A literature review of machine learning algorithms for crash injury severity prediction

K Santos, JP Dias, C Amado - Journal of safety research, 2022 - Elsevier
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 …

[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review

Y Ali, F Hussain, MM Haque - Accident Analysis & Prevention, 2024 - Elsevier
Accurately modelling crashes, and predicting crash occurrence and associated severities
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

AB Parsa, A Movahedi, H Taghipour, S Derrible… - Accident Analysis & …, 2020 - Elsevier
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 …

The application of XGBoost and SHAP to examining the factors in freight truck-related crashes: An exploratory analysis

C Yang, M Chen, Q Yuan - Accident Analysis & Prevention, 2021 - Elsevier
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 …

[HTML][HTML] A study on road accident prediction and contributing factors using explainable machine learning models: analysis and performance

S Ahmed, MA Hossain, SK Ray, MMI Bhuiyan… - Transportation research …, 2023 - Elsevier
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 …

Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study

A Jamal, M Zahid, M Tauhidur Rahman… - … journal of injury …, 2021 - Taylor & Francis
A better understanding of injury severity risk factors is fundamental to improving crash
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 …

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 …

Transparent deep machine learning framework for predicting traffic crash severity

K Sattar, F Chikh Oughali, K Assi, N Ratrout… - Neural Computing and …, 2023 - Springer
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 …

A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw

M Ijaz, M Zahid, A Jamal - Accident Analysis & Prevention, 2021 - Elsevier
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 …