine learning algorithms
N Fiorentini, M Losa - Infrastructures, 2020 - mdpi.com
Crash severity is undoubtedly a fundamental aspect of a crash event. Although machine
learning algorithms for predicting crash severity have recently gained interest by the …
learning algorithms for predicting crash severity have recently gained interest by the …
Transparent deep machine learning framework for predicting traffic crash severity
Abstract Analysis of crash injury severity is a promising research target in highway safety
studies. A better understanding of crash severity risk factors is vital for the proactive …
studies. A better understanding of crash severity risk factors is vital for the proactive …
A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw
Motorcycles and motorcyclists have a variety of attributes that have been found to be a
potential contributor to the high liability of vulnerable road users (VRUs). Vulnerable Road …
potential contributor to the high liability of vulnerable road users (VRUs). Vulnerable Road …