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] Applications of machine learning methods for engineering risk assessment–A review
The purpose of this article is to present a structured review of publications utilizing machine
learning methods to aid in engineering risk assessment. A keyword search is performed to …
learning methods to aid in engineering risk assessment. A keyword search is performed to …
Big data, traditional data and the tradeoffs between prediction and causality in highway-safety analysis
The analysis of highway accident data is largely dominated by traditional statistical methods
(standard regression-based approaches), advanced statistical methods (such as models …
(standard regression-based approaches), advanced statistical methods (such as models …
[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 develo** effective road safety …
are a prerequisite for devising countermeasures and develo** effective road safety …
Visualization and analysis of map** knowledge domain of road safety studies
Map** knowledge domain (MKD) is an important application of visualization technology in
Bibliometrics, which has been extensively applied in psychology, medicine, and information …
Bibliometrics, which has been extensively applied in psychology, medicine, and information …
Comparison of four statistical and machine learning methods for crash severity prediction
Crash severity prediction models enable different agencies to predict the severity of a
reported crash with unknown severity or the severity of crashes that may be expected to …
reported crash with unknown severity or the severity of crashes that may be expected to …
A deep learning based traffic crash severity prediction framework
Highway work zones are most vulnerable roadway segments for congestion and traffic
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
[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 …
Comparing prediction performance for crash injury severity among various machine learning and statistical methods
Crash injury severity prediction is a promising research target in traffic safety. Traditionally,
various statistical methods were used for modeling crash injury severities. In recent years …
various statistical methods were used for modeling crash injury severities. In recent years …
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 …