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] Machine learning applied to road safety modeling: A systematic literature review
Road safety modeling is a valuable strategy for promoting safe mobility, enabling the
development of crash prediction models (CPM) and the investigation of factors contributing …
development of crash prediction models (CPM) and the investigation of factors contributing …
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 …
Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets
The future performance of stock markets is the most crucial factor in portfolio creation. As
machine learning technique is advancing, new possibilities have opened up for …
machine learning technique is advancing, new possibilities have opened up for …
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 …
How did COVID-19 impact driving behaviors and crash Severity? A multigroup structural equation modeling
Risky driving behaviors such as speeding and failing to signal have been witnessed more
frequently during the COVID-19 pandemic, resulting in higher rates of severe crashes. This …
frequently during the COVID-19 pandemic, resulting in higher rates of severe crashes. This …
Handling imbalanced data in road crash severity prediction by machine learning algorithms
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 …
Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles
Abstract The era of Big Data has arrived. Recently, under the environment of intelligent
transportation systems (ITS) and connected/automated vehicles (CAV), Big Data has been …
transportation systems (ITS) and connected/automated vehicles (CAV), Big Data has been …