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 …
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 …
Comparison of four statistical and machine learning methods for crash severity prediction
A Iranitalab, A Khattak - Accident Analysis & Prevention, 2017 - Elsevier
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 …
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 …
[HTML][HTML] Assessment of the level of road crash severity: comparison of intelligence studies
In measuring road safety, accident severity is a key concern. Crash severity prediction
models inform researchers about the severity of a crash based on a variety of criteria. To …
models inform researchers about the severity of a crash based on a variety of criteria. To …
Using machine learning models to forecast severity level of traffic crashes by R Studio and ArcGIS
This study describes crash causes, conditions, and distribution of accident hot spots along
with an analysis of the risk factors that significantly affect severity levels of crashes and their …
with an analysis of the risk factors that significantly affect severity levels of crashes and their …
Single-vehicle crash severity outcome prediction and determinant extraction using tree-based and other non-parametric models
Single-vehicle crashes are more fatality-concentrated and have posed increasing
challenges in traffic safety, which is of great research necessity. Tremendous previous …
challenges in traffic safety, which is of great research necessity. Tremendous previous …
Analyzing factors associated with fatal road crashes: a machine learning approach
AJ Ghandour, H Hammoud, S Al-Hajj - International journal of …, 2020 - mdpi.com
Road traffic injury accounts for a substantial human and economic burden globally.
Understanding risk factors contributing to fatal injuries is of paramount importance. In this …
Understanding risk factors contributing to fatal injuries is of paramount importance. In this …
Predicting crash injury severity with machine learning algorithm synergized with clustering technique: A promising protocol
Predicting crash injury severity is a crucial constituent of reducing the consequences of
traffic crashes. This study developed machine learning (ML) models to predict crash injury …
traffic crashes. This study developed machine learning (ML) models to predict crash injury …
An analytic framework using deep learning for prediction of traffic accident injury severity based on contributing factors
Vulnerable road users (VRUs) are exposed to the highest risk in the road traffic environment.
Analyzing contributing factors that affect injury severity facilitates injury severity prediction …
Analyzing contributing factors that affect injury severity facilitates injury severity prediction …