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 …
Applications of machine learning methods in traffic crash severity modelling: current status and future directions
As a key area of traffic safety research, crash severity modelling has attracted tremendous
attention. Recently, there has been growing interest in applying machine learning (ML) …
attention. Recently, there has been growing interest in applying machine learning (ML) …
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 …
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 …
On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development
Abstract Machine learning (ML) model interpretability has attracted much attention recently
given the promising performance of ML methods in crash frequency studies. Extracting …
given the promising performance of ML methods in crash frequency studies. Extracting …
[HTML][HTML] Application of machine learning models and SHAP to examine crashes involving young drivers in New Jersey
Motor vehicle crashes are the leading cause of the death of teenagers in the United States.
Young drivers have shown a higher propensity to get involved in crashes due to using a …
Young drivers have shown a higher propensity to get involved in crashes due to using a …
Predicting pedestrian-involved crash severity using inception-v3 deep learning model
This research leverages a novel deep learning model, Inception-v3, to predict pedestrian
crash severity using data collected over five years (2016–2021) from Louisiana. The final …
crash severity using data collected over five years (2016–2021) from Louisiana. The final …
Severity prediction of highway crashes in Saudi Arabia using machine learning techniques
Kingdom of Among the G20 countries, Saudi Arabia (KSA) is facing alarming traffic safety
issues compared to other G-20 countries. Mitigating the burden of traffic accidents has been …
issues compared to other G-20 countries. Mitigating the burden of traffic accidents has been …
[HTML][HTML] Modelling crash severity outcomes for low speed urban roads using back propagation–Artificial neural network (BP–ANN)–A case study in Indian context
S Barman, R Bandyopadhyaya - IATSS research, 2023 - Elsevier
This work analyses influence of road, weather and crash-specific factors on crash severity
outcomes for low-speed urban midblock sections and intersections, for day and night time …
outcomes for low-speed urban midblock sections and intersections, for day and night time …
Ensemble learning with pre-trained transformers for crash severity classification: A Deep NLP Approach
Transfer learning has gained significant traction in natural language processing due to the
emergence of state-of-the-art pre-trained language models (PLMs). Unlike traditional word …
emergence of state-of-the-art pre-trained language models (PLMs). Unlike traditional word …