[HTML][HTML] Enhancing road safety with machine learning: Current advances and future directions in accident prediction using non-visual data
Road traffic accident (RTA) poses a significant road safety issue due to the increased
fatalities worldwide. To address it, various artificial intelligence solutions are developed to …
fatalities worldwide. To address it, various artificial intelligence solutions are developed to …
A brief review of explainable artificial intelligence in healthcare
XAI refers to the techniques and methods for building AI applications which assist end users
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
[HTML][HTML] Analysis and visualization of accidents severity based on LightGBM-TPE
K Li, H Xu, X Liu - Chaos, Solitons & Fractals, 2022 - Elsevier
In recent years, road traffic accidents, as a leading cause of accidental deaths, have been
attracting more and more attention across several disciplines. Notably, the feature study on …
attracting more and more attention across several disciplines. Notably, the feature study on …
Comparative study of machine learning classifiers for modelling road traffic accidents
Road traffic accidents (RTAs) are a major cause of injuries and fatalities worldwide. In recent
years, there has been a growing global interest in analysing RTAs, specifically concerned …
years, there has been a growing global interest in analysing RTAs, specifically concerned …
Understanding the potential of emerging digital technologies for improving road safety
Abstract Each year, 1.35 million people are killed on the world's roads and another 20–50
million are seriously injured. Morbidity or serious injury from road traffic collisions is …
million are seriously injured. Morbidity or serious injury from road traffic collisions is …
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 …
Road car accident prediction using a machine-learning-enabled data analysis
S Pourroostaei Ardakani, X Liang, KT Mengistu, RS So… - Sustainability, 2023 - mdpi.com
Traffic accidents have become severe risks as they are one of the causes of enormous
deaths worldwide. Reducing the number of incidents is critical to saving lives and achieving …
deaths worldwide. Reducing the number of incidents is critical to saving lives and achieving …
An improved density peaks clustering algorithm based on k nearest neighbors and turning point for evaluating the severity of railway accidents
L Shi, X Yang, X Chang, J Wu, H Sun - Reliability Engineering & System …, 2023 - Elsevier
The timely and scientific assessment of railway accident severity can provide effective
support for making a suitable rescue plan. This paper proposes an improved density peaks …
support for making a suitable rescue plan. This paper proposes an improved density peaks …
Prediction of traffic accident severity based on random forest
J Yang, S Han, Y Chen - Journal of Advanced Transportation, 2023 - Wiley Online Library
This paper used the data of automobile traffic accidents from 2018 to 2020 in the Chinese
National Automobile Accident In‐Depth Investigation System. The prediction features of …
National Automobile Accident In‐Depth Investigation System. The prediction features of …
Comparison of traffic accident injury severity prediction models with explainable machine learning
Traffic accidents are still the main cause of fatalities, injuries and significant delays in
highways. Understanding the accident contributing factor is imperative to increase safety in …
highways. Understanding the accident contributing factor is imperative to increase safety in …